作者: Julia E Altman , Amy L Olex , Emily K Zboril , Carson J Walker , David C Boyd
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摘要: 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 …