Wang Kaile, Ye Rui, Bai Shanshan, Xiao Zhenna, Yang Lei, Li Jianzhuo, Tang Chenling, Sei Emi, Peng Jinyu, Casasent Anna K, Lin Steven H, Nagi Chandandeep, Thompson Alastair M, Krishnamurthy Savitri, Navin Nicholas E
Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; State Key Laboratory of RNA Innovation, Science and Engineering, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Radiation Oncology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; MD Anderson UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, USA.
Cell. 2025 Aug 26. doi: 10.1016/j.cell.2025.08.012.
Understanding 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, a high-genomic-resolution, high-throughput method to simultaneously profile the genome and transcriptome of thousands of single cells. 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. In contrast to bulk studies, wellDR-seq enabled the study of subclone-level gene-dosage relationships, which showed near-linear correlations in large chromosomal segments and extensive variation at the single-gene level. We identified dosage-sensitive and dosage-insensitive genes, including many breast cancer genes as well as sporadic copy-number aberrations in non-cancer cells. Overall, these data reveal complex relationships between copy number and gene expression in single cells, improving our understanding of breast cancer progression.
了解乳腺癌的上皮谱系以及基因型与表型的关系需要大规模直接测量同一单细胞的基因组和转录组。为实现这一目标，我们开发了wellDR-seq，这是一种高基因组分辨率、高通量的方法，可同时对数千个单细胞的基因组和转录组进行分析。我们对来自12例雌激素受体阳性乳腺癌的33646个单细胞进行了分析，并在多名患者中鉴定出显示管腔激素反应谱系的祖先亚克隆，这表明了潜在的起源细胞。与整体研究不同，wellDR-seq能够研究亚克隆水平的基因剂量关系，这种关系在大的染色体片段中显示出近线性相关性，而在单基因水平上则存在广泛变异。我们鉴定出了剂量敏感和剂量不敏感基因，包括许多乳腺癌基因以及非癌细胞中的散发性拷贝数畸变。总体而言，这些数据揭示了单细胞中拷贝数与基因表达之间的复杂关系，增进了我们对乳腺癌进展的理解。
