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Defining the condensate landscape of fusion oncoproteins.

Swarnendu TripathiHazheen K ShirnekhiScott D GormanBappaditya ChandraDavid W BaggettCheon-Gil ParkRamiz SomjeeBenjamin LangSeyed Mohammad Hadi HosseiniBrittany J PiosoYongsheng LiIlaria IacobucciQingsong GaoMichael N EdmonsonStephen V RiceXin ZhouJohn BollingerDiana M MitreaMichael R WhiteDaniel J McGrailDaniel F JaroszS Stephen YiM Madan BabuCharles G MullighanJinghui ZhangNidhi SahniRichard W Kriwacki
Published in: Nature communications (2023)
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.
Keyphrases
  • gene expression
  • single cell
  • machine learning
  • dna methylation
  • induced apoptosis
  • stem cells
  • cell cycle arrest
  • rna seq
  • mesenchymal stem cells
  • signaling pathway
  • bone marrow