Machine learning, WGCNA and molecular docking identify SLC transporter genes as biomarkers and drug targets in Helicobacter pylori-associated carcinogenesis.

Solute carrier (SLC) family genes govern transmembrane transport and cellular metabolism, yet their systematic roles from Helicobacter pylori infection to gastric cancer (GC) remain undefined. By integrating multiple GEO datasets with weighted gene co-expression network analysis, differential expression, and machine learning algorithms, we identified seven core SLC genes (SLC9A9, SLC43A2, SLC16A6, SLC7A14, SLC28A3, SLC4A11, SLC5A2) for H. pylori infection and nine (SLC1A3, SLC2A3, SLC15A3, SLC19A3, SLC2A12, SLC16A4, SLC25A4, SLC9A7, SLC28A3) for GC. Logistic regression models achieved high diagnostic accuracy (AUC = 0.976 and 0.874, respectively). Immune infiltration analysis revealed distinct correlation patterns: SLC4A11 and SLC5A2 associated with activated mast cells, neutrophils, and M2 macrophages in infection, while SLC1A3 and SLC2A3 correlated broadly with M1/M2 macrophages and activated CD4+ T cells in GC. Enrichment analyses confirmed involvement in transmembrane transport, immune-related pathways, and cancer signaling. Transcription factor prediction identified CEBPB, RELB, and STAT5A as key upstream regulators. Molecular docking demonstrated strong binding affinities between SLC proteins and repurposable compounds (3'-azido-3'-deoxythymidine, CHEMBL1182312, quinine). This study provides the first systematic characterization of SLC family expression across the H. pylori-GC continuum, identifying potential diagnostic biomarkers and therapeutic targets that warrant further experimental validation.