Purpose: Semaphorin 5A (SEMA5A) and autophagy-related genes (ARGs) are pivotal in the pathogenesis of gastric cancer (GC). However, the potential regulatory role of SEMA5A in autophagy via its associated ARGs and the underlying molecular mechanisms remain unresolved.<br /> Patients and Methods: GC-related datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were analyzed to identify differentially expressed genes (DEGs) between GC and control samples. The intersection of DEGs with ARGs produced candidate genes, which were further analyzed using Spearman correlation with SEMA5A to identify signature genes. Stratification of GC samples based on signature gene expression, followed by Kaplan-Meier survival analysis, identified key genes. Subsequent analyses, including gene set enrichment analysis (GSEA), immune infiltration, and immune checkpoint evaluation, were conducted on the key genes and SEMA5A. The mRNA expression level was quantified using real-time quantitative polymerase chain reaction (RT-qPCR).<br /> Results: Ninety candidate genes were identified for Spearman correlation with SEMA5A, revealing TNFSF11, BMP6, ITPR1, and DLC1 with correlation coefficients exceeding 0.3. Survival analysis underscored DLC1 and BMP6 as key genes due to significant prognostic differences. GSEA implicated SEMA5A, BMP6, and DLC1 in the ECM receptor interaction pathway. Immune infiltration analysis indicated a negative correlation of SEMA5A and BMP6 with M1 macrophages, while DLC1 exhibited the strongest association with the immune checkpoint PDCD1LG2 (p < 0.05, cor = 0.43). The mRNA expression level of SEMA5A was significantly upregulated in AGS parental cells compared to GES-1 cells (p < 0.01), whereas DLC1 and BMP6 mRNA levels were markedly downregulated in AGS parental cells relative to GES-1 (p < 0.0001).<br /> Conclusion: ARGs BMP6 and DLC1, associated with SEMA5A, were identified, and their prognostic significance in GC was demonstrated. Additionally, their regulatory mechanisms were further elucidated through immune infiltration analysis and molecular network construction, providing a theoretical foundation for future research on the molecular mechanisms in patients with GC.