21 Inhibiting PARP-1 to restore temozolomide sensitivity and prevent resistance in glioblastoma
Bibliographic record
Abstract
Adult Glioblastomas (GBMs) remain one of the least curable brain cancers despite the discovery and use of DNA alkylating agent Temozolomide (TMZ). TMZ provides a moderate survival benefit to sensitive patients whose O6-methylguanine-methyltransferase (MGMT) gene is silenced by promoter methylation. Unfortunately, TMZ potential is stunted because of the rapid onset of tumour recurrence and acquired resistance believed to result from the upregulation of DNA damage repair by the base excision repair (BER), mismatch repair (MMR), or homologous recombination (HR) systems. Our laboratory previously demonstrated that cell lines obtained from recurrent, TMZ-resistant GBMs could be re-sensitized to TMZ when treated with an inhibitor of poly (ADP-ribose) polymerase-1 (PARP-1) – a protein instrumental in the recruitment of BER machinery. From this preliminary research, we postulate that PARP-1 inhibition may not only be used to overcome established resistance in GBM but may also be used to prevent its emergence altogether. To test this hypothesis, we utilized the MGMT-methylated GBM cell line U251N and developed an in vitro model of inducible TMZ resistance. We verified that prolonged treatment of U251N cells with TMZ resulted in the emergence of resistant colonies that resembled recurrent GBM clinically observed in TMZ-treated patients. However, when the parental U251N line was co-treated with TMZ and PARP-1 inhibitor ABT-888, resistant colonies failed to appear. Therefore, PARP-1 inhibition may possess the potential to maintain tumour sensitivity to TMZ as well as evade the otherwise inevitable development of resistance in GBM.
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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".