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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...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cell Press
2019
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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. |
format | Online Article Text |
id | pubmed-6436961 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Cell Press |
record_format | MEDLINE/PubMed |
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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