Functional characterization of 84 PALB2 variants of uncertain significance
Bibliographic record
Abstract
PURPOSE: Inherited pathogenic variants in PALB2 are associated with increased risk of breast and pancreatic cancer. However, the functional and clinical relevance of many missense variants of uncertain significance (VUS) identified through clinical genetic testing is unclear. The ability of patient-derived germline missense VUS to disrupt PALB2 function was assessed to identify variants with potential clinical relevance. METHODS: The influence of 84 VUS on PALB2 function was evaluated using a cellular homology directed DNA repair (HDR) assay and VUS impacting activity were further characterized using secondary functional assays. RESULTS: Four (~5%) variants (p.L24S,c.71T>C; p.L35P,c.104T>C; pI944N,c.2831T>A; and p.L1070P,c.3209T>C) disrupted PALB2-mediated HDR activity. These variants conferred sensitivity to cisplatin and a poly(ADP-ribose) polymerase (PARP) inhibitor and reduced RAD51 foci formation in response to DNA damage. The p.L24S and p.L35P variants disrupted BRCA1-PALB2 protein complexes, p.I944N was associated with protein instability, and both p.I944N and p.L1070P mislocalized PALB2 to the cytoplasm. CONCLUSION: These findings show that the HDR assay is an effective method for screening the influence of inherited variants on PALB2 function, that four missense variants impact PALB2 function and may influence cancer risk and response to therapy, and suggest that few inherited PALB2 missense variants disrupt PALB2 function in DNA repair.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".