Prediction of prognosis and immunotherapy response in lung adenocarcinoma based on CD79A, DKK1 and VEGFC

Tumor immune microenvironment (TIME) is crucial for tumor initiation, progression, and metastasis; however, its relationship with lung adenocarcinoma (LUAD) is unknown. Traditional predictive models screen for biomarkers that are too general and infrequently associated with immune genes. RNA sequencing data of LUAD patients and immune-related gene sets were retrieved from public databases. Using the common genes shared by The Cancer Genome Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort), differential gene expression analysis, survival analysis, Lasso regression analysis, and univariate and multivariate Cox regression analyses were performed to generate a novel risk score model. LUAD cohort in International Cancer Genome Consortium (ICGC), GSE68465 cohort in Gene Expression Omnibus (GEO) and an immunohistochemical assay were used to validate the key genes constructed risk score. The LUAD-related prognosis, clinical indicators, immune infiltrate characteristics, response to immunotherapy, and response to chemotherapeutic agents in different risk groups were evaluated by CIBERSORT, ImmuCellAI, pRRophetic and other tools. The risk score model was constructed using CD79a molecule (CD79A), Dickkopf WNT signaling pathway inhibitor 1 (DKK1), and vascular endothelial growth factor C (VEGFC). High risk score was identified as a negative predictor for overall survival (OS) in subgroup analyses with tumor stage, TNM classification, therapy outcome, and ESTIMATE scores (P