CGB5, INHBA and TRAJ19 Hold Prognostic Potential as Immune Genes for Patients with Gastric Cancer.

Dig Dis Sci

Department of Gastroenterology, The Second People's Hospital of Liaocheng, The Second Hospital of Liaocheng Affiliated to Shandong First Medical University, No. 306, Jiankang Road, Liaocheng, 252600, Shandong Province, People's Republic of China.

Published: March 2023

Background: Gastric cancer (GC) seriously threatens people's health and life quality worldwide.

Aim: The current study sought to explore prognostic immune genes and their regulatory network in GC.

Methods: First, expression data in GC and normal samples were analyzed based on bioinformatics analysis. Immune-related genes were identified and confirmed with univariate/multivariate Cox analysis and receiver-operating characteristic curve. The upstream transcription factors of immune genes were subsequently predicted, and their regulatory network was constructed. GC and adjacent normal tissues were obtained from 76 patients with GC to determine the expression patterns of immune genes and their correlation with overall prognosis. CD8 T-cell infiltration of patients with high or low risk was detected by means of immunohistochemistry.

Results: Bioinformatics analysis highlighted 3689 differentially expressed genes in GC, including 87 immune genes, 8 of which were significantly associated with patient survival. CGB5 and INHBA were high-risk genes, while TRAJ19 was identified as a low-risk gene, all of which were found to be regulated by 11 different transcription factors. Furthermore, CGB5 and INHBA exhibited negative correlation with the prognosis of GC patients; however, TRAJ19 was positively correlated with GC patient prognosis. The incidence of lymph node metastasis was higher, the pathological stage was advanced and the infiltrated CD8 T cells were fewer in the high-risk GC group.

Conclusions: Overall, our findings identified the key roles of CGB5, INHBA and TRAJ19 in prognosis GC patients, serving as an important gene set for prognostic prediction.

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Source
http://dx.doi.org/10.1007/s10620-022-07513-9DOI Listing

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