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Record W4293802590 · doi:10.3389/fonc.2022.976959

Characterization of genetic predisposition to molecular subtypes of breast cancer in Brazilian patients

2022· article· en· W4293802590 on OpenAlexaff
Daniele Paixão, Giovana Tardin Torrezan, Karina Miranda Santiago, Maria Nirvana Formiga, Samuel Terkper Ahuno, Emmanuel Dias‐Neto, Israel Tojal da Silva, William D. Foulkes, Paz Polak, Dirce Maria Carraro

Bibliographic record

VenueFrontiers in Oncology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsMcGill University
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsCHEK2PALB2Breast cancerPenetranceGermline mutationGeneticsGermlineCancerBiologyPopulationGeneMutationOncologyMedicineInternal medicinePhenotype

Abstract

fetched live from OpenAlex

Introduction BRCA1 and BRCA2 germline pathogenic variants (GPVs) account for most of the 5-10% of breast cancer (BC) that is attributable to inherited genetic variants. BRCA1 GPVs are associated with the triple negative subtype, whereas BRCA2 GPVs are likely to result in higher grade, estrogen-receptor positive BCs. The contribution of other genes of high and moderate risk for BC has not been well defined and risk estimates to specific BC subtypes is lacking, especially for an admixed population like Brazilian. Objective The aim of this study is to evaluate the value of a multigene panel in detecting germline mutations in cancer-predisposing genes for Brazilian BC patients and its relation with molecular subtypes and the predominant molecular ancestry. Patients and methods A total of 321 unrelated BC patients who fulfilled NCCN criteria for BRCA1/2 testing between 2016-2018 were investigated with a 94-genes panel. Molecular subtypes were retrieved from medical records and ancestry-specific variants were obtained from off-target reads obtained from the sequencing data. Results We detected 83 GPVs in 81 patients (positivity rate of 25.2%). Among GPVs, 47% (39/83) were identified in high-risk BC genes ( BRCA1/2, PALB2 and TP53 ) and 18% (15/83) in moderate-penetrance genes ( ATM, CHEK2 and RAD51C ). The remainder of the GPVs (35% - 29/83), were identified in lower-risk genes. As for the molecular subtypes, triple negative BC had a mutation frequency of 31.6% (25/79), with predominance in BRCA1 (12.6%; 10/79). Among the luminal subtypes, except Luminal B HER2-positive, 18.7% (29/155) had GPV with BRCA1/2 genes contributing 7.1% (11/155) and non- BRCA1/2 genes, 12.9% (20/155). For Luminal B HER2-positive subtype, 40% (16/40) had GPVs, with a predominance of ATM gene (15% - 6/40) and BRCA2 with only 2.5% (1/40). Finally, HER2-enriched subtype presented a mutation rate of 30.8% (4/13) with contribution of BRCA2 of 7.5% (1/13) and non- BRCA1/2 of 23% (3/13). Variants of uncertain significance (VUS) were identified in 77.6% (249/321) of the patients and the number of VUS was increased in patients with Asian and Native American ancestry. Conclusion The multigene panel contributed to identify GPVs in genes other than BRCA1 / 2 , increasing the positivity of the genetic test from 9.6% ( BRCA1/2 ) to 25.2% and, considering only the most clinically relevant BC predisposing genes, to 16.2%. These results indicate that women with clinical criteria for hereditary BC may benefit from a multigene panel testing, as it allows identifying GPVs in genes that directly impact the clinical management of these patients and family members.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

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

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 head0.003
GPT teacher head0.245
Teacher spread0.242 · 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 teacher head, 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".

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Citations8
Published2022
Admission routes1
Has abstractyes

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