A Three-Gene Prognostic Signature Driven by an ER Stress-Associated ceRNA Network: Integrating Single-Cell Transcriptomics and Cross-Platform Validation in Hepatocellular Carcinoma.

The progression and immune escape of HCC are closely regulated by endoplasmic reticulum stress (ERS). However, the associated ceRNA regulatory networks and their prognostic value remain to be systematically elucidated. Here, we sought to establish a prognostic signature derived from an ERS-associated ceRNA network and to investigate its relationship with the tumor immune microenvironment. We integrated TCGA-LIHC transcriptomic data with the MSigDB ERS gene set to identify ERS-associated differentially expressed genes and construct a ceRNA regulatory network. Using a forward search strategy with 10-fold cross-validation, we screened candidate genes to select the optimal prognostic combination and constructed a multigene Cox regression signature. External validation was performed in the independent microarray cohort GSE14520. By integrating single-cell transcriptomics, CIBERSORT, ESTIMATE, TIDE, and drug sensitivity analyses, we revealed immune microenvironment characteristics associated with this signature. Based on the ceRNA network's eight core ERS mRNAs, an optimal three-gene signature comprising