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Linking single cell genomes and transcriptomes at scale to decode breast cancer progression

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NIAID Data Ecosystem2026-05-02 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP494626
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Understanding the epithelial lineages of breast cancer and genotype-phenotype relationships requires direct measurements of the genome and transcriptome of the same single cells at scale. To achieve this, we developed wellDR-seq, the first high-genomic resolution, high-throughput method to simultaneously profile the genome and transcriptome of thousands of single cells in parallel. We profiled 33,646 single cells from 12 estrogen receptor-positive breast cancers, and identified ancestral subclones in multiple patients that showed a luminal hormone responsive lineage, indicating a potential cell-of-origin. Our data also identified sporadic copy number aberrations (CNAs) in the two luminal epithelial lineages and stromal cells. While gene expression was highly correlated with copy number in larger chromosome segments, our data reveals extensive variation at the single gene-level, reflecting differences in dosage-sensitive and dosage-insensitive genes. Overall, these data reveal the complex relationships between CNAs and gene expression in single cancer cells, improving our understanding of breast cancer progression.
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2025-05-11
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