Single‐cell transcriptional atlas of human breast cancers and model systems

作者：Julia E. Altman, Amy L. Olex, Emily K. Zboril, Carson J. Walker, David C. Boyd, Rachel K. Myrick, Nicole S. Hairr, Jennifer E. Koblinski, Madhavi Puchalapalli, Bin Hu, Mikhail G. Dozmorov, Xi Chen, Yunshun Chen, Charles M. Perou, Brian D. Lehmann, Jane E. Visvader, J. Chuck Harrell · 发表于：Clinical and Translational Medicine · 年份：2024 · DOI：10.1002/ctm2.70044 · 被引用次数：9 · 研究领域：Single-cell and spatial transcriptomics、Cancer Cells and Metastasis、Cancer Genomics and Diagnostics

BACKGROUND: Breast cancer's complex transcriptional landscape requires an improved understanding of cellular diversity to identify effective treatments. The study of genetic variations among breast cancer subtypes at single-cell resolution has potential to deepen our insights into cancer progression. METHODS: In this study, we amalgamate single-cell RNA sequencing data from patient tumours and matched lymph metastasis, reduction mammoplasties, breast cancer patient-derived xenografts (PDXs), PDX-derived organoids (PDXOs), and cell lines resulting in a diverse dataset of 117 samples with 506 719 total cells. These samples encompass hormone receptor positive (HR+), human epidermal growth factor receptor 2 positive (HER2+), and triple-negative breast cancer (TNBC) subtypes, including isogenic model pairs. Herein, we delineated similarities and distinctions across models and patient samples and explore therapeutic drug efficacy based on subtype proportions. RESULTS: PDX models more closely resemble patient samples in terms of tumour heterogeneity and cell cycle characteristics when compared with TNBC cell lines. Acquired drug resistance was associated with an increase in basal-like cell proportions within TNBC PDX tumours as defined with SCSubtype and TNBCtype cell typing predictors. All patient samples contained a mixture of subtypes; compared to primary tumours HR+ lymph node metastases had lower proportions of HER2-Enriched cells. PDXOs exhibited differences in metabolic-relat...