Cancer-causing mutations in the tumor suppressor PALB2 reveal a novel cancer mechanism using a hidden nuclear export signal in the WD40 repeat motif
Bibliographic record
Abstract
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".