Quantitative proteomics identified 3 oxidative phosphorylation genes with clinical prognostic significance in gastric cancer

The aim of the present study was to explore the underlying mechanisms involved in gastric cancer (GC) formation using data‐independent acquisition (DIA) quantitative proteomics analysis. We identified the differences in protein expression and related functions involved in biological metabolic proces...

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Bibliographic Details
Published in:Journal of cellular and molecular medicine 2020-09, Vol.24 (18), p.10842-10854
Main Authors: Su, Fei, Zhou, Fen‐fang, Zhang, Tao, Wang, Dan‐wen, Zhao, Da, Hou, Xiao‐ming, Feng, Mao‐hui
Format: Article
Language:English
Subjects:
Antibodies
Biomarkers
DIA
Gastric cancer
Gene expression
Genomes
Mass spectrometry
metabolic network
Metastasis
NADH
NADH dehydrogenase
Original
Oxidative phosphorylation
Peptides
Phosphatase
Phosphorylation
Principal components analysis
Proteins
Proteomics
Scientific imaging
Survival analysis
Tricarboxylic acid cycle
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Summary:The aim of the present study was to explore the underlying mechanisms involved in gastric cancer (GC) formation using data‐independent acquisition (DIA) quantitative proteomics analysis. We identified the differences in protein expression and related functions involved in biological metabolic processes in GC. Totally, 745 differentially expressed proteins (DEPs) were found in GC tissues vs. gastric normal tissues. Despite enormous complexity in the details of the underlying regulatory network, we find that clusters of proteins from the DEPs were mainly involved in 38 pathways. All of the identified DEPs involved in oxidative phosphorylation were down‐regulated. Moreover, GC possesses significantly altered biological metabolic processes, such as NADH dehydrogenase complex assembly and tricarboxylic acid cycle, which is mostly consistent with that in KEGG analysis. Furthermore the higher expression of UQCRQ, NDUFB7 and UQCRC2 were positively correlated with a better prognosis, implicating these proteins may as novel candidate diagnostic and prognostic biomarkers.
ISSN:1582-1838
1582-4934
DOI:10.1111/jcmm.15712