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

Autor: 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
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: iScience, Vol 27, Iss 12, Pp 111340- (2024)
Druh dokumentu: article
ISSN: 2589-0042
DOI: 10.1016/j.isci.2024.111340
Popis: Summary: 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.
Databáze: Directory of Open Access Journals