Abstract 2952: Targeting CDK9 reactivates epigenetically silenced genes in cancer
Notice bibliographique
Résumé
Abstract In cancer, the epigenome is aberrantly reprogrammed leading to a wide range of heritable changes in gene expression, such as silencing of tumor suppressor genes (TSG). Altered epigenetic marks in cancer involve DNA methylation and histone post-translational modifications, and these come about as a result of aging and acquisition of genetic and epigenetic changes in readers/writers/editors of the epigenome. Given the reversible nature of epigenetic modifications, one goal of epigenetic therapy of cancer is to induce TSG reactivation, leading to cancer cell differentiation and cancer cell death. To identify novel targets that can reactivate epigenetically silenced genes, we developed a phenotypic-based system, YB5. YB5 is a colon cancer cell line generated by stably transfecting SW48 cells with a vector containing GFP driven by a methylated and silenced CMV promoter. GFP re-expression can be achieved by known epigenetic drugs that lead to demethylation or induce active chromatin marks in the CMV promoter. We screened a natural compound library for GFP activation in YB5 and identified a novel drug class that shares an aminothiazole core structure, and has epigenetic effects that are equivalent to DNA methyltransferase inhibitor (DNMTi). Target deconvolution identified CDK9 as the target of these drugs, which reactivate gene expression without affecting DNA methylation. It is well established that CDK9, the catalytic subunit of p-TEFb, is a transcriptional activator. CDK9 in complex with its regulatory subunit, Cyclin T1 or T2, is recruited by multiple mechanisms to promote RNAPII promoter-proximal pause release by phosphorylating negative elongation factors (DSIF and NELF). In addition, phosphorylation of the C-terminal domain (CTD) of RNAPII on Serine-2 allows recruitment of RNA processing factors, which work on the nascent RNA as it emerges from RNAPII. Our new data show that long-term CDK9 inhibition can reactivate epigenetically silenced genes with minimal downregulation effects, effects which are the opposite of the canonical role of CDK9-mediated transcriptional elongation. Mechanistically, we showed that CDK9 inhibition dephosphorylates the SWI/SNF protein SMARCA4 and represses HP1α expression, both of which contribute to gene reactivation. Based on gene activation, we developed the highly selective and potent CDK9 inhibitor MC180295 (IC50 =5nM) that has broad anti-cancer activity in-vitro and is effective in in-vivo cancer models. Additionally, CDK9 inhibition sensitizes with the immune checkpoint inhibitor α-PD-1 in vivo, making it an excellent target for epigenetic therapy of cancer. This is the first study that links CDK9 to maintaining gene silencing at epigenetically repressed loci in mammals. Excitingly, this is also the first example of kinase inhibitors as potential drugs that reverse epigenetic silencing. Citation Format: Hanghang Zhang, Somnath Pandey, Meghan Travers, Jittasak Khowsathit, George Morton, Hongxing Sum, Carlos A. Barrero, Carmen Merali, Yasuyuki Okamoto, Takahiro Sato, Judit Garriga, Natarajan V. Bhanu, Johayra Simithy, Bela Patel, Jozef Madzo, Noël Raynal, Benjamin A. Garcia, Marlene A. Jacobson, Salim Merali, Yi Zhang, Wayne Childers, Magid Abou-Gharbia, John Karanicolas, Stephen B. Baylin, Cynthia A. Zahnow, Jaroslav Jelinek, Xavier Graña, Jean-Pierre J. Issa. Targeting CDK9 reactivates epigenetically silenced genes in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2952.
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) | 0,003 | 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 ».