Delineating copy number and clonal substructure in human tumors from single-cell transcriptomes.
Nat Biotechnol
; 39(5): 599-608, 2021 05.
Article
em En
| MEDLINE
| ID: mdl-33462507
ABSTRACT
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 copy number karyotyping of aneuploid tumors (CopyKAT) to estimate genomic copy number profiles at an average genomic resolution of 5 Mb from read depth in high-throughput single-cell RNA sequencing (scRNA-seq) data. We applied CopyKAT to analyze 46,501 single cells from 21 tumors, including triple-negative breast cancer, pancreatic ductal adenocarcinoma, 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 epithelial-to-mesenchymal transition, DNA repair, apoptosis and hypoxia. These data show that CopyKAT can aid in the analysis of scRNA-seq data in a variety of solid human tumors.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Neoplasias da Mama
/
Carcinoma Ductal Pancreático
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Variações do Número de Cópias de DNA
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Transcriptoma
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Evolução Clonal
Limite:
Humans
Idioma:
En
Revista:
Nat Biotechnol
Assunto da revista:
BIOTECNOLOGIA
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
Estados Unidos