Interpreting cancer genetics through a two-step “evolutionary cascade hypothesis”: bridging neutral and selective perspectives
As predictive models of tumor evolution advance through genomic big data and artificial intelligence-driven analysis, the future of cancer treatment may extend beyond targeting individual mutations to disrupting the underlying evolutionary mechanisms that sustain malignancy. This paradigm shift could redefine therapeutic strategies and ultimately improve patient outcomes.
Authors
- Francesco Sabbatino (ORCID: https://orcid.org/0000-0001-6431-8278)
- Anna Ceccarelli
- Silvia Zappavigna
- Mariachiara Santorsola
- Roberto Sirica (ORCID: https://orcid.org/0000-0002-3923-4889)
- Ines Simeone
- Giovanni Savarese (ORCID: https://orcid.org/0009-0004-5274-3989)
- Francesco Caraglia (ORCID: https://orcid.org/0009-0000-1853-9897)
- Vincenza Granata
- Massimiliano Berretta
Institutions
- University of Messina (IT)
- University of Salerno (IT)
- University of Campania "Luigi Vanvitelli" (IT)
- Regione Campania (IT)
- Agostino Gemelli University Polyclinic (IT)
- Biogem (IT)
- Federico II University Hospital (IT)
- University of Campania "Luigi Vanvitelli" (IT)
- Istituto Nazionale Tumori IRCCS "Fondazione G. Pascale" (IT)
- University of Naples Federico II (IT)
Publication Details
- Journal
- Journal of Translational Medicine
- Published
- 2026-02-13
- DOI
- https://doi.org/10.1186/s12967-026-07869-w
- Primary Topic
- Cancer Genomics and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 0.00