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

PubMed

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

2014-09-05

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

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

PubMed

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

2018-03-20

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

Quantitative Imaging Biomarkers: A Review of Statistical Methods for Technical Performance Assessment

PubMed Central

2017-01-01

Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers (QIBs) to measure changes in these features. Critical to the performance of a QIB in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method and metrics used to assess a QIB for clinical use. It is therefore, difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America (RSNA) and the Quantitative Imaging Biomarker Alliance (QIBA) with technical, radiological and statistical experts developed a set of technical performance analysis methods, metrics and study designs that provide terminology, metrics and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of QIB performance studies so that results from multiple studies can be compared, contrasted or combined. PMID:24919831

Affinity Proteomics for Fast, Sensitive, Quantitative Analysis of Proteins in Plasma.

PubMed

O'Grady, John P; Meyer, Kevin W; Poe, Derrick N

2017-01-01

The improving efficacy of many biological therapeutics and identification of low-level biomarkers are driving the analytical proteomics community to deal with extremely high levels of sample complexity relative to their analytes. Many protein quantitation and biomarker validation procedures utilize an immunoaffinity enrichment step to purify the sample and maximize the sensitivity of the corresponding liquid chromatography tandem mass spectrometry measurements. In order to generate surrogate peptides with better mass spectrometric properties, protein enrichment is followed by a proteolytic cleavage step. This is often a time-consuming multistep process. Presented here is a workflow which enables rapid protein enrichment and proteolytic cleavage to be performed in a single, easy-to-use reactor. Using this strategy Klotho, a low-abundance biomarker found in plasma, can be accurately quantitated using a protocol that takes under 5 h from start to finish.

Portable Biomarker Detection with Magnetic Nanotags

PubMed Central

Hall, Drew A.; Wang, Shan X.; Murmann, Boris; Gaster, Richard S.

2012-01-01

This paper presents a hand-held, portable biosensor platform for quantitative biomarker measurement. By combining magnetic nanoparticle (MNP) tags with giant magnetoresistive (GMR) spin-valve sensors, the hand-held platform achieves highly sensitive (picomolar) and specific biomarker detection in less than 20 minutes. The rapid analysis and potential low cost make this technology ideal for point-of-care (POC) diagnostics. Furthermore, this platform is able to detect multiple biomarkers simultaneously in a single assay, creating a promising diagnostic tool for a vast number of applications. PMID:22495252

Application of Microchip for Biomarker Analysis

NASA Astrophysics Data System (ADS)

Kataoka, Masatoshi; Yatsushiro, Shouki; Yamamura, Shouhei; Abe, Hiroko

Microchip technologies have received considerable attention, due to their competitive advantages, especially in regards to reduced sample and reagent consumption, analysis time, and easy operation. This approach has been successfully used to analyze DNA, amino acids, proteins, and carbohydrates. In the present study, we showed the potential of microchip technologies for the biomarker analysis, blood carbohydrate analysis on microchip electrophoresis, quantitative analysis of protein with antigen-antibody reaction on microchip, and the detection of malaria-infected erythrocyte with a cell microarray chip.

Precise quantitation of 136 urinary proteins by LC/MRM-MS using stable isotope labeled peptides as internal standards for biomarker discovery and/or verification studies.

PubMed

Percy, Andrew J; Yang, Juncong; Hardie, Darryl B; Chambers, Andrew G; Tamura-Wells, Jessica; Borchers, Christoph H

2015-06-15

Spurred on by the growing demand for panels of validated disease biomarkers, increasing efforts have focused on advancing qualitative and quantitative tools for more highly multiplexed and sensitive analyses of a multitude of analytes in various human biofluids. In quantitative proteomics, evolving strategies involve the use of the targeted multiple reaction monitoring (MRM) mode of mass spectrometry (MS) with stable isotope-labeled standards (SIS) used for internal normalization. Using that preferred approach with non-invasive urine samples, we have systematically advanced and rigorously assessed the methodology toward the precise quantitation of the largest, multiplexed panel of candidate protein biomarkers in human urine to date. The concentrations of the 136 proteins span >5 orders of magnitude (from 8.6 μg/mL to 25 pg/mL), with average CVs of 8.6% over process triplicate. Detailed here is our quantitative method, the analysis strategy, a feasibility application to prostate cancer samples, and a discussion of the utility of this method in translational studies. Copyright © 2015 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-06-01

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

The emerging science of quantitative imaging biomarkers terminology and definitions for scientific studies and regulatory submissions.

PubMed

Kessler, Larry G; Barnhart, Huiman X; Buckler, Andrew J; Choudhury, Kingshuk Roy; Kondratovich, Marina V; Toledano, Alicia; Guimaraes, Alexander R; Filice, Ross; Zhang, Zheng; Sullivan, Daniel C

2015-02-01

The development and implementation of quantitative imaging biomarkers has been hampered by the inconsistent and often incorrect use of terminology related to these markers. Sponsored by the Radiological Society of North America, an interdisciplinary group of radiologists, statisticians, physicists, and other researchers worked to develop a comprehensive terminology to serve as a foundation for quantitative imaging biomarker claims. Where possible, this working group adapted existing definitions derived from national or international standards bodies rather than invent new definitions for these terms. This terminology also serves as a foundation for the design of studies that evaluate the technical performance of quantitative imaging biomarkers and for studies of algorithms that generate the quantitative imaging biomarkers from clinical scans. This paper provides examples of research studies and quantitative imaging biomarker claims that use terminology consistent with these definitions as well as examples of the rampant confusion in this emerging field. We provide recommendations for appropriate use of quantitative imaging biomarker terminological concepts. It is hoped that this document will assist researchers and regulatory reviewers who examine quantitative imaging biomarkers and will also inform regulatory guidance. More consistent and correct use of terminology could advance regulatory science, improve clinical research, and provide better care for patients who undergo imaging studies. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Meta-analysis of the technical performance of an imaging procedure: guidelines and statistical methodology.

PubMed

Huang, Erich P; Wang, Xiao-Feng; Choudhury, Kingshuk Roy; McShane, Lisa M; Gönen, Mithat; Ye, Jingjing; Buckler, Andrew J; Kinahan, Paul E; Reeves, Anthony P; Jackson, Edward F; Guimaraes, Alexander R; Zahlmann, Gudrun

2015-02-01

Medical imaging serves many roles in patient care and the drug approval process, including assessing treatment response and guiding treatment decisions. These roles often involve a quantitative imaging biomarker, an objectively measured characteristic of the underlying anatomic structure or biochemical process derived from medical images. Before a quantitative imaging biomarker is accepted for use in such roles, the imaging procedure to acquire it must undergo evaluation of its technical performance, which entails assessment of performance metrics such as repeatability and reproducibility of the quantitative imaging biomarker. Ideally, this evaluation will involve quantitative summaries of results from multiple studies to overcome limitations due to the typically small sample sizes of technical performance studies and/or to include a broader range of clinical settings and patient populations. This paper is a review of meta-analysis procedures for such an evaluation, including identification of suitable studies, statistical methodology to evaluate and summarize the performance metrics, and complete and transparent reporting of the results. This review addresses challenges typical of meta-analyses of technical performance, particularly small study sizes, which often causes violations of assumptions underlying standard meta-analysis techniques. Alternative approaches to address these difficulties are also presented; simulation studies indicate that they outperform standard techniques when some studies are small. The meta-analysis procedures presented are also applied to actual [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) test-retest repeatability data for illustrative purposes. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Meta-analysis of the technical performance of an imaging procedure: Guidelines and statistical methodology

PubMed Central

Huang, Erich P; Wang, Xiao-Feng; Choudhury, Kingshuk Roy; McShane, Lisa M; Gönen, Mithat; Ye, Jingjing; Buckler, Andrew J; Kinahan, Paul E; Reeves, Anthony P; Jackson, Edward F; Guimaraes, Alexander R; Zahlmann, Gudrun

2017-01-01

Medical imaging serves many roles in patient care and the drug approval process, including assessing treatment response and guiding treatment decisions. These roles often involve a quantitative imaging biomarker, an objectively measured characteristic of the underlying anatomic structure or biochemical process derived from medical images. Before a quantitative imaging biomarker is accepted for use in such roles, the imaging procedure to acquire it must undergo evaluation of its technical performance, which entails assessment of performance metrics such as repeatability and reproducibility of the quantitative imaging biomarker. Ideally, this evaluation will involve quantitative summaries of results from multiple studies to overcome limitations due to the typically small sample sizes of technical performance studies and/or to include a broader range of clinical settings and patient populations. This paper is a review of meta-analysis procedures for such an evaluation, including identification of suitable studies, statistical methodology to evaluate and summarize the performance metrics, and complete and transparent reporting of the results. This review addresses challenges typical of meta-analyses of technical performance, particularly small study sizes, which often causes violations of assumptions underlying standard meta-analysis techniques. Alternative approaches to address these difficulties are also presented; simulation studies indicate that they outperform standard techniques when some studies are small. The meta-analysis procedures presented are also applied to actual [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) test–retest repeatability data for illustrative purposes. PMID:24872353

Low-frequency quantitative ultrasound imaging of cell death in vivo

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

Sadeghi-Naini, Ali; Falou, Omar; Czarnota, Gregory J.

Purpose: Currently, no clinical imaging modality is used routinely to assess tumor response to cancer therapies within hours to days of the delivery of treatment. Here, the authors demonstrate the efficacy of ultrasound at a clinically relevant frequency to quantitatively detect changes in tumors in response to cancer therapies using preclinical mouse models.Methods: Conventional low-frequency and corresponding high-frequency ultrasound (ranging from 4 to 28 MHz) were used along with quantitative spectroscopic and signal envelope statistical analyses on data obtained from xenograft tumors treated with chemotherapy, x-ray radiation, as well as a novel vascular targeting microbubble therapy.Results: Ultrasound-based spectroscopic biomarkers indicatedmore » significant changes in cell-death associated parameters in responsive tumors. Specifically changes in the midband fit, spectral slope, and 0-MHz intercept biomarkers were investigated for different types of treatment and demonstrated cell-death related changes. The midband fit and 0-MHz intercept biomarker derived from low-frequency data demonstrated increases ranging approximately from 0 to 6 dBr and 0 to 8 dBr, respectively, depending on treatments administrated. These data paralleled results observed for high-frequency ultrasound data. Statistical analysis of ultrasound signal envelope was performed as an alternative method to obtain histogram-based biomarkers and provided confirmatory results. Histological analysis of tumor specimens indicated up to 61% cell death present in the tumors depending on treatments administered, consistent with quantitative ultrasound findings indicating cell death. Ultrasound-based spectroscopic biomarkers demonstrated a good correlation with histological morphological findings indicative of cell death (r{sup 2}= 0.71, 0.82; p < 0.001).Conclusions: In summary, the results provide preclinical evidence, for the first time, that quantitative ultrasound used at a clinically relevant frequency, in addition to high-frequency ultrasound, can detect tissue changes associated with cell death in vivo in response to cancer treatments.« less

Quantum dot nanoprobe-based quantitative analysis for prostate cancer (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kang, Benedict J.; Jang, Gun Hyuk; Park, Sungwook; Lee, Kwan Hyi

2016-09-01

Prostate cancer causes one of the leading cancer-related deaths among the Caucasian adult males in Europe and the United State of America. However, it has a high recovery rate indicating when a proper treatment is delivered to a patient. There are cases of over- or under-treatments which exacerbate the disease states indicating the importance of proper therapeutic approach depending on stage of the disease. Recognition of the unmet needs has raised a need for stratification of the disease. There have been attempts to stratify based on biomarker expression patterns in the course of disease progression. To closely observe the biomarker expression patterns, we propose the use of quantitative imaging method by using fabricated quantum dot-based nanoprobe to quantify biomarker expression on the surface of prostate cancer cells. To characterize the cell line and analyze the biomarker levels, cluster of differentiation 44 (CD 44), prostate specific membrane antigen (PSMA), and epithelial cell adhesion molecule (EpCAM) are used. Each selected biomarker per cell line has been quantified from which we established a signature of biomarkers of a prostate cancer cell line.

Quantitative Medical Image Analysis for Clinical Development of Therapeutics

NASA Astrophysics Data System (ADS)

Analoui, Mostafa

There has been significant progress in development of therapeutics for prevention and management of several disease areas in recent years, leading to increased average life expectancy, as well as of quality of life, globally. However, due to complexity of addressing a number of medical needs and financial burden of development of new class of therapeutics, there is a need for better tools for decision making and validation of efficacy and safety of new compounds. Numerous biological markers (biomarkers) have been proposed either as adjunct to current clinical endpoints or as surrogates. Imaging biomarkers are among rapidly increasing biomarkers, being examined to expedite effective and rational drug development. Clinical imaging often involves a complex set of multi-modality data sets that require rapid and objective analysis, independent of reviewer's bias and training. In this chapter, an overview of imaging biomarkers for drug development is offered, along with challenges that necessitate quantitative and objective image analysis. Examples of automated and semi-automated analysis approaches are provided, along with technical review of such methods. These examples include the use of 3D MRI for osteoarthritis, ultrasound vascular imaging, and dynamic contrast enhanced MRI for oncology. Additionally, a brief overview of regulatory requirements is discussed. In conclusion, this chapter highlights key challenges and future directions in this area.

DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research.

PubMed

Fedorov, Andriy; Clunie, David; Ulrich, Ethan; Bauer, Christian; Wahle, Andreas; Brown, Bartley; Onken, Michael; Riesmeier, Jörg; Pieper, Steve; Kikinis, Ron; Buatti, John; Beichel, Reinhard R

2016-01-01

Background. Imaging biomarkers hold tremendous promise for precision medicine clinical applications. Development of such biomarkers relies heavily on image post-processing tools for automated image quantitation. Their deployment in the context of clinical research necessitates interoperability with the clinical systems. Comparison with the established outcomes and evaluation tasks motivate integration of the clinical and imaging data, and the use of standardized approaches to support annotation and sharing of the analysis results and semantics. We developed the methodology and tools to support these tasks in Positron Emission Tomography and Computed Tomography (PET/CT) quantitative imaging (QI) biomarker development applied to head and neck cancer (HNC) treatment response assessment, using the Digital Imaging and Communications in Medicine (DICOM(®)) international standard and free open-source software. Methods. Quantitative analysis of PET/CT imaging data collected on patients undergoing treatment for HNC was conducted. Processing steps included Standardized Uptake Value (SUV) normalization of the images, segmentation of the tumor using manual and semi-automatic approaches, automatic segmentation of the reference regions, and extraction of the volumetric segmentation-based measurements. Suitable components of the DICOM standard were identified to model the various types of data produced by the analysis. A developer toolkit of conversion routines and an Application Programming Interface (API) were contributed and applied to create a standards-based representation of the data. Results. DICOM Real World Value Mapping, Segmentation and Structured Reporting objects were utilized for standards-compliant representation of the PET/CT QI analysis results and relevant clinical data. A number of correction proposals to the standard were developed. The open-source DICOM toolkit (DCMTK) was improved to simplify the task of DICOM encoding by introducing new API abstractions. Conversion and visualization tools utilizing this toolkit were developed. The encoded objects were validated for consistency and interoperability. The resulting dataset was deposited in the QIN-HEADNECK collection of The Cancer Imaging Archive (TCIA). Supporting tools for data analysis and DICOM conversion were made available as free open-source software. Discussion. We presented a detailed investigation of the development and application of the DICOM model, as well as the supporting open-source tools and toolkits, to accommodate representation of the research data in QI biomarker development. We demonstrated that the DICOM standard can be used to represent the types of data relevant in HNC QI biomarker development, and encode their complex relationships. The resulting annotated objects are amenable to data mining applications, and are interoperable with a variety of systems that support the DICOM standard.

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.

Quantitative and Qualitative Analysis of Biomarkers in Fusarium verticillioides

USDA-ARS?s Scientific Manuscript database

In this study, a combination HPLC-DART-TOF-MS system was utilized to identify and quantitatively analyze carbohydrates in wild type and mutant strains of Fusarium verticillioides. Carbohydrate fractions were isolated from F. verticillioides cellular extracts by HPLC using a cation-exchange size-excl...

The use of immunohistochemistry for biomarker assessment--can it compete with other technologies?

PubMed

Dunstan, Robert W; Wharton, Keith A; Quigley, Catherine; Lowe, Amanda

2011-10-01

A morphology-based assay such as immunohistochemistry (IHC) should be a highly effective means to define the expression of a target molecule of interest, especially if the target is a protein. However, over the past decade, IHC as a platform for biomarkers has been challenged by more quantitative molecular assays with reference standards but that lack morphologic context. For IHC to be considered a "top-tier" biomarker assay, it must provide truly quantitative data on par with non-morphologic assays, which means it needs to be run with reference standards. However, creating such standards for IHC will require optimizing all aspects of tissue collection, fixation, section thickness, morphologic criteria for assessment, staining processes, digitization of images, and image analysis. This will also require anatomic pathology to evolve from a discipline that is descriptive to one that is quantitative. A major step in this transformation will be replacing traditional ocular microscopes with computer monitors and whole slide images, for without digitization, there can be no accurate quantitation; without quantitation, there can be no standardization; and without standardization, the value of morphology-based IHC assays will not be realized.

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.

Quantitation of isobaric phosphatidylcholine species in human plasma using a hybrid quadrupole linear ion trap mass spectrometer

USDA-ARS?s Scientific Manuscript database

Phosphatidylcholine (PC) species in human plasma are used as biomarkers of disease. PC biomarkers are often limited by the inability to separate isobaric PC. In this work, we developed a targeted shotgun approach for analysis of isobaric and isomeric PC. This approach is comprised of two mass spectr...

Dissociable brain biomarkers of fluid intelligence.

PubMed

Paul, Erick J; Larsen, Ryan J; Nikolaidis, Aki; Ward, Nathan; Hillman, Charles H; Cohen, Neal J; Kramer, Arthur F; Barbey, Aron K

2016-08-15

Cognitive neuroscience has long sought to understand the biological foundations of human intelligence. Decades of research have revealed that general intelligence is correlated with two brain-based biomarkers: the concentration of the brain biochemical N-acetyl aspartate (NAA) measured by proton magnetic resonance spectroscopy (MRS) and total brain volume measured using structural MR imaging (MRI). However, the relative contribution of these biomarkers in predicting performance on core facets of human intelligence remains to be well characterized. In the present study, we sought to elucidate the role of NAA and brain volume in predicting fluid intelligence (Gf). Three canonical tests of Gf (BOMAT, Number Series, and Letter Sets) and three working memory tasks (Reading, Rotation, and Symmetry span tasks) were administered to a large sample of healthy adults (n=211). We conducted exploratory factor analysis to investigate the factor structure underlying Gf independent from working memory and observed two Gf components (verbal/spatial and quantitative reasoning) and one working memory component. Our findings revealed a dissociation between two brain biomarkers of Gf (controlling for age and sex): NAA concentration correlated with verbal/spatial reasoning, whereas brain volume correlated with quantitative reasoning and working memory. A follow-up analysis revealed that this pattern of findings is observed for males and females when analyzed separately. Our results provide novel evidence that distinct brain biomarkers are associated with specific facets of human intelligence, demonstrating that NAA and brain volume are independent predictors of verbal/spatial and quantitative facets of Gf. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Capillary nano-immunoassays: advancing quantitative proteomics analysis, biomarker assessment, and molecular diagnostics.

PubMed

Chen, Jin-Qiu; Wakefield, Lalage M; Goldstein, David J

2015-06-06

There is an emerging demand for the use of molecular profiling to facilitate biomarker identification and development, and to stratify patients for more efficient treatment decisions with reduced adverse effects. In the past decade, great strides have been made to advance genomic, transcriptomic and proteomic approaches to address these demands. While there has been much progress with these large scale approaches, profiling at the protein level still faces challenges due to limitations in clinical sample size, poor reproducibility, unreliable quantitation, and lack of assay robustness. A novel automated capillary nano-immunoassay (CNIA) technology has been developed. This technology offers precise and accurate measurement of proteins and their post-translational modifications using either charge-based or size-based separation formats. The system not only uses ultralow nanogram levels of protein but also allows multi-analyte analysis using a parallel single-analyte format for increased sensitivity and specificity. The high sensitivity and excellent reproducibility of this technology make it particularly powerful for analysis of clinical samples. Furthermore, the system can distinguish and detect specific protein post-translational modifications that conventional Western blot and other immunoassays cannot easily capture. This review will summarize and evaluate the latest progress to optimize the CNIA system for comprehensive, quantitative protein and signaling event characterization. It will also discuss how the technology has been successfully applied in both discovery research and clinical studies, for signaling pathway dissection, proteomic biomarker assessment, targeted treatment evaluation and quantitative proteomic analysis. Lastly, a comparison of this novel system with other conventional immuno-assay platforms is performed.

Quantitative imaging test approval and biomarker qualification: interrelated but distinct activities.

PubMed

Buckler, Andrew J; Bresolin, Linda; Dunnick, N Reed; Sullivan, Daniel C; Aerts, Hugo J W L; Bendriem, Bernard; Bendtsen, Claus; Boellaard, Ronald; Boone, John M; Cole, Patricia E; Conklin, James J; Dorfman, Gary S; Douglas, Pamela S; Eidsaunet, Willy; Elsinger, Cathy; Frank, Richard A; Gatsonis, Constantine; Giger, Maryellen L; Gupta, Sandeep N; Gustafson, David; Hoekstra, Otto S; Jackson, Edward F; Karam, Lisa; Kelloff, Gary J; Kinahan, Paul E; McLennan, Geoffrey; Miller, Colin G; Mozley, P David; Muller, Keith E; Patt, Rick; Raunig, David; Rosen, Mark; Rupani, Haren; Schwartz, Lawrence H; Siegel, Barry A; Sorensen, A Gregory; Wahl, Richard L; Waterton, John C; Wolf, Walter; Zahlmann, Gudrun; Zimmerman, Brian

2011-06-01

Quantitative imaging biomarkers could speed the development of new treatments for unmet medical needs and improve routine clinical care. However, it is not clear how the various regulatory and nonregulatory (eg, reimbursement) processes (often referred to as pathways) relate, nor is it clear which data need to be collected to support these different pathways most efficiently, given the time- and cost-intensive nature of doing so. The purpose of this article is to describe current thinking regarding these pathways emerging from diverse stakeholders interested and active in the definition, validation, and qualification of quantitative imaging biomarkers and to propose processes to facilitate the development and use of quantitative imaging biomarkers. A flexible framework is described that may be adapted for each imaging application, providing mechanisms that can be used to develop, assess, and evaluate relevant biomarkers. From this framework, processes can be mapped that would be applicable to both imaging product development and to quantitative imaging biomarker development aimed at increasing the effectiveness and availability of quantitative imaging. http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.10100800/-/DC1. RSNA, 2011

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

PubMed

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

2016-08-01

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

Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps.

PubMed

Sadeghi-Naini, Ali; Suraweera, Harini; Tran, William Tyler; Hadizad, Farnoosh; Bruni, Giancarlo; Rastegar, Rashin Fallah; Curpen, Belinda; Czarnota, Gregory J

2017-10-20

This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant breast lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious breast lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for breast cancer screening and rapid diagnosis in clinic.

Ultratrace level determination and quantitative analysis of kidney injury biomarkers in patient samples attained by zinc oxide nanorods

NASA Astrophysics Data System (ADS)

Singh, Manpreet; Alabanza, Anginelle; Gonzalez, Lorelis E.; Wang, Weiwei; Reeves, W. Brian; Hahm, Jong-In

2016-02-01

Determining ultratrace amounts of protein biomarkers in patient samples in a straightforward and quantitative manner is extremely important for early disease diagnosis and treatment. Here, we successfully demonstrate the novel use of zinc oxide nanorods (ZnO NRs) in the ultrasensitive and quantitative detection of two acute kidney injury (AKI)-related protein biomarkers, tumor necrosis factor (TNF)-α and interleukin (IL)-8, directly from patient samples. We first validate the ZnO NRs-based IL-8 results via comparison with those obtained from using a conventional enzyme-linked immunosorbent method in samples from 38 individuals. We further assess the full detection capability of the ZnO NRs-based technique by quantifying TNF-α, whose levels in human urine are often below the detection limits of conventional methods. Using the ZnO NR platforms, we determine the TNF-α concentrations of all 46 patient samples tested, down to the fg per mL level. Subsequently, we screen for TNF-α levels in approximately 50 additional samples collected from different patient groups in order to demonstrate a potential use of the ZnO NRs-based assay in assessing cytokine levels useful for further clinical monitoring. Our research efforts demonstrate that ZnO NRs can be straightforwardly employed in the rapid, ultrasensitive, quantitative, and simultaneous detection of multiple AKI-related biomarkers directly in patient urine samples, providing an unparalleled detection capability beyond those of conventional analysis methods. Additional key advantages of the ZnO NRs-based approach include a fast detection speed, low-volume assay condition, multiplexing ability, and easy automation/integration capability to existing fluorescence instrumentation. Therefore, we anticipate that our ZnO NRs-based detection method will be highly beneficial for overcoming the frequent challenges in early biomarker development and treatment assessment, pertaining to the facile and ultrasensitive quantification of hard-to-trace biomolecules.Determining ultratrace amounts of protein biomarkers in patient samples in a straightforward and quantitative manner is extremely important for early disease diagnosis and treatment. Here, we successfully demonstrate the novel use of zinc oxide nanorods (ZnO NRs) in the ultrasensitive and quantitative detection of two acute kidney injury (AKI)-related protein biomarkers, tumor necrosis factor (TNF)-α and interleukin (IL)-8, directly from patient samples. We first validate the ZnO NRs-based IL-8 results via comparison with those obtained from using a conventional enzyme-linked immunosorbent method in samples from 38 individuals. We further assess the full detection capability of the ZnO NRs-based technique by quantifying TNF-α, whose levels in human urine are often below the detection limits of conventional methods. Using the ZnO NR platforms, we determine the TNF-α concentrations of all 46 patient samples tested, down to the fg per mL level. Subsequently, we screen for TNF-α levels in approximately 50 additional samples collected from different patient groups in order to demonstrate a potential use of the ZnO NRs-based assay in assessing cytokine levels useful for further clinical monitoring. Our research efforts demonstrate that ZnO NRs can be straightforwardly employed in the rapid, ultrasensitive, quantitative, and simultaneous detection of multiple AKI-related biomarkers directly in patient urine samples, providing an unparalleled detection capability beyond those of conventional analysis methods. Additional key advantages of the ZnO NRs-based approach include a fast detection speed, low-volume assay condition, multiplexing ability, and easy automation/integration capability to existing fluorescence instrumentation. Therefore, we anticipate that our ZnO NRs-based detection method will be highly beneficial for overcoming the frequent challenges in early biomarker development and treatment assessment, pertaining to the facile and ultrasensitive quantification of hard-to-trace biomolecules. Electronic supplementary information (ESI) available: Typical SEM images of the ZnO NRs used in the biomarker assays are provided in Fig. S1. See DOI: 10.1039/c5nr08706f

DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research

PubMed Central

Clunie, David; Ulrich, Ethan; Bauer, Christian; Wahle, Andreas; Brown, Bartley; Onken, Michael; Riesmeier, Jörg; Pieper, Steve; Kikinis, Ron; Buatti, John; Beichel, Reinhard R.

2016-01-01

Background. Imaging biomarkers hold tremendous promise for precision medicine clinical applications. Development of such biomarkers relies heavily on image post-processing tools for automated image quantitation. Their deployment in the context of clinical research necessitates interoperability with the clinical systems. Comparison with the established outcomes and evaluation tasks motivate integration of the clinical and imaging data, and the use of standardized approaches to support annotation and sharing of the analysis results and semantics. We developed the methodology and tools to support these tasks in Positron Emission Tomography and Computed Tomography (PET/CT) quantitative imaging (QI) biomarker development applied to head and neck cancer (HNC) treatment response assessment, using the Digital Imaging and Communications in Medicine (DICOM®) international standard and free open-source software. Methods. Quantitative analysis of PET/CT imaging data collected on patients undergoing treatment for HNC was conducted. Processing steps included Standardized Uptake Value (SUV) normalization of the images, segmentation of the tumor using manual and semi-automatic approaches, automatic segmentation of the reference regions, and extraction of the volumetric segmentation-based measurements. Suitable components of the DICOM standard were identified to model the various types of data produced by the analysis. A developer toolkit of conversion routines and an Application Programming Interface (API) were contributed and applied to create a standards-based representation of the data. Results. DICOM Real World Value Mapping, Segmentation and Structured Reporting objects were utilized for standards-compliant representation of the PET/CT QI analysis results and relevant clinical data. A number of correction proposals to the standard were developed. The open-source DICOM toolkit (DCMTK) was improved to simplify the task of DICOM encoding by introducing new API abstractions. Conversion and visualization tools utilizing this toolkit were developed. The encoded objects were validated for consistency and interoperability. The resulting dataset was deposited in the QIN-HEADNECK collection of The Cancer Imaging Archive (TCIA). Supporting tools for data analysis and DICOM conversion were made available as free open-source software. Discussion. We presented a detailed investigation of the development and application of the DICOM model, as well as the supporting open-source tools and toolkits, to accommodate representation of the research data in QI biomarker development. We demonstrated that the DICOM standard can be used to represent the types of data relevant in HNC QI biomarker development, and encode their complex relationships. The resulting annotated objects are amenable to data mining applications, and are interoperable with a variety of systems that support the DICOM standard. PMID:27257542

DMS-prefiltered mass spectrometry for the detection of biomarkers

NASA Astrophysics Data System (ADS)

Coy, Stephen L.; Krylov, Evgeny V.; Nazarov, Erkinjon G.

2008-04-01

Technologies based on Differential Mobility Spectrometry (DMS) are ideally matched to rapid, sensitive, and selective detection of chemicals like biomarkers. Biomarkers linked to exposure to radiation, exposure to CWA's, exposure to toxic materials (TICs and TIMs) and to specific diseases are being examined in a number of laboratories. Screening for these types of exposure can be improved in accuracy and greatly speeded up by using DMS-MS instead of slower techniques like LC-MS and GC-MS. We have performed an extensive series of tests with nanospray-DMS-mass spectroscopy and standalone nanospray-DMS obtaining extensive information on chemistry and detectivity. DMS-MS systems implemented with low-resolution, low-cost, portable mass-spectrometry systems are very promising. Lowresolution mass spectrometry alone would be inadequate for the task, but with DMS pre-filtration to suppress interferences, can be quite effective, even for quantitative measurement. Bio-fluids and digests are well suited to ionization by electrospray and detection by mass-spectrometry, but signals from critical markers are overwhelmed by chemical noise from unrelated species, making essential quantitative analysis impossible. Sionex and collaborators have presented data using DMS to suppress chemical noise, allowing detection of cancer biomarkers in 10,000-fold excess of normal products 1,2. In addition, a linear dynamic range of approximately 2,000 has been demonstrated with accurate quantitation 3. We will review the range of possible applications and present new data on DMS-MS biomarker detection.

Quantitative imaging biomarkers: Effect of sample size and bias on confidence interval coverage.

PubMed

Obuchowski, Nancy A; Bullen, Jennifer

2017-01-01

Introduction Quantitative imaging biomarkers (QIBs) are being increasingly used in medical practice and clinical trials. An essential first step in the adoption of a quantitative imaging biomarker is the characterization of its technical performance, i.e. precision and bias, through one or more performance studies. Then, given the technical performance, a confidence interval for a new patient's true biomarker value can be constructed. Estimating bias and precision can be problematic because rarely are both estimated in the same study, precision studies are usually quite small, and bias cannot be measured when there is no reference standard. Methods A Monte Carlo simulation study was conducted to assess factors affecting nominal coverage of confidence intervals for a new patient's quantitative imaging biomarker measurement and for change in the quantitative imaging biomarker over time. Factors considered include sample size for estimating bias and precision, effect of fixed and non-proportional bias, clustered data, and absence of a reference standard. Results Technical performance studies of a quantitative imaging biomarker should include at least 35 test-retest subjects to estimate precision and 65 cases to estimate bias. Confidence intervals for a new patient's quantitative imaging biomarker measurement constructed under the no-bias assumption provide nominal coverage as long as the fixed bias is <12%. For confidence intervals of the true change over time, linearity must hold and the slope of the regression of the measurements vs. true values should be between 0.95 and 1.05. The regression slope can be assessed adequately as long as fixed multiples of the measurand can be generated. Even small non-proportional bias greatly reduces confidence interval coverage. Multiple lesions in the same subject can be treated as independent when estimating precision. Conclusion Technical performance studies of quantitative imaging biomarkers require moderate sample sizes in order to provide robust estimates of bias and precision for constructing confidence intervals for new patients. Assumptions of linearity and non-proportional bias should be assessed thoroughly.

Statistical Issues in Testing Conformance with the Quantitative Imaging Biomarker Alliance (QIBA) Profile Claims.

PubMed

Obuchowski, Nancy A; Buckler, Andrew; Kinahan, Paul; Chen-Mayer, Heather; Petrick, Nicholas; Barboriak, Daniel P; Bullen, Jennifer; Barnhart, Huiman; Sullivan, Daniel C

2016-04-01

A major initiative of the Quantitative Imaging Biomarker Alliance is to develop standards-based documents called "Profiles," which describe one or more technical performance claims for a given imaging modality. The term "actor" denotes any entity (device, software, or person) whose performance must meet certain specifications for the claim to be met. The objective of this paper is to present the statistical issues in testing actors' conformance with the specifications. In particular, we present the general rationale and interpretation of the claims, the minimum requirements for testing whether an actor achieves the performance requirements, the study designs used for testing conformity, and the statistical analysis plan. We use three examples to illustrate the process: apparent diffusion coefficient in solid tumors measured by MRI, change in Perc 15 as a biomarker for the progression of emphysema, and percent change in solid tumor volume by computed tomography as a biomarker for lung cancer progression. Copyright © 2016 The Association of University Radiologists. All rights reserved.

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

PubMed

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

2014-04-01

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

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

PubMed Central

2016-01-01

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. PMID:26745651

TH-A-207B-00: Shear-Wave Imaging and a QIBA US Biomarker Update

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

NONE

Imaging of tissue elastic properties is a relatively new and powerful approach to one of the oldest and most important diagnostic tools. Imaging of shear wave speed with ultrasound is has been added to most high-end ultrasound systems. Understanding this exciting imaging mode aiding its most effective use in medicine can be a rewarding effort for medical physicists and other medical imaging and treatment professionals. Assuring consistent, quantitative measurements across the many ultrasound systems in a typical imaging department will constitute a major step toward realizing the great potential of this technique and other quantitative imaging. This session will targetmore » these two goals with two presentations. A. Basics and Current Implementations of Ultrasound Imaging of Shear Wave Speed and Elasticity - Shigao Chen, Ph.D. Learning objectives-To understand: Introduction: Importance of tissue elasticity measurement Strain vs. shear wave elastography (SWE), beneficial features of SWE The link between shear wave speed and material properties, influence of viscosity Generation of shear waves External vibration (Fibroscan) ultrasound radiation force Point push Supersonic push (Aixplorer) Comb push (GE Logiq E9) Detection of shear waves Motion detection from pulse-echo ultrasound Importance of frame rate for shear wave imaging Plane wave imaging detection How to achieve high effective frame rate using line-by-line scanners Shear wave speed calculation Time to peak Random sample consensus (RANSAC) Cross correlation Sources of bias and variation in SWE Tissue viscosity Transducer compression or internal pressure of organ Reflection of shear waves at boundaries B. Elasticity Imaging System Biomarker Qualification and User Testing of Systems – Brian Garra, M.D. Learning objectives-To understand: Goals Review the need for quantitative medical imaging Provide examples of quantitative imaging biomarkers Acquaint the participant with the purpose of the RSNA Quantitative Imaging Biomarker Alliance and the need for such an organization Review the QIBA process for creating a quantitative biomarker Summarize steps needed to verify adherence of site, operators, and imaging systems to a QIBA profile Underlying Premise and Assumptions Objective, quantifiable results are needed to enhance the value of diagnostic imaging in clinical practice Reasons for quantification Evidence based medicine requires objective, not subjective observer data Computerized decision support tools (eg CAD) generally require quantitative input. Quantitative, reproducible measures are more easily used to develop personalized molecular medical diagnostic and treatment systems What is quantitative imaging? Definition from Imaging Metrology Workshop The Quantitative Imaging Biomarker Alliance Formation 2008 Mission Structure Example Imaging Biomarkers Being Explored Biomarker Selection Groundwork Draft Protocol for imaging and data evaluation QIBA Profile Drafting Equipment and Site Validation Technical Clinical Site and Equipment QA and Compliance Checking Ultrasound Elasticity Estimation Biomarker US Elasticity Estimation Background Current Status and Problems Biomarker Selection-process and outcome US SWS for Liver Fibrosis Biomarker Work Groundwork Literature search and analysis results Phase I phantom testing-Elastic phantoms Phase II phantom testing-Viscoelastic phantoms Digital Simulated Data Protocol and Profile Drafting Protocol: based on UPICT and existing literature and standards bodies protocols Profile-Current claims, Manufacturer specific appendices What comes after the profile Profile Validation Technical validation Clinical validation QA and Compliance Possible approaches Site Operator testing Site protocol re-evaluation Imaging system Manufacturer testing and attestation User acceptance testing and periodic QA Phantom Tests Digital Phantom Based Testing Standard QA Testing Remediation Schemes Profile Evolution Towards additional applications Towards higher accuracy and precision Supported in part by NIH contract HHSN268201300071C from NIBIB. Collaboration with GE Global Research, no personal support.; S. Chen, Some technologies described in this presentation have been licensed. Mayo Clinic and Dr. Chen have financial interests these technologies.« less

TH-A-207B-02: QIBA Ultrasound Elasticity Imaging System Biomarker Qualification and User Testing of Systems

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

Garra, B.

Imaging of tissue elastic properties is a relatively new and powerful approach to one of the oldest and most important diagnostic tools. Imaging of shear wave speed with ultrasound is has been added to most high-end ultrasound systems. Understanding this exciting imaging mode aiding its most effective use in medicine can be a rewarding effort for medical physicists and other medical imaging and treatment professionals. Assuring consistent, quantitative measurements across the many ultrasound systems in a typical imaging department will constitute a major step toward realizing the great potential of this technique and other quantitative imaging. This session will targetmore » these two goals with two presentations. A. Basics and Current Implementations of Ultrasound Imaging of Shear Wave Speed and Elasticity - Shigao Chen, Ph.D. Learning objectives-To understand: Introduction: Importance of tissue elasticity measurement Strain vs. shear wave elastography (SWE), beneficial features of SWE The link between shear wave speed and material properties, influence of viscosity Generation of shear waves External vibration (Fibroscan) ultrasound radiation force Point push Supersonic push (Aixplorer) Comb push (GE Logiq E9) Detection of shear waves Motion detection from pulse-echo ultrasound Importance of frame rate for shear wave imaging Plane wave imaging detection How to achieve high effective frame rate using line-by-line scanners Shear wave speed calculation Time to peak Random sample consensus (RANSAC) Cross correlation Sources of bias and variation in SWE Tissue viscosity Transducer compression or internal pressure of organ Reflection of shear waves at boundaries B. Elasticity Imaging System Biomarker Qualification and User Testing of Systems – Brian Garra, M.D. Learning objectives-To understand: Goals Review the need for quantitative medical imaging Provide examples of quantitative imaging biomarkers Acquaint the participant with the purpose of the RSNA Quantitative Imaging Biomarker Alliance and the need for such an organization Review the QIBA process for creating a quantitative biomarker Summarize steps needed to verify adherence of site, operators, and imaging systems to a QIBA profile Underlying Premise and Assumptions Objective, quantifiable results are needed to enhance the value of diagnostic imaging in clinical practice Reasons for quantification Evidence based medicine requires objective, not subjective observer data Computerized decision support tools (eg CAD) generally require quantitative input. Quantitative, reproducible measures are more easily used to develop personalized molecular medical diagnostic and treatment systems What is quantitative imaging? Definition from Imaging Metrology Workshop The Quantitative Imaging Biomarker Alliance Formation 2008 Mission Structure Example Imaging Biomarkers Being Explored Biomarker Selection Groundwork Draft Protocol for imaging and data evaluation QIBA Profile Drafting Equipment and Site Validation Technical Clinical Site and Equipment QA and Compliance Checking Ultrasound Elasticity Estimation Biomarker US Elasticity Estimation Background Current Status and Problems Biomarker Selection-process and outcome US SWS for Liver Fibrosis Biomarker Work Groundwork Literature search and analysis results Phase I phantom testing-Elastic phantoms Phase II phantom testing-Viscoelastic phantoms Digital Simulated Data Protocol and Profile Drafting Protocol: based on UPICT and existing literature and standards bodies protocols Profile-Current claims, Manufacturer specific appendices What comes after the profile Profile Validation Technical validation Clinical validation QA and Compliance Possible approaches Site Operator testing Site protocol re-evaluation Imaging system Manufacturer testing and attestation User acceptance testing and periodic QA Phantom Tests Digital Phantom Based Testing Standard QA Testing Remediation Schemes Profile Evolution Towards additional applications Towards higher accuracy and precision Supported in part by NIH contract HHSN268201300071C from NIBIB. Collaboration with GE Global Research, no personal support.; S. Chen, Some technologies described in this presentation have been licensed. Mayo Clinic and Dr. Chen have financial interests these technologies.« less

Mass Spectrometry-based Assay for High Throughput and High Sensitivity Biomarker Verification

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

Guo, Xuejiang; Tang, Keqi

Searching for disease specific biomarkers has become a major undertaking in the biomedical research field as the effective diagnosis, prognosis and treatment of many complex human diseases are largely determined by the availability and the quality of the biomarkers. A successful biomarker as an indicator to a specific biological or pathological process is usually selected from a large group of candidates by a strict verification and validation process. To be clinically useful, the validated biomarkers must be detectable and quantifiable by the selected testing techniques in their related tissues or body fluids. Due to its easy accessibility, protein biomarkers wouldmore » ideally be identified in blood plasma or serum. However, most disease related protein biomarkers in blood exist at very low concentrations (<1ng/mL) and are “masked” by many none significant species at orders of magnitude higher concentrations. The extreme requirements of measurement sensitivity, dynamic range and specificity make the method development extremely challenging. The current clinical protein biomarker measurement primarily relies on antibody based immunoassays, such as ELISA. Although the technique is sensitive and highly specific, the development of high quality protein antibody is both expensive and time consuming. The limited capability of assay multiplexing also makes the measurement an extremely low throughput one rendering it impractical when hundreds to thousands potential biomarkers need to be quantitatively measured across multiple samples. Mass spectrometry (MS)-based assays have recently shown to be a viable alternative for high throughput and quantitative candidate protein biomarker verification. Among them, the triple quadrupole MS based assay is the most promising one. When it is coupled with liquid chromatography (LC) separation and electrospray ionization (ESI) source, a triple quadrupole mass spectrometer operating in a special selected reaction monitoring (SRM) mode, also known as multiple reaction monitoring (MRM), is capable of quantitatively measuring hundreds of candidate protein biomarkers from a relevant clinical sample in a single analysis. The specificity, reproducibility and sensitivity could be as good as ELISA. Furthermore, SRM MS can also quantify protein isoforms and post-translational modifications, for which traditional antibody-based immunoassays often don’t exist.« less

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.

Multivariate Analysis As a Support for Diagnostic Flowcharts in Allergic Bronchopulmonary Aspergillosis: A Proof-of-Concept Study.

PubMed

Vitte, Joana; Ranque, Stéphane; Carsin, Ania; Gomez, Carine; Romain, Thomas; Cassagne, Carole; Gouitaa, Marion; Baravalle-Einaudi, Mélisande; Bel, Nathalie Stremler-Le; Reynaud-Gaubert, Martine; Dubus, Jean-Christophe; Mège, Jean-Louis; Gaudart, Jean

2017-01-01

Molecular-based allergy diagnosis yields multiple biomarker datasets. The classical diagnostic score for allergic bronchopulmonary aspergillosis (ABPA), a severe disease usually occurring in asthmatic patients and people with cystic fibrosis, comprises succinct immunological criteria formulated in 1977: total IgE, anti- Aspergillus fumigatus ( Af ) IgE, anti- Af "precipitins," and anti- Af IgG. Progress achieved over the last four decades led to multiple IgE and IgG(4) Af biomarkers available with quantitative, standardized, molecular-level reports. These newly available biomarkers have not been included in the current diagnostic criteria, either individually or in algorithms, despite persistent underdiagnosis of ABPA. Large numbers of individual biomarkers may hinder their use in clinical practice. Conversely, multivariate analysis using new tools may bring about a better chance of less diagnostic mistakes. We report here a proof-of-concept work consisting of a three-step multivariate analysis of Af IgE, IgG, and IgG4 biomarkers through a combination of principal component analysis, hierarchical ascendant classification, and classification and regression tree multivariate analysis. The resulting diagnostic algorithms might show the way for novel criteria and improved diagnostic efficiency in Af -sensitized patients at risk for ABPA.

Comparative study of two protocols for quantitative image-analysis of serotonin transporter clustering in lymphocytes, a putative biomarker of therapeutic efficacy in major depression.

PubMed

Romay-Tallon, Raquel; Rivera-Baltanas, Tania; Allen, Josh; Olivares, Jose M; Kalynchuk, Lisa E; Caruncho, Hector J

2017-01-01

The pattern of serotonin transporter clustering on the plasma membrane of lymphocytes extracted from human whole blood samples has been identified as a putative biomarker of therapeutic efficacy in major depression. Here we evaluated the possibility of performing a similar analysis using blood smears obtained from rats, and from control human subjects and depression patients. We hypothesized that we could optimize a protocol to make the analysis of serotonin protein clustering in blood smears comparable to the analysis of serotonin protein clustering using isolated lymphocytes. Our data indicate that blood smears require a longer fixation time and longer times of incubation with primary and secondary antibodies. In addition, one needs to optimize the image analysis settings for the analysis of smears. When these steps are followed, the quantitative analysis of both the number and size of serotonin transporter clusters on the plasma membrane of lymphocytes is similar using both blood smears and isolated lymphocytes. The development of this novel protocol will greatly facilitate the collection of appropriate samples by eliminating the necessity and cost of specialized personnel for drawing blood samples, and by being a less invasive procedure. Therefore, this protocol will help us advance the validation of membrane protein clustering in lymphocytes as a biomarker of therapeutic efficacy in major depression, and bring it closer to its clinical application.

Analytical validation of quantitative immunohistochemical assays of tumor infiltrating lymphocyte biomarkers.

PubMed

Singh, U; Cui, Y; Dimaano, N; Mehta, S; Pruitt, S K; Yearley, J; Laterza, O F; Juco, J W; Dogdas, B

2018-06-04

Tumor infiltrating lymphocytes (TIL), especially T-cells, have both prognostic and therapeutic applications. The presence of CD8+ effector T-cells and the ratio of CD8+ cells to FOXP3+ regulatory T-cells have been used as biomarkers of disease prognosis to predict response to various immunotherapies. Blocking the interaction between inhibitory receptors on T-cells and their ligands with therapeutic antibodies including atezolizumab, nivolumab, pembrolizumab and tremelimumab increases the immune response against cancer cells and has shown significant improvement in clinical benefits and survival in several different tumor types. The improved clinical outcome is presumed to be associated with a higher tumor infiltration; therefore, it is thought that more accurate methods for measuring the amount of TIL could assist prognosis and predict treatment response. We have developed and validated quantitative immunohistochemistry (IHC) assays for CD3, CD8 and FOXP3 for immunophenotyping T-lymphocytes in tumor tissue. Various types of formalin fixed, paraffin embedded (FFPE) tumor tissues were immunolabeled with anti-CD3, anti-CD8 and anti-FOXP3 antibodies using an IHC autostainer. The tumor area of stained tissues, including the invasive margin of the tumor, was scored by a pathologist (visual scoring) and by computer-based quantitative image analysis. Two image analysis scores were obtained for the staining of each biomarker: the percent positive cells in the tumor area and positive cells/mm 2 tumor area. Comparison of visual vs. image analysis scoring methods using regression analysis showed high correlation and indicated that quantitative image analysis can be used to score the number of positive cells in IHC stained slides. To demonstrate that the IHC assays produce consistent results in normal daily testing, we evaluated the specificity, sensitivity and reproducibility of the IHC assays using both visual and image analysis scoring methods. We found that CD3, CD8 and FOXP3 IHC assays met the fit-for-purpose analytical acceptance validation criteria and that they can be used to support clinical studies.

Widely-targeted quantitative lipidomics methodology by supercritical fluid chromatography coupled with fast-scanning triple quadrupole mass spectrometry.

PubMed

Takeda, Hiroaki; Izumi, Yoshihiro; Takahashi, Masatomo; Paxton, Thanai; Tamura, Shohei; Koike, Tomonari; Yu, Ying; Kato, Noriko; Nagase, Katsutoshi; Shiomi, Masashi; Bamba, Takeshi

2018-05-03

Lipidomics, the mass spectrometry-based comprehensive analysis of lipids, has attracted attention as an analytical approach to provide novel insight into lipid metabolism and to search for biomarkers. However, an ideal method for both comprehensive and quantitative analysis of lipids has not been fully developed. Herein, we have proposed a practical methodology for widely-targeted quantitative lipidome analysis using supercritical fluid chromatography fast-scanning triple-quadrupole mass spectrometry (SFC/QqQMS) and theoretically calculated a comprehensive lipid multiple reaction monitoring (MRM) library. Lipid classes can be separated by SFC with a normal phase diethylamine-bonded silica column with high-resolution, high-throughput, and good repeatability. Structural isomers of phospholipids can be monitored by mass spectrometric separation with fatty acyl-based MRM transitions. SFC/QqQMS analysis with an internal standard-dilution method offers quantitative information for both lipid class and individual lipid molecular species in the same lipid class. Additionally, data acquired using this method has advantages including reduction of misidentification and acceleration of data analysis. Using the SFC/QqQMS system, alteration of plasma lipid levels in myocardial infarction-prone rabbits to the supplementation of eicosapentaenoic acid was first observed. Our developed SFC/QqQMS method represents a potentially useful tool for in-depth studies focused on complex lipid metabolism and biomarker discovery. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.

Isobaric Tags for Relative and Absolute Quantification (iTRAQ)-Based Untargeted Quantitative Proteomic Approach To Identify Change of the Plasma Proteins by Salbutamol Abuse in Beef Cattle.

PubMed

Zhang, Kai; Tang, Chaohua; Liang, Xiaowei; Zhao, Qingyu; Zhang, Junmin

2018-01-10

Salbutamol, a selective β 2 -agonist, endangers the safety of animal products as a result of illegal use in food animals. In this study, an iTRAQ-based untargeted quantitative proteomic approach was applied to screen potential protein biomarkers in plasma of cattle before and after treatment with salbutamol for 21 days. A total of 62 plasma proteins were significantly affected by salbutamol treatment, which can be used as potential biomarkers to screen for the illegal use of salbutamol in beef cattle. Enzyme-linked immunosorbent assay measurements of five selected proteins demonstrated the reliability of iTRAQ-based proteomics in screening of candidate biomarkers among the plasma proteins. The plasma samples collected before and after salbutamol treatment were well-separated by principal component analysis (PCA) using the differentially expressed proteins. These results suggested that an iTRAQ-based untargeted quantitative proteomic strategy combined with PCA pattern recognition methods can discriminate differences in plasma protein profiles collected before and after salbutamol treatment.

Optimized protocol for quantitative multiple reaction monitoring-based proteomic analysis of formalin-fixed, paraffin embedded tissues

PubMed Central

Kennedy, Jacob J.; Whiteaker, Jeffrey R.; Schoenherr, Regine M.; Yan, Ping; Allison, Kimberly; Shipley, Melissa; Lerch, Melissa; Hoofnagle, Andrew N.; Baird, Geoffrey Stuart; Paulovich, Amanda G.

2016-01-01

Despite a clinical, economic, and regulatory imperative to develop companion diagnostics, precious few new biomarkers have been successfully translated into clinical use, due in part to inadequate protein assay technologies to support large-scale testing of hundreds of candidate biomarkers in formalin-fixed paraffin embedded (FFPE) tissues. While the feasibility of using targeted, multiple reaction monitoring-mass spectrometry (MRM-MS) for quantitative analyses of FFPE tissues has been demonstrated, protocols have not been systematically optimized for robust quantification across a large number of analytes, nor has the performance of peptide immuno-MRM been evaluated. To address this gap, we used a test battery approach coupled to MRM-MS with the addition of stable isotope labeled standard peptides (targeting 512 analytes) to quantitatively evaluate the performance of three extraction protocols in combination with three trypsin digestion protocols (i.e. 9 processes). A process based on RapiGest buffer extraction and urea-based digestion was identified to enable similar quantitation results from FFPE and frozen tissues. Using the optimized protocols for MRM-based analysis of FFPE tissues, median precision was 11.4% (across 249 analytes). There was excellent correlation between measurements made on matched FFPE and frozen tissues, both for direct MRM analysis (R2 = 0.94) and immuno-MRM (R2 = 0.89). The optimized process enables highly reproducible, multiplex, standardizable, quantitative MRM in archival tissue specimens. PMID:27462933

TH-A-207B-01: Basics and Current Implementations of Ultrasound Imaging of Shear Wave Speed and Elasticity

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

Chen, S.

Imaging of tissue elastic properties is a relatively new and powerful approach to one of the oldest and most important diagnostic tools. Imaging of shear wave speed with ultrasound is has been added to most high-end ultrasound systems. Understanding this exciting imaging mode aiding its most effective use in medicine can be a rewarding effort for medical physicists and other medical imaging and treatment professionals. Assuring consistent, quantitative measurements across the many ultrasound systems in a typical imaging department will constitute a major step toward realizing the great potential of this technique and other quantitative imaging. This session will targetmore » these two goals with two presentations. A. Basics and Current Implementations of Ultrasound Imaging of Shear Wave Speed and Elasticity - Shigao Chen, Ph.D. Learning objectives-To understand: Introduction: Importance of tissue elasticity measurement Strain vs. shear wave elastography (SWE), beneficial features of SWE The link between shear wave speed and material properties, influence of viscosity Generation of shear waves External vibration (Fibroscan) ultrasound radiation force Point push Supersonic push (Aixplorer) Comb push (GE Logiq E9) Detection of shear waves Motion detection from pulse-echo ultrasound Importance of frame rate for shear wave imaging Plane wave imaging detection How to achieve high effective frame rate using line-by-line scanners Shear wave speed calculation Time to peak Random sample consensus (RANSAC) Cross correlation Sources of bias and variation in SWE Tissue viscosity Transducer compression or internal pressure of organ Reflection of shear waves at boundaries B. Elasticity Imaging System Biomarker Qualification and User Testing of Systems – Brian Garra, M.D. Learning objectives-To understand: Goals Review the need for quantitative medical imaging Provide examples of quantitative imaging biomarkers Acquaint the participant with the purpose of the RSNA Quantitative Imaging Biomarker Alliance and the need for such an organization Review the QIBA process for creating a quantitative biomarker Summarize steps needed to verify adherence of site, operators, and imaging systems to a QIBA profile Underlying Premise and Assumptions Objective, quantifiable results are needed to enhance the value of diagnostic imaging in clinical practice Reasons for quantification Evidence based medicine requires objective, not subjective observer data Computerized decision support tools (eg CAD) generally require quantitative input. Quantitative, reproducible measures are more easily used to develop personalized molecular medical diagnostic and treatment systems What is quantitative imaging? Definition from Imaging Metrology Workshop The Quantitative Imaging Biomarker Alliance Formation 2008 Mission Structure Example Imaging Biomarkers Being Explored Biomarker Selection Groundwork Draft Protocol for imaging and data evaluation QIBA Profile Drafting Equipment and Site Validation Technical Clinical Site and Equipment QA and Compliance Checking Ultrasound Elasticity Estimation Biomarker US Elasticity Estimation Background Current Status and Problems Biomarker Selection-process and outcome US SWS for Liver Fibrosis Biomarker Work Groundwork Literature search and analysis results Phase I phantom testing-Elastic phantoms Phase II phantom testing-Viscoelastic phantoms Digital Simulated Data Protocol and Profile Drafting Protocol: based on UPICT and existing literature and standards bodies protocols Profile-Current claims, Manufacturer specific appendices What comes after the profile Profile Validation Technical validation Clinical validation QA and Compliance Possible approaches Site Operator testing Site protocol re-evaluation Imaging system Manufacturer testing and attestation User acceptance testing and periodic QA Phantom Tests Digital Phantom Based Testing Standard QA Testing Remediation Schemes Profile Evolution Towards additional applications Towards higher accuracy and precision Supported in part by NIH contract HHSN268201300071C from NIBIB. Collaboration with GE Global Research, no personal support.; S. Chen, Some technologies described in this presentation have been licensed. Mayo Clinic and Dr. Chen have financial interests these technologies.« less

Methylation analysis of plasma cell-free DNA for breast cancer early detection using bisulfite next-generation sequencing.

PubMed

Li, Zibo; Guo, Xinwu; Tang, Lili; Peng, Limin; Chen, Ming; Luo, Xipeng; Wang, Shouman; Xiao, Zhi; Deng, Zhongping; Dai, Lizhong; Xia, Kun; Wang, Jun

2016-10-01

Circulating cell-free DNA (cfDNA) has been considered as a potential biomarker for non-invasive cancer detection. To evaluate the methylation levels of six candidate genes (EGFR, GREM1, PDGFRB, PPM1E, SOX17, and WRN) in plasma cfDNA as biomarkers for breast cancer early detection, quantitative analysis of the promoter methylation of these genes from 86 breast cancer patients and 67 healthy controls was performed by using microfluidic-PCR-based target enrichment and next-generation bisulfite sequencing technology. The predictive performance of different logistic models based on methylation status of candidate genes was investigated by means of the area under the ROC curve (AUC) and odds ratio (OR) analysis. Results revealed that EGFR, PPM1E, and 8 gene-specific CpG sites showed significantly hypermethylation in cancer patients' plasma and significantly associated with breast cancer (OR ranging from 2.51 to 9.88). The AUC values for these biomarkers were ranging from 0.66 to 0.75. Combinations of multiple hypermethylated genes or CpG sites substantially improved the predictive performance for breast cancer detection. Our study demonstrated the feasibility of quantitative measurement of candidate gene methylation in cfDNA by using microfluidic-PCR-based target enrichment and bisulfite next-generation sequencing, which is worthy of further validation and potentially benefits a broad range of applications in clinical oncology practice. Quantitative analysis of methylation pattern of plasma cfDNA by next-generation sequencing might be a valuable non-invasive tool for early detection of breast cancer.

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

PubMed

Wilson, Jennifer L; Altman, Russ B

2018-02-01

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

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

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

Volumetric CT in lung cancer: an example for the qualification of imaging as a biomarker.

PubMed

Buckler, Andrew J; Mozley, P David; Schwartz, Lawrence; Petrick, Nicholas; McNitt-Gray, Michael; Fenimore, Charles; O'Donnell, Kevin; Hayes, Wendy; Kim, Hyun J; Clarke, Laurence; Sullivan, Daniel

2010-01-01

New ways to understand biology as well as increasing interest in personalized treatments requires new capabilities for the assessment of therapy response. The lack of consensus methods and qualification evidence needed for large-scale multicenter trials, and in turn the standardization that allows them, are widely acknowledged to be the limiting factor in the deployment of qualified imaging biomarkers. The Quantitative Imaging Biomarker Alliance is organized to establish a methodology whereby multiple stakeholders collaborate. It has charged the Volumetric Computed Tomography (CT) Technical Subcommittee with investigating the technical feasibility and clinical value of quantifying changes over time in either volume or other parameters as biomarkers. The group selected solid tumors of the chest in subjects with lung cancer as its first case in point. Success is defined as sufficiently rigorous improvements in CT-based outcome measures to allow individual patients in clinical settings to switch treatments sooner if they are no longer responding to their current regimens, and reduce the costs of evaluating investigational new drugs to treat lung cancer. The team has completed a systems engineering analysis, has begun a roadmap of experimental groundwork, documented profile claims and protocols, and documented a process for imaging biomarker qualification as a general paradigm for qualifying other imaging biomarkers as well. This report addresses a procedural template for the qualification of quantitative imaging biomarkers. This mechanism is cost-effective for stakeholders while simultaneously advancing the public health by promoting the use of measures that prove effective.

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

PubMed Central

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

2014-01-01

Protein biomarkers are needed to deepen our understanding of cancer biology and to improve our ability to diagnose, monitor and treat cancers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Although contemporary proteomics technologies support the measurement of large numbers of proteins in individual clinical specimens, sample throughput remains comparatively low. This problem is amplified in typical clinical proteomics research studies, which routinely suffer from a lack of proper experimental design, resulting in analysis of too few biospecimens to achieve adequate statistical power at each stage of a biomarker pipeline. To address this critical shortcoming, a joint workshop was held by the National Cancer Institute (NCI), National Heart, Lung and Blood Institute (NHLBI), and American Association for Clinical Chemistry (AACC), with participation from the U.S. Food and Drug Administration (FDA). An important output from the workshop was a statistical framework for the design of biomarker discovery and verification studies. Herein, we describe the use of quantitative clinical judgments to set statistical criteria for clinical relevance, and the development of an approach to calculate biospecimen sample size for proteomic studies in discovery and verification stages prior to clinical validation stage. This represents a first step towards building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research. PMID:24063748

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

PubMed

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

2013-12-06

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

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

PubMed Central

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

2016-01-01

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

High-throughput SISCAPA quantitation of peptides from human plasma digests by ultrafast, liquid chromatography-free mass spectrometry.

PubMed

Razavi, Morteza; Frick, Lauren E; LaMarr, William A; Pope, Matthew E; Miller, Christine A; Anderson, N Leigh; Pearson, Terry W

2012-12-07

We investigated the utility of an SPE-MS/MS platform in combination with a modified SISCAPA workflow for chromatography-free MRM analysis of proteotypic peptides in digested human plasma. This combination of SISCAPA and SPE-MS/MS technology allows sensitive, MRM-based quantification of peptides from plasma digests with a sample cycle time of ∼7 s, a 300-fold improvement over typical MRM analyses with analysis times of 30-40 min that use liquid chromatography upstream of MS. The optimized system includes capture and enrichment to near purity of target proteotypic peptides using rigorously selected, high affinity, antipeptide monoclonal antibodies and reduction of background peptides using a novel treatment of magnetic bead immunoadsorbents. Using this method, we have successfully quantitated LPS-binding protein and mesothelin (concentrations of ∼5000 ng/mL and ∼10 ng/mL, respectively) in human plasma. The method eliminates the need for upstream liquid-chromatography and can be multiplexed, thus facilitating quantitative analysis of proteins, including biomarkers, in large sample sets. The method is ideal for high-throughput biomarker validation after affinity enrichment and has the potential for applications in clinical laboratories.

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

PubMed Central

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

2015-01-01

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

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.

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

Complementary biomarker-based methods for characterising Arctic sea ice conditions: A case study comparison between multivariate analysis and the PIP25 index

NASA Astrophysics Data System (ADS)

Köseoğlu, Denizcan; Belt, Simon T.; Smik, Lukas; Yao, Haoyi; Panieri, Giuliana; Knies, Jochen

2018-02-01

The discovery of IP25 as a qualitative biomarker proxy for Arctic sea ice and subsequent introduction of the so-called PIP25 index for semi-quantitative descriptions of sea ice conditions has significantly advanced our understanding of long-term paleo Arctic sea ice conditions over the past decade. We investigated the potential for classification tree (CT) models to provide a further approach to paleo Arctic sea ice reconstruction through analysis of a suite of highly branched isoprenoid (HBI) biomarkers in ca. 200 surface sediments from the Barents Sea. Four CT models constructed using different HBI assemblages revealed IP25 and an HBI triene as the most appropriate classifiers of sea ice conditions, achieving a >90% cross-validated classification rate. Additionally, lower model performance for locations in the Marginal Ice Zone (MIZ) highlighted difficulties in characterisation of this climatically-sensitive region. CT model classification and semi-quantitative PIP25-derived estimates of spring sea ice concentration (SpSIC) for four downcore records from the region were consistent, although agreement between proxy and satellite/observational records was weaker for a core from the west Svalbard margin, likely due to the highly variable sea ice conditions. The automatic selection of appropriate biomarkers for description of sea ice conditions, quantitative model assessment, and insensitivity to the c-factor used in the calculation of the PIP25 index are key attributes of the CT approach, and we provide an initial comparative assessment between these potentially complementary methods. The CT model should be capable of generating longer-term temporal shifts in sea ice conditions for the climatically sensitive Barents Sea.

Phospholipid-derived fatty acids and quinones as markers for bacterial biomass and community structure in marine sediments.

PubMed

Kunihiro, Tadao; Veuger, Bart; Vasquez-Cardenas, Diana; Pozzato, Lara; Le Guitton, Marie; Moriya, Kazuyoshi; Kuwae, Michinobu; Omori, Koji; Boschker, Henricus T S; van Oevelen, Dick

2014-01-01

Phospholipid-derived fatty acids (PLFA) and respiratory quinones (RQ) are microbial compounds that have been utilized as biomarkers to quantify bacterial biomass and to characterize microbial community structure in sediments, waters, and soils. While PLFAs have been widely used as quantitative bacterial biomarkers in marine sediments, applications of quinone analysis in marine sediments are very limited. In this study, we investigated the relation between both groups of bacterial biomarkers in a broad range of marine sediments from the intertidal zone to the deep sea. We found a good log-log correlation between concentrations of bacterial PLFA and RQ over several orders of magnitude. This relationship is probably due to metabolic variation in quinone concentrations in bacterial cells in different environments, whereas PLFA concentrations are relatively stable under different conditions. We also found a good agreement in the community structure classifications based on the bacterial PLFAs and RQs. These results strengthen the application of both compounds as quantitative bacterial biomarkers. Moreover, the bacterial PLFA- and RQ profiles revealed a comparable dissimilarity pattern of the sampled sediments, but with a higher level of dissimilarity for the RQs. This means that the quinone method has a higher resolution for resolving differences in bacterial community composition. Combining PLFA and quinone analysis as a complementary method is a good strategy to yield higher resolving power in bacterial community structure.

Visibility graph analysis of heart rate time series and bio-marker of congestive heart failure

NASA Astrophysics Data System (ADS)

Bhaduri, Anirban; Bhaduri, Susmita; Ghosh, Dipak

2017-09-01

Study of RR interval time series for Congestive Heart Failure had been an area of study with different methods including non-linear methods. In this article the cardiac dynamics of heart beat are explored in the light of complex network analysis, viz. visibility graph method. Heart beat (RR Interval) time series data taken from Physionet database [46, 47] belonging to two groups of subjects, diseased (congestive heart failure) (29 in number) and normal (54 in number) are analyzed with the technique. The overall results show that a quantitative parameter can significantly differentiate between the diseased subjects and the normal subjects as well as different stages of the disease. Further, the data when split into periods of around 1 hour each and analyzed separately, also shows the same consistent differences. This quantitative parameter obtained using the visibility graph analysis thereby can be used as a potential bio-marker as well as a subsequent alarm generation mechanism for predicting the onset of Congestive Heart Failure.

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

PubMed

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

2014-02-26

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

Optimal tumor sampling for immunostaining of biomarkers in breast carcinoma

PubMed Central

2011-01-01

Introduction Biomarkers, such as Estrogen Receptor, are used to determine therapy and prognosis in breast carcinoma. Immunostaining assays of biomarker expression have a high rate of inaccuracy; for example, estimates are as high as 20% for Estrogen Receptor. Biomarkers have been shown to be heterogeneously expressed in breast tumors and this heterogeneity may contribute to the inaccuracy of immunostaining assays. Currently, no evidence-based standards exist for the amount of tumor that must be sampled in order to correct for biomarker heterogeneity. The aim of this study was to determine the optimal number of 20X fields that are necessary to estimate a representative measurement of expression in a whole tissue section for selected biomarkers: ER, HER-2, AKT, ERK, S6K1, GAPDH, Cytokeratin, and MAP-Tau. Methods Two collections of whole tissue sections of breast carcinoma were immunostained for biomarkers. Expression was quantified using the Automated Quantitative Analysis (AQUA) method of quantitative immunofluorescence. Simulated sampling of various numbers of fields (ranging from one to thirty five) was performed for each marker. The optimal number was selected for each marker via resampling techniques and minimization of prediction error over an independent test set. Results The optimal number of 20X fields varied by biomarker, ranging between three to fourteen fields. More heterogeneous markers, such as MAP-Tau protein, required a larger sample of 20X fields to produce representative measurement. Conclusions The optimal number of 20X fields that must be sampled to produce a representative measurement of biomarker expression varies by marker with more heterogeneous markers requiring a larger number. The clinical implication of these findings is that breast biopsies consisting of a small number of fields may be inadequate to represent whole tumor biomarker expression for many markers. Additionally, for biomarkers newly introduced into clinical use, especially if therapeutic response is dictated by level of expression, the optimal size of tissue sample must be determined on a marker-by-marker basis. PMID:21592345

Brain tissues atrophy is not always the best structural biomarker of physiological aging: A multimodal cross-sectional study.

PubMed

Cherubini, Andrea; Caligiuri, Maria Eugenia; Péran, Patrice; Sabatini, Umberto; Cosentino, Carlo; Amato, Francesco

2015-01-01

This study presents a voxel-based multiple regression analysis of different magnetic resonance image modalities, including anatomical T1-weighted, T2* relaxometry, and diffusion tensor imaging. Quantitative parameters sensitive to complementary brain tissue alterations, including morphometric atrophy, mineralization, microstructural damage, and anisotropy loss, were compared in a linear physiological aging model in 140 healthy subjects (range 20-74 years). The performance of different predictors and the identification of the best biomarker of age-induced structural variation were compared without a priori anatomical knowledge. The best quantitative predictors in several brain regions were iron deposition and microstructural damage, rather than macroscopic tissue atrophy. Age variations were best resolved with a combination of markers, suggesting that multiple predictors better capture age-induced tissue alterations. These findings highlight the importance of a combined evaluation of multimodal biomarkers for the study of aging and point to a number of novel applications for the method described.

MicroRNA Expression Profiling of the Armed Forces Health Surveillance Branch Cohort for Identification of "Enviro-miRs" Associated With Deployment-Based Environmental Exposure.

PubMed

Dalgard, Clifton L; Polston, Keith F; Sukumar, Gauthaman; Mallon, Col Timothy M; Wilkerson, Matthew D; Pollard, Harvey B

2016-08-01

The aim of this study was to identify serum microRNA (miRNA) biomarkers that indicate deployment-associated exposures in service members at military installations with open burn pits. Another objective was to determine detection rates of miRNAs in Department of Defense Serum Repository (DoDSR) samples with a high-throughput methodology. Low-volume serum samples (n = 800) were profiled by miRNA-capture isolation, pre-amplification, and measurement by a quantitative PCR-based OpenArray platform. Normalized quantitative cycle values were used for differential expression analysis between groups. Assay specificity, dynamic range, reproducibility, and detection rates by OpenArray passed target desired specifications. Serum abundant miRNAs were consistently measured in study specimens. Four miRNAs were differentially expressed in the case deployment group subjects. miRNAs are suitable RNA species for biomarker discovery in the DoDSR serum specimens. Serum miRNAs are candidate biomarkers for deployment and environmental exposure in military service members.

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

PubMed

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

2013-08-26

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

From differences in means between cases and controls to risk stratification: a business plan for biomarker development.

PubMed

Wentzensen, Nicolas; Wacholder, Sholom

2013-02-01

Researchers developing biomarkers for early detection can determine the potential for clinical benefit at early stages of development. We provide the theoretical background showing the quantitative connection between biomarker levels in cases and controls and clinically meaningful risk measures, as well as a spreadsheet for researchers to use in their own research. We provide researchers with tools to decide whether a test is useful, whether it needs technical improvement, whether it may work only in specific populations, or whether any further development is futile. The methods described here apply to any method that aims to estimate risk of disease based on biomarkers, clinical tests, genetics, environment, or behavior. Many efforts go into futile biomarker development and premature clinical testing. In many instances, predictions for translational success or failure can be made early, simply based on critical analysis of case–control data. Our article presents well-established theory in a form that can be appreciated by biomarker researchers. Furthermore, we provide an interactive spreadsheet that links biomarker performance with specific disease characteristics to evaluate the promise of biomarker candidates at an early stage.

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.

Quantitation of heat-shock proteins in clinical samples using mass spectrometry.

PubMed

Kaur, Punit; Asea, Alexzander

2011-01-01

Mass spectrometry (MS) is a powerful analytical tool for proteomics research and drug and biomarker discovery. MS enables identification and quantification of known and unknown compounds by revealing their structural and chemical properties. Proper sample preparation for MS-based analysis is a critical step in the proteomics workflow because the quality and reproducibility of sample extraction and preparation for downstream analysis significantly impact the separation and identification capabilities of mass spectrometers. The highly expressed proteins represent potential biomarkers that could aid in diagnosis, therapy, or drug development. Because the proteome is so complex, there is no one standard method for preparing protein samples for MS analysis. Protocols differ depending on the type of sample, source, experiment, and method of analysis. Molecular chaperones play significant roles in almost all biological functions due to their capacity for detecting intracellular denatured/unfolded proteins, initiating refolding or denaturation of such malfolded protein sequences and more recently for their role in the extracellular milieu as chaperokines. In this chapter, we describe the latest techniques for quantitating the expression of molecular chaperones in human clinical samples.

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

PubMed

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

2013-11-01

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

Quantitative multiplex detection of pathogen biomarkers

DOEpatents

Mukundan, Harshini; Xie, Hongzhi; Swanson, Basil I.; Martinez, Jennifer; Grace, Wynne K.

2016-02-09

The present invention addresses the simultaneous detection and quantitative measurement of multiple biomolecules, e.g., pathogen biomarkers through either a sandwich assay approach or a lipid insertion approach. The invention can further employ a multichannel, structure with multi-sensor elements per channel.

Quantitative multiplex detection of pathogen biomarkers

DOEpatents

Mukundan, Harshini; Xie, Hongzhi; Swanson, Basil I; Martinez, Jennifer; Grace, Wynne K

2014-10-14

The present invention addresses the simultaneous detection and quantitative measurement of multiple biomolecules, e.g., pathogen biomarkers through either a sandwich assay approach or a lipid insertion approach. The invention can further employ a multichannel, structure with multi-sensor elements per channel.

[Recent advances in metabonomics].

PubMed

Xu, Guo-Wang; Lu, Xin; Yang, Sheng-Li

2007-12-01

Metabonomics (or metabolomics) aims at the comprehensive and quantitative analysis of the wide arrays of metabolites in biological samples. Metabonomics has been labeled as one of the new" -omics" joining genomics, transcriptomics, and proteomics as a science employed toward the understanding of global systems biology. It has been widely applied in many research areas including drug toxicology, biomarker discovery, functional genomics, and molecular pathology etc. The comprehensive analysis of the metabonome is particularly challenging due to the diverse chemical natures of metabolites. Metabonomics investigations require special approaches for sample preparation, data-rich analytical chemical measurements, and information mining. The outputs from a metabonomics study allow sample classification, biomarker discovery, and interpretation of the reasons for classification information. This review focuses on the currently new advances in various technical platforms of metabonomics and its applications in drug discovery and development, disease biomarker identification, plant and microbe related fields.

Quantitative Imaging Biomarkers of NAFLD

PubMed Central

Kinner, Sonja; Reeder, Scott B.

2016-01-01

Conventional imaging modalities, including ultrasonography (US), computed tomography (CT), and magnetic resonance (MR), play an important role in the diagnosis and management of patients with nonalcoholic fatty liver disease (NAFLD) by allowing noninvasive diagnosis of hepatic steatosis. However, conventional imaging modalities are limited as biomarkers of NAFLD for various reasons. Multi-parametric quantitative MRI techniques overcome many of the shortcomings of conventional imaging and allow comprehensive and objective evaluation of NAFLD. MRI can provide unconfounded biomarkers of hepatic fat, iron, and fibrosis in a single examination—a virtual biopsy has become a clinical reality. In this article, we will review the utility and limitation of conventional US, CT, and MR imaging for the diagnosis NAFLD. Recent advances in imaging biomarkers of NAFLD are also discussed with an emphasis in multi-parametric quantitative MRI. PMID:26848588

Absolute Quantification of Middle- to High-Abundant Plasma Proteins via Targeted Proteomics.

PubMed

Dittrich, Julia; Ceglarek, Uta

2017-01-01

The increasing number of peptide and protein biomarker candidates requires expeditious and reliable quantification strategies. The utilization of liquid chromatography coupled to quadrupole tandem mass spectrometry (LC-MS/MS) for the absolute quantitation of plasma proteins and peptides facilitates the multiplexed verification of tens to hundreds of biomarkers from smallest sample quantities. Targeted proteomics assays derived from bottom-up proteomics principles rely on the identification and analysis of proteotypic peptides formed in an enzymatic digestion of the target protein. This protocol proposes a procedure for the establishment of a targeted absolute quantitation method for middle- to high-abundant plasma proteins waiving depletion or enrichment steps. Essential topics as proteotypic peptide identification and LC-MS/MS method development as well as sample preparation and calibration strategies are described in detail.

Digital imaging biomarkers feed machine learning for melanoma screening.

PubMed

Gareau, Daniel S; Correa da Rosa, Joel; Yagerman, Sarah; Carucci, John A; Gulati, Nicholas; Hueto, Ferran; DeFazio, Jennifer L; Suárez-Fariñas, Mayte; Marghoob, Ashfaq; Krueger, James G

2017-07-01

We developed an automated approach for generating quantitative image analysis metrics (imaging biomarkers) that are then analysed with a set of 13 machine learning algorithms to generate an overall risk score that is called a Q-score. These methods were applied to a set of 120 "difficult" dermoscopy images of dysplastic nevi and melanomas that were subsequently excised/classified. This approach yielded 98% sensitivity and 36% specificity for melanoma detection, approaching sensitivity/specificity of expert lesion evaluation. Importantly, we found strong spectral dependence of many imaging biomarkers in blue or red colour channels, suggesting the need to optimize spectral evaluation of pigmented lesions. © 2016 The Authors. Experimental Dermatology Published by John Wiley & Sons Ltd.

Quantitative assessment of the relationship between biomarker content and biomass in marine phytoplankton in responses to temperature and nutrient supply ratio changes

NASA Astrophysics Data System (ADS)

Ding, Y.; Chen, X.; Bi, R.; Zhang, L. H.; Li, L.; Zhao, M.

2016-12-01

Alkenones and sterols are useful biomarkers to construct past productivity and community structure changes in aquatic environments. Until now, the quantitative relationship between biomarker content and biomass in marine phytoplankton remains understudied, which hinders the quantitative reconstruction of ocean changes. In this study, we carried out laboratory culture experiments to determine the quantitative relationship between biomarker content and biomass under three temperatures (15°, 20° and 25°) and three N:P supply ratios (N:P=10:1, 24:1 and 63:1 mol mol-1) for three common phytoplankton groups, diatoms (Phaeodactylum tricornutum Bohlin, Skeletonema costatum, Chaetoceros muelleri), dinoflagellates (Karenia mikimotoi, Prorocentrum donghaiense, Prorocentrum minimum), and coccolithophores (Emiliania huxleyi). Alkenones were only detected in E. huxleyiand dinosterol was only detected in dinoflagellates, confirming that they are the biomarkers for these two groups of phytoplankton, respectively. Brassicasterol was detected in all three groups of phytoplankton, but its content was higher in diatoms, suggesting that it is still a useful biomarker for diatoms. Cell-normalized alkenone content (pg/cell) increases with increasing growth temperature by up to 30%; while the effect of nutrients on alkenone content is minimum. On the other hand, cell-normalized dinosterol content is not temperature dependent, but it is strongly affected by nutrient ratio changes. The effects of temperature and nutrients on cell-normalized brassicasterol content are phytoplankton dependent. For diatoms, the temperature effect is minimum while the nutrient effect is significant but also varies with temperatures. Our results have strong implications for understanding how different phytoplankton respond to global changes, and for more quantitative reconstruction of past productivity and community structure changes using these biomarkers.

Wastewater analysis to monitor use of caffeine and nicotine and evaluation of their metabolites as biomarkers for population size assessment.

PubMed

Senta, Ivan; Gracia-Lor, Emma; Borsotti, Andrea; Zuccato, Ettore; Castiglioni, Sara

2015-05-01

The use of caffeine, nicotine and some major metabolites was investigated by wastewater analysis in 13 sewage treatment plants (STPs) across Italy, and their suitability was tested as qualitative and quantitative biomarkers for assessing population size and dynamics. A specific analytical method based on mass spectrometry was developed and validated in raw urban wastewater, and included two caffeine metabolites, 1-methylxanthine and 7-methylxanthine, never reported in wastewater before. All these compounds were found widely at the μg/L level. Mass loads, calculated by multiplying concentrations by the wastewater daily flow rate and normalized to the population served by each plant, were used to compare the profiles from different cities. Some regional differences were observed in the mass loads, especially for nicotine metabolites, which were significantly higher in the south than in the center and north of Italy, reflecting smoking prevalences from population surveys. There were no significant weekly trends, although the mean mass loads of caffeine and its metabolites were slightly lower during the weekend. Most caffeine and nicotine metabolites fulfilled the requirements for an ideal biomarker for the assessment of population size, i.e. being easily detectable in wastewater, stable in sewage and during sampling, and reflecting human metabolism. Nicotine metabolites were tested as quantitative biomarkers to estimate population size and the results agreed well with census data. Caffeine and its metabolites were confirmed as good qualitative biomarkers, but additional information is needed on the caffeine metabolism in relation to the multiple sources of its main metabolites. This exploratory study opens the way to the routine use of nicotine metabolites for estimating population size and dynamics. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed

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

2013-07-01

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

A HILIC-UHPLC-MS/MS untargeted urinary metabonomics combined with quantitative analysis of five polar biomarkers on osteoporosis rats after oral administration of Gushudan.

PubMed

Wu, Xiao; Huang, Yue; Sun, Jinghan; Wen, Yongqing; Qin, Feng; Zhao, Longshan; Xiong, Zhili

2018-01-01

A HILIC-UHPLC-MS/MS untargeted urinary metabonomic method combined with quantitative analysis of five potential polar biomarkers in rat urine was developed and validated, to further understand the anti-osteoporosis effect of Gushudan(GSD) and its mechanism on prednisolone-induced osteoporosis(OP) rats in this study. The metabolites were separated and identified on Waters BEH HILIC (2.1mm×100mm, 1.7μm) column using the Waters ACQUITY™ ultra performance liquid chromatography system (Waters Corporation, Milford, USA) coupled with a Micromass Quattro Micro™ API mass spectrometer (Waters Corp, Milford, MA, USA). Principal component analysis (PCA) was used to identify potential biomarkers. Primary potential polar biomarkers including creatinine, taurine, betaine, hypoxanthine and cytosine, which were related to energy metabolism, lipid metabolism and amino acid metabolism, were found in the untargeted metabonomic research. Moreover, these targeted biomarkers were further separated and quantified in multiple-reaction monitoring (MRM) with positive ionization mode, using tinidazole as internal standard (I.S.). Good linearities (r>0.99) were obtained for all the analytes with the low limit of quantification from 1.00 to 12.8μg/mL. The relative standard deviation (RSD) of the intra-day and inter-day precisions were within 15.0% and the accuracy ranged from -14.3% to 13.5%. The recovery was more than 85.0%. And the validated method was successfully applied to investigate the urine samples of the control group, prednisolone-induced osteoporosis model group and Gushudan-treatment group in rats. Compared to the control group, the level of creatinine, taurine, betaine, hypoxanthine and cytosine in the model group revealed a significant decrease trend (p<0.05), while the Gushudan-treatment group showed no statistically differences by an independent sample t-test. This paper provided a better understanding of the therapeutic effect and mechanism of GSD on prednisolone-induced osteoporosis rats. Copyright © 2017. Published by Elsevier B.V.

Quantitative Proteomic Analysis of Differentially Expressed Protein Profiles Involved in Pancreatic Ductal Adenocarcinoma

PubMed Central

Kuo, Kung-Kai; Kuo, Chao-Jen; Chiu, Chiang-Yen; Liang, Shih-Shin; Huang, Chun-Hao; Chi, Shu-Wen; Tsai, Kun-Bow; Chen, Chiao-Yun; Hsi, Edward; Cheng, Kuang-Hung; Chiou, Shyh-Horng

2016-01-01

Objectives The aim of this study was to identify differentially expressed proteins among various stages of pancreatic ductal adenocarcinoma (PDAC) by shotgun proteomics using nano-liquid chromatography coupled tandem mass spectrometry and stable isotope dimethyl labeling. Methods Differentially expressed proteins were identified and compared based on the mass spectral differences of their isotope-labeled peptide fragments generated from protease digestion. Results Our quantitative proteomic analysis of the differentially expressed proteins with stable isotope (deuterium/hydrogen ratio, ≥2) identified a total of 353 proteins, with at least 5 protein biomarker proteins that were significantly differentially expressed between cancer and normal mice by at least a 2-fold alteration. These 5 protein biomarker candidates include α-enolase, α-catenin, 14-3-3 β, VDAC1, and calmodulin with high confidence levels. The expression levels were also found to be in agreement with those examined by Western blot and histochemical staining. Conclusions The systematic decrease or increase of these identified marker proteins may potentially reflect the morphological aberrations and diseased stages of pancreas carcinoma throughout progressive developments leading to PDAC. The results would form a firm foundation for future work concerning validation and clinical translation of some identified biomarkers into targeted diagnosis and therapy for various stages of PDAC. PMID:26262590

Metabolomics Coupled with Multivariate Data and Pathway Analysis on Potential Biomarkers in Gastric Ulcer and Intervention Effects of Corydalis yanhusuo Alkaloid

PubMed Central

Shuai, Wang; Yongrui, Bao; Shanshan, Guan; Bo, Liu; Lu, Chen; Lei, Wang; Xiaorong, Ran

2014-01-01

Metabolomics, the systematic analysis of potential metabolites in a biological specimen, has been increasingly applied to discovering biomarkers, identifying perturbed pathways, measuring therapeutic targets, and discovering new drugs. By analyzing and verifying the significant difference in metabolic profiles and changes of metabolite biomarkers, metabolomics enables us to better understand substance metabolic pathways which can clarify the mechanism of Traditional Chinese Medicines (TCM). Corydalis yanhusuo alkaloid (CA) is a major component of Qizhiweitong (QZWT) prescription which has been used for treating gastric ulcer for centuries and its mechanism remains unclear completely. Metabolite profiling was performed by high-performance liquid chromatography combined with time-of-flight mass spectrometry (HPLC/ESI-TOF-MS) and in conjunction with multivariate data analysis and pathway analysis. The statistic software Mass Profiller Prossional (MPP) and statistic method including ANOVA and principal component analysis (PCA) were used for discovering novel potential biomarkers to clarify mechanism of CA in treating acid injected rats with gastric ulcer. The changes in metabolic profiling were restored to their base-line values after CA treatment according to the PCA score plots. Ten different potential biomarkers and seven key metabolic pathways contributing to the treatment of gastric ulcer were discovered and identified. Among the pathways, sphingophospholipid metabolism and fatty acid metabolism related network were acutely perturbed. Quantitative real time polymerase chain reaction (RT-PCR) analysis were performed to evaluate the expression of genes related to the two pathways for verifying the above results. The results show that changed biomarkers and pathways may provide evidence to insight into drug action mechanisms and enable us to increase research productivity toward metabolomics drug discovery. PMID:24454691

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 of glycans can also be achieved, which might provide more potential information for PC biomarker discovery. Copyright © 2018 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

Serial analysis of gene expression identifies connective tissue growth factor expression as a prognostic biomarker in gallbladder cancer.

PubMed

Alvarez, Hector; Corvalan, Alejandro; Roa, Juan C; Argani, Pedram; Murillo, Francisco; Edwards, Jennifer; Beaty, Robert; Feldmann, Georg; Hong, Seung-Mo; Mullendore, Michael; Roa, Ivan; Ibañez, Luis; Pimentel, Fernando; Diaz, Alfonso; Riggins, Gregory J; Maitra, Anirban

2008-05-01

Gallbladder cancer (GBC) is an uncommon neoplasm in the United States, but one with high mortality rates. This malignancy remains largely understudied at the molecular level such that few targeted therapies or predictive biomarkers exist. We built the first series of serial analysis of gene expression (SAGE) libraries from GBC and nonneoplastic gallbladder mucosa, composed of 21-bp long-SAGE tags. SAGE libraries were generated from three stage-matched GBC patients (representing Hispanic/Latino, Native American, and Caucasian ethnicities, respectively) and one histologically alithiasic gallbladder. Real-time quantitative PCR was done on microdissected epithelium from five matched GBC and corresponding nonneoplastic gallbladder mucosa. Immunohistochemical analysis was done on a panel of 182 archival GBC in high-throughput tissue microarray format. SAGE tags corresponding to connective tissue growth factor (CTGF) transcripts were identified as differentially overexpressed in all pairwise comparisons of GBC (P < 0.001). Real-time quantitative PCR confirmed significant overexpression of CTGF transcripts in microdissected primary GBC (P < 0.05), but not in metastatic GBC, compared with nonneoplastic gallbladder epithelium. By immunohistochemistry, 66 of 182 (36%) GBC had high CTGF antigen labeling, which was significantly associated with better survival on univariate analysis (P = 0.0069, log-rank test). An unbiased analysis of the GBC transcriptome by SAGE has identified CTGF expression as a predictive biomarker of favorable prognosis in this malignancy. The SAGE libraries from GBC and nonneoplastic gallbladder mucosa are publicly available at the Cancer Genome Anatomy Project web site and should facilitate much needed research into this lethal neoplasm.

Design and analysis of quantitative differential proteomics investigations using LC-MS technology.

PubMed

Bukhman, Yury V; Dharsee, Moyez; Ewing, Rob; Chu, Peter; Topaloglou, Thodoros; Le Bihan, Thierry; Goh, Theo; Duewel, Henry; Stewart, Ian I; Wisniewski, Jacek R; Ng, Nancy F

2008-02-01

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics is becoming an increasingly important tool in characterizing the abundance of proteins in biological samples of various types and across conditions. Effects of disease or drug treatments on protein abundance are of particular interest for the characterization of biological processes and the identification of biomarkers. Although state-of-the-art instrumentation is available to make high-quality measurements and commercially available software is available to process the data, the complexity of the technology and data presents challenges for bioinformaticians and statisticians. Here, we describe a pipeline for the analysis of quantitative LC-MS data. Key components of this pipeline include experimental design (sample pooling, blocking, and randomization) as well as deconvolution and alignment of mass chromatograms to generate a matrix of molecular abundance profiles. An important challenge in LC-MS-based quantitation is to be able to accurately identify and assign abundance measurements to members of protein families. To address this issue, we implement a novel statistical method for inferring the relative abundance of related members of protein families from tryptic peptide intensities. This pipeline has been used to analyze quantitative LC-MS data from multiple biomarker discovery projects. We illustrate our pipeline here with examples from two of these studies, and show that the pipeline constitutes a complete workable framework for LC-MS-based differential quantitation. Supplementary material is available at http://iec01.mie.utoronto.ca/~thodoros/Bukhman/.

Serum proteome profiling in canine idiopathic dilated cardiomyopathy using TMT-based quantitative proteomics approach.

PubMed

Bilić, Petra; Guillemin, Nicolas; Kovačević, Alan; Beer Ljubić, Blanka; Jović, Ines; Galan, Asier; Eckersall, Peter David; Burchmore, Richard; Mrljak, Vladimir

2018-05-15

Idiopathic dilated cardiomyopathy (iDCM) is a primary myocardial disorder with an unknown aetiology, characterized by reduced contractility and ventricular dilation of the left or both ventricles. Naturally occurring canine iDCM was used herein to identify serum proteomic signature of the disease compared to the healthy state, providing an insight into underlying mechanisms and revealing proteins with biomarker potential. To achieve this, we used high-throughput label-based quantitative LC-MS/MS proteomics approach and bioinformatics analysis of the in silico inferred interactome protein network created from the initial list of differential proteins. To complement the proteomic analysis, serum biochemical parameters and levels of know biomarkers of cardiac function were measured. Several proteins with biomarker potential were identified, such as inter-alpha-trypsin inhibitor heavy chain H4, microfibril-associated glycoprotein 4 and apolipoprotein A-IV, which were validated using an independent method (Western blotting) and showed high specificity and sensitivity according to the receiver operating characteristic curve analysis. Bioinformatics analysis revealed involvement of different pathways in iDCM, such as complement cascade activation, lipoprotein particles dynamics, elastic fibre formation, GPCR signalling and respiratory electron transport chain. Idiopathic dilated cardiomyopathy is a severe primary myocardial disease of unknown cause, affecting both humans and dogs. This study is a contribution to the canine heart disease research by means of proteomic and bioinformatic state of the art analyses, following similar approach in human iDCM research. Importantly, we used serum as non-invasive and easily accessible biological source of information and contributed to the scarce data on biofluid proteome research on this topic. Bioinformatics analysis revealed biological pathways modulated in canine iDCM with potential of further targeted research. Also, several proteins with biomarker potential have been identified and successfully validated. Copyright © 2018 Elsevier B.V. All rights reserved.

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

PubMed

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

2007-09-01

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

Comparison of Pancreas Juice Proteins from Cancer Versus Pancreatitis Using Quantitative Proteomic Analysis

PubMed Central

Chen, Ru; Pan, Sheng; Cooke, Kelly; Moyes, Kara White; Bronner, Mary P.; Goodlett, David R.; Aebersold, Ruedi; Brentnall, Teresa A.

2008-01-01

Objectives Pancreatitis is an inflammatory condition of the pancreas. However, it often shares many molecular features with pancreatic cancer. Biomarkers present in pancreatic cancer frequently occur in the setting of pancreatitis. The efforts to develop diagnostic biomarkers for pancreatic cancer have thus been complicated by the false-positive involvement of pancreatitis. Methods In an attempt to develop protein biomarkers for pancreatic cancer, we previously use quantitative proteomics to identify and quantify the proteins from pancreatic cancer juice. Pancreatic juice is a rich source of proteins that are shed by the pancreatic ductal cells. In this study, we used a similar approach to identify and quantify proteins from pancreatitis juice. Results In total, 72 proteins were identified and quantified in the comparison of pancreatic juice from pancreatitis patients versus pooled normal control juice. Nineteen of the juice proteins were overexpressed, and 8 were underexpressed in pancreatitis juice by at least 2-fold compared with normal pancreatic juice. Of these 27 differentially expressed proteins in pancreatitis, 9 proteins were also differentially expressed in the pancreatic juice from pancreatic cancer patient. Conclusions Identification of these differentially expressed proteins from pancreatitis juice provides useful information for future study of specific pancreatitis-associated proteins and to eliminate potential false-positive biomarkers for pancreatic cancer. PMID:17198186

Comparison of pancreas juice proteins from cancer versus pancreatitis using quantitative proteomic analysis.

PubMed

Chen, Ru; Pan, Sheng; Cooke, Kelly; Moyes, Kara White; Bronner, Mary P; Goodlett, David R; Aebersold, Ruedi; Brentnall, Teresa A

2007-01-01

Pancreatitis is an inflammatory condition of the pancreas. However, it often shares many molecular features with pancreatic cancer. Biomarkers present in pancreatic cancer frequently occur in the setting of pancreatitis. The efforts to develop diagnostic biomarkers for pancreatic cancer have thus been complicated by the false-positive involvement of pancreatitis. In an attempt to develop protein biomarkers for pancreatic cancer, we previously use quantitative proteomics to identify and quantify the proteins from pancreatic cancer juice. Pancreatic juice is a rich source of proteins that are shed by the pancreatic ductal cells. In this study, we used a similar approach to identify and quantify proteins from pancreatitis juice. In total, 72 proteins were identified and quantified in the comparison of pancreatic juice from pancreatitis patients versus pooled normal control juice. Nineteen of the juice proteins were overexpressed, and 8 were underexpressed in pancreatitis juice by at least 2-fold compared with normal pancreatic juice. Of these 27 differentially expressed proteins in pancreatitis, 9 proteins were also differentially expressed in the pancreatic juice from pancreatic cancer patient. Identification of these differentially expressed proteins from pancreatitis juice provides useful information for future study of specific pancreatitis-associated proteins and to eliminate potential false-positive biomarkers for pancreatic cancer.

Identification of Tengfu Jiangya Tablet Target Biomarkers with Quantitative Proteomic Technique

PubMed Central

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

2017-01-01

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

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.

Quantitative Image Informatics for Cancer Research (QIICR) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Imaging has enormous untapped potential to improve cancer research through software to extract and process morphometric and functional biomarkers. In the era of non-cytotoxic treatment agents, multi- modality image-guided ablative therapies and rapidly evolving computational resources, quantitative imaging software can be transformative in enabling minimally invasive, objective and reproducible evaluation of cancer treatment response. Post-processing algorithms are integral to high-throughput analysis and fine- grained differentiation of multiple molecular targets.

Quantitative proteomic analysis for high-throughput screening of differential glycoproteins in hepatocellular carcinoma serum

PubMed Central

Gao, Hua-Jun; Chen, Ya-Jing; Zuo, Duo; Xiao, Ming-Ming; Li, Ying; Guo, Hua; Zhang, Ning; Chen, Rui-Bing

2015-01-01

Objective Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths. Novel serum biomarkers are required to increase the sensitivity and specificity of serum screening for early HCC diagnosis. This study employed a quantitative proteomic strategy to analyze the differential expression of serum glycoproteins between HCC and normal control serum samples. Methods Lectin affinity chromatography (LAC) was used to enrich glycoproteins from the serum samples. Quantitative mass spectrometric analysis combined with stable isotope dimethyl labeling and 2D liquid chromatography (LC) separations were performed to examine the differential levels of the detected proteins between HCC and control serum samples. Western blot was used to analyze the differential expression levels of the three serum proteins. Results A total of 2,280 protein groups were identified in the serum samples from HCC patients by using the 2D LC-MS/MS method. Up to 36 proteins were up-regulated in the HCC serum, whereas 19 proteins were down-regulated. Three differential glycoproteins, namely, fibrinogen gamma chain (FGG), FOS-like antigen 2 (FOSL2), and α-1,6-mannosylglycoprotein 6-β-N-acetylglucosaminyltransferase B (MGAT5B) were validated by Western blot. All these three proteins were up-regulated in the HCC serum samples. Conclusion A quantitative glycoproteomic method was established and proven useful to determine potential novel biomarkers for HCC. PMID:26487969

Review of quantitative phase-digital holographic microscopy: promising novel imaging technique to resolve neuronal network activity and identify cellular biomarkers of psychiatric disorders

PubMed Central

Marquet, Pierre; Depeursinge, Christian; Magistretti, Pierre J.

2014-01-01

Abstract. Quantitative phase microscopy (QPM) has recently emerged as a new powerful quantitative imaging technique well suited to noninvasively explore a transparent specimen with a nanometric axial sensitivity. In this review, we expose the recent developments of quantitative phase-digital holographic microscopy (QP-DHM). Quantitative phase-digital holographic microscopy (QP-DHM) represents an important and efficient quantitative phase method to explore cell structure and dynamics. In a second part, the most relevant QPM applications in the field of cell biology are summarized. A particular emphasis is placed on the original biological information, which can be derived from the quantitative phase signal. In a third part, recent applications obtained, with QP-DHM in the field of cellular neuroscience, namely the possibility to optically resolve neuronal network activity and spine dynamics, are presented. Furthermore, potential applications of QPM related to psychiatry through the identification of new and original cell biomarkers that, when combined with a range of other biomarkers, could significantly contribute to the determination of high risk developmental trajectories for psychiatric disorders, are discussed. PMID:26157976

Review of quantitative phase-digital holographic microscopy: promising novel imaging technique to resolve neuronal network activity and identify cellular biomarkers of psychiatric disorders.

PubMed

Marquet, Pierre; Depeursinge, Christian; Magistretti, Pierre J

2014-10-01

Quantitative phase microscopy (QPM) has recently emerged as a new powerful quantitative imaging technique well suited to noninvasively explore a transparent specimen with a nanometric axial sensitivity. In this review, we expose the recent developments of quantitative phase-digital holographic microscopy (QP-DHM). Quantitative phase-digital holographic microscopy (QP-DHM) represents an important and efficient quantitative phase method to explore cell structure and dynamics. In a second part, the most relevant QPM applications in the field of cell biology are summarized. A particular emphasis is placed on the original biological information, which can be derived from the quantitative phase signal. In a third part, recent applications obtained, with QP-DHM in the field of cellular neuroscience, namely the possibility to optically resolve neuronal network activity and spine dynamics, are presented. Furthermore, potential applications of QPM related to psychiatry through the identification of new and original cell biomarkers that, when combined with a range of other biomarkers, could significantly contribute to the determination of high risk developmental trajectories for psychiatric disorders, are discussed.

European Organisation for Research and Treatment of Cancer (EORTC) Pathobiology Group standard operating procedure for the preparation of human tumour tissue extracts suited for the quantitative analysis of tissue-associated biomarkers.

PubMed

Schmitt, Manfred; Mengele, Karin; Schueren, Elisabeth; Sweep, Fred C G J; Foekens, John A; Brünner, Nils; Laabs, Juliane; Malik, Abha; Harbeck, Nadia

2007-03-01

With the new concept of 'individualized treatment and targeted therapies', tumour tissue-associated biomarkers have been given a new role in selection of cancer patients for treatment and in cancer patient management. Tumour biomarkers can give support to cancer patient stratification and risk assessment, treatment response identification, or to identifying those patients who are expected to respond to certain anticancer drugs. As the field of tumour-associated biomarkers has expanded rapidly over the last years, it has become increasingly apparent that a strong need exists to establish guidelines on how to easily disintegrate the tumour tissue for assessment of the presence of tumour tissue-associated biomarkers. Several mechanical tissue (cell) disruption techniques exist, ranging from bead mill homogenisation and freeze-fracturing through to blade or pestle-type homogenisation, to grinding and ultrasonics. Still, only a few directives have been given on how fresh-frozen tumour tissues should be processed for the extraction and determination of tumour biomarkers. The PathoBiology Group of the European Organisation for Research and Treatment of Cancer therefore has devised a standard operating procedure for the standardised preparation of human tumour tissue extracts which is designed for the quantitative analysis of tumour tissue-associated biomarkers. The easy to follow technical steps involved require 50-300 mg of deep-frozen cancer tissue placed into small size (1.2 ml) cryogenic tubes. These are placed into the shaking flask of a Mikro-Dismembrator S machine (bead mill) to pulverise the tumour tissue in the capped tubes in the deep-frozen state by use of a stainless steel ball, all within 30 s of exposure. RNA is isolated from the pulverised tissue following standard procedures. Proteins are extracted from the still frozen pulverised tissue by addition of Tris-buffered saline to obtain the cytosol fraction of the tumour or by the Tris buffer supplemented with the non-ionic detergent Triton X-100, and, after high-speed centrifugation, are found in the tissue supernatant. The resulting tissue cell debris sediment is a rich source of genomic DNA.

Integration of co-localized glandular morphometry and protein biomarker expression in immunofluorescent images for prostate cancer prognosis

NASA Astrophysics Data System (ADS)

Scott, Richard; Khan, Faisal M.; Zeineh, Jack; Donovan, Michael; Fernandez, Gerardo

2015-03-01

Immunofluorescent (IF) image analysis of tissue pathology has proven to be extremely valuable and robust in developing prognostic assessments of disease, particularly in prostate cancer. There have been significant advances in the literature in quantitative biomarker expression as well as characterization of glandular architectures in discrete gland rings. However, while biomarker and glandular morphometric features have been combined as separate predictors in multivariate models, there is a lack of integrative features for biomarkers co-localized within specific morphological sub-types; for example the evaluation of androgen receptor (AR) expression within Gleason 3 glands only. In this work we propose a novel framework employing multiple techniques to generate integrated metrics of morphology and biomarker expression. We demonstrate the utility of the approaches in predicting clinical disease progression in images from 326 prostate biopsies and 373 prostatectomies. Our proposed integrative approaches yield significant improvements over existing IF image feature metrics. This work presents some of the first algorithms for generating innovative characteristics in tissue diagnostics that integrate co-localized morphometry and protein biomarker expression.

A matrix approach to guide IHC-based tissue biomarker development in oncology drug discovery.

PubMed

Smith, Neil R; Womack, Christopher

2014-01-01

Immunohistochemistry (IHC) is a core platform for the analysis of tissue samples, and there is an increasing demand for reliable and quantitative IHC-based tissue biomarkers in oncology clinical research and development (R&D) environments. Biomarker assay and drug development proceed in parallel. Furthermore, biomarker assay requirements change with each phase of drug development. We have therefore developed a matrix tool to enable researchers to evaluate whether a particular IHC biomarker assay is fit for purpose. Experience gained from the development of 130 IHC biomarkers, supporting a large number of oncology drug projects, was used to formulate a practical approach to IHC assay development. The resultant matrix grid and accompanying work flow incorporates 16 core decision points that link antibody and assay specificity and sensitivity, and assay performance in preclinical and clinical samples, with stages of drug development. The matrix provides a means to ensure that relevant information on an IHC assay in development is recorded and communicated consistently and that minimum assay validation requirements are met. Copyright © 2013 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

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

PubMed

Parker, Carol E; Borchers, Christoph H

2014-06-01

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

Fundamentals of quantitative dynamic contrast-enhanced MR imaging.

PubMed

Paldino, Michael J; Barboriak, Daniel P

2009-05-01

Quantitative analysis of dynamic contrast-enhanced MR imaging (DCE-MR imaging) has the power to provide information regarding physiologic characteristics of the microvasculature and is, therefore, of great potential value to the practice of oncology. In particular, these techniques could have a significant impact on the development of novel anticancer therapies as a promising biomarker of drug activity. Standardization of DCE-MR imaging acquisition and analysis to provide more reproducible measures of tumor vessel physiology is of crucial importance to realize this potential. The purpose of this article is to review the pathophysiologic basis and technical aspects of DCE-MR imaging techniques.

Quantification of proteins in urine samples using targeted mass spectrometry methods.

PubMed

Khristenko, Nina; Domon, Bruno

2015-01-01

Numerous clinical proteomics studies are focused on the development of biomarkers to improve either diagnostics for early disease detection or the monitoring of the response to the treatment. Although, a wealth of biomarker candidates are available, their evaluation and validation in a true clinical setup remains challenging. In biomarkers evaluation studies, a panel of proteins of interest are systematically analyzed in a large cohort of samples. However, in spite of the latest progresses in mass spectrometry, the consistent detection of pertinent proteins in high complex biological samples is still a challenging task. Thus, targeted LC-MS/MS methods are better suited for the systematic analysis of biomarkers rather than shotgun approaches. This chapter describes the workflow used to perform targeted quantitative analyses of proteins in urinary samples. The peptides, as surrogates of the protein of interest, are commonly measured using a triple quadrupole mass spectrometers operated in selected reaction monitoring (SRM) mode. More recently, the advances in targeted LC-MS/MS analysis based on parallel reaction monitoring (PRM) performed on a quadrupole-orbitrap instrument have allowed to increase the specificity and selectivity of the measurements.

Quantitative measurement of a candidate serum biomarker peptide derived from α2-HS-glycoprotein, and a preliminary trial of multidimensional peptide analysis in females with pregnancy-induced hypertension.

PubMed

Hamamura, Kensuke; Yanagida, Mitsuaki; Ishikawa, Hitoshi; Banzai, Michio; Yoshitake, Hiroshi; Nonaka, Daisuke; Tanaka, Kenji; Sakuraba, Mayumi; Miyakuni, Yasuka; Takamori, Kenji; Nojima, Michio; Yoshida, Koyo; Fujiwara, Hiroshi; Takeda, Satoru; Araki, Yoshihiko

2018-03-01

Purpose We previously attempted to develop quantitative enzyme-linked immunosorbent assay (ELISA) systems for the PDA039/044/071 peptides, potential serum disease biomarkers (DBMs) of pregnancy-induced hypertension (PIH), primarily identified by a peptidomic approach (BLOTCHIP®-mass spectrometry (MS)). However, our methodology did not extend to PDA071 (cysteinyl α2-HS-glycoprotein 341-367 ), due to difficulty to produce a specific antibody against the peptide. The aim of the present study was to establish an alternative PDA071 quantitation system using liquid chromatography-multiple reaction monitoring (LC-MRM)/MS, to explore the potential utility of PDA071 as a DBM for PIH. Methods We tested heat/acid denaturation methods in efforts to purify serum PDA071 and developed an LC-MRM/MS method allowing for specific quantitation thereof. We measured serum PDA071 concentrations, and these results were validated including by three-dimensional (3D) plotting against PDA039 (kininogen-1 439-456 )/044 (kininogen-1 438-456 ) concentrations, followed by discriminant analysis. Results PDA071 was successfully extracted from serum using a heat denaturation method. Optimum conditions for quantitation via LC-MRM/MS were developed; the assayed serum PDA071 correlated well with the BLOTCHIP® assay values. Although the PDA071 alone did not significantly differ between patients and controls, 3D plotting of PDA039/044/071 peptide concentrations and construction of a Jackknife classification matrix were satisfactory in terms of PIH diagnostic precision. Conclusions Combination analysis using both PDA071 and PDA039/044 concentrations allowed PIH diagnostic accuracy to be attained, and our method will be valuable in future pathophysiological studies of hypertensive disorders of pregnancy.

Statistical issues in the comparison of quantitative imaging biomarker algorithms using pulmonary nodule volume as an example.

PubMed

Obuchowski, Nancy A; Barnhart, Huiman X; Buckler, Andrew J; Pennello, Gene; Wang, Xiao-Feng; Kalpathy-Cramer, Jayashree; Kim, Hyun J Grace; Reeves, Anthony P

2015-02-01

Quantitative imaging biomarkers are being used increasingly in medicine to diagnose and monitor patients' disease. The computer algorithms that measure quantitative imaging biomarkers have different technical performance characteristics. In this paper we illustrate the appropriate statistical methods for assessing and comparing the bias, precision, and agreement of computer algorithms. We use data from three studies of pulmonary nodules. The first study is a small phantom study used to illustrate metrics for assessing repeatability. The second study is a large phantom study allowing assessment of four algorithms' bias and reproducibility for measuring tumor volume and the change in tumor volume. The third study is a small clinical study of patients whose tumors were measured on two occasions. This study allows a direct assessment of six algorithms' performance for measuring tumor change. With these three examples we compare and contrast study designs and performance metrics, and we illustrate the advantages and limitations of various common statistical methods for quantitative imaging biomarker studies. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Inferring diagnosis and trajectory of wet age-related macular degeneration from OCT imagery of retina

NASA Astrophysics Data System (ADS)

Irvine, John M.; Ghadar, Nastaran; Duncan, Steve; Floyd, David; O'Dowd, David; Lin, Kristie; Chang, Tom

2017-03-01

Quantitative biomarkers for assessing the presence, severity, and progression of age-related macular degeneration (AMD) would benefit research, diagnosis, and treatment. This paper explores development of quantitative biomarkers derived from OCT imagery of the retina. OCT images for approximately 75 patients with Wet AMD, Dry AMD, and no AMD (healthy eyes) were analyzed to identify image features indicative of the patients' conditions. OCT image features provide a statistical characterization of the retina. Healthy eyes exhibit a layered structure, whereas chaotic patterns indicate the deterioration associated with AMD. Our approach uses wavelet and Frangi filtering, combined with statistical features that do not rely on image segmentation, to assess patient conditions. Classification analysis indicates clear separability of Wet AMD from other conditions, including Dry AMD and healthy retinas. The probability of correct classification of was 95.7%, as determined from cross validation. Similar classification analysis predicts the response of Wet AMD patients to treatment, as measured by the Best Corrected Visual Acuity (BCVA). A statistical model predicts BCVA from the imagery features with R2 = 0.846. Initial analysis of OCT imagery indicates that imagery-derived features can provide useful biomarkers for characterization and quantification of AMD: Accurate assessment of Wet AMD compared to other conditions; image-based prediction of outcome for Wet AMD treatment; and features derived from the OCT imagery accurately predict BCVA; unlike many methods in the literature, our techniques do not rely on segmentation of the OCT image. Next steps include larger scale testing and validation.

The Application of SILAC Mouse in Human Body Fluid Proteomics Analysis Reveals Protein Patterns Associated with IgA Nephropathy.

PubMed

Zhao, Shilin; Li, Rongxia; Cai, Xiaofan; Chen, Wanjia; Li, Qingrun; Xing, Tao; Zhu, Wenjie; Chen, Y Eugene; Zeng, Rong; Deng, Yueyi

2013-01-01

Body fluid proteome is the most informative proteome from a medical viewpoint. But the lack of accurate quantitation method for complicated body fluid limited its application in disease research and biomarker discovery. To address this problem, we introduced a novel strategy, in which SILAC-labeled mouse serum was used as internal standard for human serum and urine proteome analysis. The SILAC-labeled mouse serum was mixed with human serum and urine, and multidimensional separation coupled with tandem mass spectrometry (IEF-LC-MS/MS) analysis was performed. The shared peptides between two species were quantified by their SILAC pairs, and the human-only peptides were quantified by mouse peptides with coelution. The comparison for the results from two replicate experiments indicated the high repeatability of our strategy. Then the urine from Immunoglobulin A nephropathy patients treated and untreated was compared by this quantitation strategy. Fifty-three peptides were found to be significantly changed between two groups, including both known diagnostic markers for IgAN and novel candidates, such as Complement C3, Albumin, VDBP, ApoA,1 and IGFBP7. In conclusion, we have developed a practical and accurate quantitation strategy for comparison of complicated human body fluid proteome. The results from such strategy could provide potential disease-related biomarkers for evaluation of treatment.

Epitope mapping and targeted quantitation of the cardiac biomarker troponin by SID-MRM mass spectrometry.

PubMed

Zhao, Cheng; Trudeau, Beth; Xie, Helen; Prostko, John; Fishpaugh, Jeffrey; Ramsay, Carol

2014-06-01

The absolute quantitation of the targeted protein using MS provides a promising method to evaluate/verify biomarkers used in clinical diagnostics. In this study, a cardiac biomarker, troponin I (TnI), was used as a model protein for method development. The epitope peptide of TnI was characterized by epitope excision followed with LC/MS/MS method and acted as the surrogate peptide for the targeted protein quantitation. The MRM-based MS assay using a stable internal standard that improved the selectivity, specificity, and sensitivity of the protein quantitation. Also, plasma albumin depletion and affinity enrichment of TnI by anti-TnI mAb-coated microparticles reduced the sample complexity, enhanced the dynamic range, and further improved the detecting sensitivity of the targeted protein in the biological matrix. Therefore, quantitation of TnI, a low abundant protein in human plasma, has demonstrated the applicability of the targeted protein quantitation strategy through its epitope peptide determined by epitope mapping method. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Advances in multiplexed MRM-based protein biomarker quantitation toward clinical utility.

PubMed

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

2014-05-01

Accurate and rapid protein quantitation is essential for screening biomarkers for disease stratification and monitoring, and to validate the hundreds of putative markers in human biofluids, including blood plasma. An analytical method that utilizes stable isotope-labeled standard (SIS) peptides and selected/multiple reaction monitoring-mass spectrometry (SRM/MRM-MS) has emerged as a promising technique for determining protein concentrations. This targeted approach has analytical merit, but its true potential (in terms of sensitivity and multiplexing) has yet to be realized. Described herein is a method that extends the multiplexing ability of the MRM method to enable the quantitation 142 high-to-moderate abundance proteins (from 31mg/mL to 44ng/mL) in undepleted and non-enriched human plasma in a single run. The proteins have been reported to be associated to a wide variety of non-communicable diseases (NCDs), from cardiovascular disease (CVD) to diabetes. The concentrations of these proteins in human plasma are inferred from interference-free peptides functioning as molecular surrogates (2 peptides per protein, on average). A revised data analysis strategy, involving the linear regression equation of normal control plasma, has been instituted to enable the facile application to patient samples, as demonstrated in separate nutrigenomics and CVD studies. The exceptional robustness of the LC/MS platform and the quantitative method, as well as its high throughput, makes the assay suitable for application to patient samples for the verification of a condensed or complete protein panel. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge. © 2013.

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

PubMed Central

2013-01-01

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

Integrated preservation and sample clean up procedures for studying water ingestion by recreational swimmers via urinary biomarker determination.

PubMed

Cantú, Ricardo; Shoemaker, Jody A; Kelty, Catherine A; Wymer, Larry J; Behymer, Thomas D; Dufour, Alfred P; Magnuson, Matthew L

2017-08-22

The use of cyanuric acid as a biomarker for ingestion of swimming pool water may lead to quantitative knowledge of the volume of water ingested during swimming, contributing to a better understanding of disease resulting from ingestion of environmental contaminants. When swimming pool water containing chlorinated cyanurates is inadvertently ingested, cyanuric acid is excreted quantitatively within 24 h as a urinary biomarker of ingestion. Because the volume of water ingested can be quantitatively estimated by calculation from the concentration of cyanuric acid in 24 h urine samples, a procedure for preservation, cleanup, and analysis of cyanuric acid was developed to meet the logistical demands of large scale studies. From a practical stand point, urine collected from swimmers cannot be analyzed immediately, given requirements of sample collection, shipping, handling, etc. Thus, to maintain quality control to allow confidence in the results, it is necessary to preserve the samples in a manner that ensures as quantitative analysis as possible. The preservation and clean-up of cyanuric acid in urine is complicated because typical approaches often are incompatible with the keto-enol tautomerization of cyanuric acid, interfering with cyanuric acid sample preparation, chromatography, and detection. Therefore, this paper presents a novel integration of sample preservation, clean-up, chromatography, and detection to determine cyanuric acid in 24 h urine samples. Fortification of urine with cyanuric acid (0.3-3.0 mg/L) demonstrated accuracy (86-93% recovery) and high reproducibility (RSD < 7%). Holding time studies in unpreserved urine suggested sufficient cyanuric acid stability for sample collection procedures, while longer holding times suggested instability of the unpreserved urine. Preserved urine exhibited a loss of around 0.5% after 22 days at refrigerated storage conditions of 4 °C. Published by Elsevier B.V.

Quantitative fluorescence in intracranial tumor: implications for ALA-induced PpIX as an intraoperative biomarker

PubMed Central

Valdés, Pablo A.; Leblond, Frederic; Kim, Anthony; Harris, Brent T.; Wilson, Brian C.; Fan, Xiaoyao; Tosteson, Tor D.; Hartov, Alex; Ji, Songbai; Erkmen, Kadir; Simmons, Nathan E.; Paulsen, Keith D.; Roberts, David W.

2011-01-01

Object Accurate discrimination between tumor and normal tissue is crucial for optimal tumor resection. Qualitative fluorescence of protoporphyrin IX (PpIX), synthesized endogenously following δ-aminolevulinic acid (ALA) administration, has been used for this purpose in high-grade glioma (HGG). The authors show that diagnostically significant but visually imperceptible concentrations of PpIX can be quantitatively measured in vivo and used to discriminate normal from neoplastic brain tissue across a range of tumor histologies. Methods The authors studied 14 patients with diagnoses of low-grade glioma (LGG), HGG, meningioma, and metastasis under an institutional review board–approved protocol for fluorescence-guided resection. The primary aim of the study was to compare the diagnostic capabilities of a highly sensitive, spectrally resolved quantitative fluorescence approach to conventional fluorescence imaging for detection of neoplastic tissue in vivo. Results A significant difference in the quantitative measurements of PpIX concentration occurred in all tumor groups compared with normal brain tissue. Receiver operating characteristic (ROC) curve analysis of PpIX concentration as a diagnostic variable for detection of neoplastic tissue yielded a classification efficiency of 87% (AUC = 0.95, specificity = 92%, sensitivity = 84%) compared with 66% (AUC = 0.73, specificity = 100%, sensitivity = 47%) for conventional fluorescence imaging (p < 0.0001). More than 81% (57 of 70) of the quantitative fluorescence measurements that were below the threshold of the surgeon's visual perception were classified correctly in an analysis of all tumors. Conclusions These findings are clinically profound because they demonstrate that ALA-induced PpIX is a targeting biomarker for a variety of intracranial tumors beyond HGGs. This study is the first to measure quantitative ALA-induced PpIX concentrations in vivo, and the results have broad implications for guidance during resection of intracranial tumors. PMID:21438658

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

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

PubMed

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

2017-03-01

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

Differential Mobility Spectrometry-Mass Spectrometry (DMS-MS) in Radiation Biodosimetry: Rapid and High-Throughput Quantitation of Multiple Radiation Biomarkers in Nonhuman Primate Urine.

PubMed

Chen, Zhidan; Coy, Stephen L; Pannkuk, Evan L; Laiakis, Evagelia C; Fornace, Albert J; Vouros, Paul

2018-05-07

High-throughput methods to assess radiation exposure are a priority due to concerns that include nuclear power accidents, the spread of nuclear weapon capability, and the risk of terrorist attacks. Metabolomics, the assessment of small molecules in an easily accessible sample, is the most recent method to be applied for the identification of biomarkers of the biological radiation response with a useful dose-response profile. Profiling for biomarker identification is frequently done using an LC-MS platform which has limited throughput due to the time-consuming nature of chromatography. We present here a chromatography-free simplified method for quantitative analysis of seven metabolites in urine with radiation dose-response using urine samples provided from the Pannkuk et al. (2015) study of long-term (7-day) radiation response in nonhuman primates (NHP). The stable isotope dilution (SID) analytical method consists of sample preparation by strong cation exchange-solid phase extraction (SCX-SPE) to remove interferences and concentrate the metabolites of interest, followed by differential mobility spectrometry (DMS) ion filtration to select the ion of interest and reduce chemical background, followed by mass spectrometry (overall SID-SPE-DMS-MS). Since no chromatography is used, calibration curves were prepared rapidly, in under 2 h (including SPE) for six simultaneously analyzed radiation biomarkers. The seventh, creatinine, was measured separately after 2500× dilution. Creatinine plays a dual role, measuring kidney glomerular filtration rate (GFR), and indicating kidney damage at high doses. The current quantitative method using SID-SPE-DMS-MS provides throughput which is 7.5 to 30 times higher than that of LC-MS and provides a path to pre-clinical radiation dose estimation. Graphical Abstract.

Differential Mobility Spectrometry-Mass Spectrometry (DMS-MS) in Radiation Biodosimetry: Rapid and High-Throughput Quantitation of Multiple Radiation Biomarkers in Nonhuman Primate Urine

NASA Astrophysics Data System (ADS)

Chen, Zhidan; Coy, Stephen L.; Pannkuk, Evan L.; Laiakis, Evagelia C.; Fornace, Albert J.; Vouros, Paul

2018-05-01

High-throughput methods to assess radiation exposure are a priority due to concerns that include nuclear power accidents, the spread of nuclear weapon capability, and the risk of terrorist attacks. Metabolomics, the assessment of small molecules in an easily accessible sample, is the most recent method to be applied for the identification of biomarkers of the biological radiation response with a useful dose-response profile. Profiling for biomarker identification is frequently done using an LC-MS platform which has limited throughput due to the time-consuming nature of chromatography. We present here a chromatography-free simplified method for quantitative analysis of seven metabolites in urine with radiation dose-response using urine samples provided from the Pannkuk et al. (2015) study of long-term (7-day) radiation response in nonhuman primates (NHP). The stable isotope dilution (SID) analytical method consists of sample preparation by strong cation exchange-solid phase extraction (SCX-SPE) to remove interferences and concentrate the metabolites of interest, followed by differential mobility spectrometry (DMS) ion filtration to select the ion of interest and reduce chemical background, followed by mass spectrometry (overall SID-SPE-DMS-MS). Since no chromatography is used, calibration curves were prepared rapidly, in under 2 h (including SPE) for six simultaneously analyzed radiation biomarkers. The seventh, creatinine, was measured separately after 2500× dilution. Creatinine plays a dual role, measuring kidney glomerular filtration rate (GFR), and indicating kidney damage at high doses. The current quantitative method using SID-SPE-DMS-MS provides throughput which is 7.5 to 30 times higher than that of LC-MS and provides a path to pre-clinical radiation dose estimation. [Figure not available: see fulltext.

Quantitative, multiplexed workflow for deep analysis of human blood plasma and biomarker discovery by mass spectrometry.

PubMed

Keshishian, Hasmik; Burgess, Michael W; Specht, Harrison; Wallace, Luke; Clauser, Karl R; Gillette, Michael A; Carr, Steven A

2017-08-01

Proteomic characterization of blood plasma is of central importance to clinical proteomics and particularly to biomarker discovery studies. The vast dynamic range and high complexity of the plasma proteome have, however, proven to be serious challenges and have often led to unacceptable tradeoffs between depth of coverage and sample throughput. We present an optimized sample-processing pipeline for analysis of the human plasma proteome that provides greatly increased depth of detection, improved quantitative precision and much higher sample analysis throughput as compared with prior methods. The process includes abundant protein depletion, isobaric labeling at the peptide level for multiplexed relative quantification and ultra-high-performance liquid chromatography coupled to accurate-mass, high-resolution tandem mass spectrometry analysis of peptides fractionated off-line by basic pH reversed-phase (bRP) chromatography. The overall reproducibility of the process, including immunoaffinity depletion, is high, with a process replicate coefficient of variation (CV) of <12%. Using isobaric tags for relative and absolute quantitation (iTRAQ) 4-plex, >4,500 proteins are detected and quantified per patient sample on average, with two or more peptides per protein and starting from as little as 200 μl of plasma. The approach can be multiplexed up to 10-plex using tandem mass tags (TMT) reagents, further increasing throughput, albeit with some decrease in the number of proteins quantified. In addition, we provide a rapid protocol for analysis of nonfractionated depleted plasma samples analyzed in 10-plex. This provides ∼600 quantified proteins for each of the ten samples in ∼5 h of instrument time.

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

PubMed

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

2013-01-01

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

THE FERTILITY BIOMARKER (SP22) IS COMPROMISED IN AN ADDITIVE FASHION BY HALOACIDS: COMPARATIVE QUANTITATION BY IMMUNOASSAY AND 2D-GEL ANALYSIS

EPA Science Inventory

Dibromoacetic acid (DBA) and bromochloroacetic acid (BCA) are prevalent disinfection by-products of drinking water known to produce defects in spermatogenesis and fertility in adult rats. Previous work in our laboratory demonstated a high correlation between fertility of sperm fr...

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

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

PubMed

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

2007-03-01

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

Miniature Time-of-Flight Mass Spectrometer

NASA Technical Reports Server (NTRS)

Potember, Richard S.

1999-01-01

Major advances must occur to protect astronauts from prolonged periods in near-zero gravity and high radiation associated with extended space travel. The dangers of living in space must be thoroughly understood and methods developed to reverse those effects that cannot be avoided. Six of the seven research teams established by the National Space Biomedical Research Institute (NSBRI) are studying biomedical factors for prolonged space travel to deliver effective countermeasures. To develop effective countermeasures, each of these teams require identification of and quantitation of complex pharmacological, hormonal, and growth factor compounds (biomarkers) in humans and in experimental animals to develop an in-depth knowledge of the physiological changes associated with space travel. At present, identification of each biomarker requires a separate protocol. Many of these procedures are complicated and the identification of each biomarker requires a separate protocol and associated laboratory equipment. To carry all of this equipment and chemicals on a spacecraft would require a complex clinical laboratory; and it would occupy much of the astronauts time. What is needed is a small, efficient, broadband medical diagnostic instrument to rapidly identify important biomarkers for human space exploration. The Miniature Time-Of- Flight Mass Spectrometer Project in the Technology Development Team is developing a small, high resolution, time-of-flight mass spectrometer (TOFMS) to quantitatively measure biomarkers for human space exploration. Virtues of the JHU/APL TOFMS technologies reside in the promise for a small (less than one cubic ft), lightweight (less than 5 kg), low-power (less than 50 watts), rugged device that can be used continuously with advanced signal processing diagnostics. To date, the JHU/APL program has demonstrated mass capability from under 100 to beyond 10,000 atomic mass units (amu) in a very small, low power prototype for biological analysis. Further, the electronic nature of the TOFMS output makes it ideal for rapid telemetry to earth for in-depth analysis by ground support teams.

Circulating RNAs as new biomarkers for detecting pancreatic cancer

PubMed Central

Kishikawa, Takahiro; Otsuka, Motoyuki; Ohno, Motoko; Yoshikawa, Takeshi; Takata, Akemi; Koike, Kazuhiko

2015-01-01

Pancreatic cancer remains difficult to treat and has a high mortality rate. It is difficult to diagnose early, mainly due to the lack of screening imaging modalities and specific biomarkers. Consequently, it is important to develop biomarkers that enable the detection of early stage tumors. Emerging evidence is accumulating that tumor cells release substantial amounts of RNA into the bloodstream that strongly resist RNases in the blood and are present at sufficient levels for quantitative analyses. These circulating RNAs are upregulated in the serum and plasma of cancer patients, including those with pancreatic cancer, compared with healthy controls. The majority of RNA biomarker studies have assessed circulating microRNAs (miRs), which are often tissue-specific. There are few reports of the tumor-specific upregulation of other types of small non-coding RNAs (ncRNAs), such as small nucleolar RNAs and Piwi-interacting RNAs. Long ncRNAs (lncRNAs), such as HOTAIR and MALAT1, in the serum/plasma of pancreatic cancer patients have also been reported as diagnostic and prognostic markers. Among tissue-derived RNAs, some miRs show increased expression even in pre-cancerous tissues, and their expression profiles may allow for the discrimination between a chronic inflammatory state and carcinoma. Additionally, some miRs and lncRNAs have been reported with significant alterations in expression according to disease progression, and they may thus represent potential candidate diagnostic or prognostic biomarkers that may be used to evaluate patients once detection methods in peripheral blood are well established. Furthermore, recent innovations in high-throughput sequencing techniques have enabled the discovery of unannotated tumor-associated ncRNAs and tumor-specific alternative splicing as novel and specific biomarkers of cancers. Although much work is required to clarify the release mechanism, origin of tumor-specific circulating RNAs, and selectivity of carrier complexes, and technical advances must also be achieved, such as creating a consensus normalization protocol for quantitative data analysis, circulating RNAs are largely unexplored and might represent novel clinical biomarkers. PMID:26229396

Potential usefulness of a topic model-based categorization of lung cancers as quantitative CT biomarkers for predicting the recurrence risk after curative resection

NASA Astrophysics Data System (ADS)

Kawata, Y.; Niki, N.; Ohmatsu, H.; Satake, M.; Kusumoto, M.; Tsuchida, T.; Aokage, K.; Eguchi, K.; Kaneko, M.; Moriyama, N.

2014-03-01

In this work, we investigate a potential usefulness of a topic model-based categorization of lung cancers as quantitative CT biomarkers for predicting the recurrence risk after curative resection. The elucidation of the subcategorization of a pulmonary nodule type in CT images is an important preliminary step towards developing the nodule managements that are specific to each patient. We categorize lung cancers by analyzing volumetric distributions of CT values within lung cancers via a topic model such as latent Dirichlet allocation. Through applying our scheme to 3D CT images of nonsmall- cell lung cancer (maximum lesion size of 3 cm) , we demonstrate the potential usefulness of the topic model-based categorization of lung cancers as quantitative CT biomarkers.

Effect of intra-pregnancy nonsurgical periodontal therapy on inflammatory biomarkers and adverse pregnancy outcomes: a systematic review with meta-analysis.

PubMed

da Silva, Helbert Eustáquio Cardoso; Stefani, Cristine Miron; de Santos Melo, Nilce; de Almeida de Lima, Adriano; Rösing, Cassiano Kuchenbecker; Porporatti, André Luís; Canto, Graziela De Luca

2017-10-10

The aim of this systematic review with meta-analysis was to analyze the effects of intra-pregnancy nonsurgical periodontal therapy on periodontal inflammatory biomarkers and adverse pregnancy outcomes. On June 5, 2017, we searched PubMed, Cochrane, SCOPUS, Web of Science, LILACS, ProQuest, Open Grey, and Google Scholar databases. Randomized clinical trials in which pregnant women with chronic periodontitis underwent nonsurgical periodontal therapy, compared with an untreated group, tested for inflammatory biomarkers, and followed till delivery were included. Primary outcomes were preterm birth, low birth weight, and preeclampsia. Meta-analysis was performed with 5.3.5 version of Review Manager software. We found 565 references in the databases, 326 after duplicates removal, 28 met criteria for full text reading, and 4 met eligibility criteria for quantitative and qualitative synthesis. Intra-pregnancy nonsurgical periodontal therapy improved periodontal clinical parameters (periodontal pocket depth, clinical attachment level, and bleeding on probing) and reduced biomarker level from gingival crevicular fluid (GCF), and some from blood serum; however, it did not influence biomarker level from umbilical cord blood. Meta-analysis showed tendency for reduction of the risk of preterm birth before 37 weeks for treated group (risk ratio (RR) = 0.54, 95% CI 0.38-0.77; p = 0.0007; inconsistency indexes (I2) 32%) but did not show any difference for low birth weight occurrence (RR = 0.78, 95%CI 0.50-1.21; p = 0.27; I2 41%). No included study considered preeclampsia as a gestational outcome. These results demonstrated that the intra-pregnancy nonsurgical periodontal therapy decreased periodontal inflammatory biomarker levels from gingival crevicular fluid and some from serum blood, with no influence on inflammatory biomarker level from cord blood, and it did not consistently reduce adverse gestational adverse outcome occurrence. PROSPERO CRD42015027750.

Supercritical Fluid Extraction of Bacterial and Archaeal Lipid Biomarkers from Anaerobically Digested Sludge

PubMed Central

Hanif, Muhammad; Atsuta, Yoichi; Fujie, Koichi; Daimon, Hiroyuki

2012-01-01

Supercritical fluid extraction (SFE) was used in the analysis of bacterial respiratory quinone (RQ), bacterial phospholipid fatty acid (PLFA), and archaeal phospholipid ether lipid (PLEL) from anaerobically digested sludge. Bacterial RQ were determined using ultra performance liquid chromatography (UPLC). Determination of bacterial PLFA and archaeal PLEL was simultaneously performed using gas chromatography-mass spectrometry (GC-MS). The effects of pressure, temperature, and modifier concentration on the total amounts of RQ, PLFA, and PLEL were investigated by 23 experiments with five settings chosen for each variable. The optimal extraction conditions that were obtained through a multiple-response optimization included a pressure of 23.6 MPa, temperature of 77.6 °C, and 10.6% (v/v) of methanol as the modifier. Thirty nine components of microbial lipid biomarkers were identified in the anaerobically digested sludge. Overall, the SFE method proved to be more effective, rapid, and quantitative for simultaneously extracting bacterial and archaeal lipid biomarkers, compared to conventional organic solvent extraction. This work shows the potential application of SFE as a routine method for the comprehensive analysis of microbial community structures in environmental assessments using the lipid biomarkers profile. PMID:22489140

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.

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

PubMed Central

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

2015-01-01

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

UHPLC/PDA-ESI/MS analysis of the main berry and leaf flavonol glycosides from different Carpathian Hippophaë rhamnoides L. varieties.

PubMed

Pop, Raluca Maria; Socaciu, Carmen; Pintea, Adela; Buzoianu, Anca Dana; Sanders, Mark Gerardus; Gruppen, Harry; Vincken, Jean-Paul

2013-01-01

Sea buckthorn (Hippophaë rhamnoides L.) is known to be rich in many bioactive compounds (such as vitamins, phenolics, carotenoids) important for human health and nutrition. Among the phenolics, berries and leaves contain a wide range of flavonols that are good quality and authenticity biomarkers. To compare the composition of the main flavonols of Romanian sea buckthorn berry and leaf varieties and to identify the specific biomarkers that contribute to sample differentiation among varieties. Six varieties of cultivated sea buckthorn (ssp. Carpatica) berries and leaves were analysed by UHPLC/PDA-ESI/MS. Berries and leaves contained mainly isorhamnetin (I) glycosides in different ratios. Whereas I-3-neohesperidoside, I-3-glucoside, I-3-rhamnosylglucoside, I-3-sophoroside-7-rhamnoside and free isorhamnetin were predominant for berries (out of 17 compounds identified), I-3-rhamnosylglucoside, I-3-neohesperidoside, I-3-glucoside, quercetin-3-pentoside, kaempferol-3-rutinoside, and quercetin-3-glucoside were predominant in leaves (out of 19 compounds identified). Berries contained, on average, 917 mg/100 g DW flavonol glycosides. Leaves had higher content of flavonol glycosides than berries, on average 1118 mg/100 g DW. The variation of the quantitative dataset analysed using principal component analysis accounted for 91% of the total variance in the case of berries and 73% in case of leaves, demonstrating a good discrimination among samples. Based on quantitative analysis, by principal component analysis, the flavonol derivatives can be considered as biomarkers to discriminate among varieties and to recognise specifically the berry versus leaf composition. Copyright © 2013 John Wiley & Sons, Ltd.

Association analysis of rare variants near the APOE region with CSF and neuroimaging biomarkers of Alzheimer's disease.

PubMed

Nho, Kwangsik; Kim, Sungeun; Horgusluoglu, Emrin; Risacher, Shannon L; Shen, Li; Kim, Dokyoon; Lee, Seunggeun; Foroud, Tatiana; Shaw, Leslie M; Trojanowski, John Q; Aisen, Paul S; Petersen, Ronald C; Jack, Clifford R; Weiner, Michael W; Green, Robert C; Toga, Arthur W; Saykin, Andrew J

2017-05-24

The APOE ε4 allele is the most significant common genetic risk factor for late-onset Alzheimer's disease (LOAD). The region surrounding APOE on chromosome 19 has also shown consistent association with LOAD. However, no common variants in the region remain significant after adjusting for APOE genotype. We report a rare variant association analysis of genes in the vicinity of APOE with cerebrospinal fluid (CSF) and neuroimaging biomarkers of LOAD. Whole genome sequencing (WGS) was performed on 817 blood DNA samples from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Sequence data from 757 non-Hispanic Caucasian participants was used in the present analysis. We extracted all rare variants (MAF (minor allele frequency) < 0.05) within a 312 kb window in APOE's vicinity encompassing 12 genes. We assessed CSF and neuroimaging (MRI and PET) biomarkers as LOAD-related quantitative endophenotypes. Gene-based analyses of rare variants were performed using the optimal Sequence Kernel Association Test (SKAT-O). A total of 3,334 rare variants (MAF < 0.05) were found within the APOE region. Among them, 72 rare non-synonymous variants were observed. Eight genes spanning the APOE region were significantly associated with CSF Aβ 1-42 (p < 1.0 × 10 -3 ). After controlling for APOE genotype and adjusting for multiple comparisons, 4 genes (CBLC, BCAM, APOE, and RELB) remained significant. Whole-brain surface-based analysis identified highly significant clusters associated with rare variants of CBLC in the temporal lobe region including the entorhinal cortex, as well as frontal lobe regions. Whole-brain voxel-wise analysis of amyloid PET identified significant clusters in the bilateral frontal and parietal lobes showing associations of rare variants of RELB with cortical amyloid burden. Rare variants within genes spanning the APOE region are significantly associated with LOAD-related CSF Aβ 1-42 and neuroimaging biomarkers after adjusting for APOE genotype. These findings warrant further investigation and illustrate the role of next generation sequencing and quantitative endophenotypes in assessing rare variants which may help explain missing heritability in AD and other complex diseases.

Topic model-based mass spectrometric data analysis in cancer biomarker discovery studies.

PubMed

Wang, Minkun; Tsai, Tsung-Heng; Di Poto, Cristina; Ferrarini, Alessia; Yu, Guoqiang; Ressom, Habtom W

2016-08-18

A fundamental challenge in quantitation of biomolecules for cancer biomarker discovery is owing to the heterogeneous nature of human biospecimens. Although this issue has been a subject of discussion in cancer genomic studies, it has not yet been rigorously investigated in mass spectrometry based proteomic and metabolomic studies. Purification of mass spectometric data is highly desired prior to subsequent analysis, e.g., quantitative comparison of the abundance of biomolecules in biological samples. We investigated topic models to computationally analyze mass spectrometric data considering both integrated peak intensities and scan-level features, i.e., extracted ion chromatograms (EICs). Probabilistic generative models enable flexible representation in data structure and infer sample-specific pure resources. Scan-level modeling helps alleviate information loss during data preprocessing. We evaluated the capability of the proposed models in capturing mixture proportions of contaminants and cancer profiles on LC-MS based serum proteomic and GC-MS based tissue metabolomic datasets acquired from patients with hepatocellular carcinoma (HCC) and liver cirrhosis as well as synthetic data we generated based on the serum proteomic data. The results we obtained by analysis of the synthetic data demonstrated that both intensity-level and scan-level purification models can accurately infer the mixture proportions and the underlying true cancerous sources with small average error ratios (<7 %) between estimation and ground truth. By applying the topic model-based purification to mass spectrometric data, we found more proteins and metabolites with significant changes between HCC cases and cirrhotic controls. Candidate biomarkers selected after purification yielded biologically meaningful pathway analysis results and improved disease discrimination power in terms of the area under ROC curve compared to the results found prior to purification. We investigated topic model-based inference methods to computationally address the heterogeneity issue in samples analyzed by LC/GC-MS. We observed that incorporation of scan-level features have the potential to lead to more accurate purification results by alleviating the loss in information as a result of integrating peaks. We believe cancer biomarker discovery studies that use mass spectrometric analysis of human biospecimens can greatly benefit from topic model-based purification of the data prior to statistical and pathway analyses.

Long noncoding RNA MALAT1 as a potential novel biomarker in digestive system cancers: a meta-analysis.

PubMed

Song, Wei; Zhang, Run J; Zou, Shu B

2016-08-01

Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), a newly discovered long non-coding RNA (lncRNA), has been reported to be overexpressed in various cancers. However, the clinical value of MALAT1 in digestive system cancers is unclear. This study was designed to investigate the potential value of MALAT1 as a prognostic biomarker in digestive system cancers. We searched the Medline, Embase and Cochrane Library databases. All studies that explored the correlation between lncRNA MALAT1 expression and survival in digestive system tumors were selected. A quantitative meta-analysis was performed for the correlation between lncRNA MALAT1 expression and survival in digestive system tumors. Five studies were eligible for analysis, which included 547 patients. Meta-analysis showed that high expression of MALAT1 could predict poor overall survival (OS) in digestive system cancers (pooled HR: 1.85, 95% CI: 1.41-2.43, P<0.0001). For disease-free survival (DFS), elevated MALAT1 expression was also a significant predictor with a combined HR of 2.28 (95% CI: 1.42-3.67, P=0.0007). lncRNA MALAT1 may serve as a potential novel prognostic biomarker in digestive system cancers.

Long noncoding RNA MALAT1 as a potential novel biomarker in digestive system cancers: a meta-analysis.

PubMed

Song, Wei; Zhang, Run J; Zou, Shu B

2016-05-17

MALAT1 (Metastasis-associated lung adenocarcinoma transcript 1), a newly discovered long non-coding RNA (lncRNA), has been reported to be overexpressed in various cancers. However, the clinical value of MALAT1 in digestive system cancers is unclear. This study was designed to investigate the potential value of MALAT1 as a prognostic biomarker in digestive system cancers. We searched the MEDLINE, EMBASE and Cochrane Library databases. All studies that explored the correlation between lncRNA MALAT1 expression and survival in digestive system tumors were selected. A quantitative meta-analysis was performed for the correlation between lncRNA MALAT1 expression and survival in digestive system tumors. Five studies were eligible for analysis, which included 547 patients. Meta-analysis showed that high expression of MALAT1 could predict poor overall survival (OS) in digestive system cancers (pooled HR: 1.85, 95% CI: 1.41-2.43, p < 0.0001). For disease-free survival (DFS), elevated MALAT1 expression was also a significant predictor with a combined HR of 2.28 (95% CI: 1.42-3.67, p = 0.0007). lncRNA MALAT1 may serve as a potential novel prognostic biomarker in digestive system cancers.

A quantitative systems pharmacology model of blood coagulation network describes in vivo biomarker changes in non-bleeding subjects.

PubMed

Lee, D; Nayak, S; Martin, S W; Heatherington, A C; Vicini, P; Hua, F

2016-12-01

Essentials Baseline coagulation activity can be detected in non-bleeding state by in vivo biomarker levels. A detailed mathematical model of coagulation was developed to describe the non-bleeding state. Optimized model described in vivo biomarkers with recombinant activated factor VII treatment. Sensitivity analysis predicted prothrombin fragment 1 + 2 and D-dimer are regulated differently. Background Prothrombin fragment 1 + 2 (F 1 + 2 ), thrombin-antithrombin III complex (TAT) and D-dimer can be detected in plasma from non-bleeding hemostatically normal subjects or hemophilic patients. They are often used as safety or pharmacodynamic biomarkers for hemostatis-modulating therapies in the clinic, and provide insights into in vivo coagulation activity. Objectives To develop a quantitative systems pharmacology (QSP) model of the blood coagulation network to describe in vivo biomarkers, including F 1 + 2 , TAT, and D-dimer, under non-bleeding conditions. Methods The QSP model included intrinsic and extrinsic coagulation pathways, platelet activation state-dependent kinetics, and a two-compartment pharmacokinetics model for recombinant activated factor VII (rFVIIa). Literature data on F 1 + 2 and D-dimer at baseline and changes with rFVIIa treatment were used for parameter optimization. Multiparametric sensitivity analysis (MPSA) was used to understand key proteins that regulate F 1 + 2 , TAT and D-dimer levels. Results The model was able to describe tissue factor (TF)-dependent baseline levels of F 1 + 2 , TAT and D-dimer in a non-bleeding state, and their increases in hemostatically normal subjects and hemophilic patients treated with different doses of rFVIIa. The amount of TF required is predicted to be very low in a non-bleeding state. The model also predicts that these biomarker levels will be similar in hemostatically normal subjects and hemophilic patients. MPSA revealed that F 1 + 2 and TAT levels are highly correlated, and that D-dimer is more sensitive to the perturbation of coagulation protein concentrations. Conclusions A QSP model for non-bleeding baseline coagulation activity was established with data from clinically relevant in vivo biomarkers at baseline and changes in response to rFVIIa treatment. This model will provide future mechanistic insights into this system. © 2016 International Society on Thrombosis and Haemostasis.

Rapid Verification of Candidate Serological Biomarkers Using Gel-based, Label-free Multiple Reaction Monitoring

PubMed Central

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

2011-01-01

Stable isotope dilution-multiple reaction monitoring-mass spectrometry (SID-MRM-MS) has emerged as a promising platform for verification of serological candidate biomarkers. However, cost and time needed to synthesize and evaluate stable isotope peptides, optimize spike-in assays, and generate standard curves, quickly becomes unattractive when testing many candidate biomarkers. In this study, we demonstrate that label-free multiplexed MRM-MS coupled with major protein depletion and 1-D gel separation is a time-efficient, cost-effective initial biomarker verification strategy requiring less than 100 μl serum. Furthermore, SDS gel fractionation can resolve different molecular weight forms of targeted proteins with potential diagnostic value. Because fractionation is at the protein level, consistency of peptide quantitation profiles across fractions permits rapid detection of quantitation problems for specific peptides from a given protein. Despite the lack of internal standards, the entire workflow can be highly reproducible, and long-term reproducibility of relative protein abundance can be obtained using different mass spectrometers and LC methods with external reference standards. Quantitation down to ~200 pg/mL could be achieved using this workflow. Hence, the label-free GeLC-MRM workflow enables rapid, sensitive, and economical initial screening of large numbers of candidate biomarkers prior to setting up SID-MRM assays or immunoassays for the most promising candidate biomarkers. PMID:21726088

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

PubMed

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

2011-09-02

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

A fully integrated distance readout ELISA-Chip for point-of-care testing with sample-in-answer-out capability.

PubMed

Liu, Dan; Li, Xingrui; Zhou, Junkai; Liu, Shibo; Tian, Tian; Song, Yanling; Zhu, Zhi; Zhou, Leiji; Ji, Tianhai; Yang, Chaoyong

2017-10-15

Enzyme-linked immunosorbent assay (ELISA) is a popular laboratory technique for detection of disease-specific protein biomarkers with high specificity and sensitivity. However, ELISA requires labor-intensive and time-consuming procedures with skilled operators and spectroscopic instrumentation. Simplification of the procedures and miniaturization of the devices are crucial for ELISA-based point-of-care (POC) testing in resource-limited settings. Here, we present a fully integrated, instrument-free, low-cost and portable POC platform which integrates the process of ELISA and the distance readout into a single microfluidic chip. Based on manipulation using a permanent magnet, the process is initiated by moving magnetic beads with capture antibody through different aqueous phases containing ELISA reagents to form bead/antibody/antigen/antibody sandwich structure, and finally converts the molecular recognition signal into a highly sensitive distance readout for visual quantitative bioanalysis. Without additional equipment and complicated operations, our integrated ELISA-Chip with distance readout allows ultrasensitive quantitation of disease biomarkers within 2h. The ELISA-Chip method also showed high specificity, good precision and great accuracy. Furthermore, the ELISA-Chip system is highly applicable as a sandwich-based platform for the detection of a variety of protein biomarkers. With the advantages of visual analysis, easy operation, high sensitivity, and low cost, the integrated sample-in-answer-out ELISA-Chip with distance readout shows great potential for quantitative POCT in resource-limited settings. Copyright © 2017. Published by Elsevier B.V.

Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues

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

Zhou, Jian-Ying; Chen, Lijun; Zhang, Bai

The identification of protein biomarkers requires large-scale analysis of human specimens to achieve statistical significance. In this study, we evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification) based quantitative proteomics strategy using one channel for universal normalization across all samples. A total of 307 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating 107 one-dimensional (1D) LC-MS/MS datasets and 8 offline two-dimensional (2D) LC-MS/MS datasets (25 fractions for each set) for human-in-mouse breast cancer xenograft tissues representative of basal and luminal subtypes. Such large-scale studies require the implementation of robust metrics to assessmore » the contributions of technical and biological variability in the qualitative and quantitative data. Accordingly, we developed a quantification confidence score based on the quality of each peptide-spectrum match (PSM) to remove quantification outliers from each analysis. After combining confidence score filtering and statistical analysis, reproducible protein identification and quantitative results were achieved from LC-MS/MS datasets collected over a 16 month period.« less

Correlating MALDI and MRI Biomarkers of Breast Cancer

DTIC Science & Technology

2010-07-01

resonance imaging ( MRI ) with matrix-assisted laser desorption ionization (MALDI) analysis of healthy and tumorous ex vivo specimens in order to examine the...assess the correlation between physiological parameters reported by magnetic resonance (MR) imaging and tumor protein distribution determined from... imaging research (e.g., Cancer Imaging , Quantitative Magnetic Resonance Imaging , and Medical Image Registration classes) • completion of

Quantitative Analysis of the Cervical Texture by Ultrasound and Correlation with Gestational Age.

PubMed

Baños, Núria; Perez-Moreno, Alvaro; Migliorelli, Federico; Triginer, Laura; Cobo, Teresa; Bonet-Carne, Elisenda; Gratacos, Eduard; Palacio, Montse

2017-01-01

Quantitative texture analysis has been proposed to extract robust features from the ultrasound image to detect subtle changes in the textures of the images. The aim of this study was to evaluate the feasibility of quantitative cervical texture analysis to assess cervical tissue changes throughout pregnancy. This was a cross-sectional study including singleton pregnancies between 20.0 and 41.6 weeks of gestation from women who delivered at term. Cervical length was measured, and a selected region of interest in the cervix was delineated. A model to predict gestational age based on features extracted from cervical images was developed following three steps: data splitting, feature transformation, and regression model computation. Seven hundred images, 30 per gestational week, were included for analysis. There was a strong correlation between the gestational age at which the images were obtained and the estimated gestational age by quantitative analysis of the cervical texture (R = 0.88). This study provides evidence that quantitative analysis of cervical texture can extract features from cervical ultrasound images which correlate with gestational age. Further research is needed to evaluate its applicability as a biomarker of the risk of spontaneous preterm birth, as well as its role in cervical assessment in other clinical situations in which cervical evaluation might be relevant. © 2016 S. Karger AG, Basel.

The PAXgene® Tissue System Preserves Phosphoproteins in Human Tissue Specimens and Enables Comprehensive Protein Biomarker Research

PubMed Central

Gündisch, Sibylle; Schott, Christina; Wolff, Claudia; Tran, Kai; Beese, Christian; Viertler, Christian; Zatloukal, Kurt; Becker, Karl-Friedrich

2013-01-01

Precise quantitation of protein biomarkers in clinical tissue specimens is a prerequisite for accurate and effective diagnosis, prognosis, and personalized medicine. Although progress is being made, protein analysis from formalin-fixed and paraffin-embedded tissues is still challenging. In previous reports, we showed that the novel formalin-free tissue preservation technology, the PAXgene Tissue System, allows the extraction of intact and immunoreactive proteins from PAXgene-fixed and paraffin-embedded (PFPE) tissues. In the current study, we focused on the analysis of phosphoproteins and the applicability of two-dimensional gel electrophoresis (2D-PAGE) and enzyme-linked immunosorbent assay (ELISA) to the analysis of a variety of malignant and non-malignant human tissues. Using western blot analysis, we found that phosphoproteins are quantitatively preserved in PFPE tissues, and signal intensities are comparable to that in paired, frozen tissues. Furthermore, proteins extracted from PFPE samples are suitable for 2D-PAGE and can be quantified by ELISA specific for denatured proteins. In summary, the PAXgene Tissue System reliably preserves phosphoproteins in human tissue samples, even after prolonged fixation or stabilization times, and is compatible with methods for protein analysis such as 2D-PAGE and ELISA. We conclude that the PAXgene Tissue System has the potential to serve as a versatile tissue fixative for modern pathology. PMID:23555997

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

PubMed

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

2017-04-01

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

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

PubMed Central

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

2013-01-01

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

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.

Retinal health information and notification system (RHINO)

NASA Astrophysics Data System (ADS)

Dashtbozorg, Behdad; Zhang, Jiong; Abbasi-Sureshjani, Samaneh; Huang, Fan; ter Haar Romeny, Bart M.

2017-03-01

The retinal vasculature is the only part of the blood circulation system that can be observed non-invasively using fundus cameras. Changes in the dynamic properties of retinal blood vessels are associated with many systemic and vascular diseases, such as hypertension, coronary heart disease and diabetes. The assessment of the characteristics of the retinal vascular network provides important information for an early diagnosis and prognosis of many systemic and vascular diseases. The manual analysis of the retinal vessels and measurement of quantitative biomarkers in large-scale screening programs is a tedious task, time-consuming and costly. This paper describes a reliable, automated, and efficient retinal health information and notification system (acronym RHINO) which can extract a wealth of geometric biomarkers in large volumes of fundus images. The fully automated software presented in this paper includes vessel enhancement and segmentation, artery/vein classification, optic disc, fovea, and vessel junction detection, and bifurcation/crossing discrimination. Pipelining these tools allows the assessment of several quantitative vascular biomarkers: width, curvature, bifurcation geometry features and fractal dimension. The brain-inspired algorithms outperform most of the state-of-the-art techniques. Moreover, several annotation tools are implemented in RHINO for the manual labeling of arteries and veins, marking optic disc and fovea, and delineating vessel centerlines. The validation phase is ongoing and the software is currently being used for the analysis of retinal images from the Maastricht study (the Netherlands) which includes over 10,000 subjects (healthy and diabetic) with a broad spectrum of clinical measurements

Unraveling Molecular Differences of Gastric Cancer by Label-Free Quantitative Proteomics Analysis.

PubMed

Dai, Peng; Wang, Qin; Wang, Weihua; Jing, Ruirui; Wang, Wei; Wang, Fengqin; Azadzoi, Kazem M; Yang, Jing-Hua; Yan, Zhen

2016-01-21

Gastric cancer (GC) has significant morbidity and mortality worldwide and especially in China. Its molecular pathogenesis has not been thoroughly elaborated. The acknowledged biomarkers for diagnosis, prognosis, recurrence monitoring and treatment are lacking. Proteins from matched pairs of human GC and adjacent tissues were analyzed by a coupled label-free Mass Spectrometry (MS) approach, followed by functional annotation with software analysis. Nano-LC-MS/MS, quantitative real-time polymerase chain reaction (qRT-PCR), western blot and immunohistochemistry were used to validate dysregulated proteins. One hundred forty-six dysregulated proteins with more than twofold expressions were quantified, 22 of which were first reported to be relevant with GC. Most of them were involved in cancers and gastrointestinal disease. The expression of a panel of four upregulated nucleic acid binding proteins, heterogeneous nuclear ribonucleoprotein hnRNPA2B1, hnRNPD, hnRNPL and Y-box binding protein 1 (YBX-1) were validated by Nano-LC-MS/MS, qRT-PCR, western blot and immunohistochemistry assays in ten GC patients' tissues. They were located in the keynotes of a predicted interaction network and might play important roles in abnormal cell growth. The label-free quantitative proteomic approach provides a deeper understanding and novel insight into GC-related molecular changes and possible mechanisms. It also provides some potential biomarkers for clinical diagnosis.

Determination of burn patient outcome by large-scale quantitative discovery proteomics

PubMed Central

Finnerty, Celeste C.; Jeschke, Marc G.; Qian, Wei-Jun; Kaushal, Amit; Xiao, Wenzhong; Liu, Tao; Gritsenko, Marina A.; Moore, Ronald J.; Camp, David G.; Moldawer, Lyle L.; Elson, Constance; Schoenfeld, David; Gamelli, Richard; Gibran, Nicole; Klein, Matthew; Arnoldo, Brett; Remick, Daniel; Smith, Richard D.; Davis, Ronald; Tompkins, Ronald G.; Herndon, David N.

2013-01-01

Objective Emerging proteomics techniques can be used to establish proteomic outcome signatures and to identify candidate biomarkers for survival following traumatic injury. We applied high-resolution liquid chromatography-mass spectrometry (LC-MS) and multiplex cytokine analysis to profile the plasma proteome of survivors and non-survivors of massive burn injury to determine the proteomic survival signature following a major burn injury. Design Proteomic discovery study. Setting Five burn hospitals across the U.S. Patients Thirty-two burn patients (16 non-survivors and 16 survivors), 19–89 years of age, were admitted within 96 h of injury to the participating hospitals with burns covering >20% of the total body surface area and required at least one surgical intervention. Interventions None. Measurements and Main Results We found differences in circulating levels of 43 proteins involved in the acute phase response, hepatic signaling, the complement cascade, inflammation, and insulin resistance. Thirty-two of the proteins identified were not previously known to play a role in the response to burn. IL-4, IL-8, GM-CSF, MCP-1, and β2-microglobulin correlated well with survival and may serve as clinical biomarkers. Conclusions These results demonstrate the utility of these techniques for establishing proteomic survival signatures and for use as a discovery tool to identify candidate biomarkers for survival. This is the first clinical application of a high-throughput, large-scale LC-MS-based quantitative plasma proteomic approach for biomarker discovery for the prediction of patient outcome following burn, trauma or critical illness. PMID:23507713

Novel CT-based objective imaging biomarkers of long term radiation-induced lung damage.

PubMed

Veiga, Catarina; Landau, David; Devaraj, Anand; Doel, Tom; White, Jared; Ngai, Yenting; Hawkes, David J; McClelland, Jamie R

2018-06-14

and Purpose: Recent improvements in lung cancer survival have spurred an interest in understanding and minimizing long term radiation-induced lung damage (RILD). However, there is still no objective criteria to quantify RILD leading to variable reporting across centres and trials. We propose a set of objective imaging biomarkers to quantify common radiological findings observed 12-months after lung cancer radiotherapy (RT). Baseline and 12-month CT scans of 27 patients from a phase I/II clinical trial of isotoxic chemoradiation were included in this study. To detect and measure the severity of RILD, twelve quantitative imaging biomarkers were developed. These describe basic CT findings including parenchymal change, volume reduction and pleural change. The imaging biomarkers were implemented as semi-automated image analysis pipelines and assessed against visual assessment of the occurrence of each change. The majority of the biomarkers were measurable in each patient. Their continuous nature allows objective scoring of severity for each patient. For each imaging biomarker the cohort was split into two groups according to the presence or absence of the biomarker by visual assessment, testing the hypothesis that the imaging biomarkers were different in these two groups. All features were statistically significant except for rotation of the main bronchus and diaphragmatic curvature. The majority of the biomarkers were not strongly correlated with each other suggesting that each of the biomarkers is measuring a separate element of RILD pathology. We developed objective CT-based imaging biomarkers that quantify the severity of radiological lung damage after RT. These biomarkers are representative of typical radiological findings of RILD. Copyright © 2018. Published by Elsevier Inc.

Quantitative mass spectrometric analysis of glycoproteins combined with enrichment methods.

PubMed

Ahn, Yeong Hee; Kim, Jin Young; Yoo, Jong Shin

2015-01-01

Mass spectrometry (MS) has been a core technology for high sensitive and high-throughput analysis of the enriched glycoproteome in aspects of quantitative assays as well as qualitative profiling of glycoproteins. Because it has been widely recognized that aberrant glycosylation in a glycoprotein may involve in progression of a certain disease, the development of efficient analysis tool for the aberrant glycoproteins is very important for deep understanding about pathological function of the glycoprotein and new biomarker development. This review first describes the protein glycosylation-targeting enrichment technologies mainly employing solid-phase extraction methods such as hydrizide-capturing, lectin-specific capturing, and affinity separation techniques based on porous graphitized carbon, hydrophilic interaction chromatography, or immobilized boronic acid. Second, MS-based quantitative analysis strategies coupled with the protein glycosylation-targeting enrichment technologies, by using a label-free MS, stable isotope-labeling, or targeted multiple reaction monitoring (MRM) MS, are summarized with recent published studies. © 2014 The Authors. Mass Spectrometry Reviews Published by Wiley Periodicals, Inc.

Somatic mutation detection in human biomonitoring.

PubMed

Olsen, L S; Nielsen, L R; Nexø, B A; Wassermann, K

1996-06-01

Somatic cell gene mutation arising in vivo may be considered to be a biomarker for genotoxicity. Assays detecting mutations of the haemoglobin and glycophorin A genes in red blood cells and of the hypoxanthine-guanine phosphoribosyltransferase and human leucocyte antigenes in T-lymphocytes are available in humans. This MiniReview describes these assays and their application to studies of individuals exposed to genotoxic agents. Moreover, with the implementation of techniques of molecular biology mutation spectra can now be defined in addition to the quantitation of in vivo mutant frequencies. We describe current screening methods for unknown mutations, including the denaturing gradient gel electrophoresis, single strand conformation polymorphism analysis, heteroduplex analysis, chemical modification techniques and enzymatic cleavage methods. The advantage of mutation detection as a biomarker is that it integrates exposure and sensitivity in one measurement. With the analysis of mutation spectra it may thus be possible to identify the causative genotoxic agent.

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

PubMed

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

2017-03-01

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

Detection of Radiation-Exposure Biomarkers by Differential Mobility Prefiltered Mass Spectrometry (DMS-MS)

PubMed Central

Coy, Stephen L.; Krylov, Evgeny V.; Schneider, Bradley B.; Covey, Thomas R.; Brenner, David J.; Tyburski, John B.; Patterson, Andrew D.; Krausz, Kris W.; Fornace, Albert J.; Nazarov, Erkinjon G.

2010-01-01

Technology to enable rapid screening for radiation exposure has been identified as an important need, and, as a part of a NIH / NIAD effort in this direction, metabolomic biomarkers for radiation exposure have been identified in a recent series of papers. To reduce the time necessary to detect and measure these biomarkers, differential mobility spectrometry – mass spectrometry (DMS-MS) systems have been developed and tested. Differential mobility ion filters preselect specific ions and also suppress chemical noise created in typical atmospheric-pressure ionization sources (ESI, MALDI, and others). Differential-mobility-based ion selection is based on the field dependence of ion mobility, which, in turn, depends on ion characteristics that include conformation, charge distribution, molecular polarizability, and other properties, and on the transport gas composition which can be modified to enhance resolution. DMS-MS is able to resolve small-molecule biomarkers from nearly-isobaric interferences, and suppresses chemical noise generated in the ion source and in the mass spectrometer, improving selectivity and quantitative accuracy. Our planar DMS design is rapid, operating in a few milliseconds, and analyzes ions before fragmentation. Depending on MS inlet conditions, DMS-selected ions can be dissociated in the MS inlet expansion, before mass analysis, providing a capability similar to MS/MS with simpler instrumentation. This report presents selected DMS-MS experimental results, including resolution of complex test mixtures of isobaric compounds, separation of charge states, separation of isobaric biomarkers (citrate and isocitrate), and separation of nearly-isobaric biomarker anions in direct analysis of a bio-fluid sample from the radiation-treated group of a mouse-model study. These uses of DMS combined with moderate resolution MS instrumentation indicate the feasibility of field-deployable instrumentation for biomarker evaluation. PMID:20305793

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2013-01-01

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

Biomarkers are used to predict quantitative metabolite concentration profiles in human red blood cells

DOE PAGES

Yurkovich, James T.; Yang, Laurence; Palsson, Bernhard O.; ...

2017-03-06

Deep-coverage metabolomic profiling has revealed a well-defined development of metabolic decay in human red blood cells (RBCs) under cold storage conditions. A set of extracellular biomarkers has been recently identified that reliably defines the qualitative state of the metabolic network throughout this metabolic decay process. Here, we extend the utility of these biomarkers by using them to quantitatively predict the concentrations of other metabolites in the red blood cell. We are able to accurately predict the concentration profile of 84 of the 91 (92%) measured metabolites ( p < 0.05) in RBC metabolism using only measurements of these five biomarkers.more » The median of prediction errors (symmetric mean absolute percent error) across all metabolites was 13%. Furthermore, the ability to predict numerous metabolite concentrations from a simple set of biomarkers offers the potential for the development of a powerful workflow that could be used to evaluate the metabolic state of a biological system using a minimal set of measurements.« less

Biomarkers are used to predict quantitative metabolite concentration profiles in human red blood cells

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

Yurkovich, James T.; Yang, Laurence; Palsson, Bernhard O.

Deep-coverage metabolomic profiling has revealed a well-defined development of metabolic decay in human red blood cells (RBCs) under cold storage conditions. A set of extracellular biomarkers has been recently identified that reliably defines the qualitative state of the metabolic network throughout this metabolic decay process. Here, we extend the utility of these biomarkers by using them to quantitatively predict the concentrations of other metabolites in the red blood cell. We are able to accurately predict the concentration profile of 84 of the 91 (92%) measured metabolites ( p < 0.05) in RBC metabolism using only measurements of these five biomarkers.more » The median of prediction errors (symmetric mean absolute percent error) across all metabolites was 13%. Furthermore, the ability to predict numerous metabolite concentrations from a simple set of biomarkers offers the potential for the development of a powerful workflow that could be used to evaluate the metabolic state of a biological system using a minimal set of measurements.« less

Cartilage Repair Surgery: Outcome Evaluation by Using Noninvasive Cartilage Biomarkers Based on Quantitative MRI Techniques?

PubMed Central

Jungmann, Pia M.; Baum, Thomas; Bauer, Jan S.; Karampinos, Dimitrios C.; Link, Thomas M.; Li, Xiaojuan; Trattnig, Siegfried; Rummeny, Ernst J.; Woertler, Klaus; Welsch, Goetz H.

2014-01-01

Background. New quantitative magnetic resonance imaging (MRI) techniques are increasingly applied as outcome measures after cartilage repair. Objective. To review the current literature on the use of quantitative MRI biomarkers for evaluation of cartilage repair at the knee and ankle. Methods. Using PubMed literature research, studies on biochemical, quantitative MR imaging of cartilage repair were identified and reviewed. Results. Quantitative MR biomarkers detect early degeneration of articular cartilage, mainly represented by an increasing water content, collagen disruption, and proteoglycan loss. Recently, feasibility of biochemical MR imaging of cartilage repair tissue and surrounding cartilage was demonstrated. Ultrastructural properties of the tissue after different repair procedures resulted in differences in imaging characteristics. T2 mapping, T1rho mapping, delayed gadolinium-enhanced MRI of cartilage (dGEMRIC), and diffusion weighted imaging (DWI) are applicable on most clinical 1.5 T and 3 T MR scanners. Currently, a standard of reference is difficult to define and knowledge is limited concerning correlation of clinical and MR findings. The lack of histological correlations complicates the identification of the exact tissue composition. Conclusions. A multimodal approach combining several quantitative MRI techniques in addition to morphological and clinical evaluation might be promising. Further investigations are required to demonstrate the potential for outcome evaluation after cartilage repair. PMID:24877139

Rapid and Sensitive Detection of Protein Biomarker Using a Portable Fluorescence Biosensor based on Quantum Dots and a Lateral Flow Test Strip

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

Li, Zhaohui; Wang, Ying; Wang, Jun

2010-08-15

A portable fluorescence biosensor with rapid and ultrasensitive response for trace protein has been built up with quantum dots and lateral flow test strip. The superior signal brightness and high photostability of quantum dots are combined with the promising advantages of lateral flow test strip and resulted in high sensitivity, selectivity and speedy for protein detection. Nitrated ceruloplasmin, a significant biomarker for cardiovascular disease, lung cancer and stress response to smoking, was used as model protein to demonstrate the good performances of this proposed Qdot-based lateral flow test strip. Quantitative detection of nitrated ceruloplasmin was realized by recording the fluorescencemore » intensity of quantum dots captured on the test line. Under optimal conditions, this portable fluorescence biosensor displays rapid responses for nitrated ceruloplasmin in wide dynamic range with a detection limit of 0.1ng/mL (S/N=3). Furthermore, the biosensor was successfully utilized for spiked human plasma sample detection with the concentration as low as 1ng/mL. The results demonstrate that the quantum dot-based lateral flow test strip is capable for rapid, sensitive, and quantitative detection of nitrated ceruloplasmin and hold a great promise for point-of-care and in field analysis of other protein biomarkers.« less

Second harmonic generation for collagen I characterization in rectal cancer patients with and without preoperative radiotherapy

NASA Astrophysics Data System (ADS)

Blockhuys, Stéphanie; Agarwal, Nisha Rani; Hildesjö, Camilla; Jarlsfelt, Ingvar; Wittung-Stafshede, Pernilla; Sun, Xiao-Feng

2017-10-01

Rectal cancer is treated with preoperative radiotherapy (RT) to downstage the tumor, reduce local recurrence, and improve patient survival. Still, the treatment outcome varies significantly and new biomarkers are desired. Collagen I (Col-I) is a potential biomarker, which can be visualized label-free by second harmonic generation (SHG). Here, we used SHG to identify Col-I changes induced by RT in surgical tissue, with the aim to evaluate the clinical significance of RT-induced Col-I changes. First, we established a procedure for quantitative evaluation of Col-I by SHG in CDX2-stained tissue sections. Next, we evaluated Col-I properties in material from 31 non-RT and 29 RT rectal cancer patients. We discovered that the Col-I intensity and anisotropy were higher in the tumor invasive margin than in the inner tumor and normal mucosa, and RT increased and decreased the intensity in inner tumor and normal mucosa, respectively. Furthermore, higher Col-I intensity in the inner tumor was related to increased distant recurrence in the non-RT group but to longer survival in the RT group. In conclusion, we present a new application of SHG for quantitative analysis of Col-I in surgical material, and the first data suggest Col-I intensity as a putative prognostic biomarker in rectal cancer.

Functionalized vertical GaN micro pillar arrays with high signal-to-background ratio for detection and analysis of proteins secreted from breast tumor cells.

PubMed

Choi, Mun-Ki; Kim, Gil-Sung; Jeong, Jin-Tak; Lim, Jung-Taek; Lee, Won-Yong; Umar, Ahmad; Lee, Sang-Kwon

2017-11-02

The detection of cancer biomarkers has recently attracted significant attention as a means of determining the correct course of treatment with targeted therapeutics. However, because the concentration of these biomarkers in blood is usually relatively low, highly sensitive biosensors for fluorescence imaging and precise detection are needed. In this study, we have successfully developed vertical GaN micropillar (MP) based biosensors for fluorescence sensing and quantitative measurement of CA15-3 antigens. The highly ordered vertical GaN MP arrays result in the successful immobilization of CA15-3 antigens on each feature of the arrays, thereby allowing the detection of an individual fluorescence signal from the top surface of the arrays owing to the high regularity of fluorophore-tagged MP spots and relatively low background signal. Therefore, our fluorescence-labeled and CA15-3 functionalized vertical GaN-MP-based biosensor is suitable for the selective quantitative analysis of secreted CA15-3 antigens from MCF-7 cell lines, and helps in the early diagnosis and prognosis of serious diseases as well as the monitoring of the therapeutic response of breast cancer patients.

Expanded metabolomics approach to profiling endogenous carbohydrates in the serum of ovarian cancer patients.

PubMed

Cheng, Yu; Li, Li; Zhu, Bangjie; Liu, Feng; Wang, Yan; Gu, Xue; Yan, Chao

2016-01-01

We applied hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry to the quantitative analysis of serum from 58 women, including ovarian cancer patients, ovarian benign tumor patients, and healthy controls. All of these ovarian cancer and ovarian benign tumor patients have elevated cancer antigen 125, which makes them clinically difficult to differentiate the malignant from the benign. All of the 16 endogenous carbohydrates were quantitatively detected in the human sera, of which, eight endogenous carbohydrates were significantly different (P-value < 0.05) between the ovarian cancer and healthy control. According to the receiver operating characteristic curve analysis, arabitol was the most potentially specific biomarker for discriminating ovarian cancer from healthy control, having an area under the curve of 0.911. A panel of metabolite markers composed of maltose, maltotriose, raffinose, and mannitol was selected, which was able to discriminate the ovarian cancer from the benign ovarian tumor counterparts, with an area under concentration-time curve value of 0.832. Endogenous carbohydrates in the expanded metabolomics approach after the global metabolic profiling are characterized and are potential biomarkers for the early diagnosis of ovarian cancer. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2016-03-01

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

MicroRNAs and toxicology: A love marriage.

PubMed

Schraml, Elisabeth; Hackl, Matthias; Grillari, Johannes

2017-01-01

With the dawn of personalized medicine, secreted microRNAs (miRNAs) have come into the very focus of biomarker development for various diseases. MiRNAs fulfil key requirements of diagnostic tools such as i) non or minimally invasive accessibility, ii) robust, standardized and non-expensive quantitative analysis, iii) rapid turnaround of the test result and iv) most importantly because they provide a comprehensive snapshot of the ongoing physiologic processes in cells and tissues that package and release miRNAs into cell-free space. These characteristics have also established circulating miRNAs as promising biomarker candidates for toxicological studies, where they are used as biomarkers of drug-, or chemical-induced tissue injury for safety assessment. The tissue-specificity and early release of circulating miRNAs upon tissue injury, when damage is still reversible, are main factors for their clinical utility in toxicology. Here we summarize in brief, current knowledge of this field.

A Microfluidic Immunostaining System Enables Quality Assured and Standardized Immunohistochemical Biomarker Analysis

NASA Astrophysics Data System (ADS)

Kwon, Seyong; Cho, Chang Hyun; Kwon, Youngmee; Lee, Eun Sook; Park, Je-Kyun

2017-04-01

Immunohistochemistry (IHC) plays an important role in biomarker-driven cancer therapy. Although there has been a high demand for standardized and quality assured IHC, it has rarely been achieved due to the complexity of IHC testing and the subjective validation-based process flow of IHC quality control. We present here a microfluidic immunostaining system for the standardization of IHC by creating a microfluidic linearly graded antibody (Ab)-staining device and a reference cell microarray. Unlike conventional efforts, our system deals primarily with the screening of biomarker staining conditions for quantitative quality assurance testing in IHC. We characterized the microfluidic matching of Ab staining intensity using three HER2 Abs produced by different manufacturers. The quality of HER2 Ab was also validated using tissues of breast cancer patients, demonstrating that our system is an efficient and powerful tool for the standardization and quality assurance of IHC.

The electrophotonic silicon biosensor

NASA Astrophysics Data System (ADS)

Juan-Colás, José; Parkin, Alison; Dunn, Katherine E.; Scullion, Mark G.; Krauss, Thomas F.; Johnson, Steven D.

2016-09-01

The emergence of personalized and stratified medicine requires label-free, low-cost diagnostic technology capable of monitoring multiple disease biomarkers in parallel. Silicon photonic biosensors combine high-sensitivity analysis with scalable, low-cost manufacturing, but they tend to measure only a single biomarker and provide no information about their (bio)chemical activity. Here we introduce an electrochemical silicon photonic sensor capable of highly sensitive and multiparameter profiling of biomarkers. Our electrophotonic technology consists of microring resonators optimally n-doped to support high Q resonances alongside electrochemical processes in situ. The inclusion of electrochemical control enables site-selective immobilization of different biomolecules on individual microrings within a sensor array. The combination of photonic and electrochemical characterization also provides additional quantitative information and unique insight into chemical reactivity that is unavailable with photonic detection alone. By exploiting both the photonic and the electrical properties of silicon, the sensor opens new modalities for sensing on the microscale.

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

PubMed

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

2016-10-25

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

Genomic analysis, cytokine expression, and microRNA profiling reveal biomarkers of human dietary zinc depletion and homeostasis.

PubMed

Ryu, Moon-Suhn; Langkamp-Henken, Bobbi; Chang, Shou-Mei; Shankar, Meena N; Cousins, Robert J

2011-12-27

Implementation of zinc interventions for subjects suspected of being zinc-deficient is a global need, but is limited due to the absence of reliable biomarkers. To discover molecular signatures of human zinc deficiency, a combination of transcriptome, cytokine, and microRNA analyses was applied to a dietary zinc depletion/repletion protocol with young male human subjects. Concomitant with a decrease in serum zinc concentration, changes in buccal and blood gene transcripts related to zinc homeostasis occurred with zinc depletion. Microarray analyses of whole blood RNA revealed zinc-responsive genes, particularly, those associated with cell cycle regulation and immunity. Responses of potential signature genes of dietary zinc depletion were further assessed by quantitative real-time PCR. The diagnostic properties of specific serum microRNAs for dietary zinc deficiency were identified by acute responses to zinc depletion, which were reversible by subsequent zinc repletion. Depression of immune-stimulated TNFα secretion by blood cells was observed after low zinc consumption and may serve as a functional biomarker. Our findings introduce numerous novel candidate biomarkers for dietary zinc status assessment using a variety of contemporary technologies and which identify changes that occur prior to or with greater sensitivity than the serum zinc concentration which represents the current zinc status assessment marker. In addition, the results of gene network analysis reveal potential clinical outcomes attributable to suboptimal zinc intake including immune function defects and predisposition to cancer. These demonstrate through a controlled depletion/repletion dietary protocol that the illusive zinc biomarker(s) can be identified and applied to assessment and intervention strategies.

Increased Depth and Breadth of Plasma Protein Quantitation via Two-Dimensional Liquid Chromatography/Multiple Reaction Monitoring-Mass Spectrometry with Labeled Peptide Standards.

PubMed

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

2016-01-01

Absolute quantitative strategies are emerging as a powerful and preferable means of deriving concentrations in biological samples for systems biology applications. Method development is driven by the need to establish new-and validate current-protein biomarkers of high-to-low abundance for clinical utility. In this chapter, we describe a methodology involving two-dimensional (2D) reversed-phase liquid chromatography (RPLC), operated under alkaline and acidic pH conditions, combined with multiple reaction monitoring (MRM)-mass spectrometry (MS) (also called selected reaction monitoring (SRM)-MS) and a complex mixture of stable isotope-labeled standard (SIS) peptides, to quantify a broad and diverse panel of 253 proteins in human blood plasma. The quantitation range spans 8 orders of magnitude-from 15 mg/mL (for vitamin D-binding protein) to 450 pg/mL (for protein S100-B)-and includes 31 low-abundance proteins (defined as being <10 ng/mL) of potential disease relevance. The method is designed to assess candidates at the discovery and/or verification phases of the biomarker pipeline and can be adapted to examine smaller or alternate panels of proteins for higher sample throughput. Also detailed here is the application of our recently developed software tool-Qualis-SIS-for protein quantitation (via regression analysis of standard curves) and quality assessment of the resulting data. Overall, this chapter provides the blueprint for the replication of this quantitative proteomic method by proteomic scientists of all skill levels.

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

PubMed

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

2016-11-23

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

[What can we expect from clinical trials in psychiatry?

PubMed

Marsot, A; Boucherie, Q; Kheloufi, F; Riff, C; Braunstein, D; Dupouey, J; Guilhaumou, R; Zendjidjian, X; Bonin-Guillaume, S; Fakra, E; Guye, M; Jirsa, V; Azorin, J-M; Belzeaux, R; Adida, M; Micallef, J; Blin, O

2016-12-01

Clinical trials in psychiatry allow to build the regulatory dossiers for market authorization but also to document the mechanism of action of new drugs, to build pharmacodynamics models, evaluate the treatment effects, propose prognosis, efficacy or tolerability biomarkers and altogether to assess the impact of drugs for patient, caregiver and society. However, clinical trials have shown some limitations. Number of recent dossiers failed to convince the regulators. The clinical and biological heterogeneity of psychiatric disorders, the pharmacokinetic and pharmacodynamics properties of the compounds, the lack of translatable biomarkers possibly explain these difficulties. Several breakthrough options are now available: quantitative system pharmacology analysis of drug effects variability, pharmacometry and pharmacoepidemiology, Big Data analysis, brain modelling. In addition to more classical approaches, these opportunities lead to a paradigm change for clinical trials in psychiatry. © L’Encéphale, Paris, 2016.

Integrating multiparametric prostate MRI into clinical practice

PubMed Central

2011-01-01

Abstract Multifunctional magnetic resonance imaging (MRI) techniques are increasingly being used to address bottlenecks in prostate cancer patient management. These techniques yield qualitative, semi-quantitative and fully quantitative biomarkers that reflect on the underlying biological status of a tumour. If these techniques are to have a role in patient management, then standard methods of data acquisition, analysis and reporting have to be developed. Effective communication by the use of scoring systems, structured reporting and a graphical interface that matches prostate anatomy are key elements. Practical guidelines for integrating multiparametric MRI into clinical practice are presented. PMID:22187067

Clinical peptidomic analysis by a one-step direct transfer technology: its potential utility for monitoring of pathophysiological status in female reproductive system disorders.

PubMed

Araki, Yoshihiko; Nonaka, Daisuke; Hamamura, Kensuke; Yanagida, Mitsuaki; Ishikawa, Hitoshi; Banzai, Michio; Maruyama, Mayuko; Endo, Shuichiro; Tajima, Atsushi; Lee, Lyang-Ja; Nojima, Michio; Takamori, Kenji; Yoshida, Koyo; Takeda, Satoru; Tanaka, Kenji

2013-10-01

To date, numerous studies have searched for candidate molecules or clinical examination methods as potential biomarkers for monitoring intractable diseases, such as carcinomas. Evidence accumulated over the past decade shows that many proteolytic peptides appear in human humoral fluids, including peripheral blood, in association with an individual's health condition. Although an analysis of the whole peptide (the 'peptidome') using mass spectrometry is thought to be one of the most powerful and promising experimental approaches, it has failed to identify biomarkers in the clinical blood samples, presumably due to the methodological limitations. In general, commonly used techniques for proteomic analysis of blood require the removal of large amounts of serum/plasma proteins prior to mass spectrometry analysis, and this step seems to have resulted in the overlooking of important biomarkers during the analytical process. Here, we provide a brief overview of a new quantitative peptidomic analysis by a one-step direct transfer technology without depletion of major blood proteins. Using this technology, we herein report experimental data on serum peptidomic analysis for patients with pregnancy-induced hypertension as a clinical model. In addition, we refer to the potential utility of this approach for the monitoring of pathophysiological status in female reproductive system disorders in general. © 2013 The Authors. Journal of Obstetrics and Gynaecology Research © 2013 Japan Society of Obstetrics and Gynecology.

Quantitative proteomics in cardiovascular research: global and targeted strategies

PubMed Central

Shen, Xiaomeng; Young, Rebeccah; Canty, John M.; Qu, Jun

2014-01-01

Extensive technical advances in the past decade have substantially expanded quantitative proteomics in cardiovascular research. This has great promise for elucidating the mechanisms of cardiovascular diseases (CVD) and the discovery of cardiac biomarkers used for diagnosis and treatment evaluation. Global and targeted proteomics are the two major avenues of quantitative proteomics. While global approaches enable unbiased discovery of altered proteins via relative quantification at the proteome level, targeted techniques provide higher sensitivity and accuracy, and are capable of multiplexed absolute quantification in numerous clinical/biological samples. While promising, technical challenges need to be overcome to enable full utilization of these techniques in cardiovascular medicine. Here we discuss recent advances in quantitative proteomics and summarize applications in cardiovascular research with an emphasis on biomarker discovery and elucidating molecular mechanisms of disease. We propose the integration of global and targeted strategies as a high-throughput pipeline for cardiovascular proteomics. Targeted approaches enable rapid, extensive validation of biomarker candidates discovered by global proteomics. These approaches provide a promising alternative to immunoassays and other low-throughput means currently used for limited validation. PMID:24920501

A new strategy for faster urinary biomarkers identification by Nano-LC-MALDI-TOF/TOF mass spectrometry

PubMed Central

Benkali, K; Marquet, P; Rérolle, JP; Le Meur, Y; Gastinel, LN

2008-01-01

Background LC-MALDI-TOF/TOF analysis is a potent tool in biomarkers discovery characterized by its high sensitivity and high throughput capacity. However, methods based on MALDI-TOF/TOF for biomarkers discovery still need optimization, in particular to reduce analysis time and to evaluate their reproducibility for peak intensities measurement. The aims of this methodological study were: (i) to optimize and critically evaluate each step of urine biomarker discovery method based on Nano-LC coupled off-line to MALDI-TOF/TOF, taking full advantage of the dual decoupling between Nano-LC, MS and MS/MS to reduce the overall analysis time; (ii) to evaluate the quantitative performance and reproducibility of nano-LC-MALDI analysis in biomarker discovery; and (iii) to evaluate the robustness of biomarkers selection. Results A pool of urine sample spiked at increasing concentrations with a mixture of standard peptides was used as a specimen for biological samples with or without biomarkers. Extraction and nano-LC-MS variabilities were estimated by analyzing in triplicates and hexaplicates, respectively. The stability of chromatographic fractions immobilised with MALDI matrix on MALDI plates was evaluated by successive MS acquisitions after different storage times at different temperatures. Low coefficient of variation (CV%: 10–22%) and high correlation (R2 > 0.96) values were obtained for the quantification of the spiked peptides, allowing quantification of these peptides in the low fentomole range, correct group discrimination and selection of "specific" markers using principal component analysis. Excellent peptide integrity and stable signal intensity were found when MALDI plates were stored for periods of up to 2 months at +4°C. This allowed storage of MALDI plates between LC separation and MS acquisition (first decoupling), and between MS and MSMS acquisitions while the selection of inter-group discriminative ions is done (second decoupling). Finally the recording of MSMS spectra to obtain structural information was focused only on discriminative ions in order to minimize analysis time. Conclusion Contrary to other classical approaches with direct online coupling of chromatographic separation and on the flight MS and/or MSMS data acquisition for all detected analytes, our dual decoupling strategy allowed us to focus on the most discriminative analytes, giving us more time to acquire more replicates of the same urine samples thus increasing detection sensitivity and mass precision. PMID:19014585

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

PubMed Central

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

2009-01-01

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

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

PubMed

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

2008-02-01

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

Quantitative biomarkers of colonic dysplasia based on intrinsic second-harmonic generation signal

NASA Astrophysics Data System (ADS)

Zhuo, Shuangmu; Zhu, Xiaoqin; Wu, Guizhu; Chen, Jianxin; Xie, Shusen

2011-12-01

Most colorectal cancers arise from dysplastic lesions, such as adenomatous polyps, and these lesions are difficult to be detected by the current endoscopic screening approaches. Here, we present the use of an intrinsic second-harmonic generation (SHG) signal as a novel means to differentiate between normal and dysplastic human colonic tissues. We find that the SHG signal can quantitatively identify collagen change associated with colonic dysplasia that is indiscernible by conventional pathologic techniques. By comparing normal with dysplastic mucosa, there were significant differences in collagen density and collagen fiber direction, providing substantial potential to become quantitative intrinsic biomarkers for in vivo clinical diagnosis of colonic dysplasia.

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

Biomarkers for Prostate and Bladder Cancer — EDRN Public Portal

Cancer.gov

CD26+ cancer cells and CD90+ tumor-associated stromal cells were sorted from tumor tissue. Dataset analysis with transcriptomes of CD26+ luminal, CD104+ basal, CD49a+ stromal and CD31+ endothelial was carried out to identify candidates: CD90, AGR2, BCMP11, CEACAM5, CRISP3. Quantitative protomics was applied to measure these proteins in urine samples.

Predicting MCI outcome with clinically available MRI and CSF biomarkers

PubMed Central

Heister, D.; Brewer, J.B.; Magda, S.; Blennow, K.

2011-01-01

Objective: To determine the ability of clinically available volumetric MRI (vMRI) and CSF biomarkers, alone or in combination with a quantitative learning measure, to predict conversion to Alzheimer disease (AD) in patients with mild cognitive impairment (MCI). Methods: We stratified 192 MCI participants into positive and negative risk groups on the basis of 1) degree of learning impairment on the Rey Auditory Verbal Learning Test; 2) medial temporal atrophy, quantified from Food and Drug Administration–approved software for automated vMRI analysis; and 3) CSF biomarker levels. We also stratified participants based on combinations of risk factors. We computed Cox proportional hazards models, controlling for age, to assess 3-year risk of converting to AD as a function of risk group and used Kaplan-Meier analyses to determine median survival times. Results: When risk factors were examined separately, individuals testing positive showed significantly higher risk of converting to AD than individuals testing negative (hazard ratios [HR] 1.8–4.1). The joint presence of any 2 risk factors substantially increased risk, with the combination of greater learning impairment and increased atrophy associated with highest risk (HR 29.0): 85% of patients with both risk factors converted to AD within 3 years, vs 5% of those with neither. The presence of medial temporal atrophy was associated with shortest median dementia-free survival (15 months). Conclusions: Incorporating quantitative assessment of learning ability along with vMRI or CSF biomarkers in the clinical workup of MCI can provide critical information on risk of imminent conversion to AD. PMID:21998317

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 furthers our understanding of malignant mesothelioma, identified galectin 1 as a potential diagnostic biomarker, and highlighted several possible prognostic biomarkers of this disease.

Investigation of Pokemon-regulated proteins in hepatocellular carcinoma using mass spectrometry-based multiplex quantitative proteomics.

PubMed

Bi, Xin; Jin, Yibao; Gao, Xiang; Liu, Feng; Gao, Dan; Jiang, Yuyang; Liu, Hongxia

2013-01-01

Pokemon is a transcription regulator involved in embryonic development, cellular differentiation and oncogenesis. It is aberrantly overexpressed in multiple human cancers including Hepatocellular carcinoma (HCC) and is considered as a promising biomarker for HCC. In this work, the isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomics strategy was used to investigate the proteomic profile associated with Pokemon in human HCC cell line QGY7703 and human hepatocyte line HL7702. Samples were labeled with four-plex iTRAQ reagents followed by two-dimensional liquid chromatography coupled with tandem mass spectrometry analysis. A total of 24 differentially expressed proteins were selected as significant. Nine proteins were potentially up-regulated by Pokemon while 15 proteins were potentially down-regulated and many proteins were previously identified as potential biomarkers for HCC. Gene ontology (GO) term enrichment revealed that the listed proteins were mainly involved in DNA metabolism and biosynthesis process. The changes of glucose-6-phosphate 1-dehydrogenase (G6PD, up-regulated) and ribonucleoside-diphosphate reductase large sub-unit (RIM1, down-regulated) were validated by Western blotting analysis and denoted as Pokemon's function of oncogenesis. We also found that Pokemon potentially repressed the expression of highly clustered proteins (MCM3, MCM5, MCM6, MCM7) which played key roles in promoting DNA replication. Altogether, our results may help better understand the role of Pokemon in HCC and promote the clinical applications.

Automated fluorescent miscroscopic image analysis of PTBP1 expression in glioma

PubMed Central

Becker, Aline; Elder, Brad; Puduvalli, Vinay; Winter, Jessica; Gurcan, Metin

2017-01-01

Multiplexed immunofluorescent testing has not entered into diagnostic neuropathology due to the presence of several technical barriers, amongst which includes autofluorescence. This study presents the implementation of a methodology capable of overcoming the visual challenges of fluorescent microscopy for diagnostic neuropathology by using automated digital image analysis, with long term goal of providing unbiased quantitative analyses of multiplexed biomarkers for solid tissue neuropathology. In this study, we validated PTBP1, a putative biomarker for glioma, and tested the extent to which immunofluorescent microscopy combined with automated and unbiased image analysis would permit the utility of PTBP1 as a biomarker to distinguish diagnostically challenging surgical biopsies. As a paradigm, we utilized second resections from patients diagnosed either with reactive brain changes (pseudoprogression) and recurrent glioblastoma (true progression). Our image analysis workflow was capable of removing background autofluorescence and permitted quantification of DAPI-PTBP1 positive cells. PTBP1-positive nuclei, and the mean intensity value of PTBP1 signal in cells. Traditional pathological interpretation was unable to distinguish between groups due to unacceptably high discordance rates amongst expert neuropathologists. Our data demonstrated that recurrent glioblastoma showed more DAPI-PTBP1 positive cells and a higher mean intensity value of PTBP1 signal compared to resections from second surgeries that showed only reactive gliosis. Our work demonstrates the potential of utilizing automated image analysis to overcome the challenges of implementing fluorescent microscopy in diagnostic neuropathology. PMID:28282372

Data-Independent Acquisition-Based Quantitative Proteomic Analysis Reveals Potential Biomarkers of Kidney Cancer.

PubMed

Song, Yimeng; Zhong, Lijun; Zhou, Juntuo; Lu, Min; Xing, Tianying; Ma, Lulin; Shen, Jing

2017-12-01

Renal cell carcinoma (RCC) is a malignant and metastatic cancer with 95% mortality, and clear cell RCC (ccRCC) is the most observed among the five major subtypes of RCC. Specific biomarkers that can distinguish cancer tissues from adjacent normal tissues should be developed to diagnose this disease in early stages and conduct a reliable prognostic evaluation. Data-independent acquisition (DIA) strategy has been widely employed in proteomic analysis because of various advantages, including enhanced protein coverage and reliable data acquisition. In this study, a DIA workflow is constructed on a quadrupole-Orbitrap LC-MS platform to reveal dysregulated proteins between ccRCC and adjacent normal tissues. More than 4000 proteins are identified, 436 of these proteins are dysregulated in ccRCC tissues. Bioinformatic analysis reveals that multiple pathways and Gene Ontology items are strongly associated with ccRCC. The expression levels of L-lactate dehydrogenase A chain, annexin A4, nicotinamide N-methyltransferase, and perilipin-2 examined through RT-qPCR, Western blot, and immunohistochemistry confirm the validity of the proteomic analysis results. The proposed DIA workflow yields optimum time efficiency and data reliability and provides a good choice for proteomic analysis in biological and clinical studies, and these dysregulated proteins might be potential biomarkers for ccRCC diagnosis. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification of miR-194-5p as a potential biomarker for postmenopausal osteoporosis

PubMed Central

Pan, Nanan; Sun, Ning; Wang, Qiujun; Fan, Jingxue; Zhou, Ping

2015-01-01

The incidence of osteoporosis is high in postmenopausal women due to altered estrogen levels and continuous calcium loss that occurs with aging. Recent studies have shown that microRNAs (miRNAs) are involved in the development of osteoporosis. These miRNAs may be used as potential biomarkers to identify women at a high risk for developing the disease. In this study, whole blood samples were collected from 48 postmenopausal Chinese women with osteopenia or osteoporosis and pooled into six groups according to individual T-scores. A miRNA microarray analysis was performed on pooled blood samples to identify potential miRNA biomarkers for postmenopausal osteoporosis. Five miRNAs (miR-130b-3p, -151a-3p, -151b, -194-5p, and -590-5p) were identified in the microarray analysis. These dysregulated miRNAs were subjected to a pathway analysis investigating whether they were involved in regulating osteoporosis-related pathways. Among them, only miR-194-5p was enriched in multiple osteoporosis-related pathways. Enhanced miR-194-5p expression in women with osteoporosis was confirmed by quantitative reverse transcription–polymerase chain reaction analysis. For external validation, a significant correlation between the expression of miR-194-5p and T-scores was found in an independent patient collection comprised of 24 postmenopausal women with normal bone mineral density, 30 postmenopausal women with osteopenia, and 32 postmenopausal women with osteoporosis (p < 0.05). Taken together, the present findings suggest that miR-194-5p may be a viable miRNA biomarker for postmenopausal osteoporosis. PMID:26038726

Identification of miR-194-5p as a potential biomarker for postmenopausal osteoporosis.

PubMed

Meng, Jia; Zhang, Dapeng; Pan, Nanan; Sun, Ning; Wang, Qiujun; Fan, Jingxue; Zhou, Ping; Zhu, Wenliang; Jiang, Lihong

2015-01-01

The incidence of osteoporosis is high in postmenopausal women due to altered estrogen levels and continuous calcium loss that occurs with aging. Recent studies have shown that microRNAs (miRNAs) are involved in the development of osteoporosis. These miRNAs may be used as potential biomarkers to identify women at a high risk for developing the disease. In this study, whole blood samples were collected from 48 postmenopausal Chinese women with osteopenia or osteoporosis and pooled into six groups according to individual T-scores. A miRNA microarray analysis was performed on pooled blood samples to identify potential miRNA biomarkers for postmenopausal osteoporosis. Five miRNAs (miR-130b-3p, -151a-3p, -151b, -194-5p, and -590-5p) were identified in the microarray analysis. These dysregulated miRNAs were subjected to a pathway analysis investigating whether they were involved in regulating osteoporosis-related pathways. Among them, only miR-194-5p was enriched in multiple osteoporosis-related pathways. Enhanced miR-194-5p expression in women with osteoporosis was confirmed by quantitative reverse transcription-polymerase chain reaction analysis. For external validation, a significant correlation between the expression of miR-194-5p and T-scores was found in an independent patient collection comprised of 24 postmenopausal women with normal bone mineral density, 30 postmenopausal women with osteopenia, and 32 postmenopausal women with osteoporosis (p < 0.05). Taken together, the present findings suggest that miR-194-5p may be a viable miRNA biomarker for postmenopausal osteoporosis.

Identification of novel biomarker and therapeutic target candidates for acute intracerebral hemorrhage by quantitative plasma proteomics.

PubMed

Li, Guo-Chun; Zhang, Lina; Yu, Ming; Jia, Haiyu; Tian, Ting; Wang, Junqin; Wang, Fuqiang; Zhou, Ling

2017-01-01

The systematic mechanisms of acute intracerebral hemorrhage are still unknown and unverified, although many recent researches have indicated the secondary insults. This study was aimed to disclose the pathological mechanism and identify novel biomarker and therapeutic target candidates by plasma proteome. Patients with AICH (n = 8) who demographically matched healthy controls (n = 4) were prospectively enrolled, and their plasma samples were obtained. The TMT-LC-MS/MS-based proteomics approach was used to quantify the differential proteome across plasma samples, and the results were analyzed by Ingenuity Pathway Analysis to explore canonical pathways and the relationship involved in the uploaded data. Compared with healthy controls, there were 31 differentially expressed proteins in the ICH group ( P  < 0.05), of which 21 proteins increased while 10 proteins decreased in abundance. These proteins are involved in 21 canonical pathways. One network with high confidence level was selected by the function network analysis, in which 23 proteins, P38MAPK and NFκB signaling pathways participated. Upstream regulator analysis found two regulators, IL6 and TNF, with an activation z -score. Seven biomarker candidates: APCS, FGB, LBP, MGMT, IGFBP2, LYZ, and APOA4 were found. Six candidate proteins were selected to assess the validity of the results by subsequent Western blotting analysis. Our analysis provided several intriguing pathways involved in ICH, like LXR/RXR activation, acute phase response signaling, and production of NO and ROS in macrophages pathways. The three upstream regulators: IL-6, TNF, LPS, and seven biomarker candidates: APCS, APOA4, FGB, IGFBP2, LBP, LYZ, and MGMT were uncovered. LPS, APOA4, IGFBP2, LBP, LYZ, and MGMT are novel potential biomarkers in ICH development. The identified proteins and pathways provide new perspectives to the potential pathological mechanism and therapeutic targets underlying ICH.

Metrology Standards for Quantitative Imaging Biomarkers

PubMed Central

Obuchowski, Nancy A.; Kessler, Larry G.; Raunig, David L.; Gatsonis, Constantine; Huang, Erich P.; Kondratovich, Marina; McShane, Lisa M.; Reeves, Anthony P.; Barboriak, Daniel P.; Guimaraes, Alexander R.; Wahl, Richard L.

2015-01-01

Although investigators in the imaging community have been active in developing and evaluating quantitative imaging biomarkers (QIBs), the development and implementation of QIBs have been hampered by the inconsistent or incorrect use of terminology or methods for technical performance and statistical concepts. Technical performance is an assessment of how a test performs in reference objects or subjects under controlled conditions. In this article, some of the relevant statistical concepts are reviewed, methods that can be used for evaluating and comparing QIBs are described, and some of the technical performance issues related to imaging biomarkers are discussed. More consistent and correct use of terminology and study design principles will improve clinical research, advance regulatory science, and foster better care for patients who undergo imaging studies. © RSNA, 2015 PMID:26267831

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

PubMed

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

2015-08-01

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

Pollution biomarkers in the spiny lizard (Sceloporus spp.) from two suburban populations of Monterrey, Mexico.

PubMed

Aguilera, Carlos; del Pliego, Pamela González; Alfaro, Roberto Mendoza; Lazcano, David; Cruz, Julio

2012-11-01

Environmental pollution may severely impact reptile species in urbanized areas. The magnitude of the impact is analyzed in the present study using lizard tail tips for the quantitative evaluation of enzymatic biomarkers of pollution. Spiny lizards (Sceloporus serrifer and S. torquatus) were collected from two suburban localities in the Monterrey metropolitan area, Mexico: Chipinque Ecological Park, a natural protected area, and El Carmen Industrial Park (IP), a highly polluted site. Different enzymes were used as biomarkers including: acetylcholinesterase (AChE), butyrylcholinesterase (BChE), carboxylesterase (CaE), alkaline phosphatase (ALP), acid phosphatase (ACP), superoxide dismutase (SOD) and glutathione S-transferase (GST). The levels of AChE, BChE and ACP activity were not significantly different between localities. AChE and BChE, commonly used as biomarkers of neurotoxic polluting agents (e.g. organophosphate pesticides) do not appear to be affecting the populations from the study locations. In contrast, the levels of CaE, GST, ALP and SOD were significantly different between the localities. These biomarkers are regularly associated with oxidative stress and processes of detoxification, and generally indicate pollution caused by heavy metals or hydrocarbons, which are common in industrial sites. The data resulting from the analysis of these biomarkers indicate that these polluting agents are affecting the populations of Sceloporus in IP. The present work validates the possibility of conducting additional ecotoxicological studies using biomarkers in combination with a nondestructive sampling technique in species of spiny lizards that are abundant in many North America areas.

An exploratory NMR nutri-metabonomic investigation reveals dimethyl sulfone as a dietary biomarker for onion intake.

PubMed

Winning, Hanne; Roldán-Marín, Eduvigis; Dragsted, Lars O; Viereck, Nanna; Poulsen, Morten; Sánchez-Moreno, Concepción; Cano, M Pilar; Engelsen, Søren B

2009-11-01

The metabolome following intake of onion by-products is evaluated. Thirty-two rats were fed a diet containing an onion by-product or one of the two derived onion by-product fractions: an ethanol extract and the residue. A 24 hour urine sample was analyzed using (1)H NMR spectroscopy in order to investigate the effects of onion intake on the rat metabolism. Application of interval extended canonical variates analysis (ECVA) proved to be able to distinguish between the metabolomic profiles from rats consuming normal feed and rats fed with an onion diet. Two dietary biomarkers for onion intake were identified as dimethyl sulfone and 3-hydroxyphenylacetic acid. The same two dietary biomarkers were subsequently revealed by interval partial least squares regression (PLS) to be perfect quantitative markers for onion intake. The best PLS calibration model yielded a root mean square error of cross-validation (RMSECV) of 0.97% (w/w) with only 1 latent variable and a squared correlation coefficient of 0.94. This indicates that urine from rats on the by-product diet, the extract diet, and the residue diet all contain the same dietary biomarkers and it is concluded that dimethyl sulfone and 3-hydroxyphenylacetic acid are dietary biomarkers for onion intake. Being able to detect specific dietary biomarkers is highly beneficial in the control of nutritionally enhanced functional foods.

Development of a Multi-Biomarker Disease Activity Test for Rheumatoid Arthritis

PubMed Central

Shen, Yijing; Ramanujan, Saroja; Knowlton, Nicholas; Swan, Kathryn A.; Turner, Mary; Sutton, Chris; Smith, Dustin R.; Haney, Douglas J.; Chernoff, David; Hesterberg, Lyndal K.; Carulli, John P.; Taylor, Peter C.; Shadick, Nancy A.; Weinblatt, Michael E.; Curtis, Jeffrey R.

2013-01-01

Background Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment. Objectives To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. Methods Candidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing. Results 130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities. Conclusion We followed a stepwise approach to develop a quantitative serum-based measure of RA disease activity, based on 12-biomarkers, which was consistently associated with clinical disease activity levels. PMID:23585841

Development of a multi-biomarker disease activity test for rheumatoid arthritis.

PubMed

Centola, Michael; Cavet, Guy; Shen, Yijing; Ramanujan, Saroja; Knowlton, Nicholas; Swan, Kathryn A; Turner, Mary; Sutton, Chris; Smith, Dustin R; Haney, Douglas J; Chernoff, David; Hesterberg, Lyndal K; Carulli, John P; Taylor, Peter C; Shadick, Nancy A; Weinblatt, Michael E; Curtis, Jeffrey R

2013-01-01

Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment. To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. Candidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing. 130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities. We followed a stepwise approach to develop a quantitative serum-based measure of RA disease activity, based on 12-biomarkers, which was consistently associated with clinical disease activity levels.

QUANTITATIVE MASS SPECTROMETRIC ANALYSIS OF GLYCOPROTEINS COMBINED WITH ENRICHMENT METHODS

PubMed Central

Ahn, Yeong Hee; Kim, Jin Young; Yoo, Jong Shin

2015-01-01

Mass spectrometry (MS) has been a core technology for high sensitive and high-throughput analysis of the enriched glycoproteome in aspects of quantitative assays as well as qualitative profiling of glycoproteins. Because it has been widely recognized that aberrant glycosylation in a glycoprotein may involve in progression of a certain disease, the development of efficient analysis tool for the aberrant glycoproteins is very important for deep understanding about pathological function of the glycoprotein and new biomarker development. This review first describes the protein glycosylation-targeting enrichment technologies mainly employing solid-phase extraction methods such as hydrizide-capturing, lectin-specific capturing, and affinity separation techniques based on porous graphitized carbon, hydrophilic interaction chromatography, or immobilized boronic acid. Second, MS-based quantitative analysis strategies coupled with the protein glycosylation-targeting enrichment technologies, by using a label-free MS, stable isotope-labeling, or targeted multiple reaction monitoring (MRM) MS, are summarized with recent published studies. © 2014 The Authors. Mass Spectrometry Reviews Published by Wiley Periodicals, Inc. Rapid Commun. Mass Spec Rev 34:148–165, 2015. PMID:24889823

Label-free quantitative proteomic analysis of human plasma-derived microvesicles to find protein signatures of abdominal aortic aneurysms.

PubMed

Martinez-Pinna, Roxana; Gonzalez de Peredo, Anne; Monsarrat, Bernard; Burlet-Schiltz, Odile; Martin-Ventura, Jose Luis

2014-08-01

To find potential biomarkers of abdominal aortic aneurysms (AAA), we performed a differential proteomic study based on human plasma-derived microvesicles. Exosomes and microparticles isolated from plasma of AAA patients and control subjects (n = 10 each group) were analyzed by a label-free quantitative MS-based strategy. Homemade and publicly available software packages have been used for MS data analysis. The application of two kinds of bioinformatic tools allowed us to find differential protein profiles from AAA patients. Some of these proteins found by the two analysis methods belong to main pathological mechanisms of AAA such as oxidative stress, immune-inflammation, and thrombosis. Data analysis from label-free MS-based experiments requires the use of sophisticated bioinformatic approaches to perform quantitative studies from complex protein mixtures. The application of two of these bioinformatic tools provided us a preliminary list of differential proteins found in plasma-derived microvesicles not previously associated to AAA, which could help us to understand the pathological mechanisms related to this disease. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative Imaging Biomarkers: A Review of Statistical Methods for Computer Algorithm Comparisons

PubMed Central

2014-01-01

Quantitative biomarkers from medical images are becoming important tools for clinical diagnosis, staging, monitoring, treatment planning, and development of new therapies. While there is a rich history of the development of quantitative imaging biomarker (QIB) techniques, little attention has been paid to the validation and comparison of the computer algorithms that implement the QIB measurements. In this paper we provide a framework for QIB algorithm comparisons. We first review and compare various study designs, including designs with the true value (e.g. phantoms, digital reference images, and zero-change studies), designs with a reference standard (e.g. studies testing equivalence with a reference standard), and designs without a reference standard (e.g. agreement studies and studies of algorithm precision). The statistical methods for comparing QIB algorithms are then presented for various study types using both aggregate and disaggregate approaches. We propose a series of steps for establishing the performance of a QIB algorithm, identify limitations in the current statistical literature, and suggest future directions for research. PMID:24919829

Use of quantitative SPECT/CT reconstruction in 99mTc-sestamibi imaging of patients with renal masses.

PubMed

Jones, Krystyna M; Solnes, Lilja B; Rowe, Steven P; Gorin, Michael A; Sheikhbahaei, Sara; Fung, George; Frey, Eric C; Allaf, Mohamad E; Du, Yong; Javadi, Mehrbod S

2018-02-01

Technetium-99m ( 99m Tc)-sestamibi single-photon emission computed tomography/computed tomography (SPECT/CT) has previously been shown to allow for the accurate differentiation of benign renal oncocytomas and hybrid oncocytic/chromophobe tumors (HOCTs) apart from other malignant renal tumor histologies, with oncocytomas/HOCTs showing high uptake and renal cell carcinoma (RCC) showing low uptake based on uptake ratios from non-quantitative single-photon emission computed tomography (SPECT) reconstructions. However, in this study, several tumors fell close to the uptake ratio cutoff, likely due to limitations in conventional SPECT/CT reconstruction methods. We hypothesized that application of quantitative SPECT/CT (QSPECT) reconstruction methods developed by our group would provide more robust separation of hot and cold lesions, serving as an imaging framework on which quantitative biomarkers can be validated for evaluation of renal masses with 99m Tc-sestamibi. Single-photon emission computed tomography data were reconstructed using the clinical Flash 3D reconstruction and QSPECT methods. Two blinded readers then characterized each tumor as hot or cold. Semi-quantitative uptake ratios were calculated by dividing lesion activity by background renal activity for both Flash 3D and QSPECT reconstructions. The difference between median (mean) hot and cold tumor uptake ratios measured 0.655 (0.73) with the QSPECT method and 0.624 (0.67) with the conventional method, resulting in increased separation between hot and cold tumors. Sub-analysis of 7 lesions near the separation point showed a higher absolute difference (0.16) between QPSECT and Flash 3D mean uptake ratios compared to the remaining lesions. Our finding of improved separation between uptake ratios of hot and cold lesions using QSPECT reconstruction lays the foundation for additional quantitative SPECT techniques such as SPECT-UV in the setting of renal 99m Tc-sestamibi and other SPECT/CT exams. With robust quantitative image reconstruction and biomarker analysis, there may be an expanded role for SPECT/CT imaging in renal masses and other pathologic conditions.

miRNA 206 and miRNA 574-5p are highly expression in coronary artery disease

PubMed Central

Zhou, Jianqing; Shao, Guofeng; Chen, Xiaoliang; Yang, Xi; Huang, Xiaoyan; Peng, Ping; Ba, Yanna; Zhang, Lin; Jehangir, Tashina; Bu, Shizhong; Liu, Ningsheng; Lian, Jiangfang

2015-01-01

Coronary artery disease (CAD) is the leading cause of human morbidity and mortality worldwide. Innovative diagnostic biomarkers are a pressing need for this disease. miRNAs profiling is an innovative method of identifying biomarkers for many diseases and could be proven as a powerful tool in the diagnosis and treatment of CAD. We performed miRNA microarray analysis from the plasma of three CAD patients and three healthy controls. Subsequently, we performed quantitative real-time PCR (qRT-PCR) analysis of miRNA expression in plasma of another 67 CAD patients and 67 healthy controls. We identified two miRNAs (miR-206 and miR-574-5p) that were significantly up-regulated in CAD patients as compared with healthy controls (P<0.05). The receiver operating characteristic (ROC) curves indicated these two miRNAs had great potential to provide sensitive and specific diagnostic value for CAD. PMID:26685009

Advanced diffusion MRI and biomarkers in the central nervous system: a new approach.

PubMed

Martín Noguerol, T; Martínez Barbero, J P

The introduction of diffusion-weighted sequences has revolutionized the detection and characterization of central nervous system (CNS) disease. Nevertheless, the assessment of diffusion studies of the CNS is often limited to qualitative estimation. Moreover, the pathophysiological complexity of the different entities that affect the CNS cannot always be correctly explained through classical models. The development of new models for the analysis of diffusion sequences provides numerous parameters that enable a quantitative approach to both diagnosis and prognosis as well as to monitoring the response to treatment; these parameters can be considered potential biomarkers of health and disease. In this update, we review the physical bases underlying diffusion studies and diffusion tensor imaging, advanced models for their analysis (intravoxel coherent motion and kurtosis), and the biological significance of the parameters derived. Copyright © 2017 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

Circulating Tumor Cell Analysis in Preclinical Mouse Models of Metastasis.

PubMed

Kitz, Jenna; Lowes, Lori E; Goodale, David; Allan, Alison L

2018-04-28

The majority of cancer deaths occur because of metastasis since current therapies are largely non-curative in the metastatic setting. The use of in vivo preclinical mouse models for assessing metastasis is, therefore, critical for developing effective new cancer biomarkers and therapies. Although a number of quantitative tools have been previously developed to study in vivo metastasis, the detection and quantification of rare metastatic events has remained challenging. This review will discuss the use of circulating tumor cell (CTC) analysis as an effective means of tracking and characterizing metastatic disease progression in preclinical mouse models of breast and prostate cancer and the resulting lessons learned about CTC and metastasis biology. We will also discuss how the use of clinically-relevant CTC technologies such as the CellSearch ® and Parsortix™ platforms for preclinical CTC studies can serve to enhance the study of cancer biology, new biomarkers, and novel therapies from the bench to the bedside.

Proteomic and N-glycoproteomic quantification reveal aberrant changes in the human saliva of oral ulcer patients.

PubMed

Zhang, Ying; Wang, Xi; Cui, Dan; Zhu, Jun

2016-12-01

Human whole saliva is a vital body fluid for studying the physiology and pathology of the oral cavity. As a powerful technique for biomarker discovery, MS-based proteomic strategies have been introduced for saliva analysis and identified hundreds of proteins and N-glycosylation sites. However, there is still a lack of quantitative analysis, which is necessary for biomarker screening and biological research. In this study, we establish an integrated workflow by the combination of stable isotope dimethyl labeling, HILIC enrichment, and high resolution MS for both quantification of the global proteome and N-glycoproteome of human saliva from oral ulcer patients. With the help of advanced bioinformatics, we comprehensively studied oral ulcers at both protein and glycoprotein scales. Bioinformatics analyses revealed that starch digestion and protein degradation activities are inhibited while the immune response is promoted in oral ulcer saliva. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Importance of choice of materials and methods in PD-L1 and TIL assessment in oropharyngeal squamous cell carcinoma.

PubMed

De Meulenaere, Astrid; Vermassen, Tijl; Creytens, David; Aspeslagh, Sandrine; Deron, Philippe; Duprez, Frederic; Rottey, Sylvie; Van Dorpe, Jo; Ferdinande, Liesbeth

2018-05-16

A great deal of research is being conducted into PD-L1 immunohistochemistry (IHC) and tumor infiltrating lymphocytes (TILs) as predictive or prognostic biomarkers for immunotherapy, although several practical issues exist concerning their assessment. The aim of this research was therefore to assess the importance of choice of materials and methods in PD-L1 and TILs scoring in oropharyngeal squamous cell carcinoma (OSCC). IHC for PD-L1 (SP142 and 22C3 clone) and TILs subtyping was performed on formalin-fixed paraffin-embedded tissue slides (biopsy, resection and/or lymph nodes specimens) of 99 patients with OSCC. A comparative analysis of PD-L1 and TILs scoring was made between different types of tissue specimens, between different PD-L1 clones, between TILs and different subsets of TILs, and between the quantitative and semi-quantitative assessment. PD-L1 scoring resulted in fair to moderate agreement for 22C3 and SP142 between various tissue specimens, with higher agreement at higher cut-off values, and in moderate agreement for 22C3 versus SP142. Evaluation by four independent observers proved substantial inter-rater agreement for both clones with high consistency in their ratings. Moderate agreement was observed for TILs and TILs subsets for the comparison between biopsy and resection. Lastly, strong correlations were found between quantitative and semi-quantitative assessment for all PD-L1 and TILs scores. Our results highlight the challenges associated with the evaluation of PD-L1 and TILs in OSCC. Further research is warranted to evaluate the use of these biomarkers in order to allow implementation of PD-L1 and TILs infiltrate as biomarkers in daily clinical practice. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

The Biomarker-Surrogacy Evaluation Schema: a review of the biomarker-surrogate literature and a proposal for a criterion-based, quantitative, multidimensional hierarchical levels of evidence schema for evaluating the status of biomarkers as surrogate endpoints.

PubMed

Lassere, Marissa N

2008-06-01

There are clear advantages to using biomarkers and surrogate endpoints, but concerns about clinical and statistical validity and systematic methods to evaluate these aspects hinder their efficient application. Section 2 is a systematic, historical review of the biomarker-surrogate endpoint literature with special reference to the nomenclature, the systems of classification and statistical methods developed for their evaluation. In Section 3 an explicit, criterion-based, quantitative, multidimensional hierarchical levels of evidence schema - Biomarker-Surrogacy Evaluation Schema - is proposed to evaluate and co-ordinate the multiple dimensions (biological, epidemiological, statistical, clinical trial and risk-benefit evidence) of the biomarker clinical endpoint relationships. The schema systematically evaluates and ranks the surrogacy status of biomarkers and surrogate endpoints using defined levels of evidence. The schema incorporates the three independent domains: Study Design, Target Outcome and Statistical Evaluation. Each domain has items ranked from zero to five. An additional category called Penalties incorporates additional considerations of biological plausibility, risk-benefit and generalizability. The total score (0-15) determines the level of evidence, with Level 1 the strongest and Level 5 the weakest. The term ;surrogate' is restricted to markers attaining Levels 1 or 2 only. Surrogacy status of markers can then be directly compared within and across different areas of medicine to guide individual, trial-based or drug-development decisions. This schema would facilitate communication between clinical, researcher, regulatory, industry and consumer participants necessary for evaluation of the biomarker-surrogate-clinical endpoint relationship in their different settings.

Quantitative Analysis of {sup 18}F-Fluorodeoxyglucose Positron Emission Tomography Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated With Stereotactic Body Radiation Therapy

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

Cui, Yi; Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo; Song, Jie

Purpose: To identify prognostic biomarkers in pancreatic cancer using high-throughput quantitative image analysis. Methods and Materials: In this institutional review board–approved study, we retrospectively analyzed images and outcomes for 139 locally advanced pancreatic cancer patients treated with stereotactic body radiation therapy (SBRT). The overall population was split into a training cohort (n=90) and a validation cohort (n=49) according to the time of treatment. We extracted quantitative imaging characteristics from pre-SBRT {sup 18}F-fluorodeoxyglucose positron emission tomography, including statistical, morphologic, and texture features. A Cox proportional hazard regression model was built to predict overall survival (OS) in the training cohort using 162more » robust image features. To avoid over-fitting, we applied the elastic net to obtain a sparse set of image features, whose linear combination constitutes a prognostic imaging signature. Univariate and multivariate Cox regression analyses were used to evaluate the association with OS, and concordance index (CI) was used to evaluate the survival prediction accuracy. Results: The prognostic imaging signature included 7 features characterizing different tumor phenotypes, including shape, intensity, and texture. On the validation cohort, univariate analysis showed that this prognostic signature was significantly associated with OS (P=.002, hazard ratio 2.74), which improved upon conventional imaging predictors including tumor volume, maximum standardized uptake value, and total legion glycolysis (P=.018-.028, hazard ratio 1.51-1.57). On multivariate analysis, the proposed signature was the only significant prognostic index (P=.037, hazard ratio 3.72) when adjusted for conventional imaging and clinical factors (P=.123-.870, hazard ratio 0.53-1.30). In terms of CI, the proposed signature scored 0.66 and was significantly better than competing prognostic indices (CI 0.48-0.64, Wilcoxon rank sum test P<1e-6). Conclusion: Quantitative analysis identified novel {sup 18}F-fluorodeoxyglucose positron emission tomography image features that showed improved prognostic value over conventional imaging metrics. If validated in large, prospective cohorts, the new prognostic signature might be used to identify patients for individualized risk-adaptive therapy.« less

Pre-analytical effects of blood sampling and handling in quantitative immunoassays for rheumatoid arthritis.

PubMed

Zhao, Xiaoyan; Qureshi, Ferhan; Eastman, P Scott; Manning, William C; Alexander, Claire; Robinson, William H; Hesterberg, Lyndal K

2012-04-30

Variability in pre-analytical blood sampling and handling can significantly impact results obtained in quantitative immunoassays. Understanding the impact of these variables is critical for accurate quantification and validation of biomarker measurements. Particularly, in the design and execution of large clinical trials, even small differences in sample processing and handling can have dramatic effects in analytical reliability, results interpretation, trial management and outcome. The effects of two common blood sampling methods (serum vs. plasma) and two widely-used serum handling methods (on the clot with ambient temperature shipping, "traditional", vs. centrifuged with cold chain shipping, "protocol") on protein and autoantibody concentrations were examined. Matched serum and plasma samples were collected from 32 rheumatoid arthritis (RA) patients representing a wide range of disease activity status. Additionally, a set of matched serum samples with two sample handling methods was collected. One tube was processed per manufacturer's instructions and shipped overnight on cold packs (protocol). The matched tube, without prior centrifugation, was simultaneously shipped overnight at ambient temperatures (traditional). Upon delivery, the traditional tube was centrifuged. All samples were subsequently aliquoted and frozen prior to analysis of protein and autoantibody biomarkers. Median correlation between paired serum and plasma across all autoantibody assays was 0.99 (0.98-1.00) with a median % difference of -3.3 (-7.5 to 6.0). In contrast, observed protein biomarker concentrations were significantly affected by sample types, with median correlation of 0.99 (0.33-1.00) and a median % difference of -10 (-55 to 23). When the two serum collection/handling methods were compared, the median correlation between paired samples for autoantibodies was 0.99 (0.91-1.00) with a median difference of 4%. In contrast, significant increases were observed in protein biomarker concentrations among certain biomarkers in samples processed with the 'traditional' method. Autoantibody quantification appears robust to both sample type (plasma vs. serum) and pre-analytical sample collection/handling methods (protocol vs. traditional). In contrast, for non-antibody protein biomarker concentrations, sample type had a significant impact; plasma samples generally exhibit decreased protein biomarker concentrations relative to serum. Similarly, sample handling significantly impacted the variability of protein biomarker concentrations. When biomarker concentrations are combined algorithmically into a single test score such as a multi-biomarker disease activity test for rheumatoid arthritis (MBDA), changes in protein biomarker concentrations may result in a bias of the score. These results illustrate the importance of characterizing pre-analytical methodology, sample type, sample processing and handling procedures for clinical testing in order to ensure test accuracy. Copyright © 2012 Elsevier B.V. All rights reserved.

State-of-the-art MS technology applications in lung disease.

PubMed

Végvári, Ákos; Döme, Balázs

2011-12-01

Two frontline MS technologies, which have recently gained much attention, are discussed within the scope of this review. Besides a brief summary on the contemporary state of lung cancer and chronic obstructive pulmonary disease, the principles of multiple reaction monitoring and matrix assisted laser desorption ionization (MALDI) MS imaging are presented. A comprehensive overview of quantitative mass spectrometry applications is provided, covering multiple reaction monitoring assay developments for analysis of proteins (biomarkers) and low-molecular-weight compounds (drugs) with a special focus on the disease areas of lung cancer and chronic obstructive pulmonary disease. The MALDI-MS imaging applications are discussed similarly, providing references to studies conducted on lung tissues in order to localize drug compounds and protein biomarkers.

A novel approach for quantitation of glucosylceramide in human dried blood spot using LC-MS/MS.

PubMed

Ji, Allena Ji; Wang, Haixing; Ziso-Qejvanaj, Enida; Zheng, Kefei; Chung, Lee Lee; Foley, Timothy; Chuang, Wei-Lien; Richards, Susan; Sung, Crystal

2015-01-01

Glucosylceramide, an efficacy biomarker for Gaucher Type 1 disease, exhibits poor solubility in polar solvents and whole blood which makes it difficult to prepare a homogenous blood standard. We developed a novel method using standard addition approach by spiking a small volume of analyte solution on the surface of prespotted dried blood spot. The whole spots were punched out for subsequent extraction and LC-MS/MS analysis. The assay performance met all validation acceptance criteria. Glucosylceramide concentrations in 50 paired plasma and dry blood spot samples obtained from Gaucher Type 1 patients were tested and the results demonstrated the feasibility of using the DBS method for clinical biomarker monitoring. The new approach greatly improves assay precision and accuracy.

Brain Oscillations in Sport: Toward EEG Biomarkers of Performance.

PubMed

Cheron, Guy; Petit, Géraldine; Cheron, Julian; Leroy, Axelle; Cebolla, Anita; Cevallos, Carlos; Petieau, Mathieu; Hoellinger, Thomas; Zarka, David; Clarinval, Anne-Marie; Dan, Bernard

2016-01-01

Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The non-invasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP) in sport. In this context, the hypotheses of unified brain rhythms and continuity between wake and sleep states should provide a functional template for EEG biomarkers in sport. The oscillations in the thalamo-cortical and hippocampal circuitry including the physiology of the place cells and the grid cells provide a frame of reference for the analysis of delta, theta, beta, alpha (incl.mu), and gamma oscillations recorded in the space field of human performance. Based on recent neuronal models facilitating the distinction between the different dynamic regimes (selective gating and binding) in these different oscillations we suggest an integrated approach articulating together the classical biomechanical factors (3D movements and EMG) and the high-density EEG and ERP signals to allow finer mathematical analysis to optimize sport performance, such as microstates, coherency/directionality analysis and neural generators.

Brain Oscillations in Sport: Toward EEG Biomarkers of Performance

PubMed Central

Cheron, Guy; Petit, Géraldine; Cheron, Julian; Leroy, Axelle; Cebolla, Anita; Cevallos, Carlos; Petieau, Mathieu; Hoellinger, Thomas; Zarka, David; Clarinval, Anne-Marie; Dan, Bernard

2016-01-01

Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The non-invasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP) in sport. In this context, the hypotheses of unified brain rhythms and continuity between wake and sleep states should provide a functional template for EEG biomarkers in sport. The oscillations in the thalamo-cortical and hippocampal circuitry including the physiology of the place cells and the grid cells provide a frame of reference for the analysis of delta, theta, beta, alpha (incl.mu), and gamma oscillations recorded in the space field of human performance. Based on recent neuronal models facilitating the distinction between the different dynamic regimes (selective gating and binding) in these different oscillations we suggest an integrated approach articulating together the classical biomechanical factors (3D movements and EMG) and the high-density EEG and ERP signals to allow finer mathematical analysis to optimize sport performance, such as microstates, coherency/directionality analysis and neural generators. PMID:26955362

Quantitative Tissue Proteomics Analysis Reveals Versican as Potential Biomarker for Early-Stage Hepatocellular Carcinoma.

PubMed

Naboulsi, Wael; Megger, Dominik A; Bracht, Thilo; Kohl, Michael; Turewicz, Michael; Eisenacher, Martin; Voss, Don Marvin; Schlaak, Jörg F; Hoffmann, Andreas-Claudius; Weber, Frank; Baba, Hideo A; Meyer, Helmut E; Sitek, Barbara

2016-01-04

Hepatocellular carcinoma (HCC) is one of the most aggressive tumors, and the treatment outcome of this disease is improved when the cancer is diagnosed at an early stage. This requires biomarkers allowing an accurate and early tumor diagnosis. To identify potential markers for such applications, we analyzed a patient cohort consisting of 50 patients (50 HCC and 50 adjacent nontumorous tissue samples as controls) using two independent proteomics approaches. We performed label-free discovery analysis on 19 HCC and corresponding tissue samples. The data were analyzed considering events known to take place in early events of HCC development, such as abnormal regulation of Wnt/b-catenin and activation of receptor tyrosine kinases (RTKs). 31 proteins were selected for verification experiments. For this analysis, the second set of the patient cohort (31 HCC and corresponding tissue samples) was analyzed using selected (multiple) reaction monitoring (SRM/MRM). We present the overexpression of ATP-dependent RNA helicase (DDX39), Fibulin-5 (FBLN5), myristoylated alanine-rich C-kinase substrate (MARCKS), and Serpin H1 (SERPINH1) in HCC for the first time. We demonstrate Versican core protein (VCAN) to be significantly associated with well differentiated and low-stage HCC. We revealed for the first time the evidence of VCAN as a potential biomarker for early-HCC diagnosis.

Chemical Warfare Agent Operational Exposure Hazard Assessment Research: FY07 Report and Analysis

DTIC Science & Technology

2010-07-01

of the nerve agents sarin, soman, cyclohexylsarin, VX, and Russian VX in human urine using isotope-dilution gas chromatography-tandem mass...Needham L.L.; Barr, D.B. Quantitation of organophosphorous nerve agent metabolites in human urine using isotope dilution gas chromatography-tandem mass... nerve agents , VX, GB, or GF, and to determine lethal percutaneous (PC) levels of VX. Calibration of Physiologically-based pharmacokinetic biomarkers

MO-DE-303-03: Session on quantitative imaging for assessment of tumor response to radiation therapy

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

Bowen, S.

This session will focus on quantitative imaging for assessment of tumor response to radiation therapy. This is a technically challenging method to translate to practice in radiation therapy. In the new era of precision medicine, however, delivering the right treatment, to the right patient, and at the right time, can positively impact treatment choices and patient outcomes. Quantitative imaging provides the spatial sensitivity required by radiation therapy for precision medicine that is not available by other means. In this Joint ESTRO -AAPM Symposium, three leading-edge investigators will present specific motivations for quantitative imaging biomarkers in radiation therapy of esophageal, headmore » and neck, locally advanced non-small cell lung cancer, and hepatocellular carcinoma. Experiences with the use of dynamic contrast enhanced (DCE) MRI, diffusion- weighted (DW) MRI, PET/CT, and SPECT/CT will be presented. Issues covered will include: response prediction, dose-painting, timing between therapy and imaging, within-therapy biomarkers, confounding effects, normal tissue sparing, dose-response modeling, and association with clinical biomarkers and outcomes. Current information will be presented from investigational studies and clinical practice. Learning Objectives: Learn motivations for the use of quantitative imaging biomarkers for assessment of response to radiation therapy Review the potential areas of application in cancer therapy Examine the challenges for translation, including imaging confounds and paucity of evidence to date Compare exemplary examples of the current state of the art in DCE-MRI, DW-MRI, PET/CT and SPECT/CT imaging for assessment of response to radiation therapy Van der Heide: Research grants from the Dutch Cancer Society and the European Union (FP7) Bowen: RSNA Scholar grant.« less

Applying a radiomics approach to predict prognosis of lung cancer patients

NASA Astrophysics Data System (ADS)

Emaminejad, Nastaran; Yan, Shiju; Wang, Yunzhi; Qian, Wei; Guan, Yubao; Zheng, Bin

2016-03-01

Radiomics is an emerging technology to decode tumor phenotype based on quantitative analysis of image features computed from radiographic images. In this study, we applied Radiomics concept to investigate the association among the CT image features of lung tumors, which are either quantitatively computed or subjectively rated by radiologists, and two genomic biomarkers namely, protein expression of the excision repair cross-complementing 1 (ERCC1) genes and a regulatory subunit of ribonucleotide reductase (RRM1), in predicting disease-free survival (DFS) of lung cancer patients after surgery. An image dataset involving 94 patients was used. Among them, 20 had cancer recurrence within 3 years, while 74 patients remained DFS. After tumor segmentation, 35 image features were computed from CT images. Using the Weka data mining software package, we selected 10 non-redundant image features. Applying a SMOTE algorithm to generate synthetic data to balance case numbers in two DFS ("yes" and "no") groups and a leave-one-case-out training/testing method, we optimized and compared a number of machine learning classifiers using (1) quantitative image (QI) features, (2) subjective rated (SR) features, and (3) genomic biomarkers (GB). Data analyses showed relatively lower correlation among the QI, SR and GB prediction results (with Pearson correlation coefficients < 0.5 including between ERCC1 and RRM1 biomarkers). By using area under ROC curve as an assessment index, the QI, SR and GB based classifiers yielded AUC = 0.89+/-0.04, 0.73+/-0.06 and 0.76+/-0.07, respectively, which showed that all three types of features had prediction power (AUC>0.5). Among them, using QI yielded the highest performance.

Quantitative proteomic profiling of paired cancerous and normal colon epithelial cells isolated freshly from colorectal cancer patients.

PubMed

Tu, Chengjian; Mojica, Wilfrido; Straubinger, Robert M; Li, Jun; Shen, Shichen; Qu, Miao; Nie, Lei; Roberts, Rick; An, Bo; Qu, Jun

2017-05-01

The heterogeneous structure in tumor tissues from colorectal cancer (CRC) patients excludes an informative comparison between tumors and adjacent normal tissues. Here, we develop and apply a strategy to compare paired cancerous (CEC) versus normal (NEC) epithelial cells enriched from patients and discover potential biomarkers and therapeutic targets for CRC. CEC and NEC cells are respectively isolated from five different tumor and normal locations in the resected colon tissue from each patient (N = 12 patients) using an optimized epithelial cell adhesion molecule (EpCAM)-based enrichment approach. An ion current-based quantitative method is employed to perform comparative proteomic analysis for each patient. A total of 458 altered proteins that are common among >75% of patients are observed and selected for further investigation. Besides known findings such as deregulation of mitochondrial function, tricarboxylic acid cycle, and RNA post-transcriptional modification, functional analysis further revealed RAN signaling pathway, small nucleolar ribonucleoproteins (snoRNPs), and infection by RNA viruses are altered in CEC cells. A selection of the altered proteins of interest is validated by immunohistochemistry analyses. The informative comparison between matched CEC and NEC enhances our understanding of molecular mechanisms of CRC development and provides biomarker candidates and new pathways for therapeutic intervention. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Tissue-based quantitative proteome analysis of human hepatocellular carcinoma using tandem mass tags.

PubMed

Megger, Dominik Andre; Rosowski, Kristin; Ahrens, Maike; Bracht, Thilo; Eisenacher, Martin; Schlaak, Jörg F; Weber, Frank; Hoffmann, Andreas-Claudius; Meyer, Helmut E; Baba, Hideo A; Sitek, Barbara

2017-03-01

Human hepatocellular carcinoma (HCC) is a severe malignant disease, and accurate and reliable diagnostic markers are still needed. This study was aimed for the discovery of novel marker candidates by quantitative proteomics. Proteomic differences between HCC and nontumorous liver tissue were studied by mass spectrometry. Among several significantly upregulated proteins, translocator protein 18 (TSPO) and Ras-related protein Rab-1A (RAB1A) were selected for verification by immunohistochemistry in an independent cohort. For RAB1A, a high accuracy for the discrimination of HCC and nontumorous liver tissue was observed. RAB1A was verified to be a potent biomarker candidate for HCC.

Rapid and High-Throughput Detection and Quantitation of Radiation Biomarkers in Human and Nonhuman Primates by Differential Mobility Spectrometry-Mass Spectrometry

NASA Astrophysics Data System (ADS)

Chen, Zhidan; Coy, Stephen L.; Pannkuk, Evan L.; Laiakis, Evagelia C.; Hall, Adam B.; Fornace, Albert J.; Vouros, Paul

2016-10-01

Radiation exposure is an important public health issue due to a range of accidental and intentional threats. Prompt and effective large-scale screening and appropriate use of medical countermeasures (MCM) to mitigate radiation injury requires rapid methods for determining the radiation dose. In a number of studies, metabolomics has identified small-molecule biomarkers responding to the radiation dose. Differential mobility spectrometry-mass spectrometry (DMS-MS) has been used for similar compounds for high-throughput small-molecule detection and quantitation. In this study, we show that DMS-MS can detect and quantify two radiation biomarkers, trimethyl-L-lysine (TML) and hypoxanthine. Hypoxanthine is a human and nonhuman primate (NHP) radiation biomarker and metabolic intermediate, whereas TML is a radiation biomarker in humans but not in NHP, which is involved in carnitine synthesis. They have been analyzed by DMS-MS from urine samples after a simple strong cation exchange-solid phase extraction (SCX-SPE). The dramatic suppression of background and chemical noise provided by DMS-MS results in an approximately 10-fold reduction in time, including sample pretreatment time, compared with liquid chromatography-mass spectrometry (LC-MS). DMS-MS quantitation accuracy has been verified by validation testing for each biomarker. Human samples are not yet available, but for hypoxanthine, selected NHP urine samples (pre- and 7-d-post 10 Gy exposure) were analyzed, resulting in a mean change in concentration essentially identical to that obtained by LC-MS (fold-change 2.76 versus 2.59). These results confirm the potential of DMS-MS for field or clinical first-level rapid screening for radiation exposure.

Quantitative analysis of biological tissues using Fourier transform-second-harmonic generation imaging

NASA Astrophysics Data System (ADS)

Ambekar Ramachandra Rao, Raghu; Mehta, Monal R.; Toussaint, Kimani C., Jr.

2010-02-01

We demonstrate the use of Fourier transform-second-harmonic generation (FT-SHG) imaging of collagen fibers as a means of performing quantitative analysis of obtained images of selected spatial regions in porcine trachea, ear, and cornea. Two quantitative markers, preferred orientation and maximum spatial frequency are proposed for differentiating structural information between various spatial regions of interest in the specimens. The ear shows consistent maximum spatial frequency and orientation as also observed in its real-space image. However, there are observable changes in the orientation and minimum feature size of fibers in the trachea indicating a more random organization. Finally, the analysis is applied to a 3D image stack of the cornea. It is shown that the standard deviation of the orientation is sensitive to the randomness in fiber orientation. Regions with variations in the maximum spatial frequency, but with relatively constant orientation, suggest that maximum spatial frequency is useful as an independent quantitative marker. We emphasize that FT-SHG is a simple, yet powerful, tool for extracting information from images that is not obvious in real space. This technique can be used as a quantitative biomarker to assess the structure of collagen fibers that may change due to damage from disease or physical injury.

Quantitative twoplex glycan analysis using 12C6 and 13C6 stable isotope 2-aminobenzoic acid labelling and capillary electrophoresis mass spectrometry.

PubMed

Váradi, Csaba; Mittermayr, Stefan; Millán-Martín, Silvia; Bones, Jonathan

2016-12-01

Capillary electrophoresis (CE) offers excellent efficiency and orthogonality to liquid chromatographic (LC) separations for oligosaccharide structural analysis. Combination of CE with high resolution mass spectrometry (MS) for glycan analysis remains a challenging task due to the MS incompatibility of background electrolyte buffers and additives commonly used in offline CE separations. Here, a novel method is presented for the analysis of 2-aminobenzoic acid (2-AA) labelled glycans by capillary electrophoresis coupled to mass spectrometry (CE-MS). To ensure maximum resolution and excellent precision without the requirement for excessive analysis times, CE separation conditions including the concentration and pH of the background electrolyte, the effect of applied pressure on the capillary inlet and the capillary length were evaluated. Using readily available 12/13 C 6 stable isotopologues of 2-AA, the developed method can be applied for quantitative glycan profiling in a twoplex manner based on the generation of extracted ion electropherograms (EIE) for 12 C 6 'light' and 13 C 6 'heavy' 2-AA labelled glycan isotope clusters. The twoplex quantitative CE-MS glycan analysis platform is ideally suited for comparability assessment of biopharmaceuticals, such as monoclonal antibodies, for differential glycomic analysis of clinical material for potential biomarker discovery or for quantitative microheterogeneity analysis of different glycosylation sites within a glycoprotein. Additionally, due to the low injection volume requirements of CE, subsequent LC-MS analysis of the same sample can be performed facilitating the use of orthogonal separation techniques for structural elucidation or verification of quantitative performance.

Quantitative Serum Nuclear Magnetic Resonance Metabolomics in Large-Scale Epidemiology: A Primer on -Omic Technologies

PubMed Central

Kangas, Antti J; Soininen, Pasi; Lawlor, Debbie A; Davey Smith, George; Ala-Korpela, Mika

2017-01-01

Abstract Detailed metabolic profiling in large-scale epidemiologic studies has uncovered novel biomarkers for cardiometabolic diseases and clarified the molecular associations of established risk factors. A quantitative metabolomics platform based on nuclear magnetic resonance spectroscopy has found widespread use, already profiling over 400,000 blood samples. Over 200 metabolic measures are quantified per sample; in addition to many biomarkers routinely used in epidemiology, the method simultaneously provides fine-grained lipoprotein subclass profiling and quantification of circulating fatty acids, amino acids, gluconeogenesis-related metabolites, and many other molecules from multiple metabolic pathways. Here we focus on applications of magnetic resonance metabolomics for quantifying circulating biomarkers in large-scale epidemiology. We highlight the molecular characterization of risk factors, use of Mendelian randomization, and the key issues of study design and analyses of metabolic profiling for epidemiology. We also detail how integration of metabolic profiling data with genetics can enhance drug development. We discuss why quantitative metabolic profiling is becoming widespread in epidemiology and biobanking. Although large-scale applications of metabolic profiling are still novel, it seems likely that comprehensive biomarker data will contribute to etiologic understanding of various diseases and abilities to predict disease risks, with the potential to translate into multiple clinical settings. PMID:29106475

Quantitative analysis of N-glycans from human alfa-acid-glycoprotein using stable isotope labeling and zwitterionic hydrophilic interaction capillary liquid chromatography electrospray mass spectrometry as tool for pancreatic disease diagnosis.

PubMed

Giménez, Estela; Balmaña, Meritxell; Figueras, Joan; Fort, Esther; de Bolós, Carme; Sanz-Nebot, Victòria; Peracaula, Rosa; Rizzi, Andreas

2015-03-25

In this work we demonstrate the potential of glycan reductive isotope labeling (GRIL) using [(12)C]- and [(13)C]-coded aniline and zwitterionic hydrophilic interaction capillary liquid chromatography electrospray mass spectrometry (μZIC-HILIC-ESI-MS) for relative quantitation of glycosylation variants in selected glycoproteins present in samples from cancer patients. Human α1-acid-glycoprotein (hAGP) is an acute phase serum glycoprotein whose glycosylation has been described to be altered in cancer and chronic inflammation. However, it is not clear yet whether some particular glycans in hAGP can be used as biomarker for differentiating between these two pathologies. In this work, hAGP was isolated by immunoaffinity chromatography (IAC) from serum samples of healthy individuals and from those suffering chronic pancreatitis and different stages of pancreatic cancer, respectively. After de-N-glycosylation, relative quantitation of the hAGP glycans was carried out using stable isotope labeling and μZIC-HILIC-ESI-MS analysis. First, protein denaturing conditions prior to PNGase F digestion were optimized to achieve quantitative digestion yields, and the reproducibility of the established methodology was evaluated with standard hAGP. Then, the proposed method was applied to the analysis of the clinical samples (control vs. pathological). Pancreatic cancer samples clearly showed an increase in the abundance of fucosylated glycans as the stage of the disease increases and this was unlike to samples from chronic pancreatitis. The results gained here indicate the mentioned glycan in hAGP as a candidate structure worth to be corroborated by an extended study including more clinical cases; especially those with chronic pancreatitis and initial stages of pancreatic cancer. Importantly, the results demonstrate that the presented methodology combining an enrichment of a target protein by IAC with isotope coded relative quantitation of N-glycans can be successfully used for targeted glycomics studies. The methodology is assumed being suitable as well for other such studies aimed at finding novel cancer associated glycoprotein biomarkers. Copyright © 2015 Elsevier B.V. All rights reserved.

Biological and Dose Thresholds for an Early Genomic Biomarker of Liver Carcinogenesis in Mice.

EPA Science Inventory

Traditional data sources for cancer risk assessment are resource-intensive, retrospective, and not feasible for the vast majority of environmental chemicals. The use of quantitative short-term genomic biomarkers may streamline this process by providing protective limits for known...

Biological and Dose Thresholds for an Early Genomic Biomarker of Liver Carcinogenesis in Mice

EPA Science Inventory

Traditional data sources for cancer risk assessment are resource-intensive, retrospective, and not feasible for the vast majority of environmental chemicals. The use of quantitative short-term genomic biomarkers may streamline this process by providing protective limits for known...

Spot Sampling and Exposure Surrogate Selection as Sources of Bias in Environmental Epidemiology Studies

EPA Science Inventory

Spot measurements of chemical biomarkers are often used as quantitative exposure surrogates in environmental epidemiology studies. These measures can be expressed a number of different ways – for example, urinary biomarkers can be expressed in units of concentration (&micr...

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

PubMed

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

2017-01-01

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

ALA-induced PpIX spectroscopy for brain tumor image-guided surgery

NASA Astrophysics Data System (ADS)

Valdes, Pablo A.; Leblond, Frederic; Kim, Anthony; Harris, Brent T.; Wilson, Brian C.; Paulsen, Keith D.; Roberts, David W.

2011-03-01

Maximizing the extent of brain tumor resection correlates with improved survival and quality of life outcomes in patients. Optimal surgical resection requires accurate discrimination between normal and abnormal, cancerous tissue. We present our recent experience using quantitative optical spectroscopy in 5-aminolevulinic acid (ALA)-induced protoporphyrin IX (PpIX) fluorescence-guided resection. Exogenous administration of ALA leads to preferential accumulation in tumor tissue of the fluorescent compound, PpIX, which can be used for in vivo surgical guidance. Using the state of the art approach with a fluorescence surgical microscope, we have been able to visualize a subset of brain tumors, but the sensitivity and accuracy of fluorescence detection for tumor tissue with this system are low. To take full advantage of the biological selectivity of PpIX accumulation in brain tumors, we used a quantitative optical spectroscopy system for in vivo measurements of PpIX tissue concentrations. We have shown that, using our quantitative approach for determination of biomarker concentrations, ALA-induced PpIX fluorescence-guidance can achieve accuracies of greater than 90% for most tumor histologies. Here we show multivariate analysis of fluorescence and diffuse reflectance signals in brain tumors with comparable diagnostic performance to our previously reported quantitative approach. These results are promising, since they show that technological improvements in current fluorescence-guided surgical technologies and more biologically relevant approaches are required to take full advantage of fluorescent biomarkers, achieve better tumor identification, increase extent of resection, and subsequently, lead to improve survival and quality of life in patients.

Dose reconstruction for individuals exposed to ionizing radiation using chromosome painting

NASA Technical Reports Server (NTRS)

Lucas, J. N.; Cox, A. B. (Principal Investigator)

1997-01-01

To be most useful, a biomarker for dose reconstruction should employ an end point that is highly quantitative, stable with time and easily measured. Reciprocal translocations have been shown to be a promising biomarker that is linked to both prior exposure and risk, and they can be measured easily and quantitatively using fluorescence in situ hybridization. In contrast to other biomarkers that are available, the frequency of reciprocal translocations in individuals exposed to whole-body radiation is stable with time after exposure, has rather small interindividual variability and can be measured accurately at low levels of exposure. Results from recent studies demonstrate that measurements of reciprocal translocation frequencies, facilitated by chromosome painting, can be used to reconstruct radiation dose for individuals exposed in the distant past.

Dose reconstruction for individuals exposed to ionizing radiation using chromosome painting.

PubMed

Lucas, J N

1997-11-01

To be most useful, a biomarker for dose reconstruction should employ an end point that is highly quantitative, stable with time and easily measured. Reciprocal translocations have been shown to be a promising biomarker that is linked to both prior exposure and risk, and they can be measured easily and quantitatively using fluorescence in situ hybridization. In contrast to other biomarkers that are available, the frequency of reciprocal translocations in individuals exposed to whole-body radiation is stable with time after exposure, has rather small interindividual variability and can be measured accurately at low levels of exposure. Results from recent studies demonstrate that measurements of reciprocal translocation frequencies, facilitated by chromosome painting, can be used to reconstruct radiation dose for individuals exposed in the distant past.

Earth Mover's Distance (EMD): A True Metric for Comparing Biomarker Expression Levels in Cell Populations.

PubMed

Orlova, Darya Y; Zimmerman, Noah; Meehan, Stephen; Meehan, Connor; Waters, Jeffrey; Ghosn, Eliver E B; Filatenkov, Alexander; Kolyagin, Gleb A; Gernez, Yael; Tsuda, Shanel; Moore, Wayne; Moss, Richard B; Herzenberg, Leonore A; Walther, Guenther

2016-01-01

Changes in the frequencies of cell subsets that (co)express characteristic biomarkers, or levels of the biomarkers on the subsets, are widely used as indices of drug response, disease prognosis, stem cell reconstitution, etc. However, although the currently available computational "gating" tools accurately reveal subset frequencies and marker expression levels, they fail to enable statistically reliable judgements as to whether these frequencies and expression levels differ significantly between/among subject groups. Here we introduce flow cytometry data analysis pipeline which includes the Earth Mover's Distance (EMD) metric as solution to this problem. Well known as an informative quantitative measure of differences between distributions, we present three exemplary studies showing that EMD 1) reveals clinically-relevant shifts in two markers on blood basophils responding to an offending allergen; 2) shows that ablative tumor radiation induces significant changes in the murine colon cancer tumor microenvironment; and, 3) ranks immunological differences in mouse peritoneal cavity cells harvested from three genetically distinct mouse strains.

Quantification of the heterogeneity of prognostic cellular biomarkers in ewing sarcoma using automated image and random survival forest analysis.

PubMed

Bühnemann, Claudia; Li, Simon; Yu, Haiyue; Branford White, Harriet; Schäfer, Karl L; Llombart-Bosch, Antonio; Machado, Isidro; Picci, Piero; Hogendoorn, Pancras C W; Athanasou, Nicholas A; Noble, J Alison; Hassan, A Bassim

2014-01-01

Driven by genomic somatic variation, tumour tissues are typically heterogeneous, yet unbiased quantitative methods are rarely used to analyse heterogeneity at the protein level. Motivated by this problem, we developed automated image segmentation of images of multiple biomarkers in Ewing sarcoma to generate distributions of biomarkers between and within tumour cells. We further integrate high dimensional data with patient clinical outcomes utilising random survival forest (RSF) machine learning. Using material from cohorts of genetically diagnosed Ewing sarcoma with EWSR1 chromosomal translocations, confocal images of tissue microarrays were segmented with level sets and watershed algorithms. Each cell nucleus and cytoplasm were identified in relation to DAPI and CD99, respectively, and protein biomarkers (e.g. Ki67, pS6, Foxo3a, EGR1, MAPK) localised relative to nuclear and cytoplasmic regions of each cell in order to generate image feature distributions. The image distribution features were analysed with RSF in relation to known overall patient survival from three separate cohorts (185 informative cases). Variation in pre-analytical processing resulted in elimination of a high number of non-informative images that had poor DAPI localisation or biomarker preservation (67 cases, 36%). The distribution of image features for biomarkers in the remaining high quality material (118 cases, 104 features per case) were analysed by RSF with feature selection, and performance assessed using internal cross-validation, rather than a separate validation cohort. A prognostic classifier for Ewing sarcoma with low cross-validation error rates (0.36) was comprised of multiple features, including the Ki67 proliferative marker and a sub-population of cells with low cytoplasmic/nuclear ratio of CD99. Through elimination of bias, the evaluation of high-dimensionality biomarker distribution within cell populations of a tumour using random forest analysis in quality controlled tumour material could be achieved. Such an automated and integrated methodology has potential application in the identification of prognostic classifiers based on tumour cell heterogeneity.

MicroRNAs for Detection of Pancreatic Neoplasia

PubMed Central

Vila-Navarro, Elena; Vila-Casadesús, Maria; Moreira, Leticia; Duran-Sanchon, Saray; Sinha, Rupal; Ginés, Àngels; Fernández-Esparrach, Glòria; Miquel, Rosa; Cuatrecasas, Miriam; Castells, Antoni; Lozano, Juan José; Gironella, Meritxell

2017-01-01

Objective: The aim of our study was to analyze the miRNome of pancreatic ductal adenocarcinoma (PDAC) and its preneoplastic lesion intraductal papillary mucinous neoplasm (IPMN), to find new microRNA (miRNA)-based biomarkers for early detection of pancreatic neoplasia. Objective: Effective early detection methods for PDAC are needed. miRNAs are good biomarker candidates. Methods: Pancreatic tissues (n = 165) were obtained from patients with PDAC, IPMN, or from control individuals (C), from Hospital Clínic of Barcelona. Biomarker discovery was done using next-generation sequencing in a discovery set of 18 surgical samples (11 PDAC, 4 IPMN, 3 C). MiRNA validation was carried out by quantitative reverse transcriptase PCR in 2 different set of samples. Set 1—52 surgical samples (24 PDAC, 7 IPMN, 6 chronic pancreatitis, 15 C), and set 2—95 endoscopic ultrasound-guided fine-needle aspirations (60 PDAC, 9 IPMN, 26 C). Results: In all, 607 and 396 miRNAs were significantly deregulated in PDAC and IPMN versus C. Of them, 40 miRNAs commonly overexpressed in both PDAC and IPMN were selected for further validation. Among them, significant up-regulation of 31 and 30 miRNAs was confirmed by quantitative reverse transcriptase PCR in samples from set 1 and set 2, respectively. Conclusions: miRNome analysis shows that PDAC and IPMN have differential miRNA profiles with respect to C, with a large number of deregulated miRNAs shared by both neoplastic lesions. Indeed, we have identified and validated 30 miRNAs whose expression is significantly increased in PDAC and IPMN lesions. The feasibility of detecting these miRNAs in endoscopic ultrasound-guided fine-needle aspiration samples makes them good biomarker candidates for early detection of pancreatic cancer. PMID:27232245

Automated wholeslide analysis of multiplex-brightfield IHC images for cancer cells and carcinoma-associated fibroblasts

NASA Astrophysics Data System (ADS)

Lorsakul, Auranuch; Andersson, Emilia; Vega Harring, Suzana; Sade, Hadassah; Grimm, Oliver; Bredno, Joerg

2017-03-01

Multiplex-brightfield immunohistochemistry (IHC) staining and quantitative measurement of multiple biomarkers can support therapeutic targeting of carcinoma-associated fibroblasts (CAF). This paper presents an automated digitalpathology solution to simultaneously analyze multiple biomarker expressions within a single tissue section stained with an IHC duplex assay. Our method was verified against ground truth provided by expert pathologists. In the first stage, the automated method quantified epithelial-carcinoma cells expressing cytokeratin (CK) using robust nucleus detection and supervised cell-by-cell classification algorithms with a combination of nucleus and contextual features. Using fibroblast activation protein (FAP) as biomarker for CAFs, the algorithm was trained, based on ground truth obtained from pathologists, to automatically identify tumor-associated stroma using a supervised-generation rule. The algorithm reported distance to nearest neighbor in the populations of tumor cells and activated-stromal fibroblasts as a wholeslide measure of spatial relationships. A total of 45 slides from six indications (breast, pancreatic, colorectal, lung, ovarian, and head-and-neck cancers) were included for training and verification. CK-positive cells detected by the algorithm were verified by a pathologist with good agreement (R2=0.98) to ground-truth count. For the area occupied by FAP-positive cells, the inter-observer agreement between two sets of ground-truth measurements was R2=0.93 whereas the algorithm reproduced the pathologists' areas with R2=0.96. The proposed methodology enables automated image analysis to measure spatial relationships of cells stained in an IHC-multiplex assay. Our proof-of-concept results show an automated algorithm can be trained to reproduce the expert assessment and provide quantitative readouts that potentially support a cutoff determination in hypothesis testing related to CAF-targeting-therapy decisions.

Improvements to direct quantitative analysis of multiple microRNAs facilitating faster analysis.

PubMed

Ghasemi, Farhad; Wegman, David W; Kanoatov, Mirzo; Yang, Burton B; Liu, Stanley K; Yousef, George M; Krylov, Sergey N

2013-11-05

Studies suggest that patterns of deregulation in sets of microRNA (miRNA) can be used as cancer diagnostic and prognostic biomarkers. Establishing a "miRNA fingerprint"-based diagnostic technique requires a suitable miRNA quantitation method. The appropriate method must be direct, sensitive, capable of simultaneous analysis of multiple miRNAs, rapid, and robust. Direct quantitative analysis of multiple microRNAs (DQAMmiR) is a recently introduced capillary electrophoresis-based hybridization assay that satisfies most of these criteria. Previous implementations of the method suffered, however, from slow analysis time and required lengthy and stringent purification of hybridization probes. Here, we introduce a set of critical improvements to DQAMmiR that address these technical limitations. First, we have devised an efficient purification procedure that achieves the required purity of the hybridization probe in a fast and simple fashion. Second, we have optimized the concentrations of the DNA probe to decrease the hybridization time to 10 min. Lastly, we have demonstrated that the increased probe concentrations and decreased incubation time removed the need for masking DNA, further simplifying the method and increasing its robustness. The presented improvements bring DQAMmiR closer to use in a clinical setting.

Epileptogenic networks in nodular heterotopia: A stereoelectroencephalography study.

PubMed

Pizzo, Francesca; Roehri, Nicolas; Catenoix, Hélène; Medina, Samuel; McGonigal, Aileen; Giusiano, Bernard; Carron, Romain; Scavarda, Didier; Ostrowsky, Karine; Lepine, Anne; Boulogne, Sébastien; Scholly, Julia; Hirsch, Edouard; Rheims, Sylvain; Bénar, Christian-George; Bartolomei, Fabrice

2017-12-01

Defining the roles of heterotopic and normotopic cortex in the epileptogenic networks in patients with nodular heterotopia is challenging. To elucidate this issue, we compared heterotopic and normotopic cortex using quantitative signal analysis on stereoelectroencephalography (SEEG) recordings. Clinically relevant biomarkers of epileptogenicity during ictal (epileptogenicity index; EI) and interictal recordings (high-frequency oscillation and spike) were evaluated in 19 patients undergoing SEEG. These biomarkers were then compared between heterotopic cortex and neocortical regions. Seizures were classified as normotopic, heterotopic, or normoheterotopic according to respective values of quantitative analysis (EI ≥0.3). A total of 1,246 contacts were analyzed: 259 in heterotopic tissue (heterotopic cortex), 873 in neocortex in the same lobe of the lesion (local neocortex), and 114 in neocortex distant from the lesion (distant neocortex). No significant difference in EI values, high-frequency oscillations, and spike rate was found comparing local neocortex and heterotopic cortex at a patient level, but local neocortex appears more epileptogenic (p < 0.001) than heterotopic cortex analyzing EI values at a seizure level. According to EI values, seizures were mostly normotopic (48.5%) or normoheterotopic (45.5%); only 6% were purely heterotopic. A good long-term treatment response was obtained in only two patients after thermocoagulation and surgical disconnection. This is the first quantitative SEEG study providing insight into the mechanisms generating seizures in nodular heterotopia. We demonstrate that both the heterotopic lesion and particularly the normotopic cortex are involved in the epileptogenic network. This could open new perspectives on multitarget treatments, other than resective surgery, aimed at modifying the epileptic network. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Proteomic profiling of a mouse model of acute intestinal Apc deletion leads to identification of potential novel biomarkers of human colorectal cancer (CRC).

PubMed

Hammoudi, Abeer; Song, Fei; Reed, Karen R; Jenkins, Rosalind E; Meniel, Valerie S; Watson, Alastair J M; Pritchard, D Mark; Clarke, Alan R; Jenkins, John R

2013-10-25

Colorectal cancer (CRC) is the fourth most common cause of cancer-related death worldwide. Accurate non-invasive screening for CRC would greatly enhance a population's health. Adenomatous polyposis coli (Apc) gene mutations commonly occur in human colorectal adenomas and carcinomas, leading to Wnt signalling pathway activation. Acute conditional transgenic deletion of Apc in murine intestinal epithelium (AhCre(+)Apc(fl)(/)(fl)) causes phenotypic changes similar to those found during colorectal tumourigenesis. This study comprised a proteomic analysis of murine small intestinal epithelial cells following acute Apc deletion to identify proteins that show altered expression during human colorectal carcinogenesis, thus identifying proteins that may prove clinically useful as blood/serum biomarkers of colorectal neoplasia. Eighty-one proteins showed significantly increased expression following iTRAQ analysis, and validation of nine of these by Ingenuity Pathaway Analysis showed they could be detected in blood or serum. Expression was assessed in AhCre(+)Apc(fl)(/)(fl) small intestinal epithelium by immunohistochemistry, western blot and quantitative real-time PCR; increased nucelolin concentrations were also detected in the serum of AhCre(+)Apc(fl)(/)(fl) and Apc(Min)(/)(+) mice by ELISA. Six proteins; heat shock 60kDa protein 1, Nucleolin, Prohibitin, Cytokeratin 18, Ribosomal protein L6 and DEAD (Asp-Glu-Ala-Asp) box polypeptide 5,were selected for further investigation. Increased expression of 4 of these was confirmed in human CRC by qPCR. In conclusion, several novel candidate biomarkers have been identified from analysis of transgenic mice in which the Apc gene was deleted in the intestinal epithelium that also showed increased expression in human CRC. Some of these warrant further investigation as potential serum-based biomarkers of human CRC. Copyright © 2013 Elsevier Inc. All rights reserved.

MRI-Derived Cellularity Index as a Potential Noninvasive Imaging Biomarker of Prostate Cancer

DTIC Science & Technology

2016-12-01

whole mount pathology sections. Analysis of these UCLA data resulted in four published manuscripts (White et al, Cancer Research 2014; Rakow-Penner...Yamin et al., Clinical Cancer Research , 2016) RSI-MRI mean z-score grouped by pathologic Gleason grade. Mean RSI-MRI cellularity index represented as...Figure 2). A quantitative validation of this approach is now provided in this study. Specifically, in a group of patients with known PCa, ROC

Perturbations in the Urinary Exosome in Transplant Rejection

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

Sigdel, Tara K.; NG, Yolanda; Lee, Sangho

Background: Urine exosomes, vesicles exocytosed into urine by all renal epithelial cell types, occur under normal physiologic and disease states. Exosome contents may mirror disease-specific proteome perturbations in kidney injury. Analysis methodologies for the exosomal fraction of the urinary proteome were developed and for comparing the urinary exosomal fraction versus unfractionated proteome for biomarker discovery. Methods: Urine exosomes were isolated by centrifugal filtration from mid-stream, second morning void, urine samples collected from kidney transplant recipients with and without biopsy matched acute rejection. The proteomes of unfractionated whole urine (Uw) and urine exosomes (Uexo) underwent mass spectrometry-based quantitative proteomics analysis. Themore » proteome data were analyzed for significant differential protein abundances in acute rejection (AR). Results: Identifications of 1018 and 349 proteins, Uw and Uexo fractions, respectively, demonstrated a 279 protein overlap between the two urinary compartments with 25%(70) of overlapping proteins unique to Uexoand represented membrane bound proteins (p=9.31e-7). Of 349 urine exosomal proteins identified in transplant patients 220 were not previously identified in the normal urine exosomal fraction. Uexo proteins (11), functioning in the inflammatory / stress response, were more abundant in patients with biopsy-confirmed acute rejection, 3 of which were exclusive to Uexo. Uexo AR-specific biomarkers (8) were also detected in Uw, but since they were observed at significantly lower abundances in Uw, they were not significant for AR in Uw. Conclusions: A rapid urinary exosome isolation method and quantitative measurement of enriched Uexo proteins was applied. Urine proteins specific to the exosomal fraction were detected either in unfractionated urine (at low abundances) or by Uexo fraction analysis. Perturbed proteins in the exosomal compartment of urine collected from kidney transplant patients were specific to inflammatory responses, and were not observed in the Uexo fraction from normal healthy subjects. Uexo specific protein alterations in renal disease provide potential mechanistic insights and offer a unique panel of sensitive biomarkers for monitoring for acute transplant rejection.« less

Cell Electrical Impedance as a Novel Approach for Studies on Senescence Not Based on Biomarkers

PubMed Central

Cha, Jung-Joon; Park, Yangkyu; Yun, Joho; Kim, Hyeon Woo; Park, Chang-Ju; Kang, Giseok; Jung, Minhyun; Pak, Boryeong; Jin, Suk-Won

2016-01-01

Senescence of cardiac myocytes is frequently associated with heart diseases. To analyze senescence in cardiac myocytes, a number of biomarkers have been isolated. However, due to the complex nature of senescence, multiple markers are required for a single assay to accurately depict complex physiological changes associated with senescence. In single cells, changes in both cytoplasm and cell membrane during senescence can affect the changes in electrical impedance. Based on this phenomenon, we developed MEDoS, a novel microelectrochemical impedance spectroscopy for diagnosis of senescence, which allows us to precisely measure quantitative changes in electrical properties of aging cells. Using cardiac myocytes isolated from 3-, 6-, and 18-month-old isogenic zebrafish, we examined the efficacy of MEDoS and showed that MEDoS can identify discernible changes in electrical impedance. Taken together, our data demonstrated that electrical impedance in cells at different ages is distinct with quantitative values; these results were comparable with previously reported ones. Therefore, we propose that MEDoS be used as a new biomarker-independent methodology to obtain quantitative data on the biological senescence status of individual cells. PMID:27812531

Quantitative imaging biomarkers: a review of statistical methods for computer algorithm comparisons.

PubMed

Obuchowski, Nancy A; Reeves, Anthony P; Huang, Erich P; Wang, Xiao-Feng; Buckler, Andrew J; Kim, Hyun J Grace; Barnhart, Huiman X; Jackson, Edward F; Giger, Maryellen L; Pennello, Gene; Toledano, Alicia Y; Kalpathy-Cramer, Jayashree; Apanasovich, Tatiyana V; Kinahan, Paul E; Myers, Kyle J; Goldgof, Dmitry B; Barboriak, Daniel P; Gillies, Robert J; Schwartz, Lawrence H; Sullivan, Daniel C

2015-02-01

Quantitative biomarkers from medical images are becoming important tools for clinical diagnosis, staging, monitoring, treatment planning, and development of new therapies. While there is a rich history of the development of quantitative imaging biomarker (QIB) techniques, little attention has been paid to the validation and comparison of the computer algorithms that implement the QIB measurements. In this paper we provide a framework for QIB algorithm comparisons. We first review and compare various study designs, including designs with the true value (e.g. phantoms, digital reference images, and zero-change studies), designs with a reference standard (e.g. studies testing equivalence with a reference standard), and designs without a reference standard (e.g. agreement studies and studies of algorithm precision). The statistical methods for comparing QIB algorithms are then presented for various study types using both aggregate and disaggregate approaches. We propose a series of steps for establishing the performance of a QIB algorithm, identify limitations in the current statistical literature, and suggest future directions for research. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

A Method for Label-Free, Differential Top-Down Proteomics.

PubMed

Ntai, Ioanna; Toby, Timothy K; LeDuc, Richard D; Kelleher, Neil L

2016-01-01

Biomarker discovery in the translational research has heavily relied on labeled and label-free quantitative bottom-up proteomics. Here, we describe a new approach to biomarker studies that utilizes high-throughput top-down proteomics and is the first to offer whole protein characterization and relative quantitation within the same experiment. Using yeast as a model, we report procedures for a label-free approach to quantify the relative abundance of intact proteins ranging from 0 to 30 kDa in two different states. In this chapter, we describe the integrated methodology for the large-scale profiling and quantitation of the intact proteome by liquid chromatography-mass spectrometry (LC-MS) without the need for metabolic or chemical labeling. This recent advance for quantitative top-down proteomics is best implemented with a robust and highly controlled sample preparation workflow before data acquisition on a high-resolution mass spectrometer, and the application of a hierarchical linear statistical model to account for the multiple levels of variance contained in quantitative proteomic comparisons of samples for basic and clinical research.

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

PubMed

Song, Ehwang; Mechref, Yehia

2015-01-01

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

Validation of Biomarker Proteins Using Reverse Capture Protein Microarrays.

PubMed

Jozwik, Catherine; Eidelman, Ofer; Starr, Joshua; Pollard, Harvey B; Srivastava, Meera

2017-01-01

Genomics has revolutionized large-scale and high-throughput sequencing and has led to the discovery of thousands of new proteins. Protein chip technology is emerging as a miniaturized and highly parallel platform that is suited to rapid, simultaneous screening of large numbers of proteins and the analysis of various protein-binding activities, enzyme substrate relationships, and posttranslational modifications. Specifically, reverse capture protein microarrays provide the most appropriate platform for identifying low-abundance, disease-specific biomarker proteins in a sea of high-abundance proteins from biological fluids such as blood, serum, plasma, saliva, urine, and cerebrospinal fluid as well as tissues and cells obtained by biopsy. Samples from hundreds of patients can be spotted in serial dilutions on many replicate glass slides. Each slide can then be probed with one specific antibody to the biomarker of interest. That antibody's titer can then be determined quantitatively for each patient, allowing for the statistical assessment and validation of the diagnostic or prognostic utility of that particular antigen. As the technology matures and the availability of validated, platform-compatible antibodies increases, the platform will move further into the desirable realm of discovery science for detecting and quantitating low-abundance signaling proteins. In this chapter, we describe methods for the successful application of the reverse capture protein microarray platform for which we have made substantial contributions to the development and application of this method, particularly in the use of body fluids other than serum/plasma.

Functional Near-Infrared Spectroscopy Reveals Reduced Interhemispheric Cortical Communication after Pediatric Concussion

PubMed Central

Urban, Karolina J.; Barlow, Karen M.; Jimenez, Jon J.; Goodyear, Bradley G.

2015-01-01

Abstract Concussion, or mild traumatic brain injury (mTBI), is a growing concern, especially among the pediatric population. By age 25, as many as 30% of the population are likely to have had a concussion. Many result in long-term disability, with some evolving to postconcussion syndrome. Treatments are being developed, but are difficult to assess given the lack of measures to quantitatively monitor concussion. There is no accepted quantitative imaging metric for monitoring concussion. We hypothesized that because cognitive function and fiber tracks are often impacted in concussion, interhemispheric brain communication may be impaired. We used functional near-infrared spectroscopy (fNIRS) to quantify functional coherence between the left and right motor cortex as a marker of interhemispheric communication. Studies were undertaken during the resting state and with a finger-tapping task to activate the motor cortex. Pediatric patients (ages 12–18) had symptoms for 31–473 days, compared to controls, who have not had reported a previous concussion. We detected differences between patients and controls in coherence between the contralateral motor cortices using measurements of total hemoglobin and oxy-hemoglobin with a p<0.01 (n=8, control; n=12 mTBI). Given the critical need for a quantitative biomarker for recovery after a concussion, we present these data to highlight the potential of fNIRS coupled with interhemispheric coherence analysis as a biomarker of concussion injury. PMID:25387354

Anatomical location differences between mutated and wild-type isocitrate dehydrogenase 1 in low-grade gliomas.

PubMed

Yu, Jinhua; Shi, Zhifeng; Ji, Chunhong; Lian, Yuxi; Wang, Yuanyuan; Chen, Liang; Mao, Ying

2017-10-01

Anatomical location of gliomas has been considered as a factor implicating the contributions of a specific precursor cells during the tumor growth. Isocitrate dehydrogenase 1 (IDH1) is a pathognomonic biomarker with a significant impact on the development of gliomas and remarkable prognostic effect. The correlation between anatomical location of tumor and IDH1 states for low-grade gliomas was analyzed quantitatively in this study. Ninety-two patients diagnosed of low-grade glioma pathologically were recruited in this study, including 65 patients with IDH1-mutated glioma and 27 patients with wide-type IDH1. A convolutional neural network was designed to segment the tumor from three-dimensional magnetic resonance imaging images. Voxel-based lesion symptom mapping was then employed to study the tumor location distribution differences between gliomas with mutated and wild-type IDH1. In order to characterize the location differences quantitatively, the Automated Anatomical Labeling Atlas was used to partition the standard brain atlas into 116 anatomical volumes of interests (AVOIs). The percentages of tumors with different IDH1 states in 116 AVOIs were calculated and compared. Support vector machine and AdaBoost algorithms were used to estimate the IDH1 status based on the 116 location features of each patient. Experimental results proved that the quantitative tumor location measurement could be a very important group of imaging features in biomarker estimation based on radiomics analysis of glioma.

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

PubMed Central

Serkova, Natalie J.; Standiford, Theodore J.

2011-01-01

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

Metabolomic Changes in Rat Model of Cauda Equina Injury.

PubMed

Liu, Yang; Yang, Rui; Kong, Qingjie; Wang, Yuan; Zhang, Bin; Sun, Jingchuan; Yang, Yong; Zheng, Bing; Yuan, Hongbin; Shi, Jiangang

2017-06-01

To show the differences of metabolomic changes in a rat model of cauda equina injury (CEI) and find potent metabolic biomarkers of CEI. A total of 28 Sprague-Dawley rats were used in this study. After the rats were given anesthesia and fixed in a prone position, a piece of silicone block was placed into the epidural space below the lamina. Behavior tests including the Basso, Beattie, and Bresnahan open field locomotor scale and an inclined plane test were conducted 1 day and 2 days after surgery. The cauda equina tissue was collected 12 hours, 1 day, and 2 days after surgery. Ultraperformance liquid chromatography coupled with quadruple time-of-flight mass spectrometry was used for a quantitative analysis of cauda equine metabolic changes in rats from different groups. The differences between the metabolic profiles of the rats in 4 groups were analyzed using partial least squares discriminant analysis. In behavior tests and histologic analyses given 2 days after surgery, the animals showed remarkable organ dysfunction and pathologic damage. Metabolic profiles showed remarkable differences between the control and model groups. Thirty-four potential CEI metabolite biomarkers were identified between the control group and different time-point model groups. These potential biomarkers appeared in 15 metabolic pathways. Our results may improve the cause of CEI and provide a basis for clinical diagnosis and locating biomarkers in the early stages of the pathologic process of CEI. Copyright © 2017 Elsevier Inc. All rights reserved.

Assessment of DNA Damage and Telomerase Activity in Exfoliated Urinary Cells as Sensitive and Noninvasive Biomarkers for Early Diagnosis of Bladder Cancer in Ex-Workers of a Rubber Tyres Industry

PubMed Central

Pira, Enrico; Romano, Canzio; Fresegna, Anna Maria; Ciervo, Aureliano; Buresti, Giuliana; Zoli, Wainer; Calistri, Daniele

2014-01-01

The aim of the present study was to identify sensitive and noninvasive biomarkers of early carcinogenic effect at target organ to use in biomonitoring studies of workers at risk for previous occupational exposure to potential carcinogens. Standard urine cytology (Papanicolaou staining test), comet assay, and quantitative telomerase repeat amplification protocol (TRAP) assay were performed in 159 ex-rubber workers employed in tyres production and 97 unexposed subjects. In TRAP positive cases, a second level analysis using FISH (Urovysion) was done. Cystoscopy results were available for 11 individuals whose 6 FISH/TRAP/comet positive showed in 3 cases a dysplastic condition confirmed by biopsy, 1 comet positive resulted in infiltrating UBC to the biopsy and with hyperplasia and slight dysplasia to the urinary cytology, 1 comet positive resulted in papillary superficial UBC to the biopsy, 1 FISH/TRAP positive showed a normal condition, and 2 TRAP positive showed in one case a phlogosis condition. The results evidenced good concordance of TRAP, comet, and FISH assays as early biomarkers of procarcinogenic effect confirmed by the dysplastic condition and UBC found by cystoscopy-biopsy analysis. The analysis of these markers in urine cells could be potentially more accurate than conventional cytology in monitoring workers exposed to mixture of bladder potential carcinogens. PMID:24877087

Assessment of DNA damage and telomerase activity in exfoliated urinary cells as sensitive and noninvasive biomarkers for early diagnosis of bladder cancer in ex-workers of a rubber tyres industry.

PubMed

Cavallo, Delia; Casadio, Valentina; Bravaccini, Sara; Iavicoli, Sergio; Pira, Enrico; Romano, Canzio; Fresegna, Anna Maria; Maiello, Raffaele; Ciervo, Aureliano; Buresti, Giuliana; Zoli, Wainer; Calistri, Daniele

2014-01-01

The aim of the present study was to identify sensitive and noninvasive biomarkers of early carcinogenic effect at target organ to use in biomonitoring studies of workers at risk for previous occupational exposure to potential carcinogens. Standard urine cytology (Papanicolaou staining test), comet assay, and quantitative telomerase repeat amplification protocol (TRAP) assay were performed in 159 ex-rubber workers employed in tyres production and 97 unexposed subjects. In TRAP positive cases, a second level analysis using FISH (Urovysion) was done. Cystoscopy results were available for 11 individuals whose 6 FISH/TRAP/comet positive showed in 3 cases a dysplastic condition confirmed by biopsy, 1 comet positive resulted in infiltrating UBC to the biopsy and with hyperplasia and slight dysplasia to the urinary cytology, 1 comet positive resulted in papillary superficial UBC to the biopsy, 1 FISH/TRAP positive showed a normal condition, and 2 TRAP positive showed in one case a phlogosis condition. The results evidenced good concordance of TRAP, comet, and FISH assays as early biomarkers of procarcinogenic effect confirmed by the dysplastic condition and UBC found by cystoscopy-biopsy analysis. The analysis of these markers in urine cells could be potentially more accurate than conventional cytology in monitoring workers exposed to mixture of bladder potential carcinogens.

Porous Silicon Antibody Microarrays for Quantitative Analysis: Measurement of Free and Total PSA in Clinical Plasma Samples

PubMed Central

Tojo, Axel; Malm, Johan; Marko-Varga, György; Lilja, Hans; Laurell, Thomas

2014-01-01

The antibody microarrays have become widespread, but their use for quantitative analyses in clinical samples has not yet been established. We investigated an immunoassay based on nanoporous silicon antibody microarrays for quantification of total prostate-specific-antigen (PSA) in 80 clinical plasma samples, and provide quantitative data from a duplex microarray assay that simultaneously quantifies free and total PSA in plasma. To further develop the assay the porous silicon chips was placed into a standard 96-well microtiter plate for higher throughput analysis. The samples analyzed by this quantitative microarray were 80 plasma samples obtained from men undergoing clinical PSA testing (dynamic range: 0.14-44ng/ml, LOD: 0.14ng/ml). The second dataset, measuring free PSA (dynamic range: 0.40-74.9ng/ml, LOD: 0.47ng/ml) and total PSA (dynamic range: 0.87-295ng/ml, LOD: 0.76ng/ml), was also obtained from the clinical routine. The reference for the quantification was a commercially available assay, the ProStatus PSA Free/Total DELFIA. In an analysis of 80 plasma samples the microarray platform performs well across the range of total PSA levels. This assay might have the potential to substitute for the large-scale microtiter plate format in diagnostic applications. The duplex assay paves the way for a future quantitative multiplex assay, which analyses several prostate cancer biomarkers simultaneously. PMID:22921878

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

PubMed Central

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

2013-01-01

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

Prediction of Bacillus weihenstephanensis acid resistance: the use of gene expression patterns to select potential biomarkers.

PubMed

Desriac, N; Postollec, F; Coroller, L; Sohier, D; Abee, T; den Besten, H M W

2013-10-01

Exposure to mild stress conditions can activate stress adaptation mechanisms and provide cross-resistance towards otherwise lethal stresses. In this study, an approach was followed to select molecular biomarkers (quantitative gene expressions) to predict induced acid resistance after exposure to various mild stresses, i.e. exposure to sublethal concentrations of salt, acid and hydrogen peroxide during 5 min to 60 min. Gene expression patterns of unstressed and mildly stressed cells of Bacillus weihenstephanensis were correlated to their acid resistance (3D value) which was estimated after exposure to lethal acid conditions. Among the twenty-nine candidate biomarkers, 12 genes showed expression patterns that were correlated either linearly or non-linearly to acid resistance, while for the 17 other genes the correlation remains to be determined. The selected genes represented two types of biomarkers, (i) four direct biomarker genes (lexA, spxA, narL, bkdR) for which expression patterns upon mild stress treatment were linearly correlated to induced acid resistance; and (ii) nine long-acting biomarker genes (spxA, BcerKBAB4_0325, katA, trxB, codY, lacI, BcerKBAB4_1716, BcerKBAB4_2108, relA) which were transiently up-regulated during mild stress exposure and correlated to increased acid resistance over time. Our results highlight that mild stress induced transcripts can be linearly or non-linearly correlated to induced acid resistance and both approaches can be used to find relevant biomarkers. This quantitative and systematic approach opens avenues to select cellular biomarkers that could be incremented in mathematical models to predict microbial behaviour. Copyright © 2013 Elsevier B.V. All rights reserved.

Quantitative targeted proteomic analysis of potential markers of tyrosine kinase inhibitor (TKI) sensitivity in EGFR mutated lung adenocarcinoma.

PubMed

Awasthi, Shivangi; Maity, Tapan; Oyler, Benjamin L; Qi, Yue; Zhang, Xu; Goodlett, David R; Guha, Udayan

2018-04-13

Lung cancer causes the highest mortality among all cancers. Patients harboring kinase domain mutations in the epidermal growth factor receptor (EGFR) respond to EGFR tyrosine kinase inhibitors (TKIs), however, acquired resistance always develops. Moreover, 30-40% of patients with EGFR mutations exhibit primary resistance. Hence, there is an unmet need for additional biomarkers of TKI sensitivity that complement EGFR mutation testing and predict treatment response. We previously identified phosphopeptides whose phosphorylation is inhibited upon treatment with EGFR TKIs, erlotinib and afatinib in TKI sensitive cells, but not in resistant cells. These phosphosites are potential biomarkers of TKI sensitivity. Here, we sought to develop modified immuno-multiple reaction monitoring (immuno-MRM)-based quantitation assays for select phosphosites including EGFR-pY1197, pY1172, pY998, AHNAK-pY160, pY715, DAPP1-pY139, CAV1-pY14, INPPL1-pY1135, NEDD9-pY164, NF1-pY2579, and STAT5A-pY694. These sites were significantly hypophosphorylated by erlotinib and a 3rd generation EGFR TKI, osimertinib, in TKI-sensitive H3255 cells, which harbor the TKI-sensitizing EGFR L858R mutation. However, in H1975 cells, which harbor the TKI-resistant EGFR L858R/T790M mutant, osimertinib, but not erlotinib, could significantly inhibit phosphorylation of EGFR-pY-1197, STAT5A-pY694 and CAV1-pY14, suggesting these sites also predict response in TKI-resistant cells. We could further validate EGFR-pY-1197 as a biomarker of TKI sensitivity by developing a calibration curve-based modified immuno-MRM assay. In this report, we have shown the development and optimization of MRM assays coupled with global phosphotyrosine enrichment (modified immuno-MRM) for a list of 11 phosphotyrosine peptides. Our optimized assays identified the targets reproducibly in biological samples with good selectivity. We also developed and characterized quantitation methods to determine endogenous abundance of these targets and correlated the results of the relative quantification with amounts estimated from the calibration curves. This approach represents a way to validate and verify biomarker candidates discovered from large-scale global phospho-proteomics analysis. The application of these modified immuno-MRM assays in lung adenocarcinoma cells provides proof-of concept for the feasibility of clinical applications. These assays may be used in prospective clinical studies of EGFR TKI treatment of EGFR mutant lung cancer to correlate treatment response and other clinical endpoints. Copyright © 2018. Published by Elsevier B.V.

iTRAQ-based quantitative protein expression profiling and MRM verification of markers in type 2 diabetes.

PubMed

Kaur, Prabhjit; Rizk, Nasser M; Ibrahim, Sereen; Younes, Noura; Uppal, Arushi; Dennis, Kevin; Karve, Tejaswita; Blakeslee, Kenneth; Kwagyan, John; Zirie, Mahmoud; Ressom, Habtom W; Cheema, Amrita K

2012-11-02

The pathogenesis of Type 2 diabetes mellitus (T2DM) is complex owing to molecular heterogeneity in the afflicted population. Current diagnostic methods rely on blood glucose measurements, which are noninformative with respect to progression of the disease to other associated pathologies. Thus, predicting the risk and development of T2DM-related complications, such as cardiovascular disease, remains a major challenge. We have used a combination of quantitative methods for characterization of circulating serum biomarkers of T2DM using a cohort of nondiabetic control subjects (n = 76) and patients diagnosed with T2DM (n = 106). In this case-control study, the samples were randomly divided as training and validation data sets. In the first step, iTRAQ (isobaric tagging for relative and absolute quantification) based protein expression profiling was performed for identification of proteins displaying a significant differential expression in the two study groups. Five of these protein markers were selected for validation using multiple reaction-monitoring mass spectrometry (MRM-MS) and further confirmed with Western blot and QPCR analysis. Functional pathway analysis identified perturbations in lipid and small molecule metabolism as well as pathways that lead to disruption of glucose homeostasis and blood coagulation. These putative biomarkers may be clinically useful for subset stratification of T2DM patients as well as for the development of novel therapeutics targeting the specific pathology.

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

Liu, Xing; Xu, Yanli; Meng, Qian

Colorectal cancer (CRC) is one of the most common types of malignant tumor worldwide. Currently, although many researchers have been devoting themselves in CRC studies, the process of locating biomarkers for CRC early diagnosis and prognostic is still very slow. Using a centrifugal proteomic reactor-based proteomic analysis of minute amount of colonic biopsies by enteroscopy sampling, 2620 protein groups were quantified between cancer mucosa and adjacent normal colorectal mucosa. Of which, 403 protein groups were differentially expressed with statistic significance between cancer and normal tissues, including 195 up-regulated and 208 down-regulated proteins in cancer tissues. Three proteins (SOD3, PRELP andmore » NGAL) were selected for further Western blot validation. And the resulting Western blot experimental results were consistent with the quantitative proteomic data. SOD3 and PRELP are down-regulated in CRC mucosa comparing to adjacent normal tissue, while NGAL is up-regulated in CRC mucosa. In conclusion, the centrifugal proteomic reactor-based label-free quantitative proteomic approach provides a highly sensitive and powerful tool for analyzing minute protein sample from tiny colorectal biopsies, which may facilitate CRC biomarkers discovery for diagnoses and prognoses. -- Highlights: •Minute amount of colonic biopsies by endoscopy is suitable for proteomic analysis. •Centrifugal proteomic reactor can be used for processing tiny clinic biopsy sample. •SOD3 and PRELP are down-regulated in CRC, while NGAL is up-regulated in CRC.« less

Recent advances in simultaneous analysis of bisphenol A and its conjugates in human matrices: Exposure biomarker perspectives.

PubMed

Andra, Syam S; Austin, Christine; Yang, Juan; Patel, Dhavalkumar; Arora, Manish

2016-12-01

Human exposures to bisphenol A (BPA) has attained considerable global health attention and represents one of the leading environmental contaminants with potential adverse health effects including endocrine disruption. Current practice of measuring of exposure to BPA includes the measurement of unconjugated BPA (aglycone) and total (both conjugated and unconjugated) BPA; the difference between the two measurements leads to estimation of conjugated forms. However, the measurement of BPA as the end analyte leads to inaccurate estimates from potential interferences from background sources during sample collection and analysis. BPA glucuronides (BPAG) and sulfates (BPAS) represent better candidates for biomarkers of BPA exposure, since they require in vivo metabolism and are not prone to external contamination. In this work, the primary focus was to review the current state of the art in analytical methods available to quantitate BPA conjugates. The entire analytical procedure for the simultaneous extraction and detection of aglycone BPA and conjugates is covered, from sample pre-treatment, extraction, separation, ionization, and detection. Solid phase extraction coupled with liquid chromatograph and tandem mass spectrometer analysis provides the most sensitive detection and quantification of BPA conjugates. Discussed herein are the applications of BPA conjugates analysis in human exposure assessment studies. Measuring these potential biomarkers of BPA exposure has only recently become analytically feasible and there are limitations and challenges to overcome in biomonitoring studies. Copyright © 2016 Elsevier B.V. All rights reserved.

Targeted proteomic assays for quantitation of proteins identified by proteogenomic analysis of ovarian cancer

DOE PAGES

Song, Ehwang; Gao, Yuqian; Wu, Chaochao; ...

2017-07-19

Here, mass spectrometry (MS) based targeted proteomic methods such as selected reaction monitoring (SRM) are becoming the method of choice for preclinical verification of candidate protein biomarkers. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute has investigated the standardization and analytical validation of the SRM assays and demonstrated robust analytical performance on different instruments across different laboratories. An Assay Portal has also been established by CPTAC to provide the research community a resource consisting of large set of targeted MS-based assays, and a depository to share assays publicly, providing that assays meet the guidelines proposed bymore » CPTAC. Herein, we report 98 SRM assays covering 70 candidate protein biomarkers previously reported as associated with ovarian cancer that have been thoroughly characterized according to the CPTAC Assay Characterization Guidance Document. The experiments, methods and results for characterizing these SRM assays for their MS response, repeatability, selectivity, stability, and reproducible detection of endogenous analytes are described in detail.« less

A comparative analysis of high-throughput platforms for validation of a circulating microRNA signature in diabetic retinopathy.

PubMed

Farr, Ryan J; Januszewski, Andrzej S; Joglekar, Mugdha V; Liang, Helena; McAulley, Annie K; Hewitt, Alex W; Thomas, Helen E; Loudovaris, Tom; Kay, Thomas W H; Jenkins, Alicia; Hardikar, Anandwardhan A

2015-06-02

MicroRNAs are now increasingly recognized as biomarkers of disease progression. Several quantitative real-time PCR (qPCR) platforms have been developed to determine the relative levels of microRNAs in biological fluids. We systematically compared the detection of cellular and circulating microRNA using a standard 96-well platform, a high-content microfluidics platform and two ultra-high content platforms. We used extensive analytical tools to compute inter- and intra-run variability and concordance measured using fidelity scoring, coefficient of variation and cluster analysis. We carried out unprejudiced next generation sequencing to identify a microRNA signature for Diabetic Retinopathy (DR) and systematically assessed the validation of this signature on clinical samples using each of the above four qPCR platforms. The results indicate that sensitivity to measure low copy number microRNAs is inversely related to qPCR reaction volume and that the choice of platform for microRNA biomarker validation should be made based on the abundance of miRNAs of interest.

Enhanced sensitivity and multiplexing with 2D LC/MRM-MS and labeled standards for deeper and more comprehensive protein quantitation.

PubMed

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

2014-06-25

Mass spectrometry (MS)-based protein quantitation is increasingly being employed to verify candidate protein biomarkers. Multiple or selected reaction monitoring-mass spectrometry (MRM-MS or SRM-MS) with isotopically labeled internal standards has proven to be a successful approach in that regard, but has yet to reach its full potential in terms of multiplexing and sensitivity. Here, we report the development of a new MRM method for the quantitation of 253 disease-associated proteins (represented by 625 interference-free peptides) in 13 LC fractions. This 2D RPLC/MRM-MS approach extends the depth and breadth of the assay by 2 orders of magnitude over pre-fractionation-free assays, with 31 proteins below 10 ng/mL and 41 proteins above 10 ng/mL now quantifiable. Standard flow rates are used in both chromatographic dimensions, and up-front depletion or antibody-based enrichment is not required. The LC separations utilize high and low pH conditions, with the former employing an ammonium hydroxide-based eluent, instead of the conventional ammonium formate, resulting in improved LC column lifetime and performance. The high sensitivity (determined concentration range: 15 mg/mL to 452 pg/mL) and robustness afforded by this method makes the full MRM panel, or subsets thereof, useful for the verification of disease-associated plasma protein biomarkers in patient samples. The described research extends the breadth and depth of protein quantitation in undepleted and non-enriched human plasma by employing standard-flow 2D RPLC/MRM-MS in conjunction with a complex mixture of isotopically labeled peptide standards. The proteins quantified are mainly putative biomarkers of non-communicable (i.e., non-infectious) disease (e.g., cardiovascular or cancer), which require pre-clinical verification and validation before clinical implementation. Based on the enhanced sensitivity and multiplexing, this quantitative plasma proteomic method should prove useful in future candidate biomarker verification studies. Copyright © 2014 Elsevier B.V. All rights reserved.

Metagenomic analysis of faecal microbiome as a tool towards targeted non-invasive biomarkers for colorectal cancer.

PubMed

Yu, Jun; Feng, Qiang; Wong, Sunny Hei; Zhang, Dongya; Liang, Qiao Yi; Qin, Youwen; Tang, Longqing; Zhao, Hui; Stenvang, Jan; Li, Yanli; Wang, Xiaokai; Xu, Xiaoqiang; Chen, Ning; Wu, William Ka Kei; Al-Aama, Jumana; Nielsen, Hans Jørgen; Kiilerich, Pia; Jensen, Benjamin Anderschou Holbech; Yau, Tung On; Lan, Zhou; Jia, Huijue; Li, Junhua; Xiao, Liang; Lam, Thomas Yuen Tung; Ng, Siew Chien; Cheng, Alfred Sze-Lok; Wong, Vincent Wai-Sun; Chan, Francis Ka Leung; Xu, Xun; Yang, Huanming; Madsen, Lise; Datz, Christian; Tilg, Herbert; Wang, Jian; Brünner, Nils; Kristiansen, Karsten; Arumugam, Manimozhiyan; Sung, Joseph Jao-Yiu; Wang, Jun

2017-01-01

To evaluate the potential for diagnosing colorectal cancer (CRC) from faecal metagenomes. We performed metagenome-wide association studies on faecal samples from 74 patients with CRC and 54 controls from China, and validated the results in 16 patients and 24 controls from Denmark. We further validated the biomarkers in two published cohorts from France and Austria. Finally, we employed targeted quantitative PCR (qPCR) assays to evaluate diagnostic potential of selected biomarkers in an independent Chinese cohort of 47 patients and 109 controls. Besides confirming known associations of Fusobacterium nucleatum and Peptostreptococcus stomatis with CRC, we found significant associations with several species, including Parvimonas micra and Solobacterium moorei. We identified 20 microbial gene markers that differentiated CRC and control microbiomes, and validated 4 markers in the Danish cohort. In the French and Austrian cohorts, these four genes distinguished CRC metagenomes from controls with areas under the receiver-operating curve (AUC) of 0.72 and 0.77, respectively. qPCR measurements of two of these genes accurately classified patients with CRC in the independent Chinese cohort with AUC=0.84 and OR of 23. These genes were enriched in early-stage (I-II) patient microbiomes, highlighting the potential for using faecal metagenomic biomarkers for early diagnosis of CRC. We present the first metagenomic profiling study of CRC faecal microbiomes to discover and validate microbial biomarkers in ethnically different cohorts, and to independently validate selected biomarkers using an affordable clinically relevant technology. Our study thus takes a step further towards affordable non-invasive early diagnostic biomarkers for CRC from faecal samples. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

A Method for Identification and Analysis of Non-Overlapping Myeloid Immunophenotypes in Humans

PubMed Central

Gustafson, Michael P.; Lin, Yi; Maas, Mary L.; Van Keulen, Virginia P.; Johnston, Patrick B.; Peikert, Tobias; Gastineau, Dennis A.; Dietz, Allan B.

2015-01-01

The development of flow cytometric biomarkers in human studies and clinical trials has been slowed by inconsistent sample processing, use of cell surface markers, and reporting of immunophenotypes. Additionally, the function(s) of distinct cell types as biomarkers cannot be accurately defined without the proper identification of homogeneous populations. As such, we developed a method for the identification and analysis of human leukocyte populations by the use of eight 10-color flow cytometric protocols in combination with novel software analyses. This method utilizes un-manipulated biological sample preparation that allows for the direct quantitation of leukocytes and non-overlapping immunophenotypes. We specifically designed myeloid protocols that enable us to define distinct phenotypes that include mature monocytes, granulocytes, circulating dendritic cells, immature myeloid cells, and myeloid derived suppressor cells (MDSCs). We also identified CD123 as an additional distinguishing marker for the phenotypic characterization of immature LIN-CD33+HLA-DR- MDSCs. Our approach permits the comprehensive analysis of all peripheral blood leukocytes and yields data that is highly amenable for standardization across inter-laboratory comparisons for human studies. PMID:25799053

Peptide biomarkers as a way to determine meat authenticity.

PubMed

Sentandreu, Miguel Angel; Sentandreu, Enrique

2011-11-01

Meat fraud implies many illegal procedures affecting the composition of meat and meat products, something that is commonly done with the aim to increase profit. These practices need to be controlled by legal authorities by means of robust, accurate and sensitive methodologies capable to assure that fraudulent or accidental mislabelling does not arise. Common strategies traditionally used to assess meat authenticity have been based on methods such as chemometric analysis of a large set of data analysis, immunoassays or DNA analysis. The identification of peptide biomarkers specific of a particular meat species, tissue or ingredient by proteomic technologies constitutes an interesting and promising alternative to existing methodologies due to its high discriminating power, robustness and sensitivity. The possibility to develop standardized protein extraction protocols, together with the considerably higher resistance of peptide sequences to food processing as compared to DNA sequences, would overcome some of the limitations currently existing for quantitative determinations of highly processed food samples. The use of routine mass spectrometry equipment would make the technology suitable for control laboratories. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

PubMed

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

2016-11-30

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

Circulating microRNAs as novel biomarkers for bone diseases - Complex signatures for multifactorial diseases?

PubMed

Hackl, Matthias; Heilmeier, Ursula; Weilner, Sylvia; Grillari, Johannes

2016-09-05

Biomarkers are essential tools in clinical research and practice. Useful biomarkers must combine good measurability, validated association with biological processes or outcomes, and should support clinical decision making if used in clinical practice. Several types of validated biomarkers have been reported in the context of bone diseases. However, because these biomarkers face certain limitations there is an interest in the identification of novel biomarkers for bone diseases, specifically in those that are tightly linked to the disease pathology leading to increased fracture-risk. MicroRNAs (miRNAs) are the most abundant RNA species to be found in cell-free blood. Encapsulated within microvesicles or bound to proteins, circulating miRNAs are remarkably stable analytes that can be measured using gold-standard technologies such as quantitative polymerase-chain-reaction (qPCR). Nevertheless, the analysis of circulating miRNAs faces several pre-analytical as well as analytical challenges. From a biological view, there is accumulating evidence that miRNAs play essential roles in the regulation of various biological processes including bone homeostasis. Moreover, specific changes in miRNA transcription levels or miRNA secretory levels have been linked to the development and progression of certain bone diseases. Only recently, results from circulating miRNAs analysis in patients with osteopenia, osteoporosis and fragility fractures have been reported. By comparing these findings to studies on circulating miRNAs in cellular senescence and aging or muscle physiology and sarcopenia, several overlaps were observed. This suggests that signatures observed during osteoporosis might not be specific to the pathophysiology in bone, but rather integrate information from several tissue types. Despite these promising first data, more work remains to be done until circulating miRNAs can serve as established and robust diagnostic tools for bone diseases in clinical research, clinical routine and in personalized medicine. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

A survey of liquid chromatographic-mass spectrometric analysis of mercapturic acid biomarkers in occupational and environmental exposure monitoring.

PubMed

Mathias, Patricia I; B'Hymer, Clayton

2014-08-01

High-performance liquid chromatography/mass spectrometry (HPLC/MS) is sensitive and specific for targeted quantitative analysis and is readily utilized for small molecules from biological matrices. This brief review describes recent selected HPLC/MS methods for the determination of urinary mercapturic acids (mercapturates) which are useful as biomarkers in characterizing human exposure to electrophilic industrial chemicals in occupational and environmental studies. Electrophilic compounds owing to their reactivity are used in chemical and industrial processes. They are present in industrial emissions, are combustion products of fossil fuels, and are components in tobacco smoke. Their presence in both the industrial and general environments are of concern for human and environmental health. Urinary mercapturates which are the products of metabolic detoxification of reactive chemicals provide a non-invasive tool to investigate human exposure to electrophilic toxicants. Selected recent mercapturate quantification methods are summarized and specific cases are presented. The biological formation of mercapturates is introduced and their use as biomarkers of metabolic processing of electrophilic compounds is discussed. Also, the use of liquid chromatography/tandem mass spectrometry in simultaneous determinations of the mercapturates of multiple parent compounds in a single determination is considered, as well as future trends and limitations in this area of research. Published by Elsevier B.V.

Skeletal muscle magnetic resonance biomarkers correlate with function and sentinel events in Duchenne muscular dystrophy.

PubMed

Barnard, Alison M; Willcocks, Rebecca J; Finanger, Erika L; Daniels, Michael J; Triplett, William T; Rooney, William D; Lott, Donovan J; Forbes, Sean C; Wang, Dah-Jyuu; Senesac, Claudia R; Harrington, Ann T; Finkel, Richard S; Russman, Barry S; Byrne, Barry J; Tennekoon, Gihan I; Walter, Glenn A; Sweeney, H Lee; Vandenborne, Krista

2018-01-01

To provide evidence for quantitative magnetic resonance (qMR) biomarkers in Duchenne muscular dystrophy by investigating the relationship between qMR measures of lower extremity muscle pathology and functional endpoints in a large ambulatory cohort using a multicenter study design. MR spectroscopy and quantitative imaging were implemented to measure intramuscular fat fraction and the transverse magnetization relaxation time constant (T2) in lower extremity muscles of 136 participants with Duchenne muscular dystrophy. Measures were collected at 554 visits over 48 months at one of three imaging sites. Fat fraction was measured in the soleus and vastus lateralis using MR spectroscopy, while T2 was assessed using MRI in eight lower extremity muscles. Ambulatory function was measured using the 10m walk/run, climb four stairs, supine to stand, and six minute walk tests. Significant correlations were found between all qMR and functional measures. Vastus lateralis qMR measures correlated most strongly to functional endpoints (|ρ| = 0.68-0.78), although measures in other rapidly progressing muscles including the biceps femoris (|ρ| = 0.63-0.73) and peroneals (|ρ| = 0.59-0.72) also showed strong correlations. Quantitative MR biomarkers were excellent indicators of loss of functional ability and correlated with qualitative measures of function. A VL FF of 0.40 was an approximate lower threshold of muscle pathology associated with loss of ambulation. Lower extremity qMR biomarkers have a robust relationship to clinically meaningful measures of ambulatory function in Duchenne muscular dystrophy. These results provide strong supporting evidence for qMR biomarkers and set the stage for their potential use as surrogate outcomes in clinical trials.

Semi-Quantitative Imaging Biomarkers of Knee Osteoarthritis Progression: Data from the FNIH OA Biomarkers Consortium

PubMed Central

Collins, Jamie E.; Losina, Elena; Nevitt, Michael C.; Roemer, Frank W.; Guermazi, Ali; Lynch, John A.; Katz, Jeffrey N.; Kwoh, C. Kent; Kraus, Virginia B.; Hunter, David J.

2017-01-01

Objective To determine the association between changes in semi-quantitative knee MRI biomarkers over 24 months and radiographic and pain progression over 48 months in knees with mild to moderate osteoarthritis. Methods We undertook a nested case-control study as part of the Osteoarthritis Biomarkers Consortium Project. We built multivariable logistic regression models to examine the association between change over 24 months in semi-quantitative MR imaging markers and knee OA radiographic and pain progression. MRIs were read according to the MRI Osteoarthritis Knee Score (MOAKS) scoring system. We focused on changes in cartilage, osteophytes, meniscus, bone marrow lesions, Hoffa-synovitis, and synovitis-effusion. Results The most parsimonious model included changes in cartilage thickness and surface area, synovitis-effusion, Hoffa-synovitis, and meniscal morphology (C-statistic =0.740). Subjects with worsening cartilage thickness in 3+ subregions vs. no worsening had 2.8-fold (95% CI: 1.3 – 5.9) greater odds of being a case while subjects with worsening in cartilage surface area in 3+ subregions vs. no worsening had 2.4-fold (95% CI: 1.3 – 4.4) greater odds of being a case. Having worsening in any region in meniscal morphology was associated with a 2.2-fold (95%CI: 1.3 – 3.8) greater odds of being a case. Worsening synovitis-effusion (OR=2.7) and Hoffa-synovitis (OR=2.0) were also associated with greater odds of being a case. Conclusion Twenty-four-month change in cartilage thickness, cartilage surface area, synovitis-effusion, Hoffa-synovitis, and meniscal morphology were independently associated with OA progression, suggesting that they may serve as efficacy biomarkers in clinical trials of disease modifying interventions for knee OA. PMID:27111771

Quantitative imaging by pixel-based contrast-enhanced ultrasound reveals a linear relationship between synovial vascular perfusion and the recruitment of pathogenic IL-17A-F+IL-23+ CD161+ CD4+ T helper cells in psoriatic arthritis joints.

PubMed

Fiocco, Ugo; Stramare, Roberto; Martini, Veronica; Coran, Alessandro; Caso, Francesco; Costa, Luisa; Felicetti, Mara; Rizzo, Gaia; Tonietto, Matteo; Scanu, Anna; Oliviero, Francesca; Raffeiner, Bernd; Vezzù, Maristella; Lunardi, Francesca; Scarpa, Raffaele; Sacerdoti, David; Rubaltelli, Leopoldo; Punzi, Leonardo; Doria, Andrea; Grisan, Enrico

2017-02-01

To develop quantitative imaging biomarkers of synovial tissue perfusion by pixel-based contrast-enhanced ultrasound (CEUS), we studied the relationship between CEUS synovial vascular perfusion and the frequencies of pathogenic T helper (Th)-17 cells in psoriatic arthritis (PsA) joints. Eight consecutive patients with PsA were enrolled in this study. Gray scale CEUS evaluation was performed on the same joint immediately after joint aspiration, by automatic assessment perfusion data, using a new quantification approach of pixel-based analysis and the gamma-variate model. The set of perfusional parameters considered by the time intensity curve includes the maximum value (peak) of the signal intensity curve, the blood volume index or area under the curve, (BVI, AUC) and the contrast mean transit time (MTT). The direct ex vivo analysis of the frequencies of SF IL17A-F + CD161 + IL23 + CD4 + T cells subsets were quantified by fluorescence-activated cell sorter (FACS). In cross-sectional analyses, when tested for multiple comparison setting, a false discovery rate at 10%, a common pattern of correlations between CEUS Peak, AUC (BVI) and MTT parameters with the IL17A-F + IL23 + - IL17A-F + CD161 + - and IL17A-F + CD161 + IL23 + CD4 + T cells subsets, as well as lack of correlation between both peak and AUC values and both CD4 + T and CD4 + IL23 + T cells, was observed. The pixel-based CEUS assessment is a truly measure synovial inflammation, as a useful tool to develop quantitative imaging biomarker for monitoring target therapeutics in PsA.

Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

PubMed

Davatzikos, Christos; Rathore, Saima; Bakas, Spyridon; Pati, Sarthak; Bergman, Mark; Kalarot, Ratheesh; Sridharan, Patmaa; Gastounioti, Aimilia; Jahani, Nariman; Cohen, Eric; Akbari, Hamed; Tunc, Birkan; Doshi, Jimit; Parker, Drew; Hsieh, Michael; Sotiras, Aristeidis; Li, Hongming; Ou, Yangming; Doot, Robert K; Bilello, Michel; Fan, Yong; Shinohara, Russell T; Yushkevich, Paul; Verma, Ragini; Kontos, Despina

2018-01-01

The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer. CaPTk leverages the value of quantitative imaging analytics along with machine learning to derive phenotypic imaging signatures, based on two-level functionality. First, image analysis algorithms are used to extract comprehensive panels of diverse and complementary features, such as multiparametric intensity histogram distributions, texture, shape, kinetics, connectomics, and spatial patterns. At the second level, these quantitative imaging signatures are fed into multivariate machine learning models to produce diagnostic, prognostic, and predictive biomarkers. Results from clinical studies in three areas are shown: (i) computational neuro-oncology of brain gliomas for precision diagnostics, prediction of outcome, and treatment planning; (ii) prediction of treatment response for breast and lung cancer, and (iii) risk assessment for breast cancer.

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

PubMed

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

2013-01-01

RNA transcripts such as mRNA or microRNA are frequently used as biomarkers to determine disease state or response to therapy. Reverse transcription (RT) in combination with quantitative PCR (qPCR) has become the method of choice to quantify small amounts of such RNA molecules. In parallel with the democratization of RT-qPCR and its increasing use in biomedical research or biomarker discovery, we witnessed a growth in the number of gene expression data analysis methods. Most of these methods are based on the principle that the position of the amplification curve with respect to the cycle-axis is a measure for the initial target quantity: the later the curve, the lower the target quantity. However, most methods differ in the mathematical algorithms used to determine this position, as well as in the way the efficiency of the PCR reaction (the fold increase of product per cycle) is determined and applied in the calculations. Moreover, there is dispute about whether the PCR efficiency is constant or continuously decreasing. Together this has lead to the development of different methods to analyze amplification curves. In published comparisons of these methods, available algorithms were typically applied in a restricted or outdated way, which does not do them justice. Therefore, we aimed at development of a framework for robust and unbiased assessment of curve analysis performance whereby various publicly available curve analysis methods were thoroughly compared using a previously published large clinical data set (Vermeulen et al., 2009) [11]. The original developers of these methods applied their algorithms and are co-author on this study. We assessed the curve analysis methods' impact on transcriptional biomarker identification in terms of expression level, statistical significance, and patient-classification accuracy. The concentration series per gene, together with data sets from unpublished technical performance experiments, were analyzed in order to assess the algorithms' precision, bias, and resolution. While large differences exist between methods when considering the technical performance experiments, most methods perform relatively well on the biomarker data. The data and the analysis results per method are made available to serve as benchmark for further development and evaluation of qPCR curve analysis methods (http://qPCRDataMethods.hfrc.nl). Copyright © 2012 Elsevier Inc. All rights reserved.

An integrated proteomics and metabolomics approach for defining oncofetal biomarkers in the colorectal cancer.

PubMed

Ma, Yanlei; Zhang, Peng; Wang, Feng; Liu, Weijie; Yang, Jianjun; Qin, Huanlong

2012-04-01

The present study was designed to search for potential diagnostic biomarkers in the serum of colorectal cancer (CRC). CRC is the third most common cancer worldwide, and its prognosis is poor at early stages. A panel of novel biomarkers is urgently needed for early diagnosis of CRC. An integrated proteomics and metabolomics approach was performed to define oncofetal biomarkers in CRC by protein and metabolite profiling of serum samples from CRC patients, healthy control adults, and fetus. The differentially expressed proteins were identified by a 2-D DIGE (2-Dimensional Difference Gel Electrophoresis) coupled with a Finnigan LTQ-based proteomics approach. Meanwhile, the serum metabolome was analyzed using gas chromatography-mass spectrometry integrated with a commercial mass spectral library for peak identification. Of the 28 identified proteins and the 34 analyzed metabolites, only 5 protein spots and 6 metabolites were significantly increased or decreased in both CRC and fetal serum groups compared with the healthy adult group. Data from supervised predictive models allowed a separation of 93.5% of CRC patients from the healthy controls using the 6 metabolites. Finally, correlation analysis was applied to establish quantitative linkages between the 5 individual metabolite 3-hydroxybutyric acid, L-valine, L-threonine, 1-deoxyglucose, and glycine and the 5 individual proteins MACF1, APOH, A2M, IGL@, and VDB. Furthermore, 10 potential oncofetal biomarkers were characterized and their potential for CRC diagnosis was validated. The integrated approach we developed will promote the translation of biomarkers with clinical value into routine clinical practice.

Evaluation of miR-122 as a Serum Biomarker for Hepatotoxicity in Investigative Rat Toxicology Studies.

PubMed

Sharapova, T; Devanarayan, V; LeRoy, B; Liguori, M J; Blomme, E; Buck, W; Maher, J

2016-01-01

MicroRNAs are short noncoding RNAs involved in regulation of gene expression. Certain microRNAs, including miR-122, seem to have ideal properties as biomarkers due to good stability, high tissue specificity, and ease of detection across multiple species. Recent reports have indicated that miR-122 is a highly liver-specific marker detectable in serum after liver injury. The purpose of the current study was to assess the performance of miR-122 as a serum biomarker for hepatotoxicity in short-term (5-28 days) repeat-dose rat toxicology studies when benchmarked against routine clinical chemistry and histopathology. A total of 23 studies with multiple dose levels of experimental compounds were examined, and they included animals with or without liver injury and with various hepatic histopathologic changes. Serum miR-122 levels were quantified by reverse transcription quantitative polymerase chain reaction. Increases in circulating miR-122 levels highly correlated with serum elevations of liver enzymes, such as alanine aminotransferase (ALT), aspartate aminotransferase (AST) and glutamate dehydrogenase (GLDH). Statistical analysis showed that miR-122 outperformed ALT as a biomarker for histopathologically confirmed liver toxicity and was equivalent in performance to AST and GLDH. Additionally, an increase of 4% in predictive accuracy was obtained using a multiparameter approach incorporating miR-122 with ALT, AST, and GLDH. In conclusion, serum miR-122 levels can be utilized as a biomarker of hepatotoxicity in acute and subacute rat toxicology studies, and its performance can rival or exceed those of standard enzyme biomarkers such as the liver transaminases. © The Author(s) 2015.

Urinary vitamin D-binding protein, a novel biomarker for lupus nephritis, predicts the development of proteinuric flare.

PubMed

Go, D J; Lee, J Y; Kang, M J; Lee, E Y; Lee, E B; Yi, E C; Song, Y W

2018-01-01

Lupus nephritis (LN) is a major complication of systemic lupus erythematosus (SLE). Conventional biomarkers for assessing renal disease activity are imperfect in predicting clinical outcomes associated with LN. The aim of this study is to identify urinary protein biomarkers that reliably reflect the disease activity or predict clinical outcomes. A quantitative proteomic analysis was performed to identify protein biomarker candidates that can differentiate between SLE patients with and without LN. Selected biomarker candidates were further verified by enzyme-linked immunosorbent assay using urine samples from a larger cohort of SLE patients ( n = 121) to investigate their predictive values for LN activity measure. Furthermore, the association between urinary levels of a selected panel of potential biomarkers and prognosis of LN was assessed with a four-year follow-up study of renal outcomes. Urinary vitamin D-binding protein (VDBP), transthyretin (TTR), retinol binding protein 4 (RBP4), and prostaglandin D synthase (PTGDS) were significantly elevated in SLE patients with LN, especially in patients with active LN ( n = 21). Among them, VDBP well correlated with severity of proteinuria (rho = 0.661, p < 0.001) and renal SLE Disease Activity Index (renal SLEDAI) (rho = 0.520, p < 0.001). In the four-year follow-up, VDBP was a significant risk factor (hazard ratio 9.627, 95% confidence interval 1.698 to 54.571, p = 0.011) for the development of proteinuric flare in SLE patients without proteinuria ( n = 100) after adjustments for multiple confounders. Urinary VDBP correlated with proteinuria and renal SLEDAI, and predicted the development of proteinuria.

Assessment of the sources of sedimentary organic matter in the Bohai Sea and the northern Yellow Sea using biomarker proxies

NASA Astrophysics Data System (ADS)

Xing, Lei; Hou, Di; Wang, Xinchen; Li, Li; Zhao, Meixun

2016-07-01

To evaluate the applicability of source proxies and to assess the sources of sedimentary organic matter in the Bohai Sea (BS) and the northern Yellow Sea (NYS), we analyzed total organic carbon (TOC), total nitrogen (TN), δ13C of TOC, n-alkanes, phytoplankton biomarkers, and glycerol dialkyl glycerol tetraethers (GDGTs) including branched GDGTs (brGDGTs) in 60 surface sediment samples covering the BS and the NYS. Spatial distribution comparison and principal component analysis indicate that with the exception of brGDGTs, terrestrial biomarkers have different spatial distribution pattern from marine biomarkers, suggesting that the sources control the distributions of these biomarkers in spite of hydrodynamic forcing. Significantly positive correlation (R2 = 0.5) between TOC normalized brGDGTs content and TOC normalized crenarchaeol content suggested in situ production of brGDGTs in the BS and the NYS. The δ13C values, TMBR [terrestrial and marine biomarker ratio: (C27 + C29 + C31n-alkanes)/[(C27 + C29 + C31n-alkanes) + (brassicasterol + dinosterol + alkenones)] ] and BIT (branched isoprenoid tetratether index) proxy indicated high terrestrial organic matter (TOM) input near the Huanghe River Estuary, while TOC/TON did not reveal similar distribution pattern. Quantitative estimates of TOM using a binary model revealed much higher TOM percentage from δ13C (avg. 58%) and TMBR (avg. 31%) than from BIT (avg. 7.4%). Our results suggest that, owing to significant in situ production of brGDGTs, the BIT is not a good proxy for indicating soil OM contribution in marine sediments from the BS and the NYS.

A differential mobility spectrometry/mass spectrometry platform for the rapid detection and quantitation of DNA adduct dG-ABP.

PubMed

Kafle, Amol; Klaene, Joshua; Hall, Adam B; Glick, James; Coy, Stephen L; Vouros, Paul

2013-07-15

There is continued interest in exploring new analytical technologies for the detection and quantitation of DNA adducts, biomarkers which provide direct evidence of exposure and genetic damage in cells. With the goal of reducing clean-up steps and improving sample throughput, a Differential Mobility Spectrometry/Mass Spectrometry (DMS/MS) platform has been introduced for adduct analysis. A DMS/MS platform has been utilized for the analysis of dG-ABP, the deoxyguanosine adduct of the bladder carcinogen 4-aminobiphenyl (4-ABP). After optimization of the DMS parameters, each sample was analyzed in just 30 s following a simple protein precipitation step of the digested DNA. A detection limit of one modification in 10^6 nucleosides has been achieved using only 2 µg of DNA. A brief comparison (quantitative and qualitative) with liquid chromatography/mass spectrometry is also presented highlighting the advantages of using the DMS/MS method as a high-throughput platform. The data presented demonstrate the successful application of a DMS/MS/MS platform for the rapid quantitation of DNA adducts using, as a model analyte, the deoxyguanosine adduct of the bladder carcinogen 4-aminobiphenyl. Copyright © 2013 John Wiley & Sons, Ltd.

Use of MicroRNA biomarkers to distinguish enchondroma from low-grade chondrosarcoma.

PubMed

Zhang, Liang; Yang, Maozhou; Mayer, Theodore; Johnstone, Brian; Les, Clifford; Frisch, Nicholas; Parsons, Theodore; Mi, Qing-Sheng; Gibson, Gary

2017-03-01

Establishing a definitive diagnosis between benign enchondroma versus low-grade chondrosarcoma presents a potential challenge to both clinicians and pathologists. microRNAs (small non-coding RNAs) have proven to be effective biomarkers for the identification of tumors and tumor progression. We present analysis, both array and quantitative PCR, that shows consistently and substantially increased expression of two microRNAs, miRs-181a and -138, in low-grade chondrosarcomas compared with enchondromas. The data suggest these microRNAs would provide an analytical distinction between the chondrosarcoma and benign neoplasms that can be performed in formalin-fixed paraffin-embedded specimens. Together with recent publications, these data indicate that miRs-181a and -138 also play a role in tumor development and homeostasis and may provide new targets for the development of much needed therapeutic intervention.

Development of imaging biomarkers and generation of big data.

PubMed

Alberich-Bayarri, Ángel; Hernández-Navarro, Rafael; Ruiz-Martínez, Enrique; García-Castro, Fabio; García-Juan, David; Martí-Bonmatí, Luis

2017-06-01

Several image processing algorithms have emerged to cover unmet clinical needs but their application to radiological routine with a clear clinical impact is still not straightforward. Moving from local to big infrastructures, such as Medical Imaging Biobanks (millions of studies), or even more, Federations of Medical Imaging Biobanks (in some cases totaling to hundreds of millions of studies) require the integration of automated pipelines for fast analysis of pooled data to extract clinically relevant conclusions, not uniquely linked to medical imaging, but in combination to other information such as genetic profiling. A general strategy for the development of imaging biomarkers and their integration in the cloud for the quantitative management and exploitation in large databases is herein presented. The proposed platform has been successfully launched and is being validated nowadays among the early adopters' community of radiologists, clinicians, and medical imaging researchers.

Challenges and Opportunities for Extracting Cardiovascular Risk Biomarkers from Imaging Data

NASA Astrophysics Data System (ADS)

Kakadiaris, I. A.; Mendizabal-Ruiz, E. G.; Kurkure, U.; Naghavi, M.

Complications attributed to cardiovascular diseases (CDV) are the leading cause of death worldwide. In the United States, sudden heart attack remains the number one cause of death and accounts for the majority of the 280 billion burden of cardiovascular diseases. In spite of the advancements in cardiovascular imaging techniques, the rate of deaths due to unpredicted heart attack remains high. Thus, novel computational tools are of critical need, in order to mine quantitative parameters from the imaging data for early detection of persons with a high likelihood of developing a heart attack in the near future (vulnerable patients). In this paper, we present our progress in the research of computational methods for the extraction of cardiovascular risk biomarkers from cardiovascular imaging data. In particular, we focus on the methods developed for the analysis of intravascular ultrasound (IVUS) data.

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.

Alzheimer Disease: New Concepts on Its Neurobiology and the Clinical Role Imaging Will Play

PubMed Central

2012-01-01

Alzheimer disease (AD) is one of, if not the most, feared diseases associated with aging. The prevalence of AD increases exponentially with age after 60 years. Increasing life expectancy coupled with the absence of any approved disease-modifying therapies at present position AD as a dominant public health problem. Major advances have occurred in the development of disease biomarkers for AD in the past 2 decades. At present, the most well-developed AD biomarkers are the cerebrospinal fluid analytes amyloid-β 42 and tau and the brain imaging measures amyloid positron emission tomography (PET), fluorodeoxyglucose PET, and magnetic resonance imaging. CSF and imaging biomarkers are incorporated into revised diagnostic guidelines for AD, which have recently been updated for the first time since their original formulation in 1984. Results of recent studies suggest the possibility of an ordered evolution of AD biomarker abnormalities that can be used to stage the typical 20–30-year course of the disease. When compared with biomarkers in other areas of medicine, however, the absence of standardized quantitative metrics for AD imaging biomarkers constitutes a major deficiency. Failure to move toward a standardized system of quantitative metrics has substantially limited potential diagnostic usefulness of imaging in AD. This presents an important opportunity that, if widely embraced, could greatly expand the application of imaging to improve clinical diagnosis and the quality and efficiency of clinical trials. © RSNA, 2012 PMID:22517954

Current trends in quantitative proteomics - an update.

PubMed

Li, H; Han, J; Pan, J; Liu, T; Parker, C E; Borchers, C H

2017-05-01

Proteins can provide insights into biological processes at the functional level, so they are very promising biomarker candidates. The quantification of proteins in biological samples has been routinely used for the diagnosis of diseases and monitoring the treatment. Although large-scale protein quantification in complex samples is still a challenging task, a great amount of effort has been made to advance the technologies that enable quantitative proteomics. Seven years ago, in 2009, we wrote an article about the current trends in quantitative proteomics. In writing this current paper, we realized that, today, we have an even wider selection of potential tools for quantitative proteomics. These tools include new derivatization reagents, novel sampling formats, new types of analyzers and scanning techniques, and recently developed software to assist in assay development and data analysis. In this review article, we will discuss these innovative methods, and their current and potential applications in proteomics. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Methanospirillum respiratory mRNA biomarkers correlate with hydrogenotrophic methanogenesis rate during growth and competition for hydrogen in an organochlorine-respiring mixed culture.

PubMed

Rowe, Annette R; Mansfeldt, Cresten B; Heavner, Gretchen L; Richardson, Ruth E

2013-01-02

Molecular biomarkers hold promise for inferring rates of key metabolic activities in complex microbial systems. However, few studies have assessed biomarker levels for simultaneously occurring (and potentially competing) respirations. In this study, methanogenesis biomarkers for Methanospirillum hungatei were developed, tested, and compared to Dehalococcoides mccartyi biomarkers in a well-characterized mixed culture. Proteomic analyses of mixed culture samples (n = 4) confirmed expression of many M. hungatei methanogenesis enzymes. The mRNAs for two oxidoreductases detected were explored as quantitative biomarkers of hydrogenotrophic methanogenesis: a coenzyme F(420)-reducing hydrogenase (FrcA) and an iron sulfur protein (MvrD). As shown previously in D. mccartyi, M. hungatei transcript levels correlated linearly with measured (R = 0.97 for FrcA, R = 0.91 for MvrD; n = 7) or calculated respiration rate (R = 0.81 for FrcA, R = 0.62 for MvrD; n = 35) across two orders of magnitude on a log-log scale. The average abundance of MvrD transcripts was consistently two orders of magnitude lower than FrcA, regardless of experimental condition. In experiments where M. hungatei was competing for hydrogen with D. mccartyi, transcripts for the key respiratory hydrogenase HupL were generally less abundant per mL than FrcA and more abundant than MvrD. With no chlorinated electron acceptor added, HupL transcripts fell below both targets. These biomarkers hold promise for the prediction of in situ rates of respiration for these microbes, even when growing in mixed culture and utilizing a shared substrate which has important implications for both engineered and environmental systems. However, the differences in overall biomarker abundances suggest that the strength of any particular mRNA biomarker relies upon empirically established quantitative trends under a range of pertinent conditions.

Enzyme-Encapsulated Liposome-Linked Immunosorbent Assay Enabling Sensitive Personal Glucose Meter Readout for Portable Detection of Disease Biomarkers.

PubMed

Lin, Bingqian; Liu, Dan; Yan, Jinmao; Qiao, Zhi; Zhong, Yunxin; Yan, Jiawei; Zhu, Zhi; Ji, Tianhai; Yang, Chaoyong James

2016-03-23

There is considerable demand for sensitive, selective, and portable detection of disease-associated proteins, particularly in clinical practice and diagnostic applications. Portable devices are highly desired for detection of disease biomarkers in daily life due to the advantages of being simple, rapid, user-friendly, and low-cost. Herein we report an enzyme-encapsulated liposome-linked immunosorbent assay for sensitive detection of proteins using personal glucose meters (PGM) for portable quantitative readout. Liposomes encapsulating a large amount of amyloglucosidase or invertase are surface-coated with recognition elements such as aptamers or antibodies for target recognition. By translating molecular recognition signal into a large amount of glucose with the encapsulated enzyme, disease biomarkers such as thrombin or C-reactive protein (CRP) can be quantitatively detected by a PGM with a high detection limit of 1.8 or 0.30 nM, respectively. With the advantages of portability, ease of use, and low-cost, the method reported here has potential for portable and quantitative detection of various targets for different POC testing scenarios, such as rapid diagnosis in clinic offices, health monitoring at the bedside, and chemical/biochemical safety control in the field.

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

PubMed

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

2014-07-01

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

Diagnostics based on nucleic acid sequence variant profiling: PCR, hybridization, and NGS approaches.

PubMed

Khodakov, Dmitriy; Wang, Chunyan; Zhang, David Yu

2016-10-01

Nucleic acid sequence variations have been implicated in many diseases, and reliable detection and quantitation of DNA/RNA biomarkers can inform effective therapeutic action, enabling precision medicine. Nucleic acid analysis technologies being translated into the clinic can broadly be classified into hybridization, PCR, and sequencing, as well as their combinations. Here we review the molecular mechanisms of popular commercial assays, and their progress in translation into in vitro diagnostics. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

MRMer, an interactive open source and cross-platform system for data extraction and visualization of multiple reaction monitoring experiments.

PubMed

Martin, Daniel B; Holzman, Ted; May, Damon; Peterson, Amelia; Eastham, Ashley; Eng, Jimmy; McIntosh, Martin

2008-11-01

Multiple reaction monitoring (MRM) mass spectrometry identifies and quantifies specific peptides in a complex mixture with very high sensitivity and speed and thus has promise for the high throughput screening of clinical samples for candidate biomarkers. We have developed an interactive software platform, called MRMer, for managing highly complex MRM-MS experiments, including quantitative analyses using heavy/light isotopic peptide pairs. MRMer parses and extracts information from MS files encoded in the platform-independent mzXML data format. It extracts and infers precursor-product ion transition pairings, computes integrated ion intensities, and permits rapid visual curation for analyses exceeding 1000 precursor-product pairs. Results can be easily output for quantitative comparison of consecutive runs. Additionally MRMer incorporates features that permit the quantitative analysis experiments including heavy and light isotopic peptide pairs. MRMer is open source and provided under the Apache 2.0 license.

Biomass, community structure and nutritional status attributes of the deep subsurface microbiota---at Idaho and Hanford sites

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

White, D.C.; Ringelberg, D.B.

1991-10-28

The signature lipid biomarker technique based on phospholipid ester-linked fatty acid pattern analysis (PLFA) provides data on the total viable or potentially viable communities without the necessity of: (1) Quantitative recovery from the sediments or (2) The ability to culture the organisms. Analysis of PLFA provides evidence for the nutritional status (starvation and/or unbalanced growth) in situ. PLFA analysis of SSP samples from the INEL and PNL sites vadose zones showed higher biomass at the surface with prominent Actinomyces biomarkers with lower biomasses of stressed microbiota at progressively greater depth. The biomass and community diversity increased at the water tablemore » at both sites. Both these Western sites showed lower viable microbial biomasses than the WSRS samples. Cluster analysis of the total patterns from various sedimentary horizons showed three major consortia of microbes, with surface microbiota related at both sites, low viable biomass sites closely related at both sites, with anaerobic desaturase pathway being predominant at INEL and consortia utilizing predominantly branched saturated and the aerobic desaturase pathway at both sites. Preliminary examination of the consortia recovered from NTS show a clear relationship to water level.« less

To label or not to label: applications of quantitative proteomics in neuroscience research.

PubMed

Filiou, Michaela D; Martins-de-Souza, Daniel; Guest, Paul C; Bahn, Sabine; Turck, Christoph W

2012-02-01

Proteomics has provided researchers with a sophisticated toolbox of labeling-based and label-free quantitative methods. These are now being applied in neuroscience research where they have already contributed to the elucidation of fundamental mechanisms and the discovery of candidate biomarkers. In this review, we evaluate and compare labeling-based and label-free quantitative proteomic techniques for applications in neuroscience research. We discuss the considerations required for the analysis of brain and central nervous system specimens, the experimental design of quantitative proteomic workflows as well as the feasibility, advantages, and disadvantages of the available techniques for neuroscience-oriented questions. Furthermore, we assess the use of labeled standards as internal controls for comparative studies in humans and review applications of labeling-based and label-free mass spectrometry approaches in relevant model organisms and human subjects. Providing a comprehensive guide of feasible and meaningful quantitative proteomic methodologies for neuroscience research is crucial not only for overcoming current limitations but also for gaining useful insights into brain function and translating proteomics from bench to bedside. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Simultaneous Determination of Oxysterols, Cholesterol and 25-Hydroxy-Vitamin D3 in Human Plasma by LC-UV-MS

PubMed Central

Narayanaswamy, Rohini; Iyer, Vignesh; Khare, Prachi; Bodziak, Mary Lou; Badgett, Darlene; Zivadinov, Robert; Weinstock-Guttman, Bianca; Rideout, Todd C.; Ramanathan, Murali; Browne, Richard W.

2015-01-01

Background Oxysterols are promising biomarkers of neurodegenerative diseases that are linked with cholesterol and vitamin D metabolism. There is an unmet need for methods capable of sensitive, and simultaneous quantitation of multiple oxysterols, vitamin D and cholesterol pathway biomarkers. Methods A method for simultaneous determination of 5 major oxysterols, 25-hydroxy vitamin D3 and cholesterol in human plasma was developed. Total oxysterols were prepared by room temperature saponification followed by solid phase extraction from plasma spiked with deuterated internal standards. Oxysterols were resolved by reverse phase HPLC using a methanol/water/0.1% formic acid gradient. Oxysterols and 25-hydroxy vitamin D3 were detected with atmospheric pressure chemical ionization mass spectrometry in positive ion mode; in-series photodiode array detection at 204nm was used for cholesterol. Method validation studies were performed. Oxysterol levels in 220 plasma samples from healthy control subjects, multiple sclerosis and other neurological disorders patients were quantitated. Results Our method quantitated 5 oxysterols, cholesterol and 25-hydroxy vitamin D3 from 200 μL plasma in 35 minutes. Recoveries were >85% for all analytes and internal standards. The limits of detection were 3-10 ng/mL for oxysterols and 25-hydroxy vitamin D3 and 1 μg/mL for simultaneous detection of cholesterol. Analytical imprecision was <10 %CV for 24(S)-, 25-, 27-, 7α-hydroxycholesterol (HC) and cholesterol and ≤15 % for 7-keto-cholesterol. Multiple Sclerosis and other neurological disorder patients had lower 27-hydroxycholesterol levels compared to controls whereas 7α-hydroxycholesterol was lower specifically in Multiple Sclerosis. Conclusion The method is suitable for measuring plasma oxysterols levels in human health and disease. Analysis of human plasma indicates that the oxysterol, bile acid precursors 7α-hydroxycholesterol and 27-hydroxycholesterol are lower in Multiple Sclerosis and may serve as potential biomarkers of disease. PMID:25875771

Proteomic Analysis of Serum from Patients with Major Depressive Disorder to Compare Their Depressive and Remission Statuses

PubMed Central

Lee, Jiyeong; Joo, Eun-Jeong; Lim, Hee-Joung; Park, Jong-Moon; Lee, Kyu Young; Park, Arum; Seok, AeEun

2015-01-01

Objective Currently, there are a few biological markers to aid in the diagnosis and treatment of depression. However, it is not sufficient for diagnosis. We attempted to identify differentially expressed proteins during depressive moods as putative diagnostic biomarkers by using quantitative proteomic analysis of serum. Methods Blood samples were collected twice from five patients with major depressive disorder (MDD) at depressive status before treatment and at remission status during treatment. Samples were individually analyzed by liquid chromatography-tandem mass spectrometry for protein profiling. Differentially expressed proteins were analyzed by label-free quantification. Enzyme-linked immunosorbent assay (ELISA) results and receiver-operating characteristic (ROC) curves were used to validate the differentially expressed proteins. For validation, 8 patients with MDD including 3 additional patients and 8 matched normal controls were analyzed. Results The quantitative proteomic studies identified 10 proteins that were consistently upregulated or downregulated in 5 MDD patients. ELISA yielded results consistent with the proteomic analysis for 3 proteins. Expression levels were significantly different between normal controls and MDD patients. The 3 proteins were ceruloplasmin, inter-alpha-trypsin inhibitor heavy chain H4 and complement component 1qC, which were upregulated during the depressive status. The depressive status could be distinguished from the euthymic status from the ROC curves for these proteins, and this discrimination was enhanced when all 3 proteins were analyzed together. Conclusion This is the first proteomic study in MDD patients to compare intra-individual differences dependent on mood. This technique could be a useful approach to identify MDD biomarkers, but requires additional proteomic studies for validation. PMID:25866527

Relative quantitation of glycoisoforms of intact apolipoprotein C3 in human plasma by liquid chromatography-high-resolution mass spectrometry.

PubMed

Jian, Wenying; Edom, Richard W; Wang, Dai; Weng, Naidong; Zhang, Stanley Weihua

2013-03-05

Glycosylation is one of the most important post-translational modifications to mammalian proteins. Distribution of different glycoisoforms of certain proteins may reflect disease conditions and, therefore, can potentially be utilized as biomarkers. Apolipoprotein C3 (ApoC3) is one of the many plasma glycoproteins extensively studied for association with disease states. ApoC3 exists in three main glycoisoforms, including ApoC3-1 and ApoC3-2, which contain an O-linked carbohydrate moiety consisting of three and four monosaccharide residues, respectively, and ApoC3-0 that lacks the entire glycosylation chain. Changes in the ratio of different glycoisoforms of ApoC3 have been observed in pathological conditions such as kidney disease, liver disease, and diabetes. They may provide important information for diagnosis, prognosis, and evaluation of therapeutic response for metabolic conditions. In this current work, a liquid chromatography (LC)-high-resolution (HR) time-of-flight (TOF) mass spectrometry (MS) method was developed for relative quantitation of different glycoisoforms of intact ApoC3 in human plasma. The samples were processed using a solid-phase extraction (SPE) method and then subjected to LC-full scan HRMS analysis. Isotope peaks for each targeted glycoisoform at two charge states were extracted using a window of 50 mDa and integrated into a chromatographic peak. The peak area ratios of ApoC3-1/ApoC3-0 and ApoC3-2/ApoC3-0 were calculated and evaluated for assay performance. The results indicated that the ratio can be determined with excellent reproducibility in multiple subjects. It has also been observed that the ratios remained constant in plasma exposed to room temperature, freeze-thaw cycles, and long-term frozen storage. The method was applied in preliminary biomarker research of diabetes by analyzing plasma samples collected from normal, prediabetic, and diabetic subjects. Significant differences were revealed in the ApoC3-1/ApoC3-0 ratio and in the ApoC3-2/ApoC3-0 ratio among the three groups. The workflow of intact protein analysis using full scan HRMS established in this current work can be potentially extended to relative quantitation of other glycosylated proteins. To our best knowledge, this is the first time that a systematic approach of relative quantitation of targeted intact protein glycoisoforms using LC-MS has been established and utilized in biomarker research.

Transcriptome discovery in non-model wild fish species for the development of quantitative transcript abundance assays

USGS Publications Warehouse

Hahn, Cassidy M.; Iwanowicz, Luke R.; Cornman, Robert S.; Mazik, Patricia M.; Blazer, Vicki S.

2016-01-01

Environmental studies increasingly identify the presence of both contaminants of emerging concern (CECs) and legacy contaminants in aquatic environments; however, the biological effects of these compounds on resident fishes remain largely unknown. High throughput methodologies were employed to establish partial transcriptomes for three wild-caught, non-model fish species; smallmouth bass (Micropterus dolomieu), white sucker (Catostomus commersonii) and brown bullhead (Ameiurus nebulosus). Sequences from these transcriptome databases were utilized in the development of a custom nCounter CodeSet that allowed for direct multiplexed measurement of 50 transcript abundance endpoints in liver tissue. Sequence information was also utilized in the development of quantitative real-time PCR (qPCR) primers. Cross-species hybridization allowed the smallmouth bass nCounter CodeSet to be used for quantitative transcript abundance analysis of an additional non-model species, largemouth bass (Micropterus salmoides). We validated the nCounter analysis data system with qPCR for a subset of genes and confirmed concordant results. Changes in transcript abundance biomarkers between sexes and seasons were evaluated to provide baseline data on transcript modulation for each species of interest.

Image segmentation evaluation for very-large datasets

NASA Astrophysics Data System (ADS)

Reeves, Anthony P.; Liu, Shuang; Xie, Yiting

2016-03-01

With the advent of modern machine learning methods and fully automated image analysis there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. Current approaches of visual inspection and manual markings do not scale well to big data. We present a new approach that depends on fully automated algorithm outcomes for segmentation documentation, requires no manual marking, and provides quantitative evaluation for computer algorithms. The documentation of new image segmentations and new algorithm outcomes are achieved by visual inspection. The burden of visual inspection on large datasets is minimized by (a) customized visualizations for rapid review and (b) reducing the number of cases to be reviewed through analysis of quantitative segmentation evaluation. This method has been applied to a dataset of 7,440 whole-lung CT images for 6 different segmentation algorithms designed to fully automatically facilitate the measurement of a number of very important quantitative image biomarkers. The results indicate that we could achieve 93% to 99% successful segmentation for these algorithms on this relatively large image database. The presented evaluation method may be scaled to much larger image databases.

A novel image-based quantitative method for the characterization of NETosis

PubMed Central

Zhao, Wenpu; Fogg, Darin K.; Kaplan, Mariana J.

2015-01-01

NETosis is a newly recognized mechanism of programmed neutrophil death. It is characterized by a stepwise progression of chromatin decondensation, membrane rupture, and release of bactericidal DNA-based structures called neutrophil extracellular traps (NETs). Conventional ‘suicidal’ NETosis has been described in pathogenic models of systemic autoimmune disorders. Recent in vivo studies suggest that a process of ‘vital’ NETosis also exists, in which chromatin is condensed and membrane integrity is preserved. Techniques to assess ‘suicidal’ or ‘vital’ NET formation in a specific, quantitative, rapid and semiautomated way have been lacking, hindering the characterization of this process. Here we have developed a new method to simultaneously assess both ‘suicidal’ and ‘vital’ NETosis, using high-speed multi-spectral imaging coupled to morphometric image analysis, to quantify spontaneous NET formation observed ex-vivo or stimulus-induced NET formation triggered in vitro. Use of imaging flow cytometry allows automated, quantitative and rapid analysis of subcellular morphology and texture, and introduces the potential for further investigation using NETosis as a biomarker in pre-clinical and clinical studies. PMID:26003624

T1, diffusion tensor, and quantitative magnetization transfer imaging of the hippocampus in an Alzheimer's disease mouse model.

PubMed

Whittaker, Heather T; Zhu, Shenghua; Di Curzio, Domenico L; Buist, Richard; Li, Xin-Min; Noy, Suzanna; Wiseman, Frances K; Thiessen, Jonathan D; Martin, Melanie

2018-07-01

Alzheimer's disease (AD) pathology causes microstructural changes in the brain. These changes, if quantified with magnetic resonance imaging (MRI), could be studied for use as an early biomarker for AD. The aim of our study was to determine if T 1 relaxation, diffusion tensor imaging (DTI), and quantitative magnetization transfer imaging (qMTI) metrics could reveal changes within the hippocampus and surrounding white matter structures in ex vivo transgenic mouse brains overexpressing human amyloid precursor protein with the Swedish mutation. Delineation of hippocampal cell layers using DTI color maps allows more detailed analysis of T 1 -weighted imaging, DTI, and qMTI metrics, compared with segmentation of gross anatomy based on relaxation images, and with analysis of DTI or qMTI metrics alone. These alterations are observed in the absence of robust intracellular Aβ accumulation or plaque deposition as revealed by histology. This work demonstrates that multiparametric quantitative MRI methods are useful for characterizing changes within the hippocampal substructures and surrounding white matter tracts of mouse models of AD. Copyright © 2018. Published by Elsevier Inc.

Comparative biomarker expression and RNA integrity in biospecimens derived from radical retropubic and robot-assisted laparoscopic prostatectomies.

PubMed

Ricciardelli, Carmela; Bianco-Miotto, Tina; Jindal, Shalini; Dodd, Thomas J; Cohen, Penelope A; Marshall, Villis R; Sutherland, Peter D; Samaratunga, Hemamali; Kench, James G; Dong, Ying; Wang, Hong; Clements, Judith A; Risbridger, Gail P; Sutherland, Robert L; Tilley, Wayne D; Horsfall, David J

2010-07-01

Knowledge of preanalytic conditions that biospecimens are subjected to is critically important because novel surgical procedures, tissue sampling, handling, and storage might affect biomarker expression or invalidate tissue samples as analytes for some technologies. We investigated differences in RNA quality, gene expression by quantitative real-time PCR, and immunoreactive protein expression of selected prostate cancer biomarkers between tissues from retropubic radical prostatectomy (RRP) and robot-assisted laparoscopic prostatectomy (RALP). Sections of tissue microarray of 23 RALP and 22 RRP samples were stained with antibodies to androgen receptor (AR) and prostate-specific antigen (PSA) as intersite controls, and 14 other candidate biomarkers of research interest to three laboratories within the Australian Prostate Cancer BioResource tissue banking network. Quantitative real-time PCR was done for AR, PSA (KLK3), KLK2, KLK4, and HIF1A on RNA extracted from five RALP and five RRP frozen tissue cores. No histologic differences were observed between RALP and RRP tissue. Biomarker staining grouped these samples into those with increased (PSA, CK8/18, CKHMW, KLK4), decreased (KLK2, KLK14), or no change in expression (AR, ghrelin, Ki67, PCNA, VEGF-C, PAR2, YB1, p63, versican, and chondroitin 0-sulfate) in RALP compared with RRP tissue. No difference in RNA quality or gene expression was detected between RALP and RRP tissue. Changes in biomarker expression between RALP and RRP tissue exist at the immunoreactive protein level, but the etiology is unclear. Future studies should account for changes in biomarker expression when using RALP tissues, and mixed cohorts of RALP and RRP tissue should be avoided.

Searching for biomarkers of CDKL5 disorder: early-onset visual impairment in CDKL5 mutant mice

PubMed Central

Mazziotti, Raffaele; Lupori, Leonardo; Sagona, Giulia; Gennaro, Mariangela; Della Sala, Grazia; Putignano, Elena

2017-01-01

Abstract CDKL5 disorder is a neurodevelopmental disorder still without a cure. Murine models of CDKL5 disorder have been recently generated raising the possibility of preclinical testing of treatments. However, unbiased, quantitative biomarkers of high translational value to monitor brain function are still missing. Moreover, the analysis of treatment is hindered by the challenge of repeatedly and non-invasively testing neuronal function. We analyzed the development of visual responses in a mouse model of CDKL5 disorder to introduce visually evoked responses as a quantitative method to assess cortical circuit function. Cortical visual responses were assessed in CDKL5 null male mice, heterozygous females, and their respective control wild-type littermates by repeated transcranial optical imaging from P27 until P32. No difference between wild-type and mutant mice was present at P25-P26 whereas defective responses appeared from P27-P28 both in heterozygous and homozygous CDKL5 mutant mice. These results were confirmed by visually evoked potentials (VEPs) recorded from the visual cortex of a different cohort. The previously imaged mice were also analyzed at P60–80 using VEPs, revealing a persistent reduction of response amplitude, reduced visual acuity and defective contrast function. The level of adult impairment was significantly correlated with the reduction in visual responses observed during development. Support vector machine showed that multi-dimensional visual assessment can be used to automatically classify mutant and wt mice with high reliability. Thus, monitoring visual responses represents a promising biomarker for preclinical and clinical studies on CDKL5 disorder. PMID:28369421

Cell-based quantification of biomarkers from an ultra-fast microfluidic immunofluorescent staining: application to human breast cancer cell lines

NASA Astrophysics Data System (ADS)

Migliozzi, D.; Nguyen, H. T.; Gijs, M. A. M.

2018-02-01

Immunohistochemistry (IHC) is one of the main techniques currently used in the clinics for biomarker characterization. It consists in colorimetric labeling with specific antibodies followed by microscopy analysis. The results are then used for diagnosis and therapeutic targeting. Well-known drawbacks of such protocols are their limited accuracy and precision, which prevent the clinicians from having quantitative and robust IHC results. With our work, we combined rapid microfluidic immunofluorescent staining with efficient image-based cell segmentation and signal quantification to increase the robustness of both experimental and analytical protocols. The experimental protocol is very simple and based on fast-fluidic-exchange in a microfluidic chamber created on top of the formalin-fixed-paraffin-embedded (FFPE) slide by clamping it a silicon chip with a polydimethyl siloxane (PDMS) sealing ring. The image-processing protocol is based on enhancement and subsequent thresholding of the local contrast of the obtained fluorescence image. As a case study, given that the human epidermal growth factor receptor 2 (HER2) protein is often used as a biomarker for breast cancer, we applied our method to HER2+ and HER2- cell lines. We report very fast (5 minutes) immunofluorescence staining of both HER2 and cytokeratin (a marker used to define the tumor region) on FFPE slides. The image-processing program can segment cells correctly and give a cell-based quantitative immunofluorescent signal. With this method, we found a reproducible well-defined separation for the HER2-to-cytokeratin ratio for positive and negative control samples.

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

PubMed Central

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

2011-01-01

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

A novel strategy for rapid detection of NT-proBNP

NASA Astrophysics Data System (ADS)

Cui, Qiyao; Sun, Honghao; Zhu, Hui

2017-09-01

In order to establish a simple, rapid, sensitive, and specific quantitative assay to detect the biomarkers of heart failure, in this study, biotin-streptavidin technology was employed with fluorescence immunochromatographic assay to detect the concentration of the biomarkers in serum, and this method was applied to detect NT-proBNP, which is valuable for diagnostic evaluation of heart failure.

Imaging blood-brain barrier dysfunction as a biomarker for epileptogenesis.

PubMed

Bar-Klein, Guy; Lublinsky, Svetlana; Kamintsky, Lyn; Noyman, Iris; Veksler, Ronel; Dalipaj, Hotjensa; Senatorov, Vladimir V; Swissa, Evyatar; Rosenbach, Dror; Elazary, Netta; Milikovsky, Dan Z; Milk, Nadav; Kassirer, Michael; Rosman, Yossi; Serlin, Yonatan; Eisenkraft, Arik; Chassidim, Yoash; Parmet, Yisrael; Kaufer, Daniela; Friedman, Alon

2017-06-01

A biomarker that will enable the identification of patients at high-risk for developing post-injury epilepsy is critically required. Microvascular pathology and related blood-brain barrier dysfunction and neuroinflammation were shown to be associated with epileptogenesis after injury. Here we used prospective, longitudinal magnetic resonance imaging to quantitatively follow blood-brain barrier pathology in rats following status epilepticus, late electrocorticography to identify epileptic animals and post-mortem immunohistochemistry to confirm blood-brain barrier dysfunction and neuroinflammation. Finally, to test the pharmacodynamic relevance of the proposed biomarker, two anti-epileptogenic interventions were used; isoflurane anaesthesia and losartan. Our results show that early blood-brain barrier pathology in the piriform network is a sensitive and specific predictor (area under the curve of 0.96, P < 0.0001) for epilepsy, while diffused pathology is associated with a lower risk. Early treatments with either isoflurane anaesthesia or losartan prevented early microvascular damage and late epilepsy. We suggest quantitative assessment of blood-brain barrier pathology as a clinically relevant predictive, diagnostic and pharmaco!dynamics biomarker for acquired epilepsy. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Quantitative Ultrasound for Measuring Obstructive Severity in Children with Hydronephrosis.

PubMed

Cerrolaza, Juan J; Peters, Craig A; Martin, Aaron D; Myers, Emmarie; Safdar, Nabile; Linguraru, Marius George

2016-04-01

We define sonographic biomarkers for hydronephrotic renal units that can predict the necessity of diuretic nuclear renography. We selected a cohort of 50 consecutive patients with hydronephrosis of varying severity in whom 2-dimensional sonography and diuretic mercaptoacetyltriglycine renography had been performed. A total of 131 morphological parameters were computed using quantitative image analysis algorithms. Machine learning techniques were then applied to identify ultrasound based safety thresholds that agreed with the t½ for washout. A best fit model was then derived for each threshold level of t½ that would be clinically relevant at 20, 30 and 40 minutes. Receiver operating characteristic curve analysis was performed. Sensitivity, specificity and area under the receiver operating characteristic curve were determined. Improvement obtained by the quantitative imaging method compared to the Society for Fetal Urology grading system and the hydronephrosis index was statistically verified. For the 3 thresholds considered and at 100% sensitivity the specificities of the quantitative imaging method were 94%, 70% and 74%, respectively. Corresponding area under the receiver operating characteristic curve values were 0.98, 0.94 and 0.94, respectively. Improvement obtained by the quantitative imaging method over the Society for Fetal Urology grade and hydronephrosis index was statistically significant (p <0.05 in all cases). Quantitative imaging analysis of renal sonograms in children with hydronephrosis can identify thresholds of clinically significant washout times with 100% sensitivity to decrease the number of diuretic renograms in up to 62% of children. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Performance of a new HPV and biomarker assay in the management of hrHPV positive women: Subanalysis of the ongoing multicenter TRACE clinical trial (n > 6,000) to evaluate POU4F3 methylation as a potential biomarker of cervical precancer and cancer.

PubMed

Kocsis, Adrienn; Takács, Tibor; Jeney, Csaba; Schaff, Zsuzsa; Koiss, Róbert; Járay, Balázs; Sobel, Gábor; Pap, Károly; Székely, István; Ferenci, Tamás; Lai, Hung-Cheng; Nyíri, Miklós; Benczik, Márta

2017-03-01

The ongoing Triage and Risk Assessment of Cervical Precancer by Epigenetic Biomarker (TRACE) prospective, multicenter study aimed to provide a clinical evaluation of the CONFIDENCE™ assay, which comprises a human papillomavirus (HPV) DNA and a human epigenetic biomarker test. Between 2013 and 2015 over 6,000 women aged 18 or older were recruited in Hungary. Liquid-based cytology (LBC), high-risk HPV (hrHPV) DNA detection and single target host gene methylation test of the promoter sequence of the POU4F3 gene by quantitative methylation-specific polymerase chain reaction (PCR) were performed from the same liquid-based cytology sample. The current analysis is focused on the baseline cross-sectional clinical results of 5,384 LBC samples collected from subjects aged 25 years or older. The performance of the CONFIDENCE HPV™ test was found to be comparable to the cobas® HPV test with good agreement. When applying the CONFIDENCE Marker™ test alone in hrHPV positives, it showed significantly higher sensitivity with matching specificity compared to LBC-based triage. For CIN3+ histological endpoint in the age group of 25-65 and 30-65, the methylation test of POU4F3 achieved relative sensitivities of 1.74 (95% CI: 1.25-2.33) and 1.64 (95% CI: 1.08-2.27), respectively, after verification bias adjustment. On the basis of our findings, POU4F3 methylation as a triage test of hrHPV positives appears to be a noteworthy method. We can reasonably assume that its quantitative nature offers the potential for a more objective and discriminative risk assessment tool in the prevention and diagnostics of high-grade cervical intraepithelial neoplasia (CIN) lesions and cervical cancer. © 2016 UICC.

Posttranscriptional deregulation of signaling pathways in meningioma subtypes by differential expression of miRNAs.

PubMed

Ludwig, Nicole; Kim, Yoo-Jin; Mueller, Sabine C; Backes, Christina; Werner, Tamara V; Galata, Valentina; Sartorius, Elke; Bohle, Rainer M; Keller, Andreas; Meese, Eckart

2015-09-01

Micro (mi)RNAs are key regulators of gene expression and offer themselves as biomarkers for cancer development and progression. Meningioma is one of the most frequent primary intracranial tumors. As of yet, there are limited data on the role of miRNAs in meningioma of different histological subtypes and the affected signaling pathways. In this study, we compared expression of 1205 miRNAs in different meningioma grades and histological subtypes using microarrays and independently validated deregulation of selected miRNAs with quantitative real-time PCR. Clinical utility of a subset of miRNAs as biomarkers for World Health Organization (WHO) grade II meningioma based on quantitative real-time data was tested. Potential targets of deregulated miRNAs were discovered with an in silico analysis. We identified 13 miRNAs deregulated between different subtypes of benign meningiomas, and 52 miRNAs deregulated in anaplastic meningioma compared with benign meningiomas. Known and putative target genes of deregulated miRNAs include genes involved in epithelial-to-mesenchymal transition for benign meningiomas, and Wnt, transforming growth factor-β, and vascular endothelial growth factor signaling for higher-grade meningiomas. Furthermore, a 4-miRNA signature (miR-222, -34a*, -136, and -497) shows promise as a biomarker differentiating WHO grade II from grade I meningiomas with an area under the curve of 0.75. Our data provide novel insights into the contribution of miRNAs to the phenotypic spectrum in benign meningiomas. By deregulating translation of genes belonging to signaling pathways known to be important for meningioma genesis and progression, miRNAs provide a second in line amplification of growth promoting cellular signals. MiRNAs as biomarkers for diagnosis of aggressive meningiomas might prove useful and should be explored further in a prospective manner. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

miR-758-3p: a blood-based biomarker that’s influence on the expression of CERP/ABCA1 may contribute to the progression of obesity to metabolic syndrome

PubMed Central

O’Neill, Sadhbh; Larsen, Mette Bohl; Gregersen, Søren; Hermansen, Kjeld; O’Driscoll, Lorraine

2018-01-01

Due to increasing prevalence of obesity, a simple method or methods for the diagnosis of metabolic syndrome are urgently required to reduce the risk of associated cardiovascular disease, diabetes and cancer. This study aimed to identify a miRNA biomarker that may distinguish metabolic syndrome from obesity and to investigate if such a miRNA may have functional relevance for metabolic syndrome. 52 adults with clinical obesity (n=26) or metabolic syndrome (n=26) were recruited. Plasma specimens were procured from all and were randomly designated to discovery and validation cohorts. miRNA discovery profiling was performed, using array technology, on plasma RNA. Validation was performed by quantitative polymerase chain reaction. The functional effect of miR-758-3p on its predicted target, cholesterol efflux regulatory protein/ATP-binding cassette transporter, was investigated using HepG2 liver cells. Custom miRNA profiling of 25 miRNAs in the discovery cohort found miR-758-3p to be detected in the obese cohort but undetected in the metabolic syndrome cohort. miR-758-3p was subsequently validated as a potential biomarker for metabolic syndrome by quantitative polymerase chain reaction. Bioinformatics analysis identified cholesterol efflux regulatory protein/ATP-binding cassette transporter as miR-758-3p’s predicted target. Specifically, mimicking miR-758-3p in HepG2 cells suppressed cholesterol efflux regulatory protein/ATP-binding cassette transporter protein expression; conversely, inhibiting miR-758-3p increased cholesterol efflux regulatory protein/ATP-binding cassette transporter protein expression. miR-758-3p holds potential as a blood-based biomarker for distinguishing progression from obesity to metabolic syndrome and as a driver in controlling cholesterol efflux regulatory protein/ATP-binding cassette transporter expression, indicating it potential role in cholesterol control in metabolic syndrome. PMID:29507696

miR-758-3p: a blood-based biomarker that's influence on the expression of CERP/ABCA1 may contribute to the progression of obesity to metabolic syndrome.

PubMed

O'Neill, Sadhbh; Larsen, Mette Bohl; Gregersen, Søren; Hermansen, Kjeld; O'Driscoll, Lorraine

2018-02-06

Due to increasing prevalence of obesity, a simple method or methods for the diagnosis of metabolic syndrome are urgently required to reduce the risk of associated cardiovascular disease, diabetes and cancer. This study aimed to identify a miRNA biomarker that may distinguish metabolic syndrome from obesity and to investigate if such a miRNA may have functional relevance for metabolic syndrome. 52 adults with clinical obesity (n=26) or metabolic syndrome (n=26) were recruited. Plasma specimens were procured from all and were randomly designated to discovery and validation cohorts. miRNA discovery profiling was performed, using array technology, on plasma RNA. Validation was performed by quantitative polymerase chain reaction. The functional effect of miR-758-3p on its predicted target, cholesterol efflux regulatory protein/ATP-binding cassette transporter, was investigated using HepG2 liver cells. Custom miRNA profiling of 25 miRNAs in the discovery cohort found miR-758-3p to be detected in the obese cohort but undetected in the metabolic syndrome cohort. miR-758-3p was subsequently validated as a potential biomarker for metabolic syndrome by quantitative polymerase chain reaction. Bioinformatics analysis identified cholesterol efflux regulatory protein/ATP-binding cassette transporter as miR-758-3p's predicted target. Specifically, mimicking miR-758-3p in HepG2 cells suppressed cholesterol efflux regulatory protein/ATP-binding cassette transporter protein expression; conversely, inhibiting miR-758-3p increased cholesterol efflux regulatory protein/ATP-binding cassette transporter protein expression. miR-758-3p holds potential as a blood-based biomarker for distinguishing progression from obesity to metabolic syndrome and as a driver in controlling cholesterol efflux regulatory protein/ATP-binding cassette transporter expression, indicating it potential role in cholesterol control in metabolic syndrome.

UPLC-ESI-MS/MS method for the quantitative measurement of aliphatic diamines, trimethylamine N-oxide, and β-methylamino-l-alanine in human urine.

PubMed

Bhandari, Deepak; Bowman, Brett A; Patel, Anish B; Chambers, David M; De Jesús, Víctor R; Blount, Benjamin C

2018-04-15

This work describes a quantitative high-throughput analytical method for the simultaneous measurement of small aliphatic nitrogenous biomarkers, i.e., 1,6-hexamethylenediamine (HDA), isophoronediamine (IPDA), β-methylamino-l-alanine (BMAA), and trimethylamine N-oxide (TMAO), in human urine. Urinary aliphatic diamines, HDA and IPDA, are potential biomarkers of environmental exposure to their corresponding diisocyanates. Urinary BMAA forms as a result of human exposure to blue-green algae contaminated food. And, TMAO is excreted in urine due to the consumption of carnitine- and choline-rich diets. These urinary biomarkers represent classes of small aliphatic nitrogen-containing compounds (N-compounds) that have a high aqueous solubility, low logP, and/or high basic pK a . Because of the highly polar characteristics, analysis of these compounds in complex sample matrices is often challenging. We report on the development of ion-pairing chemistry based ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS/MS) method for the simultaneous measurement of these biomarkers in human urine. Chromatographic separation was optimized using heptafluorobutyric acid-(HFBA-) based mobile phase and a reversed-phase C18 column. All four analytes were baseline separated within 2.6 min with an overall run time of 5 min per sample injection. Sample preparation involved 4 h of acid hydrolysis followed by automated solid phase extraction (SPE) performed using strong cation exchange sorbent bed with 7 N ammonia solution in methanol as eluent. Limits of detection ranged from 0.05 ng/mL to 1.60 ng/mL. The inter-day and intra-day accuracy were within 10%, and reproducibility within 15%. The method is accurate, fast, and well-suited for biomonitoring studies within targeted groups, as well as larger population-based studies such as the U. S. National Health and Nutrition Examination Survey (NHANES). Published by Elsevier B.V.

Altered serum microRNAs as biomarkers for the early diagnosis of pulmonary tuberculosis infection

PubMed Central

2012-01-01

Background Pulmonary tuberculosis (TB) is a highly lethal infectious disease and early diagnosis of TB is critical for the control of disease progression. The objective of this study was to profile a panel of serum microRNAs (miRNAs) as potential biomarkers for the early diagnosis of pulmonary TB infection. Methods Using TaqMan Low-Density Array (TLDA) analysis followed by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) validation, expression levels of miRNAs in serum samples from 30 patients with active tuberculosis and 60 patients with Bordetella pertussis (BP), varicella-zoster virus (VZV) and enterovirus (EV) were analyzed. Results The Low-Density Array data showed that 97 miRNAs were differentially expressed in pulmonary TB patient sera compared with healthy controls (90 up-regulated and 7 down-regulated). Following qRT-PCR confirmation and receiver operational curve (ROC) analysis, three miRNAs (miR-361-5p, miR-889 and miR-576-3p) were shown to distinguish TB infected patients from healthy controls and other microbial infections with moderate sensitivity and specificity (area under curve (AUC) value range, 0.711-0.848). Multiple logistic regression analysis of a combination of these three miRNAs showed an enhanced ability to discriminate between these two groups with an AUC value of 0.863. Conclusions Our study suggests that altered levels of serum miRNAs have great potential to serve as non-invasive biomarkers for early detection of pulmonary TB infection. PMID:23272999

Quantitative mass spectrometry of unconventional human biological matrices

NASA Astrophysics Data System (ADS)

Dutkiewicz, Ewelina P.; Urban, Pawel L.

2016-10-01

The development of sensitive and versatile mass spectrometric methodology has fuelled interest in the analysis of metabolites and drugs in unconventional biological specimens. Here, we discuss the analysis of eight human matrices-hair, nail, breath, saliva, tears, meibum, nasal mucus and skin excretions (including sweat)-by mass spectrometry (MS). The use of such specimens brings a number of advantages, the most important being non-invasive sampling, the limited risk of adulteration and the ability to obtain information that complements blood and urine tests. The most often studied matrices are hair, breath and saliva. This review primarily focuses on endogenous (e.g. potential biomarkers, hormones) and exogenous (e.g. drugs, environmental contaminants) small molecules. The majority of analytical methods used chromatographic separation prior to MS; however, such a hyphenated methodology greatly limits analytical throughput. On the other hand, the mass spectrometric methods that exclude chromatographic separation are fast but suffer from matrix interferences. To enable development of quantitative assays for unconventional matrices, it is desirable to standardize the protocols for the analysis of each specimen and create appropriate certified reference materials. Overcoming these challenges will make analysis of unconventional human biological matrices more common in a clinical setting. This article is part of the themed issue 'Quantitative mass spectrometry'.

A Method for Comprehensive Glycosite-Mapping and Direct Quantitation of Serum Glycoproteins.

PubMed

Hong, Qiuting; Ruhaak, L Renee; Stroble, Carol; Parker, Evan; Huang, Jincui; Maverakis, Emanual; Lebrilla, Carlito B

2015-12-04

A comprehensive glycan map was constructed for the top eight abundant glycoproteins in plasma using both specific and nonspecific enzyme digestions followed by nano liquid chromatography (LC)-chip/quadrupole time-of-flight mass spectrometry (MS) analysis. Glycopeptides were identified using an in-house software tool, GPFinder. A sensitive and reproducible multiple reaction monitoring (MRM) technique on a triple quadrupole MS was developed and applied to quantify immunoglobulins G, A, M, and their site-specific glycans simultaneously and directly from human serum/plasma without protein enrichments. A total of 64 glycopeptides and 15 peptides were monitored for IgG, IgA, and IgM in a 20 min ultra high performance (UP)LC gradient. The absolute protein contents were quantified using peptide calibration curves. The glycopeptide ion abundances were normalized to the respective protein abundances to separate protein glycosylation from protein expression. This technique yields higher method reproducibility and less sample loss when compared with the quantitation method that involves protein enrichments. The absolute protein quantitation has a wide linear range (3-4 orders of magnitude) and low limit of quantitation (femtomole level). This rapid and robust quantitation technique, which provides quantitative information for both proteins and glycosylation, will further facilitate disease biomarker discoveries.

A fully integrated standalone portable cavity ringdown breath acetone analyzer.

PubMed

Sun, Meixiu; Jiang, Chenyu; Gong, Zhiyong; Zhao, Xiaomeng; Chen, Zhuying; Wang, Zhennan; Kang, Meiling; Li, Yingxin; Wang, Chuji

2015-09-01

Breath analysis is a promising new technique for nonintrusive disease diagnosis and metabolic status monitoring. One challenging issue in using a breath biomarker for potential particular disease screening is to find a quantitative relationship between the concentration of the breath biomarker and clinical diagnostic parameters of the specific disease. In order to address this issue, we need a new instrument that is capable of conducting real-time, online breath analysis with high data throughput, so that a large scale of clinical test (more subjects) can be achieved in a short period of time. In this work, we report a fully integrated, standalone, portable analyzer based on the cavity ringdown spectroscopy technique for near-real time, online breath acetone measurements. The performance of the portable analyzer in measurements of breath acetone was interrogated and validated by using the certificated gas chromatography-mass spectrometry. The results show that this new analyzer is useful for reliable online (online introduction of a breath sample without pre-treatment) breath acetone analysis with high sensitivity (57 ppb) and high data throughput (one data per second). Subsequently, the validated breath analyzer was employed for acetone measurements in 119 human subjects under various situations. The instrument design, packaging, specifications, and future improvements were also described. From an optical ringdown cavity operated by the lab-set electronics reported previously to this fully integrated standalone new instrument, we have enabled a new scientific tool suited for large scales of breath acetone analysis and created an instrument platform that can even be adopted for study of other breath biomarkers by using different lasers and ringdown mirrors covering corresponding spectral fingerprints.

A fully integrated standalone portable cavity ringdown breath acetone analyzer

NASA Astrophysics Data System (ADS)

Sun, Meixiu; Jiang, Chenyu; Gong, Zhiyong; Zhao, Xiaomeng; Chen, Zhuying; Wang, Zhennan; Kang, Meiling; Li, Yingxin; Wang, Chuji

2015-09-01

Breath analysis is a promising new technique for nonintrusive disease diagnosis and metabolic status monitoring. One challenging issue in using a breath biomarker for potential particular disease screening is to find a quantitative relationship between the concentration of the breath biomarker and clinical diagnostic parameters of the specific disease. In order to address this issue, we need a new instrument that is capable of conducting real-time, online breath analysis with high data throughput, so that a large scale of clinical test (more subjects) can be achieved in a short period of time. In this work, we report a fully integrated, standalone, portable analyzer based on the cavity ringdown spectroscopy technique for near-real time, online breath acetone measurements. The performance of the portable analyzer in measurements of breath acetone was interrogated and validated by using the certificated gas chromatography-mass spectrometry. The results show that this new analyzer is useful for reliable online (online introduction of a breath sample without pre-treatment) breath acetone analysis with high sensitivity (57 ppb) and high data throughput (one data per second). Subsequently, the validated breath analyzer was employed for acetone measurements in 119 human subjects under various situations. The instrument design, packaging, specifications, and future improvements were also described. From an optical ringdown cavity operated by the lab-set electronics reported previously to this fully integrated standalone new instrument, we have enabled a new scientific tool suited for large scales of breath acetone analysis and created an instrument platform that can even be adopted for study of other breath biomarkers by using different lasers and ringdown mirrors covering corresponding spectral fingerprints.

Proteomic analysis in type 2 diabetes patients before and after a very low calorie diet reveals potential disease state and intervention specific biomarkers.

PubMed

Sleddering, Maria A; Markvoort, Albert J; Dharuri, Harish K; Jeyakar, Skhandhan; Snel, Marieke; Juhasz, Peter; Lynch, Moira; Hines, Wade; Li, Xiaohong; Jazet, Ingrid M; Adourian, Aram; Hilbers, Peter A J; Smit, Johannes W A; Van Dijk, Ko Willems

2014-01-01

Very low calorie diets (VLCD) with and without exercise programs lead to major metabolic improvements in obese type 2 diabetes patients. The mechanisms underlying these improvements have so far not been elucidated fully. To further investigate the mechanisms of a VLCD with or without exercise and to uncover possible biomarkers associated with these interventions, blood samples were collected from 27 obese type 2 diabetes patients before and after a 16-week VLCD (Modifast ∼ 450 kcal/day). Thirteen of these patients followed an exercise program in addition to the VCLD. Plasma was obtained from 27 lean and 27 obese controls as well. Proteomic analysis was performed using mass spectrometry (MS) and targeted multiple reaction monitoring (MRM) and a large scale isobaric tags for relative and absolute quantitation (iTRAQ) approach. After the 16-week VLCD, there was a significant decrease in body weight and HbA1c in all patients, without differences between the two intervention groups. Targeted MRM analysis revealed differences in several proteins, which could be divided in diabetes-associated (fibrinogen, transthyretin), obesity-associated (complement C3), and diet-associated markers (apolipoproteins, especially apolipoprotein A-IV). To further investigate the effects of exercise, large scale iTRAQ analysis was performed. However, no proteins were found showing an exercise effect. Thus, in this study, specific proteins were found to be differentially expressed in type 2 diabetes patients versus controls and before and after a VLCD. These proteins are potential disease state and intervention specific biomarkers. Controlled-Trials.com ISRCTN76920690.

Proteomic Analysis in Type 2 Diabetes Patients before and after a Very Low Calorie Diet Reveals Potential Disease State and Intervention Specific Biomarkers

PubMed Central

Dharuri, Harish K.; Jeyakar, Skhandhan; Snel, Marieke; Juhasz, Peter; Lynch, Moira; Hines, Wade; Li, Xiaohong; Jazet, Ingrid M.; Adourian, Aram; Hilbers, Peter A. J.; Smit, Johannes W. A.; Van Dijk, Ko Willems

2014-01-01

Very low calorie diets (VLCD) with and without exercise programs lead to major metabolic improvements in obese type 2 diabetes patients. The mechanisms underlying these improvements have so far not been elucidated fully. To further investigate the mechanisms of a VLCD with or without exercise and to uncover possible biomarkers associated with these interventions, blood samples were collected from 27 obese type 2 diabetes patients before and after a 16-week VLCD (Modifast ∼450 kcal/day). Thirteen of these patients followed an exercise program in addition to the VCLD. Plasma was obtained from 27 lean and 27 obese controls as well. Proteomic analysis was performed using mass spectrometry (MS) and targeted multiple reaction monitoring (MRM) and a large scale isobaric tags for relative and absolute quantitation (iTRAQ) approach. After the 16-week VLCD, there was a significant decrease in body weight and HbA1c in all patients, without differences between the two intervention groups. Targeted MRM analysis revealed differences in several proteins, which could be divided in diabetes-associated (fibrinogen, transthyretin), obesity-associated (complement C3), and diet-associated markers (apolipoproteins, especially apolipoprotein A-IV). To further investigate the effects of exercise, large scale iTRAQ analysis was performed. However, no proteins were found showing an exercise effect. Thus, in this study, specific proteins were found to be differentially expressed in type 2 diabetes patients versus controls and before and after a VLCD. These proteins are potential disease state and intervention specific biomarkers. Trial Registration Controlled-Trials.com ISRCTN76920690 PMID:25415563

Multiplexed Quantitation of Endogenous Proteins in Dried Blood Spots by Multiple Reaction Monitoring - Mass Spectrometry

PubMed Central

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

2013-01-01

Dried blood spot (DBS) sampling, coupled with multiple reaction monitoring mass spectrometry (MRM-MS), is a well-established approach for quantifying a wide range of small molecule biomarkers and drugs. This sampling procedure is simpler and less-invasive than those required for traditional plasma or serum samples enabling collection by minimally trained personnel. Many analytes are stable in the DBS format without refrigeration, which reduces the cost and logistical challenges of sample collection in remote locations. These advantages make DBS sample collection desirable for advancing personalized medicine through population-wide biomarker screening. Here we expand this technology by demonstrating the first multiplexed method for the quantitation of endogenous proteins in DBS samples. A panel of 60 abundant proteins in human blood was targeted by monitoring proteotypic tryptic peptides and their stable isotope-labeled analogs by MRM. Linear calibration curves were obtained for 40 of the 65 peptide targets demonstrating multiple proteins can be quantitatively extracted from DBS collection cards. The method was also highly reproducible with a coefficient of variation of <15% for all 40 peptides. Overall, this assay quantified 37 proteins spanning a range of more than four orders of magnitude in concentration within a single 25 min LC/MRM-MS analysis. The protein abundances of the 33 proteins quantified in matching DBS and whole blood samples showed an excellent correlation, with a slope of 0.96 and an R2 value of 0.97. Furthermore, the measured concentrations for 80% of the proteins were stable for at least 10 days when stored at −20 °C, 4 °C and 37 °C. This work represents an important first step in evaluating the integration of DBS sampling with highly-multiplexed MRM for quantitation of endogenous proteins. PMID:23221968

Mass spectrometric based approaches in urine metabolomics and biomarker discovery.

PubMed

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

2017-03-01

Urine metabolomics has recently emerged as a prominent field for the discovery of non-invasive biomarkers that can detect subtle metabolic discrepancies in response to a specific disease or therapeutic intervention. Urine, compared to other biofluids, is characterized by its ease of collection, richness in metabolites and its ability to reflect imbalances of all biochemical pathways within the body. Following urine collection for metabolomic analysis, samples must be immediately frozen to quench any biogenic and/or non-biogenic chemical reactions. According to the aim of the experiment; sample preparation can vary from simple procedures such as filtration to more specific extraction protocols such as liquid-liquid extraction. Due to the lack of comprehensive studies on urine metabolome stability, higher storage temperatures (i.e. 4°C) and repetitive freeze-thaw cycles should be avoided. To date, among all analytical techniques, mass spectrometry (MS) provides the best sensitivity, selectivity and identification capabilities to analyze the majority of the metabolite composition in the urine. Combined with the qualitative and quantitative capabilities of MS, and due to the continuous improvements in its related technologies (i.e. ultra high-performance liquid chromatography [UPLC] and hydrophilic interaction liquid chromatography [HILIC]), liquid chromatography (LC)-MS is unequivocally the most utilized and the most informative analytical tool employed in urine metabolomics. Furthermore, differential isotope tagging techniques has provided a solution to ion suppression from urine matrix thus allowing for quantitative analysis. In addition to LC-MS, other MS-based technologies have been utilized in urine metabolomics. These include direct injection (infusion)-MS, capillary electrophoresis-MS and gas chromatography-MS. In this article, the current progresses of different MS-based techniques in exploring the urine metabolome as well as the recent findings in providing potentially diagnostic urinary biomarkers are discussed. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:115-134, 2017. © 2015 Wiley Periodicals, Inc.

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 biomarkers for distinguishing PTB and LTBI.

Advancing Precision Nuclear Medicine and Molecular Imaging for Lymphoma.

PubMed

Wright, Chadwick L; Maly, Joseph J; Zhang, Jun; Knopp, Michael V

2017-01-01

PET with fluorodeoxyglucose F 18 ( 18 F FDG-PET) is a meaningful biomarker for the detection, targeted biopsy, and treatment of lymphoma. This article reviews the evolution of 18 F FDG-PET as a putative biomarker for lymphoma and addresses the current capabilities, challenges, and opportunities to enable precision medicine practices for lymphoma. Precision nuclear medicine is driven by new imaging technologies and methodologies to more accurately detect malignant disease. Although quantitative assessment of response is limited, such technologies will enable a more precise metabolic mapping with much higher definition image detail and thus may make it a robust and valid quantitative response assessment methodology. Copyright © 2016 Elsevier Inc. All rights reserved.

Ecology and distribution of a new biomarker linked to 1,2-dichloropropane dechlorination in subsurface environments

NASA Astrophysics Data System (ADS)

Padilla-Crespo, E.; Loeffler, F. E.

2011-12-01

Reductive dechlorination plays a major role in the transformation and detoxification of chlorinated solvents, including chlorinated ethenes. Molecular biological tools are being applied at contaminated sites in order to assess the process-specific biomarkers that impact site performance, and to monitor the progress of bioremediation approaches. The few current biomarker genes in use provide an incomplete picture of the reductively dechlorinating bacterial community; this is a limitation for implementing enhanced bioremediation and monitored natural attenuation as cleanup strategies at chlorinated solvent contaminated sites. Reductively dehalogenating organisms, particularly Dehalococcoides (Dhc) strains, possess multiple reductive dehalogenase (RDase) genes, which are promising targets to specifically monitor dehalogenation processes of interest. Dehalococcoides populations in two highly enriched cultures (RC and KS) have been implicated in the reductive dechlorination of dechlorination of 1,2-dichloropropane (1,2-D), a widespread halogenated organic pollutant, to the non-toxic propene. Using a combined approach of transcription, expression and molecular analysis a new biomarker linked to 1,2-dichloropropane has been identified in Dhc strains RC and KS providing for the first time, convincing evidence of a specific RDase implicated in 1,2-D dechlorination to propene. Further analyses imply that new biomarker is in a "mobile DNA segment", a genomic island (GI) of horizontal gene transfer origin. A valid quantitative PCR approach was designed to detect and enumerate this gene in cultures and environmental samples; this will be a useful to bioremediation practitioners to more efficiently implement reductive dechlorination as a remediation tool. The new biomarker has been identified in fresh water sediment samples from different geographical locations in Europe, North and South America. Further research aims to shed light on RDase gene dissemination and the adaptation of dehalospiring populations in subsurface environments.

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

PubMed Central

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

2011-01-01

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

Phenotypic and biomarker evaluation of zebrafish larvae as an alternative model to predict mammalian hepatotoxicity.

PubMed

Verstraelen, Sandra; Peers, Bernard; Maho, Walid; Hollanders, Karen; Remy, Sylvie; Berckmans, Pascale; Covaci, Adrian; Witters, Hilda

2016-09-01

Zebrafish phenotypic assays have shown promise to assess human hepatotoxicity, though scoring of liver morphology remains subjective and difficult to standardize. Liver toxicity in zebrafish larvae at 5 days was assessed using gene expression as the biomarker approach, complementary to phenotypic analysis and analytical data on compound uptake. This approach aimed to contribute to improved hepatotoxicity prediction, with the goal of identifying biomarker(s) as a step towards the development of transgenic models for prioritization. Morphological effects of hepatotoxic compounds (acetaminophen, amiodarone, coumarin, methapyrilene and myclobutanil) and saccharin as the negative control were assessed after exposure in zebrafish larvae. The hepatotoxic compounds induced the expected zebrafish liver degeneration or changes in size, whereas saccharin did not have any phenotypic adverse effect. Analytical methods based on liquid chromatography-mass spectrometry were optimized to measure stability of selected compounds in exposure medium and internal concentration in larvae. All compounds were stable, except amiodarone for which precipitation was observed. There was a wide variation between the levels of compound in the zebrafish larvae with a higher uptake of amiodarone, methapyrilene and myclobutanil. Detection of hepatocyte markers (CP, CYP3A65, GC and TF) was accomplished by in situ hybridization of larvae to coumarin and myclobutanil and confirmed by real-time reverse transcription-quantitative polymerase chain reaction. Experiments showed decreased expression of all markers. Next, other liver-specific biomarkers (i.e. FABP10a and NR1H4) and apoptosis (i.e. CASP-3 A and TP53) or cytochrome P450-related (CYP2K19) and oxidoreductase activity-related (ZGC163022) genes, were screened. Links between basic mechanisms of liver injury and results of biomarker responses are described. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A priori-defined diet quality indices, biomarkers and risk for type 2 diabetes in five ethnic groups: the Multiethnic Cohort.

PubMed

Jacobs, Simone; Boushey, Carol J; Franke, Adrian A; Shvetsov, Yurii B; Monroe, Kristine R; Haiman, Christopher A; Kolonel, Laurence N; Le Marchand, Loic; Maskarinec, Gertraud

2017-08-01

Dietary indices have been related to risk for type 2 diabetes (T2D) predominantly in white populations. The present study evaluated this association in the ethnically diverse Multiethnic Cohort and examined four diet quality indices in relation to T2D risk, homoeostatic model assessment-estimated insulin resistance (HOMA-IR) and biomarkers of dyslipidaemia, inflammation and adipokines. The T2D analysis included 166 550 white, African American, Native Hawaiian, Japanese American and Latino participants (9200 incident T2D cases). Dietary intake was assessed at baseline using a quantitative FFQ and T2D status was based on three self-reports and confirmed by administrative data. Biomarkers were assessed about 10 years later in a biomarker subcohort (n 10 060). Sex- and ethnicity-specific hazard ratios were calculated for the Healthy Eating Index-2010 (HEI-2010), the alternative HEI-2010 (AHEI-2010), the alternate Mediterranean diet score (aMED) and the Dietary Approaches to Stop Hypertension (DASH). Multivariable-adjusted means of biomarkers were compared across dietary index tertiles in the biomarker subcohort. The AHEI-2010, aMED (in men only) and DASH scores were related to a 10-20 % lower T2D risk, with the strongest associations in whites and the direction of the relationships mostly consistent across ethnic groups. Higher scores on the four indices were related to lower HOMA-IR, TAG and C-reactive protein concentrations, not related to leptin, and the DASH score was directly associated with adiponectin. The AHEI-2010 and DASH were directly related to HDL-cholesterol in women. Potential underlying biological mechanisms linking diet quality and T2D risk are an improved lipid profile and reduced systemic inflammation and, with regards to DASH alone, an improved adiponectin profile.

Selenium-binding protein 1: a sensitive urinary biomarker to detect heavy metal-induced nephrotoxicity.

PubMed

Lee, Eui Kyung; Shin, Young-Jun; Park, Eun Young; Kim, Nam Deuk; Moon, Aree; Kwack, Seung Jun; Son, Ji Yeon; Kacew, Sam; Lee, Byung Mu; Bae, Ok-Nam; Kim, Hyung Sik

2017-04-01

Identifying novel biomarkers to detect nephrotoxicity is clinically important. Here, we attempted to identify new biomarkers for mercury-induced nephrotoxicity and compared their sensitivity to that of traditional biomarkers in animal models. Comparative proteomics analysis was performed in kidney tissues of Sprague-Dawley rats after oral treatment with HgCl 2 (0.1, 1, or 5 mg/kg/day) for 21 days. Kidney cortex tissues were analyzed by two-dimensional gel electrophoresis/matrix-assisted laser desorption/ionization, and differentially expressed proteins were identified. The corresponding spots were quantitated by RT-PCR. Selenium-binding protein 1 (SBP1) was found to be the most markedly upregulated protein in the kidney cortex of rats after HgCl 2 administration. However, blood urea nitrogen, serum creatinine, and glucose levels increased significantly only in the 1 or 5 mg/kg HgCl 2 -treated groups. A number of urinary excretion proteins, including kidney injury molecule-1, clusterin, monocyte chemoattractant protein-1, and β-microglobulin, increased dose-dependently. Histopathological examination revealed severe proximal tubular damage in high-dose (5 mg/kg) HgCl 2 -exposed groups. In addition, urinary excretion of SBP1 significantly increased in a dose-dependent manner. To confirm the critical role of SBP1 as a biomarker for nephrotoxicity, normal kidney proximal tubular cells were treated with HgCl 2 , CdCl 2 , or cisplatin for 24 h. SBP1 levels significantly increased in conditioned media exposed to nephrotoxicants, but decreased in cell lysates. Our investigations suggest that SBP1 may play a critical role in the pathological processes underlying chemical-induced nephrotoxicity. Thus, urinary excretion of SBP1 might be a sensitive and specific biomarker to detect early stages of kidney injury.

Radiomics biomarkers for accurate tumor progression prediction of oropharyngeal cancer

NASA Astrophysics Data System (ADS)

Hadjiiski, Lubomir; Chan, Heang-Ping; Cha, Kenny H.; Srinivasan, Ashok; Wei, Jun; Zhou, Chuan; Prince, Mark; Papagerakis, Silvana

2017-03-01

Accurate tumor progression prediction for oropharyngeal cancers is crucial for identifying patients who would best be treated with optimized treatment and therefore minimize the risk of under- or over-treatment. An objective decision support system that can merge the available radiomics, histopathologic and molecular biomarkers in a predictive model based on statistical outcomes of previous cases and machine learning may assist clinicians in making more accurate assessment of oropharyngeal tumor progression. In this study, we evaluated the feasibility of developing individual and combined predictive models based on quantitative image analysis from radiomics, histopathology and molecular biomarkers for oropharyngeal tumor progression prediction. With IRB approval, 31, 84, and 127 patients with head and neck CT (CT-HN), tumor tissue microarrays (TMAs) and molecular biomarker expressions, respectively, were collected. For 8 of the patients all 3 types of biomarkers were available and they were sequestered in a test set. The CT-HN lesions were automatically segmented using our level sets based method. Morphological, texture and molecular based features were extracted from CT-HN and TMA images, and selected features were merged by a neural network. The classification accuracy was quantified using the area under the ROC curve (AUC). Test AUCs of 0.87, 0.74, and 0.71 were obtained with the individual predictive models based on radiomics, histopathologic, and molecular features, respectively. Combining the radiomics and molecular models increased the test AUC to 0.90. Combining all 3 models increased the test AUC further to 0.94. This preliminary study demonstrates that the individual domains of biomarkers are useful and the integrated multi-domain approach is most promising for tumor progression prediction.

Metabolon, Inc.

PubMed

Ryals, John; Lawton, Kay; Stevens, Daniel; Milburn, Michael

2007-07-01

Metabolon is an emerging technology company developing proprietary analytical methods and software for biomarker discovery using metabolomics. The company's aim is to measure all small molecules (<1500 Da) in a biological sample. These small-molecule compounds include biochemicals of cellular metabolism and xenobiotics from diet and environment. Our proprietary mLIMStrade mark system contains advanced metabolomic software and automated data-processing tools that use a variety of data-analysis and quality-control algorithms to convert raw mass-spectrometry data to identified, quantitated compounds. Metabolon's primary focus is a fee-for-service business that exploits this technology for pharmaceutical and biotechnology companies, with additional clients in the consumer goods, cosmetics and agricultural industries. Fee-for-service studies are often collaborations with groups that employ a variety of technologies for biomarker discovery. Metabolon's goal is to develop technology that will automatically analyze any sample for the small-molecule components present and become a standard technology for applications in health and related sciences.

Cytochrome P450 isozyme protein verified in the skin of southern hemisphere humpback whales (Megaptera novaeangliae): implications for biochemical biomarker assessment.

PubMed

Waugh, Courtney A; Huston, Wilhelmina M; Noad, Michael J; Bengtson Nash, Susan

2011-04-01

Large mysticete whales represent a unique challenge for chemical risk assessment. Few epidemiological investigations are possible due to the low incidence of adult stranding events. Similarly their often extreme life-history adaptations of prolonged migration and fasting challenge exposure assumptions. Molecular biomarkers offer the potential to complement information yielded through tissue chemical analysis, as well as providing evidence of a molecular response to chemical exposure. In this study we confirm the presence of cytochrome P450 reductase (CPR) and cytochrome P450 isoenzyme 1A1 (CYP1A1) in epidermal tissue of southern hemisphere humpback whales (Megaptera novaeangliae). The detection of CYP1A1 in the integument of the humpback whale affords the opportunity for further quantitative non-destructive investigations of enzyme activity as a function of chemical stress. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

PubMed

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

2013-01-01

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

Photocleavable DNA barcode-antibody conjugates allow sensitive and multiplexed protein analysis in single cells.

PubMed

Agasti, Sarit S; Liong, Monty; Peterson, Vanessa M; Lee, Hakho; Weissleder, Ralph

2012-11-14

DNA barcoding is an attractive technology, as it allows sensitive and multiplexed target analysis. However, DNA barcoding of cellular proteins remains challenging, primarily because barcode amplification and readout techniques are often incompatible with the cellular microenvironment. Here we describe the development and validation of a photocleavable DNA barcode-antibody conjugate method for rapid, quantitative, and multiplexed detection of proteins in single live cells. Following target binding, this method allows DNA barcodes to be photoreleased in solution, enabling easy isolation, amplification, and readout. As a proof of principle, we demonstrate sensitive and multiplexed detection of protein biomarkers in a variety of cancer cells.

Hsa_circ_0001649: A circular RNA and potential novel biomarker for hepatocellular carcinoma.

PubMed

Qin, Meilin; Liu, Gang; Huo, Xisong; Tao, Xuemei; Sun, Xiaomeng; Ge, Zhouhong; Yang, Juan; Fan, Jia; Liu, Lei; Qin, Wenxin

2016-01-01

It has been shown that circular RNA (circRNA) is associated with human cancers, however, few studies have been reported in hepatocellular carcinoma (HCC). To estimate clinical values of a circular RNA, Hsa_circ_0001649, in HCC. Expression level of hsa_circ_0001649 was detected in HCC and paired adjacent liver tissues by real-time quantitative reverse transcription-polymerase chain reactions (qRT-PCRs). Differences in expression level of hsa_circ_0001649 were analyzed using the paired t-test. Tests were performed between clinical information and hsa_circ_0001649 expression level by analysis of variance (ANOVA) or welch t-test and a receiver operating characteristics (ROC) curve was established to estimate the value of hsa_circ_0001649 expression as a biomarker in HCC. hsa_circ_0001649 expression was significantly downregulated in HCC tissues (p = 0.0014) based on an analysis of 89 paired samples of HCC and adjacent liver tissues and the area under the ROC curve (AUC) was 0.63. Furthermore, hsa_circ_0001649 expression was correlated with tumor size (p = 0.045) and the occurrence of tumor embolus (p = 0.017) in HCC. We first found hsa_circ_0001649 was significantly downregulated in HCC. Our findings indicate hsa_circ_0001649 might serve as a novel potential biomarker for HCC and may function in tumorigenesis and metastasis of HCC.

Quantitative Lateral Flow Assays for Salivary Biomarker Assessment: A Review

PubMed Central

Miočević, Olga; Cole, Craig R.; Laughlin, Mary J.; Buck, Robert L.; Slowey, Paul D.; Shirtcliff, Elizabeth A.

2017-01-01

Saliva is an emerging biofluid with a significant number of applications in use across research and clinical settings. The present paper explores the reasons why saliva has grown in popularity in recent years, balancing both the potential strengths and weaknesses of this biofluid. Focusing on reasons why saliva is different from other common biological fluids such as blood, urine, or tears, we review how saliva is easily obtained, with minimal risk to the donor, and reduced costs for collection, transportation, and analysis. We then move on to a brief review of the history and progress in rapid salivary testing, again reviewing the strengths and weaknesses of rapid immunoassays (e.g., lateral flow immunoassay) compared to more traditional immunoassays. We consider the potential for saliva as an alternative biofluid in a setting where rapid results are important. We focus the review on salivary tests for small molecule biomarkers using cortisol as an example. Such salivary tests can be applied readily in a variety of settings and for specific measurement purposes, providing researchers and clinicians with opportunities to assess biomarkers in real time with lower transportation, collection, and analysis costs, faster turnaround time, and minimal training requirements. We conclude with a note of cautious optimism that the field will soon gain the ability to collect and analyze salivary specimens at any location and return viable results within minutes. PMID:28660183

iTRAQ Quantitative Proteomic Comparison of Metastatic and Non-Metastatic Uveal Melanoma Tumors

PubMed Central

Crabb, John W.; Hu, Bo; Crabb, John S.; Triozzi, Pierre; Saunthararajah, Yogen; Singh, Arun D.

2015-01-01

Background Uveal melanoma is the most common malignancy of the adult eye. The overall mortality rate is high because this aggressive cancer often metastasizes before ophthalmic diagnosis. Quantitative proteomic analysis of primary metastasizing and non-metastasizing tumors was pursued for insights into mechanisms and biomarkers of uveal melanoma metastasis. Methods Eight metastatic and 7 non-metastatic human primary uveal melanoma tumors were analyzed by LC MS/MS iTRAQ technology with Bruch’s membrane/choroid complex from normal postmortem eyes as control tissue. Tryptic peptides from tumor and control proteins were labeled with iTRAQ tags, fractionated by cation exchange chromatography, and analyzed by LC MS/MS. Protein identification utilized the Mascot search engine and the human Uni-Prot/Swiss-Protein database with false discovery ≤ 1%; protein quantitation utilized the Mascot weighted average method. Proteins designated differentially expressed exhibited quantitative differences (p ≤ 0.05, t-test) in a training set of five metastatic and five non-metastatic tumors. Logistic regression models developed from the training set were used to classify the metastatic status of five independent tumors. Results Of 1644 proteins identified and quantified in 5 metastatic and 5 non-metastatic tumors, 12 proteins were found uniquely in ≥ 3 metastatic tumors, 28 were found significantly elevated and 30 significantly decreased only in metastatic tumors, and 31 were designated differentially expressed between metastatic and non-metastatic tumors. Logistic regression modeling of differentially expressed collagen alpha-3(VI) and heat shock protein beta-1 allowed correct prediction of metastasis status for each of five independent tumor specimens. Conclusions The present data provide new clues to molecular differences in metastatic and non-metastatic uveal melanoma tumors. While sample size is limited and validation required, the results support collagen alpha-3(VI) and heat shock protein beta-1 as candidate biomarkers of uveal melanoma metastasis and establish a quantitative proteomic database for uveal melanoma primary tumors. PMID:26305875

Lipophilic organic pollutants induce changes in phospholipid and membrane protein composition leading to Vero cell morphological change.

PubMed

Liao, Ting T; Wang, Lei; Jia, Ru W; Fu, Xiao H; Chua, Hong

2014-01-01

Membrane damage related to morphological change in Vero cells is a sensitive index of the composite biotoxicity of trace lipophilic chemicals. However, judging whether the morphological change in Vero cells happens and its ratio are difficult because it is not a quantitative characteristic. To find biomarkers of cell morphological change for quantitatively representing the ratio of morphological changed cell, the mechanism of cell membrane damage driven by typical lipophilic chemicals, such as trichlorophenol (TCP) and perfluorooctanesulphonate (PFOS), was explored. The ratio of morphologically changed cells generally increased with increased TCP or PFOS concentrations, and the level of four major components of phospholipids varied with concentrations of TCP or PFOS, but only the ratio of phosphatidylcholine (PC)/phosphatidylethanolamine (PE) decreased regularly as TCP or PFOS concentrations increased. Analysis of membrane proteins showed that the level of vimentin in normal cell membranes is high, while it decreases or vanishes after TCP exposure. These variations in phospholipid and membrane protein components may result in membrane leakage and variation in rigid structure, which leads to changes in cell morphology. Therefore, the ratio of PC/PE and amount of vimentin may be potential biomarkers for representing the ratio of morphological changed Vero cell introduced by trace lipophilic compounds, thus their composite bio-toxicity.

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

PubMed

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

2013-02-05

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

Fully electronic urine dipstick probe for combinatorial detection of inflammatory biomarkers

PubMed Central

Kamakoti, Vikramshankar; Kinnamon, David; Choi, Kang Hyeok; Jagannath, Badrinath; Prasad, Shalini

2018-01-01

Aim: An electrochemical urine dipstick probe biosensor has been demonstrated using molybdenum electrodes on nanoporous polyamide substrate for the quantitative detection of two inflammatory protein biomarkers, CRP and IL-6. Materials & methods: The electrode interface was characterized using ζ-potential and Fourier transform infrared spectroscopy. Detection of biomarkers was demonstrated by measuring impedance changes associated with the dose concentrations of the two biomarkers. A proof of feasibility of point-of-care implementation of the biosensor was demonstrated using a portable electronics platform. Results & conclusion: Limit of detection of 1 pg/ml was achieved for CRP and IL-6 in human urine and synthetic urine buffers. The developed portable hardware demonstrated close correlation with benchtop equipment results. PMID:29796304

Classifying oxidative stress by F2-isoprostane levels across human diseases: A meta-analysis.

PubMed

van 't Erve, Thomas J; Kadiiska, Maria B; London, Stephanie J; Mason, Ronald P

2017-08-01

The notion that oxidative stress plays a role in virtually every human disease and environmental exposure has become ingrained in everyday knowledge. However, mounting evidence regarding the lack of specificity of biomarkers traditionally used as indicators of oxidative stress in human disease and exposures now necessitates re-evaluation. To prioritize these re-evaluations, published literature was comprehensively analyzed in a meta-analysis to quantitatively classify the levels of systemic oxidative damage across human disease and in response to environmental exposures. In this meta-analysis, the F 2 -isoprostane, 8-iso-PGF 2α , was specifically chosen as the representative marker of oxidative damage. To combine published values across measurement methods and specimens, the standardized mean differences (Hedges' g) in 8-iso-PGF 2α levels between affected and control populations were calculated. The meta-analysis resulted in a classification of oxidative damage levels as measured by 8-iso-PGF 2α across 50 human health outcomes and exposures from 242 distinct publications. Relatively small increases in 8-iso-PGF 2α levels (g<0.8) were found in the following conditions: hypertension (g=0.4), metabolic syndrome (g=0.5), asthma (g=0.4), and tobacco smoking (g=0.7). In contrast, large increases in 8-iso-PGF 2α levels were observed in pathologies of the kidney, e.g., chronic renal insufficiency (g=1.9), obstructive sleep apnoea (g=1.1), and pre-eclampsia (g=1.1), as well as respiratory tract disorders, e.g., cystic fibrosis (g=2.3). In conclusion, we have established a quantitative classification for the level of 8-iso-PGF 2α generation in different human pathologies and exposures based on a comprehensive meta-analysis of published data. This analysis provides knowledge on the true involvement of oxidative damage across human health outcomes as well as utilizes past research to prioritize those conditions requiring further scrutiny on the mechanisms of biomarker generation. Copyright © 2017. Published by Elsevier B.V.

Automated tumor analysis for molecular profiling in lung cancer

PubMed Central

Boyd, Clinton; James, Jacqueline A.; Loughrey, Maurice B.; Hougton, Joseph P.; Boyle, David P.; Kelly, Paul; Maxwell, Perry; McCleary, David; Diamond, James; McArt, Darragh G.; Tunstall, Jonathon; Bankhead, Peter; Salto-Tellez, Manuel

2015-01-01

The discovery and clinical application of molecular biomarkers in solid tumors, increasingly relies on nucleic acid extraction from FFPE tissue sections and subsequent molecular profiling. This in turn requires the pathological review of haematoxylin & eosin (H&E) stained slides, to ensure sample quality, tumor DNA sufficiency by visually estimating the percentage tumor nuclei and tumor annotation for manual macrodissection. In this study on NSCLC, we demonstrate considerable variation in tumor nuclei percentage between pathologists, potentially undermining the precision of NSCLC molecular evaluation and emphasising the need for quantitative tumor evaluation. We subsequently describe the development and validation of a system called TissueMark for automated tumor annotation and percentage tumor nuclei measurement in NSCLC using computerized image analysis. Evaluation of 245 NSCLC slides showed precise automated tumor annotation of cases using Tissuemark, strong concordance with manually drawn boundaries and identical EGFR mutational status, following manual macrodissection from the image analysis generated tumor boundaries. Automated analysis of cell counts for % tumor measurements by Tissuemark showed reduced variability and significant correlation (p < 0.001) with benchmark tumor cell counts. This study demonstrates a robust image analysis technology that can facilitate the automated quantitative analysis of tissue samples for molecular profiling in discovery and diagnostics. PMID:26317646

Breast Cancer Diagnosis Using a Microfluidic Multiplexed Immunohistochemistry Platform

PubMed Central

Kim, Minseok S.; Kim, Taemin; Kong, Sun-Young; Kwon, Soim; Bae, Chae Yun; Choi, Jaekyu; Kim, Chul Hwan; Lee, Eun Sook; Park, Je-Kyun

2010-01-01

Background Biomarkers play a key role in risk assessment, assessing treatment response, and detecting recurrence and the investigation of multiple biomarkers may also prove useful in accurate prediction and prognosis of cancers. Immunohistochemistry (IHC) has been a major diagnostic tool to identify therapeutic biomarkers and to subclassify breast cancer patients. However, there is no suitable IHC platform for multiplex assay toward personalized cancer therapy. Here, we report a microfluidics-based multiplexed IHC (MMIHC) platform that significantly improves IHC performance in reduction of time and tissue consumption, quantification, consistency, sensitivity, specificity and cost-effectiveness. Methodology/Principal Findings By creating a simple and robust interface between the device and human breast tissue samples, we not only applied conventional thin-section tissues into on-chip without any additional modification process, but also attained perfect fluid control for various solutions, without any leakage, bubble formation, or cross-contamination. Four biomarkers, estrogen receptor (ER), human epidermal growth factor receptor 2 (HER2), progesterone receptor (PR) and Ki-67, were examined simultaneously on breast cancer cells and human breast cancer tissues. The MMIHC method improved immunoreaction, reducing time and reagent consumption. Moreover, it showed the availability of semi-quantitative analysis by comparing Western blot. Concordance study proved strong consensus between conventional whole-section analysis and MMIHC (n = 105, lowest Kendall's coefficient of concordance, 0.90). To demonstrate the suitability of MMIHC for scarce samples, it was also applied successfully to tissues from needle biopsies. Conclusions/Significance The microfluidic system, for the first time, was successfully applied to human clinical tissue samples and histopathological diagnosis was realized for breast cancers. Our results showing substantial agreement indicate that several cancer-related proteins can be simultaneously investigated on a single tumor section, giving clear advantages and technical advances over standard immunohistochemical method. This novel concept will enable histopathological diagnosis using numerous specific biomarkers at a time even for small-sized specimens, thus facilitating the individualization of cancer therapy. PMID:20454672

Tubulin Beta-3 Chain as a New Candidate Protein Biomarker of Human Skin Aging: A Preliminary Study

PubMed Central

2017-01-01

Skin aging is a complex process, and a lot of efforts have been made to identify new and specific targets that could help to diagnose, prevent, and treat skin aging. Several studies concerning skin aging have analyzed the changes in gene expression, and very few investigations have been performed at the protein level. Moreover, none of these proteomic studies has used a global quantitative labeled proteomic offgel approach that allows a more accurate description of aging phenotype. We applied such an approach on human primary keratinocytes obtained from sun-nonexposed skin biopsies of young and elderly women. A total of 517 unique proteins were identified, and 58 proteins were significantly differentially expressed with 40 that were downregulated and 18 upregulated with aging. Gene ontology and pathway analysis performed on these 58 putative biomarkers of skin aging evidenced that these dysregulated proteins were mostly involved in metabolism and cellular processes such as cell cycle and signaling pathways. Change of expression of tubulin beta-3 chain was confirmed by western blot on samples originated from several donors. Thus, this study suggested the tubulin beta-3 chain has a promising biomarker in skin aging. PMID:28626498

Biomarkers of Cell Senescence Assessed by Imaging Cytometry

PubMed Central

Zhao, Hong; Darzynkiewicz, Zbigniew

2012-01-01

The characteristic features of senescent cells such as their “flattened” appearance, enlarged nuclei and low saturation density at the plateau phase of cell growth, can be conveniently measured by image-assisted d cytometry such as provided by the laser scanning cytometry (LSC). The “flattening” of senescent cells is reflected by the decline in local density of staining (intensity of maximal pixel) of DNA-associated fluorescence [4,6-diamidino-2- phenylindole (DAPI)] paralleled by an increase in nuclear size (area). Thus, the ratio of the maximal pixel of DAPI fluorescence per nucleus to the nuclear area provides a very sensitive morphometric biomarker of “depth” of senescence, which progressively declines during induction of senescence. Also recorded is cellular DNA content revealing cell cycle phase, as well as the saturation cell density at plateau phase of growth, which is dramatically decreased in cultures of senescent cells. Concurrent immunocytochemical analysis of expression of p21WAF1, p16INK4a or p27KIP1 cyclin kinase inhibitor provides additional markers of senescence. These biomarker indices can be expressed in quantitative terms (“senescence indices”) as a fraction of the same markers of the exponentially growing cells in control cultures. PMID:23296652

Enhancing image classification models with multi-modal biomarkers

NASA Astrophysics Data System (ADS)

Caban, Jesus J.; Liao, David; Yao, Jianhua; Mollura, Daniel J.; Gochuico, Bernadette; Yoo, Terry

2011-03-01

Currently, most computer-aided diagnosis (CAD) systems rely on image analysis and statistical models to diagnose, quantify, and monitor the progression of a particular disease. In general, CAD systems have proven to be effective at providing quantitative measurements and assisting physicians during the decision-making process. As the need for more flexible and effective CADs continues to grow, questions about how to enhance their accuracy have surged. In this paper, we show how statistical image models can be augmented with multi-modal physiological values to create more robust, stable, and accurate CAD systems. In particular, this paper demonstrates how highly correlated blood and EKG features can be treated as biomarkers and used to enhance image classification models designed to automatically score subjects with pulmonary fibrosis. In our results, a 3-5% improvement was observed when comparing the accuracy of CADs that use multi-modal biomarkers with those that only used image features. Our results show that lab values such as Erythrocyte Sedimentation Rate and Fibrinogen, as well as EKG measurements such as QRS and I:40, are statistically significant and can provide valuable insights about the severity of the pulmonary fibrosis disease.

Tubulin Beta-3 Chain as a New Candidate Protein Biomarker of Human Skin Aging: A Preliminary Study.

PubMed

Lehmann, Sylvia G; Bourgoin-Voillard, Sandrine; Seve, Michel; Rachidi, Walid

2017-01-01

Skin aging is a complex process, and a lot of efforts have been made to identify new and specific targets that could help to diagnose, prevent, and treat skin aging. Several studies concerning skin aging have analyzed the changes in gene expression, and very few investigations have been performed at the protein level. Moreover, none of these proteomic studies has used a global quantitative labeled proteomic offgel approach that allows a more accurate description of aging phenotype. We applied such an approach on human primary keratinocytes obtained from sun-nonexposed skin biopsies of young and elderly women. A total of 517 unique proteins were identified, and 58 proteins were significantly differentially expressed with 40 that were downregulated and 18 upregulated with aging. Gene ontology and pathway analysis performed on these 58 putative biomarkers of skin aging evidenced that these dysregulated proteins were mostly involved in metabolism and cellular processes such as cell cycle and signaling pathways. Change of expression of tubulin beta-3 chain was confirmed by western blot on samples originated from several donors. Thus, this study suggested the tubulin beta-3 chain has a promising biomarker in skin aging.

Synthesis and Characterization of a deuterium labeled Stercobilin: A Potential Biomarker for Autism.

PubMed

Coffey, J M; Vadas, A; Puleo, Y; Lewis, K; Pirone, G; Rudolph, H L; Helms, E; Wood, T D; Flynn-Charlebois, A

2018-05-14

Stercobilin is an end-stage metabolite of hemoglobin, a component of red blood cells. It has been found that there is a significantly lower concentration of stercobilin in the urine of people diagnosed with Autism Spectrum Disorders (ASD), suggesting potential utility as a biomarker. In vitro, we have synthesized stercobilin from its precursor bilirubin through a reduction reaction proceeded by an oxidation reaction. In addition, we have isotopically labeled the stercobilin product with deuterium using this protocol. Nuclear Magnetic Resonance (NMR) investigations show the products of the unlabeled stercobilin (Rxn 1) and the deuterated stercobilin (Rxn 2) both had a loss of signals in the 5.0-7.0 ppm range indicating proper conversion to stercobilin. Changes in the multiplicity of the sp3 region of the proton NMR suggest proper deuterium incorporation. Mass Spectrometry (MS) studies of Rxn 1 show a difference in fragmentation patterns than that of Rxn 2 proposing potential locations for deuterium incorporation. This isotopologue of stercobilin is stable (> 6 months), and further analysis permits investigation for its use as a biomarker and potential quantitative diagnostic probe for ASD. This article is protected by copyright. All rights reserved.

Quantitative O-glycomics based on improvement of the one-pot method for nonreductive O-glycan release and simultaneous stable isotope labeling with 1-(d0/d5)phenyl-3-methyl-5-pyrazolone followed by mass spectrometric analysis.

PubMed

Wang, Chengjian; Zhang, Ping; Jin, Wanjun; Li, Lingmei; Qiang, Shan; Zhang, Ying; Huang, Linjuan; Wang, Zhongfu

2017-01-06

Rapid, simple and versatile methods for quantitative analysis of glycoprotein O-glycans are urgently required for current studies on protein O-glycosylation patterns and the search for disease O-glycan biomarkers. Relative quantitation of O-glycans using stable isotope labeling followed by mass spectrometric analysis represents an ideal and promising technique. However, it is hindered by the shortage of reliable nonreductive O-glycan release methods as well as the too large or too small inconstant mass difference between the light and heavy isotope form derivatives of O-glycans, which results in difficulties during the recognition and quantitative analysis of O-glycans by mass spectrometry. Herein we report a facile and versatile O-glycan relative quantification strategy, based on an improved one-pot method that can quantitatively achieve nonreductive release and in situ chromophoric labeling of intact mucin-type O-glycans in one step. In this study, the one-pot method is optimized and applied for quantitative O-glycan release and tagging with either non-deuterated (d 0 -) or deuterated (d 5 -) 1-phenyl-3-methyl-5-pyrazolone (PMP). The obtained O-glycan derivatives feature a permanent 10-Da mass difference between the d 0 - and d 5 -PMP forms, allowing complete discrimination and comparative quantification of these isotopically labeled O-glycans by mass spectrometric techniques. Moreover, the d 0 - and d 5 -PMP derivatives of O-glycans also have a relatively high hydrophobicity as well as a strong UV adsorption, especially suitable for high-resolution separation and high-sensitivity detection by RP-HPLC-UV. We have refined the conditions for the one-pot reaction as well as the corresponding sample purification approach. The good quantitation feasibility, reliability and linearity of this strategy have been verified using bovine fetuin and porcine stomach mucin as model O-glycoproteins. Additionally, we have also successfully applied this method to the quantitative O-glycomic comparison between perch and salmon eggs by ESI-MS, MS/MS and online RP-HPLC-UV-ESI-MS/MS, demonstrating its excellent applicability to various complex biological samples. O-Linked glycoproteins, generated via a widely existing glycosylation modification process on serine (Ser) or threonine (Thr) residues of nascent proteins, play essential roles in a series of biological processes. As a type of informational molecule, the O-glycans of these glycoproteins participate directly in these biological mechanisms. Thus, the characteristic differences or changes of O-glycans in expression level usually relate to pathologies of many diseases and represent an important opportunity to uncover the functional mechanisms of various glycoprotein O-glycans. The novel strategy introduced here provides a simple and versatile analytical method for the precise quantitation of glycoprotein O-glycans by mass spectrometry, enabling rapid evaluation of the differences or changes of O-glycans in expression level. It is attractive for the field of quantitative/comparative O-glycomics, which has great significance for exploring the complex structure-function relationship of O-glycans, as well as for the search of O-glycan biomarkers of some major diseases and O-glycan related targets of some drugs. Copyright © 2016 Elsevier B.V. All rights reserved.

Biomarkers in inflammatory bowel disease: current practices and recent advances.

PubMed

Iskandar, Heba N; Ciorba, Matthew A

2012-04-01

Crohn's disease and ulcerative colitis represent the two main forms of the idiopathic chronic inflammatory bowel diseases (IBD). Currently available blood and stool based biomarkers provide reproducible, quantitative tools that can complement clinical assessment to aid clinicians in IBD diagnosis and management. C-reactive protein and fecal based leukocyte markers can help the clinician distinguish IBD from noninflammatory diarrhea and assess disease activity. The ability to differentiate between forms of IBD and predict risk for disease complications is specific to serologic tests including antibodies against Saccharomyces cerevisiae and perinuclear antineutrophil cytoplasmic proteins. Advances in genomic, proteomic, and metabolomic array based technologies are facilitating the development of new biomarkers for IBD. The discovery of novel biomarkers, which can correlate with mucosal healing or predict long-term disease course has the potential to significantly improve patient care. This article reviews the uses and limitations of currently available biomarkers and highlights recent advances in IBD biomarker discovery. Copyright © 2012 Mosby, Inc. All rights reserved.

Bladder cancer biomarker discovery using global metabolomic profiling of urine.

PubMed

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

2014-01-01

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

Circulating microRNAs as emerging cardiac biomarkers responsive to acute exercise.

PubMed

de Gonzalo-Calvo, David; Dávalos, Alberto; Fernández-Sanjurjo, Manuel; Amado-Rodríguez, Laura; Díaz-Coto, Susana; Tomás-Zapico, Cristina; Montero, Ana; García-González, Ángela; Llorente-Cortés, Vicenta; Heras, Maria Eugenia; Boraita Pérez, Araceli; Díaz-Martínez, Ángel E; Úbeda, Natalia; Iglesias-Gutiérrez, Eduardo

2018-08-01

Circulating microRNAs (c-miRNAs) are mediators of intercellular communication with great potential as cardiac biomarkers. The analysis of c-miRNAs in response to physiological stress, such as exercise, would provide valuable information for clinical practice and a deeper understanding of the molecular response to physical activity. Here, we analysed for the first time the acute exercise response of c-miRNAs reported as biomarkers of cardiac disease in a well-characterized cohort of healthy active adults. Blood samples were collected immediately before and after (0 h, 24 h, 72 h) a 10-km race, a half-marathon (HM) and a marathon (M). Serum RNA from 10-km and M samples was extracted and a panel of 74 miRNAs analysed using RT-qPCR. c-miRNA response was compared with a panel of nine cardiac biomarkers. Functional enrichment analysis was performed. Pre- and post-M echocardiographic analyses were carried out. Serum levels of all cardiac biomarkers were upregulated in a dose-dependent manner in response to exercise, even in the absence of symptoms or signs of cardiac injury. A deregulation in the profiles of 5 and 19 c-miRNAs was observed for 10-km and M, respectively. Each race induced a specific qualitative and quantitative alteration of c-miRNAs implicated in cardiac adaptions. Supporting their discriminative potential, a number of c-miRNAs previously associated with cardiac disease were undetectable or stable in response to exercise. Conversely, "pseudo-disease" signatures were also observed. c-miRNAs may be useful for the management of cardiac conditions in the context of acute aerobic exercise. Circulating microRNAs could offer incremental diagnostic value to established and emerging cardiac biomarkers, such as hs-cTnT or NT-proBNP, in those patients with cardiac dysfunction symptoms after an acute bout of endurance exercise. Furthermore, circulating miRNAs could also show "pseudo-disease" signatures in response to acute exercise. Clinical practitioners should be aware of the impact caused by exercise in the interpretation of miRNA data. Copyright © 2018 Elsevier B.V. All rights reserved.

Analysis of sea ice and phytoplankton biomarkers in marine sediments from the Nordic Seas - a calibration study

NASA Astrophysics Data System (ADS)

Navarro Rodriguez, A.; Cabedo Sanz, P.; Belt, S.; Brown, T.; Knies, J.; Husum, K.; Giraudeau, J.

2012-04-01

The work presented here is part of the Changing Arctic and SubArctic Environment program (EU CASE) which is an Initial Training Network (ITN) on climate change and marine environment and is an interdisciplinary project focussing on biological proxies. One of these proxies is the sea ice diatom biomarker IP25 which is a highly branched isoprenoid (HBI) alkene synthesised by some Arctic sea-ice diatoms and has been shown to be a specific, stable and sensitive proxy measure of Arctic sea ice when detected in underlying sediments (Belt et al., 2007). The current study focuses on two key elements: (1) An analytical calibration of IP25 isolated from marine sediments and purified using a range of chromatographic methods was conducted in order to improve the quantification of this biomarker in sediment extracts. (2) Analysis of >30 near-surface sediments from the Nordic Seas was carried out to quantify biomarkers previously suggested as indicators of open-water phytoplankton (brassicasterol) (Müller et al., 2011) and sea-ice (IP25) conditions (Belt et al., 2010). The outcomes of the biomarker analyses were used to make comparisons between proxy data and known sea ice conditions in the study area derived from satellite record over the last 20 years. The results of this study should inform longer timescale reconstructions of sea ice conditions in the Nordic sea in the future. Belt, S.T., Massé, G., Rowland. S.J., Poulin. M., Michel. C., LeBlanc. B., (2007). A novel chemical fossil of palaeo sea ice : IP25 . Organic Geochemistry 38 (16-27). Belt, S. T., Vare, L. L., Massé, G., Manners, H. R., Price, J. C., MacLachlan, S. E., Andrews, J. T. & Schmidt, S. (2010) 'Striking similarities in temporal changes to spring sea ice occurrence across the central Canadian Arctic Archipelago over the last 7000 years', Quaternary Science Reviews, 29 (25-26), pp. 3489-3504. Müller, J., Wagner, A., Fahl, K., Stein, R., Prange, M., & Lohmann, G. (2011). Towards quantitative sea ice reconstructions in the northern North Atlantic: A combined biomarker and numerical modelling approach. Earth and Planetary Science Letters, 306, 137-148.

3D Slicer as an Image Computing Platform for the Quantitative Imaging Network

PubMed Central

Fedorov, Andriy; Beichel, Reinhard; Kalpathy-Cramer, Jayashree; Finet, Julien; Fillion-Robin, Jean-Christophe; Pujol, Sonia; Bauer, Christian; Jennings, Dominique; Fennessy, Fiona; Sonka, Milan; Buatti, John; Aylward, Stephen; Miller, James V.; Pieper, Steve; Kikinis, Ron

2012-01-01

Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical imaging. In 2008, the National Cancer Institute began building the Quantitative Imaging Network (QIN) initiative with the goal of advancing quantitative imaging in the context of personalized therapy and evaluation of treatment response. Computerized analysis is an important component contributing to reproducibility and efficiency of the quantitative imaging techniques. The success of quantitative imaging is contingent on robust analysis methods and software tools to bring these methods from bench to bedside. 3D Slicer is a free open source software application for medical image computing. As a clinical research tool, 3D Slicer is similar to a radiology workstation that supports versatile visualizations but also provides advanced functionality such as automated segmentation and registration for a variety of application domains. Unlike a typical radiology workstation, 3D Slicer is free and is not tied to specific hardware. As a programming platform, 3D Slicer facilitates translation and evaluation of the new quantitative methods by allowing the biomedical researcher to focus on the implementation of the algorithm, and providing abstractions for the common tasks of data communication, visualization and user interface development. Compared to other tools that provide aspects of this functionality, 3D Slicer is fully open source and can be readily extended and redistributed. In addition, 3D Slicer is designed to facilitate the development of new functionality in the form of 3D Slicer extensions. In this paper, we present an overview of 3D Slicer as a platform for prototyping, development and evaluation of image analysis tools for clinical research applications. To illustrate the utility of the platform in the scope of QIN, we discuss several use cases of 3D Slicer by the existing QIN teams, and we elaborate on the future directions that can further facilitate development and validation of imaging biomarkers using 3D Slicer. PMID:22770690

Methodologies for the quantitative estimation of toxicant dose to cigarette smokers using physical, chemical and bioanalytical data.

PubMed

St Charles, Frank Kelley; McAughey, John; Shepperd, Christopher J

2013-06-01

Methodologies have been developed, described and demonstrated that convert mouth exposure estimates of cigarette smoke constituents to dose by accounting for smoke spilled from the mouth prior to inhalation (mouth-spill (MS)) and the respiratory retention (RR) during the inhalation cycle. The methodologies are applicable to just about any chemical compound in cigarette smoke that can be measured analytically and can be used with ambulatory population studies. Conversion of exposure to dose improves the relevancy for risk assessment paradigms. Except for urinary nicotine plus metabolites, biomarkers generally do not provide quantitative exposure or dose estimates. In addition, many smoke constituents have no reliable biomarkers. We describe methods to estimate the RR of chemical compounds in smoke based on their vapor pressure (VP) and to estimate the MS for a given subject. Data from two clinical studies were used to demonstrate dose estimation for 13 compounds, of which only 3 have urinary biomarkers. Compounds with VP > 10(-5) Pa generally have RRs of 88% or greater, which do not vary appreciably with inhalation volume (IV). Compounds with VP < 10(-7) Pa generally have RRs dependent on IV and lung exposure time. For MS, mean subject values from both studies were slightly greater than 30%. For constituents with urinary biomarkers, correlations with the calculated dose were significantly improved over correlations with mouth exposure. Of toxicological importance is that the dose correlations provide an estimate of the metabolic conversion of a constituent to its respective biomarker.

Electron Spin Resonance (ESR) for the study of Reactive Oxygen Species (ROS) on the isolated frog skin (Pelophylax bergeri): A non-invasive method for environmental monitoring.

PubMed

D'Errico, Gerardino; Vitiello, Giuseppe; De Tommaso, Gaetano; Abdel-Gawad, Fagr Kh; Brundo, Maria Violetta; Ferrante, Margherita; De Maio, Anna; Trocchia, Samantha; Bianchi, Anna Rita; Ciarcia, Gaetano; Guerriero, Giulia

2018-04-11

Reactive oxygen species (ROS) in biological tissues of elected biosentinels represent an optimal biomarker for eco-monitoring of polluted areas. Electron spin resonance (ESR) is the most definitive method for detecting, quantifying and possibly identifying radicals in complex systems. A non-invasive method for monitoring polluted areas by the quantitative determination of ROS in frog skin biopsy is presented. We assessed by ESR spectroscopy the ROS level in adult male of Pelophylax bergeri, specie not a risk of extinction, collected from the polluted Sarno River (SA, Italy) basin. The spin-trap ESR method was validated by immunohistochemical analysis of the well-assessed pollution biomarkers cytochrome P450 aromatase 1A (CYP1A) and glutathione S-transferase (GST), and by determining the poly(ADPribose) polymerase (PARP) and GST enzymatic activity. ROS concentration in skin samples from frogs collected in the polluted area is significantly higher than that determined for the unpolluted reference area. Immunohistochemical analysis of CYP1A and GST supported the reliability of our approach, even in the absence of evident morphological and ultrastructural differences. PARP activity assay, connected to possible oxidative DNA damage, and the detoxification index by GST enzymatic assay give statistically significant evidence that higher levels of ROS are associated to alterations of the different biomarkers. ROS concentration, measured by ESR on isolated frog skin, through the presented non-lethal method, is a reliable biomarker for toxicity screening and represents a useful basic datum for future modelling studies on environmental monitoring and biodiversity loss prevention. Copyright © 2018 Elsevier Inc. All rights reserved.

Differential protein-coding gene and long noncoding RNA expression in smoking-related lung squamous cell carcinoma.

PubMed

Li, Shicheng; Sun, Xiao; Miao, Shuncheng; Liu, Jia; Jiao, Wenjie

2017-11-01

Cigarette smoking is one of the greatest preventable risk factors for developing cancer, and most cases of lung squamous cell carcinoma (lung SCC) are associated with smoking. The pathogenesis mechanism of tumor progress is unclear. This study aimed to identify biomarkers in smoking-related lung cancer, including protein-coding gene, long noncoding RNA, and transcription factors. We selected and obtained messenger RNA microarray datasets and clinical data from the Gene Expression Omnibus database to identify gene expression altered by cigarette smoking. Integrated bioinformatic analysis was used to clarify biological functions of the identified genes, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, the construction of a protein-protein interaction network, transcription factor, and statistical analyses. Subsequent quantitative real-time PCR was utilized to verify these bioinformatic analyses. Five hundred and ninety-eight differentially expressed genes and 21 long noncoding RNA were identified in smoking-related lung SCC. GO and KEGG pathway analysis showed that identified genes were enriched in the cancer-related functions and pathways. The protein-protein interaction network revealed seven hub genes identified in lung SCC. Several transcription factors and their binding sites were predicted. The results of real-time quantitative PCR revealed that AURKA and BIRC5 were significantly upregulated and LINC00094 was downregulated in the tumor tissues of smoking patients. Further statistical analysis indicated that dysregulation of AURKA, BIRC5, and LINC00094 indicated poor prognosis in lung SCC. Protein-coding genes AURKA, BIRC5, and LINC00094 could be biomarkers or therapeutic targets for smoking-related lung SCC. © 2017 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.

Comprehensive analytical strategy for biomonitoring of pesticides in urine by liquid chromatography–orbitrap high resolution masss pectrometry.

PubMed

Roca, M; Leon, N; Pastor, A; Yusà, V

2014-12-29

In this study we propose an analytical strategy that combines a target approach for the quantitative analysis of contemporary pesticide metabolites with a comprehensive post-target screening for the identification of biomarkers of exposure to environmental contaminants in urine using liquid chromatography coupled to high-resolution mass spectrometry (LC–HRMS). The quantitative method for the target analysis of 29 urinary metabolites of organophosphate (OP) insecticides, synthetic pyrethroids, herbicides and fungicides was validated after a previous statistical optimization of the main factors governing the ion source ionization and a fragmentation study using the high energy collision dissociation (HCD) cell. The full scan accurate mass data were acquired with a resolving power of 50,000 FWHM (scan speed, 2 Hz), in both ESI+ and ESI− modes, and with and without HCD-fragmentation. The method – LOQ was lower than 3.2 μg L−1 for the majority of the analytes. For post-target screening a customized theoretical database was built, for the identification of 60 metabolites including pesticides, PAHs, phenols, and other metabolites of environmental pollutants. For identification purposes, accurate exact mass with less than 5 ppm, and diagnostic ions including isotopes and/or fragments were used. The analytical strategy was applied to 20 urine sample collected from children living in Valencia Region. Eleven target metabolites were detected with concentrations ranging from 1.18 to 131 μg L−1. Likewise, several compounds were tentatively identified in the post-target analysis belonging to the families of phthalates, phenols and parabenes. The proposed strategy is suitable for the determination of target pesticide biomarkers in urine in the framework of biomonitoring studies, and appropriate for the identification of other non-target metabolites.

Metabolomics and proteomics technologies to explore the herbal preparation affecting metabolic disorders using high resolution mass spectrometry.

PubMed

Zhang, Aihua; Zhou, Xiaohang; Zhao, Hongwei; Zou, Shiyu; Ma, Chung Wah; Liu, Qi; Sun, Hui; Liu, Liang; Wang, Xijun

2017-01-31

An integrative metabolomics and proteomics approach can provide novel insights in the understanding of biological systems. We have integrated proteome and metabolome data sets for a holistic view of the molecular mechanisms in disease. Using quantitative iTRAQ-LC-MS/MS proteomics coupled with UPLC-Q-TOF-HDMS based metabolomics, we determined the protein and metabolite expression changes in the kidney-yang deficiency syndrome (KYDS) rat model and further investigated the intervention effects of the Jinkui Shenqi Pill (JSP). The VIP-plot of the orthogonal PLS-DA (OPLS-DA) was used for discovering the potential biomarkers to clarify the therapeutic mechanisms of JSP in treating KYDS. The results showed that JSP can alleviate the kidney impairment induced by KYDS. Sixty potential biomarkers, including 5-l-glutamyl-taurine, phenylacetaldehyde, 4,6-dihydroxyquinoline, and xanthurenic acid etc., were definitely up- or down-regulated. The regulatory effect of JSP on the disturbed metabolic pathways was proved by the established metabonomic method. Using pathway analyses, we identified the disturbed metabolic pathways such as taurine and hypotaurine metabolism, pyrimidine metabolism, tyrosine metabolism, tryptophan metabolism, histidine metabolism, steroid hormone biosynthesis, etc. Furthermore, using iTRAQ-based quantitative proteomics analysis, seventeen differential proteins were identified and significantly altered by the JSP treatment. These proteins appear to be involved in Wnt, chemokine, PPAR, and MAPK signaling pathways, etc. Functional pathway analysis revealed that most of the proteins were found to play a key role in the regulation of metabolism pathways. Bioinformatics analysis with the IPA software found that these differentially-expressed moleculars had a strong correlation with the α-adrenergic signaling, FGF signaling, etc. Our data indicate that high-throughput metabolomics and proteomics can provide an insight on the herbal preparations affecting the metabolic disorders using high resolution mass spectrometry.

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

Cancer.gov

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

Translational Profiles of Medullary Myofibroblasts during Kidney Fibrosis

PubMed Central

Grgic, Ivica; Krautzberger, A. Michaela; Hofmeister, Andreas; Lalli, Matthew; DiRocco, Derek P.; Fleig, Susanne V.; Liu, Jing; Duffield, Jeremy S.; McMahon, Andrew P.; Aronow, Bruce

2014-01-01

Myofibroblasts secrete matrix during chronic injury, and their ablation ameliorates fibrosis. Development of new biomarkers and therapies for CKD will be aided by a detailed analysis of myofibroblast gene expression during the early stages of fibrosis. However, dissociating myofibroblasts from fibrotic kidney is challenging. We therefore adapted translational ribosome affinity purification (TRAP) to isolate and profile mRNA from myofibroblasts and their precursors during kidney fibrosis. We generated and characterized a transgenic mouse expressing an enhanced green fluorescent protein (eGFP)–tagged L10a ribosomal subunit protein under control of the collagen1α1 promoter. We developed a one-step procedure for isolation of polysomal RNA from collagen1α1-eGFPL10a mice subject to unilateral ureteral obstruction and analyzed and validated the resulting transcriptional profiles. Pathway analysis revealed strong gene signatures for cell proliferation, migration, and shape change. Numerous novel genes and candidate biomarkers were upregulated during fibrosis, specifically in myofibroblasts, and we validated these results by quantitative PCR, in situ, and Western blot analysis. This study provides a comprehensive analysis of early myofibroblast gene expression during kidney fibrosis and introduces a new technique for cell-specific polysomal mRNA isolation in kidney injury models that is suited for RNA-sequencing technologies. PMID:24652793

Digital image analysis in pathology: benefits and obligation.

PubMed

Laurinavicius, Arvydas; Laurinaviciene, Aida; Dasevicius, Darius; Elie, Nicolas; Plancoulaine, Benoît; Bor, Catherine; Herlin, Paulette

2012-01-01

Pathology has recently entered the era of personalized medicine. This brings new expectations for the accuracy and precision of tissue-based diagnosis, in particular, when quantification of histologic features and biomarker expression is required. While for many years traditional pathologic diagnosis has been regarded as ground truth, this concept is no longer sufficient in contemporary tissue-based biomarker research and clinical use. Another major change in pathology is brought by the advancement of virtual microscopy technology enabling digitization of microscopy slides and presenting new opportunities for digital image analysis. Computerized vision provides an immediate benefit of increased capacity (automation) and precision (reproducibility), but not necessarily the accuracy of the analysis. To achieve the benefit of accuracy, pathologists will have to assume an obligation of validation and quality assurance of the image analysis algorithms. Reference values are needed to measure and control the accuracy. Although pathologists' consensus values are commonly used to validate these tools, we argue that the ground truth can be best achieved by stereology methods, estimating the same variable as an algorithm is intended to do. Proper adoption of the new technology will require a new quantitative mentality in pathology. In order to see a complete and sharp picture of a disease, pathologists will need to learn to use both their analogue and digital eyes.

Quantitative bone scan lesion area as an early surrogate outcome measure indicative of overall survival in metastatic prostate cancer.

PubMed

Brown, Matthew S; Kim, Grace Hyun J; Chu, Gregory H; Ramakrishna, Bharath; Allen-Auerbach, Martin; Fischer, Cheryce P; Levine, Benjamin; Gupta, Pawan K; Schiepers, Christiaan W; Goldin, Jonathan G

2018-01-01

A clinical validation of the bone scan lesion area (BSLA) as a quantitative imaging biomarker was performed in metastatic castration-resistant prostate cancer (mCRPC). BSLA was computed from whole-body bone scintigraphy at baseline and week 12 posttreatment in a cohort of 198 mCRPC subjects (127 treated and 71 placebo) from a clinical trial involving a different drug from the initial biomarker development. BSLA computation involved automated image normalization, lesion segmentation, and summation of the total area of segmented lesions on bone scan AP and PA views as a measure of tumor burden. As a predictive biomarker, treated subjects with baseline BSLA [Formula: see text] had longer survival than those with higher BSLA ([Formula: see text] and [Formula: see text]). As a surrogate outcome biomarker, subjects were categorized as progressive disease (PD) if the BSLA increased by a prespecified 30% or more from baseline to week 12 and non-PD otherwise. Overall survival rates between PD and non-PD groups were statistically different ([Formula: see text] and [Formula: see text]). Subjects without PD at week 12 had longer survival than subjects with PD: median 398 days versus 280 days. BSLA has now been demonstrated to be an early surrogate outcome for overall survival in different prostate cancer drug treatments.

Searching for biomarkers of CDKL5 disorder: early-onset visual impairment in CDKL5 mutant mice.

PubMed

Mazziotti, Raffaele; Lupori, Leonardo; Sagona, Giulia; Gennaro, Mariangela; Della Sala, Grazia; Putignano, Elena; Pizzorusso, Tommaso

2017-06-15

CDKL5 disorder is a neurodevelopmental disorder still without a cure. Murine models of CDKL5 disorder have been recently generated raising the possibility of preclinical testing of treatments. However, unbiased, quantitative biomarkers of high translational value to monitor brain function are still missing. Moreover, the analysis of treatment is hindered by the challenge of repeatedly and non-invasively testing neuronal function. We analyzed the development of visual responses in a mouse model of CDKL5 disorder to introduce visually evoked responses as a quantitative method to assess cortical circuit function. Cortical visual responses were assessed in CDKL5 null male mice, heterozygous females, and their respective control wild-type littermates by repeated transcranial optical imaging from P27 until P32. No difference between wild-type and mutant mice was present at P25-P26 whereas defective responses appeared from P27-P28 both in heterozygous and homozygous CDKL5 mutant mice. These results were confirmed by visually evoked potentials (VEPs) recorded from the visual cortex of a different cohort. The previously imaged mice were also analyzed at P60-80 using VEPs, revealing a persistent reduction of response amplitude, reduced visual acuity and defective contrast function. The level of adult impairment was significantly correlated with the reduction in visual responses observed during development. Support vector machine showed that multi-dimensional visual assessment can be used to automatically classify mutant and wt mice with high reliability. Thus, monitoring visual responses represents a promising biomarker for preclinical and clinical studies on CDKL5 disorder. © The Author 2017. Published by Oxford University Press.

The Effects of Exercise on Cardiovascular Biomarkers: New Insights, Recent Data, and Applications.

PubMed

Che, Lin; Li, Dong

2017-01-01

The benefit of regular exercise or physical activity with appropriate intensity on improving cardiopulmonary function and endurance has long been accepted with less controversy. The challenge remains, however, quantitatively evaluate the effect of exercise on cardiovascular health due in part to the amount and intensity of exercise varies widely plus lack of effective, robust and efficient biomarker evaluation systems. Better evaluating the overall function of biomarker and validate biomarkers utility in cardiovascular health should improve the evidence regarding the benefit or the effect of exercise or physical activity on cardiovascular health, in turn increasing the efficiency of the biomarker on individuals with mild to moderate cardiovascular risk. In this review, beyond traditional cytokines, chemokines and inflammatory factors, we systemic reviewed the latest novel biomarkers in metabolomics, genomics, proteomics, and molecular imaging mainly focus on heart health, as well as cardiovascular diseases such as atherosclerosis and ischemic heart disease. Furthermore, we highlight the state-of-the-art biomarker developing techniques and its application in the field of heart health. Finally, we discuss the clinical relevance of physical activity and exercise on key biomarkers in molecular basis and practical considerations.

The Role of High-resolution Peripheral Quantitative Computed Tomography as a Biomarker for Joint Damage in Inflammatory Arthritis.

PubMed

Tam, Lai-Shan

2016-10-01

Since 2011, members of the SPECTRA Collaboration (Study grouP for xtrEme-Computed Tomography in Rheumatoid Arthritis) have investigated the validity, reliability, and responsiveness of high-resolution peripheral quantitative computed tomography (HR-pQCT) as a biomarker for joint damage in inflammatory arthritis. Presented in this series of articles are a systematic review of HR-pQCT-related findings to date, a review of selected images of cortical and subchondral trabecular bone of metacarpophalangeal (MCP) joints, results of a consensus process to standardize the definition of erosions and their quantification, as well as an examination of the effect of joint flexion on width and volume assessment of the joint space.

Systems Toxicology: From Basic Research to Risk Assessment

PubMed Central

2014-01-01

Systems Toxicology is the integration of classical toxicology with quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Society demands increasingly close scrutiny of the potential health risks associated with exposure to chemicals present in our everyday life, leading to an increasing need for more predictive and accurate risk-assessment approaches. Developing such approaches requires a detailed mechanistic understanding of the ways in which xenobiotic substances perturb biological systems and lead to adverse outcomes. Thus, Systems Toxicology approaches offer modern strategies for gaining such mechanistic knowledge by combining advanced analytical and computational tools. Furthermore, Systems Toxicology is a means for the identification and application of biomarkers for improved safety assessments. In Systems Toxicology, quantitative systems-wide molecular changes in the context of an exposure are measured, and a causal chain of molecular events linking exposures with adverse outcomes (i.e., functional and apical end points) is deciphered. Mathematical models are then built to describe these processes in a quantitative manner. The integrated data analysis leads to the identification of how biological networks are perturbed by the exposure and enables the development of predictive mathematical models of toxicological processes. This perspective integrates current knowledge regarding bioanalytical approaches, computational analysis, and the potential for improved risk assessment. PMID:24446777

Label-free protein profiling of formalin-fixed paraffin-embedded (FFPE) heart tissue reveals immediate mitochondrial impairment after ionising radiation.

PubMed

Azimzadeh, Omid; Scherthan, Harry; Yentrapalli, Ramesh; Barjaktarovic, Zarko; Ueffing, Marius; Conrad, Marcus; Neff, Frauke; Calzada-Wack, Julia; Aubele, Michaela; Buske, Christian; Atkinson, Michael J; Hauck, Stefanie M; Tapio, Soile

2012-04-18

Qualitative proteome profiling of formalin-fixed, paraffin-embedded (FFPE) tissue is advancing the field of clinical proteomics. However, quantitative proteome analysis of FFPE tissue is hampered by the lack of an efficient labelling method. The usage of conventional protein labelling on FFPE tissue has turned out to be inefficient. Classical labelling targets lysine residues that are blocked by the formalin treatment. The aim of this study was to establish a quantitative proteomics analysis of FFPE tissue by combining the label-free approach with optimised protein extraction and separation conditions. As a model system we used FFPE heart tissue of control and exposed C57BL/6 mice after total body irradiation using a gamma ray dose of 3 gray. We identified 32 deregulated proteins (p≤0.05) in irradiated hearts 24h after the exposure. The proteomics data were further evaluated and validated by bioinformatics and immunoblotting investigation. In good agreement with our previous results using fresh-frozen tissue, the analysis indicated radiation-induced alterations in three main biological pathways: respiratory chain, lipid metabolism and pyruvate metabolism. The label-free approach enables the quantitative measurement of radiation-induced alterations in FFPE tissue and facilitates retrospective biomarker identification using clinical archives. Copyright © 2012 Elsevier B.V. All rights reserved.

Systems toxicology: from basic research to risk assessment.

PubMed

Sturla, Shana J; Boobis, Alan R; FitzGerald, Rex E; Hoeng, Julia; Kavlock, Robert J; Schirmer, Kristin; Whelan, Maurice; Wilks, Martin F; Peitsch, Manuel C

2014-03-17

Systems Toxicology is the integration of classical toxicology with quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Society demands increasingly close scrutiny of the potential health risks associated with exposure to chemicals present in our everyday life, leading to an increasing need for more predictive and accurate risk-assessment approaches. Developing such approaches requires a detailed mechanistic understanding of the ways in which xenobiotic substances perturb biological systems and lead to adverse outcomes. Thus, Systems Toxicology approaches offer modern strategies for gaining such mechanistic knowledge by combining advanced analytical and computational tools. Furthermore, Systems Toxicology is a means for the identification and application of biomarkers for improved safety assessments. In Systems Toxicology, quantitative systems-wide molecular changes in the context of an exposure are measured, and a causal chain of molecular events linking exposures with adverse outcomes (i.e., functional and apical end points) is deciphered. Mathematical models are then built to describe these processes in a quantitative manner. The integrated data analysis leads to the identification of how biological networks are perturbed by the exposure and enables the development of predictive mathematical models of toxicological processes. This perspective integrates current knowledge regarding bioanalytical approaches, computational analysis, and the potential for improved risk assessment.

Rapid quantitative analysis of 8-iso-prostaglandin-F(2alpha) using liquid chromatography-tandem mass spectrometry and comparison with an enzyme immunoassay method.

PubMed

Dahl, Jeffrey H; van Breemen, Richard B

2010-09-15

A rapid liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay was developed for the measurement of urinary 8-iso-prostaglandin F(2alpha) (8-iso-PGF(2alpha)), a biomarker of lipid peroxidation. Because urine contains numerous F(2) prostaglandin isomers, each with identical mass and similar mass spectrometric fragmentation patterns, chromatographic separation of 8-iso-PGF(2alpha) from its isomers is necessary for its quantitative analysis using MS/MS. We were able to achieve this separation using an isocratic LC method with a run time of less than 9min, which is at least threefold faster than previous methods, while maintaining sensitivity, accuracy, precision, and reliability. The limits of detection and quantitation were 53 and 178pg/ml urine, respectively. We compared our method with a commercially available affinity purification and enzyme immunoassay kit and found both assays to be in agreement. Despite the high sensitivity of the enzyme immunoassay method, it is more expensive and has a narrower dynamic range than LC-MS/MS. Our method was optimized for rapid measurement of 8-iso-PGF(2alpha) in urine, and it is ideally suited for clinical sample analysis. 2010 Elsevier Inc. All rights reserved.

Amino terminal pro brain natriuretic peptide predicts all-cause mortality in patients with chronic obstructive pulmonary disease: Systematic review and meta-analysis.

PubMed

Pavasini, Rita; Tavazzi, Guido; Biscaglia, Simone; Guerra, Federico; Pecoraro, Alessandro; Zaraket, Fatima; Gallo, Francesco; Spitaleri, Giosafat; Contoli, Marco; Ferrari, Roberto; Campo, Gianluca

2017-05-01

Natriuretic peptides (NPs) are a family of prognostic biomarkers in patients with heart failure (HF). HF is one of the most frequent comorbidities in patients with chronic obstructive pulmonary disease (COPD). However, the prognostic role of NP in COPD patients remains unclear. The aim of this meta-analysis was to evaluate the relation between NP and all-cause mortality in COPD patients. We performed a systematic review and meta-analysis of observational studies assessing prognostic implications of elevated NP levels on all-cause mortality in COPD patients. Nine studies were considered for qualitative analysis for a total of 2788 patients. Only two studies focused on Mid Regional-pro Atrial Natriuretic Peptide (MR-proANP) and brain natriuretic peptide (BNP), respectively, but seven studies focused on pro-BNP (NT-proBNP) and were included in the quantitative analysis. Elevated NT-proBNP values were related to increased risk of all-cause mortality in COPD patients both with and without exacerbation (hazard ratio (HR): 2.87, p < 0.0001 and HR: 3.34, p = 0.04, respectively). The results were confirmed also after meta-regression analysis for confounding factors (previous cardiovascular history, hypertension, HF, forced expiratory volume at 1 second and mean age). NT-proBNP may be considered a reliable predictive biomarker of poor prognosis in patients with COPD.

Long non-coding RNA PVT1 as a novel potential biomarker for predicting the prognosis of colorectal cancer.

PubMed

Fan, Heng; Zhu, Jian-Hua; Yao, Xue-Qing

2018-05-01

Long non-coding RNA (lncRNA) plays a very important role in the occurrence and development of various tumors, and is a potential biomarker for cancer diagnosis and prognosis. The purpose of this study was to investigate the relationship between the expression of lncRNA plasmacytoma variant translocation 1 (PVT1) and the prognostic significance in patients with colorectal cancer. The expression of PVT1 was measured by real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) in cancerous and adjacent tissues of 210 colorectal cancer patients. The disease-free survival and overall survival of colorectal cancer patients were evaluated by Kaplan-Meier analysis, and univariate and multivariate analysis were performed by Cox proportional-hazards model. Our results revealed that PVT1 expression in cancer tissues of colorectal cancer was significantly higher than that of adjacent tissues ( P<0.001). High PVT1 expression was increased by 51.4% (108/210), which was significantly correlated with the tumor differentiation, the depth of invasion, the stage of tumor, node, metastasis (TNM), and lymphatic metastasis. The Kaplan-Meier analysis showed that high PVT1 expression resulted in a shorter disease-free survival (Log-rank test P<0.001) and overall survival (Log-rank test P<0.001) compared with the low PVT1 expression group in colorectal cancer patients, whether at TNM I/II stage or at TNM III/IV stage. A multivariate Cox regression analysis demonstrated that high PVT1 expression was an independent predictor of poor prognosis in colorectal cancer patients. Our results suggest that high PVT1 expression might be a potential biomarker for assessing tumor recurrence and prognosis in colorectal cancer patients.

Application of artificial neural network model combined with four biomarkers in auxiliary diagnosis of lung cancer.

PubMed

Duan, Xiaoran; Yang, Yongli; Tan, Shanjuan; Wang, Sihua; Feng, Xiaolei; Cui, Liuxin; Feng, Feifei; Yu, Songcheng; Wang, Wei; Wu, Yongjun

2017-08-01

The purpose of the study was to explore the application of artificial neural network model in the auxiliary diagnosis of lung cancer and compare the effects of back-propagation (BP) neural network with Fisher discrimination model for lung cancer screening by the combined detections of four biomarkers of p16, RASSF1A and FHIT gene promoter methylation levels and the relative telomere length. Real-time quantitative methylation-specific PCR was used to detect the levels of three-gene promoter methylation, and real-time PCR method was applied to determine the relative telomere length. BP neural network and Fisher discrimination analysis were used to establish the discrimination diagnosis model. The levels of three-gene promoter methylation in patients with lung cancer were significantly higher than those of the normal controls. The values of Z(P) in two groups were 2.641 (0.008), 2.075 (0.038) and 3.044 (0.002), respectively. The relative telomere lengths of patients with lung cancer (0.93 ± 0.32) were significantly lower than those of the normal controls (1.16 ± 0.57), t = 4.072, P < 0.001. The areas under the ROC curve (AUC) and 95 % CI of prediction set from Fisher discrimination analysis and BP neural network were 0.670 (0.569-0.761) and 0.760 (0.664-0.840). The AUC of BP neural network was higher than that of Fisher discrimination analysis, and Z(P) was 0.76. Four biomarkers are associated with lung cancer. BP neural network model for the prediction of lung cancer is better than Fisher discrimination analysis, and it can provide an excellent and intelligent diagnosis tool for lung cancer.

Automatic vertebral bodies detection of x-ray images using invariant multiscale template matching

NASA Astrophysics Data System (ADS)

Sharifi Sarabi, Mona; Villaroman, Diane; Beckett, Joel; Attiah, Mark; Marcus, Logan; Ahn, Christine; Babayan, Diana; Gaonkar, Bilwaj; Macyszyn, Luke; Raghavendra, Cauligi

2017-03-01

Lower back pain and pathologies related to it are one of the most common results for a referral to a neurosurgical clinic in the developed and the developing world. Quantitative evaluation of these pathologies is a challenge. Image based measurements of angles/vertebral heights and disks could provide a potential quantitative biomarker for tracking and measuring these pathologies. Detection of vertebral bodies is a key element and is the focus of the current work. From the variety of medical imaging techniques, MRI and CT scans have been typically used for developing image segmentation methods. However, CT scans are known to give a large dose of x-rays, increasing cancer risk [8]. MRI can be substituted for CTs when the risk is high [8] but are difficult to obtain in smaller facilities due to cost and lack of expertise in the field [2]. X-rays provide another option with its ability to control the x-ray dosage, especially for young people, and its accessibility for smaller facilities. Hence, the ability to create quantitative biomarkers from x-ray data is especially valuable. Here, we develop a multiscale template matching, inspired by [9], to detect centers of vertebral bodies from x-ray data. The immediate application of such detection lies in developing quantitative biomarkers and in querying similar images in a database. Previously, shape similarity classification methods have been used to address this problem, but these are challenging to use in the presence of variation due to gross pathology and even subtle effects [1].

Identification of predictive biomarkers of disease state in transition dairy cows.

PubMed

Hailemariam, D; Mandal, R; Saleem, F; Dunn, S M; Wishart, D S; Ametaj, B N

2014-05-01

In dairy cows, periparturient disease states, such as metritis, mastitis, and laminitis, are leading to increasingly significant economic losses for the dairy industry. Treatments for these pathologies are often expensive, ineffective, or not cost-efficient, leading to production losses, high veterinary bills, or early culling of the cows. Early diagnosis or detection of these conditions before they manifest themselves could lower their incidence, level of morbidity, and the associated economic losses. In an effort to identify predictive biomarkers for postpartum or periparturient disease states in dairy cows, we undertook a cross-sectional and longitudinal metabolomics study to look at plasma metabolite levels of dairy cows during the transition period, before and after becoming ill with postpartum diseases. Specifically we employed a targeted quantitative metabolomics approach that uses direct flow injection mass spectrometry to track the metabolite changes in 120 different plasma metabolites. Blood plasma samples were collected from 12 dairy cows at 4 time points during the transition period (-4 and -1 wk before and 1 and 4 wk after parturition). Out of the 12 cows studied, 6 developed multiple periparturient disorders in the postcalving period, whereas the other 6 remained healthy during the entire experimental period. Multivariate data analysis (principal component analysis and partial least squares discriminant analysis) revealed a clear separation between healthy controls and diseased cows at all 4 time points. This analysis allowed us to identify several metabolites most responsible for separating the 2 groups, especially before parturition and the start of any postpartum disease. Three metabolites, carnitine, propionyl carnitine, and lysophosphatidylcholine acyl C14:0, were significantly elevated in diseased cows as compared with healthy controls as early as 4 wk before parturition, whereas 2 metabolites, phosphatidylcholine acyl-alkyl C42:4 and phosphatidylcholine diacyl C42:6, could be used to discriminate healthy controls from diseased cows 1 wk before parturition. A 3-metabolite plasma biomarker profile was developed that could predict which cows would develop periparturient diseases, up to 4 wk before clinical symptoms appearing, with a sensitivity of 87% and a specificity of 85%. This is the first report showing that periparturient diseases can be predicted in dairy cattle before their development using a multimetabolite biomarker model. Further research is warranted to validate these potential predictive biomarkers. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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. Using a mass balance model we can use the carbon isotope ratios of Sphagnum biomarkers to assess the contribution of methane-derived CO2, and hence, the wetness of the peatland surface.

Highly sensitive and quantitative detection of rare pathogens through agarose droplet microfluidic emulsion PCR at the single-cell level.

PubMed

Zhu, Zhi; Zhang, Wenhua; Leng, Xuefei; Zhang, Mingxia; Guan, Zhichao; Lu, Jiangquan; Yang, Chaoyong James

2012-10-21

Genetic alternations can serve as highly specific biomarkers to distinguish fatal bacteria or cancer cells from their normal counterparts. However, these mutations normally exist in very rare amount in the presence of a large excess of non-mutated analogs. Taking the notorious pathogen E. coli O157:H7 as the target analyte, we have developed an agarose droplet-based microfluidic ePCR method for highly sensitive, specific and quantitative detection of rare pathogens in the high background of normal bacteria. Massively parallel singleplex and multiplex PCR at the single-cell level in agarose droplets have been successfully established. Moreover, we challenged the system with rare pathogen detection and realized the sensitive and quantitative analysis of a single E. coli O157:H7 cell in the high background of 100,000 excess normal K12 cells. For the first time, we demonstrated rare pathogen detection through agarose droplet microfluidic ePCR. Such a multiplex single-cell agarose droplet amplification method enables ultra-high throughput and multi-parameter genetic analysis of large population of cells at the single-cell level to uncover the stochastic variations in biological systems.

Transcriptome discovery in non-model wild fish species for the development of quantitative transcript abundance assays.

PubMed

Hahn, Cassidy M; Iwanowicz, Luke R; Cornman, Robert S; Mazik, Patricia M; Blazer, Vicki S

2016-12-01

Environmental studies increasingly identify the presence of both contaminants of emerging concern (CECs) and legacy contaminants in aquatic environments; however, the biological effects of these compounds on resident fishes remain largely unknown. High throughput methodologies were employed to establish partial transcriptomes for three wild-caught, non-model fish species; smallmouth bass (Micropterus dolomieu), white sucker (Catostomus commersonii) and brown bullhead (Ameiurus nebulosus). Sequences from these transcriptome databases were utilized in the development of a custom nCounter CodeSet that allowed for direct multiplexed measurement of 50 transcript abundance endpoints in liver tissue. Sequence information was also utilized in the development of quantitative real-time PCR (qPCR) primers. Cross-species hybridization allowed the smallmouth bass nCounter CodeSet to be used for quantitative transcript abundance analysis of an additional non-model species, largemouth bass (Micropterus salmoides). We validated the nCounter analysis data system with qPCR for a subset of genes and confirmed concordant results. Changes in transcript abundance biomarkers between sexes and seasons were evaluated to provide baseline data on transcript modulation for each species of interest. Published by Elsevier Inc.

The role of quantitative mass spectrometry in the discovery of pancreatic cancer biomarkers for translational science

PubMed Central

2014-01-01

In the post-genomic era, it has become evident that genetic changes alone are not sufficient to understand most disease processes including pancreatic cancer. Genome sequencing has revealed a complex set of genetic alterations in pancreatic cancer such as point mutations, chromosomal losses, gene amplifications and telomere shortening that drive cancerous growth through specific signaling pathways. Proteome-based approaches are important complements to genomic data and provide crucial information of the target driver molecules and their post-translational modifications. By applying quantitative mass spectrometry, this is an alternative way to identify biomarkers for early diagnosis and personalized medicine. We review the current quantitative mass spectrometric technologies and analyses that have been developed and applied in the last decade in the context of pancreatic cancer. Examples of candidate biomarkers that have been identified from these pancreas studies include among others, asporin, CD9, CXC chemokine ligand 7, fibronectin 1, galectin-1, gelsolin, intercellular adhesion molecule 1, insulin-like growth factor binding protein 2, metalloproteinase inhibitor 1, stromal cell derived factor 4, and transforming growth factor beta-induced protein. Many of these proteins are involved in various steps in pancreatic tumor progression including cell proliferation, adhesion, migration, invasion, metastasis, immune response and angiogenesis. These new protein candidates may provide essential information for the development of protein diagnostics and targeted therapies. We further argue that new strategies must be advanced and established for the integration of proteomic, transcriptomic and genomic data, in order to enhance biomarker translation. Large scale studies with meta data processing will pave the way for novel and unexpected correlations within pancreatic cancer, that will benefit the patient, with targeted treatment. PMID:24708694

Quantitative EEG Neurometric Analysis-Guided Neurofeedback Treatment in Postconcussion Syndrome (PCS): Forty Cases. How Is Neurometric Analysis Important for the Treatment of PCS and as a Biomarker?

PubMed

Surmeli, Tanju; Eralp, Emin; Mustafazade, Ilham; Kos, Ismet Hadi; Özer, Gül Elif; Surmeli, Orkun H

2017-05-01

Postconcussion syndrome (PCS) has been used to describe a range of residual symptoms that persist 12 months or more after the injury, often despite a lack of evidence of brain abnormalities on magnetic resonance imaging and computed tomography scans. In this clinical case series, the efficacy of quantitative EEG-guided neurofeedback in 40 subjects diagnosed with PCS was investigated. Overall improvement was seen in all the primary (Symptom Assessment-45 Questionnaire, Clinical Global Impressions Scale, Hamilton Depression Scale) and secondary measures (Minnesota Multiphasic Personality Inventory, Test of Variables for Attention). The Neuroguide Traumatic Brain Index for the group also showed a decrease. Thirty-nine subjects were followed up long term with an average follow-up length of 3.1 years (CI = 2.7-3.3). All but 2 subjects were stable and were off medication. Overall neurofeedback treatment was shown to be effective in this group of subjects studied.

Prognosis for Survival of Young Women with Breast Cancer by Quantitative p53 Immunohistochemistry

PubMed Central

Axelrod, David E.; Shah, Kinsuk; Yang, Qifeng; Haffty, Bruce G.

2015-01-01

p53 protein detected immunohistochemically has not been accepted as a biomarker for breast cancer patients because of disparate reports of the relationship between the amount of p53 protein detected and patient survival. The purpose of this study was to determine experimental conditions and methods of data analysis for which p53 stain intensity could be prognostic for survival of young breast cancer patients. A tissue microarray of specimens from 93 patients was stained with anti-p53 antibody, and stain intensity measured with a computer-aided image analysis system. A cut-point at one standard deviation below the mean of the distribution of p53 stain intensity separated patients into two groups with significantly different survival. These results were confirmed by Quantitative Nuclear Grade determined by DNA-specific Feulgen staining. P53 provided information beyond ER and PR status. Therefore, under the conditions reported here, p53 protein can be an effective prognostic factor for young breast cancer patients. PMID:26322145

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

PubMed

Amacher, David E

2010-05-15

Biomarkers are biometric measurements that provide critical quantitative information about the biological condition of the animal or individual being tested. In drug safety studies, established toxicity biomarkers are used along with other conventional study data to determine dose-limiting organ toxicity, and to define species sensitivity for new chemical entities intended for possible use as human medicines. A continuing goal of drug safety scientists in the pharmaceutical industry is to discover and develop better trans-species biomarkers that can be used to determine target organ toxicities for preclinical species in short-term studies at dose levels that are some multiple of the intended human dose and again later in full development for monitoring clinical trials at lower therapeutic doses. Of particular value are early, predictive, noninvasive biomarkers that have in vitro, in vivo, and clinical transferability. Such translational biomarkers bridge animal testing used in preclinical science and human studies that are part of subsequent clinical testing. Although suitable for in vivo preclinical regulatory studies, conventional hepatic safety biomarkers are basically confirmatory markers because they signal organ toxicity after some pathological damage has occurred, and are therefore not well-suited for short-term, predictive screening assays early in the discovery-to-development progression of new chemical entities (NCEs) available in limited quantities. Efforts between regulatory agencies and the pharmaceutical industry are underway for the coordinated discovery, qualification, verification and validation of early predictive toxicity biomarkers. Early predictive safety biomarkers are those that are detectable and quantifiable prior to the onset of irreversible tissue injury and which are associated with a mechanism of action relevant to a specific type of potential hepatic injury. Potential drug toxicity biomarkers are typically endogenous macromolecules in biological fluids with varying immunoreactivity which can present bioanalytical challenges when first discovered. The potential success of these efforts is greatly enhanced by recent advances in two closely linked technologies, toxicoproteomics and targeted, quantitative mass spectrometry. This review focuses on the examination of the current status of these technologies as they relate to the discovery and development of novel preclinical biomarkers of hepatotoxicity. A critical assessment of the current literature reveals two distinct lines of safety biomarker investigation, (1) peripheral fluid biomarkers of organ toxicity and (2) tissue or cell-based toxicity signatures. Improved peripheral fluid biomarkers should allow the sensitive detection of potential organ toxicity prior to the onset of overt organ pathology. Advancements in tissue or cell-based toxicity biomarkers will provide sensitive in vitro or ex vivo screening systems based on toxicity pathway markers. An examination of the current practices in clinical pathology and the critical evaluation of some recently proposed biomarker candidates in comparison to the desired characteristics of an ideal toxicity biomarker lead this author to conclude that a combination of selected biomarkers will be more informative if not predictive of potential animal organ toxicity than any single biomarker, new or old. For the practical assessment of combinations of conventional and/or novel toxicity biomarkers in rodent and large animal preclinical species, mass spectrometry has emerged as the premier analytical tool compared to specific immunoassays or functional assays. Selected and multiple reaction monitoring mass spectrometry applications make it possible for this same basic technology to be used in the progressive stages of biomarker discovery, development, and more importantly, routine study applications without the use of specific antibody reagents. This technology combined with other "omics" technologies can provide added selectivity and sensitivity in preclinical drug safety testing.

Superolateral Hoffa's fat pad (SHFP) oedema and patellar cartilage volume loss: quantitative analysis using longitudinal data from the Foundation for the National Institute of Health (FNIH) Osteoarthritis Biomarkers Consortium.

PubMed

Haj-Mirzaian, Arya; Guermazi, Ali; Hafezi-Nejad, Nima; Sereni, Christopher; Hakky, Michael; Hunter, David J; Zikria, Bashir; Roemer, Frank W; Demehri, Shadpour

2018-04-12

To determine the association of superolateral Hoffa's fat pad (SHFP) oedema and patellofemoral joint structural damage in participants of Foundation for the National Institute of Health Osteoarthritis Biomarkers Consortium study. Baseline and 24-month MRIs of 600 subjects were assessed. The presence of SHFP oedema (using 0-3 grading scale) and patellar morphology metrics were determined using baseline MRI. Quantitative patellar cartilage volume and semi-quantitative MRI osteoarthritis knee score (MOAKS) variables were extracted. The associations between SHFP oedema and patellar cartilage damage, bone marrow lesion (BML), osteophyte and morphology were evaluated in cross-sectional model. In longitudinal analysis, the associations between oedema and cartilage volume loss (defined using reliable change index) and MOAKS worsening were evaluated. In cross-sectional evaluations, the presence of SHFP oedema was associated with simultaneous lateral patellar cartilage/BML defects and inferior-medial patellar osteophyte size. A significant positive correlation between the degree of patella alta and SHFP oedema was detected (r = 0.259, p < 0.001). The presence of oedema was associated with 24-month cartilage volume loss (odds ratio (OR) 2.11, 95% confidence interval 1.46-3.06) and medial patellar BML size (OR 1.92 (1.15-3.21)) and number (OR 2.50 (1.29-4.88)) worsening. The optimal cut-off value for the grade of baseline SHFP oedema regarding both presence and worsening of patellar structural damage was ≥ 1 (presence of any SHFP hyperintensity). The presence of SHFP oedema could be considered as a predictor of future patellar cartilage loss and BML worsening, and an indicator of simultaneous cartilage, BML and osteophyte defects. • SHFP oedema was associated with simultaneous lateral patellar OA-related structural damage. • SHFP oedema was associated with longitudinal patellar cartilage loss over 24 months. • SHFP oedema could be considered as indicator and predictor of patellar OA.

A Potential Biomarker in Amyotrophic Lateral Sclerosis: Can Assessment of Brain Iron Deposition with SWI and Corticospinal Tract Degeneration with DTI Help?

PubMed

Sheelakumari, R; Madhusoodanan, M; Radhakrishnan, A; Ranjith, G; Thomas, B

2016-02-01

Iron-mediated oxidative stress plays a pivotal role in the pathogenesis of amyotrophic lateral sclerosis. This study aimed to assess iron deposition qualitatively and quantitatively by using SWI and microstructural changes in the corticospinal tract by using DTI in patients with amyotrophic lateral sclerosis. Seventeen patients with amyotrophic lateral sclerosis and 15 age- and sex-matched controls underwent brain MR imaging with SWI and DTI. SWI was analyzed for both signal-intensity scoring and quantitative estimation of iron deposition in the anterior and posterior banks of the motor and sensory cortices and deep gray nuclei. The diffusion measurements along the corticospinal tract at the level of pons and medulla were obtained by ROI analysis. Patients with amyotrophic lateral sclerosis showed reduced signal-intensity grades in the posterior bank of the motor cortex bilaterally. Quantitative analysis confirmed significantly higher iron content in the posterior bank of the motor cortex in patients with amyotrophic lateral sclerosis. In contrast, no significant differences were noted for the anterior bank of the motor cortex, anterior and posterior banks of the sensory cortex, and deep nuclei. Receiver operating characteristic comparison showed a cutoff of 35μg Fe/g of tissue with an area under the curve of 0.78 (P = .008) for the posterior bank of the motor cortex in discriminating patients with amyotrophic lateral sclerosis from controls. Fractional anisotropy was lower in the pyramidal tracts of patients with amyotrophic lateral sclerosis at the pons and medulla on either side, along with higher directionally averaged mean diffusivity values. The combination of SWI and DTI revealed an area under the curve of 0.784 for differentiating patients with amyotrophic lateral sclerosis from controls. Measurements of motor cortex iron deposition and diffusion tensor parameters of the corticospinal tract may be useful biomarkers for the diagnosis of clinically suspected amyotrophic lateral sclerosis. © 2016 by American Journal of Neuroradiology.

Assessment of Biomarkers Associated with Joint Injury and Subsequent Post-Traumatic Arthritis

DTIC Science & Technology

2016-12-01

models of the patella and patellar cartilage (Geomagic Studio, Research Triangle Park, NC). Changes in cartilage thickness between post -operative... quantitative scales, and "Assessment of Biomarkers Associated with Joint Injury and Subsequent Post -Traumatic Arthritis" Start date: 9/30/2012 PIs...Geomagic®). Positive and negative deviations of the bone surface were measured, and defined as the distance to a test surface ( post -fx bone surface

Negative Ion Chemical Ionization Mass Spectrometry for the Analysis of 3,5,6-trichloro-2-pyridinol in Saliva of Rats Exposed to Chlorpyrifos

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

Campbell, James A.; Timchalk, Chuck; Kousba, Ahmed A.

2005-05-01

Organophosphorus (OP) insecticides (e.g. chlorpyrifos) are widely used in a variety of applications, and the potential exists for significant occupational and environmental exposures. They have been associated with more occupational poisoning cases than any other class of insecticides. One of the best approaches for accurately assessing human dosimetry and determining risk from both occupational and environmental exposure is biomonitoring. Biological matrices such as blood and urine have been routinely used for biomonitoring; however, other matrices such as saliva represent a simple and readily obtainable fluid. As a result, saliva has been suggested as an alternative biological matrix for the evaluationmore » of a broad range of biomarkers such as environmental contaminants, drugs of abuse, hormones, chemotherapeutics, heavy metals, and pesticides. Chlorpyrifos (CPF), and its major metabolite, 3,5,6-trichloro-2-pyridinol (TCP), have been quantified in urine and blood as a biomarker for exposure to OP insecticides. The purpose of this study was to develop an analytical approach for detecting and quantitating the levels of TCP in saliva obtained from rats exposed to CPF and to evaluate the potential of saliva as a non-invasive biomonitoring matrix. Adult male rats were administered CPF, and blood and saliva were humanely collected for analysis of TCP and CPF. TCP was detected and quantitated in saliva using negative ion chemical ionization mass spectrometry with selected ion monitoring. Initial results indicate that saliva may be potentially utilized as a non-invasive biomonitoring matrix to determine exposure to organophosphate insecticides.« less

Isolating specific cell and tissue compartments from 3D images for quantitative regional distribution analysis using novel computer algorithms.

PubMed

Fenrich, Keith K; Zhao, Ethan Y; Wei, Yuan; Garg, Anirudh; Rose, P Ken

2014-04-15

Isolating specific cellular and tissue compartments from 3D image stacks for quantitative distribution analysis is crucial for understanding cellular and tissue physiology under normal and pathological conditions. Current approaches are limited because they are designed to map the distributions of synapses onto the dendrites of stained neurons and/or require specific proprietary software packages for their implementation. To overcome these obstacles, we developed algorithms to Grow and Shrink Volumes of Interest (GSVI) to isolate specific cellular and tissue compartments from 3D image stacks for quantitative analysis and incorporated these algorithms into a user-friendly computer program that is open source and downloadable at no cost. The GSVI algorithm was used to isolate perivascular regions in the cortex of live animals and cell membrane regions of stained spinal motoneurons in histological sections. We tracked the real-time, intravital biodistribution of injected fluorophores with sub-cellular resolution from the vascular lumen to the perivascular and parenchymal space following a vascular microlesion, and mapped the precise distributions of membrane-associated KCC2 and gephyrin immunolabeling in dendritic and somatic regions of spinal motoneurons. Compared to existing approaches, the GSVI approach is specifically designed for isolating perivascular regions and membrane-associated regions for quantitative analysis, is user-friendly, and free. The GSVI algorithm is useful to quantify regional differences of stained biomarkers (e.g., cell membrane-associated channels) in relation to cell functions, and the effects of therapeutic strategies on the redistributions of biomolecules, drugs, and cells in diseased or injured tissues. Copyright © 2014 Elsevier B.V. All rights reserved.

Novel cardiac magnetic resonance biomarkers: native T1 and extracellular volume myocardial mapping.

PubMed

Cannaò, Paola Maria; Altabella, Luisa; Petrini, Marcello; Alì, Marco; Secchi, Francesco; Sardanelli, Francesco

2016-04-28

Cardiac magnetic resonance (CMR) is a non-invasive diagnostic tool playing a key role in the assessment of cardiac morphology and function as well as in tissue characterization. Late gadolinium enhancement is a fundamental CMR technique for detecting focal or regional abnormalities such as scar tissue, replacement fibrosis, or inflammation using qualitative, semi-quantitative, or quantitative methods, but not allowing for evaluating the whole myocardium in the presence of diffuse disease. The novel T1 mapping approach permits a quantitative assessment of the entire myocardium providing a voxel-by-voxel map of native T1 relaxation time, obtained before the intravenous administration of gadolinium-based contrast material. Combining T1 data obtained before and after contrast injection, it is also possible to calculate the voxel-by-voxel extracellular volume (ECV), resulting in another myocardial parametric map. This article describes technical challenges and clinical perspectives of these two novel CMR biomarkers: myocardial native T1 and ECV mapping.

Alzheimer’s Disease Neuroimaging Initiative biomarkers as quantitative phenotypes: Genetics core aims, progress, and plans

PubMed Central

Saykin, Andrew J.; Shen, Li; Foroud, Tatiana M.; Potkin, Steven G.; Swaminathan, Shanker; Kim, Sungeun; Risacher, Shannon L.; Nho, Kwangsik; Huentelman, Matthew J.; Craig, David W.; Thompson, Paul M.; Stein, Jason L.; Moore, Jason H.; Farrer, Lindsay A.; Green, Robert C.; Bertram, Lars; Jack, Clifford R.; Weiner, Michael W.

2010-01-01

The role of the Alzheimer’s Disease Neuroimaging Initiative Genetics Core is to facilitate the investigation of genetic influences on disease onset and trajectory as reflected in structural, functional, and molecular imaging changes; fluid biomarkers; and cognitive status. Major goals include (1) blood sample processing, genotyping, and dissemination, (2) genome-wide association studies (GWAS) of longitudinal phenotypic data, and (3) providing a central resource, point of contact and planning group for genetics within Alzheimer’s Disease Neuroimaging Initiative. Genome-wide array data have been publicly released and updated, and several neuroimaging GWAS have recently been reported examining baseline magnetic resonance imaging measures as quantitative phenotypes. Other preliminary investigations include copy number variation in mild cognitive impairment and Alzheimer’s disease and GWAS of baseline cerebrospinal fluid biomarkers and longitudinal changes on magnetic resonance imaging. Blood collection for RNA studies is a new direction. Genetic studies of longitudinal phenotypes hold promise for elucidating disease mechanisms and risk, development of therapeutic strategies, and refining selection criteria for clinical trials. PMID:20451875

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

PubMed Central

Barkla, Bronwyn J.

2016-01-01

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

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

PubMed

Barkla, Bronwyn J

2016-09-08

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

Stability of miRNA in human urine supports its biomarker potential

PubMed Central

Mall, Christine; Rocke, David M; Durbin-Johnson, Blythe; Weiss, Robert H

2013-01-01

Aim miRNAs are showing utility as biomarkers in urologic disease, however, a rigorous evaluation of their stability in urine is lacking. Here, we evaluate the stability of miRNAs in urine under clinically relevant storage procedures. Materials & methods Eight healthy individuals provided clean catch urine samples that were stored at room temperature or at 4°C for 5 days, or subjected to ten freeze–thaw cycles at -80°C. For each condition, two miRNAs, miR-16 and miR-21, were quantitated by quantitative real-time PCR. Results All conditions demonstrated a surprising degree of stability of miRNAs in the urine: by the end of ten freeze–thaw cycles, 23–37% of the initial amount remained; over the 5-day period of storage at room temperature, 35% of the initial amount remained; and at 4°C, 42–56% of the initial amount remained. Both miRNAs also showed degradation at approximately the same rate. Conclusion miRNAs are relatively stable in urine under a variety of storage conditions, which supports their utility as urinary biomarkers. PMID:23905899

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

Amacher, David E.

Biomarkers are biometric measurements that provide critical quantitative information about the biological condition of the animal or individual being tested. In drug safety studies, established toxicity biomarkers are used along with other conventional study data to determine dose-limiting organ toxicity, and to define species sensitivity for new chemical entities intended for possible use as human medicines. A continuing goal of drug safety scientists in the pharmaceutical industry is to discover and develop better trans-species biomarkers that can be used to determine target organ toxicities for preclinical species in short-term studies at dose levels that are some multiple of the intendedmore » human dose and again later in full development for monitoring clinical trials at lower therapeutic doses. Of particular value are early, predictive, noninvasive biomarkers that have in vitro, in vivo, and clinical transferability. Such translational biomarkers bridge animal testing used in preclinical science and human studies that are part of subsequent clinical testing. Although suitable for in vivo preclinical regulatory studies, conventional hepatic safety biomarkers are basically confirmatory markers because they signal organ toxicity after some pathological damage has occurred, and are therefore not well-suited for short-term, predictive screening assays early in the discovery-to-development progression of new chemical entities (NCEs) available in limited quantities. Efforts between regulatory agencies and the pharmaceutical industry are underway for the coordinated discovery, qualification, verification and validation of early predictive toxicity biomarkers. Early predictive safety biomarkers are those that are detectable and quantifiable prior to the onset of irreversible tissue injury and which are associated with a mechanism of action relevant to a specific type of potential hepatic injury. Potential drug toxicity biomarkers are typically endogenous macromolecules in biological fluids with varying immunoreactivity which can present bioanalytical challenges when first discovered. The potential success of these efforts is greatly enhanced by recent advances in two closely linked technologies, toxicoproteomics and targeted, quantitative mass spectrometry. This review focuses on the examination of the current status of these technologies as they relate to the discovery and development of novel preclinical biomarkers of hepatotoxicity. A critical assessment of the current literature reveals two distinct lines of safety biomarker investigation, (1) peripheral fluid biomarkers of organ toxicity and (2) tissue or cell-based toxicity signatures. Improved peripheral fluid biomarkers should allow the sensitive detection of potential organ toxicity prior to the onset of overt organ pathology. Advancements in tissue or cell-based toxicity biomarkers will provide sensitive in vitro or ex vivo screening systems based on toxicity pathway markers. An examination of the current practices in clinical pathology and the critical evaluation of some recently proposed biomarker candidates in comparison to the desired characteristics of an ideal toxicity biomarker lead this author to conclude that a combination of selected biomarkers will be more informative if not predictive of potential animal organ toxicity than any single biomarker, new or old. For the practical assessment of combinations of conventional and/or novel toxicity biomarkers in rodent and large animal preclinical species, mass spectrometry has emerged as the premier analytical tool compared to specific immunoassays or functional assays. Selected and multiple reaction monitoring mass spectrometry applications make it possible for this same basic technology to be used in the progressive stages of biomarker discovery, development, and more importantly, routine study applications without the use of specific antibody reagents. This technology combined with other 'omics' technologies can provide added selectivity and sensitivity in preclinical drug safety testing.« less

Quinone-based stable isotope probing for assessment of 13C substrate-utilizing bacteria

NASA Astrophysics Data System (ADS)

Kunihiro, Tadao; Katayama, Arata; Demachi, Toyoko; Veuger, Bart; Boschker, Henricus T. S.; van Oevelen, Dick

2015-04-01

In this study, we attempted to establish quinone-stable-isotope probing (SIP) technique to link substrate-utilizing bacterial group to chemotaxonomic group in bacterial community. To identify metabolically active bacterial group in various environments, SIP techniques combined with biomarkers have been widely utilized as an attractive method for environmental study. Quantitative approaches of the SIP technique have unique advantage to assess substrate-incorporation into bacteria. As a most major quantitative approach, SIP technique based on phospholipid-derived fatty acids (PLFA) have been applied to simultaneously assess substrate-incorporation rate into bacteria and microbial community structure. This approach is powerful to estimate the incorporation rate because of the high sensitivity due to the detection by a gas chromatograph-combustion interface-isotope ratio mass spectrometer (GC-c-IRMS). However, its phylogenetic resolution is limited by specificity of a compound-specific marker. We focused on respiratory quinone as a biomarker. Our previous study found a good correlation between concentrations of bacteria-specific PLFAs and quinones over several orders of magnitude in various marine sediments, and the quinone method has a higher resolution (bacterial phylum level) for resolving differences in bacterial community composition more than that of bacterial PLFA. Therefore, respiratory quinones are potentially good biomarkers for quantitative approaches of the SIP technique. The LC-APCI-MS method as molecular-mass based detection method for quinone was developed and provides useful structural information for identifying quinone molecular species in environmental samples. LC-MS/MS on hybrid triple quadrupole/linear ion trap, which enables to simultaneously identify and quantify compounds in a single analysis, can detect high molecular compounds with their isotope ions. Use of LC-MS/MS allows us to develop quinone-SIP based on molecular mass differences due to 13C abundance in the quinone. In this study, we verified carbon stable isotope of quinone compared with bulk carbon stable isotope of bacterial culture. Results indicated a good correlation between carbon stable isotope of quinone compared with bulk carbon stable isotope. However, our measurement conditions for detection of quinone isotope-ions incurred underestimation of 13C abundance in the quinone. The quinone-SIP technique needs further optimization for measurement conditions of LC-MS/MS.

A critical insight into the development pipeline of microfluidic immunoassay devices for the sensitive quantitation of protein biomarkers at the point of care.

PubMed

Barbosa, Ana I; Reis, Nuno M

2017-03-13

The latest clinical procedures for the timely and cost-effective diagnosis of chronic and acute clinical conditions, such as cardiovascular diseases, cancer, chronic respiratory diseases, diabetes or sepsis (i.e. the biggest causes of death worldwide), involve the quantitation of specific protein biomarkers released into the blood stream or other physiological fluids (e.g. urine or saliva). The clinical thresholds are usually in the femtomolar to picolomar range, and consequently the measurement of these protein biomarkers heavily relies on highly sophisticated, bulky and automated equipment in centralised pathology laboratories. The first microfluidic devices capable of measuring protein biomarkers in miniaturised immunoassays were presented nearly two decades ago and promised to revolutionise point-of-care (POC) testing by offering unmatched sensitivity and automation in a compact POC format; however, the development and adoption of microfluidic protein biomarker tests has fallen behind expectations. This review presents a detailed critical overview into the pipeline of microfluidic devices developed in the period 2005-2016 capable of measuring protein biomarkers from the pM to fM range in formats compatible with POC testing, with a particular focus on the use of affordable microfluidic materials and compact low-cost signal interrogation. The integration of these two important features (essential unique selling points for the successful microfluidic diagnostic products) has been missed in previous review articles and explain the poor adoption of microfluidic technologies in this field. Most current miniaturised devices compromise either on the affordability, compactness and/or performance of the test, making current tests unsuitable for the POC measurement of protein biomarkers. Seven core technical areas, including (i) the selected strategy for antibody immobilisation, (ii) the surface area and surface-area-to-volume ratio, (iii) surface passivation, (iv) the biological matrix interference, (v) fluid control, (vi) the signal detection modes and (vii) the affordability of the manufacturing process and detection system, were identified as the key to the effective development of a sensitive and affordable microfluidic protein biomarker POC test.

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

PubMed

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

2017-04-07

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

Diagnosis of major depressive disorder by combining multimodal information from heart rate dynamics and serum proteomics using machine-learning algorithm.

PubMed

Kim, Eun Young; Lee, Min Young; Kim, Se Hyun; Ha, Kyooseob; Kim, Kwang Pyo; Ahn, Yong Min

2017-06-02

Major depressive disorder (MDD) is a systemic and multifactorial disorder that involves abnormalities in multiple biochemical pathways and the autonomic nervous system. This study applied a machine-learning method to classify MDD and control groups by incorporating data from serum proteomic analysis and heart rate variability (HRV) analysis for the identification of novel peripheral biomarkers. The study subjects consisted of 25 drug-free female MDD patients and 25 age- and sex-matched healthy controls. First, quantitative serum proteome profiles were analyzed by liquid chromatography-tandem mass spectrometry using pooled serum samples from 10 patients and 10 controls. Next, candidate proteins were quantified with multiple reaction monitoring (MRM) in 50 subjects. We also analyzed 22 linear and nonlinear HRV parameters in 50 subjects. Finally, we identified a combined biomarker panel consisting of proteins and HRV indexes using a support vector machine with recursive feature elimination. A separation between MDD and control groups was achieved using five parameters (apolipoprotein B, group-specific component, ceruloplasmin, RMSSD, and SampEn) at 80.1% classification accuracy. A combination of HRV and proteomic data achieved better classification accuracy. A high classification accuracy can be achieved by combining multimodal information from heart rate dynamics and serum proteomics in MDD. Our approach can be helpful for accurate clinical diagnosis of MDD. Further studies using larger, independent cohorts are needed to verify the role of these candidate biomarkers for MDD diagnosis. Copyright © 2017 Elsevier Inc. All rights reserved.

MiR-21 Expression in the Tumor Stroma of Oral Squamous Cell Carcinoma: An Independent Biomarker of Disease Free Survival

PubMed Central

Specht, Lena; Fiehn, Anne-Marie K.; Therkildsen, Marianne H.; Friis-Hansen, Lennart; Dabelsteen, Erik; von Buchwald, Christian

2014-01-01

Oral squamous cell carcinoma (OSCC) patients have a high mortality rate; thus, new clinical biomarkers and therapeutic options are needed. MicroRNAs (miRNAs) are short noncoding RNAs that regulate posttranscriptional gene expression and are commonly deregulated in OSCC and other cancers. MicroRNA-21 (miR-21) is the most consistently overexpressed miRNA in several types of cancer, and it might be a useful clinical biomarker and therapeutic target. To better understand the role of miR-21 in OSCC, paraffin-embedded tumor tissue samples from 86 patients with primary OSCC were analyzed by in situ hybridization. We found that miR-21 was primarily expressed in the tumor stroma and in some tumor-associated blood vessels with no expression in the adjacent normal epithelia or stroma. Using image analysis, we quantitatively estimated miR-21 expression levels specifically in the stroma of a cohort of OSCC samples. These miR-21 levels significantly correlated with disease free survival with the highest levels being located in the stroma. Stromal miR-21 expression was independently associated with a poorer prognosis, even after adjusting for clinical parameters (perineural invasion and N-stage) in a multivariate analysis. In summary, we have shown that miR-21 is located in the carcinoma cells, stroma and blood vessels of tumors, and its expression specifically in the stromal compartment has a negative prognostic value in OSCC. PMID:24755828

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

PubMed Central

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

2012-01-01

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

miR-22-5p revealed as a potential biomarker involved in the acute phase of myocardial infarction via profiling of circulating microRNAs.

PubMed

Maciejak, Agata; Kiliszek, Marek; Opolski, Grzegorz; Segiet, Agnieszka; Matlak, Krzysztof; Dobrzycki, Slawomir; Tulacz, Dorota; Sygitowicz, Grazyna; Burzynska, Beata; Gora, Monika

2016-09-01

Acute myocardial infarction (AMI) is a life-threatening episode of coronary artery disease. Recently, circulating myocardial-derived microRNAs (miRNAs) have been reported as potential biomarkers of infarction. The present study aimed to identify differentially expressed miRNAs in patients with ST-segment elevation myocardial infarction that could be potentially dysregulated in response to early myocardial damage. miRNA expression profile analysis was performed using the Serum/Plasma Focus miRNA Polymerase Chain Reaction (PCR) panel of Exiqon A/S (Vedbaek, Denmark) on plasma samples of patients on the first day of AMI (admission) and on samples from the identical patients collected six months following AMI. Selected miRNAs were validated by reverse transcription‑quantitative PCR (RT‑qPCR) using independent patients with AMI and a control group of patients with a stable coronary artery disease. Thirty‑two species of plasma miRNA were differentially expressed (P<0.05) on admission compared with six months following AMI. Subsequent validation in an independent patient group confirmed that miR‑133b and miR‑22‑5p were significantly up‑regulated in the serum of patients with AMI. The receiver operating characteristic (ROC) curve analysis demonstrated a diagnostic utility for miR-22-5p, which has not previously been reported to be associated with AMI. Among the selected miRNAs, miR‑22‑5p represents a novel promising biomarker for the diagnosis of AMI.

Development of a Multiplexed Liquid Chromatography Multiple-Reaction-Monitoring Mass Spectrometry (LC-MRM/MS) Method for Evaluation of Salivary Proteins as Oral Cancer Biomarkers*

PubMed Central

Chen, Hsiao-Wei; Wu, Chun-Feng; Chu, Lichieh Julie; Chiang, Wei-Fang; Wu, Chih-Ching; Yu, Jau-Song; Tsai, Cheng-Han; Liang, Kung-Hao; Chang, Yu-Sun; Wu, Maureen; Ou Yang, Wei-Ting

2017-01-01

Multiple (selected) reaction monitoring (MRM/SRM) of peptides is a growing technology for target protein quantification because it is more robust, precise, accurate, high-throughput, and multiplex-capable than antibody-based techniques. The technique has been applied clinically to the large-scale quantification of multiple target proteins in different types of fluids. However, previous MRM-based studies have placed less focus on sample-preparation workflow and analytical performance in the precise quantification of proteins in saliva, a noninvasively sampled body fluid. In this study, we evaluated the analytical performance of a simple and robust multiple reaction monitoring (MRM)-based targeted proteomics approach incorporating liquid chromatography with mass spectrometry detection (LC-MRM/MS). This platform was used to quantitatively assess the biomarker potential of a group of 56 salivary proteins that have previously been associated with human cancers. To further enhance the development of this technology for assay of salivary samples, we optimized the workflow for salivary protein digestion and evaluated quantification performance, robustness and technical limitations in analyzing clinical samples. Using a clinically well-characterized cohort of two independent clinical sample sets (total n = 119), we quantitatively characterized these protein biomarker candidates in saliva specimens from controls and oral squamous cell carcinoma (OSCC) patients. The results clearly showed a significant elevation of most targeted proteins in saliva samples from OSCC patients compared with controls. Overall, this platform was capable of assaying the most highly multiplexed panel of salivary protein biomarkers, highlighting the clinical utility of MRM in oral cancer biomarker research. PMID:28235782

Methodologies for the quantitative estimation of toxicant dose to cigarette smokers using physical, chemical and bioanalytical data

PubMed Central

McAughey, John; Shepperd, Christopher J.

2013-01-01

Methodologies have been developed, described and demonstrated that convert mouth exposure estimates of cigarette smoke constituents to dose by accounting for smoke spilled from the mouth prior to inhalation (mouth-spill (MS)) and the respiratory retention (RR) during the inhalation cycle. The methodologies are applicable to just about any chemical compound in cigarette smoke that can be measured analytically and can be used with ambulatory population studies. Conversion of exposure to dose improves the relevancy for risk assessment paradigms. Except for urinary nicotine plus metabolites, biomarkers generally do not provide quantitative exposure or dose estimates. In addition, many smoke constituents have no reliable biomarkers. We describe methods to estimate the RR of chemical compounds in smoke based on their vapor pressure (VP) and to estimate the MS for a given subject. Data from two clinical studies were used to demonstrate dose estimation for 13 compounds, of which only 3 have urinary biomarkers. Compounds with VP > 10−5 Pa generally have RRs of 88% or greater, which do not vary appreciably with inhalation volume (IV). Compounds with VP < 10−7 Pa generally have RRs dependent on IV and lung exposure time. For MS, mean subject values from both studies were slightly greater than 30%. For constituents with urinary biomarkers, correlations with the calculated dose were significantly improved over correlations with mouth exposure. Of toxicological importance is that the dose correlations provide an estimate of the metabolic conversion of a constituent to its respective biomarker. PMID:23742081

Gene Expression Biomarkers Provide Sensitive Indicators of in Planta Nitrogen Status in Maize[W][OA

PubMed Central

Yang, Xiaofeng S.; Wu, Jingrui; Ziegler, Todd E.; Yang, Xiao; Zayed, Adel; Rajani, M.S.; Zhou, Dafeng; Basra, Amarjit S.; Schachtman, Daniel P.; Peng, Mingsheng; Armstrong, Charles L.; Caldo, Rico A.; Morrell, James A.; Lacy, Michelle; Staub, Jeffrey M.

2011-01-01

Over the last several decades, increased agricultural production has been driven by improved agronomic practices and a dramatic increase in the use of nitrogen-containing fertilizers to maximize the yield potential of crops. To reduce input costs and to minimize the potential environmental impacts of nitrogen fertilizer that has been used to optimize yield, an increased understanding of the molecular responses to nitrogen under field conditions is critical for our ability to further improve agricultural sustainability. Using maize (Zea mays) as a model, we have characterized the transcriptional response of plants grown under limiting and sufficient nitrogen conditions and during the recovery of nitrogen-starved plants. We show that a large percentage (approximately 7%) of the maize transcriptome is nitrogen responsive, similar to previous observations in other plant species. Furthermore, we have used statistical approaches to identify a small set of genes whose expression profiles can quantitatively assess the response of plants to varying nitrogen conditions. Using a composite gene expression scoring system, this single set of biomarker genes can accurately assess nitrogen responses independently of genotype, developmental stage, tissue type, or environment, including in plants grown under controlled environments or in the field. Importantly, the biomarker composite expression response is much more rapid and quantitative than phenotypic observations. Consequently, we have successfully used these biomarkers to monitor nitrogen status in real-time assays of field-grown maize plants under typical production conditions. Our results suggest that biomarkers have the potential to be used as agronomic tools to monitor and optimize nitrogen fertilizer usage to help achieve maximal crop yields. PMID:21980173

Test–retest repeatability of human speech biomarkers from static and real-time dynamic magnetic resonance imaging

PubMed Central

Töger, Johannes; Sorensen, Tanner; Somandepalli, Krishna; Toutios, Asterios; Lingala, Sajan Goud; Narayanan, Shrikanth; Nayak, Krishna

2017-01-01

Static anatomical and real-time dynamic magnetic resonance imaging (RT-MRI) of the upper airway is a valuable method for studying speech production in research and clinical settings. The test–retest repeatability of quantitative imaging biomarkers is an important parameter, since it limits the effect sizes and intragroup differences that can be studied. Therefore, this study aims to present a framework for determining the test–retest repeatability of quantitative speech biomarkers from static MRI and RT-MRI, and apply the framework to healthy volunteers. Subjects (n = 8, 4 females, 4 males) are imaged in two scans on the same day, including static images and dynamic RT-MRI of speech tasks. The inter-study agreement is quantified using intraclass correlation coefficient (ICC) and mean within-subject standard deviation (σe). Inter-study agreement is strong to very strong for static measures (ICC: min/median/max 0.71/0.89/0.98, σe: 0.90/2.20/6.72 mm), poor to strong for dynamic RT-MRI measures of articulator motion range (ICC: 0.26/0.75/0.90, σe: 1.6/2.5/3.6 mm), and poor to very strong for velocities (ICC: 0.21/0.56/0.93, σe: 2.2/4.4/16.7 cm/s). In conclusion, this study characterizes repeatability of static and dynamic MRI-derived speech biomarkers using state-of-the-art imaging. The introduced framework can be used to guide future development of speech biomarkers. Test–retest MRI data are provided free for research use. PMID:28599561

Gene expression biomarkers provide sensitive indicators of in planta nitrogen status in maize.

PubMed

Yang, Xiaofeng S; Wu, Jingrui; Ziegler, Todd E; Yang, Xiao; Zayed, Adel; Rajani, M S; Zhou, Dafeng; Basra, Amarjit S; Schachtman, Daniel P; Peng, Mingsheng; Armstrong, Charles L; Caldo, Rico A; Morrell, James A; Lacy, Michelle; Staub, Jeffrey M

2011-12-01

Over the last several decades, increased agricultural production has been driven by improved agronomic practices and a dramatic increase in the use of nitrogen-containing fertilizers to maximize the yield potential of crops. To reduce input costs and to minimize the potential environmental impacts of nitrogen fertilizer that has been used to optimize yield, an increased understanding of the molecular responses to nitrogen under field conditions is critical for our ability to further improve agricultural sustainability. Using maize (Zea mays) as a model, we have characterized the transcriptional response of plants grown under limiting and sufficient nitrogen conditions and during the recovery of nitrogen-starved plants. We show that a large percentage (approximately 7%) of the maize transcriptome is nitrogen responsive, similar to previous observations in other plant species. Furthermore, we have used statistical approaches to identify a small set of genes whose expression profiles can quantitatively assess the response of plants to varying nitrogen conditions. Using a composite gene expression scoring system, this single set of biomarker genes can accurately assess nitrogen responses independently of genotype, developmental stage, tissue type, or environment, including in plants grown under controlled environments or in the field. Importantly, the biomarker composite expression response is much more rapid and quantitative than phenotypic observations. Consequently, we have successfully used these biomarkers to monitor nitrogen status in real-time assays of field-grown maize plants under typical production conditions. Our results suggest that biomarkers have the potential to be used as agronomic tools to monitor and optimize nitrogen fertilizer usage to help achieve maximal crop yields.

Blood Pyrrole-Protein Adducts--A Biomarker of Pyrrolizidine Alkaloid-Induced Liver Injury in Humans.

PubMed

Ruan, Jianqing; Gao, Hong; Li, Na; Xue, Junyi; Chen, Jie; Ke, Changqiang; Ye, Yang; Fu, Peter Pi-Cheng; Zheng, Jiang; Wang, Jiyao; Lin, Ge

2015-01-01

Pyrrolizidine alkaloids (PAs) induce liver injury (PA-ILI) and is very likely to contribute significantly to drug-induced liver injury (DILI). In this study we used a newly developed ultra-high performance liquid chromatography-triple quadrupole-mass spectrometry (UHPLC-MS)-based method to detect and quantitate blood pyrrole-protein adducts in DILI patients. Among the 46 suspected DILI patients, 15 were identified as PA-ILI by the identification of PA-containing herbs exposed. Blood pyrrole-protein adducts were detected in all PA-ILI patients (100%). These results confirm that PA-ILI is one of the major causes of DILI and that blood pyrrole-protein adducts quantitated by the newly developed UHPLC-MS method can serve as a specific biomarker of PA-ILI.

iTRAQ-Based Proteomics Reveals Novel Biomarkers for Idiopathic Pulmonary Fibrosis

PubMed Central

Niu, Rui; Liu, Ying; Zhang, Ying; Zhang, Yuan; Wang, Hui; Wang, Yongbin; Wang, Wei; Li, Xiaohui

2017-01-01

Idiopathic pulmonary fibrosis (IPF) is a gradual lung disease with a survival of less than 5 years post-diagnosis for most patients. Poor molecular description of IPF has led to unsatisfactory interpretation of the pathogenesis of this disease, resulting in the lack of successful treatments. The objective of this study was to discover novel noninvasive biomarkers for the diagnosis of IPF. We employed a coupled isobaric tag for relative and absolute quantitation (iTRAQ)-liquid chromatography–tandem mass spectrometry (LC–MS/MS) approach to examine protein expression in patients with IPF. A total of 97 differentially expressed proteins (38 upregulated proteins and 59 downregulated proteins) were identified in the serum of IPF patients. Using String software, a regulatory network containing 87 nodes and 244 edges was built, and the functional enrichment showed that differentially expressed proteins were predominantly involved in protein activation cascade, regulation of response to wounding and extracellular components. A set of three most significantly upregulated proteins (HBB, CRP and SERPINA1) and four most significantly downregulated proteins (APOA2, AHSG, KNG1 and AMBP) were selected for validation in an independent cohort of IPF and other lung diseases using ELISA test. The results confirmed the iTRAQ profiling results and AHSG, AMBP, CRP and KNG1 were found as specific IPF biomarkers. ROC analysis indicated the diagnosis potential of the validated biomarkers. The findings of this study will contribute in understanding the pathogenesis of IPF and facilitate the development of therapeutic targets. PMID:28122020

Genome-wide association study to identify potential genetic modifiers in a canine model for Duchenne muscular dystrophy.

PubMed

Brinkmeyer-Langford, Candice; Balog-Alvarez, Cynthia; Cai, James J; Davis, Brian W; Kornegay, Joe N

2016-08-22

Duchenne muscular dystrophy (DMD) causes progressive muscle degeneration, cardiomyopathy and respiratory failure in approximately 1/5,000 boys. Golden Retriever muscular dystrophy (GRMD) resembles DMD both clinically and pathologically. Like DMD, GRMD exhibits remarkable phenotypic variation among affected dogs, suggesting the influence of modifiers. Understanding the role(s) of genetic modifiers of GRMD may identify genes and pathways that also modify phenotypes in DMD and reveal novel therapies. Therefore, our objective in this study was to identify genetic modifiers that affect discrete GRMD phenotypes. We performed a linear mixed-model (LMM) analysis using 16 variably-affected dogs from our GRMD colony (8 dystrophic, 8 non-dystrophic). All of these dogs were either full or half-siblings, and phenotyped for 19 objective, quantitative biomarkers at ages 6 and 12 months. Each biomarker was individually assessed. Gene expression profiles of 59 possible candidate genes were generated for two muscle types: the cranial tibialis and medial head of the gastrocnemius. SNPs significantly associated with GRMD biomarkers were identified on multiple chromosomes (including the X chromosome). Gene expression levels for candidate genes located near these SNPs correlated with biomarker values, suggesting possible roles as GRMD modifiers. The results of this study enhance our understanding of GRMD pathology and represent a first step toward the characterization of GRMD modifiers that may be relevant to DMD pathology. Such modifiers are likely to be useful for DMD treatment development based on their relationships to GRMD phenotypes.

iTRAQ-Based Proteomics Reveals Novel Biomarkers for Idiopathic Pulmonary Fibrosis.

PubMed

Niu, Rui; Liu, Ying; Zhang, Ying; Zhang, Yuan; Wang, Hui; Wang, Yongbin; Wang, Wei; Li, Xiaohui

2017-01-01

Idiopathic pulmonary fibrosis (IPF) is a gradual lung disease with a survival of less than 5 years post-diagnosis for most patients. Poor molecular description of IPF has led to unsatisfactory interpretation of the pathogenesis of this disease, resulting in the lack of successful treatments. The objective of this study was to discover novel noninvasive biomarkers for the diagnosis of IPF. We employed a coupled isobaric tag for relative and absolute quantitation (iTRAQ)-liquid chromatography-tandem mass spectrometry (LC-MS/MS) approach to examine protein expression in patients with IPF. A total of 97 differentially expressed proteins (38 upregulated proteins and 59 downregulated proteins) were identified in the serum of IPF patients. Using String software, a regulatory network containing 87 nodes and 244 edges was built, and the functional enrichment showed that differentially expressed proteins were predominantly involved in protein activation cascade, regulation of response to wounding and extracellular components. A set of three most significantly upregulated proteins (HBB, CRP and SERPINA1) and four most significantly downregulated proteins (APOA2, AHSG, KNG1 and AMBP) were selected for validation in an independent cohort of IPF and other lung diseases using ELISA test. The results confirmed the iTRAQ profiling results and AHSG, AMBP, CRP and KNG1 were found as specific IPF biomarkers. ROC analysis indicated the diagnosis potential of the validated biomarkers. The findings of this study will contribute in understanding the pathogenesis of IPF and facilitate the development of therapeutic targets.

Potential early biomarkers of sarcopenia among independent older adults.

PubMed

Coto Montes, Ana; Boga, José Antonio; Bermejo Millo, Carlos; Rubio González, Adrián; Potes Ochoa, Yaiza; Vega Naredo, Ignacio; Martínez Reig, Marta; Romero Rizos, Luis; Sánchez Jurado, Pedro Manuel; Solano, Juan Jose; Abizanda, Pedro; Caballero, Beatriz

2017-10-01

There are no tools or biomarkers for a quantitative analysis of sarcopenia. Cross-sectional study of the diagnosis of sarcopenia in 200 independent adults aged 70 years or over. Sarcopenia was defined as loss of muscle mass together with low strength and/or loss of physical performance. We considered different clinical parameters and assayed potential blood biomarkers (cell energetic metabolism, muscle performance, inflammation, infection and oxidative stress). The prevalence of sarcopenia was 35.3% in women and 13.1% in men, and it was significantly associated with advanced age, a low functional performance in the lower extremities, deficient weekly consumption of kilocalories, risk of malnutrition, and drug use for the digestive system. A close relationship was found between sarcopenia, pre-frailty and depressed mood. With these confounding variables, we observed that products of lipid peroxidation were closely associated with sarcopenia in independent older adults (frail participants and those with severe dependence had been excluded from the sample). The best multivariate model proposed was able to predict 67.6% of the variance in sarcopenia, with a power of discrimination of 93.5%. Additional analyses considering lipid levels, fat mass, dyslipidemia, use of lipid-lowering drugs and hypertension confirmed this close association between lipid peroxidation and sarcopenia. Given the difficulty in the diagnosis of sarcopenia in clinical practice, we suggest the use of blood circulating products of lipid peroxidation as potential biomarkers for an early diagnosis of sarcopenia in independent older adults. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Quantitative DNA Methylation Analysis Identifies a Single CpG Dinucleotide Important for ZAP-70 Expression and Predictive of Prognosis in Chronic Lymphocytic Leukemia

PubMed Central

Claus, Rainer; Lucas, David M.; Stilgenbauer, Stephan; Ruppert, Amy S.; Yu, Lianbo; Zucknick, Manuela; Mertens, Daniel; Bühler, Andreas; Oakes, Christopher C.; Larson, Richard A.; Kay, Neil E.; Jelinek, Diane F.; Kipps, Thomas J.; Rassenti, Laura Z.; Gribben, John G.; Döhner, Hartmut; Heerema, Nyla A.; Marcucci, Guido; Plass, Christoph; Byrd, John C.

2012-01-01

Purpose Increased ZAP-70 expression predicts poor prognosis in chronic lymphocytic leukemia (CLL). Current methods for accurately measuring ZAP-70 expression are problematic, preventing widespread application of these tests in clinical decision making. We therefore used comprehensive DNA methylation profiling of the ZAP-70 regulatory region to identify sites important for transcriptional control. Patients and Methods High-resolution quantitative DNA methylation analysis of the entire ZAP-70 gene regulatory regions was conducted on 247 samples from patients with CLL from four independent clinical studies. Results Through this comprehensive analysis, we identified a small area in the 5′ regulatory region of ZAP-70 that showed large variability in methylation in CLL samples but was universally methylated in normal B cells. High correlation with mRNA and protein expression, as well as activity in promoter reporter assays, revealed that within this differentially methylated region, a single CpG dinucleotide and neighboring nucleotides are particularly important in ZAP-70 transcriptional regulation. Furthermore, by using clustering approaches, we identified a prognostic role for this site in four independent data sets of patients with CLL using time to treatment, progression-free survival, and overall survival as clinical end points. Conclusion Comprehensive quantitative DNA methylation analysis of the ZAP-70 gene in CLL identified important regions responsible for transcriptional regulation. In addition, loss of methylation at a specific single CpG dinucleotide in the ZAP-70 5′ regulatory sequence is a highly predictive and reproducible biomarker of poor prognosis in this disease. This work demonstrates the feasibility of using quantitative specific ZAP-70 methylation analysis as a relevant clinically applicable prognostic test in CLL. PMID:22564988

RNA-based determination of ESR1 and HER2 expression and response to neoadjuvant chemotherapy.

PubMed

Denkert, C; Loibl, S; Kronenwett, R; Budczies, J; von Törne, C; Nekljudova, V; Darb-Esfahani, S; Solbach, C; Sinn, B V; Petry, C; Müller, B M; Hilfrich, J; Altmann, G; Staebler, A; Roth, C; Ataseven, B; Kirchner, T; Dietel, M; Untch, M; von Minckwitz, G

2013-03-01

Hormone and human epidermal growth factor receptor 2 (HER2) receptors are the most important breast cancer biomarkers, and additional objective and quantitative test methods such as messenger RNA (mRNA)-based quantitative analysis are urgently needed. In this study, we investigated the clinical validity of RT-PCR-based evaluation of estrogen receptor (ESR1) and HER2 mRNA expression. A total of 1050 core biopsies from two retrospective (GeparTrio, GeparQuattro) and one prospective (PREDICT) neoadjuvant studies were evaluated by quantitative RT-PCR for ESR1 and HER2. ESR1 mRNA was significantly predictive for reduced response to neoadjuvant chemotherapy in univariate and multivariate analysis in all three cohorts. The complete pathologically documented response (pathological complete response, pCR) rate for ESR1+/HER2- tumors was 7.3%, 8.0% and 8.6%; for ESR1-/HER2- tumors it was 34.4%, 33.7% and 37.3% in GeparTrio, GeparQuattro and PREDICT, respectively (P < 0.001 in each cohort). In the Kaplan-Meier analysis in GeparTrio patients with ESR1+/HER2- tumors had the best prognosis, compared with ESR1-/HER2- and ESR1-/HER2+ tumors [disease-free survival (DFS): P < 0.0005, overall survival (OS): P < 0.0005]. Our results suggest that mRNA levels of ESR1 and HER2 predict response to neoadjuvant chemotherapy and are significantly associated with long-term outcome. As an additional option to standard immunohistochemistry and gene-array-based analysis, quantitative RT-PCR analysis might be useful for determination of the receptor status in breast cancer.

A rapid quantitative analysis of bile acids, lysophosphatidylcholines and polyunsaturated fatty acids in biofluids based on ultraperformance liquid chromatography coupled with triple quadrupole tandem massspectrometry.

PubMed

Peng, Zhangxiao; Zhang, Qian; Mao, Ziming; Wang, Jie; Liu, Chunying; Lin, Xuejing; Li, Xin; Ji, Weidan; Fan, Jianhui; Wang, Maorong; Su, Changqing

2017-11-15

Much evidence suggested that quantitative analysis of bile acids (BAs), lysophosphatidylcholines (LPCs), and polyunsaturated fatty acids (PUFAs) in biofluids may be very useful for diagnosis and prevention of hepatobiliary disease with a non-invasive manner. However, simultaneously fast analysis of these metabolites has been challenging for their huge differences of physicochemical properties and concentration levels in biofluids. In this study, we present a liquid chromatography-mass spectrometry method with a high throughput analytical cycle (10min) to fast and accurately quantify fifteen potential biomarkers (eight BAs, four LPCs and three PUFAs) of hepatobiliary disease. The accuracy for the fifteen analytes in plasma and urine matrices was 80.45%-118.99% and 84.55%-112.66%, respectively. The intra- and inter- precisions for the fifteen analytes in plasma and urine matrices were all less than 20% and the lower limit of quantification (LLOQ) of analytes is up to 0.0283-8.2172nmol/L. Therefore, this method is fast, sensitive and accurate for the quantitative analysis of BAs, LPCs and PUFAs in biofluids. Moreover, the stability and concentration differences of the analytes in plasma and serum were evaluated, and the results demonstrated that LPCs is stable, but PUFAs is very unstable in freeze and thaw cycles, and the concentrations of the analytes in serum were slightly higher than those in plasma. We suggested plasma may be a kind of better bio-sample than serum using for quantitative analysis of metabolites in blood, due to the characteristics of plasma are more close to blood than those of serum. Copyright © 2017 Elsevier B.V. All rights reserved.

The first decade of MALDI protein profiling: a lesson in translational biomarker research.

PubMed

Albrethsen, Jakob

2011-05-16

MALDI protein profiling has identified several important challenges in omics-based biomarker research. First, research into the analytical performance of a novel omics-platform of potential diagnostic impact must be carried out in a critical manner and according to common guidelines. Evaluation studies should be performed at an early time and preferably before massive advancement into explorative biomarker research. In particular, MALDI profiling underscores the need for an adequate understanding of the causal relationship between molecular abundance and the quantitative measure in multivariate biomarker research. Secondly, MALDI profiling has raised awareness of the significant risk of false-discovery in biomarker research due to several confounding factors, including sample processing and unspecific host-response to disease. Here, the experience from MALDI profiling supports that a central challenge in unbiased molecular profiling is to pinpoint the aberrations of clinical interest among potentially massive unspecific changes that can accompany disease. The lessons from the first decade of MALDI protein profiling are relevant for future efforts in advancing omics-based biomarker research beyond the laboratory setting and into clinical verification. Copyright © 2011 Elsevier B.V. All rights reserved.

Transcript and protein environmental biomarkers in fish--a review.

PubMed

Tom, Moshe; Auslander, Meirav

2005-04-01

The levels of contaminant-affected gene products (transcripts and proteins) are increasingly utilized as environmental biomarkers, and their appropriate implementation as diagnostic tools is discussed. The required characteristics of a gene product biomarker are accurate evaluation using properly normalized absolute units, aiming at long-term comparability of biomarker levels over a wide geographical range and among many laboratories. Quantitative RT-PCR and competitive ELISA are suggested as preferred evaluation methods for transcript and protein, respectively. Constitutively expressed RNAs or proteins which are part of the examined homogenate are suggested as normalizing agents, compensating for variable processing efficiency. Essential characterization of expression patterns is suggested, providing reference values to be compared to the monitored levels. This comparison would enable estimation of the intensity of biological effects of contaminants. Contaminant-independent reference expression patterns should include natural fluctuations of the biomarker level. Contaminant-dependent patterns should include dose response to model contaminants chronically administered in two environmentally-realistic routes, reaching extreme sub-lethal affected levels. Recent studies using fish as environmental sentinel species, applying gene products as environmental biomarkers, and implementing at least part of the depicted methodologies are reviewed.

CD90/THY1 is over-expressed in prostate cancer-associated fibroblasts and could serve as a cancer biomarker

PubMed Central

True, Lawrence D; Zhang, Hui; Ye, Mingliang; Huang, Chung-Ying; Nelson, Peter S; von Haller, Priska D; Tjoelker, Larry W; Kim, Jong-Seo; Qian, Wei-Jun; Smith, Richard D; Ellis, William J; Liebeskind, Emily S; Liu, Alvin Y

2010-01-01

A by-product in the processing of prostate tissue for cell sorting by collagenase digestion is the media supernatant that remains after the cells are harvested. These supernatants contain proteins made by the cells within the tissue. Quantitative proteomic analysis of N-glycosylated proteins detected an increased amount of CD90/THY1 in cancer supernatants compared to non-cancer supernatants. Immunohistochemistry showed that in all carcinomas, regardless of Gleason grade, a layer of CD90-positive stromal fibroblastic cells, approximately 5-to-10 cells deep, was localized to tumor glands. In contrast, a no more than 1-cell wide girth of CD90-positive stromal cells was found around benign glands. The increased number of CD90-positive stromal cells in cancer correlated with overexpression of CD90 mRNA detected by gene expression analysis of stromal cells obtained by laser-capture microdissection. There is increasing evidence that cancer-associated stroma plays a role in both tumor progression and carcinogenesis. Most experiments to identify cancer biomarkers have focused on the cancer cells. CD90, being a marker for prostate cancer-associated stroma, might be a potential biomarker for this cancer. A non-invasive test could be provided by a urine test. Proteomic analysis of urine from patients with prostate cancer identified CD90; conversely, CD90 was not detected in the urine of post-prostatectomy patients. Furthermore, this urinary CD90 protein was a variant CD90 protein not known to be expressed by such cells as lymphocytes that express CD90. These CD90 results were obtained from ∼90 cases consisting of proteomic analysis of tissue and urine, immunohistochemistry, Western blot analysis of tissue media, flow cytometry of cells from digested tissue, and reverse transcriptase polymerase chain reaction analysis of isolated stromal cells. PMID:20562849

Next Generation Vaccine Biomarkers workshop October 30–31, 2014 – Ottawa, Canada

PubMed Central

Twine, Susan M; Fulton, Kelly M; Spika, John; Ouellette, Marc; Raven, Jennifer F; Conlan, J Wayne; Krishnan, Lakshmi; Barreto, Luis; Richards, James C

2015-01-01

Vaccine biomarkers are critical to many aspects of vaccine development and licensure, including bridging findings in pre-clinical studies to clinical studies, predicting potential adverse events, and predicting vaccine efficacy. Despite advances in our understanding of various biological pathways, and advances in systems analyses of the immune response, there remains much to learn about qualitative and quantitative aspects of the human host response to vaccination. To stimulate discussion and identify opportunities for collaborative ways to advance the field of vaccine biomarkers, A Next Generation Vaccine Biomarker workshop was held in Ottawa. The two day workshop, sponsored by the National Research Council Canada, Canadian Institutes of Health Research, Public Health Agency of Canada, Pfizer, and Medicago, brought together stakeholders from Canadian and international industry, government and academia. The workshop was grouped in themes, covering vaccine biomarker challenges in the pre-clinical and clinical spaces, veterinary vaccines, regulatory challenges, and development of biomarkers for adjuvants and cancer vaccines. The use of case studies allowed participants to identify the needs and gaps requiring innovation. The workshop concluded with a discussion on opportunities for vaccine biomarker discovery, the Canadian context, and approaches for moving forward. This article provides a synopsis of these discussions and identifies steps forward for advancing vaccine biomarker research in Canada. PMID:26383909

Biomolecules and Biomarkers Used in Diagnosis of Alcohol Drinking and in Monitoring Therapeutic Interventions.

PubMed

Nanau, Radu M; Neuman, Manuela G

2015-06-29

The quantitative, measurable detection of drinking is important for the successful treatment of alcohol misuse in transplantation of patients with alcohol disorders, people living with human immunodeficiency virus that need to adhere to medication, and special occupational hazard offenders, many of whom continually deny drinking. Their initial misconduct usually leads to medical problems associated with drinking, impulsive social behavior, and drunk driving. The accurate identification of alcohol consumption via biochemical tests contributes significantly to the monitoring of drinking behavior. A systematic review of the current methods used to measure biomarkers of alcohol consumption was conducted using PubMed and Google Scholar databases (2010-2015). The names of the tests have been identified. The methods and publications that correlate between the social instruments and the biochemical tests were further investigated. There is a clear need for assays standardization to ensure the use of these biochemical tests as routine biomarkers. Alcohol ingestion can be measured using a breath test. Because alcohol is rapidly eliminated from the circulation, the time for detection by this analysis is in the range of hours. Alcohol consumption can alternatively be detected by direct measurement of ethanol concentration in blood or urine. Several markers have been proposed to extend the interval and sensitivities of detection, including ethyl glucuronide and ethyl sulfate in urine, phosphatidylethanol in blood, and ethyl glucuronide and fatty acid ethyl esters in hair, among others. Moreover, there is a need to correlate the indirect biomarker carbohydrate deficient transferrin, which reflects longer lasting consumption of higher amounts of alcohol, with serum γ-glutamyl transpeptidase, another long term indirect biomarker that is routinely used and standardized in laboratory medicine.

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

PubMed Central

May, Felicity E B; Westley, Bruce R

2015-01-01

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

Biomolecules and Biomarkers Used in Diagnosis of Alcohol Drinking and in Monitoring Therapeutic Interventions

PubMed Central

Nanau, Radu M.; Neuman, Manuela G.

2015-01-01

Background: The quantitative, measurable detection of drinking is important for the successful treatment of alcohol misuse in transplantation of patients with alcohol disorders, people living with human immunodeficiency virus that need to adhere to medication, and special occupational hazard offenders, many of whom continually deny drinking. Their initial misconduct usually leads to medical problems associated with drinking, impulsive social behavior, and drunk driving. The accurate identification of alcohol consumption via biochemical tests contributes significantly to the monitoring of drinking behavior. Methods: A systematic review of the current methods used to measure biomarkers of alcohol consumption was conducted using PubMed and Google Scholar databases (2010–2015). The names of the tests have been identified. The methods and publications that correlate between the social instruments and the biochemical tests were further investigated. There is a clear need for assays standardization to ensure the use of these biochemical tests as routine biomarkers. Findings: Alcohol ingestion can be measured using a breath test. Because alcohol is rapidly eliminated from the circulation, the time for detection by this analysis is in the range of hours. Alcohol consumption can alternatively be detected by direct measurement of ethanol concentration in blood or urine. Several markers have been proposed to extend the interval and sensitivities of detection, including ethyl glucuronide and ethyl sulfate in urine, phosphatidylethanol in blood, and ethyl glucuronide and fatty acid ethyl esters in hair, among others. Moreover, there is a need to correlate the indirect biomarker carbohydrate deficient transferrin, which reflects longer lasting consumption of higher amounts of alcohol, with serum γ-glutamyl transpeptidase, another long term indirect biomarker that is routinely used and standardized in laboratory medicine. PMID:26131978

Procalcitonin for the early diagnosis of sepsis in burn patients: A retrospective study.

PubMed

Cabral, Luís; Afreixo, Vera; Santos, Filipe; Almeida, Luís; Paiva, José Artur

2017-11-01

The gold standard for sepsis diagnosis in burn patient still relies on microbiological cultures, which take 48-72h to provide results, delaying the start of antimicrobial therapy. Thus, biomarkers allowing an earlier sepsis diagnosis in burn patients are needed. This retrospective observational study included 150 burn patients with total burned surface area ≥15%. Clinical diagnosis of sepsis among these patients was done according to the American Burn Association criteria. Biomarker (procalcitonin, white blood cells and platelet countings, prothrombinemia, D-dimers, C-reactive protein, blood lactate and temperature) values were available for 48 patients without sepsis (2767 timepoints) and 102 patients with sepsis (652 timepoints). Quantitative variables were compared with Mann-Whitney tests and qualitative variables were compared with Pearson chi-square test. Effect size was measured by the probability of superiority. Receiver operating characteristic (ROC) curves evaluate capacity for sepsis diagnosis. Sensitivity, specificity, positive and negative predictive values were calculated for some cut-off values, including the best cut-off defined by the maximum of Youden index. Statistically significant differences between the groups of septic and non-septic patients, with medium to large effect size, were detected for all the biomarkers considered, except temperature. PCT was the biomarker with the largest AUC and effect size (AUC=0.71). Analysis of the PCT ROC curve showed that 0.5ng/mL cut-off presented highest sensitivity and lowest specificity, whereas 1.5ng/mL cut-off was associated with lowest sensitivity and highest specificity. Procalcitonin showed to be the best of the biomarkers studied for an early diagnosis of sepsis. Its use should be considered in antimicrobial stewardship programs in Burn Units. Copyright © 2017 Elsevier Ltd and ISBI. All rights reserved.

A genetic stochastic process model for genome-wide joint analysis of biomarker dynamics and disease susceptibility with longitudinal data.

PubMed

He, Liang; Zhbannikov, Ilya; Arbeev, Konstantin G; Yashin, Anatoliy I; Kulminski, Alexander M

2017-11-01

Unraveling the underlying biological mechanisms or pathways behind the effects of genetic variations on complex diseases remains one of the major challenges in the post-GWAS (where GWAS is genome-wide association study) era. To further explore the relationship between genetic variations, biomarkers, and diseases for elucidating underlying pathological mechanism, a huge effort has been placed on examining pleiotropic and gene-environmental interaction effects. We propose a novel genetic stochastic process model (GSPM) that can be applied to GWAS and jointly investigate the genetic effects on longitudinally measured biomarkers and risks of diseases. This model is characterized by more profound biological interpretation and takes into account the dynamics of biomarkers during follow-up when investigating the hazards of a disease. We illustrate the rationale and evaluate the performance of the proposed model through two GWAS. One is to detect single nucleotide polymorphisms (SNPs) having interaction effects on type 2 diabetes (T2D) with body mass index (BMI) and the other is to detect SNPs affecting the optimal BMI level for protecting from T2D. We identified multiple SNPs that showed interaction effects with BMI on T2D, including a novel SNP rs11757677 in the CDKAL1 gene (P = 5.77 × 10 -7 ). We also found a SNP rs1551133 located on 2q14.2 that reversed the effect of BMI on T2D (P = 6.70 × 10 -7 ). In conclusion, the proposed GSPM provides a promising and useful tool in GWAS of longitudinal data for interrogating pleiotropic and interaction effects to gain more insights into the relationship between genes, quantitative biomarkers, and risks of complex diseases. © 2017 WILEY PERIODICALS, INC.

High-Throughput Sequencing Reveals Circulating miRNAs as Potential Biomarkers for Measuring Puberty Onset in Chicken (Gallus gallus).

PubMed

Han, Wei; Zhu, Yunfen; Su, Yijun; Li, Guohui; Qu, Liang; Zhang, Huiyong; Wang, Kehua; Zou, Jianmin; Liu, Honglin

2016-01-01

There are still no highly sensitive and unique biomarkers for measurement of puberty onset. Circulating miRNAs have been shown to be promising biomarkers for diagnosis of various diseases. To identify circulating miRNAs that could be served as biomarkers for measuring chicken (Gallus gallus) puberty onset, the Solexa deep sequencing was performed to analyze the miRNA expression profiles in serum and plasma of hens from two different pubertal stages, before puberty onset (BO) and after puberty onset (AO). 197 conserved and 19 novel miRNAs (reads > 10) were identified as serum/plasma-expressed miRNAs in the chicken. The common miRNA amounts and their expression changes from BO to AO between serum and plasma were very similar, indicating the different treatments to generate serum and plasma had quite small influence on the miRNAs. 130 conserved serum-miRNAs were showed to be differentially expressed (reads > 10, P < 0.05) from BO to AO, with 68 up-regulated and 62 down-regulated. 4829 putative genes were predicted as the targets of the 40 most differentially expressed miRNAs (|log2(fold-change)|>1.0, P < 0.01). Functional analysis revealed several pathways that were associated with puberty onset. Further quantitative real-time PCR (RT-qPCR) test found that a seven-miRNA panel, including miR-29c, miR-375, miR-215, miR-217, miR-19b, miR-133a and let-7a, had great potentials to serve as novel biomarkers for measuring puberty onset in chicken. Due to highly conserved nature of miRNAs, the findings could provide cues for measurement of puberty onset in other animals as well as humans.

High-Throughput Sequencing Reveals Circulating miRNAs as Potential Biomarkers for Measuring Puberty Onset in Chicken (Gallus gallus)

PubMed Central

Su, Yijun; Li, Guohui; Qu, Liang; Zhang, Huiyong; Wang, Kehua; Zou, Jianmin; Liu, Honglin

2016-01-01

There are still no highly sensitive and unique biomarkers for measurement of puberty onset. Circulating miRNAs have been shown to be promising biomarkers for diagnosis of various diseases. To identify circulating miRNAs that could be served as biomarkers for measuring chicken (Gallus gallus) puberty onset, the Solexa deep sequencing was performed to analyze the miRNA expression profiles in serum and plasma of hens from two different pubertal stages, before puberty onset (BO) and after puberty onset (AO). 197 conserved and 19 novel miRNAs (reads > 10) were identified as serum/plasma-expressed miRNAs in the chicken. The common miRNA amounts and their expression changes from BO to AO between serum and plasma were very similar, indicating the different treatments to generate serum and plasma had quite small influence on the miRNAs. 130 conserved serum-miRNAs were showed to be differentially expressed (reads > 10, P < 0.05) from BO to AO, with 68 up-regulated and 62 down-regulated. 4829 putative genes were predicted as the targets of the 40 most differentially expressed miRNAs (|log2(fold-change)|>1.0, P < 0.01). Functional analysis revealed several pathways that were associated with puberty onset. Further quantitative real-time PCR (RT-qPCR) test found that a seven-miRNA panel, including miR-29c, miR-375, miR-215, miR-217, miR-19b, miR-133a and let-7a, had great potentials to serve as novel biomarkers for measuring puberty onset in chicken. Due to highly conserved nature of miRNAs, the findings could provide cues for measurement of puberty onset in other animals as well as humans. PMID:27149515

Endocannabinoids as biomarkers of human reproduction.

PubMed

Rapino, Cinzia; Battista, Natalia; Bari, Monica; Maccarrone, Mauro

2014-01-01

Infertility is a condition of the reproductive system that affects ∼10-15% of couples attempting to conceive a baby. More than half of all cases of infertility are a result of female conditions, while the remaining cases can be attributed to male factors, or to a combination of both. The search for suitable biomarkers of pregnancy outcome is a challenging issue in human reproduction, aimed at identifying molecules with predictive significance of the reproductive potential of male and female gametes. Among the various candidates, endocannabinoids (eCBs), and in particular anandamide (AEA), represent potential biomarkers of human fertility disturbances. Any perturbation of the balance between synthesis and degradation of eCBs will result in local changes of their tone in human female and male reproductive tracts, which in turn regulates various pathophysiological processes, oocyte and sperm maturation included. PubMed and Web of Science databases were searched for papers using relevant keywords like 'biomarker', 'endocannabinoid', 'infertility', 'pregnancy' and 'reproduction'. In this review, we discuss different studies on the measurements of AEA and related eCBs in human reproductive cells, tissues and fluids, where the local contribution of these bioactive lipids could be critical in ensuring normal sperm fertilizing ability and pregnancy. Based on the available data, we suggest that the AEA tone has the potential to be exploited as a novel diagnostic biomarker of infertility, to be used in association with assays of conventional hormones (e.g. progesterone, β-chorionic gonadotrophin) and semen analysis. However further quantitative research of its predictive capacity is required. © The Author 2014. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Impact of ionic current variability on human ventricular cellular electrophysiology.

PubMed

Romero, Lucía; Pueyo, Esther; Fink, Martin; Rodríguez, Blanca

2009-10-01

Abnormalities in repolarization and its rate dependence are known to be related to increased proarrhythmic risk. A number of repolarization-related electrophysiological properties are commonly used as preclinical biomarkers of arrhythmic risk. However, the variability and complexity of repolarization mechanisms make the use of cellular biomarkers to predict arrhythmic risk preclinically challenging. Our goal is to investigate the role of ionic current properties and their variability in modulating cellular biomarkers of arrhythmic risk to improve risk stratification and identification in humans. A systematic investigation into the sensitivity of the main preclinical biomarkers of arrhythmic risk to changes in ionic current conductances and kinetics was performed using computer simulations. Four stimulation protocols were applied to the ten Tusscher and Panfilov human ventricular model to quantify the impact of +/-15 and +/-30% variations in key model parameters on action potential (AP) properties, Ca(2+) and Na(+) dynamics, and their rate dependence. Simulations show that, in humans, AP duration is moderately sensitive to changes in all repolarization current conductances and in L-type Ca(2+) current (I(CaL)) and slow component of the delayed rectifier current (I(Ks)) inactivation kinetics. AP triangulation, however, is strongly dependent only on inward rectifier K(+) current (I(K1)) and delayed rectifier current (I(Kr)) conductances. Furthermore, AP rate dependence (i.e., AP duration rate adaptation and restitution properties) and intracellular Ca(2+) and Na(+) levels are highly sensitive to both I(CaL) and Na(+)/K(+) pump current (I(NaK)) properties. This study provides quantitative insights into the sensitivity of preclinical biomarkers of arrhythmic risk to variations in ionic current properties in humans. The results show the importance of sensitivity analysis as a powerful method for the in-depth validation of mathematical models in cardiac electrophysiology.

Maternal And Neonatal Plasma MicroRNA Biomarkers For Fetal Alcohol Exposure In An Ovine Model

PubMed Central

Balaraman, Sridevi; Lunde, E. Raine; Sawant, Onkar; Cudd, Timothy A.; Washburn, Shannon E.; Miranda, Rajesh C.

2014-01-01

Background Plasma or circulating miRNAs (cirmiRNAs) have potential diagnostic value as biomarkers for a range of diseases. Based on observations that ethanol altered intracellular miRNAs during development, we tested the hypothesis that plasma miRNAs were biomarkers for maternal alcohol exposure, and for past in utero exposure, in the neonate. Methods Pregnant sheep were exposed to a binge model of ethanol consumption resulting in an average peak blood alcohol content of 243 mg/dl, for a three-trimester equivalent period from gestational day (GD) 4 to GD 132. MiRNA profiles were assessed by quantitative PCR analysis in plasma, erythrocyte and leukocytes obtained from non-pregnant ewes, and plasma from pregnant ewes 24 hours following the last binge ethanol episode, and from newborn lambs, at birth on ~GD 147. Results Pregnant ewe and newborn lamb cirmiRNA profiles were similar to each other and different from non-pregnant female plasma, erythrocyte or leukocyte miRNAs. Significant changes in cirmiRNA profiles were observed in the ethanol-exposed ewe, and at birth, in the in utero, ethanol-exposed lamb. CirmiRNAs including miR-9, -15b, -19b and -20a were sensitive and specific measures of ethanol exposure in both pregnant ewe and newborn lamb. Additionally, ethanol exposure altered guide to passenger strand cirmiRNA ratios in the pregnant ewe, but not in the lamb. Conclusion Shared profiles between pregnant dam and neonate suggest possible maternal-fetal miRNA transfer. CirmiRNAs are biomarkers for alcohol exposure during pregnancy, in both mother and neonate, and may constitute an important shared endocrine biomarker that is vulnerable to the maternal environment. PMID:24588274

High-Throughput Sequencing of microRNAs in Peripheral Blood Mononuclear Cells: Identification of Potential Weight Loss Biomarkers

PubMed Central

Milagro, Fermín I.; Miranda, Jonatan; Portillo, María P.; Fernandez-Quintela, Alfredo; Campión, Javier; Martínez, J. Alfredo

2013-01-01

Introduction MicroRNAs (miRNAs) are being increasingly studied in relation to energy metabolism and body composition homeostasis. Indeed, the quantitative analysis of miRNAs expression in different adiposity conditions may contribute to understand the intimate mechanisms participating in body weight control and to find new biomarkers with diagnostic or prognostic value in obesity management. Objective The aim of this study was the search for miRNAs in blood cells whose expression could be used as prognostic biomarkers of weight loss. Methods Ten Caucasian obese women were selected among the participants in a weight-loss trial that consisted in following an energy-restricted treatment. Weight loss was considered unsuccessful when <5% of initial body weight (non-responders) and successful when >5% (responders). At baseline, total miRNA isolated from peripheral blood mononuclear cells (PBMC) was sequenced with SOLiD v4. The miRNA sequencing data were validated by RT-PCR. Results Differential baseline expression of several miRNAs was found between responders and non-responders. Two miRNAs were up-regulated in the non-responder group (mir-935 and mir-4772) and three others were down-regulated (mir-223, mir-224 and mir-376b). Both mir-935 and mir-4772 showed relevant associations with the magnitude of weight loss, although the expression of other transcripts (mir-874, mir-199b, mir-766, mir-589 and mir-148b) also correlated with weight loss. Conclusions This research addresses the use of high-throughput sequencing technologies in the search for miRNA expression biomarkers in obesity, by determining the miRNA transcriptome of PBMC. Basal expression of different miRNAs, particularly mir-935 and mir-4772, could be prognostic biomarkers and may forecast the response to a hypocaloric diet. PMID:23335998

A Customized Quantitative PCR MicroRNA Panel Provides a Technically Robust Context for Studying Neurodegenerative Disease Biomarkers and Indicates a High Correlation Between Cerebrospinal Fluid and Choroid Plexus MicroRNA Expression.

PubMed

Wang, Wang-Xia; Fardo, David W; Jicha, Gregory A; Nelson, Peter T

2017-12-01

MicroRNA (miRNA) expression varies in association with different tissue types and in diseases. Having been found in body fluids including blood and cerebrospinal fluid (CSF), miRNAs constitute potential biomarkers. CSF miRNAs have been proposed as biomarkers for neurodegenerative diseases; however, there is a lack of consensus about the best candidate miRNA biomarkers and there has been variability in results from different research centers, perhaps due to technical factors. Here, we sought to optimize technical parameters for CSF miRNA studies. We examined different RNA isolation methods and performed miRNA expression profiling with TaqMan® miRNA Arrays. More specifically, we developed a customized CSF-miRNA low-density array (TLDA) panel that contains 47 targets: miRNAs shown previously to be relevant to neurodegenerative disease, miRNAs that are abundant in CSF, data normalizers, and controls for potential blood and tissue contamination. The advantages of using this CSF-miRNA TLDA panel include specificity, sensitivity, fast processing and data analysis, and cost effectiveness. We optimized technical parameters for this assay. Further, the TLDA panel can be tailored to other specific purposes. We tested whether the profile of miRNAs in the CSF resembled miRNAs isolated from brain tissue (hippocampus or cerebellum), blood, or the choroid plexus. We found that the CSF miRNA expression profile most closely resembles that of choroid plexus tissue, underscoring the potential importance of choroid plexus-derived signaling through CSF miRNAs. In summary, the TLDA miRNA array panel will enable evaluation and discovery of CSF miRNA biomarkers and can potentially be utilized in clinical diagnosis and disease stage monitoring.

Characteristics of the level-of-evidence-1 disease forecast cancer biomarkers uPA and its inhibitor PAI-1.

PubMed

Mengele, Karin; Napieralski, Rudolf; Magdolen, Viktor; Reuning, Ute; Gkazepis, Apostolos; Sweep, Fred; Brünner, Nils; Foekens, John; Harbeck, Nadia; Schmitt, Manfred

2010-10-01

In cancer, the serine protease urokinase-type plasminogen activator, its inhibitor (plasminogen activator inhibitor type-1) and the receptor (CD87), among other proteolytic factors, are involved in tumor cell dissemination and turnover of the extracellular matrix. Unsurprisingly, a battery of very uniform data, amassed since the end of the 1990s, has put these members of the plasminogen activation system into the forefront of prognostic/predictive cancer biomarkers relevant to predict the clinical course of cancer patients and their response to cancer therapy. The present review focuses on the molecular characteristics of the disease forecast biomarkers urokinase-type plasminogen activator and plasminogen activator inhibitor type-1, and techniques to quantitatively assess these cancer biomarkers, in the context of potential clinical application and personalized disease management.

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

Identification of cypermethrin induced protein changes in green algae by iTRAQ quantitative proteomics.

PubMed

Gao, Yan; Lim, Teck Kwang; Lin, Qingsong; Li, Sam Fong Yau

2016-04-29

Cypermethrin (CYP) is one of the most widely used pesticides in large scale for agricultural and domestic purpose and the residue often seriously affects aquatic system. Environmental pollutant-induced protein changes in organisms could be detected by proteomics, leading to discovery of potential biomarkers and understanding of mode of action. While proteomics investigations of CYP stress in some animal models have been well studied, few reports about the effects of exposure to CYP on algae proteome were published. To determine CYP effect in algae, the impact of various dosages (0.001μg/L, 0.01μg/L and 1μg/L) of CYP on green algae Chlorella vulgaris for 24h and 96h was investigated by using iTRAQ quantitative proteomics technique. A total of 162 and 198 proteins were significantly altered after CYP exposure for 24h and 96h, respectively. Overview of iTRAQ results indicated that the influence of CYP on algae protein might be dosage-dependent. Functional analysis of differentially expressed proteins showed that CYP could induce protein alterations related to photosynthesis, stress responses and carbohydrate metabolism. This study provides a comprehensive view of complex mode of action of algae under CYP stress and highlights several potential biomarkers for further investigation of pesticide-exposed plant and algae. Copyright © 2016 Elsevier B.V. All rights reserved.

Proteomic analysis of urine in rats chronically exposed to fluoride.

PubMed

Kobayashi, Claudia Ayumi Nakai; Leite, Aline de Lima; da Silva, Thelma Lopes; dos Santos, Lucilene Delazari; Nogueira, Fábio César Sousa; Santos, Keity Souza; de Oliveira, Rodrigo Cardoso; Palma, Mario Sérgio; Domont, Gilberto Barbosa; Buzalaf, Marília Afonso Rabelo

2011-01-01

Urine is an ideal source of materials to search for potential disease-related biomarkers as it is produced by the affected tissues and can be easily obtained by noninvasive methods. 2-DE-based proteomic approach was used to better understand the molecular mechanisms of injury induced by fluoride (F(-)) and define potential biomarkers of dental fluorosis. Three groups of weanling male Wistar rats were treated with drinking water containing 0 (control), 5, or 50 ppm F(-) for 60 days (n = 15/group). During the experimental period, the animals were kept individually in metabolic cages, to analyze the water and food consumption, as well as fecal and urinary F(-) excretion. Urinary proteome profiles were examined using 2-DE and Colloidal Coomassie Brilliant Blue staining. A dose-response regarding F(-) intake and excretion was detected. Quantitative intensity analysis revealed 8, 11, and 8 significantly altered proteins between control vs. 5 ppm F(-), control vs. 50 ppm F(-) and 5 ppm F(-) vs. 50 ppm F(-) groups, respectively. Two proteins regulated by androgens (androgen-regulated 20-KDa protein and α-2μ-globulin) and one related to detoxification (aflatoxin-B1-aldehyde-reductase) were identified by MALDI-TOF-TOF MS/MS. Thus, proteomic analysis can help to better understand the mechanisms underlying F(-) toxicity, even in low doses. Copyright © 2010 Wiley Periodicals, Inc.

I: Biomarker quantification in fish exposed to crude oil as input to species sensitivity distributions and threshold values for environmental monitoring.

PubMed

Sanni, Steinar; Björkblom, Carina; Jonsson, Henrik; Godal, Brit F; Liewenborg, Birgitta; Lyng, Emily; Pampanin, Daniela M

2017-04-01

The aim of this study was to determine a suitable set of biomarker based methods for environmental monitoring in sub-arctic and temperate offshore areas using scientific knowledge on the sensitivity of fish species to dispersed crude oil. Threshold values for environmental monitoring and risk assessment were obtained based on a quantitative comparison of biomarker responses. Turbot, halibut, salmon and sprat were exposed for up to 8 weeks to five different sub-lethal concentrations of dispersed crude oil. Biomarkers assessing PAH metabolites, oxidative stress, detoxification system I activity, genotoxicity, immunotoxicity, endocrine disruption, general cellular stress and histological changes were measured. Results showed that PAH metabolites, CYP1A/EROD, DNA adducts and histopathology rendered the most robust results across the different fish species, both in terms of sensitivity and dose-responsiveness. The reported results contributed to forming links between biomonitoring and risk assessment procedures by using biomarker species sensitivity distributions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Genome-Wide Association Analysis of Blood Biomarkers in Chronic Obstructive Pulmonary Disease

PubMed Central

Kim, Deog Kyeom; Cho, Michael H.; Hersh, Craig P.; Lomas, David A.; Miller, Bruce E.; Kong, Xiangyang; Bakke, Per; Gulsvik, Amund; Agustí, Alvar; Wouters, Emiel; Celli, Bartolome; Coxson, Harvey; Vestbo, Jørgen; MacNee, William; Yates, Julie C.; Rennard, Stephen; Litonjua, Augusto; Qiu, Weiliang; Beaty, Terri H.; Crapo, James D.; Riley, John H.; Tal-Singer, Ruth

2012-01-01

Rationale: A genome-wide association study (GWAS) for circulating chronic obstructive pulmonary disease (COPD) biomarkers could identify genetic determinants of biomarker levels and COPD susceptibility. Objectives: To identify genetic variants of circulating protein biomarkers and novel genetic determinants of COPD. Methods: GWAS was performed for two pneumoproteins, Clara cell secretory protein (CC16) and surfactant protein D (SP-D), and five systemic inflammatory markers (C-reactive protein, fibrinogen, IL-6, IL-8, and tumor necrosis factor-α) in 1,951 subjects with COPD. For genome-wide significant single nucleotide polymorphisms (SNPs) (P < 1 × 10−8), association with COPD susceptibility was tested in 2,939 cases with COPD and 1,380 smoking control subjects. The association of candidate SNPs with mRNA expression in induced sputum was also elucidated. Measurements and Main Results: Genome-wide significant susceptibility loci affecting biomarker levels were found only for the two pneumoproteins. Two discrete loci affecting CC16, one region near the CC16 coding gene (SCGB1A1) on chromosome 11 and another locus approximately 25 Mb away from SCGB1A1, were identified, whereas multiple SNPs on chromosomes 6 and 16, in addition to SNPs near SFTPD, had genome-wide significant associations with SP-D levels. Several SNPs affecting circulating CC16 levels were significantly associated with sputum mRNA expression of SCGB1A1 (P = 0.009–0.03). Several SNPs highly associated with CC16 or SP-D levels were nominally associated with COPD in a collaborative GWAS (P = 0.001–0.049), although these COPD associations were not replicated in two additional cohorts. Conclusions: Distant genetic loci and biomarker-coding genes affect circulating levels of COPD-related pneumoproteins. A subset of these protein quantitative trait loci may influence their gene expression in the lung and/or COPD susceptibility. Clinical trial registered with www.clinicaltrials.gov (NCT 00292552). PMID:23144326

Statistical Analysis of Variation in the Human Plasma Proteome

DOE PAGES

Corzett, Todd H.; Fodor, Imola K.; Choi, Megan W.; ...

2010-01-01

Quantifying the variation in the human plasma proteome is an essential prerequisite for disease-specific biomarker detection. We report here on the longitudinal and individual variation in human plasma characterized by two-dimensional difference gel electrophoresis (2-D DIGE) using plasma samples from eleven healthy subjects collected three times over a two week period. Fixed-effects modeling was used to remove dye and gel variability. Mixed-effects modeling was then used to quantitate the sources of proteomic variation. The subject-to-subject variation represented the largest variance component, while the time-within-subject variation was comparable to the experimental variation found in a previous technical variability study where onemore » human plasma sample was processed eight times in parallel and each was then analyzed by 2-D DIGE in triplicate. Here, 21 protein spots had larger than 50% CV, suggesting that these proteins may not be appropriate as biomarkers and should be carefully scrutinized in future studies. Seventy-eight protein spots showing differential protein levels between different individuals or individual collections were identified by mass spectrometry and further characterized using hierarchical clustering. The results present a first step toward understanding the complexity of longitudinal and individual variation in the human plasma proteome, and provide a baseline for improved biomarker discovery.« less

Sebaceous lipid profiling of bat integumentary tissues: quantitative analysis of free Fatty acids, monoacylglycerides, squalene, and sterols.

PubMed

Pannkuk, Evan L; Gilmore, David F; Fuller, Nathan W; Savary, Brett J; Risch, Thomas S

2013-12-01

White-nose syndrome (WNS) is a fungal disease caused by Pseudogymnoascus destructans and is devastating North American bat populations. Sebaceous lipids secreted from host integumentary tissues are implicated in the initial attachment and recognition of host tissues by pathogenic fungi. We are interested in determining if ratios of lipid classes in sebum can be used as biomarkers to diagnose severity of fungal infection in bats. To first establish lipid compositions in bats, we isolated secreted and integral lipid fractions from the hair and wing tissues of three species: big brown bats (Eptesicus fuscus), Eastern red bats (Lasiurus borealis), and evening bats (Nycticeius humeralis). Sterols, FFAs, MAGs, and squalene were derivatized as trimethylsilyl esters, separated by gas chromatography, and identified by mass spectrometry. Ratios of sterol to squalene in different tissues were determined, and cholesterol as a disease biomarker was assessed. Free sterol was the dominant lipid class of bat integument. Squalene/sterol ratio is highest in wing sebum. Secreted wing lipid contained higher proportions of saturated FFAs and MAGs than integral wing or secreted hair lipid. These compounds are targets for investigating responses of P. destructans to specific host lipid compounds and as biomarkers to diagnose WNS. Copyright © 2013 Verlag Helvetica Chimica Acta AG, Zürich.

Metallothionein from Wild Populations of the African Catfish Clarias gariepinus: From Sequence, Protein Expression and Metal Binding Properties to Transcriptional Biomarker of Metal Pollution.

PubMed

M'kandawire, Ethel; Mierek-Adamska, Agnieszka; Stürzenbaum, Stephen R; Choongo, Kennedy; Yabe, John; Mwase, Maxwell; Saasa, Ngonda; Blindauer, Claudia A

2017-07-18

Anthropogenic pollution with heavy metals is an on-going concern throughout the world, and methods to monitor release and impact of heavy metals are of high importance. With a view to probe its suitability as molecular biomarker of metal pollution, this study has determined a coding sequence for metallothionein of the African sharptooth catfish Clarias gariepinus . The gene product was recombinantly expressed in Escherichia coli in presence of Zn(II), Cd(II), or Cu, and characterised by Electrospray Ionisation Mass Spectrometry and elemental analysis. C. gariepinus MT displays typical features of fish MTs, including 20 conserved cysteines, and seven bound divalent cations (Zn(II) or Cd(II)) when saturated. Livers from wild C. gariepinus fish collected in all three seasons from four different sites on the Kafue River of Zambia were analysed for their metal contents and for MT expression levels by quantitative PCR. Significant correlations were found between Zn and Cu levels and MT expression in livers, with MT expression clearly highest at the most polluted site, Chililabombwe, which is situated in the Copperbelt region. Based on our findings, hepatic expression of MT from C. gariepinus may be further developed as a major molecular biomarker of heavy metal pollution resulting from mining activities in this region.

A novel immunochromatographic electrochemical biosensor for highly sensitive and selective detection of trichloropyridinol, a biomarker of exposure to chlorpyrifos.

PubMed

Wang, Limin; Lu, Donglai; Wang, Jun; Du, Dan; Zou, Zhexiang; Wang, Hua; Smith, Jordan N; Timchalk, Charles; Liu, Fengquan; Lin, Yuehe

2011-02-15

We present a novel portable immunochromatographic electrochemical biosensor (IEB) for simple, rapid, and sensitive biomonitoring of trichloropyridinol (TCP), a metabolite biomarker of exposure to organophosphorus insecticides. Our new approach takes the advantage of immunochromatographic test strip for a rapid competitive immunoreaction and a disposable screen-printed carbon electrode for a rapid and sensitive electrochemical analysis of captured HRP labeling. Several key experimental parameters (e.g. immunoreaction time, the amount of HRP labeled TCP, concentration of the substrate for electrochemical measurements, and the blocking agents for the nitrocellulose membrane) were optimized to achieve a high sensitivity, selectivity and stability. Under optimal conditions, the IEB has demonstrated a wide linear range (0.1-100 ng/ml) with a detection limit as low as 0.1 ng/ml TCP. Furthermore, the IEB has been successfully applied for biomonitoring of TCP in the rat plasma samples with in vivo exposure to organophosphorus insecticides like Chlorpyrifos-oxon (CPF-oxon). The IEB thus opens up new pathways for designing a simple, rapid, clinically accurate, and quantitative tool for TCP detection, as well as holds a great promise for in-field screening of metabolite biomarkers, e.g., TCP, for humans exposed to organophosphorus insecticides. Copyright © 2010 Elsevier B.V. All rights reserved.

Statistical analysis of variation in the human plasma proteome.

PubMed

Corzett, Todd H; Fodor, Imola K; Choi, Megan W; Walsworth, Vicki L; Turteltaub, Kenneth W; McCutchen-Maloney, Sandra L; Chromy, Brett A

2010-01-01

Quantifying the variation in the human plasma proteome is an essential prerequisite for disease-specific biomarker detection. We report here on the longitudinal and individual variation in human plasma characterized by two-dimensional difference gel electrophoresis (2-D DIGE) using plasma samples from eleven healthy subjects collected three times over a two week period. Fixed-effects modeling was used to remove dye and gel variability. Mixed-effects modeling was then used to quantitate the sources of proteomic variation. The subject-to-subject variation represented the largest variance component, while the time-within-subject variation was comparable to the experimental variation found in a previous technical variability study where one human plasma sample was processed eight times in parallel and each was then analyzed by 2-D DIGE in triplicate. Here, 21 protein spots had larger than 50% CV, suggesting that these proteins may not be appropriate as biomarkers and should be carefully scrutinized in future studies. Seventy-eight protein spots showing differential protein levels between different individuals or individual collections were identified by mass spectrometry and further characterized using hierarchical clustering. The results present a first step toward understanding the complexity of longitudinal and individual variation in the human plasma proteome, and provide a baseline for improved biomarker discovery.

Method and platform standardization in MRM-based quantitative plasma proteomics.

PubMed

Percy, Andrew J; Chambers, Andrew G; Yang, Juncong; Jackson, Angela M; Domanski, Dominik; Burkhart, Julia; Sickmann, Albert; Borchers, Christoph H

2013-12-16

There exists a growing demand in the proteomics community to standardize experimental methods and liquid chromatography-mass spectrometry (LC/MS) platforms in order to enable the acquisition of more precise and accurate quantitative data. This necessity is heightened by the evolving trend of verifying and validating candidate disease biomarkers in complex biofluids, such as blood plasma, through targeted multiple reaction monitoring (MRM)-based approaches with stable isotope-labeled standards (SIS). Considering the lack of performance standards for quantitative plasma proteomics, we previously developed two reference kits to evaluate the MRM with SIS peptide approach using undepleted and non-enriched human plasma. The first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). Here, these kits have been refined for practical use and then evaluated through intra- and inter-laboratory testing on 6 common LC/MS platforms. For an identical panel of 22 plasma proteins, similar concentrations were determined, regardless of the kit, instrument platform, and laboratory of analysis. These results demonstrate the value of the kit and reinforce the utility of standardized methods and protocols. The proteomics community needs standardized experimental protocols and quality control methods in order to improve the reproducibility of MS-based quantitative data. This need is heightened by the evolving trend for MRM-based validation of proposed disease biomarkers in complex biofluids such as blood plasma. We have developed two kits to assist in the inter- and intra-laboratory quality control of MRM experiments: the first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). In this paper, we report the use of these kits in intra- and inter-laboratory testing on 6 common LC/MS platforms. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics. © 2013.

DNA Repair Biomarkers Predict Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer

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

Alexander, Brian M., E-mail: bmalexander@lroc.harvard.edu; Wang Xiaozhe; Niemierko, Andrzej

2012-05-01

Purpose: The addition of neoadjuvant chemoradiotherapy prior to surgical resection for esophageal cancer has improved clinical outcomes in some trials. Pathologic complete response (pCR) following neoadjuvant therapy is associated with better clinical outcome in these patients, but only 22% to 40% of patients achieve pCR. Because both chemotherapy and radiotherapy act by inducing DNA damage, we analyzed proteins selected from multiple DNA repair pathways, using quantitative immunohistochemistry coupled with a digital pathology platform, as possible biomarkers of treatment response and clinical outcome. Methods and Materials: We identified 79 patients diagnosed with esophageal cancer between October 1994 and September 2002, withmore » biopsy tissue available, who underwent neoadjuvant chemoradiotherapy prior to surgery at the Massachusetts General Hospital and used their archived, formalin-fixed, paraffin-embedded biopsy samples to create tissue microarrays (TMA). TMA sections were stained using antibodies against proteins in various DNA repair pathways including XPF, FANCD2, PAR, MLH1, PARP1, and phosphorylated MAPKAP kinase 2 (pMK2). Stained TMA slides were evaluated using machine-based image analysis, and scoring incorporated both the intensity and the quantity of positive tumor nuclei. Biomarker scores and clinical data were assessed for correlations with clinical outcome. Results: Higher scores for MLH1 (p = 0.018) and lower scores for FANCD2 (p = 0.037) were associated with pathologic response to neoadjuvant chemoradiation on multivariable analysis. Staining of MLH1, PARP1, XPF, and PAR was associated with recurrence-free survival, and staining of PARP1 and FANCD2 was associated with overall survival on multivariable analysis. Conclusions: DNA repair proteins analyzed by immunohistochemistry may be useful as predictive markers for response to neoadjuvant chemoradiotherapy in patients with esophageal cancer. These results are hypothesis generating and need confirmation in an independent data set.« less

MR Imaging in Spinocerebellar Ataxias: A Systematic Review.

PubMed

Klaes, A; Reckziegel, E; Franca, M C; Rezende, T J R; Vedolin, L M; Jardim, L B; Saute, J A

2016-08-01

Polyglutamine expansion spinocerebellar ataxias are autosomal dominant slowly progressive neurodegenerative diseases with no current treatment. MR imaging is the best-studied surrogate biomarker candidate for polyglutamine expansion spinocerebellar ataxias, though with conflicting results. We aimed to review quantitative central nervous system MR imaging technique findings in patients with polyglutamine expansion spinocerebellar ataxias and correlations with well-established clinical and molecular disease markers. We searched MEDLINE, LILACS, and Cochrane data bases of clinical trials between January 1995 and January 2016, for quantitative MR imaging volumetric approaches, MR spectroscopy, diffusion tensor imaging, or other quantitative techniques, comparing patients with polyglutamine expansion spinocerebellar ataxias (SCAs) with controls. Pertinent details for each study regarding participants, imaging methods, and results were extracted. After reviewing the 706 results, 18 studies were suitable for inclusion: 2 studies in SCA1, 1 in SCA2, 15 in SCA3, 1 in SCA7, 1 in SCA1 and SCA6 presymptomatic carriers, and none in SCA17 and dentatorubropallidoluysian atrophy. Cerebellar hemispheres and vermis, whole brain stem, midbrain, pons, medulla oblongata, cervical spine, striatum, and thalamus presented significant atrophy in SCA3. The caudate, putamen and whole brain stem presented similar sensitivity to change compared with ataxia scales after 2 years of follow-up in a single prospective study in SCA3. MR spectroscopy and DTI showed abnormalities only in cross-sectional studies in SCA3. Results from single studies in other polyglutamine expansion spinocerebellar ataxias should be replicated in different cohorts. Additional cross-sectional and prospective volumetric analysis, MR spectroscopy, and DTI studies are necessary in polyglutamine expansion spinocerebellar ataxias. The properties of preclinical disease biomarkers (presymptomatic) of MR imaging should be targeted in future studies. © 2016 by American Journal of Neuroradiology.

Reliable LC-MS quantitative glycomics using iGlycoMab stable isotope labeled glycans as internal standards.

PubMed

Zhou, Shiyue; Tello, Nadia; Harvey, Alex; Boyes, Barry; Orlando, Ron; Mechref, Yehia

2016-06-01

Glycans have numerous functions in various biological processes and participate in the progress of diseases. Reliable quantitative glycomic profiling techniques could contribute to the understanding of the biological functions of glycans, and lead to the discovery of potential glycan biomarkers for diseases. Although LC-MS is a powerful analytical tool for quantitative glycomics, the variation of ionization efficiency and MS intensity bias are influencing quantitation reliability. Internal standards can be utilized for glycomic quantitation by MS-based methods to reduce variability. In this study, we used stable isotope labeled IgG2b monoclonal antibody, iGlycoMab, as an internal standard to reduce potential for errors and to reduce variabililty due to sample digestion, derivatization, and fluctuation of nanoESI efficiency in the LC-MS analysis of permethylated N-glycans released from model glycoproteins, human blood serum, and breast cancer cell line. We observed an unanticipated degradation of isotope labeled glycans, tracked a source of such degradation, and optimized a sample preparation protocol to minimize degradation of the internal standard glycans. All results indicated the effectiveness of using iGlycoMab to minimize errors originating from sample handling and instruments. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

IWGT report on quantitative approaches to genotoxicity risk ...

EPA Pesticide Factsheets

This is the second of two reports from the International Workshops on Genotoxicity Testing (IWGT) Working Group on Quantitative Approaches to Genetic Toxicology Risk Assessment (the QWG). The first report summarized the discussions and recommendations of the QWG related to the need for quantitative dose–response analysis of genetic toxicology data, the existence and appropriate evaluation of threshold responses, and methods to analyze exposure-response relationships and derive points of departure (PoDs) from which acceptable exposure levels could be determined. This report summarizes the QWG discussions and recommendations regarding appropriate approaches to evaluate exposure-related risks of genotoxic damage, including extrapolation below identified PoDs and across test systems and species. Recommendations include the selection of appropriate genetic endpoints and target tissues, uncertainty factors and extrapolation methods to be considered, the importance and use of information on mode of action, toxicokinetics, metabolism, and exposure biomarkers when using quantitative exposure-response data to determine acceptable exposure levels in human populations or to assess the risk associated with known or anticipated exposures. The empirical relationship between genetic damage (mutation and chromosomal aberration) and cancer in animal models was also examined. It was concluded that there is a general correlation between cancer induction and mutagenic and/or clast

Quantitative radiomic profiling of glioblastoma represents transcriptomic expression.

PubMed

Kong, Doo-Sik; Kim, Junhyung; Ryu, Gyuha; You, Hye-Jin; Sung, Joon Kyung; Han, Yong Hee; Shin, Hye-Mi; Lee, In-Hee; Kim, Sung-Tae; Park, Chul-Kee; Choi, Seung Hong; Choi, Jeong Won; Seol, Ho Jun; Lee, Jung-Il; Nam, Do-Hyun

2018-01-19

Quantitative imaging biomarkers have increasingly emerged in the field of research utilizing available imaging modalities. We aimed to identify good surrogate radiomic features that can represent genetic changes of tumors, thereby establishing noninvasive means for predicting treatment outcome. From May 2012 to June 2014, we retrospectively identified 65 patients with treatment-naïve glioblastoma with available clinical information from the Samsung Medical Center data registry. Preoperative MR imaging data were obtained for all 65 patients with primary glioblastoma. A total of 82 imaging features including first-order statistics, volume, and size features, were semi-automatically extracted from structural and physiologic images such as apparent diffusion coefficient and perfusion images. Using commercially available software, NordicICE, we performed quantitative imaging analysis and collected the dataset composed of radiophenotypic parameters. Unsupervised clustering methods revealed that the radiophenotypic dataset was composed of three clusters. Each cluster represented a distinct molecular classification of glioblastoma; classical type, proneural and neural types, and mesenchymal type. These clusters also reflected differential clinical outcomes. We found that extracted imaging signatures does not represent copy number variation and somatic mutation. Quantitative radiomic features provide a potential evidence to predict molecular phenotype and treatment outcome. Radiomic profiles represents transcriptomic phenotypes more well.

Assessment of mechanisms of metal-induced reproductive toxicity in aquatic species as a biomarker of exposure

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

Anderson, M.; George, W.; Preslan, J.

1996-05-02

This project discusses the following studies: identification and quantitation of heavy metals and petroleum products present in Bayou Trepagnier relative to control sites; assessment of the uptake and bioaccumulation of metals and organic contaminants of interest in aquatic species; establishment and use of polarographic methods for use in metal speciation studies to identify specific chemical forms present in sediments, waters and organism; and evaluation of contaminants on reproductive function of aquatic species as potential biomarkers of exposure. 14 refs.

Phosphoproteins in extracellular vesicles as candidate markers for breast cancer

PubMed Central

Chen, I-Hsuan; Xue, Liang; Hsu, Chuan-Chih; Paez, Juan Sebastian Paez; Pan, Li; Andaluz, Hillary; Wendt, Michael K.; Iliuk, Anton B.; Tao, W. Andy

2017-01-01

The state of protein phosphorylation can be a key determinant of cellular physiology such as early-stage cancer, but the development of phosphoproteins in biofluids for disease diagnosis remains elusive. Here we demonstrate a strategy to isolate and identify phosphoproteins in extracellular vesicles (EVs) from human plasma as potential markers to differentiate disease from healthy states. We identified close to 10,000 unique phosphopeptides in EVs isolated from small volumes of plasma samples. Using label-free quantitative phosphoproteomics, we identified 144 phosphoproteins in plasma EVs that are significantly higher in patients diagnosed with breast cancer compared with healthy controls. Several biomarkers were validated in individual patients using paralleled reaction monitoring for targeted quantitation. This study demonstrates that the development of phosphoproteins in plasma EV as disease biomarkers is highly feasible and may transform cancer screening and monitoring. PMID:28270605

Phosphoproteins in extracellular vesicles as candidate markers for breast cancer.

PubMed

Chen, I-Hsuan; Xue, Liang; Hsu, Chuan-Chih; Paez, Juan Sebastian Paez; Pan, Li; Andaluz, Hillary; Wendt, Michael K; Iliuk, Anton B; Zhu, Jian-Kang; Tao, W Andy

2017-03-21

The state of protein phosphorylation can be a key determinant of cellular physiology such as early-stage cancer, but the development of phosphoproteins in biofluids for disease diagnosis remains elusive. Here we demonstrate a strategy to isolate and identify phosphoproteins in extracellular vesicles (EVs) from human plasma as potential markers to differentiate disease from healthy states. We identified close to 10,000 unique phosphopeptides in EVs isolated from small volumes of plasma samples. Using label-free quantitative phosphoproteomics, we identified 144 phosphoproteins in plasma EVs that are significantly higher in patients diagnosed with breast cancer compared with healthy controls. Several biomarkers were validated in individual patients using paralleled reaction monitoring for targeted quantitation. This study demonstrates that the development of phosphoproteins in plasma EV as disease biomarkers is highly feasible and may transform cancer screening and monitoring.

Genetic Biomarker Prevalence Is Similar in Fecal Immunochemical Test Positive and Negative Colorectal Cancer Tissue.

PubMed

Levin, Theodore R; Corley, Douglas A; Jensen, Christopher D; Marks, Amy R; Zhao, Wei K; Zebrowski, Alexis M; Quinn, Virginia P; Browne, Lawrence W; Taylor, William R; Ahlquist, David A; Lidgard, Graham P; Berger, Barry M

2017-03-01

Fecal immunochemical test (FIT) screening detects most asymptomatic colorectal cancers. Combining FIT screening with stool-based genetic biomarkers increases sensitivity for cancer, but whether DNA biomarkers (biomarkers) differ for cancers detected versus missed by FIT screening has not been evaluated in a community-based population. To evaluate tissue biomarkers among Kaiser Permanente Northern California patients diagnosed with colorectal cancer within 2 years after FIT screening. FIT-negative and FIT-positive colorectal cancer patients 50-77 years of age were matched on age, sex, and cancer stage. Adequate DNA was isolated from paraffin-embedded specimens in 210 FIT-negative and 211 FIT-positive patients. Quantitative allele-specific real-time target and signal amplification assays were performed for 7 K-ras mutations and 10 aberrantly methylated DNA biomarkers (NDRG4, BMP3, SFMBT2_895, SFMBT2_896, SFMBT2_897, CHST2_7890, PDGFD, VAV3, DTX1, CHST2_7889). One or more biomarkers were found in 414 of 421 CRCs (98.3%). Biomarker expression was not associated with FIT status, with the exception of higher SFMBT2_897 expression in FIT-negative (194 of 210; 92.4%) than in FIT-positive cancers (180 of 211; 85.3%; p = 0.02). There were no consistent differences in biomarker expression by FIT status within age, sex, stage, and cancer location subgroups. The biomarkers of a currently in-use multi-target stool DNA test (K-ras, NDRG4, and BMP3) and eight newly characterized methylated biomarkers were commonly expressed in tumor tissue specimens, independent of FIT result. Additional study using stool-based testing with these new biomarkers will allow assessment of sensitivity, specificity, and clinical utility.

Reproducible Tissue Homogenization and Protein Extraction for Quantitative Proteomics Using MicroPestle-Assisted Pressure-Cycling Technology.

PubMed

Shao, Shiying; Guo, Tiannan; Gross, Vera; Lazarev, Alexander; Koh, Ching Chiek; Gillessen, Silke; Joerger, Markus; Jochum, Wolfram; Aebersold, Ruedi

2016-06-03

The reproducible and efficient extraction of proteins from biopsy samples for quantitative analysis is a critical step in biomarker and translational research. Recently, we described a method consisting of pressure-cycling technology (PCT) and sequential windowed acquisition of all theoretical fragment ions-mass spectrometry (SWATH-MS) for the rapid quantification of thousands of proteins from biopsy-size tissue samples. As an improvement of the method, we have incorporated the PCT-MicroPestle into the PCT-SWATH workflow. The PCT-MicroPestle is a novel, miniaturized, disposable mechanical tissue homogenizer that fits directly into the microTube sample container. We optimized the pressure-cycling conditions for tissue lysis with the PCT-MicroPestle and benchmarked the performance of the system against the conventional PCT-MicroCap method using mouse liver, heart, brain, and human kidney tissues as test samples. The data indicate that the digestion of the PCT-MicroPestle-extracted proteins yielded 20-40% more MS-ready peptide mass from all tissues tested with a comparable reproducibility when compared to the conventional PCT method. Subsequent SWATH-MS analysis identified a higher number of biologically informative proteins from a given sample. In conclusion, we have developed a new device that can be seamlessly integrated into the PCT-SWATH workflow, leading to increased sample throughput and improved reproducibility at both the protein extraction and proteomic analysis levels when applied to the quantitative proteomic analysis of biopsy-level samples.

Effects of Supplemental Vitamin D and Calcium on Normal Colon Tissue and Circulating Biomarkers of Risk for Colorectal Neoplasms

PubMed Central

Bostick, Roberd M.

2015-01-01

This brief review, based on an invited presentation at the 17th Workshop on Vitamin D, is to summarize a line of the author’s research that has been directed at the intertwined missions of clarifying and/or developing vitamin D and calcium and as preventive agents against colorectal cancer in humans, understanding the mechanisms by which these agents may reduce risk for the disease, and developing ‘treatable’ biomarkers of risk for colorectal cancer. The biological plausibility and observational and clinical trial evidence for vitamin D and calcium in reducing risk for colorectal neoplasms, the development of pre-neoplastic biomarkers of risk for colorectal neoplasms, and the clinical trial findings from the author’s research group on the efficacy of vitamin D and calcium in modulating these biomarkers are summarized. Regarding the latter, we tested the efficacy of 800 IU (20 µg) of vitamin D3 and 2.0g of calcium daily, alone and combined vs. placebo over 6 months on modulating normal colon tissue and circulating hypothesis-based biomarkers of risk for colorectal neoplasms in a randomized, double-blind, placebo-controlled, 2×2 factorial design clinical trial (n = 92). The tissue-based biomarkers were measured in biopsies of normal-appearing rectal mucosa using immunohistochemistry with quantitative image analysis, and a panel of circulating inflammation markers was measured using enzyme-linked immunoassays (ELISA). Statistically significant proportional tissue increases in the vitamin D group relative to the placebo group were found in bax (51%), p21 (141%), APC (48%), E-cadherin (78%), MSH2 (179%), the CaSR (39%), and CYP27B1 (159%). In blood, there was a 77% statistically significant decrease in a summary inflammation z-score. The findings for calcium were similar to those for vitamin D. These findings indicate that supplemental vitamin D3 or calcium can favorably modulate multiple normal colon tissue and circulating hypothesis-based biomarkers of risk for colorectal neoplasms in sporadic colorectal adenoma patients. PMID:25597952

Effects of supplemental vitamin D and calcium on normal colon tissue and circulating biomarkers of risk for colorectal neoplasms.

PubMed

Bostick, Roberd M

2015-04-01

This brief review, based on an invited presentation at the 17th Workshop on Vitamin D, is to summarize a line of the author's research that has been directed at the intertwined missions of clarifying and/or developing vitamin D and calcium as preventive agents against colorectal cancer in humans, understanding the mechanisms by which these agents may reduce risk for the disease, and developing 'treatable' biomarkers of risk for colorectal cancer. The biological plausibility and observational and clinical trial evidence for vitamin D and calcium in reducing risk for colorectal neoplasms, the development of pre-neoplastic biomarkers of risk for colorectal neoplasms, and the clinical trial findings from the author's research group on the efficacy of vitamin D and calcium in modulating these biomarkers are summarized. Regarding the latter, we tested the efficacy of 800 IU (20μg) of vitamin D3 and 2.0g of calcium daily, alone and combined vs. placebo over 6 months on modulating normal colon tissue and circulating hypothesis-based biomarkers of risk for colorectal neoplasms in a randomized, double-blind, placebo-controlled, 2×2 factorial design clinical trial (n=92). The tissue-based biomarkers were measured in biopsies of normal-appearing rectal mucosa using immunohistochemistry with quantitative image analysis, and a panel of circulating inflammation markers was measured using enzyme-linked immunoassays (ELISA). Statistically significant proportional tissue increases in the vitamin D group relative to the placebo group were found in bax (51%), p21 (141%), APC (48%), E-cadherin (78%), MSH2 (179%), the CaSR (39%), and CYP27B1 (159%). In blood, there was a 77% statistically significant decrease in a summary inflammation z-score. The findings for calcium were similar to those for vitamin D. These findings indicate that supplemental vitamin D3 or calcium can favorably modulate multiple normal colon tissue and circulating hypothesis-based biomarkers of risk for colorectal neoplasms in sporadic colorectal adenoma patients. This article is part of a Special Issue entitled '17th Vitamin D Workshop'. Copyright © 2015 Elsevier Ltd. All rights reserved.

Increased levels of ethane, a non-invasive, quantitative, direct marker of n-3 lipid peroxidation, in the breath of patients with schizophrenia.

PubMed

Puri, Basant K; Ross, Brian M; Treasaden, Ian H

2008-04-01

This study directly assessed whether there was a change in the level of exhaled ethane, which provides a non-invasive, quantitative, direct measure of n-3 lipid peroxidation, in the breath of patients with schizophrenia. Samples of alveolar air were obtained from 20 subjects with schizophrenia and 23 age- and sex-matched healthy control subjects. The air samples were analyzed for ethane using mass spectrometry. The mean level of ethane in the schizophrenia sample [5.15 (S.E. 0.56) ppb] was significantly higher than that of the healthy controls [2.63 (S.E. 0.31) ppb; p<0.0005]. A further sub-analysis showed that nicotine dependence was unlikely to be the cause of this difference. These results suggest that the measurement of exhaled ethane levels may offer a non-invasive direct biomarker of increased n-3 lipid peroxidation in schizophrenia.

Reliability of Using Retinal Vascular Fractal Dimension as a Biomarker in the Diabetic Retinopathy Detection

PubMed Central

Zhang, Jiong; Bekkers, Erik; Abbasi-Sureshjani, Samaneh

2016-01-01

The retinal fractal dimension (FD) is a measure of vasculature branching pattern complexity. FD has been considered as a potential biomarker for the detection of several diseases like diabetes and hypertension. However, conflicting findings were found in the reported literature regarding the association between this biomarker and diseases. In this paper, we examine the stability of the FD measurement with respect to (1) different vessel annotations obtained from human observers, (2) automatic segmentation methods, (3) various regions of interest, (4) accuracy of vessel segmentation methods, and (5) different imaging modalities. Our results demonstrate that the relative errors for the measurement of FD are significant and FD varies considerably according to the image quality, modality, and the technique used for measuring it. Automated and semiautomated methods for the measurement of FD are not stable enough, which makes FD a deceptive biomarker in quantitative clinical applications. PMID:27703803

Quantitative detection of liver-relevant biomarkers by SERS-immunolabeled gold nanoparticles

NASA Astrophysics Data System (ADS)

Payne, William Mark

Lab-on-a-chip technology has the potential to rapidly change the way experiments are conducted in a variety of fields ranging from medicine to environmental science. Specifically, sensors, detectors, and monitoring devices are increasingly being miniaturized to perform many experiments or measurements on a single chip. In this research, we develop an immunolabeled gold nanoparticle complex capable of detecting liver organoid biomarkers intended for use in a microfluidic device. Human Serum Albumin (HSA) and alpha-Glutathione S-Transferase (alpha-GST) are liver biomarkers that indicate liver health and damage respectively. Herein we demonstrate detection of the liver organoid biomarkers at nanomolar concentrations. Through plasmonic coupling induced by aggregation in the presence of analyte, the SERS signal obtained from the nanoparticles is dramatically increased. Furthermore, detection is demonstrated in a simple fluidic device to show the feasibility of implementing an optimized SERS-immunolabeled nanoparticle for translational application.

Targeted proteomics identifies liquid-biopsy signatures for extracapsular prostate cancer

PubMed Central

Kim, Yunee; Jeon, Jouhyun; Mejia, Salvador; Yao, Cindy Q; Ignatchenko, Vladimir; Nyalwidhe, Julius O; Gramolini, Anthony O; Lance, Raymond S; Troyer, Dean A; Drake, Richard R; Boutros, Paul C; Semmes, O. John; Kislinger, Thomas

2016-01-01

Biomarkers are rapidly gaining importance in personalized medicine. Although numerous molecular signatures have been developed over the past decade, there is a lack of overlap and many biomarkers fail to validate in independent patient cohorts and hence are not useful for clinical application. For these reasons, identification of novel and robust biomarkers remains a formidable challenge. We combine targeted proteomics with computational biology to discover robust proteomic signatures for prostate cancer. Quantitative proteomics conducted in expressed prostatic secretions from men with extraprostatic and organ-confined prostate cancers identified 133 differentially expressed proteins. Using synthetic peptides, we evaluate them by targeted proteomics in a 74-patient cohort of expressed prostatic secretions in urine. We quantify a panel of 34 candidates in an independent 207-patient cohort. We apply machine-learning approaches to develop clinical predictive models for prostate cancer diagnosis and prognosis. Our results demonstrate that computationally guided proteomics can discover highly accurate non-invasive biomarkers. PMID:27350604

Reliability of Using Retinal Vascular Fractal Dimension as a Biomarker in the Diabetic Retinopathy Detection.

PubMed

Huang, Fan; Dashtbozorg, Behdad; Zhang, Jiong; Bekkers, Erik; Abbasi-Sureshjani, Samaneh; Berendschot, Tos T J M; Ter Haar Romeny, Bart M

2016-01-01

The retinal fractal dimension (FD) is a measure of vasculature branching pattern complexity. FD has been considered as a potential biomarker for the detection of several diseases like diabetes and hypertension. However, conflicting findings were found in the reported literature regarding the association between this biomarker and diseases. In this paper, we examine the stability of the FD measurement with respect to (1) different vessel annotations obtained from human observers, (2) automatic segmentation methods, (3) various regions of interest, (4) accuracy of vessel segmentation methods, and (5) different imaging modalities. Our results demonstrate that the relative errors for the measurement of FD are significant and FD varies considerably according to the image quality, modality, and the technique used for measuring it. Automated and semiautomated methods for the measurement of FD are not stable enough, which makes FD a deceptive biomarker in quantitative clinical applications.

Single-band upconversion nanoprobes for multiplexed simultaneous in situ molecular mapping of cancer biomarkers.

PubMed

Zhou, Lei; Wang, Rui; Yao, Chi; Li, Xiaomin; Wang, Chengli; Zhang, Xiaoyan; Xu, Congjian; Zeng, Aijun; Zhao, Dongyuan; Zhang, Fan

2015-04-24

The identification of potential diagnostic markers and target molecules among the plethora of tumour oncoproteins for cancer diagnosis requires facile technology that is capable of quantitatively analysing multiple biomarkers in tumour cells and tissues. Diagnostic and prognostic classifications of human tumours are currently based on the western blotting and single-colour immunohistochemical methods that are not suitable for multiplexed detection. Herein, we report a general and novel method to prepare single-band upconversion nanoparticles with different colours. The expression levels of three biomarkers in breast cancer cells were determined using single-band upconversion nanoparticles, western blotting and immunohistochemical technologies with excellent correlation. Significantly, the application of antibody-conjugated single-band upconversion nanoparticle molecular profiling technology can achieve the multiplexed simultaneous in situ biodetection of biomarkers in breast cancer cells and tissue specimens and produce more accurate results for the simultaneous quantification of proteins present at low levels compared with classical immunohistochemical technology.

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.

Monitoring Progression of Amyotrophic Lateral Sclerosis Using Ultrasound Morpho-Textural Muscle Biomarkers: A Pilot Study.

PubMed

Martínez-Payá, Jacinto J; Ríos-Díaz, José; Medina-Mirapeix, Francesc; Vázquez-Costa, Juan F; Del Baño-Aledo, María Elena

2018-01-01

The need is increasing for progression biomarkers that allow the loss of motor neurons in amyotrophic lateral sclerosis (ALS) to be monitored in clinical trials. In this prospective longitudinal study, muscle thickness, echointensity, echovariation and gray level co-occurrence matrix textural features are examined as possible progression ultrasound biomarkers in ALS patients during a 5-mo follow-up period. We subjected 13 patients to 3 measurements for 20 wk. They showed a significant loss of muscle, an evident tendency to loss of thickness and increased echointensity and echovariation. In regard to textural parameters, muscle heterogeneity tended to increase as a result of the neoformation of non-contractile tissue through denervation. Considering some limitations of the study, the quantitative muscle ultrasound biomarkers evaluated showed a promising ability to monitor patients affected by ALS. Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

RECONSTRUCTING EXPOSURE SCENARIOS USING DOSE BIOMARKERS - AN APPLICATION OF BAYESIAN UNCERTAINTY ANALYSIS

EPA Science Inventory

We use Bayesian uncertainty analysis to explore how to estimate pollutant exposures from biomarker concentrations. The growing number of national databases with exposure data makes such an analysis possible. They contain datasets of pharmacokinetic biomarkers for many polluta...

A paradigm shift in imaging biomarkers in neovascular age-related macular degeneration.

PubMed

Schmidt-Erfurth, Ursula; Waldstein, Sebastian M

2016-01-01

Neovascular age-related macular degeneration (AMD) has undergone substantial break-throughs in diagnostic as well as therapeutic respect, with optical coherence tomography (OCT) allowing to identify disease morphology in great detail, and intravitreal anti-vascular endothelial growth factor therapy providing unprecedented benefit. However, these two paths have yet not been combined in an optimal way, real-world outcomes are inferior to expectations, and disease management is largely inefficient in the real-world setting. This dilemma can be solved by identification of valid biomarkers relevant for visual function, disease activity and prognosis, which can provide solid guidance for therapeutic management on an individual level as well as on the population base. Qualitative and quantitative morphological features obtained by advanced OCT provide novel insight into exudative and degenerative stages of neovascular AMD. However, conclusions from structure/function correlations evolve differently from previous paradigms. While central retinal thickness was used as biomarker for guiding retreatment management in clinical trials and practice, fluid localization in different compartments offers superior prognostic value: Intraretinal cystoid fluid has a negative impact on visual acuity and is considered as degenerative when persisting through the initial therapeutic interval. Subretinal fluid is associated with superior visual benefit and a lower rate of progression towards geographic atrophy. Detachment of the retinal pigment epithelium was identified as most pathognomonic biomarker, often irresponsive to therapy and responsible for visual decline during a pro-re-nata regimen. Alterations of neurosensory tissue are usually associated with irreversible loss of functional elements and a negative prognosis. Novel OCT technologies offer crucial insight into corresponding changes at the level of the photoreceptor--retinal pigment epithelial--choriocapillary unit, identifying the biological limits of therapeutic interventions. To optimally benefit from high-resolution multi-modal imaging, an integrated analysis of all functional and structural features is required involving reliable automated algorithms and computational data analyses. Using innovative analysis methods, retinal biomarkers can be used to provide efficient personalized therapy for the individual patient, predictive disease- and population-based models for large-scale management and identifying promising targets for the development of novel therapeutic strategies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Alteration of matrix metalloproteinase-3 O-glycan structure as a biomarker for disease activity of rheumatoid arthritis.

PubMed

Takeshita, Masaru; Kuno, Atsushi; Suzuki, Katsuya; Matsuda, Atsushi; Shimazaki, Hiroko; Nakagawa, Tomomi; Otomo, Yuki; Kabe, Yasuaki; Suematsu, Makoto; Narimatsu, Hisashi; Takeuchi, Tsutomu

2016-05-21

Nearly all secreted proteins are glycosylated, and serum glycoproteins that exhibit disease-associated glycosylation changes have potential to be biomarkers. In rheumatoid arthritis (RA), C-reactive protein (CRP), and matrix metalloproteinase-3 (MMP-3) are widely used as serologic biomarkers, but they lack sufficient specificity or precision. We performed comparative glycosylation profiling of MMP-3 using a recently developed antibody-overlay lectin microarray technology that allows semicomprehensive and quantitative analysis of specific protein glycosylation to develop an RA-specific disease activity biomarker. Serum was taken from patients with RA (n = 24) whose disease activity was scored using composite measures, and MMP-3 was immunoprecipitated and subjected to lectin microarray analysis. A disease activity index (DAI) based on lectin signal was developed and validated using another cohort (n = 60). Synovial fluid MMP-3 in patients with RA and patients with osteoarthritis (OA) was also analyzed. Intense signals were observed on a sialic acid-binding lectin (Agrocybe cylindracea galectin [ACG]) and O-glycan-binding lectins (Jacalin, Agaricus bisporus agglutinin [ABA], and Amaranthus caudatus agglutinin [ACA]) by applying subnanogram levels of serum MMP-3. ACG, ABA, and ACA revealed differences in MMP-3 quantity, and Jacalin revealed differences in MMP-3 quality. The resultant index, ACG/Jacalin, correlated well with disease activity. Further validation using another cohort confirmed that this index correlated well with several DAIs and their components, and reflected DAI changes following RA treatment, with correlations greater than those for MMP-3 and CRP. Furthermore, MMP-3, which generated a high ACG/Jacalin score, accumulated in synovial fluid of patients with RA but not in that of patients with OA. Sialidase digestion revealed that the difference in quality was derived from O-glycan α-2,6-sialylation. This is the first report of a glycoprotein biomarker using glycan change at a local lesion to assess disease activity in autoimmune diseases. Differences in the degree of serum MMP-3 α-2,6-sialylation may be a useful index for estimating disease activity.

Application of targeted quantitative proteomics analysis in human cerebrospinal fluid using a liquid chromatography matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (LC MALDI TOF/TOF) platform.

PubMed

Pan, Sheng; Rush, John; Peskind, Elaine R; Galasko, Douglas; Chung, Kathryn; Quinn, Joseph; Jankovic, Joseph; Leverenz, James B; Zabetian, Cyrus; Pan, Catherine; Wang, Yan; Oh, Jung Hun; Gao, Jean; Zhang, Jianpeng; Montine, Thomas; Zhang, Jing

2008-02-01

Targeted quantitative proteomics by mass spectrometry aims to selectively detect one or a panel of peptides/proteins in a complex sample and is particularly appealing for novel biomarker verification/validation because it does not require specific antibodies. Here, we demonstrated the application of targeted quantitative proteomics in searching, identifying, and quantifying selected peptides in human cerebrospinal spinal fluid (CSF) using a matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (MALDI TOF/TOF)-based platform. The approach involved two major components: the use of isotopic-labeled synthetic peptides as references for targeted identification and quantification and a highly selective mass spectrometric analysis based on the unique characteristics of the MALDI instrument. The platform provides high confidence for targeted peptide detection in a complex system and can potentially be developed into a high-throughput system. Using the liquid chromatography (LC) MALDI TOF/TOF platform and the complementary identification strategy, we were able to selectively identify and quantify a panel of targeted peptides in the whole proteome of CSF without prior depletion of abundant proteins. The effectiveness and robustness of the approach associated with different sample complexity, sample preparation strategies, as well as mass spectrometric quantification were evaluated. Other issues related to chromatography separation and the feasibility for high-throughput analysis were also discussed. Finally, we applied targeted quantitative proteomics to analyze a subset of previously identified candidate markers in CSF samples of patients with Parkinson's disease (PD) at different stages and Alzheimer's disease (AD) along with normal controls.

Development of a Multiplexed Liquid Chromatography Multiple-Reaction-Monitoring Mass Spectrometry (LC-MRM/MS) Method for Evaluation of Salivary Proteins as Oral Cancer Biomarkers.

PubMed

Chen, Yi-Ting; Chen, Hsiao-Wei; Wu, Chun-Feng; Chu, Lichieh Julie; Chiang, Wei-Fang; Wu, Chih-Ching; Yu, Jau-Song; Tsai, Cheng-Han; Liang, Kung-Hao; Chang, Yu-Sun; Wu, Maureen; Ou Yang, Wei-Ting

2017-05-01

Multiple (selected) reaction monitoring (MRM/SRM) of peptides is a growing technology for target protein quantification because it is more robust, precise, accurate, high-throughput, and multiplex-capable than antibody-based techniques. The technique has been applied clinically to the large-scale quantification of multiple target proteins in different types of fluids. However, previous MRM-based studies have placed less focus on sample-preparation workflow and analytical performance in the precise quantification of proteins in saliva, a noninvasively sampled body fluid. In this study, we evaluated the analytical performance of a simple and robust multiple reaction monitoring (MRM)-based targeted proteomics approach incorporating liquid chromatography with mass spectrometry detection (LC-MRM/MS). This platform was used to quantitatively assess the biomarker potential of a group of 56 salivary proteins that have previously been associated with human cancers. To further enhance the development of this technology for assay of salivary samples, we optimized the workflow for salivary protein digestion and evaluated quantification performance, robustness and technical limitations in analyzing clinical samples. Using a clinically well-characterized cohort of two independent clinical sample sets (total n = 119), we quantitatively characterized these protein biomarker candidates in saliva specimens from controls and oral squamous cell carcinoma (OSCC) patients. The results clearly showed a significant elevation of most targeted proteins in saliva samples from OSCC patients compared with controls. Overall, this platform was capable of assaying the most highly multiplexed panel of salivary protein biomarkers, highlighting the clinical utility of MRM in oral cancer biomarker research. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

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 practical data processing workflow for multi-OMICS projects.

PubMed

Kohl, Michael; Megger, Dominik A; Trippler, Martin; Meckel, Hagen; Ahrens, Maike; Bracht, Thilo; Weber, Frank; Hoffmann, Andreas-Claudius; Baba, Hideo A; Sitek, Barbara; Schlaak, Jörg F; Meyer, Helmut E; Stephan, Christian; Eisenacher, Martin

2014-01-01

Multi-OMICS approaches aim on the integration of quantitative data obtained for different biological molecules in order to understand their interrelation and the functioning of larger systems. This paper deals with several data integration and data processing issues that frequently occur within this context. To this end, the data processing workflow within the PROFILE project is presented, a multi-OMICS project that aims on identification of novel biomarkers and the development of new therapeutic targets for seven important liver diseases. Furthermore, a software called CrossPlatformCommander is sketched, which facilitates several steps of the proposed workflow in a semi-automatic manner. Application of the software is presented for the detection of novel biomarkers, their ranking and annotation with existing knowledge using the example of corresponding Transcriptomics and Proteomics data sets obtained from patients suffering from hepatocellular carcinoma. Additionally, a linear regression analysis of Transcriptomics vs. Proteomics data is presented and its performance assessed. It was shown, that for capturing profound relations between Transcriptomics and Proteomics data, a simple linear regression analysis is not sufficient and implementation and evaluation of alternative statistical approaches are needed. Additionally, the integration of multivariate variable selection and classification approaches is intended for further development of the software. Although this paper focuses only on the combination of data obtained from quantitative Proteomics and Transcriptomics experiments, several approaches and data integration steps are also applicable for other OMICS technologies. Keeping specific restrictions in mind the suggested workflow (or at least parts of it) may be used as a template for similar projects that make use of different high throughput techniques. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. Copyright © 2013 Elsevier B.V. All rights reserved.

Lipid biomarker analysis for the quantitative analysis of airborne microorganisms

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

Macnaughton, S.J.; Jenkins, T.L.; Cormier, M.R.

1997-08-01

There is an ever increasing concern regarding the presence of airborne microbial contaminants within indoor air environments. Exposure to such biocontaminants can give rise to large numbers of different health effects including infectious diseases, allergenic responses and respiratory problems, Biocontaminants typically round in indoor air environments include bacteria, fungi, algae, protozoa and dust mites. Mycotoxins, endotoxins, pollens and residues of organisms are also known to cause adverse health effects. A quantitative detection/identification technique independent of culturability that assays both culturable and non culturable biomass including endotoxin is critical in defining risks from indoor air biocontamination. Traditionally, methods employed for themore » monitoring of microorganism numbers in indoor air environments involve classical culture based techniques and/or direct microscopic counting. It has been repeatedly documented that viable microorganism counts only account for between 0.1-10% of the total community detectable by direct counting. The classic viable microbiologic approach doe`s not provide accurate estimates of microbial fragments or other indoor air components that can act as antigens and induce or potentiate allergic responses. Although bioaerosol samplers are designed to damage the microbes as little as possible, microbial stress has been shown to result from air sampling, aerosolization and microbial collection. Higher collection efficiency results in greater cell damage while less cell damage often results in lower collection efficiency. Filtration can collect particulates at almost 100% efficiency, but captured microorganisms may become dehydrated and damaged resulting in non-culturability, however, the lipid biomarker assays described herein do not rely on cell culture. Lipids are components that are universally distributed throughout cells providing a means to assess independent of culturability.« less

Quantitation of ortho-Cresyl Phosphate Adducts to Butyrylcholinesterase in Human Serum by Immunomagnetic-UHPLC-MS/MS

PubMed Central

Johnson, Darryl; Carter, Melissa D.; Crow, Brian S.; Isenberg, Samantha L.; Graham, Leigh Ann; Erol, H. Akin; Watson, Caroline M.; Pantazides, Brooke G.; van der Schans, Marcel J.; Langenberg, Jan P.; Noort, Daan; Blake, Thomas A.; Thomas, Jerry D.; Johnson, Rudolph C.

2017-01-01

Tri-ortho-cresyl phosphate (ToCP) is an anti-wear, flame retardant additive used in industrial lubricants, hydraulic fluids, and gasoline. The neurotoxic effects of ToCP arise from the liver-activated metabolite 2-(o-cresyl)-4H-1,3,2-benzodioxaphosphoran-2-one (cresyl saligenin phosphate or CBDP), which inhibits esterase enzymes including butyrylcholinesterase (BChE). Following BChE adduction, CBDP undergoes hydrolysis to form the aged adduct ortho-cresyl phosphoserine (oCP-BChE), thus providing a biomarker of CBDP exposure. Previous studies have identified ToCP in aircraft cabin and cockpit air, but assessing human exposure has been hampered by the lack of a laboratory assay to confirm exposure. This work presents the development of an immunomagnetic-UHPLC-MS/MS method for the quantitation of unadducted BChE and the long-term CBDP biomarker, oCP-BChE, in human serum. The method has a reportable range from 2.0 ng/mL to 150 ng/mL, which is consistent with the sensitivity of methods used to detect organophosphorus nerve agent protein adducts. The assay demonstrated high intraday and interday accuracy (≥ 85%) and precision (RSD ≤ 15%) across the calibration range. The method was developed for future analyses of potential human exposure to CBDP. Analysis of human serum inhibited in vitro with CBDP demonstrated that the oCP-BChE adduct was stable for at least 72 hours at 4, 22 and 37 °C. Compared to a previously reported assay, this method requires 75% less sample volume, reduces analysis time by a factor of 20, and demonstrates a 3-fold improvement in sensitivity. PMID:26149113

Diffusion MRI with Semi-Automated Segmentation Can Serve as a Restricted Predictive Biomarker of the Therapeutic Response of Liver Metastasis

PubMed Central

Stephen, Renu M.; Jha, Abhinav K.; Roe, Denise J.; Trouard, Theodore P.; Galons, Jean-Philippe; Kupinski, Matthew A.; Frey, Georgette; Cui, Haiyan; Squire, Scott; Pagel, Mark D.; Rodriguez, Jeffrey J.; Gillies, Robert J.; Stopeck, Alison T.

2015-01-01

Purpose To assess the value of semi-automated segmentation applied to diffusion MRI for predicting the therapeutic response of liver metastasis. Methods Conventional diffusion weighted magnetic resonance imaging (MRI) was performed using b-values of 0, 150, 300 and 450 s/mm2 at baseline and days 4, 11 and 39 following initiation of a new chemotherapy regimen in a pilot study with 18 women with 37 liver metastases from primary breast cancer. A semi-automated segmentation approach was used to identify liver metastases. Linear regression analysis was used to assess the relationship between baseline values of the apparent diffusion coefficient (ADC) and change in tumor size by day 39. Results A semi-automated segmentation scheme was critical for obtaining the most reliable ADC measurements. A statistically significant relationship between baseline ADC values and change in tumor size at day 39 was observed for minimally treated patients with metastatic liver lesions measuring 2–5 cm in size (p = 0.002), but not for heavily treated patients with the same tumor size range (p = 0.29), or for tumors of smaller or larger sizes. ROC analysis identified a baseline threshold ADC value of 1.33 μm2/ms as 75% sensitive and 83% specific for identifying non-responding metastases in minimally treated patients with 2–5 cm liver lesions. Conclusion Quantitative imaging can substantially benefit from a semi-automated segmentation scheme. Quantitative diffusion MRI results can be predictive of therapeutic outcome in selected patients with liver metastases, but not for all liver metastases, and therefore should be considered to be a restricted biomarker. PMID:26284600

A Molecular Clock Infers Heterogeneous Tissue Age Among Patients with Barrett’s Esophagus

PubMed Central

Wong, Chao-Jen; Hazelton, William D.; Kaz, Andrew M.; Willis, Joseph E.; Grady, William M.; Luebeck, E. Georg

2016-01-01

Biomarkers that drift differentially with age between normal and premalignant tissues, such as Barrett’s esophagus (BE), have the potential to improve the assessment of a patient’s cancer risk by providing quantitative information about how long a patient has lived with the precursor (i.e., dwell time). In the case of BE, which is a metaplastic precursor to esophageal adenocarcinoma (EAC), such biomarkers would be particularly useful because EAC risk may change with BE dwell time and it is generally not known how long a patient has lived with BE when a patient is first diagnosed with this condition. In this study we first describe a statistical analysis of DNA methylation data (both cross-sectional and longitudinal) derived from tissue samples from 50 BE patients to identify and validate a set of 67 CpG dinucleotides in 51 CpG islands that undergo age-related methylomic drift. Next, we describe how this information can be used to estimate a patient’s BE dwell time. We introduce a Bayesian model that incorporates longitudinal methylomic drift rates, patient age, and methylation data from individually paired BE and normal squamous tissue samples to estimate patient-specific BE onset times. Our application of the model to 30 sporadic BE patients’ methylomic profiles first exposes a wide heterogeneity in patient-specific BE onset times. Furthermore, independent application of this method to a cohort of 22 familial BE (FBE) patients reveals significantly earlier mean BE onset times. Our analysis supports the conjecture that differential methylomic drift occurs in BE (relative to normal squamous tissue) and hence allows quantitative estimation of the time that a BE patient has lived with BE. PMID:27168458

Diffusion MRI with Semi-Automated Segmentation Can Serve as a Restricted Predictive Biomarker of the Therapeutic Response of Liver Metastasis.

PubMed

Stephen, Renu M; Jha, Abhinav K; Roe, Denise J; Trouard, Theodore P; Galons, Jean-Philippe; Kupinski, Matthew A; Frey, Georgette; Cui, Haiyan; Squire, Scott; Pagel, Mark D; Rodriguez, Jeffrey J; Gillies, Robert J; Stopeck, Alison T

2015-12-01

To assess the value of semi-automated segmentation applied to diffusion MRI for predicting the therapeutic response of liver metastasis. Conventional diffusion weighted magnetic resonance imaging (MRI) was performed using b-values of 0, 150, 300 and 450s/mm(2) at baseline and days 4, 11 and 39 following initiation of a new chemotherapy regimen in a pilot study with 18 women with 37 liver metastases from primary breast cancer. A semi-automated segmentation approach was used to identify liver metastases. Linear regression analysis was used to assess the relationship between baseline values of the apparent diffusion coefficient (ADC) and change in tumor size by day 39. A semi-automated segmentation scheme was critical for obtaining the most reliable ADC measurements. A statistically significant relationship between baseline ADC values and change in tumor size at day 39 was observed for minimally treated patients with metastatic liver lesions measuring 2-5cm in size (p=0.002), but not for heavily treated patients with the same tumor size range (p=0.29), or for tumors of smaller or larger sizes. ROC analysis identified a baseline threshold ADC value of 1.33μm(2)/ms as 75% sensitive and 83% specific for identifying non-responding metastases in minimally treated patients with 2-5cm liver lesions. Quantitative imaging can substantially benefit from a semi-automated segmentation scheme. Quantitative diffusion MRI results can be predictive of therapeutic outcome in selected patients with liver metastases, but not for all liver metastases, and therefore should be considered to be a restricted biomarker. Copyright © 2015 Elsevier Inc. All rights reserved.

Quantitative proteomics of bronchoalveolar lavage fluid in lung adenocarcinoma.

PubMed

Almatroodi, Saleh A; McDonald, Christine F; Collins, Allison L; Darby, Ian A; Pouniotis, Dodie S

2015-01-01

The most commonly reported primary lung cancer subtype is adenocarcinoma, which is associated with a poor prognosis and short survival. Proteomic studies on human body fluids such as bronchoalveolar lavage fluid (BALF) have become essential methods for biomarker discovery, examination of tumor pathways and investigation of potential treatments. This study used quantitative proteomics to investigate the up-regulation of novel proteins in BALF from patients with primary lung adenocarcinoma in order to identify potential biomarkers. BALF samples from individuals with and without primary lung adenocarcinoma were analyzed using liquid chromatography-mass spectrometry. One thousand and one hundred proteins were identified, 33 of which were found to be consistently overexpressed in all lung adenocarcinoma samples compared to non-cancer controls. A number of overexpressed proteins have been previously shown to be related to lung cancer progression including S100-A8, annexin A1, annexin A2, thymidine phosphorylase and transglutaminase 2. The overexpression of a number of specific proteins in BALF from patients with primary lung adenocarcinoma may be used as a potential biomarker for lung adenocarcinoma. Copyright© 2015, International Institute of Anticancer Research (Dr. John G. Delinasios), All rights reserved.

Bayesian modeling and inference for diagnostic accuracy and probability of disease based on multiple diagnostic biomarkers with and without a perfect reference standard.

PubMed

Jafarzadeh, S Reza; Johnson, Wesley O; Gardner, Ian A

2016-03-15

The area under the receiver operating characteristic (ROC) curve (AUC) is used as a performance metric for quantitative tests. Although multiple biomarkers may be available for diagnostic or screening purposes, diagnostic accuracy is often assessed individually rather than in combination. In this paper, we consider the interesting problem of combining multiple biomarkers for use in a single diagnostic criterion with the goal of improving the diagnostic accuracy above that of an individual biomarker. The diagnostic criterion created from multiple biomarkers is based on the predictive probability of disease, conditional on given multiple biomarker outcomes. If the computed predictive probability exceeds a specified cutoff, the corresponding subject is allocated as 'diseased'. This defines a standard diagnostic criterion that has its own ROC curve, namely, the combined ROC (cROC). The AUC metric for cROC, namely, the combined AUC (cAUC), is used to compare the predictive criterion based on multiple biomarkers to one based on fewer biomarkers. A multivariate random-effects model is proposed for modeling multiple normally distributed dependent scores. Bayesian methods for estimating ROC curves and corresponding (marginal) AUCs are developed when a perfect reference standard is not available. In addition, cAUCs are computed to compare the accuracy of different combinations of biomarkers for diagnosis. The methods are evaluated using simulations and are applied to data for Johne's disease (paratuberculosis) in cattle. Copyright © 2015 John Wiley & Sons, Ltd.

Development of a comprehensive analytical platform for the detection and quantitation of food fraud using a biomarker approach. The oregano adulteration case study.

PubMed

Wielogorska, Ewa; Chevallier, Olivier; Black, Connor; Galvin-King, Pamela; Delêtre, Marc; Kelleher, Colin T; Haughey, Simon A; Elliott, Christopher T

2018-01-15

Due to increasing number of food fraud incidents, there is an inherent need for the development and implementation of analytical platforms enabling detection and quantitation of adulteration. In this study a set of unique biomarkers of commonly found oregano adulterants became the targets in the development of a LC-MS/MS method which underwent a rigorous in-house validation. The method presented very high selectivity and specificity, excellent linearity (R 2 >0.988) low decision limits and detection capabilities (<2%), acceptable accuracy (intra-assay 92-113%, inter-assay 69-138%) and precision (CV<20%). The method was compared with an established FTIR screening assay and revealed a good correlation of quali- and quantitative results (R 2 >0.81). An assessment of 54 suspected adulterated oregano samples revealed that almost 90% of them contained at least one bulking agent, with a median level of adulteration of 50%. Such innovative methodologies need to be established as routine testing procedures to detect and ultimately deter food fraud. Copyright © 2017 Elsevier Ltd. All rights reserved.

Integration analysis of quantitative proteomics and transcriptomics data identifies potential targets of frizzled-8 protein-related antiproliferative factor in vivo.

PubMed

Yang, Wei; Kim, Yongsoo; Kim, Taek-Kyun; Keay, Susan K; Kim, Kwang Pyo; Steen, Hanno; Freeman, Michael R; Hwang, Daehee; Kim, Jayoung

2012-12-01

What's known on the subject? and What does the study add? Interstitial cystitis (IC) is a prevalent and debilitating pelvic disorder generally accompanied by chronic pain combined with chronic urinating problems. Over one million Americans are affected, especially middle-aged women. However, its aetiology or mechanism remains unclear. No efficient drug has been provided to patients. Several urinary biomarker candidates have been identified for IC; among the most promising is antiproliferative factor (APF), whose biological activity is detectable in urine specimens from >94% of patients with both ulcerative and non-ulcerative IC. The present study identified several important mediators of the effect of APF on bladder cell physiology, suggesting several candidate drug targets against IC. In an attempt to identify potential proteins and genes regulated by APF in vivo, and to possibly expand the APF-regulated network identified by stable isotope labelling by amino acids in cell culture (SILAC), we performed an integration analysis of our own SILAC data and the microarray data of Gamper et al. (2009) BMC Genomics 10: 199. Notably, two of the proteins (i.e. MAPKSP1 and GSPT1) that are down-regulated by APF are involved in the activation of mTORC1, suggesting that the mammalian target of rapamycin (mTOR) pathway is potentially a critical pathway regulated by APF in vivo. Several components of the mTOR pathway are currently being studied as potential therapeutic targets in other diseases. Our analysis suggests that this pathway might also be relevant in the design of diagnostic tools and medications targeting IC. • To enhance our understanding of the interstitial cystitis urine biomarker antiproliferative factor (APF), as well as interstitial cystitis biology more generally at the systems level, we reanalyzed recently published large-scale quantitative proteomics and in vivo transcriptomics data sets using an integration analysis tool that we have developed. • To identify more differentially expressed genes with a lower false discovery rate from a previously published microarray data set, an integrative hypothesis-testing statistical approach was applied. • For validation experiments, expression and phosphorylation levels of select proteins were evaluated by western blotting. • Integration analysis of this transcriptomics data set with our own quantitative proteomics data set identified 10 genes that are potentially regulated by APF in vivo from 4140 differentially expressed genes identified with a false discovery rate of 1%. • Of these, five (i.e. JUP, MAPKSP1, GSPT1, PTGS2/COX-2 and XPOT) were found to be prominent after network modelling of the common genes identified in the proteomics and microarray studies. • This molecular signature reflects the biological processes of cell adhesion, cell proliferation and inflammation, which is consistent with the known physiological effects of APF. • Lastly, we found the mammalian target of rapamycin pathway was down-regulated in response to APF. • This unbiased integration analysis of in vitro quantitative proteomics data with in vivo quantitative transcriptomics data led to the identification of potential downstream mediators of the APF signal transduction pathway. © 2012 THE AUTHORS. BJU INTERNATIONAL © 2012 BJU INTERNATIONAL.

Analysis of Biomarker Utility using a PBPK Model for Carbaryl

EPA Science Inventory

There are many types of biomarkers; the two common ones are biomarkers of exposure and biomarkers of effect. The utility of a biomarker for estimating exposures or predicting risks depends on the strength of the correlation between biomarker concentrations and exposure/effects. I...

Systematic assessment of survey scan and MS2-based abundance strategies for label-free quantitative proteomics using high-resolution MS data.

PubMed

Tu, Chengjian; Li, Jun; Sheng, Quanhu; Zhang, Ming; Qu, Jun

2014-04-04

Survey-scan-based label-free method have shown no compelling benefit over fragment ion (MS2)-based approaches when low-resolution mass spectrometry (MS) was used, the growing prevalence of high-resolution analyzers may have changed the game. This necessitates an updated, comparative investigation of these approaches for data acquired by high-resolution MS. Here, we compared survey scan-based (ion current, IC) and MS2-based abundance features including spectral-count (SpC) and MS2 total-ion-current (MS2-TIC), for quantitative analysis using various high-resolution LC/MS data sets. Key discoveries include: (i) study with seven different biological data sets revealed only IC achieved high reproducibility for lower-abundance proteins; (ii) evaluation with 5-replicate analyses of a yeast sample showed IC provided much higher quantitative precision and lower missing data; (iii) IC, SpC, and MS2-TIC all showed good quantitative linearity (R(2) > 0.99) over a >1000-fold concentration range; (iv) both MS2-TIC and IC showed good linear response to various protein loading amounts but not SpC; (v) quantification using a well-characterized CPTAC data set showed that IC exhibited markedly higher quantitative accuracy, higher sensitivity, and lower false-positives/false-negatives than both SpC and MS2-TIC. Therefore, IC achieved an overall superior performance than the MS2-based strategies in terms of reproducibility, missing data, quantitative dynamic range, quantitative accuracy, and biomarker discovery.

Systematic Assessment of Survey Scan and MS2-Based Abundance Strategies for Label-Free Quantitative Proteomics Using High-Resolution MS Data

PubMed Central

2015-01-01

Survey-scan-based label-free method have shown no compelling benefit over fragment ion (MS2)-based approaches when low-resolution mass spectrometry (MS) was used, the growing prevalence of high-resolution analyzers may have changed the game. This necessitates an updated, comparative investigation of these approaches for data acquired by high-resolution MS. Here, we compared survey scan-based (ion current, IC) and MS2-based abundance features including spectral-count (SpC) and MS2 total-ion-current (MS2-TIC), for quantitative analysis using various high-resolution LC/MS data sets. Key discoveries include: (i) study with seven different biological data sets revealed only IC achieved high reproducibility for lower-abundance proteins; (ii) evaluation with 5-replicate analyses of a yeast sample showed IC provided much higher quantitative precision and lower missing data; (iii) IC, SpC, and MS2-TIC all showed good quantitative linearity (R2 > 0.99) over a >1000-fold concentration range; (iv) both MS2-TIC and IC showed good linear response to various protein loading amounts but not SpC; (v) quantification using a well-characterized CPTAC data set showed that IC exhibited markedly higher quantitative accuracy, higher sensitivity, and lower false-positives/false-negatives than both SpC and MS2-TIC. Therefore, IC achieved an overall superior performance than the MS2-based strategies in terms of reproducibility, missing data, quantitative dynamic range, quantitative accuracy, and biomarker discovery. PMID:24635752

High-throughput simultaneous analysis of RNA, protein, and lipid biomarkers in heterogeneous tissue samples.

PubMed

Reiser, Vladimír; Smith, Ryan C; Xue, Jiyan; Kurtz, Marc M; Liu, Rong; Legrand, Cheryl; He, Xuanmin; Yu, Xiang; Wong, Peggy; Hinchcliffe, John S; Tanen, Michael R; Lazar, Gloria; Zieba, Renata; Ichetovkin, Marina; Chen, Zhu; O'Neill, Edward A; Tanaka, Wesley K; Marton, Matthew J; Liao, Jason; Morris, Mark; Hailman, Eric; Tokiwa, George Y; Plump, Andrew S

2011-11-01

With expanding biomarker discovery efforts and increasing costs of drug development, it is critical to maximize the value of mass-limited clinical samples. The main limitation of available methods is the inability to isolate and analyze, from a single sample, molecules requiring incompatible extraction methods. Thus, we developed a novel semiautomated method for tissue processing and tissue milling and division (TMAD). We used a SilverHawk atherectomy catheter to collect atherosclerotic plaques from patients requiring peripheral atherectomy. Tissue preservation by flash freezing was compared with immersion in RNAlater®, and tissue grinding by traditional mortar and pestle was compared with TMAD. Comparators were protein, RNA, and lipid yield and quality. Reproducibility of analyte yield from aliquots of the same tissue sample processed by TMAD was also measured. The quantity and quality of biomarkers extracted from tissue prepared by TMAD was at least as good as that extracted from tissue stored and prepared by traditional means. TMAD enabled parallel analysis of gene expression (quantitative reverse-transcription PCR, microarray), protein composition (ELISA), and lipid content (biochemical assay) from as little as 20 mg of tissue. The mean correlation was r = 0.97 in molecular composition (RNA, protein, or lipid) between aliquots of individual samples generated by TMAD. We also demonstrated that it is feasible to use TMAD in a large-scale clinical study setting. The TMAD methodology described here enables semiautomated, high-throughput sampling of small amounts of heterogeneous tissue specimens by multiple analytical techniques with generally improved quality of recovered biomolecules.

Nanoporous Glass Integrated in Volumetric Bar-Chart Chip for Point-of-Care Diagnostics of Non-Small Cell Lung Cancer.

PubMed

Li, Ying; Xuan, Jie; Song, Yujun; Qi, Wenjin; He, Bangshun; Wang, Ping; Qin, Lidong

2016-01-26

Point-of-care (POC) testing has the potential to enable rapid, low-cost, and large-scale screening. POC detection of a multiplexed biomarker panel can facilitate the early diagnosis of non-small cell lung cancer (NSCLC) and, thus, may allow for more timely surgical intervention for life-saving treatment. Herein, we report the nanoporous glass (NPG) integrated volumetric bar-chart chip (V-Chip) for POC detection of the three NSCLC biomarkers CEA, CYFRA 21-1, and SCCA, by the naked eye. The 3D nanostructures in the NPG membrane efficiently increase the number of binding sites for antibodies and decrease the diffusion distance between antibody and antigen, enabling the low detection limit and rapid analysis time of the NPG-V-Chip. We utilized the NPG-V-Chip to test the NSCLC biomarker panel and found that the limit of detection can reach 50 pg/mL (10-fold improvement over the original V-Chip), and the total assay time can be decreased from 4 to 0.5 h. We then detected CEA in 21 serum samples from patients with common cancers, and the on-chip results showed good correlation with the clinical results. We further assayed 10 lung cancer samples using the device and confirmed the results obtained using conventional ELISA methods. In summary, the NPG-V-Chip platform has the ability of multiplex, low detection limit, low cost, lack of need for accessory equipment, and rapid analysis time, which may render the V-Chip a useful platform for quantitative POC detection in resource-limited settings and personalized diagnostics.

Comprehensive Quantitative Analysis of Ovarian and Breast Cancer Tumor Peptidomes

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

Xu, Zhe; Wu, Chaochao; Xie, Fang

Aberrant degradation of proteins is associated with many pathological states, including cancers. Mass spectrometric analysis of tumor peptidomes, the intracellular and intercellular products of protein degradation, has the potential to provide biological insights on proteolytic processing in cancer. However, attempts to use the information on these smaller protein degradation products from tumors for biomarker discovery and cancer biology studies have been fairly limited to date, largely due to the lack of effective approaches for robust peptidomics identification and quantification, and the prevalence of confounding factors and biases associated with sample handling and processing. Herein, we have developed an effective andmore » robust analytical platform for comprehensive analyses of tissue peptidomes, and which is suitable for high throughput quantitative studies. The reproducibility and coverage of the platform, as well as the suitability of clinical ovarian tumor and patient-derived breast tumor xenograft samples with post-excision delay of up to 60 min before freezing for peptidomics analysis, have been demonstrated. Additionally, our data also show that the peptidomics profiles can effectively separate breast cancer subtypes, reflecting tumor-associated protease activities. In conclusion, peptidomics complements results obtainable from conventional bottom-up proteomics, and provides insights not readily obtainable from such approaches.« less

Comprehensive Quantitative Analysis of Ovarian and Breast Cancer Tumor Peptidomes

DOE PAGES

Xu, Zhe; Wu, Chaochao; Xie, Fang; ...

2014-10-28

Aberrant degradation of proteins is associated with many pathological states, including cancers. Mass spectrometric analysis of tumor peptidomes, the intracellular and intercellular products of protein degradation, has the potential to provide biological insights on proteolytic processing in cancer. However, attempts to use the information on these smaller protein degradation products from tumors for biomarker discovery and cancer biology studies have been fairly limited to date, largely due to the lack of effective approaches for robust peptidomics identification and quantification, and the prevalence of confounding factors and biases associated with sample handling and processing. Herein, we have developed an effective andmore » robust analytical platform for comprehensive analyses of tissue peptidomes, and which is suitable for high throughput quantitative studies. The reproducibility and coverage of the platform, as well as the suitability of clinical ovarian tumor and patient-derived breast tumor xenograft samples with post-excision delay of up to 60 min before freezing for peptidomics analysis, have been demonstrated. Additionally, our data also show that the peptidomics profiles can effectively separate breast cancer subtypes, reflecting tumor-associated protease activities. In conclusion, peptidomics complements results obtainable from conventional bottom-up proteomics, and provides insights not readily obtainable from such approaches.« less

Eu3+ functionalized Sc-MOFs: Turn-on fluorescent switch for ppb-level biomarker of plastic pollutant polystyrene in serum and urine and on-site detection by smartphone.

PubMed

Lian, Xiao; Miao, Tifang; Xu, Xiaoyu; Zhang, Chi; Yan, Bing

2017-11-15

The harm of plastic pollutants for human and environment is being paid more and more attention. Polystyrene (PS) and styrene are toxic compounds used in large quantities in the production of fiberglass reinforced polyesters. In this work, a simple method was designed for independent detecting polystyrene and styrene biomarker (phenylglyoxylic acid, PGA) in serum and urine. We prepared Eu3+ functionalized Sc-based metal-organic frameworks as turn-on fluorescent switch for PGA. The distinct enhanced luminescence is observed from the Eu@MOFs with addition of PGA. The fabricated fluorescent switch has several appealing features including high sensitivity (LOD = 4.16 ppb), quick response time (less than 5s) and broad linear range (0.02mg/mL to 0.5mg/mL). Furthermore, Eu@MOFs exhibits excellent selectivity that it is not affected by congeneric biomarkers. More interestingly, a paper-based probe has been devised. The paper-based fluorescence probe would perform an obvious fluorescence change from navy to red with the variety of PGA content. The practicability of the on-site detection platform for quantitative analysis using a colour scanning APP in smartphone has been also demonstrated by coupled with our proposed paper based fluorescence probe. This work first provides a fast, accurate and sensitive method for independent monitoring PS biomarker PGA, and the paper-based probe exhibit a new idea for design portable and easy to operate sensing devices combine with smartphone. Copyright © 2017 Elsevier B.V. All rights reserved.

GeLC-MRM quantitation of mutant KRAS oncoprotein in complex biological samples.

PubMed

Halvey, Patrick J; Ferrone, Cristina R; Liebler, Daniel C

2012-07-06

Tumor-derived mutant KRAS (v-Ki-ras-2 Kirsten rat sarcoma viral oncogene) oncoprotein is a critical driver of cancer phenotypes and a potential biomarker for many epithelial cancers. Targeted mass spectrometry analysis by multiple reaction monitoring (MRM) enables selective detection and quantitation of wild-type and mutant KRAS proteins in complex biological samples. A recently described immunoprecipitation approach (Proc. Nat. Acad. Sci.2011, 108, 2444-2449) can be used to enrich KRAS for MRM analysis, but requires large protein inputs (2-4 mg). Here, we describe sodium dodecyl sulfate-polyacrylamide gel electrophoresis-based enrichment of KRAS in a low molecular weight (20-25 kDa) protein fraction prior to MRM analysis (GeLC-MRM). This approach reduces background proteome complexity, thus, allowing mutant KRAS to be reliably quantified in low protein inputs (5-50 μg). GeLC-MRM detected KRAS mutant variants (G12D, G13D, G12V, G12S) in a panel of cancer cell lines. GeLC-MRM analysis of wild-type and mutant was linear with respect to protein input and showed low variability across process replicates (CV = 14%). Concomitant analysis of a peptide from the highly similar HRAS and NRAS proteins enabled correction of KRAS-targeted measurements for contributions from these other proteins. KRAS peptides were also quantified in fluid from benign pancreatic cysts and pancreatic cancers at concentrations from 0.08 to 1.1 fmol/μg protein. GeLC-MRM provides a robust, sensitive approach to quantitation of mutant proteins in complex biological samples.

Accurate inclusion mass screening: a bridge from unbiased discovery to targeted assay development for biomarker verification.

PubMed

Jaffe, Jacob D; Keshishian, Hasmik; Chang, Betty; Addona, Theresa A; Gillette, Michael A; Carr, Steven A

2008-10-01

Verification of candidate biomarker proteins in blood is typically done using multiple reaction monitoring (MRM) of peptides by LC-MS/MS on triple quadrupole MS systems. MRM assay development for each protein requires significant time and cost, much of which is likely to be of little value if the candidate biomarker is below the detection limit in blood or a false positive in the original discovery data. Here we present a new technology, accurate inclusion mass screening (AIMS), designed to provide a bridge from unbiased discovery to MS-based targeted assay development. Masses on the software inclusion list are monitored in each scan on the Orbitrap MS system, and MS/MS spectra for sequence confirmation are acquired only when a peptide from the list is detected with both the correct accurate mass and charge state. The AIMS experiment confirms that a given peptide (and thus the protein from which it is derived) is present in the plasma. Throughput of the method is sufficient to qualify up to a hundred proteins/week. The sensitivity of AIMS is similar to MRM on a triple quadrupole MS system using optimized sample preparation methods (low tens of ng/ml in plasma), and MS/MS data from the AIMS experiments on the Orbitrap can be directly used to configure MRM assays. The method was shown to be at least 4-fold more efficient at detecting peptides of interest than undirected LC-MS/MS experiments using the same instrumentation, and relative quantitation information can be obtained by AIMS in case versus control experiments. Detection by AIMS ensures that a quantitative MRM-based assay can be configured for that protein. The method has the potential to qualify large number of biomarker candidates based on their detection in plasma prior to committing to the time- and resource-intensive steps of establishing a quantitative assay.

Novel MRI-derived quantitative biomarker for cardiac function applied to classifying ischemic cardiomyopathy within a Bayesian rule learning framework

NASA Astrophysics Data System (ADS)

Menon, Prahlad G.; Morris, Lailonny; Staines, Mara; Lima, Joao; Lee, Daniel C.; Gopalakrishnan, Vanathi

2014-03-01

Characterization of regional left ventricular (LV) function may have application in prognosticating timely response and informing choice therapy in patients with ischemic cardiomyopathy. The purpose of this study is to characterize LV function through a systematic analysis of 4D (3D + time) endocardial motion over the cardiac cycle in an effort to define objective, clinically useful metrics of pathological remodeling and declining cardiac performance, using standard cardiac MRI data for two distinct patient cohorts accessed from CardiacAtlas.org: a) MESA - a cohort of asymptomatic patients; and b) DETERMINE - a cohort of symptomatic patients with a history of ischemic heart disease (IHD) or myocardial infarction. The LV endocardium was segmented and a signed phase-to-phase Hausdorff distance (HD) was computed at 3D uniformly spaced points tracked on segmented endocardial surface contours, over the cardiac cycle. An LV-averaged index of phase-to-phase endocardial displacement (P2PD) time-histories was computed at each tracked point, using the HD computed between consecutive cardiac phases. Average and standard deviation in P2PD over the cardiac cycle was used to prepare characteristic curves for the asymptomatic and IHD cohort. A novel biomarker of RMS error between mean patient-specific characteristic P2PD over the cardiac cycle for each individual patient and the cumulative P2PD characteristic of a cohort of asymptomatic patients was established as the RMS-P2PD marker. The novel RMS-P2PD marker was tested as a cardiac function based feature for automatic patient classification using a Bayesian Rule Learning (BRL) framework. The RMS-P2PD biomarker indices were significantly different for the symptomatic patient and asymptomatic control cohorts (p<0.001). BRL accurately classified 83.8% of patients correctly from the patient and control populations, with leave-one-out cross validation, using standard indices of LV ejection fraction (LV-EF) and LV end-systolic volume index (LV-ESVI). This improved to 91.9% with inclusion of the RMS-P2PD biomarker and was congruent with improvements in both sensitivity for classifying patients and specificity for identifying asymptomatic controls from 82.6% up to 95.7%. RMS-P2PD, when contrasted against a collective normal reference, is a promising biomarker to investigate further in its utility for identifying quantitative signs of pathological endocardial function which may boost standard image makers as precursors of declining cardiac performance.