Abstract
Enhancer RNAs (eRNAs) are abundant in most human cells and tissues, and quantifying eRNAs has become a robust approach for biomarker discovery. While eRNAs play crucial roles in regulating biological processes and cancer progression, their functions in lung adenocarcinoma (LUAD) remain poorly understood. Here, we developed a LUAD prognostic model based on eRNA expression data from The Cancer Genome Atlas (TCGA). Through rigorous validation, a 7-eRNA signature was identified, which robustly stratified LUAD patients into high-risk and low-risk groups in both training and testing sets. Functional analyses revealed distinct enrichment of pathways related to amino acid biosynthesis, ribosome biogenesis, and proteasome activity in high-risk patients. Somatic mutation profiling highlighted TP53 and TTN as frequently mutated genes, while drug sensitivity prediction identified four potential therapeutic agents (including AZD4547 and Nutlin-3a) for high-risk individuals. Collectively, this study constructed a 7-eRNA prognostic model for LUAD, providing a powerful tool for clinical risk assessment and uncovering eRNA-mediated regulatory mechanisms.