Evidence map›Paper›PMID 41102664›Full record

ArticleBMC gastroenterology2025

Bioinformatics analysis and in vitro studies identify COX7C as a prognostic predictor in gastric adenocarcinoma.

Conglai Shi, Qiang Wang, Xin Zhang, Weiguo Wang, Wei Wang, Ziran Wei, Yue Liu

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Article in BMC gastroenterology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Conglai Shi *Clinical Laboratory, Fuyang People's Hospital, No.501 Sanqing Road, Yingzhou District, Fuyang City, 236000, China.
Qiang Wang *State Key Laboratory, Jiangsu Institute of Parasitic Diseases, Wuxi, Jiangsu, 214064, China.
Xin Zhang *Department of Gastrointestinal Surgery, Second Affiliated Hospital of Naval Medical University, No.415 Fengyang Rd, Shanghai, 200003, China.
Weiguo WangClinical Laboratory, Fuyang People's Hospital, No.501 Sanqing Road, Yingzhou District, Fuyang City, 236000, China.
Wei WangClinical Laboratory, Fuyang People's Hospital, No.501 Sanqing Road, Yingzhou District, Fuyang City, 236000, China. 13485899635@163.com.
Ziran WeiDepartment of Gastrointestinal Surgery, Second Affiliated Hospital of Naval Medical University, No.415 Fengyang Rd, Shanghai, 200003, China. weiziran0010185@163.com.
Yue LiuClinical Laboratory, Fuyang People's Hospital, No.501 Sanqing Road, Yingzhou District, Fuyang City, 236000, China. 18856823191@163.com.

Funding

National Natural Science Foundation of China 81773049
6 · The paper itself

Abstract

backgroundStomach adenocarcinoma (STAD) remains a significant threat to human health. This study sought to discover clinically relevant biomarkers for STAD by integrating bioinformatics analysis and in vitro experimental methods.

methodsWe utilized the GSE64951 dataset to screen for differentially expressed genes (DEGs), which were then subjected to weighted gene co-expression network analysis (WGCNA). Candidate modules were subjected to Molecular Complex Detection (MCODE) analysis to extract key genes. Survival analysis and immune infiltration analysis were conducted to identify hub genes associated with STAD prognosis. Among them, cytochrome c oxidase subunit 7 C (COX7C) was selected for further investigation. Its expression levels in normal versus tumor tissues were compared, and its diagnostic performance was assessed via receiver operating characteristic (ROC) curve analysis. Functional experiments, including COX7C overexpression and knockdown, were performed in MGC803 cells to evaluate its effects on viability, apoptosis, migration, and invasion.

resultsWGCNA identified multiple gene modules, among which the blue and turquoise modules showed the strongest correlations with clinical traits and were selected for further analysis. MCODE analysis identified 11 key genes. COX7C was identified as hub gene, and its prognostic signature demonstrated robust predictive power. Gene Set Enrichment Analysis (GSEA) indicated that COX7C was significantly involved in pathways such as amino acid metabolism and non - alcoholic fatty liver disease. Notably, COX7C mRNA expression was significantly downregulated in STAD tissues (AUC = 0.7253, P = 0.0032). Functional experiments demonstrated that overexpression of COX7C significantly inhibited cell viability, promoted apoptosis, and reduced cell migration and invasion. Conversely, knockdown of COX7C led to opposite effects.

conclusionCOX7C functions as a tumor suppressor and a potential prognostic biomarker in STAD. These findings provide new insights into STAD pathogenesis and suggest COX7C as a promising target for improving diagnostic and therapeutic strategies.

Indexed as

AdenocarcinomaStomach NeoplasmsApoptosisBiomarkers, TumorCell Line, TumorCell MovementComputational BiologyGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansPrognosisBiomarkers, TumorCOX7CDifferentially expressed genesPrognostic predictorStomach adenocarcinomaWGCNA

Identifiers

PMID41102664
PMCPMC12532943

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.