Abstract A63: Estrogen receptor signaling in fallopian tube epithelia of BRCA mutation carriers
Bibliographic record
Abstract
Abstract Background: The most common and aggressive type of epithelial ovarian cancers (EOC) is high-grade serous carcinoma (HGSC), which accounts for 90% of ovarian cancer deaths. HGSC is the predominant histotype associated with BRCA1 and BRCA2 mutations. Prophylactic surgery in BRCA mutation carriers has implicated the fallopian tube epithelium (FTE), a hormonal responsive tissue, as the etiologic site of origin for HGSC. Estrogen and its receptors are major regulators of growth and differentiation in normal ovaries and fallopian tubes, and its mutagenic properties have been linked to ovarian carcinogenesis. Estrogen receptors (ER) are rarely mutated, amplified, or deleted in HGSC, yet only 10% of patients respond to antiestrogen treatment. TP53 mutations in the form of the p53 signature have been found in serous tubal intraepithelial carcinomas (STIC) and are ubiquitously present in patients with HGSC. We hypothesized that in the presence of dysfunctional p53, subsequent promiscuous binding of ER will yield aberrant signaling, contributing to cellular transformation. Methods: We used our previously published gene expression profiles to generate a candidate gene list, which was chosen based on the presence of known estrogen-responsive elements. We analyzed expression of 6 ER responsive genes using data collected from laser capture microdissection in normal FTE tissues. Tissue microarray analysis (TMA) was also performed on a subset of HGSC tumor samples from this cohort, staining for PR, ER, and p53, and expression was analyzed alongside their respective outcome and overall survival Finally, to mimic the in vivo environment of early carcinogenesis, FTE-normal and FTE-p53 mutant cell lines were established and treated with 100nM estradiol, an estrogen analog, to observe changes in response. Results: Preliminary data showed that FTE-BRCA and FTE-nonBRCA seemingly look and express ER and PR proteins similarly. Underlying these morphologic similarities is a potential haploinsufficiency predisposing FTE-BRCA to cytotoxic stresses. Microarray gene expression of laser captured FTE-BRCA and FTE-nonBRCA showed varied levels of ER mRNA expression across samples (n=25) while PR transcript levels change dynamically. The data generated have facilitated the development of gene signatures and biomarkers that will predict response to antiestrogen therapy and identify patients who will benefit from hormonal therapies. Citation Format: Leah V. Dodds, Omar Nelson, Patricia Shaw, Anca Milea, Ramlogan Sowamber, Sophia HL George. Estrogen receptor signaling in fallopian tube epithelia of BRCA mutation carriers. [abstract]. In: Proceedings of the AACR Conference: Addressing Critical Questions in Ovarian Cancer Research and Treatment; Oct 1-4, 2017; Pittsburgh, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(15_Suppl):Abstract nr A63.
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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".