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Series GSE261713 Query DataSets for GSE261713
Status Public on Apr 22, 2024
Title Linking single cell genomes and transcriptomes at scale to decode breast cancer progression [scRNA-seq]
Organism Homo sapiens
Experiment type Expression profiling by high throughput sequencing
Summary Understanding epithelial lineages in breast cancer and genotype-phenotype interactions 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 whole genome and transcriptome of thousands of single cells. We profiled 17,427 single cells in 6 ER-positive breast cancer patients, which identified ancestral subclones in three patients that were from the luminal hormone responsive lineage, indicating a cell-of-origin. Our data show that somatic copy number aberrations (CNAs) were predominantly associated with the luminal epithelial lineages. By studying the impact of subclonal CNAs on gene dosage, we found that in addition to the expected expression changes within CNA regions, many expression differences in subclones also occur outside of CNA regions. Overall, these data link the genotypes and phenotypes together to resolve complex relationships and improve our understanding of breast cancer progression.
Overall design We developed a high-genomic resolution, high-throughput nanowell single cell DNA & RNA sequencing method (wellDR-seq), that can simultaneously profile the whole genome and transcriptome from thousands of single cells. We first demonstrated wellDR-seq was capable of generating comparable data quality as unimodal scRNA-seq and scDNA-seq technologies using MDA-MB-231 cell line. We then applied it to profile 6 ER+ breast cancer patients, which identified ancestral cancer subclones and their epithelial lineages, normal epithelial cell states with somatic CNAs and revealed the impact of subclonal CNAs on gene dosage, providing insight into the complex relationship between DNA copy number and gene expression in cancer cells.
Please note that the DNA raw data was deposited to SRA (PRJNA1086561).
Contributor(s) Wang K, Ye R, Navin N
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Submission date Mar 15, 2024
Last update date Apr 22, 2024
Contact name Nicholas Navin
Organization name MD anderson Cancer Center
Department Systems Biology
Lab Navin Lab
Street address 6565 MD Anderson Blvd
City Houston
State/province Texas
ZIP/Postal code 77030
Country USA
Platforms (1)
GPL30173 NextSeq 2000 (Homo sapiens)
Samples (18)
GSM8149395 MDA231_chip1
GSM8149396 MDA231_chip2
GSM8149397 ECIS25T_chip1
BioProject PRJNA1088478

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Supplementary file Size Download File type/resource
GSE261713_RAW.tar 2.5 Gb (http)(custom) TAR (of RDS)
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Raw data are available in SRA

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