ArticleBiochemistry and biophysics reports2024
Identification of gastric cancer biomarkers through
Article in Biochemistry and biophysics reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Impact of Perioperative Proton Pump Inhibitors on Renal Cancer Progression. A Retrospective Study.Cancer medicine · 2026Article
- Molecular and structural reprogramming of gastric cancer revealed by systems-level transcriptomic analysis.PloS one · 2026Article
- Harnessing plasma transcriptomics for non-invasive cancer biomarker identification: a comprehensive review.Discover oncology · 2025Review
- AI-Assisted Detection of Early Gastric Cancer via Visualization of Mucosal Acidity Compromise During Endoscopy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
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4 authors.
Funding
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Abstract
Gastric cancer is among the most prevalent cancers worldwide including in Pakistan. Late diagnosis of gastric cancer leads to reduced survival. The present study aimed to investigate biomarkers for early diagnosis and prognosis of gastric cancer. For this purpose, the ten microarray-based gene expression datasets (GSE54129, GSE79973, GSE161533, GSE103236, GSE33651, GSE19826, GSE118916, GSE112369, GSE13911, and GSE81948) were retrieved from GEO database and analyzed by GEO2R to identify differentially expressed genes. Datasets were arranged in subsets of different dataset combinations to identify common DEGs. The gene ontology and functional pathway enrichment analysis of common DEGs was performed by DAVID tool. Pan-cancer analysis was conducted by UALCAN database. Survival analysis of common DEGs was done by Kaplan-Meier plotter. A total of 71 common DEGs were identified in different combinations of datasets. Among them, only 5 DEGs namely ATP4B, ATP4A, CCKBR, KCNJ15, and KCNJ16 were detected to be common in all the datasets. The GO and pathway analysis represented that the identified DEGs are involved in gastric acid secretion and collecting duct acid secretion pathways. Further expression validation of these five genes using three additional datasets (GSE31811, GSE26899, and GSE26272) confirmed their differential expression in gastric cancer samples. The pan-cancer analysis also revealed aberrant expression of DEGs in various cancers. The survival analysis showed the association of these 5 DEGs with poor survival of gastric cancer patients. To conclude, this study revealed a panel of 5 genes, which can be employed as diagnostic and prognostic biomarkers of gastric cancer patients.
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