Bibliographic record
Abstract
Among Canadian women, breast cancer is the second most prevalent and second most lethal cancer. Frequently implicated in this type of cancer are hormone-related pathways, including estrogen-stimulated pathways. The effects of estrogens are mediated mainly through two nuclear receptors. One receptor, called estrogen receptor ⍺ (ER⍺), has been implicated in breast cancer and is expressed in about 70% of cases. These ER+ breast cancers are often treated with endocrine therapy; however, many patients relapse on this therapy. A possible mechanism driving this resistance is missense mutation of ER⍺ in its ligand-binding domain (LBD). Within the LBD, the most commonly mutated residues are Y537 and D538. Mutation at these residues, which is rare in primary tumours but often detectable in metastases, results in the ligand-independent activation of ER⍺. Several different mutations have been found at the Y537 residue, including Y537S. Although the Y537S mutation has been widely reported in endocrine therapy-resistant metastatic breast cancer, this mutation remains poorly characterized. The goal of this project was to characterize the ERa Y541S mutation, especially as it relates to metastasis. We hypothesized that the Y537S mutation would be associated with increased metastasis and worse overall survival in the MIC mouse model. Previously, the MIC model was modified to introduce the conditional ER⍺ Y541S mutant receptor, the murine homolog of the human ERa Y537S mutant. Using these mice with the conditional ER⍺ Y541S mutation, it was shown that the mutant allele did not affect overall survival or metastatic burden. Following this, RNASeq showed a greater expression of estrogen-response genes in ER⍺ Y541S tumours than in wild-type ERa tumours; however, immunohistochemical staining showed no difference in subcellular localization of ER⍺ between the control and ER⍺ Y514S tumours, suggesting that the increased expression of estrogen-response genes in ER⍺ Y541S tumors was not due to increased nuclear localization. Immunohistochemical staining also showed that ER⍺ Y541S tumours expressed more cytokeratin 14, a basal cytokeratin associated with a poorer prognosis. Other cytokeratins, including luminal cytokeratins, were not shown to be differentially expressed between the ER⍺-mutant and ER⍺-wild-type tumours. Motivated by the association between ERa Y537S and metastasis, an invasion assay was performed and showed greater invasiveness in an ER⍺ Y541S cell line than in a control cell line. In contrast, both cell lines showed a similar ability to migrate. Overall, this project supports previous observations that the ERa Y537S confers advantageous traits to metastases but not to primary tumours. By recapitulating these features of human metastatic breast cancer, the MIC model used here appears to be an appropriate model for studying the ERa Y537S mutation. In this way, this paper contributes to an improved understanding of ERa Y537S. In future, efforts to further understand this mutation could lead to the development of new therapeutic strategies to combat endocrine therapy-resistant metastatic breast cancer
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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 | 0.000 | 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) | 0.001 | 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 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".