DRES-06. PREVENTING THE EMERGENCE OF TEMOZOLOMIDE RESISTANCE IN GLIOBLASTOMA BY PARP-1 INHIBITION
Bibliographic record
Abstract
The DNA alkylating agent temozolomide (TMZ) is active against the subset of glioblastomas (GBMs) in which the O6-methylguanine DNA methyltransferase (MGMT) gene is silenced by promoter methylation. However, despite their initial sensitivity, virtually all MGMT-methylated tumors acquire drug resistance and regrow in patients. Previously, we tested the hypothesis that inhibiting poly(ADP-ribose) polymerase-1 (PARP-1) might increase the potency of TMZ in resistant GBMs. Our results showed that primary cell lines derived from TMZ-resistant GBMs were re-sensitized by pre-treatment with the PARP-1 inhibitor ABT-888. While PARP-1 inhibitors may be useful for treating resistant cases, we predict that greater clinical benefit can be derived from its use in sensitive cases where inhibition may prevent the emergence of resistant clones. To test this hypothesis, we established an in vitro model of inducible resistance in the MGMT-methylated, TMZ-sensitive U251N GBM cell line. In this model, prolonged treatment of the U251N line with TMZ resulted in the emergence of resistant colonies of cells with de novo alterations in DNA repair pathways. Of note, sanger sequencing and western blot analyses revealed that some resistant colonies harbored mutations in mismatch repair (MMR) genes MSH2, MSH6 and MLH1 and have reduced expression of MSH2 and MSH6. These observations are strikingly similar to the recurrent, TMZ-refractory human disease where mutations in and downregulated expression of MMR genes are frequently reported. In another set of experiments, co-treatment of the parental U251N line with TMZ and ABT-888 prevents resistant colonies from emerging. Moreover, co-treatment causes established resistant colonies to regress, suggesting that PARP-1 inhibition can target and prune the evolution of TMZ-resistant populations. In summary, this work has the potential to show that PARP-1 inhibition may prevent or delay disease progression and prolong the life of patients who inherently benefit from TMZ therapy.
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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) | 0.003 | 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".