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Chase Huizar C, Raphael I, Forsthuber TG. Genomic, proteomic, and systems biology approaches in biomarker discovery for multiple sclerosis. Cell Immunol 2020; 358:104219. [PMID: 33039896 PMCID: PMC7927152 DOI: 10.1016/j.cellimm.2020.104219] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 09/13/2020] [Accepted: 09/16/2020] [Indexed: 12/12/2022]
Abstract
Multiple sclerosis (MS) is a neuroinflammatory disorder characterized by autoimmune-mediated inflammatory lesions in CNS leading to myelin damage and axonal loss. MS is a heterogenous disease with variable and unpredictable disease course. Due to its complex nature, MS is difficult to diagnose and responses to specific treatments may vary between individuals. Therefore, there is an indisputable need for biomarkers for early diagnosis, prediction of disease exacerbations, monitoring the progression of disease, and for measuring responses to therapy. Genomic and proteomic studies have sought to understand the molecular basis of MS and find biomarker candidates. Advances in next-generation sequencing and mass-spectrometry techniques have yielded an unprecedented amount of genomic and proteomic data; yet, translation of the results into the clinic has been underwhelming. This has prompted the development of novel data science techniques for exploring these large datasets to identify biologically relevant relationships and ultimately point towards useful biomarkers. Herein we discuss optimization of omics study designs, advances in the generation of omics data, and systems biology approaches aimed at improving biomarker discovery and translation to the clinic for MS.
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Affiliation(s)
- Carol Chase Huizar
- Department of Biology, University of Texas at San Antonio, San Antonio, TX, USA
| | - Itay Raphael
- Department of Neurological Surgery, University of Pittsburgh, UPMC Children's Hospital, Pittsburgh, PA, USA.
| | - Thomas G Forsthuber
- Department of Biology, University of Texas at San Antonio, San Antonio, TX, USA.
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2
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Zhou LT, Lv LL, Liu BC. Urinary Biomarkers of Renal Fibrosis. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1165:607-623. [PMID: 31399987 DOI: 10.1007/978-981-13-8871-2_30] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Renal fibrosis is the common pathological pathway of progressive CKD. The commonly used biomarkers in clinical practice are not optimal to detect injury or predict prognosis. Therefore, it is crucial to develop novel biomarkers to allow prompt intervention. Urine serves as a valuable resource of biomarker discovery for kidney diseases. Owing to the rapid development of omics platforms and bioinformatics, research on novel urinary biomarkers for renal fibrosis has proliferated in recent years. In this chapter, we discuss the current status and provide basic knowledge in this field. We present novel promising biomarkers including tubular injury markers, proteins related to activated inflammation/fibrosis pathways, CKD273, transcriptomic biomarkers, as well as metabolomic biomarkers. Furthermore, considering the complex nature of the pathogenesis of renal fibrosis, we also highlight the combination of biomarkers to further improve the diagnostic and prognostic performance.
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Affiliation(s)
- Le-Ting Zhou
- Institute of Nephrology, Zhong Da Hospital, Southeast University School of Medicine, DingJiaQiao Road, Nanjing, China
| | - Lin-Li Lv
- Institute of Nephrology, Zhong Da Hospital, Southeast University School of Medicine, DingJiaQiao Road, Nanjing, China
| | - Bi-Cheng Liu
- Institute of Nephrology, Zhong Da Hospital, Southeast University School of Medicine, DingJiaQiao Road, Nanjing, China.
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Kupniewska A, Szymanska K, Demkow U. Proteomics in the Diagnosis of Inborn Encephalopathies of Unknown Origin: A Myth or Reality. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2018; 1040:83-99. [PMID: 28983862 DOI: 10.1007/5584_2017_104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2023]
Abstract
Synaptopathy underlies a great variety of neurological or neurodevelopmental disorders, including neurodegenerative diseases and the highly complex neuropsychiatric syndromes. Standard diagnostic assays in the majority of synaptopathies are insufficient to make an appropriate and fast diagnosis, which has spurred a search for more accurate diagnostic methods using recent technological advances. As synaptopathy phenotypes strictly depend on genetics and environmental factors, the best way to approach these diseases is the investigation of entire sets of protein characteristics. Thus, proteomics has emerged as a mainstay in the studies on synaptopathies, with mass spectrometry as a technology of choice. This review is an update on the proteomic methods and achievements in the understanding, diagnostics, and novel biomarkers of synaptopathies. The article also provides a critical point of view and future perspectives on the application of neuroproteomics in clinical practice.
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Affiliation(s)
- Anna Kupniewska
- Department of Laboratory Diagnostics and Clinical Immunology of Developmental Age, Medical University of Warsaw, 63A Zwirki and Wigury Street, 02-091, Warsaw, Poland.
| | - Krystyna Szymanska
- Department of Clinical and Experimental Neuropathology, The Mossakowski Medical Research Centre, Polish Academy of Sciences, 5 Pawińskiego Street, 02-106, Warsaw, Poland
- Department of Child Psychiatry, Warsaw Medical University, Warsaw, 24 Marszalkowska Street, 00-576, Warsaw, Poland
| | - Urszula Demkow
- Department of Laboratory Diagnostics and Clinical Immunology of Developmental Age, Medical University of Warsaw, 63A Zwirki and Wigury Street, 02-091, Warsaw, Poland
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Halford J, Shen S, Itamura K, Levine J, Chong AC, Czerwieniec G, Glenn TC, Hovda DA, Vespa P, Bullock R, Dietrich WD, Mondello S, Loo JA, Wanner IB. New astroglial injury-defined biomarkers for neurotrauma assessment. J Cereb Blood Flow Metab 2017; 37:3278-3299. [PMID: 28816095 PMCID: PMC5624401 DOI: 10.1177/0271678x17724681] [Citation(s) in RCA: 51] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Revised: 05/01/2017] [Accepted: 05/25/2017] [Indexed: 01/08/2023]
Abstract
Traumatic brain injury (TBI) is an expanding public health epidemic with pathophysiology that is difficult to diagnose and thus treat. TBI biomarkers should assess patients across severities and reveal pathophysiology, but currently, their kinetics and specificity are unclear. No single ideal TBI biomarker exists. We identified new candidates from a TBI CSF proteome by selecting trauma-released, astrocyte-enriched proteins including aldolase C (ALDOC), its 38kD breakdown product (BDP), brain lipid binding protein (BLBP), astrocytic phosphoprotein (PEA15), glutamine synthetase (GS) and new 18-25kD-GFAP-BDPs. Their levels increased over four orders of magnitude in severe TBI CSF. First post-injury week, ALDOC levels were markedly high and stable. Short-lived BLBP and PEA15 related to injury progression. ALDOC, BLBP and PEA15 appeared hyper-acutely and were similarly robust in severe and mild TBI blood; 25kD-GFAP-BDP appeared overnight after TBI and was rarely present after mild TBI. Using a human culture trauma model, we investigated biomarker kinetics. Wounded (mechanoporated) astrocytes released ALDOC, BLBP and PEA15 acutely. Delayed cell death corresponded with GFAP release and proteolysis into small GFAP-BDPs. Associating biomarkers with cellular injury stages produced astroglial injury-defined (AID) biomarkers that facilitate TBI assessment, as neurological deficits are rooted not only in death of CNS cells, but also in their functional compromise.
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Affiliation(s)
- Julia Halford
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Sean Shen
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA, USA
| | - Kyohei Itamura
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Jaclynn Levine
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Albert C Chong
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Gregg Czerwieniec
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA, USA
| | - Thomas C Glenn
- Department of Neurosurgery, Brain Injury Research Center, Department of Molecular and Medical Pharmacology
| | - David A Hovda
- Department of Neurosurgery, Brain Injury Research Center, Department of Molecular and Medical Pharmacology
| | - Paul Vespa
- Department of Neurology, UCLA-David Geffen School of Medicine, Los Angeles, CA, USA
| | - Ross Bullock
- Department of Neurological Surgery, Jackson Memorial Hospital, Miami, FL, USA
| | - W Dalton Dietrich
- The Miami Project to Cure Paralysis, University of Miami-Miller School of Medicine, Miami, FL, USA
| | - Stefania Mondello
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy
| | - Joseph A Loo
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, UCLA Molecular Biology Institute, and UCLA/DOE Institute for Genomics and Proteomics, University of California, Los Angeles, CA, USA
| | - Ina-Beate Wanner
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
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Huesgen PF, Lange PF, Overall CM. Ensembles of protein termini and specific proteolytic signatures as candidate biomarkers of disease. Proteomics Clin Appl 2014; 8:338-50. [PMID: 24497460 DOI: 10.1002/prca.201300104] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2013] [Revised: 12/04/2013] [Accepted: 12/09/2013] [Indexed: 12/23/2022]
Abstract
Early accurate diagnosis and personalized treatment are essential in order to treat complex or fatal diseases such as cancer and autoimmune, cardiovascular and neurodegenerative diseases. To realize this vision, new diagnostic and prognostic biomarkers are urgently required. MS-based proteomics is the most promising approach for protein biomarker identification, but suffers in clinical translation of biomarker candidates that show only quantitative differences from normal tissue. Indeed, success in translating proteomic data to biomarkers in the clinic has been disappointing. Here, we propose that protein termini provide a new opportunity for biomarker discovery due to qualitative differences in intact and new protein termini between diseased and normal tissues. Altered proteolysis occurs in most pathologies. Disease- and process-specific protein modifications, including proteolytic processing and subsequent modification of the terminal amino acids, frequently lead to altered protein activity that plays key roles in the disease process. Thus, mapping of ensembles of characteristic protein termini provides a proteolytic signature of high information content that shows both quantitative and most importantly qualitative differences in different diseases and stage of disease. These unique protein biomarkers have the added benefit of being mechanistically informative by revealing the activity state of the bioactive protein. Moreover, proteome-wide isolation of protein termini leads to generalized sample simplification, thereby enabling up to three orders of magnitude lower LODs compared to traditional shotgun proteomic approaches. We introduce the potential of protein termini for biomarker discovery, briefly review methods enabling large-scale studies of protein termini, and discuss how these may be integrated into a termini-oriented biomarker discovery pipeline from discovery to clinical application.
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Affiliation(s)
- Pitter F Huesgen
- Centre for Blood Research, University of British Columbia, Vancouver, Canada; Department of Oral Biological and Medical Sciences, Faculty of Dentistry, University of British Columbia, Vancouver, Canada; Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, Canada
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Liu Y, Hüttenhain R, Collins B, Aebersold R. Mass spectrometric protein maps for biomarker discovery and clinical research. Expert Rev Mol Diagn 2013; 13:811-25. [PMID: 24138574 PMCID: PMC3833812 DOI: 10.1586/14737159.2013.845089] [Citation(s) in RCA: 93] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Among the wide range of proteomic technologies, targeted mass spectrometry (MS) has shown great potential for biomarker studies. To extend the degree of multiplexing achieved by selected reaction monitoring (SRM), we recently developed SWATH MS. SWATH MS is a variant of the emerging class of data-independent acquisition (DIA) methods and essentially converts the molecules in a physical sample into perpetually re-usable digital maps. The thus generated SWATH maps are then mined using a targeted data extraction strategy, allowing us to profile disease-related proteomes at a high degree of reproducibility. The successful application of both SRM and SWATH MS requires the a priori generation of reference spectral maps that provide coordinates for quantification. Herein, we demonstrate that the application of the mass spectrometric reference maps and the acquisition of personalized SWATH maps hold a particular promise for accelerating the current process of biomarker discovery.
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Affiliation(s)
- Yansheng Liu
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Wolfgang-Pauli-Str.16, 8093 Zurich, Switzerland
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Koziol J, Griffin N, Long F, Li Y, Latterich M, Schnitzer J. On protein abundance distributions in complex mixtures. Proteome Sci 2013; 11:5. [PMID: 23360617 PMCID: PMC3599228 DOI: 10.1186/1477-5956-11-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2011] [Accepted: 05/15/2012] [Indexed: 11/20/2022] Open
Abstract
Mass spectrometry, an analytical technique that measures the mass-to-charge ratio of ionized atoms or molecules, dates back more than 100 years, and has both qualitative and quantitative uses for determining chemical and structural information. Quantitative proteomic mass spectrometry on biological samples focuses on identifying the proteins present in the samples, and establishing the relative abundances of those proteins. Such protein inventories create the opportunity to discover novel biomarkers and disease targets. We have previously introduced a normalized, label-free method for quantification of protein abundances under a shotgun proteomics platform (Griffin et al., 2010). The introduction of this method for quantifying and comparing protein levels leads naturally to the issue of modeling protein abundances in individual samples. We here report that protein abundance levels from two recent proteomics experiments conducted by the authors can be adequately represented by Sichel distributions. Mathematically, Sichel distributions are mixtures of Poisson distributions with a rather complex mixing distribution, and have been previously and successfully applied to linguistics and species abundance data. The Sichel model can provide a direct measure of the heterogeneity of protein abundances, and can reveal protein abundance differences that simpler models fail to show.
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Affiliation(s)
- Ja Koziol
- The Scripps Research Institute, 10550 N Torrey Pines Road, La Jolla, CA, 92037, USA.
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López E, Madero L, López-Pascual J, Latterich M. Clinical proteomics and OMICS clues useful in translational medicine research. Proteome Sci 2012; 10:35. [PMID: 22642823 PMCID: PMC3536680 DOI: 10.1186/1477-5956-10-35] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2011] [Accepted: 05/04/2012] [Indexed: 12/21/2022] Open
Abstract
Since the advent of the new proteomics era more than a decade ago, large-scale studies of protein profiling have been used to identify distinctive molecular signatures in a wide array of biological systems, spanning areas of basic biological research, clinical diagnostics, and biomarker discovery directed toward therapeutic applications. Recent advances in protein separation and identification techniques have significantly improved proteomic approaches, leading to enhancement of the depth and breadth of proteome coverage. Proteomic signatures, specific for multiple diseases, including cancer and pre-invasive lesions, are emerging. This article combines, in a simple manner, relevant proteomic and OMICS clues used in the discovery and development of diagnostic and prognostic biomarkers that are applicable to all clinical fields, thus helping to improve applications of clinical proteomic strategies for translational medicine research.
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Affiliation(s)
- Elena López
- Centro de Investigación i + 12, Hospital 12 de Octubre, Av, De Córdoba s/n, 28040, Madrid, Spain.
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Kamada H. [Techniques for rapid production of monoclonal antibodies for use with antibody technology]. YAKUGAKU ZASSHI 2012; 132:473-7. [PMID: 22465925 DOI: 10.1248/yakushi.132.473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
A monoclonal antibody (Mab), due to its specific binding ability to a target protein, can potentially be one of the most useful tools for the functional analysis of proteins in recent proteomics-based research. However, the production of Mab is a very time-consuming and laborious process (i.e., preparation of recombinant antigens, immunization of animals, preparation of hybridomas), making it the rate-limiting step in using Mabs in high-throughput proteomics research, which heavily relies on comprehensive and rapid methods. Therefore, there is a great demand for new methods to efficiently generate Mabs against a group of proteins identified by proteome analysis. Here, we describe a useful method called "Antibody proteomic technique" for the rapid generations of Mabs to pharmaceutical target, which were identified by proteomic analyses of disease samples (ex. tumor tissue, etc.). We also introduce another method to find profitable targets on vasculature, which is called "Vascular proteomic technique". Our results suggest that this method for the rapid generation of Mabs to proteins may be very useful in proteomics-based research as well as in clinical applications.
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Affiliation(s)
- Haruhiko Kamada
- Laboratory of Biopharmaceutical Research, National Institute of Biomedical Innovation, Ibaraki, Japan.
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Callesen AK, Mogensen O, Jensen AK, Kruse TA, Martinussen T, Jensen ON, Madsen JS. Reproducibility of mass spectrometry based protein profiles for diagnosis of ovarian cancer across clinical studies: A systematic review. J Proteomics 2012; 75:2758-72. [PMID: 22366292 DOI: 10.1016/j.jprot.2012.02.007] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2011] [Revised: 02/02/2012] [Accepted: 02/04/2012] [Indexed: 02/02/2023]
Abstract
The focus of this systematic review is to give an overview of the current status of clinical protein profiling studies using MALDI and SELDI MS platforms in the search for ovarian cancer biomarkers. A total of 34 profiling studies were qualified for inclusion in the review. Comparative analysis of published discriminatory peaks to peaks found in an original MALDI MS protein profiling study was made to address the key question of reproducibility across studies. An overlap was found despite substantial heterogeneity between studies relating to study design, biological material, pre-analytical treatment, and data analysis. About 47% of the peaks reported to be associated to ovarian cancer were also represented in our experimental study, and 34% of these redetected peaks also showed a significant difference between cases and controls in our study. Thus, despite known problems related to reproducibility an overlap in peaks between clinical studies was demonstrated, which indicate convergence toward a set of common discriminating, reproducible peaks for ovarian cancer. The potential of the discriminating protein peaks for clinical use as ovarian cancer biomarkers will be discussed and evaluated. This article is part of a Special Issue entitled: Proteomics: The clinical link.
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Affiliation(s)
- Anne K Callesen
- Institute of Regional Health Services Research, University of Southern Denmark, Odense, Denmark.
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