Identification and prognostic value of tryptophan metabolism-related genes in gastric carcinogenesis

Yongfu ShaoHaotian DongXuan YuGuoliang YeJianing Yan^*

• Affiliated Hospital, Ningbo University, Ningbo, China

Gene regulation and functional mechanisms of tryptophan metabolites in gastric carcinogenesis and their clinical importance have not been fully elucidated. Functional enrichment of tryptophan metabolism-associated differential genes was filtered and analyzed from databases. A prognostic risk model containing 11 metabolism-associated genes (MAGs) was established using Lasso-Cox regression. The association of key genes with immune cell infiltration, drug sensitivity, specific signaling pathways, prognostic prediction and miRNA regulatory networks was investigated. CellChat was utilized to analyze differences in cell subpopulations and cell communication between high-risk and low-risk groups as well as the variations in exhaustion factor scores and cytokine scores in single cells. Expression levels of key genes were validated through PCR in paired GC tissues, and biological functions of key genes were verified in vitro experiments. Total 11 key prognostic genes, GLA, MALAT1, TCIRG1, NMB, HBA2, HBB, ANXA5, RNASE1, APOD, NRP1 and ZFP36, that are involved in tryptophan metabolism of GC were identified. Additionally, a prognostic model associated with tryptophan metabolism in GC was constructed. The prognostic risk model was an independent prognostic factor that not only effectively distinguished patients in the high-risk group from those in the low-risk group but also significantly correlated with patients' clinical prognosis, tumor immune microenvironment, sensitivity to chemotherapeutic agents and clinically important indicators. The risk model has been validated across multiple datasets, and its predictive analysis results were consistent with bioinformatics analysis, demonstrating the robustness and accuracy of the tryptophan metabolism-related GC prognostic model. Knocking down APOD and TCIRG1 expression significantly inhibited cell proliferation, colony formation and invasion of GC. Our study explored a prognostic model and molecular network mechanism associated with tryptophan metabolism in GC using multiple datasets to facilitate a novel perspective on the pathogenesis, clinical diagnosis, treatment and prognostic evaluation of GC.