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Delineating copy number and clonal substructure in human tumors from single-cell transcriptomes

ABSTRACT: Delineating copy number and clonal substructure in human tumors from single-cell transcriptomes

PROVIDER: PRJNA625321 | ENA |

REPOSITORIES: ENA

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	SRR11546794.fastq.gz	Fastqsanger.gz

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Delineating copy number and clonal substructure in human tumors from single-cell transcriptomes

Project description:Single-cell transcriptomic analysis is widely used to study human tumors. However it remains challenging to distinguish normal cell types in the tumor microenvironment from malignant cells and to resolve clonal substructure within the tumor. To address these challenges, we developed an integrative Bayesian segmentation approach called CopyKAT (Copynumber Karyotyping of Aneuploid Tumors) to estimate genomic copy number profiles at an average genomic resolution of 5Mb from read depth in high-throughput scRNA-seq data. We applied CopyKAT to analyze 46,501 single cells from 21 tumors, including triple-negative breast cancer, pancreatic ductal adenocarcinomas, anaplastic thyroid cancer, invasive ductal carcinoma and glioblastoma to accurately (98%) distinguish cancer cells from normal cell types. In three breast tumors, CopyKAT resolved clonal subpopulations that differed in the expression of cancer genes such as KRAS and signatures including EMT, DNA repair, apoptosis and hypoxia. These data show that CopyKAT can aid the analysis of scRNA-seq data in a variety of solid human tumors.

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Project description:We analysed a cohort of pure DCIS cases treated only with wide local excision for genome-wide copy number and loss of heterozygosity using Affymetrix OncoScan® MIP arrays. Cases included those without recurrence within 6 years (n=25) and with recurrence between 1-5 years after diagnosis (n=15). Additional cases were excluded for low grade (n=6) or non-clonal recurrence (n=2). Recurrence tumour was available for 8 cases. Pure DCIS were broadly similar in copy number changes compared to invasive breast cancer, with the consistent exception of a greater frequency of ERBB2 amplification in DCIS. There were no significant differences in age or ER status between the cases with a recurrence versus those without. Overall, the DCIS cases with recurrence had more copy number events than the DCIS without recurrence. The increased copy number appeared non-random with several genomic regions showing an increase in frequency in recurrent cases including 20q gain, ERBB2 amplification and 15q loss. Copy number changes may provide prognostic information for DCIS recurrence but validation in additional cohorts is required.

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