Tumor microenvironment assessment-based signatures for predicting response to immunotherapy in non-small cell lung cancer

• DOI: 10.1016/j.isci.2024.111340
• Publication Date: 2024-11-13T07:46:48Z
• Authors: Jiani Wu; Yuanyuan Wang; Zhenhua Huang; Jingjing Wu; Huiying Sun; Rui Zhou; Wenjun Qiu; Zilan Ye; Yiran Fang; Xiatong Huang; Jianhua Wu; Jianping Bin; Yulin Liao; Min Shi; Jiguang Wang; Wangjun Liao; Dongqiang Zeng
• Keywords: Cancer Immunotherapy

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 who may benefit from immunotherapy. We retrospectively collected tumor tissues 65 with advanced NSCLC before treatment, and performed transcriptomic genomic analysis. By performing single-sample gene set enrichment analysis, we constructed a predictor named IKCscore based on microenvironment characteristics. is robust biomarker predicting response immunotherapy, its predictive capacity was confirmed public datasets across different types (N = 892), including OAK, POPLAR, IMvigor210, GSE135222, GSE126044, Kim cohorts. High characterized by inflammatory phenotype higher T receptor diversity. The exhibits promise as bioindicator that can predict efficacy both immunotherapy immunotherapy-based combination therapies, while providing guidance for personalized therapeutic strategies patients.