Tumor microenvironment assessment-based signatures for predicting response to immunotherapy in non-small cell lung cancer
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
Affiliations
Jiani Wu
Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
Yuanyuan Wang
Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
Zhenhua Huang
Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
Jingjing Wu
Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
Huiying Sun
Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
Rui Zhou
Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
Wenjun Qiu
Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
Zilan Ye
Department of Colorectal Surgery, Shanghai Cancer Center, Fudan University, Shanghai 200032, P.R. China
Yiran Fang
Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
Xiatong Huang
Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
Jianhua Wu
Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
Jianping Bin
Department of Cardiology, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
Yulin Liao
Department of Cardiology, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
Min Shi
Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
Jiguang Wang
Department of Chemical and Biological Engineering, Division of Life Science and State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Hong Kong, SAR 999077, P.R. China; HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute, Futian, Shenzhen 518000, P. R. China; Hong Kong Center for Neurodegenerative Diseases, InnoHK, Hong Kong, SAR, P.R. China
Wangjun Liao
Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China; Cancer Center, the Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, Guangdong 528200, P.R. China; Foshan Key Laboratory of Translational Medicine in Cancer, the Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, Guangdong 528200, P.R. China; Corresponding author
Dongqiang Zeng
Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China; Cancer Center, the Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, Guangdong 528200, P.R. China; Foshan Key Laboratory of Translational Medicine in Cancer, the Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, Guangdong 528200, P.R. China; Corresponding author
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.
