Abstract 948: A novel combinatorial therapy for lethal neuroendocrine prostate cancer
Bibliographic record
Abstract
Abstract Background: Neuroendocrine prostate cancer (NEPC) is a highly aggressive subtype of prostate cancer that can arise de novo, but more commonly develops after hormone therapies for advanced prostate adenocarcinoma. Current treatment options for NEPC are only palliative, and most patients die within several months. Additionally, single-agent clinical trials targeting NEPC so far have only produced disappointing results, highlighting the clear need to develop effective combinatorial therapies for NEPC. RB1 loss, a pivotal event in the development of NEPC, can sensitize cancer cells to ferroptosis in multiple cancer cell types, including prostate cancer. Here, we aim to identify an optimal combinatorial therapy for NEPC based on targeting ferroptosis. Methods: We determined the cell-killing efficacy of ferroptosis inducers and several current and emerging treatment regimens for NEPC as single agents, then performed drug synergism analyses of the above two potent treatments. Lastly, we investigated the molecular mechanisms of drug synergism by examining the major types of cell death induced by combinatorial treatment through molecular and biochemical assays. Results: Our results demonstrated that both ferroptosis inducers and BCL2 inhibitors as single agents led to robust cell death in NEPC cell lines tested. In contrast, cisplatin, the standard of care for NEPC, and Aurora kinase A inhibitor showed modest to no cell-killing effect. Furthermore, suboptimal doses of ferroptosis inducers and BCL-2 inhibitors synergistically induced cell death in NEPC cell lines. Unexpectedly, we found that low-dose ferroptosis inducer led to increased production of mitochondria ROS, which in turn exacerbated BCL-2 suppression-induced apoptosis. Conclusions: Our findings reveal a novel combinatorial therapy for NEPC. Based on our in vitro data, we will further test the in vivo therapeutic efficacy of ferroptosis inducers combined with BCL-2 inhibitors against NEPC growth. Citation Format: Mu-En Wang, Wei-Ling Tu, Yi Lu, Jinjin Wu, Alyssa Bawcom, Andrew J. Armstrong, Qianben Wang, Yuzhuo Wang, Jiaoti Huang, Ming Chen. A novel combinatorial therapy for lethal 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 948.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".