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• W4282935562 abstract "Abstract Advances in single cell copy number sequencing technologies have enabled the generation of data on hundreds to thousands of cells in parallel. Despite the rapid development in these technologies, there is a significant bottleneck for the analysis of the resulting large-scale datasets. Here we present CopyKit, a comprehensive and user-friendly toolkit for the analysis of single cell copy number data. CopyKit provides a suite of tools for pre-processing, QC, copy number inference, and subclone clustering to delineate the clonal diversity of tumors. We performed single cell copy number sequencing of 2977 cells from two breast tumor liver metastasis. CopyKit identified 4 and 12 subclonal populations, including amplification of PDGFRA, KRAS, and MYC as well as losses of PTEN, FOXO1, RB1, and BRCA1, many of which were spatially segregated in the tumor mass of the two tumors. Additionally, we applied CopyKit to study metastatic dissemination from a primary ER+ breast tumor with two matched metastatic sites and two colorectal carcinomas with matched liver metastatic tissues. This analysis demonstrated that the breast metastatic tumors selected for subclones that were lacking ERBB2 amplification in the primary site. Furthermore, the liver metastasis had deletions of chromosomes 18, 19, and 20p and a focal gain of FGFR1, while the pleural effusion acquired two additional focal gains on chromosome 8, including MYC. The colorectal metastatic tumors diverged from the primary tumor with copy number events affecting important cancer genes such as gain of SOX4, MYC, CDK8 and deletions of FHIT, CHEK1, and CHEK2. Collectively, this study shows that CopyKit provides a comprehensive set of tools for resolving clonal substructure from single cell copy number data for diverse applications in cancer biology. Citation Format: Darlan Conterno Minussi, Junke Wang, Aislyn Schalck, Yun Yan, Hua-Jun Wu, Cheng Peng, Min Hu, Emi Sei, Mary Edgerton, Hui Chen, Alejandro Contreras, David Hui, Senthil Damodaran, Scott Kopetz, Bora Lim, Nicholas Navin. Resolving clonal substructure from single cell genomic data in primary and metastatic tumors using CopyKit [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1210." @default.
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• W4282935562 date "2022-06-15" @default.
• W4282935562 modified "2023-10-07" @default.
• W4282935562 title "Abstract 1210: Resolving clonal substructure from single cell genomic data in primary and metastatic tumors using CopyKit" @default.
• W4282935562 doi "https://doi.org/10.1158/1538-7445.am2022-1210" @default.
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