학술논문
Defining the condensate landscape of fusion oncoproteins
Document Type
article
Author
Swarnendu Tripathi; Hazheen K. Shirnekhi; Scott D. Gorman; Bappaditya Chandra; David W. Baggett; Cheon-Gil Park; Ramiz Somjee; Benjamin Lang; Seyed Mohammad Hadi Hosseini; Brittany J. Pioso; Yongsheng Li; Ilaria Iacobucci; Qingsong Gao; Michael N. Edmonson; Stephen V. Rice; Xin Zhou; John Bollinger; Diana M. Mitrea; Michael R. White; Daniel J. McGrail; Daniel F. Jarosz; S. Stephen Yi; M. Madan Babu; Charles G. Mullighan; Jinghui Zhang; Nidhi Sahni; Richard W. Kriwacki
Source
Nature Communications, Vol 14, Iss 1, Pp 1-25 (2023)
Subject
Language
English
ISSN
2041-1723
Abstract
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.