Abstract A037: Kinase GRK3 connects angiogenesis and neuroendocrine differentiation in prostate cancer progression by enhancing epigenetic activity of HDAC2
Bibliographic record
Abstract
Abstract Background: Treatment-related neuroendocrine prostate cancer (NEPC) is an aggressive subset of castration-resistant prostate cancer (CRPC), found in ~20% of lethal CRPC. The mechanisms underlying the progression of prostate cancer to NEPC are largely unclear, and new drug targets are desperately needed. NEPC is known to be highly vascularized. Elevated expression of NE markers and increased angiogenesis are two prominent phenotypes of NEPC, and thus are expected to be linked. However, direct molecular links between these two phenotypes are still elusive, whose elucidation will substantially expand our knowledge in NEPC and enable the development of effective treatments for NEPC. Through RNAi & cDNA screening and functional validations, we previously discovered that GPCR-kinase 3 (GRK3) is essential preferentially for highly metastatic cancer cells as compared to lowly metastatic cancer cells. The mechanisms of GRK3 in prostate cancer progression were mostly unknown. Methods: We assessed GRK3’s expression in patient samples through IHC staining on TMA and data mining on public RNA-seq datasets with large cohorts. Using molecular and cell biology methods, we determined the impacts of GRK3 and HDAC2 overexpression and silencing on NE marker expression and angiogenesis in prostate cancer cells. Through biochemistry, we investigated the nature of GRK3-HDAC2 relation. By ChIP-PCR, we measured the impacts of GRK3 genetic and pharmacological modulations on HDAC2’s epigenetic activity. Through compound library screening and biochemical characterization, we searched for novel GRK3 inhibitors to study GRK3 biology and to evaluate whether GRK3 is a suitable drug target for prostate cancer. Results: GRK3 is significantly overexpressed in metastatic prostate tumors from patients, especially in NEPC. GRK3 promotes both angiogenesis and neuroendocrine differentiation in prostate cancer cells, indicating that it is a key missing link for these two phenotypes. Mechanistically, GRK3 enhances the epigenetic repressor activity of histone deacetylase 2 (HDAC2) to suppress key repressors of angiogenesis or NE phenotype. We have identified several compounds that block kinase activity of GRK3 much more potently than that of GRK2, the closest-related kinase to GRK3. Of note, our GRK3 inhibitors could substantially reduce angiogenesis and NE marker expression, as well as significantly inhibit NEPC cell growth in culture and in mouse xenografts. Conclusion: Kinase GRK3 connects angiogenesis and neuroendocrine differentiation in prostate cancer progression. Its mechanism of actions is at least in part through enhancing HDAC2’s epigenetic activity. Results based on our novel GRK3 inhibitors suggest that GRK3 is a valuable new drug target for aggressive prostate cancer. Citation Format: Samira Naderinezhad, Zheng Wang, Guoliang Zhang, Michael Ittmann, Martin Gleave, Wenliang Li. Kinase GRK3 connects angiogenesis and neuroendocrine differentiation in prostate cancer progression by enhancing epigenetic activity of HDAC2 [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 A037.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".