biostudies-literatureUnknown16Zhang N<h4>Background</h4>Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer characterized by a lack of hormone receptors, making it challenging to treat.<h4>Methods</h4>We generated a comprehensive spatial cell atlas of TNBC using a multi-omics integration approach that combined single-cell RNA sequencing (scRNA-seq) with spatial transcriptomics. This integration allowed us to characterize the spatial microenvironment and map the cell-type-specific distributions in TNBC tissues.<h4>Results</h4>Our analysis revealed significant heterogeneity in cell types and spatial distribution, with normal regions enriched in insulin resistance functions, whereas cancerous regions displayed diverse cell populations, including immune cells, cancer-associated fibroblasts (CAFs), and mFrontiers in genetics1614254https://www.ebi.ac.uk/biostudies/studies/S-EPMC12440963biostudies-literatureMulti-omics integration uncovers key transcriptional regulators in triple-negative breast cancer spatial heterogeneity.PMC12440963Yang LYZhang YZhang NChu HQLi YYYang RFRehman AZhou XGong SPCao HLfalseMulti-omics integration uncovers key transcriptional regulators in triple-negative breast cancer spatial heterogeneity.<h4>Background</h4>Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer characterized by a lack of hormone receptors, making it challenging to treat.<h4>Methods</h4>We generated a comprehensive spatial cell atlas of TNBC using a multi-omics integration approach that combined single-cell RNA sequencing (scRNA-seq) with spatial transcriptomics. This integration allowed us to characterize the spatial microenvironment and map the cell-type-specific distributions in TNBC tissues.<h4>Results</h4>Our analysis revealed significant heterogeneity in cell types and spatial distribution, with normal regions enriched in insulin resistance functions, whereas cancerous regions displayed diverse cell populations, including immune cells, cancer-associated fibroblasts (CAFs), and m2025-01-01T00:00:00Z20252026-06-03T12:06:47.604Z2026-04-27T03:11:31.424ZS-EPMC124409634096932510.3389/fgene.2025.1614254