Clustering of TP53 variants into functional classes correlates with cancer risk and identifies different phenotypes of Li-Fraumeni syndrome
Bibliographic record
Abstract
Li-Fraumeni syndrome (LFS) is a heterogeneous predisposition to an individually variable spectrum of cancers caused by pathogenic TP53 germline variants. We used a clustering method to assign TP53 missense variants to classes based on their functional activities in experimental assays assessing biological p53 functions. Correlations with LFS phenotypes were analyzed using the public germline TP53 mutation database and validated in three LFS clinical cohorts. Class A carriers recapitulated all phenotypic traits of fully penetrant LFS, whereas class B carriers showed a slightly less penetrant form dominated by specific cancers, consistent with the notion that these classes identify variants with distinct functional properties. Class C displayed a lower lifetime cancer risk associated with attenuated LFS features, consistent with the notion that these variants have hypomorphic features. Class D carriers showed low lifetime cancer risks inconsistent with LFS definitions. This classification of TP53 variants provides insights into structural/functional features causing pathogenicity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".