Unraveling tumor microenvironments with spatial genomics: Implications for precision breast cancer therapy
Year: 2025
Type: article
Abstract: Spatial genomics has revolutionized breast cancer research by mapping gene expression within the tumor microenvironment, offering unprecedented insights into the molecular and cellular interactions that drive tumor progression and therapeutic response across luminal A, luminal B, HER2-positive, and triple-negative subtypes. Unlike traditional genomic methods, spatial genomics preserves tissue architecture, revealing subtype-specific TME features, such as immune-rich regions in triple-negative breast cancer and stromal-dense environments in HER2-positive tumors. This review explores spatial genomics technologies, including Visium, GeoMx, and MERFISH, which enable precise TME analysis, highlighting their role in identifying biomarkers like PD-L1 and TGF-β for targeted therapies and immunotherapies. By elucidating TME-driven resistance mechanisms, such as hypoxia in triple-negative tumors or stromal remodeling in HER2-positive cases, spatial genomics informs clinical trials and combination therapies, enhancing patient stratification and treatment efficacy. Despite its promise, challenges including limited resolution, complex data analysis, and high costs hinder clinical adoption. Emerging technologies, artificial intelligence, and multi-omics integration offer solutions, promising higher precision and scalability. This review underscores spatial genomics’ transformative potential to bridge research and clinical practice, paving the way for personalized breast cancer therapies tailored to the dynamic TME, with future advancements poised to redefine treatment paradigms and improve patient outcomes.
Authors: Amina Suleiman Kamsalem, Obianujunwa Mercy Ubah, Tobiloba Philip Olatokun, Regina Omodolapo Oluwaniyi, Olivia Ajifa Philips, Damilola Samuel Ojo-Omoniyi, Omolola Lolade Oluwasakinju
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W4412639118
