Modelling the liver’s regenerative capacity across different clinical conditions
The aim of this study was to identify key transcriptomic, proteomic, and serum biomarkers of regeneration in mouse models under diverse conditions, using systems biology and machine learning approaches. Key molecular drivers of liver regeneration across diverse clinical conditions were identified using innovative deep learning and multi-omics approaches. By identifying conserved cell cycle genes predictive of regenerative outcomes, this study offers a powerful framework to assess and potentially enhance liver recovery in older patients, those with fibrosis or steatosis, and/or those under immunosuppression.
Authors
- Elisa Pasini (ORCID: https://orcid.org/0000-0002-1547-7077)
- Michael Brudno (ORCID: https://orcid.org/0000-0001-7947-2243)
- Anh Thu Nguyen‐Lefebvre (ORCID: https://orcid.org/0000-0001-6247-7101)
- Bima J. Hasjim (ORCID: https://orcid.org/0000-0003-4301-9011)
- Mamatha Bhat (ORCID: https://orcid.org/0000-0003-1960-8449)
- Graziano Oldani (ORCID: https://orcid.org/0000-0002-6637-0675)
- Nazia Selzner (ORCID: https://orcid.org/0000-0002-9435-2597)
- Jeffrey L. Wrana (ORCID: https://orcid.org/0000-0003-0932-0644)
- Cristina Baciu (ORCID: https://orcid.org/0000-0002-3750-5147)
- Sara Naimimohasses
- Soumita Ghosh (ORCID: https://orcid.org/0000-0003-1743-529X)
Institutions
- University of Geneva (CH)
- University Health Network (CA)
- University of British Columbia (CA)
- University of Toronto (CA)
- University of California, Irvine (US)
- Lunenfeld-Tanenbaum Research Institute (CA)
- University of California, Irvine Medical Center (US)
Publication Details
- Journal
- JHEP Reports
- Published
- 2025-05-30
- DOI
- https://doi.org/10.1016/j.jhepr.2025.101465
- Citations
- 2
- Primary Topic
- Liver physiology and pathology
- Type
- article
- Field-Weighted Citation Impact
- 2.64
Funders
- Stem Cell Network
- Hospital for Sick Children
- Scheme for Promotion of Academic and Research Collaboration
- University Health Network Foundation
- Natural Sciences and Engineering Research Council of Canada