Abstract 2898: Development of the lipid kinase PIKfyve PROTAC degrader against neuroendocrine prostate cancer
Bibliographic record
Abstract
Abstract Therapies targeting the androgen receptor (AR) as the main driver of prostate cancer (PCa) can lead to various mechanisms of resistance and promote progression to castration-resistant PCa (CRPC), which has a median survival of only 13-23 months. Amongst recurrent CRPC, 17%-30% of patients develop neuroendocrine prostate cancer (NEPC), which is a PCa subtype characterized by a unique histology. NEPC exhibits a loss of AR signaling during neuroendocrine transdifferentiation which results in resistance to AR-targeted therapies and gain of cell characteristics resembling poorly differentiated neuroendocrine tumors. Despite advances in the understanding of NEPC development, treatment options remain limited, with platinum-based chemotherapy as the first-line treatment for both de novo and treatment-induced NEPC. However, response to first-line chemotherapy in NEPC is short, with a median survival of only seven months. The poor prognosis of NEPC is attributed in part to late diagnosis and a lack of effective therapeutic agents. Our previous work demonstrated that NEPC and AR-negative PCa exhibit higher dependency on the lipid kinase PIKfyve than AR-positive CRPC. Thus, development of PIKfyve inhibitory therapies targeting the emergent vulnerabilities of NEPC or AR-negative forms of PCa is a promising approach. Using a proteolysis targeting chimera (PROTAC) technology, we designed a class of PIKfyve specific degrader. The in vitro degradation efficiency were determined by immunoblotting, and DC50s (degradation concentration at 50%) were calculated for top candidates. Pharmacokinetic and pharmacodynamic were evaluated for in vivo study. In summary, we have developed a class of PIKfyve specific degrader using the E3 ligase von Hippel-Lindau (VHL) as a ligand via a diverse set of linkers. Mechanistic studies revealed that it induced PIKfyve degradation in a VHL- and proteasome-dependent manner. Citation Format: Yuanyuan Qiao, Chungen Li, Yang Zheng, Xia Jiang, Sarah Nicole Yee, Caleb Cheng, Yi Bao, Yuping Zhang, Yuzhuo Wang, Zhen Wang, Ke Ding, Arul Chinnaiyan. Development of the lipid kinase PIKfyve PROTAC degrader against neuroendocrine prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2898.
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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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".