Proteomic Analysis of Human Esophageal Cancer Using Tandem Mass Tag Quantifications. (8th August 2020)

• Record Type: Journal Article
• Authors: Sun, Suofeng; Zhang, Huijuan; Wang, Yu; Gao, Jing; Zhou, Shen; Li, Yuan; Han, Shuangyin; Li, Xiuling; Li, Jian
• Other Names: Yang Jialiang Guest Editor.
• Is Part Of: BioMed research international. Volume 2020(2020)
• Publication Date: 2020-08-08
• Subjects: Medicine -- Periodicals; Biology -- Periodicals; Biotechnology -- Periodicals; Life sciences -- Periodicals; 610.5
• DOI: 10.1155/2020/5849323
• Languages: English
• ISSNs: 2314-6133

Abstract

Abstract : Esophageal cancer (EC) is a type of extremely aggressive gastrointestinal cancer with high incidences in China and other Asian countries. EC does not have specific symptoms and is relatively easy to metastasize, which makes it difficult in early diagnosis. Thus, novel noninvasive diagnostic method is urgently needed in clinical practice. In this study, mass spectrometry with tandem mass tags and differential protein analysis were applied for identifying esophageal cancer-related proteins. The identified proteins were annotated based on their enrichment in Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. In addition, hierarchical clustering was applied based on differentially expressed proteins. As a result, a total of 5131 quantifiable proteins were identified from our liquid chromatography-tandem mass spectrometry with tandem mass tags (LC-MS/MS-TMT) method with 63 upregulated and 97 downregulated differential proteins between esophageal cancer and controlled normal samples. The differentially expressed proteins were highly enriched in GO terms associated with mitochondrial dissemble and apoptosis, and blood vessel regulation, and the upregulated differentially expressed proteins in EC samples were significantly enriched in major histocompatibility complex MHC-class I/II pathway of immune system. The functional clustering analysis revealed potential protein-protein interactions among tetraspanin, myosin, and S-100. In summary, our study provided a practical technological procedure of proteomic analysis for discovering novel biomarkers of a specific cancer type.