The tumor microenvironment (TME) is a critical regulator of breast cancer progression and therapeutic response. While single-cell and spatial omics have revolutionized our understanding of TME heterogeneity, the functional validation of these discoveries and their translation into clinical benefits rely heavily on advanced experimental models. The integration of in vitro, sophisticated in vitro systems (e.g., organoids, spheroids), complex in vivo models, and cutting-edge computational analyses is now driving a new wave of progress.

This special issue is positioned at this critical nexus. It will highlight how these diverse model systems are being used to deconvolute the complex cellular crosstalk of the breast TME, to functionally validate newly identified therapeutic targets, and to develop biomarkers that can be tested in clinical trials. By focusing on the pipeline from model-based discovery to clinical application, this issue will provide a unique and timely resource, synthesizing the state of the art at a time when the first therapeutics targeting non-cancerous TME components are entering clinical evaluation.

This special issue aims to provide a comprehensive overview of how advanced experimental and computational models are elucidating breast cancer TME biology and accelerating clinical translation. Specifically, we welcome the submission of Original Research, Review, Mini Review, and Perspective articles that will:

• Showcase Model Systems: Highlight the application and integration of state-of-the-art models—including 3D co-cultures, patient-derived organoids (PDOs), spheroids, and genetically engineered mouse models (GEMMs) as well as regular in vitro studies—in recapitulating and studying human TME complexity.

• Elucidate Mechanisms: Use insights from these models to dissect the dynamic, functional crosstalk between cancer cells, immune cells, stromal fibroblasts, and the extracellular matrix that underlies therapy resistance and metastasis.

• Validate Discoveries: Feature research where hypotheses generated from single-cell or spatial omics data are functionally validated in sophisticated experimental systems.

• Drive Translation: Spotlight the use of PDOs and other models as "avatars" for drug screening and biomarker development, directly informing clinical trial design.

• Synthesize Evidence: Include systematic reviews and meta-analyses to provide definitive summaries of existing clinical and pre-clinical data on TME-targeting strategies.

Are you interested in contributing a manuscript to this Research Topic?

The Breast Cancer Tumor Microenvironment: From Model Systems to Clinical Translation