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Record W2584258570 · doi:10.1093/nar/gkx011

Cancer-causing mutations in the tumor suppressor PALB2 reveal a novel cancer mechanism using a hidden nuclear export signal in the WD40 repeat motif

2017· article· en· W2584258570 on OpenAlexafffund
Joris Pauty, Anthony M. Couturier, Amélie Rodrigue, Marie‐Christine Caron, Yan Coulombe, Graham Dellaire, Jean‐Yves Masson

Bibliographic record

VenueNucleic Acids Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsDalhousie UniversityUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsBiologyPALB2GeneticsNuclear export signalMutantCancer researchGenome instabilityBRCA2 ProteinMutationCancerCell biologyGeneDNA damageGermline mutationCell nucleusDNA

Abstract

fetched live from OpenAlex

One typical mechanism to promote genomic instability, a hallmark of cancer, is to inactivate tumor suppressors, such as PALB2. It has recently been reported that mutations in PALB2 increase the risk of breast cancer by 8-9-fold by age 40 and the life time risk is ∼3-4-fold. To date, predicting the functional consequences of PALB2 mutations has been challenging as they lead to different cancer risks. Here, we performed a structure-function analysis of PALB2, using PALB2 truncated mutants (R170fs, L531fs, Q775X and W1038X), and uncovered a new mechanism by which cancer cells could drive genomic instability. Remarkably, the PALB2 W1038X mutant, harboring a mutation in its C-terminal domain, is still proficient in stimulating RAD51-mediated recombination in vitro, although it is unusually localized to the cytoplasm. After further investigation, we identified a hidden NES within the WD40 domain of PALB2 and found that the W1038X truncation leads to the exposure of this NES to CRM1, an export protein. This concept was also confirmed with another WD40-containing protein, RBBP4. Consequently, our studies reveal an unreported mechanism linking the nucleocytoplasmic translocation of PALB2 mutants to cancer formation.

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)0.003
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.718

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.080
GPT teacher head0.376
Teacher spread0.295 · 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 designBench or experimental
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

Citations41
Published2017
Admission routes2
Has abstractyes

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