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

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 (<i>N</i> = 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.

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Publication Details

Journal
iScience
Published
2024-11-13
DOI
https://doi.org/10.1016/j.isci.2024.111340
Citations
7
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
1.98

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article

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

Dongqiang Zeng, Yulin Liao, Wangjun Liao, Jingjing Wu et al.
7 citations
iScience
Cancer Immunotherapy and Biomarkers
1.98
article

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

Dongqiang Zeng, Yulin Liao, Wangjun Liao, Jingjing Wu, Zilan Ye, Jianping Bin, Wenjun Qiu, Jiani Wu, Minmin Shi, Yuanyuan Wang, Rui Zhou, Jian Wu, Yiran Fang, Huiying Sun, Zhenhua Huang, Ji-Guang Wang, Xiatong Huang
article en
7 citations

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 (<i>N</i> = 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.

iScienceVol. 27(12)
Fudan University Shanghai Cancer Center (CN), HKUST Shenzhen Research Institute (CN), Nanfang Hospital (CN), City University of Hong Kong, Shenzhen Research Institute (CN), Foshan Hospital of TCM (CN), Institute for Neurodegenerative Disorders (US), Southern Medical University (CN), University of Hong Kong (HK), South China University of Technology (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation
Good health and well-being
Openalex Percentile: Top 11%
Cancer Immunotherapy and Biomarkers
1.98
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