REVIEW article
Front. Immunol.
Sec. Cancer Immunity and Immunotherapy
Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1667464
This article is part of the Research TopicExploring immune low-response states through single-cell technologies and spatial transcriptomicsView all 20 articles
Decoding Immune Low-Response States in Ovarian Cancer: Insights from Single-Cell and Spatial Transcriptomics for Precision Immunotherapy
Provisionally accepted
- 1Southwest Medical University, Luzhou, China
- 2Department of Oncology, Chongqing General Hospital, Chongqing University, Chongqing, China
- 3Western (Chongqing) Institute for Digital-Intelligent Medicine, Chongqing, China
- 4Sichuan Provincial Center for Gynecology and Breast Diseases (Gynecology), Affiliated Hospital of Southwest Medical University, Luzhou, China
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Ovarian cancer represents a typically immune "cold" tumor, where obvious immunosuppression, spatial T-cell exclusion, and cellular dysfunction collectively limit immunotherapy effectiveness. Especially in high-grade serous ovarian carcinoma (HGSOC), the immune low-response state is driven by complex interactions among tumor-associated macrophages (TAMs), suppressive stromal networks, and the T-cell compartment (regulatory T cells, Tregs, and exhausted effector T cells). Emerging multi-omics technologies—particularly single-cell RNA sequencing and spatial transcriptomics—have showed the heterogeneity and spatial immune organization underlying this suppressed state . Here, we integrate these datasets to describe TAM phenotypes and spatial niches, T-cell exhaustion, Tregs accumulation, NK-cell dysfunction, and stromal barriers that enforce exclusion. We then derive phenotype-guided combination strategies to remodel the tumor microenvironment and improve responsiveness to immune checkpoint blockade. This synthesis provides a concise, multi-dimensional framework for precision immunotherapy and for overcoming resistance in immune-low ovarian cancers.
Keywords: ovarian cancer, Immune low-response state, single-cell RNA sequencing, Spatial transcriptomics, Tumor-associated macrophages, T-cell exhaustion, Immunotherapy resistance
Received: 16 Jul 2025; Accepted: 29 Aug 2025.
Copyright: © 2025 Yan, Lu, Luo, Wang, Xu, Wang and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Ke Xu, Department of Oncology, Chongqing General Hospital, Chongqing University, Chongqing, China
Lexin Wang, Western (Chongqing) Institute for Digital-Intelligent Medicine, Chongqing, China
Qin Wang, Sichuan Provincial Center for Gynecology and Breast Diseases (Gynecology), Affiliated Hospital of Southwest Medical University, Luzhou, China
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