Immunotyping the Tumor Microenvironment Reveals Molecular Heterogeneity for Personalized Immunotherapy in Cancer.

Journal: Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Published Date: May 28, 2025

Abstract

The tumor microenvironment (TME) significantly influences cancer prognosis and therapeutic outcomes, yet its composition remains highly heterogeneous, and currently, no highly accessible, high-throughput method exists to define it. To address this complexity, the TMEclassifier, a machine-learning tool that classifies cancers into three distinct subtypes: immune Exclusive (IE), immune Suppressive (IS), and immune Activated (IA), is developed. Bulk RNA sequencing categorizes patient samples by TME subtype, and in vivo mouse model validates TME subtype differences and differential responses to immunotherapy. The IE subtype is marked by high stromal cell abundance, associated with aggressive cancer phenotypes. The IS subtype features myeloid-derived suppressor cell infiltration, intensifying immunosuppression. In contrast, the IA subtype, often linked to EBV/MSI, exhibits robust T-cell presence and improved immunotherapy response. Single-cell RNA sequencing is applied to explore TME cellular heterogeneity, and in vivo experiments demonstrate that targeting IL-1 counteracts immunosuppression of IS subtype and markedly improves its responsiveness to immunotherapy. TMEclassifier predictions are validated in this prospective gastric cancer cohort (TIMES-001) and other diverse cohorts. This classifier could effectively stratify patients, guiding personalized immunotherapeutic strategies to enhance precision and overcome resistance.

Authors

  • Dongqiang Zeng
    Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Yunfang Yu
    Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Department of Medical Oncology, Breast Tumor Centre, Phase I Clinical Trial Centre, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China; Guangdong Provincial Key Laboratory of Cancer Pathogenesis and Precision Diagnosis and Treatment, Joint Big Data Laboratory, Department of Medical Oncology, Shenshan Medical Center, Memorial Hospital of Sun Yat-sen University, Shanwei, China; Institute for AI in Medicine and faculty of Medicine, Macau University of Science and Technology, Taipa, Macao, China; Department of Breast Surgery, The First Affiliated Hospital, Jinan University, Guangzhou, China.
  • Wenjun Qiu
    Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, 510515, P. R. China.
  • Qiyun Ou
    Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, 510515, P. R. China.
  • Qianqian Mao
  • Luyang Jiang
    Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, 510515, P. R. China.
  • Jianhua Wu
  • Jiani Wu
    School of Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Huiyan Luo
    Department of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
  • Peng Luo
    Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, PR China.
  • Wenchao Gu
    Department of Diagnostic and Interventional Radiology, University of Tsukuba, Ibaraki, Japan.
  • Na Huang
    Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, Tokyo, Japan.
  • Siting Zheng
    Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, 510515, P. R. China.
  • Shaowei Li
    Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, United States.
  • Yonghong Lai
    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.
  • Yiran Fang
    Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, 510515, P. R. China.
  • Qiongzhi Zhao
    Cancer Center, The Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, 528000, China.
  • Rui Zhou
    College of New Energy and Environment, Jilin University, Changchun 130021, China.
  • Huiying Sun
    Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, 510515, P. R. China.
  • Wei Zhang
    The First Affiliated Hospital of Nanchang University, Nanchang, China.
  • Jianping Bin
    Department of Cardiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, 510515, P. R. China.
  • Yulin Liao
    Department of Cardiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, 510515, P. R. China.
  • Masami Yamamoto
    Laboratory of Physiological Pathology, School of Veterinary Nursing and Technology, Nippon Veterinary and Life Science University, Tokyo, 180-8602, Japan.
  • Tetsuya Tsukamoto
    School of Medicine, Fujita Health University, 1-98 Dengakugakubo, Kutsukake cho, Toyoake City, Aichi, 470-1192, Japan.
  • Sachiyo Nomura
    Department of Gastrointestinal Surgery, Graduate School of Medicine, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
  • Min Shi
    School of Education, Fuzhou University of International Studies and Trade, 350000, China.
  • Wangjun Liao
    Cancer Center, The Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, 528000, China.

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