Abstract POSTER-TECH-1101: Characterization of genomic landscapes of BRCA1 and BRCA2 implicated ovarian cancer specimens from a founder french canadian population
Bibliographic record
Abstract
Abstract Although molecular genetic profiling of ovarian cancers harboring germline BRCA1/BRCA2 mutations suggest that pathways in common with sporadic cases are involved in the pathogenesis of the disease, overall survival differs between BRCA1, BRCA2 and sporadic disease. To further dissect molecular pathways involved, which could account for differences in pathogenesis of the disease, we have investigated genomic landscapes in the BRCA1 and BRCA2 mutated ovarian cancers. Chromosomal anomalies were assessed in 28 specimens with BRCA1 (n=15), BRCA2 (n=12) or BRCA1 and BRCA2 (n=1) mutations using high-density Illumina SNP arrays. The majority (22/28) are serous adenocarcinomas while the remaining samples were either endometroid (2/28) or mixed adenocarcinomas (4/28). The cases harbor BRCA1/BRCA2 mutations from a French Canadian population, which exhibit strong founder effects. Allelic imbalance, copy number differences, intrachromosomal breaks and homozygous deletions were inferred visually using the Genome Viewer module of the BeadStudio software followed by ASCAT analysis. A statistical analysis was used to directly compare genotypes of BRCA1 versus BRCA2 positive samples. TP53 gene mutation status was also assessed. All samples were found to harbor a somatic TP53 mutation comprised of missense (19/28), nonsense (2/28), frame-shift (4/28) and (3/28) splice mutations. The results were compared to independently derived data generated previously from our group, which was largely comprised of sporadic cases (Wojnarowicz et al 2012), and to the genomic data from the Cancer Genome Atlas project (TCGA). The genomic landscapes of BRCA1 and BRCA2 mutated cancers overlap those reported in previous studies. However, there were significant differences in the genomic landscapes involving chromosome 6q between BRCA1 and BRCA2 mutation-positive cancers. This genomic distinction between BRCA1 and BRCA2 ovarian cancer samples may point to a region containing genes important in the etiology or progression of hereditary cancer. Citation Format: Eman AlShehri, Moria Belanger, Suzanna Arcand, Kathleen Klein Oros, Celia Greenwood, Patricia N. Tonin. Characterization of genomic landscapes of BRCA1 and BRCA2 implicated ovarian cancer specimens from a founder french canadian population [abstract]. In: Proceedings of the 10th Biennial Ovarian Cancer Research Symposium; Sep 8-9, 2014; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(16 Suppl):Abstract nr POSTER-TECH-1101.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".