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Abstract P6-06-03: Novel hereditary breast cancer gene mutations: Should there be greater concern regarding ovarian cancer risk?

2016· article· en· W2312038691 on OpenAlexaboutno aff
Nicholas J. Nassikas, J. Scalia Wilbur, JK Laprise, RD Legare

Bibliographic record

VenueCancer Research · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsnot available
Fundersnot available
KeywordsPALB2Ovarian cancerBreast cancerProbandMedicineCancerOncologyGermline mutationInternal medicineMutationGeneticsCancer researchGynecologyBiologyGene

Abstract

fetched live from OpenAlex

Abstract INTRODUCTION: As the use of multi-gene breast cancer panel testing increases the phenotype of the included genes continues to evolve. PALB2 and NBN have a well characterized association with breast cancer and are included on many breast cancer gene panels. Germline PALB2 and NBN mutations have been identified in a small percentage of ovarian carcinoma cases with one study reporting a non-significant twofold increase in carriers of the PALB2 mutations amongst ovarian cancer patients (P= 0.4). Similar to BRCA1 and BRCA2 both genes are members of the Fanconi Anemia pathway therefore a potential increased risk for both breast and ovarian cancer could be anticipated. However at present overall the current literature on the association with ovarian cancer is sparse. Here we present the cases of three hereditary breast and ovarian cancer families found to carry pathogenic mutations within the PALB2 and NBN genes. In all three families the proband was diagnosed with ovarian or fallopian tube cancer and carries a pathogenic PALB2 or NBN mutation. Our PALB2 family carries the well-known French Canadian founder mutation, c.2323C>T, and includes the proband who was diagnosed with a stage II-C, grade 3, fallopian tube carcinoma at age 58, her heterozygote sister with ovary cancer at 68 and her mother with ovary cancer at 43 who was not able to be tested. This PALB2 proband has 5 sisters, 7 brothers and 41 nieces and nephews with only one sister diagnosed with breast cancer at 69 who also is PALB2 positive and a maternal grandmother with breast cancer at 48 who was unable to be tested. The NBN Slavic founder mutation, c.657_661del, was discovered in a 66 year old woman with stage IV, high-grade serous ovarian cancer having a mother with breast cancer at 91 and a maternal aunt with ovary cancer at 59 who have not yet been tested. Lastly, our patient from Laos with a diagnosis of a stage II-C endometrioid adenocarcinoma of the ovary diagnosed at 38 years old was found to carry the deleterious NBN mutation, c.1550dupA. She is not aware of any cancer family history and reports a large family including five brothers, four sisters and multiple aunts and uncles on both side of the family. CONCLUSION: These case studies suggest a link between PALB2 and NBN, two known breast cancer susceptibility genes, and hereditary ovarian cancer risk. These observations suggest that further data are needed to accurately evaluate ovarian cancer risk within novel hereditary breast cancer genes now commonly tested as part of multiplex panel analysis. Citation Format: Nassikas N, Wilbur JS, Laprise JK, Legare RD. Novel hereditary breast cancer gene mutations: Should there be greater concern regarding ovarian cancer risk?. [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 P6-06-03.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

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 studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.104
GPT teacher head0.395
Teacher spread0.291 · 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 designNot applicable
Domainnot available
GenreOther

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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Citations0
Published2016
Admission routes1
Has abstractyes

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