Identification of SLIT3 as a novel prognostic biomarker for gastric cancer and analysis of its immunomodulatory role

Gastric cancer (GC) is a common malignancy with increasing incidence rates but lacks effective biomarkers. This study aims to validate SLIT3 as a biomarker for predicting GC progression and elucidate potential molecular mechanisms. Microarray data were collected to analyze differentially expressed genes between GC and adjacent tissues, as well as between early gastric cancer (EGC) and advanced gastric cancer (AGC). A protein interaction network was constructed via the STRING database. The MCC algorithm identified hub genes. Survival analysis was conducted using the K-M method. Single-cell data were processed with Seurat V4. ROC curves assessed gene predictive performance. The CIBERSORT algorithm depicted the tumor immune cell infiltration landscape. PCR determined gene expression in GC tissues. A protein interaction network of differentially expressed genes was constructed, identifying SLIT3 as a hub gene through the MCC algorithm. Single-cell transcriptomics showed low SLIT3 expression in GC. Patients with low SLIT3 expression had poor survival and high recurrence rates. SLIT3 was highly methylated in GC, and its methylation level was positively correlated with AKT1 expression and M2 macrophage infiltration, while its gene expression was significantly negatively correlated with both. Furthermore, increased communication between GC epithelial cells and macrophages occurs in the SLIT3 low-expression group. Downstream differentially expressed genes in the low SLIT3 group were enriched in the AKT signaling pathway. In a GC patient cohort, RT-qPCR showed a significant negative correlation between SLIT3, AKT, and CD163 expressions. SLIT3 serves as a biomarker for predicting GC progression. The loss of SLIT3 is significantly negatively correlated with AKT1 expression and M2 macrophage infiltration.