BackgroundLung squamous cell carcinoma (LUSC) represents a major subtype of non-small cell lung cancer (NSCLC), a leading contributor to cancer-related mortality. Epithelial-mesenchymal transition (EMT)-associated genes have been implicated in poor survival and metastatic gene expression in LUSC. Long non-coding RNAs (lncRNAs) are known to facilitate tumor progression and metastasis via EMT regulation. However, the prognostic significance and biological functions of EMT-associated lncRNAs in LUSC remain to be elucidated.MethodsIn this study, we aimed to develop an EMT-related lncRNA prognostic signature (EMT-LPS) utilizing RNA transcription data from LUSC patients in The Cancer Genome Atlas (TCGA) database, along with corresponding clinical characteristics. Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, and Cox regression were employed to validate and assess the model. Furthermore, we confirmed the independent prognostic value of key genes in EMT-LPS using Gene Expression Profiling Interactive Analysis (GEPIA). Additionally, we proposed a novel LUSC classification system based on EMT-related lncRNA expression patterns, evaluating the prognostic profile, tumor microenvironment, and immunotherapy sensitivity of each subtype.ResultsA prognostic signature comprising twelve genes was constructed, and patients were stratified into high and low-risk groups according to their risk scores. Cox regression analysis revealed that the risk score served as an independent prognostic factor. A nomogram was generated to predict LUSC patient survival rates. Distinct subtypes exhibited varying tumor purity, immunogenicity, and immunotherapy drug sensitivity.ConclusionsOur findings underscore the relevance of EMT-related lncRNAs in LUSC and their potential utility in guiding immunotherapy strategies. The EMT-LPS and novel LUSC typing scheme provide a new perspective for understanding the biological functions and prognostic role of EMT-related lncRNAs in LUSC.