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Defining the condensate landscape of fusion oncoproteins
Fusion oncoproteins (FOs) arise from chromosomal translocations in ~17% of cancers and are often oncogenic drivers. Although some FOs can promote oncogenesis by undergoing liquid-liquid phase separation (LLPS) to form aberrant biomolecular condensates, the generality of this phenomenon is unknown. W...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10539325/ https://www.ncbi.nlm.nih.gov/pubmed/37770423 http://dx.doi.org/10.1038/s41467-023-41655-2 |
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author | Tripathi, Swarnendu Shirnekhi, Hazheen K. Gorman, Scott D. Chandra, Bappaditya Baggett, David W. Park, Cheon-Gil Somjee, Ramiz Lang, Benjamin Hosseini, Seyed Mohammad Hadi Pioso, Brittany J. Li, Yongsheng Iacobucci, Ilaria Gao, Qingsong Edmonson, Michael N. Rice, Stephen V. Zhou, Xin Bollinger, John Mitrea, Diana M. White, Michael R. McGrail, Daniel J. Jarosz, Daniel F. Yi, S. Stephen Babu, M. Madan Mullighan, Charles G. Zhang, Jinghui Sahni, Nidhi Kriwacki, Richard W. |
author_facet | Tripathi, Swarnendu Shirnekhi, Hazheen K. Gorman, Scott D. Chandra, Bappaditya Baggett, David W. Park, Cheon-Gil Somjee, Ramiz Lang, Benjamin Hosseini, Seyed Mohammad Hadi Pioso, Brittany J. Li, Yongsheng Iacobucci, Ilaria Gao, Qingsong Edmonson, Michael N. Rice, Stephen V. Zhou, Xin Bollinger, John Mitrea, Diana M. White, Michael R. McGrail, Daniel J. Jarosz, Daniel F. Yi, S. Stephen Babu, M. Madan Mullighan, Charles G. Zhang, Jinghui Sahni, Nidhi Kriwacki, Richard W. |
author_sort | Tripathi, Swarnendu |
collection | PubMed |
description | Fusion oncoproteins (FOs) arise from chromosomal translocations in ~17% of cancers and are often oncogenic drivers. Although some FOs can promote oncogenesis by undergoing liquid-liquid phase separation (LLPS) to form aberrant biomolecular condensates, the generality of this phenomenon is unknown. We explored this question by testing 166 FOs in HeLa cells and found that 58% formed condensates. The condensate-forming FOs displayed physicochemical features distinct from those of condensate-negative FOs and segregated into distinct feature-based groups that aligned with their sub-cellular localization and biological function. Using Machine Learning, we developed a predictor of FO condensation behavior, and discovered that 67% of ~3000 additional FOs likely form condensates, with 35% of those predicted to function by altering gene expression. 47% of the predicted condensate-negative FOs were associated with cell signaling functions, suggesting a functional dichotomy between condensate-positive and -negative FOs. Our Datasets and reagents are rich resources to interrogate FO condensation in the future. |
format | Online Article Text |
id | pubmed-10539325 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105393252023-09-30 Defining the condensate landscape of fusion oncoproteins Tripathi, Swarnendu Shirnekhi, Hazheen K. Gorman, Scott D. Chandra, Bappaditya Baggett, David W. Park, Cheon-Gil Somjee, Ramiz Lang, Benjamin Hosseini, Seyed Mohammad Hadi Pioso, Brittany J. Li, Yongsheng Iacobucci, Ilaria Gao, Qingsong Edmonson, Michael N. Rice, Stephen V. Zhou, Xin Bollinger, John Mitrea, Diana M. White, Michael R. McGrail, Daniel J. Jarosz, Daniel F. Yi, S. Stephen Babu, M. Madan Mullighan, Charles G. Zhang, Jinghui Sahni, Nidhi Kriwacki, Richard W. Nat Commun Article Fusion oncoproteins (FOs) arise from chromosomal translocations in ~17% of cancers and are often oncogenic drivers. Although some FOs can promote oncogenesis by undergoing liquid-liquid phase separation (LLPS) to form aberrant biomolecular condensates, the generality of this phenomenon is unknown. We explored this question by testing 166 FOs in HeLa cells and found that 58% formed condensates. The condensate-forming FOs displayed physicochemical features distinct from those of condensate-negative FOs and segregated into distinct feature-based groups that aligned with their sub-cellular localization and biological function. Using Machine Learning, we developed a predictor of FO condensation behavior, and discovered that 67% of ~3000 additional FOs likely form condensates, with 35% of those predicted to function by altering gene expression. 47% of the predicted condensate-negative FOs were associated with cell signaling functions, suggesting a functional dichotomy between condensate-positive and -negative FOs. Our Datasets and reagents are rich resources to interrogate FO condensation in the future. Nature Publishing Group UK 2023-09-28 /pmc/articles/PMC10539325/ /pubmed/37770423 http://dx.doi.org/10.1038/s41467-023-41655-2 Text en © The Author(s) 2023 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Tripathi, Swarnendu Shirnekhi, Hazheen K. Gorman, Scott D. Chandra, Bappaditya Baggett, David W. Park, Cheon-Gil Somjee, Ramiz Lang, Benjamin Hosseini, Seyed Mohammad Hadi Pioso, Brittany J. Li, Yongsheng Iacobucci, Ilaria Gao, Qingsong Edmonson, Michael N. Rice, Stephen V. Zhou, Xin Bollinger, John Mitrea, Diana M. White, Michael R. McGrail, Daniel J. Jarosz, Daniel F. Yi, S. Stephen Babu, M. Madan Mullighan, Charles G. Zhang, Jinghui Sahni, Nidhi Kriwacki, Richard W. Defining the condensate landscape of fusion oncoproteins |
title | Defining the condensate landscape of fusion oncoproteins |
title_full | Defining the condensate landscape of fusion oncoproteins |
title_fullStr | Defining the condensate landscape of fusion oncoproteins |
title_full_unstemmed | Defining the condensate landscape of fusion oncoproteins |
title_short | Defining the condensate landscape of fusion oncoproteins |
title_sort | defining the condensate landscape of fusion oncoproteins |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10539325/ https://www.ncbi.nlm.nih.gov/pubmed/37770423 http://dx.doi.org/10.1038/s41467-023-41655-2 |
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