Development of Olaparib-Resistance Prostate Cancer Cell Lines to Identify Mechanisms Associated with Acquired Resistance
Bibliographic record
Abstract
BACKGROUND: Poly (ADP-ribose) polymerase inhibitors (PARPi) were initially deployed to target breast and ovarian tumors with mutations in DNA damage response genes. Recently, PARPi have been shown to be beneficial in the treatment of prostate cancer (PC) patients having exhausted conventional therapeutics. Despite demonstrating promising response rates, all patients treated with PARPi eventually develop resistance. However, PARPi resistance in PC is not well understood, and further studies are required to understand PARPi resistance in PC to propose strategies to circumvent resistance. METHODS: Starting from well-established olaparib-sensitive PC cell lines (LNCaP, C4-2B and DU145), we derived olaparib-resistant (OR) PC cell lines and performed a microarray analysis. RESULTS: The olaparib IC50 values of OR cell lines increased significantly as compared to the parental cell lines. Gene expression analyses revealed that different pathways, including DNA repair, cell cycle regulation and autophagy, were affected by acquired resistance. A total of 195 and 87 genes were significantly upregulated and downregulated, respectively, in all three OR cell lines compared to their parental counterparts. Among these genes, we selected BRCC3, ROCK2 and ATG2B for validation. We showed that ROCK2 expression, basal autophagy and homologous recombination (HR) efficiency were increased in all OR cell lines. CONCLUSIONS: Our study provides a new in vitro model to study PARPi resistance in PC and suggests new possible targets to reverse resistance and prolong the benefits of PARPi treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".