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Record W2990517165 · doi:10.1038/s41467-019-13194-2

Functional analysis of genetic variants in the high-risk breast cancer susceptibility gene PALB2

2019· article· en· W2990517165 on OpenAlexafffund
Rick A.C.M. Boonen, Amélie Rodrigue, Chantal Stoepker, Wouter W. Wiegant, Bas Vroling, Milan Sharma, Magdalena B. Rother, Nandi Celosse, Maaike P.G. Vreeswijk, Fergus J. Couch, Jacques Simard, Peter Devilee, Jean‐Yves Masson, Haico van Attikum

Bibliographic record

VenueNature Communications · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsCentre hospitalier universitaire de QuébecUniversité Laval
FundersGovernment of CanadaEuropean CommissionFondation du cancer du sein du QuébecCanadian Institutes of Health ResearchKWF KankerbestrijdingGenome Canada
KeywordsPALB2Breast cancerGeneticsGeneBiologyComputational biologyBioinformaticsCancerMedicineMutationGermline mutation

Abstract

fetched live from OpenAlex

Heterozygous carriers of germ-line loss-of-function variants in the DNA repair gene PALB2 are at a highly increased lifetime risk for developing breast cancer. While truncating variants in PALB2 are known to increase cancer risk, the interpretation of missense variants of uncertain significance (VUS) is in its infancy. Here we describe the development of a relatively fast and easy cDNA-based system for the semi high-throughput functional analysis of 48 VUS in human PALB2. By assessing the ability of PALB2 VUS to rescue the DNA repair and checkpoint defects in Palb2 knockout mouse embryonic stem (mES) cells, we identify various VUS in PALB2 that impair its function. Three VUS in the coiled-coil domain of PALB2 abrogate the interaction with BRCA1, whereas several VUS in the WD40 domain dramatically reduce protein stability. Thus, our functional assays identify damaging VUS in PALB2 that may increase cancer risk.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.265
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations65
Published2019
Admission routes2
Has abstractyes

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