Prognostic Impact of Aberrantly Expressed Protein-coding Gene Associated With Gastric Cancer's Regulatory T Cells, Based on Online Databases.

Context: Gastric cancer (GC) remains one of the most prevalent malignancies worldwide, and no effective cure exists for advanced GC. Clinicians believe that molecularly targeted therapy through PCGs may replace surgery, radiotherapy, and other treatments as a breakthrough in curing malignancies.

Objective: The study intended to examine the impact of aberrant expression of the protein-coding genes (PCGs) associated with regulatory T cells on the prognosis of patients with gastric cancer (GC).

Design: The research team performed a genetic study through research of genetic data in online databases.

Setting: The study took place at Zhongda Hospital.

Outcome Measures: The research team selected a publicly available dataset, genetic suppressor element 109476 (GSE109476), from the Gene Expression Omnibus (GEO) database for differential gene analysis, gene ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to screen for PCGs associated with regulatory T cells as well as the Gene Expression Profiling Interactive Analysis (GEPIA) database with the Kaplan-Meier Plotter database to analyze the expression of the above PCGs in GC and the prognostic impact on GC.

Results: The GEO2R analysis found 315 differentially expressed PCGs in GSE109476, among which nine PCGs were associated with regulatory T cells: (1) chemokine (C-C motif) ligand 19 (CCL19), (2) CCL21, (3) C-C chemokine receptor type 7 (CCR7), (4) cluster of differentiation 70 (CD70), (5) ephrin B3 (EFNB3), (6) early growth response 3 (EGR3), (7) interleukin-7 receptor (IL7R), (8) galectin-1 (LGALS1), and (9) tumor necrosis factor (TNF) receptor superfamily member 13C (TNFRSF13C). The GEPIA database indicated that no significant differences existed between the expression of CCL19, CCL21, CD70, EFNB3, EGR3, IL7R, and TNFRSF13C in stomach adenocarcinoma (STAD) tissues and that in normal tissues (P > .05), while expressions of CCR7 and LGALS1 were significantly elevated in STAD tissues compared to the normal tissues (P < .05). The Kaplan-Meier Plotter database analysis, on the other hand, showed a significant relationship between all of the above-mentioned PCGs, except CCL19, and the prognosis of GC.

Conclusions: CCL19, CCL21, CCR7, CD70, EFNB3, EGR3, IL7R, LGALS1, and TNFRSF13C are PCGs are differentially expressed in GC and closely associated with regulatory T cells. They may affect the occurrence and development of GC through a variety of pathways, including regulation of immune infiltration and inflammation, and are of great potential research value.