Comprehensive multi-omics and single-cell analysis reveals TM9SF1 as a biomarker in pan-cancer diagnosis and prognosis, with a special focus on hepatocellular carcinoma

TM9SF1, a transmembrane protein, has been linked to several cancers, but its role in oncology remains understudied. This study employed machine learning, TCGA, GTEx, and UALCAN databases to investigate TM9SF1 expression across various cancers. Prognostic value was assessed using Cox regression and Kaplan–Meier methods. Further analyses explored mutations, methylation, immune infiltration, and drug sensitivity. Results revealed that TM9SF1 expression was significantly elevated in multiple tumors and associated with poor prognosis. It was linked to increased mutation frequency and positive correlations with immune and stromal scores, as well as various immune cells and immunomodulators. TM9SF1 also correlated with tumor heterogeneity, stemness, and DNA methyltransferase genes. In hepatocellular carcinoma, it was identified as an independent risk factor, associated with drug sensitivity and closely related to Tex cells. This comprehensive analysis underscores TM9SF1’s potential as a prognostic marker and immunotherapy target, with significant implications for pan-cancer research.