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

doi:10.1016/j.isci.2024.111340

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

iScience. 2024 Nov 13;27(12):111340. doi: 10.1016/j.isci.2024.111340. eCollection 2024 Dec 20.

Authors

Jiani Wu¹, Yuanyuan Wang¹, Zhenhua Huang¹, Jingjing Wu¹, Huiying Sun¹, Rui Zhou¹, Wenjun Qiu¹, Zilan Ye², Yiran Fang¹, Xiatong Huang¹, Jianhua Wu¹, Jianping Bin³, Yulin Liao³, Min Shi¹, Jiguang Wang^{4

5

6}, Wangjun Liao^{1

7

8}, Dongqiang Zeng^{1

7

8}

Affiliations

¹ Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China.
² Department of Colorectal Surgery, Shanghai Cancer Center, Fudan University, Shanghai 200032, P.R. China.
³ Department of Cardiology, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China.
⁴ 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.
⁵ HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute, Futian, Shenzhen 518000, P. R. China.
⁶ Hong Kong Center for Neurodegenerative Diseases, InnoHK, Hong Kong, SAR, P.R. China.
⁷ Cancer Center, the Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, Guangdong 528200, P.R. China.
⁸ 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.

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.

Keywords: Bioinformatics; Cancer; Omics.