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Journal article

Unravelling intratumoral heterogeneity through high-sensitivity single-cell mutational analysis and parallel RNA sequencing

Abstract:
Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for resolving transcriptional heterogeneity. However, its application to studying cancerous tissues is currently hampered by the lack of coverage across key mutation hotspots in the vast majority of cells; this lack of coverage prevents the correlation of genetic and transcriptional readouts from the same single cell. To overcome this, we developed TARGET-seq, a method for the high-sensitivity detection of multiple mutations within single cells from both genomic and coding DNA, in parallel with unbiased whole-transcriptome analysis. Applying TARGET-seq to 4,559 single cells, we demonstrate how this technique uniquely resolves transcriptional and genetic tumor heterogeneity in myeloproliferative neoplasms (MPN) stem and progenitor cells, providing insights into deregulated pathways of mutant and non-mutant cells. TARGET-seq is a powerful tool for resolving the molecular signatures of genetically distinct subclones of cancer cells.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.molcel.2019.01.009

Authors

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Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
RDM
Sub department:
Weatherall Insti. of Molecular Medicine
Role:
Author
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
RDM
Sub department:
Weatherall Insti. of Molecular Medicine
Role:
Author
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
RDM
Sub department:
Weatherall Insti. of Molecular Medicine
Role:
Author
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
RDM
Sub department:
RDM Clinical Laboratory Sciences
Role:
Author
ORCID:
0000-0002-1892-9139


Publisher:
Cell Press
Journal:
Molecular Cell More from this journal
Volume:
73
Issue:
6
Pages:
1292-1305
Publication date:
2019-02-12
Acceptance date:
2019-01-07
DOI:
ISSN:
1097-2765


Keywords:
Pubs id:
pubs:965593
UUID:
uuid:9872dc59-d63d-4435-904d-f40884f82392
Local pid:
pubs:965593
Source identifiers:
965593
Deposit date:
2019-02-15
ARK identifier:

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