ArticleJournal of gastrointestinal oncology2025
Genes associated with calcium signaling have promising diagnostic potential for gastric cancer.
Article in Journal of gastrointestinal oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Exploration of m7G-related immune genes and construction of a prognostic risk model in gastric cancer.Scientific reports · 2026Article
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9 authors.
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Abstract
Background: Gastric cancer (GC) represents a considerable health risk, characterized by a poor 5-year survival rate of approximately 8%. Using data from The Cancer Genome Atlas (TCGA), this study investigated the function of calcium signaling-related genes in the context of GC. Methods: The RNA sequencing data and clinical characteristic data of GC patients were retrieved from TCGA database. A comprehensive analysis was conducted to identify the prognostic genes, and a significant correlation was found between these genes and the calcium signaling pathways related to GC. Results: The univariate Cox regression analysis identified 829 prognostic genes, primarily related to the calcium signaling pathway, focal adhesion, extracellular matrix (ECM)-receptor interaction, and cancer-associated pathways, all of which may significantly affect GC. Through consensus clustering, two distinct molecular subtypes of GC were identified [Cluster 1 (C1) and Cluster 2 (C2)] based on the genes associated with calcium signaling. Notably, C2 may serve as a prognostic indicator of risk, potentially reflecting the progression of clinical symptoms. The Gene Ontology (GO) analysis of biological processes revealed that these genes were significantly involved in cell-matrix adhesion, calcium ion homeostasis, and cell-substrate adhesion in the high-risk C1 cohort. Similarly, the Kyoto Encyclopedia of Genes and Genomes analysis indicated that the differentially expressed genes were largely associated with the pathways related to ECM-receptor interactions, focal adhesion, vascular smooth muscle contraction, cancer-related proteoglycans, and calcium signaling pathways in the high-risk C1 group. Further, there were significant differences in the immune activity of the two calcium signaling-related GC groups. The least absolute shrinkage and selection operator regression analysis identified 10 genes associated with calcium signaling in GC (i.e., Conclusions: We established an innovative signature associated with calcium signaling that serves as a reliable prognostic indicator for GC. Our findings may pave the way for enhanced diagnostic and therapeutic approaches in the context of GC.
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