Prognostic prediction and immune correlation analysis of anoikis- and epithelial-mesenchymal transition-related genes in lung adenocarcinoma

Background: Anoikis resistance and epithelial-mesenchymal transition (EMT) are crucial factors in tumor invasiveness and metastasis in lung adenocarcinoma (LUAD). Identifying anoikis-EMT-related genes could be beneficial for predicting prognosis and immunotherapeutic efficacy in patients with LUAD. This study aims to establish and validate a novel prognostic signature based on anoikis-EMT-related genes for LUAD and to identify the potential biomarkers encapsulated within it. Methods: Anoikis-related genes and EMT-related genes were retrieved from the GeneCards and dbEMT 2.0 databases. Univariate Cox regression analysis and principal component analysis (PCA) were conducted to define anoikis and EMT levels. Gene expression and clinical information of patients with LUAD were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Univariate Cox regression and multivariate Cox regression analyses were conducted to construct a risk score model. Immune correlation and drug sensitivity analyses were performed to investigate the association of the risk score with the immune profile and antitumor treatment. Three essential genes in the model were examined for messenger RNA (mRNA) expression by reverse transcription-polymerase chain reaction (RT-PCR) and for protein levels via the Human Protein Atlas (HPA) database. Results: LUAD patients demonstrating low Anoikis Potential Index (API) combined with high EMT Potential Index (EPI) exhibited the poorest overall survival (OS). We further constructed a nine-gene prognostic risk model that combines anoikis and EMT. High-risk patients demonstrated significantly shorter survival duration. The clinical-prognostic nomogram accurately predicted outcomes at 1, 3, and 5 years. In addition, patients in low-risk group demonstrated superior immune responses to treatment and were more sensitive to commonly used chemotherapy drugs. Our validation studies confirmed upregulated expression of ANGPTL4, SLC2A1, and BIRC5 in LUAD, observed at both transcriptional and translational levels. Conclusions: The anoikis-EMT-based risk model effectively forecasts both OS and immunotherapy response in LUAD patients, accelerating the identification of groundbreaking molecular biomarkers and prospective molecular targets.