Abstract LB-100: Optimal modulation of DNA repair in CLL therapy
Bibliographic record
Abstract
Abstract Resistance to chlorambucil (CLB) in chronic lymphocytic leukemia (CLL) can occur as a consequence of increased DNA repair including c-abl stimulated Rad-51 related homologous recombinational repair (HRR) and DNA-PK related nonhomologous endjoining (NHEJ). Recent reports suggest that the nonreceptor tyrosine kinase c-abl plays an important role in CLL. In particular, we have previously demonstrated that imatinib inhibition of c-abl or NU7026 inhibition of DNA-PK in CLL lymphocytes results in sensitization to CLB in most samples. Here we report that nilotinib, a superpotent (20-30 fold greater than niltinib) inhibitor of c-abl is more efficacious than imatinib in sensitizing CLL lymphocytes to CLB in the majority of the CLL lymphocyte samples associated with a greater nilotinib related inhibition of c-abl autophosporylation, increased apoptosis and decreased repair of CLB-induced DNA damage (increased activated H2AX). Furthermore, in CLL samples in which c-abl was inhibited by either inhibitor, there was an increased activation of DNA-PK. Utilizing NU7026, a specific inhibitor of DNA-PK, with nilotinib or imatinib resulted in further sensitization to CLB but there was a greater sensitization to CLB with nilotinib than imatinib. These results suggest: (1) a more potent inhibition of c-abl is more efficacious in sensitizing CLL lymphocytes to CLB, (2) inhibition of c-abl results in a compensatory increase in DNA-PK and (3) inhibiting both DNA repair systems optimally sensitizes CLL lymphocytes to CLB, an effect which is most pronounced with the more potent c-abl inhibitor, nilotinib. 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 LB-100.
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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 | 0.001 | 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) | 0.003 | 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".