Abstract B015: HOXA9 promotes enzalutamide resistance in RB-p53 deficient prostate cancer
Notice bibliographique
Résumé
Abstract Introduction: Castration resistant prostate cancer (CRPC) cells can acquire resistance to the androgen receptor (AR) inhibitor enzalutamide (EZ). These cells can switch lineages from an adenocarcinoma to a neuroendocrine (NE) cell type that proliferate independently of the AR signaling pathway. Cancer genomic and molecular studies identified that co-deletion of the retinoblastoma (RB1) and TP53 genes can promote the acquisition of EZ resistance and neuroendocrine features. However, RB and p53 are both tumour suppressor and are therefore difficult to target pharmacologically. The purpose of this study is to identify an actionable molecular factor downstream of RB and p53 that drives EZ resistance in CRPC. Methods and Results: To characterize functional and molecular features of RB and p53 loss, CRISPR-Cas9 was used to generate a double knockout (DKO) line in LNCaP prostate cancer cells. Compared with LNCaP wild type (WT) cells, only DKOs formed distinct colonies over a 4-week colony forming assay under EZ treatment. RNA sequencing of DKO and WT cells, followed by gene ontology (GO) analysis, revealed NE and stemness genes, including HOXA9, were significantly upregulated in DKO cells. To categorize gene loss events in EZ-treated LNCaP cells, a genome-wide CRISPR knockout screen was performed. Pools of KO cells were treated with either EZ or DMSO and then analyzed by next generation sequencing to identify gene mutations that confer increased resistance or sensitivity to EZ. GO analysis of de-enriched genes following EZ treatment identified stemness genes, including HOXA9, highlighting the potential importance of a stem-like phenotype for acquiring EZ resistance EZ. To further investigate the functional significance of HOXA9 we analyzed EZ-resistant prostate tumour genomic data. HOXA9 is mutated or mis-expressed in 10% of cases. Importantly, HOXA9 is either amplified or overexpressed in virtually all these cases, and is associated with poorer prognosis, suggesting an oncogenic role for HOXA9 in CRPC. HOXA9 transcript levels were positively correlated with neuroendocrine features and negatively correlated with RB1expression in these tumour samples. LNCaP WT and DKO cells we then engineered to overexpress HOXA9 displayed increased IC50 values following a 6-day EZ treatment, compared with either parental line. DKO cells that overexpress HOXA9 also formed significantly more colonies following a 4-week EZ treatment, compared with parentals. In contrast, shRNA knockdown of HOXA9 caused a reduction in IC50 values and formed fewer drug resistant colonies compared with control cells. Finally, DKO and WT cells were co-treated with varying concentrations of the HOXA9 inhibitor DB818 and EZ. DKO cells were more sensitive to DB818 alone at high concentrations and displayed higher synergy as measured by a ZIP synergy score when co-treated with EZ. Conclusions: Overall, these results suggest that HOXA9 regulates EZ resistance in prostate cancer. Furthermore, HOXA9 inhibition may be of therapeutic benefit for treating EZ-resistant CRPC. Citation Format: Michael V. Roes, Fred A. Dick. HOXA9 promotes enzalutamide resistance in RB-p53 deficient prostate cancer [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr B015.
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) | 0,005 | 0,002 |
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 ».