Multi-omics characterization of RNF157 expression patterns in hepatocellular carcinoma and development of an RNF157-associated prognostic signature.

Background: Hepatocellular carcinoma (HCC) remains a highly lethal malignancy due to tumor heterogeneity and treatment resistance. This study characterized E3 ubiquitin ligase RNF157 expression patterns in HCC through integrated multi-omics and single-cell analysis, developed an RNF157-associated prognostic signature, and explored its relationship with tumor microenvironment (TME) populations. Methods: Clinical and RNA expression data were obtained from TCGA, GEO databases, and scRNA-seq datasets (GSE149614). Protein-protein interaction networks were constructed via STRING database. Based on single-cell analysis revealing RNF157's heterogeneous expression in cancer-associated fibroblasts (CAFs) and tumor-associated macrophages (TAMs), we performed validation experiments using lentiviral shRNAs targeting FAP in CAFs and CD11b in TAMs. All experiments included appropriate controls with three independent biological replicates. Results: Single-cell analysis identified significant heterogeneity in HCC samples, with RNF157 showing variable expression across cell types within the TME. The prognostic model demonstrated moderate predictive performance (AUC: 0.65-0.78 for 1-5 years survival). Flow cytometry confirmed successful experimental manipulation of TME populations, with reduced FAP + CAFs (45.54%→22.01%) and CD11b+ TAMs (35.03%→24.18%) following respective gene depletion. Conclusion: We characterized RNF157 expression patterns in HCC at single-cell resolution and established a prognostic signature with moderate predictive performance requiring independent validation before clinical application.