A Novel ATRIP Mutation Detected in an Iranian Family with Familial Clustering of Breast Cancer: A Case Report
Bibliographic record
Abstract
Purpose: ATRIP (ATR-interacting protein) is a critical partner of ATR (ataxia telangiectasia and Rad3-related). The ATR-ATRIP heterodimer plays an essential role in initiating homologous recombination repair (HRR) during replication stress and inducing double-stranded DNA breaks following unresolved stalled replication forks. Our team recently identified ATRIP as a novel breast cancer susceptibility gene candidate through whole-exome sequencing (WES) of familial breast cancer patients and healthy controls from the Polish founder population, with subsequent validation in both Polish and British cohorts. In the present study, we report for the first time the detection of a novel deleterious mutation in ATRIP among several members of an Iranian family with clustering of breast cancer who were negative for mutations in the already known breast cancer risk genes. Methods: Six family members underwent germline DNA testing by WES, following initial negative results from multigene panel testing. Candidate variants were confirmed by Sanger sequencing and assessed according to ACMG guidelines. Results: We detected a novel ATRIP frameshift mutation (NM_130384.3:c.1033delC) in four of six family members that were tested, including two individuals affected with breast cancer. No pathogenic variants were found in other known cancer susceptibility genes. Conclusions: This is the first report of a deleterious ATRIP mutation in an Iranian family with familial breast cancer, suggesting a potential role of ATRIP in hereditary breast cancer. Further studies are required to confirm the role of ATRIP in breast cancer susceptibility, refine risk assessment, and evaluate potential personalized therapeutic strategies. In the interim, genetic counseling for ATRIP mutation carriers should proceed with caution, given current limitations in clinical interpretation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".