Abstract B015: HOXA9 promotes enzalutamide resistance in RB-p53 deficient prostate cancer
Bibliographic record
Abstract
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".