Abstract P2-09-10: Double heterozygosity for BRCA1 and BRCA2 pathogenic variants in a French metastatic breast cancer patient
Bibliographic record
Abstract
Abstract Double heterozygosity is an extremely rare occurrence in hereditary breast and ovarian cancer syndrome (HBOC [MIM 604370; MIM 612555]) where two pathogenic variants, one in BRCA1 and one in BRCA2, are found in an individual. To date, only a few case reports and case series have been reported in the literature (1-3). Furthermore, little is known about the clinical characteristics, family history, and tumor histology in these patients. In this study, we utilized targeted gene testing with next-generation sequencing (NGS) technology in an early-onset metastatic breast cancer patient from France. We evaluated germline variants using Pathway Genomics' BRCATrueTM NGS test, which analyzes variants covering all exons and exon flanking regions in both the BRCA1 and BRCA2 genes. All variant calls were determined after alignment and mapping to the GRCh37/hg19 reference genome. Variant calls were confirmed by Sanger sequencing. In this patient, a c.1016dupA (p.V340GfsX6) frameshift variant was found in BRCA1 along with a c.6814delA (p.R2272EfsX8) frameshift variant in BRCA2. Both frameshift variants are predicted to truncate the BRCA proteins. The BRCA1 c.1016dupA variant is considered a Norwegian founder mutation but has also been observed in individuals who are of French-Canadian, French, Italian or Dutch ancestry (4-7). The BRCA2 c.6814delA (p.R2272Efs*8) pathogenic variant, also known as 7042delA, is predicted to truncate the BRCA2 protein and has been identified in individuals with a personal or family history of breast and/or ovarian cancer (8,9). To the best of our knowledge, the combination of these two pathogenic variants in an individual has not been previously reported. In a clinical diagnostic setting, the possibility of double heterozygosity of pathogenic variants in more than one susceptibility gene should be considered, especially in patients with early-onset metastatic cancers. Furthermore, genetic testing and genetic counseling should also be indicated for high-risk family members. 1. Heidemann, S. et al. (2012) Breast cancer research and treatment 134, 1229-1239 2. Lavie, O., et al. (2011) Annals of oncology : official journal of the European Society for Medical Oncology / ESMO 22, 964-966 3. Nomizu, T., et al. (2012). Breast cancer 4. Andersen, T. I., Borresen, A. L., and Moller, P. (1996) American journal of human genetics 59, 486-487 5. Caputo, S., et al. (2012) Nucleic acids research 40, D992-1002 6. Dorum, A., et al. (1999). American journal of human genetics 65, 671-679 7. Simard, J., et al. (1994). Nature genetics 8, 392-398 8. Novakovic, S., et al. (2012) International journal of oncology 41, 1619-1627 9. Tea, M. K., et al. (2014) Maturitas 77, 68-72. Citation Format: Curtit E, Meynard G, Villanueva C, Mansi L, Chaix M, Vilalta A, Kuo JZ, Villa M, Neidich J, Tomar A, Arianpour A, Lebahar P, Pivot X. Double heterozygosity for BRCA1 and BRCA2 pathogenic variants in a French metastatic breast cancer patient. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P2-09-10.
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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 | 0.000 |
| 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 | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".