Abstract 1648: Targeting ETS factor ETV4 as a novel therapeutic for the management of breast and prostate cancer
Notice bibliographique
Résumé
Abstract Despite the development of several successful targeted therapies, drug resistance and metastasis remain a significant challenge in the treatment of both breast (BCa) and prostate (PCa) cancers. For these reasons, there is an immediate need to identify a novel class of therapeutics targeting alternative factors, such as those that promote the metastatic capacity of tumour cells. ETS translocation variant 4 (ETV4) is a member of the ETS transcription factor family and is a significant mediator of tumorigenesis through its activation of several downstream pathways that are associated with migration and invasion. ETV4 is overexpressed in breast tumours and is associated with distant metastasis and poor prognosis particularly in triple negative BCa, which still lacks an approved targeted therapy. Similarly in PCa, overexpression of ETV4 is associated with the deregulation of the PI3K and Ras signalling pathways that are commonly implicated in metastatic disease. Like other ETS factors such as ERG and ETV1, fusion of the ETV4 gene can be found in a subtype of PCa cases and is associated with the disease progression. Thus, ETV4 is an important therapeutic candidate with potential applications in both advanced BCa and PCa. Drug development against ETV4 is made even more significant due to the lack of any approved therapy that directly targets it or any other members of the ETS family. Using a combination of in silico screening and in vitro assays, we have identified several small molecules with strong binding affinities and selectivity toward the DNA binding domain of ETV4. The prostate cell line, PC3, and the triple negative breast cancer cell line, MDA-MB-231, were used for in vitro studies as they endogenously express moderate to high levels of ETV4. Over 100 candidate compounds, which were selected from virtual screening against millions of small-molecular structures, were tested across the two cell lines using a luciferase-based transcriptional reporter assay. From this assay approximately 30 compounds were identified with significant inhibition on the transcriptional activity of ETV4 without a cytotoxic effect. The most potent of these compounds was shown by protein nuclear magnetic resonance (NMR) to directly interact with specific residues within the DNA binding domain. These compounds were also able to inhibit the migratory capacity of cancer cells. This data provides evidence for the direct targeting of ETV4 by small molecules, and future work will aim to further characterize their mechanism of action and effects on downstream targets in an effort to create a novel therapeutic strategy to treat metastatic breast and prostate cancers. (Supported by grants from the Canadian Cancer Society Research Initiative and Prostate Cancer Canada) Citation Format: Miriam S. Butler, Michael Hsing, Mani Roshan Moniri, Desmond Lau, Paul Yen, Ari Kim, Scott Lien, Marta Mroczek, Fariba Ghaidi, Eric LeBlanc, Lawrence McIntosh, Michael Cox, Artem Cherkasov, Paul S. Rennie. Targeting ETS factor ETV4 as a novel therapeutic for the management of breast and prostate cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1648. doi:10.1158/1538-7445.AM2015-1648
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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».