Abstract
Immunotherapy has significantly altered the treatment paradigm of non-small cell lung cancer (NSCLC), but not all patients experience durable benefits. Predictive biomarkers are needed to identify patients who may benefit from immunotherapy. We retrospectively collected tumor tissues from 65 patients with advanced NSCLC before treatment, and performed transcriptomic and genomic analysis. By performing single-sample gene set enrichment analysis, we constructed a predictor named IKCscore based on the tumor microenvironment characteristics. IKCscore is a robust biomarker predicting response to immunotherapy, and its predictive capacity was confirmed from public datasets across different cancer types (N = 892), including OAK, POPLAR, IMvigor210, GSE135222, GSE126044, and Kim cohorts. High IKCscore was characterized by inflammatory tumor microenvironment phenotype and higher T cell receptor diversity. The IKCscore exhibits promise as a bioindicator that can predict the efficacy of both immunotherapy and immunotherapy-based combination therapies, while providing guidance for personalized therapeutic strategies for advanced NSCLC patients.