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Identification of potential glycoprotein biomarkers in oral squamous cell carcinoma using sweet strategies. Glycoconj J 2021; 38:1-11. [PMID: 33547992 DOI: 10.1007/s10719-021-09973-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 12/08/2020] [Accepted: 01/11/2021] [Indexed: 12/13/2022]
Abstract
The prevalence of oral squamous cell carcinoma (OSCC) is high in South and Southeast Asia regions. Most OSCC patients are detected at advanced stages low 5-year survival rates. Aberrant expression of glycosylated proteins was found to be associated with malignant transformation and cancer progression. Hence, identification of cancer-associated glycoproteins could be used as potential biomarkers that are beneficial for diagnosis or clinical management of patients. This study aims to identify the differentially expressed glycoproteins using lectin-based glycoproteomics approaches. Serum samples of 40 patients with OSCC, 10 patients with oral potentially malignant disorder (OPMD), and 10 healthy individuals as control group were subjected to two-dimensional gel electrophoresis (2-DE) coupled with lectin Concanavalin A and Jacalin that specifically bind to N- and O-glycosylated proteins, respectively. Five differentially expressed N- and O-glycoproteins with various potential glycosylation sites were identified, namely N-glycosylated α1-antitrypsin (AAT), α2-HS-glycoprotein (AHSG), apolipoprotein A-I (APOA1), and haptoglobin (HP); as well as O-glycosylated AHSG and clusterin (CLU). Among them, AAT and APOA1 were further validated using enzyme-linked immunosorbent assay (ELISA) (n = 120). It was found that AAT and APOA1 are significantly upregulated in OSCC and these glycoproteins are independent risk factors of OSCC. The clinical utility of AAT and APOA1 as potential biomarkers of OSCC is needed for further evaluation.
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Li Z, Chernova TA, Ju T. Novel Technologies for Quantitative O-Glycomics and Amplification/Preparation of Cellular O-Glycans. SYNTHETIC GLYCOMES 2019. [DOI: 10.1039/9781788016575-00370] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Mucin-type O-glycosylation (O-glycans, O-glycome) characterized by GalNAc linked to Serine/Threonine or even tyrosine residues in proteins is one of the major types of glycosylations. In animals, O-glycans on glycoproteins participate in many critical biological processes such as cell adhesion, development, and immunity. Importantly, the O-glycome is different in a tissue/cell-specific manner, and often altered in cells at their pathological states; and this alteration, in turn, affects cellular properties and functions. Clearly, the Functional O-glycomics, which concerns biological roles of O-glycans, requires a comprehensive understanding of O-glycome. Structural and/or quantitative analysis of O-glycans, however, is an unmet demand because no enzyme can universally release O-glycans from glycoproteins. Furthermore, the preparation of complex O-glycans for biological studies is even more challenging. To meet these demands, we have developed a novel technology termed Cellular O-glycome Reporter/Amplification (CORA) for profiling cellular O-glycan structures and amplifying/preparing complex O-glycans from cultured cells. In this chapter, we describe the recent advances of CORA: quantitative-CORA (qCORA) and preparative-CORA (pCORA). qCORA takes the strategy of “metabolic stable isotopic labeling O-glycome of culture cells (SILOC),” and pCORA adapts cells to “O-glycan factories” when supplied with R-α-GalNAc(Ac)3 derivatives. qCORA and pCORA technologies can facilitate the cellular O-glycomics and functional O-glycomics studies.
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Affiliation(s)
- Zhonghua Li
- Department of Biochemistry, Emory University School of Medicine Atlanta GA 30322 USA
| | - Tatiana A. Chernova
- Department of Biochemistry, Emory University School of Medicine Atlanta GA 30322 USA
| | - Tongzhong Ju
- Department of Biochemistry, Emory University School of Medicine Atlanta GA 30322 USA
- Office of Biotechnology Products, Center for Drug Evaluation and Research, U.S. Food and Drug Administration Silver Spring MD 20993 USA
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Dalal K, Khorate P, Dalal B, Chavan R, Bhatia S, Kale A, Shukla A, Shankarkumar A. Differentially expressed serum host proteins in hepatitis B and C viral infections. Virusdisease 2018; 29:468-477. [PMID: 30539049 PMCID: PMC6261891 DOI: 10.1007/s13337-018-0484-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2018] [Accepted: 08/17/2018] [Indexed: 12/18/2022] Open
Abstract
Hepatitis B virus (HBV) and Hepatitis C virus (HCV) infection often lead to hepatocellular carcinoma (HCC), which is mostly detected in advanced stage. Hence, its early detection is of paramount importance using a biomarker having sensitivity and specificity both. The present study highlights differentially expressed host proteins in response to HBV/HCV infection at different stages. Comparative proteomic study was done by two-dimensional gel electrophoresis followed by mass spectrometry. Sera from each of chronically infected, liver cirrhosis and HCC in HBV or HCV infection along with controls were selected. Analysis of functional association between differentially expressed proteins with viral hepatitis was extensively carried out. Forty-three differentially expressed spots (≥ 1.5 fold; P < 0.05) on two-dimensional gel electrophoresis were corresponded to 28 proteins by mass spectrometry in variable liver diseases. Haptoglobin protein levels were decreased upon disease progression to HCC due to HBV infection. The other proteins expressed differentially are ceruloplasmin, serum paraoxonase 1, retinol binding protein and leucine rich alpha 2 proteins in plasma maybe associated to HBV HCC. Whereas, upregulation of C4a/C4b showed it as a reliable marker in patients with end stage liver disease related to HCV infection. ApolipoproteinA1 levels in liver diseases in both HBV and HCV infection corresponding to healthy controls may be a common marker for early diagnosis and disease monitoring. Protein interaction studies by extensive pathway analysis using bioinformatics tools such as EnrichNet application and STRING revealed significant associations with specific infections.
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Affiliation(s)
- Kruti Dalal
- Transfusion Transmitted Diseases Department, National Institute of Immunohaematology, 13th floor, New Multi-storeyed Bldg, KEM Hospital Campus, Parel, Mumbai, 400 012 India
| | - Priyanka Khorate
- Transfusion Transmitted Diseases Department, National Institute of Immunohaematology, 13th floor, New Multi-storeyed Bldg, KEM Hospital Campus, Parel, Mumbai, 400 012 India
| | - Bhavik Dalal
- Transfusion Transmitted Diseases Department, National Institute of Immunohaematology, 13th floor, New Multi-storeyed Bldg, KEM Hospital Campus, Parel, Mumbai, 400 012 India
| | - Rahul Chavan
- School of Chemical Sciences, UM-DAE Centre for Excellence in Basic Sciences, Mumbai University Campus, Vidyanagari, Kalina, Santacruz (East), Mumbai, 400098 India
| | - Shobna Bhatia
- Department of Gastroenterology, Seth G S Medical College and K E M Hospital, Acharya Donde Marg, Parel, Mumbai, 400 012 India
| | - Avinash Kale
- School of Chemical Sciences, UM-DAE Centre for Excellence in Basic Sciences, Mumbai University Campus, Vidyanagari, Kalina, Santacruz (East), Mumbai, 400098 India
| | - Akash Shukla
- Department of Gastroenterology, Seth G S Medical College and K E M Hospital, Acharya Donde Marg, Parel, Mumbai, 400 012 India
- Present Address: Department of Gastroenterology, Lokmanya Tilak Municipal General Hospital, Sion, Mumbai, 400 022 India
| | - Aruna Shankarkumar
- Transfusion Transmitted Diseases Department, National Institute of Immunohaematology, 13th floor, New Multi-storeyed Bldg, KEM Hospital Campus, Parel, Mumbai, 400 012 India
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Bhattacharjee M, Balakrishnan L, Renuse S, Advani J, Goel R, Sathe G, Keshava Prasad TS, Nair B, Jois R, Shankar S, Pandey A. Synovial fluid proteome in rheumatoid arthritis. Clin Proteomics 2016; 13:12. [PMID: 27274716 PMCID: PMC4893419 DOI: 10.1186/s12014-016-9113-1] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2016] [Accepted: 04/26/2016] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Rheumatoid arthritis (RA) is a chronic autoinflammatory disorder that affects small joints. Despite intense efforts, there are currently no definitive markers for early diagnosis of RA and for monitoring the progression of this disease, though some of the markers like anti CCP antibodies and anti vimentin antibodies are promising. We sought to catalogue the proteins present in the synovial fluid of patients with RA. It was done with the aim of identifying newer biomarkers, if any, that might prove promising in future. METHODS To enrich the low abundance proteins, we undertook two approaches-multiple affinity removal system (MARS14) to deplete some of the most abundant proteins and lectin affinity chromatography for enrichment of glycoproteins. The peptides were analyzed by LC-MS/MS on a high resolution Fourier transform mass spectrometer. RESULTS This effort was the first total profiling of the synovial fluid proteome in RA that led to identification of 956 proteins. From the list, we identified a number of functionally significant proteins including vascular cell adhesion molecule-1, S100 proteins, AXL receptor protein tyrosine kinase, macrophage colony stimulating factor (M-CSF), programmed cell death ligand 2 (PDCD1LG2), TNF receptor 2, (TNFRSF1B) and many novel proteins including hyaluronan-binding protein 2, semaphorin 4A (SEMA4D) and osteoclast stimulating factor 1. Overall, our findings illustrate the complex and dynamic nature of RA in which multiple pathways seems to be participating actively. CONCLUSIONS The use of high resolution mass spectrometry thus, enabled identification of proteins which might be critical to the progression of RA.
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Affiliation(s)
- Mitali Bhattacharjee
- />Institute of Bioinformatics, International Technology Park, Bangalore, 560066 India
- />Amrita School of Biotechnology, Amrita University, Kollam, 690525 India
| | - Lavanya Balakrishnan
- />Institute of Bioinformatics, International Technology Park, Bangalore, 560066 India
- />Department of Biotechnology, Kuvempu University, Shankaraghatta, 577451 India
| | - Santosh Renuse
- />Institute of Bioinformatics, International Technology Park, Bangalore, 560066 India
- />Amrita School of Biotechnology, Amrita University, Kollam, 690525 India
| | - Jayshree Advani
- />Institute of Bioinformatics, International Technology Park, Bangalore, 560066 India
- />Manipal University, Madhav Nagar, Manipal, 576104 India
| | - Renu Goel
- />Institute of Bioinformatics, International Technology Park, Bangalore, 560066 India
- />Department of Biotechnology, Kuvempu University, Shankaraghatta, 577451 India
| | - Gajanan Sathe
- />Institute of Bioinformatics, International Technology Park, Bangalore, 560066 India
- />Manipal University, Madhav Nagar, Manipal, 576104 India
| | - T. S. Keshava Prasad
- />Institute of Bioinformatics, International Technology Park, Bangalore, 560066 India
- />Amrita School of Biotechnology, Amrita University, Kollam, 690525 India
| | - Bipin Nair
- />Amrita School of Biotechnology, Amrita University, Kollam, 690525 India
| | - Ramesh Jois
- />Department of Rheumatology, Fortis Hospital, Bangalore, 560066 India
| | - Subramanian Shankar
- />Department of Rheumatology, Medical Division, Command Hospital (Air Force), Bangalore, 560007 India
| | - Akhilesh Pandey
- />McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, 733 N. Broadway, BRB 527, Baltimore, MD 21205 USA
- />Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
- />Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
- />Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
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5
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Bhattacharjee M, Sharma R, Goel R, Balakrishnan L, Renuse S, Advani J, Gupta ST, Verma R, Pinto SM, Sekhar NR, Nair B, Prasad TSK, Harsha HC, Jois R, Shankar S, Pandey A. A multilectin affinity approach for comparative glycoprotein profiling of rheumatoid arthritis and spondyloarthropathy. Clin Proteomics 2013; 10:11. [PMID: 24010407 PMCID: PMC3846907 DOI: 10.1186/1559-0275-10-11] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2013] [Accepted: 08/11/2013] [Indexed: 11/10/2022] Open
Abstract
Background Arthritis refers to inflammation of joints and includes common disorders such as rheumatoid arthritis (RA) and spondyloarthropathies (SpAs). These diseases differ mainly in terms of their clinical manifestations and the underlying pathogenesis. Glycoproteins in synovial fluid might reflect the disease activity status in the joints affected by arthritis; yet they have not been systematically studied previously. Although markers have been described for assisting in the diagnosis of RA, there are currently no known biomarkers for SpA. Materials and methods We sought to determine the relative abundance of glycoproteins in RA and SpA by lectin affinity chromatography coupled to iTRAQ labeling and LC-MS/MS analysis. We also used ELISA to validate the overexpression of VCAM-1, one of the candidate proteins identified in this study, in synovial fluid from RA patients. Results and discussion We identified proteins that were previously reported to be overexpressed in RA including metalloproteinase inhibitor 1 (TIMP1), myeloperoxidase (MPO) and several S100 proteins. In addition, we discovered several novel candidates that were overexpressed in SpA including Apolipoproteins C-II and C-III and the SUN domain-containing protein 3 (SUN3). Novel molecules found overexpressed in RA included extracellular matrix protein 1 (ECM1) and lumican (LUM). We validated one of the candidate biomarkers, vascular cell adhesion molecule 1 (VCAM1), in 20 RA and SpA samples using ELISA and confirmed its overexpression in RA (p-value <0.01). Our quantitative glycoproteomic approach to study arthritic disorders should open up new avenues for additional proteomics-based discovery studies in rheumatological disorders.
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Affiliation(s)
- Mitali Bhattacharjee
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India.,Amrita School of Biotechnology, Amrita Vishwa Vidyapeetham, Kollam 690525, India
| | - Rakesh Sharma
- Department of Neurochemistry, National Institute of Mental Health and Neuro Sciences, Bangalore 560029, India
| | - Renu Goel
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India.,Department of Biotechnology, Kuvempu University, Shankaraghatta 577451, India
| | - Lavanya Balakrishnan
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India.,Department of Biotechnology, Kuvempu University, Shankaraghatta 577451, India
| | - Santosh Renuse
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India.,Amrita School of Biotechnology, Amrita Vishwa Vidyapeetham, Kollam 690525, India
| | - Jayshree Advani
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India
| | | | - Renu Verma
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India
| | - Sneha M Pinto
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India.,Manipal University, Madhav Nagar, Manipal 576104, India
| | - Nirujogi Raja Sekhar
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India.,Centre of Excellence in Bioinformatics, Bioinformatics Centre, School of Life Sciences, Pondicherry University, Puducherry 605 014, India
| | - Bipin Nair
- Amrita School of Biotechnology, Amrita Vishwa Vidyapeetham, Kollam 690525, India
| | - T S Keshava Prasad
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India.,Amrita School of Biotechnology, Amrita Vishwa Vidyapeetham, Kollam 690525, India.,Manipal University, Madhav Nagar, Manipal 576104, India.,Centre of Excellence in Bioinformatics, Bioinformatics Centre, School of Life Sciences, Pondicherry University, Puducherry 605 014, India
| | - H C Harsha
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India
| | - Ramesh Jois
- Department of Rheumatology, Fortis Hospital, Bangalore 560076, India
| | - Subramanian Shankar
- Department of Internal Medicine, Armed Forces Medical College, Pune 411040, India
| | - Akhilesh Pandey
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA.,Department of Biological Chemistry, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA.,Department of Pathology, Johns Hopkins University School of Medicine, 733 N. Broadway, Baltimore, MD 21205, USA.,Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
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6
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Pan S, Tamura Y, Chen R, May D, McIntosh MW, Brentnall TA. Large-scale quantitative glycoproteomics analysis of site-specific glycosylation occupancy. MOLECULAR BIOSYSTEMS 2012; 8:2850-6. [PMID: 22892896 PMCID: PMC3463725 DOI: 10.1039/c2mb25268f] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Disease-associated aberrant glycosylation may be protein specific and glycosylation site specific. Quantitative assessment of glycosylation changes at a site-specific molecular level may represent one of the initial steps for systematically revealing the glycosylation abnormalities associated with a disease or biological state. Comparative quantitative profiling of glycoproteome to provide accurate quantification of site-specific glycosylation occupancy has been a challenging task, requiring a concerted approach drawing from a variety of techniques. In this report, we present a quantitative glycoproteomics method that allows global scale identification and comparative quantification of glycosylation site occupancy using mass spectrometry. We further demonstrated this approach by quantitatively characterizing the N-glycoproteome of human pancreas.
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Affiliation(s)
- Sheng Pan
- Department of Medicine, University of Washington, Seattle, WA 98195, USA.
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7
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Wong KF, Luk JM. Discovery of lamin B1 and vimentin as circulating biomarkers for early hepatocellular carcinoma. Methods Mol Biol 2012; 909:295-310. [PMID: 22903723 DOI: 10.1007/978-1-61779-959-4_19] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
The recent advancements in proteomic technologies have reconstituted our research strategies over different type of liver diseases including hepatocellular carcinoma (HCC). Combined analyses on HCC proteome and clinicopathological data of patients have allowed identification of many promising biomarkers that can be further developed into noninvasive diagnostic assays for cancer surveillance. Capitalizing our established proteomic platform primarily based on two-dimensional polyacrylamide gel electrophoresis (2DE) and MALDI-TOF/TOF mass spectrometry, our groups have identified lamin B1 (LMNB1) and vimentin (VIM) as promising biomarkers for detection of early HCC. Protein levels of both biomarkers were significantly elevated in cancerous tissues when compared to the controls in disease-free and cirrhotic liver subjects. Further investigation of the circulating LMNB1 mRNA level in patients' blood samples by standard PCR showed 76% sensitivity and 82% specificity for detection of early HCC. In parallel, an ELISA assay for measuring circulating vimentin level in patients' serum samples could detect small HCC at 40.91% sensitivity and 87.5% specificity. The candidate biomarkers were evaluated with the diagnostic performance of α-fetoprotein (AFP) for HCC. In this article, we address the current protocols for HCC biomarker discovery, ranging from clinical sample preparation, 2DE proteomic profiling and informatics analysis, and assay development and clinical validation study. Focus is emphasized on the methods for sample preservation and low-abundance protein enrichment.
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Affiliation(s)
- Kwong-Fai Wong
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
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Zhao Y, Jia W, Wang J, Ying W, Zhang Y, Qian X. Fragmentation and site-specific quantification of core fucosylated glycoprotein by multiple reaction monitoring-mass spectrometry. Anal Chem 2011; 83:8802-9. [PMID: 21970473 DOI: 10.1021/ac201676a] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Glycosylation modifications of proteins have been attracting increasing attention due to their roles in the physiological and pathological processes of the cell. Core fucosylation (CF), one special type of glycan structure in glycoproteins, has been linked with tumorigenesis. The study of protein glycosylation has been hindered by the technical challenges caused by the microheterogeneity of glycan modifications. In commonly used methods, sugar chains on the peptide were released using endoglycosidase, and the glycan and peptides were analyzed separately with mass spectrometry. Although mass spectrometric analysis can be performed easily in this way, an increase in false positives when assigning glycosites was inevitable. Our earlier research demonstrated a strategy combining Endo F3-catalyzed partial deglycosylation with MS(3) (MS/MS/MS) scanning triggered by the neutral loss of a fucose to precisely identify CF proteins on a large scale. In this research, fragmentations of partially deglycosylated glycopeptides were studied using a triple quadrupole mass spectrometer, and a quantification method that coupled our published identification strategy with multiple reaction monitoring-mass spectrometry (MRM-MS) analysis was developed to obtain site-specific quantification information of core fucosylated peptides. To illustrate the feasibility of the quantification method, the CF peptides of target proteins in clinical serum were quantified and compared as a preliminary demonstration.
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Affiliation(s)
- Yan Zhao
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Changping District, Beijing, P R China
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9
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Pawar H, Kashyap MK, Sahasrabuddhe NA, Renuse S, Harsha HC, Kumar P, Sharma J, Kandasamy K, Marimuthu A, Nair B, Rajagopalan S, Maharudraiah J, Premalatha CS, Kumar KVV, Vijayakumar M, Chaerkady R, Prasad TSK, Kumar RV, Pandey A. Quantitative tissue proteomics of esophageal squamous cell carcinoma for novel biomarker discovery. Cancer Biol Ther 2011; 12:510-522. [PMID: 21743296 PMCID: PMC3218592 DOI: 10.4161/cbt.12.6.16833] [Citation(s) in RCA: 94] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2011] [Revised: 05/05/2011] [Accepted: 06/07/2011] [Indexed: 02/07/2023] Open
Abstract
Esophageal squamous cell carcinoma (ESCC) is among the top ten most frequent malignancies worldwide. In this study, our objective was to identify potential biomarkers for ESCC through a quantitative proteomic approach using the isobaric tags for relative and absolute quantitation (iTRAQ) approach. We compared the protein expression profiles of ESCC tumor tissues with the corresponding adjacent normal tissue from ten patients. LC-MS/MS analysis of strong cation exchange chromatography fractions was carried out on an Accurate Mass QTOF mass spectrometer, which led to the identification of 687 proteins. In all, 257 proteins were identified as differentially expressed in ESCC as compared to normal. We found several previously known protein biomarkers to be upregulated in ESCC including thrombospondin 1 (THBS1), periostin 1 (POSTN) and heat shock 70 kDa protein 9 (HSPA9) confirming the validity of our approach. In addition, several novel proteins that had not been reported previously were identified in our screen. These novel biomarker candidates included prosaposin (PSAP), plectin 1 (PLEC1) and protein disulfide isomerase A 4 (PDIA4) that were further validated to be overexpressed by immunohistochemical labeling using tissue microarrays. The success of our study shows that this mass spectrometric strategy can be applied to cancers in general to develop a panel of candidate biomarkers, which can then be validated by other techniques.
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Affiliation(s)
- Harsh Pawar
- Institute of Bioinformatics; International Technology Park; Bangalore, India
- Rajiv Gandhi University of Health Sciences; Bangalore, India
- Department of Pathology; Kidwai Memorial Institute of Oncology; Kidwai Memorial Institute of Oncology; Bangalore, India
| | - Manoj Kumar Kashyap
- Institute of Bioinformatics; International Technology Park; Bangalore, India
| | - Nandini A Sahasrabuddhe
- Institute of Bioinformatics; International Technology Park; Bangalore, India
- Manipal University; Manipal, India
- McKusick-Nathans Institute of Genetic Medicine; Johns Hopkins University School of Medicine; Baltimore, MD USA
- Department of Biological Chemistry; Johns Hopkins University School of Medicine; Baltimore, MD USA
| | - Santosh Renuse
- Institute of Bioinformatics; International Technology Park; Bangalore, India
- Department of Biotechnology; Amrita Vishwa Vidyapeetham; Kollam, India
- McKusick-Nathans Institute of Genetic Medicine; Johns Hopkins University School of Medicine; Baltimore, MD USA
- Department of Biological Chemistry; Johns Hopkins University School of Medicine; Baltimore, MD USA
| | - HC Harsha
- Institute of Bioinformatics; International Technology Park; Bangalore, India
| | - Praveen Kumar
- Institute of Bioinformatics; International Technology Park; Bangalore, India
| | - Jyoti Sharma
- Institute of Bioinformatics; International Technology Park; Bangalore, India
- Manipal University; Manipal, India
| | - Kumaran Kandasamy
- Institute of Bioinformatics; International Technology Park; Bangalore, India
| | - Arivusudar Marimuthu
- Institute of Bioinformatics; International Technology Park; Bangalore, India
- Manipal University; Manipal, India
| | - Bipin Nair
- Department of Biotechnology; Amrita Vishwa Vidyapeetham; Kollam, India
| | | | - Jagadeesha Maharudraiah
- Institute of Bioinformatics; International Technology Park; Bangalore, India
- RajaRajeswari Medical College; Bangalore, India
| | | | | | - M Vijayakumar
- Department of Surgical Oncology; Kidwai Memorial Institute of Oncology; Bangalore, India
| | - Raghothama Chaerkady
- Institute of Bioinformatics; International Technology Park; Bangalore, India
- McKusick-Nathans Institute of Genetic Medicine; Johns Hopkins University School of Medicine; Baltimore, MD USA
- Department of Biological Chemistry; Johns Hopkins University School of Medicine; Baltimore, MD USA
| | - Thotterthodi Subrahmanya Keshava Prasad
- Institute of Bioinformatics; International Technology Park; Bangalore, India
- Manipal University; Manipal, India
- Centre of Excellence in Bioinformatics; School of Life Sciences; Pondicherry University; Pondicherry, India
| | - Rekha V Kumar
- Department of Pathology; Kidwai Memorial Institute of Oncology; Kidwai Memorial Institute of Oncology; Bangalore, India
| | - Akhilesh Pandey
- McKusick-Nathans Institute of Genetic Medicine; Johns Hopkins University School of Medicine; Baltimore, MD USA
- Department of Biological Chemistry; Johns Hopkins University School of Medicine; Baltimore, MD USA
- Oncology; Johns Hopkins University School of Medicine; Baltimore, MD USA
- Pathology; Johns Hopkins University School of Medicine; Baltimore, MD USA
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10
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Marimuthu A, O’Meally RN, Chaerkady R, Subbannayya Y, Nanjappa V, Kumar P, Kelkar DS, Pinto SM, Sharma R, Renuse S, Goel R, Christopher R, Delanghe B, Cole RN, Harsha H, Pandey A. A comprehensive map of the human urinary proteome. J Proteome Res 2011; 10:2734-43. [PMID: 21500864 PMCID: PMC4213861 DOI: 10.1021/pr2003038] [Citation(s) in RCA: 147] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The study of the human urinary proteome has the potential to offer significant insights into normal physiology as well as disease pathology. The information obtained from such studies could be applied to the diagnosis of various diseases. The high sensitivity, resolution, and mass accuracy of the latest generation of mass spectrometers provides an opportunity to accurately catalog the proteins present in human urine, including those present at low levels. To this end, we carried out a comprehensive analysis of human urinary proteome from healthy individuals using high-resolution Fourier transform mass spectrometry. Importantly, we used the Orbitrap for detecting ions in both MS (resolution 60 000) and MS/MS (resolution 15 000) modes. To increase the depth of our analysis, we characterized both unfractionated as well as lectin-enriched proteins in our experiments. In all, we identified 1,823 proteins with less than 1% false discovery rate, of which 671 proteins have not previously been reported as constituents of human urine. This data set should serve as a comprehensive reference list for future studies aimed at identification and characterization of urinary biomarkers for various diseases.
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Affiliation(s)
- Arivusudar Marimuthu
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, Karnataka, India
- Manipal University, Manipal 576104, Karnataka, India
| | - Robert N. O’Meally
- Mass Spectrometry and Proteomics Facility, Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore 21205, Maryland, United States
| | - Raghothama Chaerkady
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, Karnataka, India
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore 21205, Maryland, United States
- Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore 21205, Maryland, United States
| | - Yashwanth Subbannayya
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, Karnataka, India
- Rajiv Gandhi University of Health Sciences, Bangalore 560041, Karnataka, India
| | - Vishalakshi Nanjappa
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, Karnataka, India
| | - Praveen Kumar
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, Karnataka, India
| | - Dhanashree S. Kelkar
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, Karnataka, India
- School of Biotechnology, Amrita University, Kollam 690525, Kerala, India
| | - Sneha M. Pinto
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, Karnataka, India
| | - Rakesh Sharma
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, Karnataka, India
- Department of Neurochemistry, National Institute of Mental Health and Neuro Sciences, Bangalore 560006, Karnataka, India
| | - Santosh Renuse
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, Karnataka, India
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore 21205, Maryland, United States
- Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore 21205, Maryland, United States
- School of Biotechnology, Amrita University, Kollam 690525, Kerala, India
| | - Renu Goel
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, Karnataka, India
- Department of Biotechnology, Kuvempu University, Shimoga 577451, Karnataka, India
| | - Rita Christopher
- Department of Neurochemistry, National Institute of Mental Health and Neuro Sciences, Bangalore 560006, Karnataka, India
| | | | - Robert N. Cole
- Mass Spectrometry and Proteomics Facility, Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore 21205, Maryland, United States
| | - H.C. Harsha
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, Karnataka, India
| | - Akhilesh Pandey
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore 21205, Maryland, United States
- Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore 21205, Maryland, United States
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore 21205, Maryland, United States
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore 21205, Maryland, United States
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11
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Li G, Xiao Z, Liu J, Li C, Li F, Chen Z. Cancer: a proteomic disease. SCIENCE CHINA-LIFE SCIENCES 2011; 54:403-8. [PMID: 21455689 DOI: 10.1007/s11427-011-4163-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Received: 05/14/2010] [Accepted: 08/17/2010] [Indexed: 01/05/2023]
Abstract
The development of cancer is a pathological process involving multiple environmental carcinogenic factors and genetic alterations. For decades, cancer researchers have focused on genomic and transcriptomic analyses. The completion of the Human Genome Project has opened the door to the post-genome era and oncoproteomics. Proteins play a critical role in tumorigenesis and influence the differences between normal cells and malignant cells. This report proposes the concept that cancer is a proteomic disease. This concept is based on examining protein expression profiles, post-translational modifications, and protein-protein interactions in carcinogenesis using recent advances in comparative, functional and structural proteomics. This approach provides a new way of viewing carcinogenesis, presents new clues in biomarker discovery for cancer diagnosis and therapy, and reveals important scientific findings and their significance to clinical applications.
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Affiliation(s)
- GuoQing Li
- Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, Xiangya Hospital, Central South University, Changsha, 410008, China
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12
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Renuse S, Chaerkady R, Pandey A. Proteogenomics. Proteomics 2011; 11:620-30. [DOI: 10.1002/pmic.201000615] [Citation(s) in RCA: 106] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2010] [Revised: 11/14/2010] [Accepted: 11/16/2010] [Indexed: 12/13/2022]
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13
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Zhang H, Cotter RJ. Glycoproteomics: New Technology Developments and Applications Provide Renewed Interest in Glycoproteins. Clin Proteomics 2008. [DOI: 10.1007/s12014-008-9020-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
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