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A functional genomic approach to actionable gene fusions for precision oncology
Fusion genes represent a class of attractive therapeutic targets. Thousands of fusion genes have been identified in patients with cancer, but the functional consequences and therapeutic implications of most of these remain largely unknown. Here, we develop a functional genomic approach that consists...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8827659/ https://www.ncbi.nlm.nih.gov/pubmed/35138907 http://dx.doi.org/10.1126/sciadv.abm2382 |
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author | Li, Jun Lu, Hengyu Ng, Patrick Kwok-Shing Pantazi, Angeliki Ip, Carman Ka Man Jeong, Kang Jin Amador, Bianca Tran, Richard Tsang, Yiu Huen Yang, Lixing Song, Xingzhi Dogruluk, Turgut Ren, Xiaojia Hadjipanayis, Angela Bristow, Christopher A. Lee, Semin Kucherlapati, Melanie Parfenov, Michael Tang, Jiabin Seth, Sahil Mahadeshwar, Harshad S. Mojumdar, Kamalika Zeng, Dong Zhang, Jianhua Protopopov, Alexei Seidman, Jonathan G. Creighton, Chad J. Lu, Yiling Sahni, Nidhi Shaw, Kenna R. Meric-Bernstam, Funda Futreal, Andrew Chin, Lynda Scott, Kenneth L. Kucherlapati, Raju Mills, Gordon B. Liang, Han |
author_facet | Li, Jun Lu, Hengyu Ng, Patrick Kwok-Shing Pantazi, Angeliki Ip, Carman Ka Man Jeong, Kang Jin Amador, Bianca Tran, Richard Tsang, Yiu Huen Yang, Lixing Song, Xingzhi Dogruluk, Turgut Ren, Xiaojia Hadjipanayis, Angela Bristow, Christopher A. Lee, Semin Kucherlapati, Melanie Parfenov, Michael Tang, Jiabin Seth, Sahil Mahadeshwar, Harshad S. Mojumdar, Kamalika Zeng, Dong Zhang, Jianhua Protopopov, Alexei Seidman, Jonathan G. Creighton, Chad J. Lu, Yiling Sahni, Nidhi Shaw, Kenna R. Meric-Bernstam, Funda Futreal, Andrew Chin, Lynda Scott, Kenneth L. Kucherlapati, Raju Mills, Gordon B. Liang, Han |
author_sort | Li, Jun |
collection | PubMed |
description | Fusion genes represent a class of attractive therapeutic targets. Thousands of fusion genes have been identified in patients with cancer, but the functional consequences and therapeutic implications of most of these remain largely unknown. Here, we develop a functional genomic approach that consists of efficient fusion reconstruction and sensitive cell viability and drug response assays. Applying this approach, we characterize ~100 fusion genes detected in patient samples of The Cancer Genome Atlas, revealing a notable fraction of low-frequency fusions with activating effects on tumor growth. Focusing on those in the RTK-RAS pathway, we identify a number of activating fusions that can markedly affect sensitivity to relevant drugs. Last, we propose an integrated, level-of-evidence classification system to prioritize gene fusions systematically. Our study reiterates the urgent clinical need to incorporate similar functional genomic approaches to characterize gene fusions, thereby maximizing the utility of gene fusions for precision oncology. |
format | Online Article Text |
id | pubmed-8827659 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-88276592022-02-24 A functional genomic approach to actionable gene fusions for precision oncology Li, Jun Lu, Hengyu Ng, Patrick Kwok-Shing Pantazi, Angeliki Ip, Carman Ka Man Jeong, Kang Jin Amador, Bianca Tran, Richard Tsang, Yiu Huen Yang, Lixing Song, Xingzhi Dogruluk, Turgut Ren, Xiaojia Hadjipanayis, Angela Bristow, Christopher A. Lee, Semin Kucherlapati, Melanie Parfenov, Michael Tang, Jiabin Seth, Sahil Mahadeshwar, Harshad S. Mojumdar, Kamalika Zeng, Dong Zhang, Jianhua Protopopov, Alexei Seidman, Jonathan G. Creighton, Chad J. Lu, Yiling Sahni, Nidhi Shaw, Kenna R. Meric-Bernstam, Funda Futreal, Andrew Chin, Lynda Scott, Kenneth L. Kucherlapati, Raju Mills, Gordon B. Liang, Han Sci Adv Biomedicine and Life Sciences Fusion genes represent a class of attractive therapeutic targets. Thousands of fusion genes have been identified in patients with cancer, but the functional consequences and therapeutic implications of most of these remain largely unknown. Here, we develop a functional genomic approach that consists of efficient fusion reconstruction and sensitive cell viability and drug response assays. Applying this approach, we characterize ~100 fusion genes detected in patient samples of The Cancer Genome Atlas, revealing a notable fraction of low-frequency fusions with activating effects on tumor growth. Focusing on those in the RTK-RAS pathway, we identify a number of activating fusions that can markedly affect sensitivity to relevant drugs. Last, we propose an integrated, level-of-evidence classification system to prioritize gene fusions systematically. Our study reiterates the urgent clinical need to incorporate similar functional genomic approaches to characterize gene fusions, thereby maximizing the utility of gene fusions for precision oncology. American Association for the Advancement of Science 2022-02-09 /pmc/articles/PMC8827659/ /pubmed/35138907 http://dx.doi.org/10.1126/sciadv.abm2382 Text en Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Biomedicine and Life Sciences Li, Jun Lu, Hengyu Ng, Patrick Kwok-Shing Pantazi, Angeliki Ip, Carman Ka Man Jeong, Kang Jin Amador, Bianca Tran, Richard Tsang, Yiu Huen Yang, Lixing Song, Xingzhi Dogruluk, Turgut Ren, Xiaojia Hadjipanayis, Angela Bristow, Christopher A. Lee, Semin Kucherlapati, Melanie Parfenov, Michael Tang, Jiabin Seth, Sahil Mahadeshwar, Harshad S. Mojumdar, Kamalika Zeng, Dong Zhang, Jianhua Protopopov, Alexei Seidman, Jonathan G. Creighton, Chad J. Lu, Yiling Sahni, Nidhi Shaw, Kenna R. Meric-Bernstam, Funda Futreal, Andrew Chin, Lynda Scott, Kenneth L. Kucherlapati, Raju Mills, Gordon B. Liang, Han A functional genomic approach to actionable gene fusions for precision oncology |
title | A functional genomic approach to actionable gene fusions for precision oncology |
title_full | A functional genomic approach to actionable gene fusions for precision oncology |
title_fullStr | A functional genomic approach to actionable gene fusions for precision oncology |
title_full_unstemmed | A functional genomic approach to actionable gene fusions for precision oncology |
title_short | A functional genomic approach to actionable gene fusions for precision oncology |
title_sort | functional genomic approach to actionable gene fusions for precision oncology |
topic | Biomedicine and Life Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8827659/ https://www.ncbi.nlm.nih.gov/pubmed/35138907 http://dx.doi.org/10.1126/sciadv.abm2382 |
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