Abstract 686: Potentiation of the cytocidal effect of streptozotocin on carcinoid neuroendocrine cells by a pharmacological inhibitor of poly(ADP-ribose) polymerase
Bibliographic record
Abstract
Abstract Carcinoid neuroendocrine tumors (CNETs) are resistant to chemotherapy and the higher level doses of single or combination chemotherapy that are effective against these cancers also cause significant side-effects to the surrounding healthy tissues; therefore it is necessary to potentiate chemotherapy of these cancers. In the advanced clinical trials for different cancers, the pharmacological inhibitors of the DNA damage-responsive nuclear enzyme poly(ADP-ribose) polymerase-1 (PARP-1 or PARP) have shown a significant promise either as monotherapy or as potentiators of other chemotherapeutic agents. Here, we examined whether PARP-inhibitor PJ-34 can potentiate the therapy of CNETs by streptozotocin (STZ), because STZ causes DNA damage that is repaired by base excision repair pathway in which PARP-1 is known to play a significant role. We used the CNDT2.5 as model NET cells to show that treatment of cells with 1 μM PJ-34 could effectively block the activation of PARP in response to 0.5 and 1 mg/ml STZ. We also show that lower dose of STZ (0.5 mg/ml), which had no impact on the viability or the clonogenicity of cells becomes cytocidal by co-treatment with PJ-34. The potentiation effect by PJ-34 was also seen at higher (1 mg/ml) doses of STZ. We are currently examining the mechanism of potentiation of STZ in NETs by PARP-inhibitors. In conclusion, our results demonstrate that PARP-inhibitor can significantly potentiate therapeutic efficacy of STZ against NETs, and thus add back the chemotherapy option against these cancers. Acknowledgment: We are thankful to the Canadian Institutes of Health Research for the Banting & Best Graduate Scholarship to VR and the research grant support (Grant # MOP-89964) to GMS. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 686.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".