MétaCan
Menu
← Back to cohort

Abstract P5-09-08: Germline variants in non-BRCA homologous recombination genes detected in HER2-negative breast cancer patients

2019· article· en· W2911340974 on OpenAlexaboutno aff
KJ Vogel Postula, AK McGill, Erin G. Sutcliffe, PD Murphy, RT Klein, KS Hruska

Bibliographic record

VenueCancer Research · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsnot available
Fundersnot available
KeywordsPALB2CHEK2Breast cancerMedicineOncologyPopulationCancerInternal medicineOlaparibGermline mutationPARP inhibitorCancer researchGeneticsMutationBiologyGene

Abstract

fetched live from OpenAlex

Abstract Background: PARP inhibitors (PARPi) are FDA approved for a subset of metastatic human epidermal growth factor receptor 2-negative (H2N) breast cancer patients who harbor a germline pathogenic or likely pathogenic variant (PV) in BRCA1/2, two of the most well-described breast cancer susceptibility genes in the homologous recombination (HR) pathway. While the NCCN guidelines recommend consideration of BRCA1/2 testing for patients with H2N disease that are eligible for single-agent therapy, there are currently clinical trials available for women with advanced H2N breast cancer who have PVs in HR genes beyond BRCA1/2 to investigate outcomes of receiving PARPi. The yield of germline PVs in other HR genes in the H2N population is not well-described. Methods: Clinical histories and test results were reviewed for women with a diagnosis of H2N breast cancer who underwent multi-gene hereditary cancer panel testing that included a minimum of 10 homologous recombination (HR) genes in addition to BRCA1/2 (ATM, BARD1, BRIP1, CHEK2, FANCC, NBN, PALB2, PTEN, RAD51C, RAD51D). Those with prior BRCA1/2 testing were excluded. We assessed the yield of PVs in non-BRCA1/2 HR genes in the H2N breast cancer population. In addition, we compared the yield of PVs in non-BRCA1/2 HR genes in a “low risk” population (probands with H2N breast cancer with no reported personal history of ovarian or pancreatic cancer and no reported family history of breast, ovarian, pancreatic, or prostate cancer) to a “high risk” population (probands with H2N breast cancer who also have a personal history of ovarian or pancreatic cancer and/or a reported family history of breast, ovarian, pancreatic, or prostate cancer) via a two-tailed Fisher's exact test. Results: A total of 6179 women with H2N breast cancer were identified. Of these, BRCA1/2 PVs were identified in 4.8% (299/6179), while 5.7% (351/6179) carried PVs in HR genes other than BRCA1/2. These included CHEK2 (145), ATM (62), PALB2 (59), BRIP1 (26), FANCC (18), BARD1 (17), RAD51C (12), NBN (11), RAD51D (6), and PTEN (2). No statistically significant difference in the likelihood to harbor a PV in one of the 10 non-BRCA1/2 HR genes was observed between those with a “low risk” presentation (4.8% (53/1096) as compared to those with a “high risk” presentation (5.9% (298/5083)) (p=0.1956). Conclusions: Our findings show that the yield of PVs in HR genes other than BRCA1/2 is appreciable in the H2N breast cancer population. As such, it may be beneficial to include all HR genes when testing H2N breast cancer patients, regardless of other personal or family history, if and/or when a patient develops metastatic disease. Citation Format: Vogel Postula KJ, McGill AK, Sutcliffe E, Murphy PD, Klein RT, Hruska KS. Germline variants in non-BRCA homologous recombination genes detected in HER2-negative breast cancer patients [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P5-09-08.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.021
GPT teacher head0.349
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueCancer Research→Same topicBRCA gene mutations in cancer→French-language works237,207→