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Updated: Jun 6, 2026

Development of Compendium for Esophageal Squamous Cell Carcinoma
Published on: April 12, 2024
Shared molecular features and candidate pathways underlying gastric cancer-depression comorbidity: a systems biology
Bin Liu1, Bowen Hou1,2, Yu Zhao1
1Department of General Surgery, The First Affiliated Hospital of Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Abstract:
The bidirectional association between gastric cancer (GC) and depression remains incompletely elucidated. This investigation examines the genetic and molecular correlations between GC and depression through bioinformatics and experimental approaches. Utilizing Gene Expression Omnibus (RRID: SCR_005012), DisGeNET (RRID: SCR_006178), and GeneCards (RRID: SCR_002773) databases, 130 GC-associated and 534 depression-associated genes were identified. Overlapping genes underwent further analysis via Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction network methodologies. Six pivotal hub genes were identified: SERPINE1, COL4A1, PDGFRB, BMP1, NOTCH3, and EDNRA, with SERPINE1 emerging as a particularly significant hub gene. These genes demonstrated upregulation in GC tissues and exhibited correlation with diminished survival outcomes. Furthermore, single-sample Gene Set Enrichment Analysis revealed their association with immune cell infiltration patterns. Additionally, miRNA-mRNA network analysis demonstrated that specific microRNAs, including miR-21-5p, miR-145-5p, miR-16-5p, miR-34a-5p, and miR-491-5p, were predicted to target these genes. Real-time quantitative polymerase chain reaction and Western blot validation subsequently verified the distinct expression patterns of these mRNAs in GC tissues. Critical pathways, encompassing the PI3K-Akt, AGE-RAGE, and proteoglycans pathways, may contribute to the interconnection between GC and depression. These findings illuminate potential molecular linkages between GC and depression, though additional investigation is required to elucidate the underlying mechanisms.
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