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TP53 variant clusters stratify phenotypic diversity in germline carriers and reveal an osteosarcoma-prone subgroup.


ABSTRACT: Li-Fraumeni syndrome (LFS) has recently been redefined as a 'spectrum' cancer predisposition disorder to reflect its broad phenotypic heterogeneity. This variability is thought to stem in part from the diverse functional impacts of TP53 variants, although the underlying mechanisms remain poorly understood and there is an unmet clinical need for effective risk stratification. Here, we apply unsupervised clustering to functional datasets and identify distinct TP53 variant groups with clinical relevance, including a monomeric subgroup enriched in osteosarcoma cases. In cellular validation assays, dermal fibroblasts from carriers of more functionally impaired variants exhibit increased metabolic growth rates, mirroring trends observed in cluster-stratified clinical outcomes. These findings demonstrate the feasibility of developing diagnostic assays to guide personalized cancer risk assessment. More broadly, our results show that nuances in TP53 dysfunction shape the germline TP53-related cancer susceptibility spectrum and provide a framework for functionally delineating variant carriers.

SUBMITTER: Fischer NW 

PROVIDER: S-EPMC12480935 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature

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TP53 variant clusters stratify phenotypic diversity in germline carriers and reveal an osteosarcoma-prone subgroup.

Fischer Nicholas W NW   Ong Noel N   Laverty Brianne B   Psarianos Pamela P   Giovino Camilla C   Alon Noa N   Montellier Emilie E   Hainaut Pierre P   Maxwell Kara N KN   Kratz Christian P CP   Kafri Ran R   Malkin David D  

Nature communications 20250929 1


Li-Fraumeni syndrome (LFS) has recently been redefined as a 'spectrum' cancer predisposition disorder to reflect its broad phenotypic heterogeneity. This variability is thought to stem in part from the diverse functional impacts of TP53 variants, although the underlying mechanisms remain poorly understood and there is an unmet clinical need for effective risk stratification. Here, we apply unsupervised clustering to functional datasets and identify distinct TP53 variant groups with clinical rele  ...[more]

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