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...

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Vydáno v:Nature communications Ročník 14; číslo 1; s. 6008 - 25
Hlavní autoři: 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.
Médium: Journal Article
Jazyk:angličtina
Vydáno: London Nature Publishing Group UK 28.09.2023
Nature Publishing Group
Nature Portfolio
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ISSN:2041-1723, 2041-1723
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Abstract 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. Many fusion oncoproteins (FOs) form condensates, some form in the nucleus and regulate gene expression while others form in the cytoplasm and promote cell signaling. In this work, the authors report the analysis of physicochemical features to enable prediction of FO condensation behavior.
AbstractList Abstract 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.
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. Many fusion oncoproteins (FOs) form condensates, some form in the nucleus and regulate gene expression while others form in the cytoplasm and promote cell signaling. In this work, the authors report the analysis of physicochemical features to enable prediction of FO condensation behavior.
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.
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. Many fusion oncoproteins (FOs) form condensates, some form in the nucleus and regulate gene expression while others form in the cytoplasm and promote cell signaling. In this work, the authors report the analysis of physicochemical features to enable prediction of FO condensation behavior.
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.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.
ArticleNumber 6008
Author Jarosz, Daniel F.
Babu, M. Madan
Edmonson, Michael N.
White, Michael R.
Park, Cheon-Gil
Rice, Stephen V.
Li, Yongsheng
Baggett, David W.
Bollinger, John
Zhang, Jinghui
Pioso, Brittany J.
Iacobucci, Ilaria
Mitrea, Diana M.
Somjee, Ramiz
Hosseini, Seyed Mohammad Hadi
Mullighan, Charles G.
McGrail, Daniel J.
Sahni, Nidhi
Shirnekhi, Hazheen K.
Zhou, Xin
Lang, Benjamin
Gao, Qingsong
Tripathi, Swarnendu
Yi, S. Stephen
Kriwacki, Richard W.
Gorman, Scott D.
Chandra, Bappaditya
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/37770423$$D View this record in MEDLINE/PubMed
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Snippet Fusion oncoproteins (FOs) arise from chromosomal translocations in ~17% of cancers and are often oncogenic drivers. Although some FOs can promote oncogenesis...
Abstract Fusion oncoproteins (FOs) arise from chromosomal translocations in ~17% of cancers and are often oncogenic drivers. Although some FOs can promote...
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StartPage 6008
SubjectTerms 13/106
14/19
631/114/663/2009
631/57/2269
Biomolecular Condensates
Carcinogenesis
Cell signaling
Cell Transformation, Neoplastic
Chromosome translocations
Condensates
Condensation
Cytoplasm
Functionals
Gene expression
HeLa Cells
Humanities and Social Sciences
Humans
Liquid phases
Localization
Machine learning
multidisciplinary
Oncogene Proteins, Fusion
Oncoproteins
Phase separation
Reagents
Science
Science (multidisciplinary)
Tumorigenesis
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Title Defining the condensate landscape of fusion oncoproteins
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