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Authors: Manoj Kumar Kashyap, H. C. Harsha, Santosh Renuse, Harsh Pawar, Nandini A. Sahasrabuddhe, Min-Sik Kim, Arivusudar Marimuthu, Shivakumar Keerthikumar, Babylakshmi Muthusamy, Kumaran Kandasamy, Yashwanth Subbannayya, Thottethodi Subrahmanya Keshava Prasad, Riaz Mahmood, Raghothama Chaerkady, Stephen J. Meltzer, Rekha V. Kumar, Anil K. Rustgi and Akhilesh Pandey

Manoj Kumar Kashyap

Institute of Bioinformatics, International Technology Park, Bangalore, India; McKusick-Nathans Institute of Genetic Medicine; Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD; Department of Biotechnology, Kuvempu University, Shimoga, India

H. C. Harsha

Institute of Bioinformatics, International Technology Park, Bangalore, India; McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD

Santosh Renuse

Institute of Bioinformatics, International Technology Park, Bangalore, India; Department of Biotechnology, Amrita Vishwa Vidyapeetham, Kollam, India

Harsh Pawar

Institute of Bioinformatics, International Technology Park, Bangalore, India; Rajiv Gandhi University of Health Sciences, Bangalore, India

Nandini A. Sahasrabuddhe

Institute of Bioinformatics, International Technology Park, Bangalore, India; Manipal University, Manipal, Karnataka

Min-Sik Kim

McKusick-Nathans Institute of Genetic Medicine; Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD

Arivusudar Marimuthu

Institute of Bioinformatics, International Technology Park, Bangalore, India; McKusick-Nathans Institute of Genetic Medicine; Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD; Manipal University, Manipal, Karnataka

Shivakumar Keerthikumar

Institute of Bioinformatics, International Technology Park, Bangalore, India

Babylakshmi Muthusamy

Institute of Bioinformatics, International Technology Park, Bangalore, India

Kumaran Kandasamy

Institute of Bioinformatics, International Technology Park, Bangalore, India; McKusick-Nathans Institute of Genetic Medicine; Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD; Department of Biotechnology, Kuvempu University, Shimoga, India

Yashwanth Subbannayya

Institute of Bioinformatics, International Technology Park, Bangalore, India; Rajiv Gandhi University of Health Sciences, Bangalore, India

Thottethodi Subrahmanya Keshava Prasad

Institute of Bioinformatics, International Technology Park, Bangalore, India

Riaz Mahmood

Department of Biotechnology, Kuvempu University, Shimoga, India

Raghothama Chaerkady

Institute of Bioinformatics, International Technology Park, Bangalore, India; McKusick-Nathans Institute of Genetic Medicine, Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD;

Stephen J. Meltzer

Department of Medicine; Oncology, Johns Hopkins University School of Medicine, Baltimore, MD

Rekha V. Kumar

Department of Pathology, Kidwai Memorial Institute of Oncology, Bangalore, India

Anil K. Rustgi

Division of Gastroenterology, Department of Medicine and Genetics, Abramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania

Akhilesh Pandey

Corresponding author: pandey@jhmi.edu
Institute for Genetic Medicine, The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins Medical Institutions, Baltimore, MD

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Abstract:

The identification of secreted proteins that are differentially expressed between non-neoplastic and esophageal squamous cell carcinoma (ESCC) cells can provide potential biomarkers of ESCC. We used a SILAC-based quantitative proteomic approach to compare the secretome of ESCC cells with that of non-neoplastic esophageal squamous epithelial cells. Proteins were resolved by SDS-PAGE, and tandem mass spectrometry analysis (LC-MS/MS) of in-gel trypsin-digested peptides was carried out on a high-accuracy qTOF mass spectrometer. In total, we identified 441 proteins in the combined secretomes, including 120 proteins with >2-fold upregulation in the ESCC secretome vs. that of non-neoplastic esophageal squamous epithelial cells. In this study, several potential protein biomarkers previously known to be increased in ESCC including matrix metalloproteinase 1, transferrin receptor, and transforming growth factor beta-induced 68 kDa were identified as overexpressed in the ESCC-derived secretome. In addition, we identified several novel proteins that have not been previously reported to be associated with ESCC. Among the novel candidate proteins identified, protein disulfide isomerase family a member 3 (PDIA3), GDP dissociation inhibitor 2 (GDI2), and lectin galactoside binding soluble 3 binding protein (LGALS3BP) were further validated by immunoblot analysis and immunohistochemical labeling using tissue microarrays. This tissue microarray analysis showed overexpression of protein disulfide isomerase family a member 3, GDP dissociation inhibitor 2, and lectin galactoside binding soluble 3 binding protein in 93%, 93% and 87% of 137 ESCC cases, respectively. Hence, we conclude that these potential biomarkers are excellent candidates for further evaluation to test their role and efficacy in the early detection of ESCC.