Proteomic Analysis of Human Esophageal Cancer Using Tandem Mass Tag Quantifications
Joint Authors
Sun, Suofeng
Zhang, Huijuan
Wang, Yu
Gao, Jing
Zhou, Shen
Li, Yuan
Han, Shuangyin
Li, Xiuling
Li, Jian
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-08
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Sun, Suofeng& Zhang, Huijuan& Wang, Yu& Gao, Jing& Zhou, Shen& Li, Yuan…[et al.]. 2020. Proteomic Analysis of Human Esophageal Cancer Using Tandem Mass Tag Quantifications. BioMed Research International،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1135031
Modern Language Association (MLA)
Sun, Suofeng…[et al.]. Proteomic Analysis of Human Esophageal Cancer Using Tandem Mass Tag Quantifications. BioMed Research International No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1135031
American Medical Association (AMA)
Sun, Suofeng& Zhang, Huijuan& Wang, Yu& Gao, Jing& Zhou, Shen& Li, Yuan…[et al.]. Proteomic Analysis of Human Esophageal Cancer Using Tandem Mass Tag Quantifications. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1135031
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1135031