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Unravelling Intratumoral Heterogeneity through High-Sensitivity Single-Cell Mutational Analysis and Parallel RNA Sequencing

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 pr...

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Autores principales: Rodriguez-Meira, Alba, Buck, Gemma, Clark, Sally-Ann, Povinelli, Benjamin J., Alcolea, Veronica, Louka, Eleni, McGowan, Simon, Hamblin, Angela, Sousos, Nikolaos, Barkas, Nikolaos, Giustacchini, Alice, Psaila, Bethan, Jacobsen, Sten Eirik W., Thongjuea, Supat, Mead, Adam J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cell Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6436961/
https://www.ncbi.nlm.nih.gov/pubmed/30765193
http://dx.doi.org/10.1016/j.molcel.2019.01.009
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author Rodriguez-Meira, Alba
Buck, Gemma
Clark, Sally-Ann
Povinelli, Benjamin J.
Alcolea, Veronica
Louka, Eleni
McGowan, Simon
Hamblin, Angela
Sousos, Nikolaos
Barkas, Nikolaos
Giustacchini, Alice
Psaila, Bethan
Jacobsen, Sten Eirik W.
Thongjuea, Supat
Mead, Adam J.
author_facet Rodriguez-Meira, Alba
Buck, Gemma
Clark, Sally-Ann
Povinelli, Benjamin J.
Alcolea, Veronica
Louka, Eleni
McGowan, Simon
Hamblin, Angela
Sousos, Nikolaos
Barkas, Nikolaos
Giustacchini, Alice
Psaila, Bethan
Jacobsen, Sten Eirik W.
Thongjuea, Supat
Mead, Adam J.
author_sort Rodriguez-Meira, Alba
collection PubMed
description 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.
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spelling pubmed-64369612019-04-10 Unravelling Intratumoral Heterogeneity through High-Sensitivity Single-Cell Mutational Analysis and Parallel RNA Sequencing Rodriguez-Meira, Alba Buck, Gemma Clark, Sally-Ann Povinelli, Benjamin J. Alcolea, Veronica Louka, Eleni McGowan, Simon Hamblin, Angela Sousos, Nikolaos Barkas, Nikolaos Giustacchini, Alice Psaila, Bethan Jacobsen, Sten Eirik W. Thongjuea, Supat Mead, Adam J. Mol Cell Article 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. Cell Press 2019-03-21 /pmc/articles/PMC6436961/ /pubmed/30765193 http://dx.doi.org/10.1016/j.molcel.2019.01.009 Text en © 2019 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Rodriguez-Meira, Alba
Buck, Gemma
Clark, Sally-Ann
Povinelli, Benjamin J.
Alcolea, Veronica
Louka, Eleni
McGowan, Simon
Hamblin, Angela
Sousos, Nikolaos
Barkas, Nikolaos
Giustacchini, Alice
Psaila, Bethan
Jacobsen, Sten Eirik W.
Thongjuea, Supat
Mead, Adam J.
Unravelling Intratumoral Heterogeneity through High-Sensitivity Single-Cell Mutational Analysis and Parallel RNA Sequencing
title Unravelling Intratumoral Heterogeneity through High-Sensitivity Single-Cell Mutational Analysis and Parallel RNA Sequencing
title_full Unravelling Intratumoral Heterogeneity through High-Sensitivity Single-Cell Mutational Analysis and Parallel RNA Sequencing
title_fullStr Unravelling Intratumoral Heterogeneity through High-Sensitivity Single-Cell Mutational Analysis and Parallel RNA Sequencing
title_full_unstemmed Unravelling Intratumoral Heterogeneity through High-Sensitivity Single-Cell Mutational Analysis and Parallel RNA Sequencing
title_short Unravelling Intratumoral Heterogeneity through High-Sensitivity Single-Cell Mutational Analysis and Parallel RNA Sequencing
title_sort unravelling intratumoral heterogeneity through high-sensitivity single-cell mutational analysis and parallel rna sequencing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6436961/
https://www.ncbi.nlm.nih.gov/pubmed/30765193
http://dx.doi.org/10.1016/j.molcel.2019.01.009
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