Immunotyping the Tumor Microenvironment Reveals Molecular Heterogeneity for Personalized Immunotherapy in Cancer
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 (ORCID: https://orcid.org/0000-0001-9724-8325)
- Na Huang (ORCID: https://orcid.org/0000-0001-7961-0677)
- Wenchao Gu (ORCID: https://orcid.org/0000-0002-0967-1682)
- Tetsuya Tsukamoto (ORCID: https://orcid.org/0000-0002-7502-8724)
- Yulin Liao (ORCID: https://orcid.org/0000-0001-5961-390X)
- Min Shi (ORCID: https://orcid.org/0000-0002-5741-4293)
- Masami Yamamoto (ORCID: https://orcid.org/0000-0003-2071-7730)
- Peng Luo (ORCID: https://orcid.org/0000-0002-8215-2045)
- Luyang Jiang
- Yong-Hong Lai
- Yunfang Yu (ORCID: https://orcid.org/0000-0003-2579-6220)
- Jianping Bin (ORCID: https://orcid.org/0000-0003-4799-1502)
- Sachiyo Nomura (ORCID: https://orcid.org/0000-0003-4293-6205)
- Wenjun Qiu
- Jiani Wu (ORCID: https://orcid.org/0000-0001-7940-4179)
- Qianqian Mao (ORCID: https://orcid.org/0000-0003-3332-2922)
- Wei Zhang (ORCID: https://orcid.org/0000-0002-4375-0368)
- Hui Luo (ORCID: https://orcid.org/0000-0001-6312-9299)
- Shao-wei Li (ORCID: https://orcid.org/0000-0002-3276-1037)
- Jianhua Wu (ORCID: https://orcid.org/0000-0003-4142-8903)
- Rui Zhou (ORCID: https://orcid.org/0000-0002-0737-3040)
- Huiying Sun (ORCID: https://orcid.org/0000-0001-8916-9387)
- Qiyun Ou
- Wangjun Liao
- Qiongzhi Zhao
- Xiatong Huang
- Yiran Fang
- Siting Zheng
Institutions
- Macau University of Science and Technology (MO)
- Nippon Veterinary and Life Science University (JP)
- Fujita Health University (JP)
- Sun Yat-sen University (CN)
- Chiba University (JP)
- Sun Yat-sen Memorial Hospital (CN)
- Nanfang Hospital (CN)
- Zhujiang Hospital (CN)
- Sun Yat-sen University Cancer Center (CN)
- First Affiliated Hospital of Jinan University (CN)
- State Key Laboratory of Oncology in South China
- Southern Medical University (CN)
- The University of Tokyo (JP)
- South China University of Technology (CN)
Publication Details
- Journal
- Advanced Science
- Published
- 2025-05-28
- DOI
- https://doi.org/10.1002/advs.202417593
- Citations
- 14
- Primary Topic
- Cancer Immunotherapy and Biomarkers
- Type
- article
- Field-Weighted Citation Impact
- 14.64
Funders
- National Natural Science Foundation of China