Abstract 2996: Pre-activation of autophagy impacts PARP inhibitor sensitivity of prostate cancer cells
Bibliographic record
Abstract
Abstract Introduction: Advanced prostate cancer (APC) is one of the most common causes of cancer-related mortality in males largely related to the development of resistance to hormonal and chemotherapeutic based regimens. Recently, the PARP inhibitor (PARPi) olaparib was shown to improve progression-free and overall survival in patients with APC although resistance remains a barrier to cure. Therapeutic resistance in cancers can be mediated by autophagy, a cellular recycling process. Here we addressed the role of autophagy in the development of olaparib resistance in APC. Methods: Autophagy levels and olaparib sensitivity were evaluated in prostate cancer (PC) cell lines (LNCaP, C4-2B and PC-3) by western blots and clonogenic assays, respectively. We introduced a double-tagged (mCherry-GFP) LC3 protein in cells to monitor autophagic flux by confocal microscopy and evaluated the temporal importance of autophagy activation by rapamycin on olaparib sensitivity. We measured cell proliferation (Incucyte), cell cycle (flow cytometry) and DNA repair (microscopy). Finally, we confirmed the role of autophagy in olaparib sensitivity using CRISPR/Cas9 Atg16L1 knockout cell lines. Results: We found a correlation between the basal level of autophagy and olaparib sensitivity in PC cell lines. PC-3 cells were olaparib resistant and had a higher basal level of autophagy compared to LNCaP and C4-2B cells, which were PARPi sensitive. When autophagy was pre-activated before olaparib treatment, PC cell lines became more resistant by increasing homologous recombination activity. This autophagy-mediated resistance was partially regulated by a balance between SQSTM1 and FLNA protein levels in the nucleus. Inhibition of autophagy or post-activated autophagy prevented development of PARPi resistance. Conclusion: The autophagic flux is associated with PARPi resistance in PC cell lines by regulating DNA repair. Inhibiting autophagy may lead to new strategies to increase PARPi efficacy. Understanding the role of autophagy in PC progression may lead to strategies that prevent the development of PARPi resistance. Citation Format: Maxime Cahuzac, Benjamin Péant, Hubert Fleury, Anne-Marie Mes-Masson, Fred Saad. Pre-activation of autophagy impacts PARP inhibitor sensitivity of prostate cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2996.
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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) | 0.001 | 0.000 |
| 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".