Characterizing the role of ER-alpha Y537S in metastatic breast cancer
Notice bibliographique
Résumé
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
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».