IKKε Inhibitor Amlexanox Promotes Olaparib Sensitivity through the C/EBP-β-Mediated Transcription of Rad51 in Castrate-Resistant Prostate Cancer
Bibliographic record
Abstract
The progression of prostate cancer (PC) is often characterized by the development of castrate-resistant PC (CRPC). Patients with CRPC are treated with a variety of agents including new generation hormonal therapies or chemotherapy. However, as the cancer develops more resistance mechanisms, these drugs eventually become less effective and finding new therapeutic approaches is critical to improving patient outcomes. Previously, we have shown that IKKε depletion and IKKε inhibitors, BX795 and Amlexanox, decrease CRPC cell proliferation in vitro and in vivo and that IKKε inhibitors induce a senescence phenotype accompanied by increased DNA damage and genomic instability in CRPC cells. Here, we describe a new role for IKKε in DNA damage repair involving Rad51 and examine the therapeutic potential of Amlexanox combined with the PARP inhibitor Olaparib in CRPC cell lines. Combining Amlexanox with Olaparib decreased CRPC cell proliferation and enhanced DNA damage through the inhibition of Olaparib-induced Rad51 recruitment and expression in CRPC cells or IKKε-depleted PC-3 cells. We demonstrated that Rad51 promoter activity, measured by luciferase assay, was decreased with Amlexanox treatment or IKKε depletion and that Amlexanox treatment decreased the occupancy of transcription factor C/EBP-β on the Rad51 promoter. Our mouse model also showed that Amlexanox combined with Olaparib inhibited tumor growth of CRPC xenografts. Our study highlights a new role for IKKε in DNA damage repair through the regulation of Rad51 transcription and provides a rationale for the combination of Amlexanox and Olaparib in the treatment of patients with CRPC.
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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) | 0.001 | 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".