AUTHOR=Sun Shihao , Chen Shuang , Li Kaiyuan , Zhang Ge , Wang Nan , Xu Yijia , Wang Xinxing , Chi Jiangrui , Li Lin , Sun Yi 

TITLE=Resolving tumor microenvironment heterogeneity to forecast immunotherapy response in triple-negative breast cancer through multi-scale analysis

JOURNAL=Frontiers in Oncology

VOLUME=Volume 15 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2025.1538574

DOI=10.3389/fonc.2025.1538574

ISSN=2234-943X

ABSTRACT=BackgroundImmunotherapy has been used in the clinical management of TNBC. While BRCA1 mutations are associated with immunotherapy response, the therapeutic outcomes in TNBC patients are not promising.MethodsThis study integrated spatial, single-cell, and bulk RNA-seq data to explore the role of BRCA1 in reshaping the TNBC microenvironment. Through multi-scale analysis, phenotype changes and potential biomarkers in cancer-associated fibroblasts (CAF) were identified. To validate these findings at the protein level, we employed high-resolution, label-free proteomics sequencing in our in-house cohort, providing critical real-world validation. A predictive system for response to ICIs was constructed through the step-by-step machine learning pipeline.ResultsCompared to BRCA1 mutant patients, BRCA1 wild-type patients experienced increased T-cell exhaustion and dendritic cell tolerance. We identified a MEG3+ pre-CAF subgroup via pseudo-time analysis. Moreover, ISG15 may serve as an immunoregulatory biomarker, and the proposed predictive model demonstrated potential in forecasting immunotherapy response, although further validation is needed.ConclusionsThis study highlighted the cellular heterogeneity of TNBC and identified ISG15 as a candidate biomarker potentially associated with treatment response. The ISG15-based predictive system might provide a robust framework for predicting ICI response.