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An integrated functional and clinical genomics approach reveals genes driving aggressive metastatic prostate cancer
Genomic sequencing of thousands of tumors has revealed many genes associated with specific types of cancer. Similarly, large scale CRISPR functional genomics efforts have mapped genes required for cancer cell proliferation or survival in hundreds of cell lines. Despite this, for specific disease sub...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322386/ https://www.ncbi.nlm.nih.gov/pubmed/34326322 http://dx.doi.org/10.1038/s41467-021-24919-7 |
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author | Das, Rajdeep Sjöström, Martin Shrestha, Raunak Yogodzinski, Christopher Egusa, Emily A. Chesner, Lisa N. Chen, William S. Chou, Jonathan Dang, Donna K. Swinderman, Jason T. Ge, Alex Hua, Junjie T. Kabir, Shaheen Quigley, David A. Small, Eric J. Ashworth, Alan Feng, Felix Y. Gilbert, Luke A. |
author_facet | Das, Rajdeep Sjöström, Martin Shrestha, Raunak Yogodzinski, Christopher Egusa, Emily A. Chesner, Lisa N. Chen, William S. Chou, Jonathan Dang, Donna K. Swinderman, Jason T. Ge, Alex Hua, Junjie T. Kabir, Shaheen Quigley, David A. Small, Eric J. Ashworth, Alan Feng, Felix Y. Gilbert, Luke A. |
author_sort | Das, Rajdeep |
collection | PubMed |
description | Genomic sequencing of thousands of tumors has revealed many genes associated with specific types of cancer. Similarly, large scale CRISPR functional genomics efforts have mapped genes required for cancer cell proliferation or survival in hundreds of cell lines. Despite this, for specific disease subtypes, such as metastatic prostate cancer, there are likely a number of undiscovered tumor specific driver genes that may represent potential drug targets. To identify such genetic dependencies, we performed genome-scale CRISPRi screens in metastatic prostate cancer models. We then created a pipeline in which we integrated pan-cancer functional genomics data with our metastatic prostate cancer functional and clinical genomics data to identify genes that can drive aggressive prostate cancer phenotypes. Our integrative analysis of these data reveals known prostate cancer specific driver genes, such as AR and HOXB13, as well as a number of top hits that are poorly characterized. In this study we highlight the strength of an integrated clinical and functional genomics pipeline and focus on two top hit genes, KIF4A and WDR62. We demonstrate that both KIF4A and WDR62 drive aggressive prostate cancer phenotypes in vitro and in vivo in multiple models, irrespective of AR-status, and are also associated with poor patient outcome. |
format | Online Article Text |
id | pubmed-8322386 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-83223862021-08-03 An integrated functional and clinical genomics approach reveals genes driving aggressive metastatic prostate cancer Das, Rajdeep Sjöström, Martin Shrestha, Raunak Yogodzinski, Christopher Egusa, Emily A. Chesner, Lisa N. Chen, William S. Chou, Jonathan Dang, Donna K. Swinderman, Jason T. Ge, Alex Hua, Junjie T. Kabir, Shaheen Quigley, David A. Small, Eric J. Ashworth, Alan Feng, Felix Y. Gilbert, Luke A. Nat Commun Article Genomic sequencing of thousands of tumors has revealed many genes associated with specific types of cancer. Similarly, large scale CRISPR functional genomics efforts have mapped genes required for cancer cell proliferation or survival in hundreds of cell lines. Despite this, for specific disease subtypes, such as metastatic prostate cancer, there are likely a number of undiscovered tumor specific driver genes that may represent potential drug targets. To identify such genetic dependencies, we performed genome-scale CRISPRi screens in metastatic prostate cancer models. We then created a pipeline in which we integrated pan-cancer functional genomics data with our metastatic prostate cancer functional and clinical genomics data to identify genes that can drive aggressive prostate cancer phenotypes. Our integrative analysis of these data reveals known prostate cancer specific driver genes, such as AR and HOXB13, as well as a number of top hits that are poorly characterized. In this study we highlight the strength of an integrated clinical and functional genomics pipeline and focus on two top hit genes, KIF4A and WDR62. We demonstrate that both KIF4A and WDR62 drive aggressive prostate cancer phenotypes in vitro and in vivo in multiple models, irrespective of AR-status, and are also associated with poor patient outcome. Nature Publishing Group UK 2021-07-29 /pmc/articles/PMC8322386/ /pubmed/34326322 http://dx.doi.org/10.1038/s41467-021-24919-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Das, Rajdeep Sjöström, Martin Shrestha, Raunak Yogodzinski, Christopher Egusa, Emily A. Chesner, Lisa N. Chen, William S. Chou, Jonathan Dang, Donna K. Swinderman, Jason T. Ge, Alex Hua, Junjie T. Kabir, Shaheen Quigley, David A. Small, Eric J. Ashworth, Alan Feng, Felix Y. Gilbert, Luke A. An integrated functional and clinical genomics approach reveals genes driving aggressive metastatic prostate cancer |
title | An integrated functional and clinical genomics approach reveals genes driving aggressive metastatic prostate cancer |
title_full | An integrated functional and clinical genomics approach reveals genes driving aggressive metastatic prostate cancer |
title_fullStr | An integrated functional and clinical genomics approach reveals genes driving aggressive metastatic prostate cancer |
title_full_unstemmed | An integrated functional and clinical genomics approach reveals genes driving aggressive metastatic prostate cancer |
title_short | An integrated functional and clinical genomics approach reveals genes driving aggressive metastatic prostate cancer |
title_sort | integrated functional and clinical genomics approach reveals genes driving aggressive metastatic prostate cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322386/ https://www.ncbi.nlm.nih.gov/pubmed/34326322 http://dx.doi.org/10.1038/s41467-021-24919-7 |
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