Abstract PS17-31: Investigating the estrogen receptor Y537S mutation in transgenic models of luminal B breast cancer
Bibliographic record
Abstract
Abstract Breast cancer is the most prevalent cancer in women and over two-thirds of cases express the estrogen receptor (ER). Significantly, metastatic ER positive breast cancer is the leading cause of breast cancer mortality. Despite the success of endocrine therapy to treat ER-positive breast cancers, resistance to treatment is a major problem and relapse commonly occurs though patients initially respond well to treatment. The ER Y537S mutant represents one of the most common gain-of-function mutations detected in the metastatic biopsies of patients with ER-positive breast cancer. Previous in-vitro analyses have shown that the ER Y537S mutant exhibits enhanced ER transcriptional activity by adopting a ligand-independent agonist confirmation. In our study, we seek to provide a deeper understanding of the role of this mutant by modeling the human ER Y537S mutant (ER Y541S in mice). Our lab has generated a Cre-inducible knock-in mouse model expressing the activating point mutation driven by the endogenous ER promoter, and it has been shown that when expressed ubiquitously the mutated ER leads to dramatic developmental effects. In order to further our observations in the context of endocrine resistant metastatic breast cancer, we characterize mamary tumour growth of the ER Y541S mutant in combination with luminal B models of mammary tumourigenesis. Consistent with the notion that these ER mutations occur seldom in primary tumours, preliminary data shows that tumour onset and tumour outgrowth is unaffected by the activating point mutation. When analysing tumours from both ER mutant and wildtype ER control animals, it was found that tumours with mutant ER display more basal-like cytokeratins at the RNA level via RNA sequencing and at the protein level via immunohistochemistry. This expression pattern is often associated with poorer prognosis in the clinic. Through ongoing analyses, we also seek to better understand our model through tumour regression studies (doxycycline withdrawal), treatment with tamoxifen and blocking the main source of estrogens via ovariotomies. By studying the ER Y537S mutation in models of luminal B breast cancer, we hope to investigate the factors leading to tumour recurrence and provide a deeper understanding of potential escape pathways to therapy. Citation Format: Gabriella Johnson, Joshua Roccamo, Cynthia Lavoie, Dongmei Zuo, Virginie Sanguin-Gendreau, Adrian Lee, Zheqi Li, Steffi Oesterreich, William Muller. Investigating the estrogen receptor Y537S mutation in transgenic models of luminal B breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS17-31.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".