A Recurrent <i>ERCC3</i> Truncating Mutation Confers Moderate Risk for Breast Cancer
Bibliographic record
Abstract
Abstract Known gene mutations account for approximately 50% of the hereditary risk for breast cancer. Moderate and low penetrance variants, discovered by genomic approaches, account for an as-yet-unknown proportion of the remaining heritability. A truncating mutation c.325C&gt;T:p.Arg109* (R109X) in the ATP-dependent helicase ERCC3 was observed recurrently among exomes sequenced in BRCA wild-type, breast cancer–affected individuals of Ashkenazi Jewish ancestry. Modeling of the mutation in ERCC3-deficient or CRISPR/Cas9-edited cell lines showed a consistent pattern of reduced expression of the protein and concomitant hypomorphic functionality when challenged with UVC exposure or treatment with the DNA alkylating agent IlludinS. Overexpressing the mutant protein in ERCC3-deficient cells only partially rescued their DNA repair–deficient phenotype. Comparison of frequency of this recurrent mutation in over 6,500 chromosomes of breast cancer cases and 6,800 Ashkenazi controls showed significant association with breast cancer risk (ORBC = 1.53, ORER+ = 1.73), particularly for the estrogen receptor–positive subset (P &lt; 0.007). Significance: A functionally significant recurrent ERCC3 mutation increased the risk for breast cancer in a genetic isolate. Mutated cell lines showed lower survival after in vitro exposure to DNA-damaging agents. Thus, similar to tumors arising in the background of homologous repair defects, mutations in nucleotide excision repair genes such as ERCC3 could constitute potential therapeutic targets in a subset of hereditary breast cancers. Cancer Discov; 6(11); 1267–75. ©2016 AACR. This article is highlighted in the In This Issue feature, p. 1197
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".