Abstract 2835: BRCA1 signature in high-risk fallopian tube epithelium
Bibliographic record
Abstract
Abstract Background: High-grade serous ovarian cancer is rarely diagnosed at an early and potentially curable stage, effective early detection and preventative strategies are few. Recently the discovery of occult invasive and intraepithelial tubal carcinomas in BRCA1 mutation carriers, who are at high risk of serous cancer, undergoing prophylactic surgery has focused attention on the fallopian tube epithelium as the cell of origin and has led to the reporting of putative serous cancer precursor lesions. However, little is known of the early molecular events of serous oncogenesis, or why cancers in BRCA 1 mutation carriers are found preferentially in tissues which are responsive to reproductive hormones. We hypothesize that molecular alterations are present in morphologically normal tubal epithelium from BRCA1 heterozygotes, and that these changes may reflect the earliest alterations in serous carcinogenesis and may be markers of increased cancer risk as well as targets for risk reduction. To identify cancer predisposition candidate genes of high-risk fallopian tube epithelium, we compared gene expression profiles of microdissected tubal epithelium from BRCA1 mutation carriers, control women and patients with HGSC. Methodology: Snap-frozen tissues were selected from the UHN Biobank; control and BRCA cases controlled for age, ovarian cycle status at surgery, and hormone therapy. Cases included 12 BRCA1 mutation carriers and 12 control women, undergoing salpingo-oophorectomy for reasons other than adnexal malignancy or family history, 15 HGSC and 8 contralateral normal tubes. Epithelium was microdissected in all cases using laser capture, RNA extracted and cDNA amplified. The gene expression profiles were generated using Affymetrix Human Genome U133 Plus 2.0 Array. Candidate genes were validated by qPCR and IHC on 2 fallopian tube TMAs. IHC was scored using Spectrum. Statistical analysis was performed using ANOVA (p<0.05) and Fisher's Exact Test p<0.05). Results: We focused the microarray analyses on identifying differential expression between BRCA1 heterozygotes and controls. Comparisons between FTE-nonBRCA and FTE-BRCA, resulted in 440 probe sets with more than 2-FC in gene expression. We selected 5 genes to validate by qPCR and IHC, based on gene ontology and known associations to cancer pathways. Conclusions: These results show that histological normal fallopian tube epithelium from BRCA1 heterozygotes have altered gene expression and these differences are most pronounced in the post-ovulatory phase of the ovarian cycle in pre-menopausal women, suggesting that factors associated with the luteal phase are implicated in the increased risk of HGSC in BRCA1 mutation carriers. We also show that genes involved in inflammation pathways are up-regulated in mutation carriers and that these genetic signatures are maintained in HGSC. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2835. doi:10.1158/1538-7445.AM2011-2835
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".