Investigating the causal role of MRE11A p.E506* in breast and ovarian cancer
Bibliographic record
Abstract
The nuclease MRE11A is often included in genetic test panels for hereditary breast and ovarian cancer (HBOC) due to its BRCA1-related molecular function in the DNA repair pathway. However, whether MRE11A is a true predisposition gene for HBOC is still questionable. We determined to investigate this notion by dissecting the molecular genetics of the c.1516G > T;p.E506* truncating MRE11A variant, that we pinpointed in two unrelated French-Canadian (FC) HBOC patients. We performed a case-control study for the variant in ~ 2500 breast, ovarian, and endometrial cancer patients from the founder FC population of Quebec. Furthermore, we looked for the presence of second somatic alterations in the MRE11A gene in the tumors of the carriers. In summary, these investigations suggested that the identified variant is not associated with an increased risk of developing breast or ovarian cancer. We finally performed a systematic review for all the previously reported MRE11A variants in breast and ovarian cancer. We found that MRE11A germline variants annotated as pathogenic on ClinVar often lacked evidence for such classification, hence misleading the clinical management for affected patients. In summary, our report suggests the lack of clinical utility of MRE11A testing in HBOC, at least in the White/Caucasian populations.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| 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) | 0.002 | 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".