Abstract LB-205: Combination of DNA methyltransferase and PARP inhibitors as a novel therapy strategy for poor prognosis acute myeloid leukemia and triple-negative breast cancers
Bibliographic record
Abstract
Abstract Poly (ADP-ribose) polymerase (PARP) inhibitors (PARPis) have shown efficacy in treatment of breast and ovarian cancers with hereditary deletions of BRCA1/2, but the high promise of these drugs has not yet been realized in sporadic cancers. We present here strong preclinical data for a novel, mechanistically based, combinatorial approach to using DNA methyltransferase inhibitors (DNMTi’s), such as decitabine (DAC) and 5-Azacytidine (5-AZA), with PARP inhibitors (PARPi’s) as a treatment strategy for acute myelogenous leukemias (AML) and estogen-, progesterone- and HER2-receptor negative, or triple negative breast cancer (TNBC). We have previously demonstrated that low doses of 5-AZA and DAC alone show efficacy in AML and TNBC, and propose treatment with PARPi's to enhance sensitivity of cancer cells to DNMTis. The mechanistic rationale for our approach is based upon: 1) data from our group and others showing DNMT1 and PARP1 associate in a complex, and this association increases with DNA damage; 2) the fact that 5-AZA and DAC trap DNMT's led us to hypothesize that these drugs might also increase PARP trapping at DNA damage sites; and 3) the cytotoxicity of the most potent PARPi's (e.g. Talazoparib) appears to correlate with the degree of trapping of PARP1 in chromatin. We find that in cultured human AML and TNBC cells, the DNMTi's (5 to 20 nM DAC or 100 to 200nM 5-AZA) and PARPi's (1 to 10 nM Talazoparib) alone trap PARP into chromatin, and this effect is enhanced when the drugs are combined. In addition, the PARPi-DNMTi combination treatment in TNBC MDA-MB-231 and AML MOLM-14 cell lines resulted in significantly increased DNA double strand breaks (DSBs) and enhanced retention of PARP1 and DNMT1 at laser microirradiation DNA damage sites. Compared with non-tumorigenic MCF10A cells, in TNBC cell lines (N = 4), the combined doses resulted in significant (p<0.05) increases in colony survival, when compared to single drug treatments. Similarly, AML cell lines (N = 3) as well as primary cells (N = 8) showed dramatic decreases (p<0.05) in colonies in combination vs single agent drug treatments. In the most important translational implications, mouse xenograft experiments, using BRCA mutant TNBC cell line SUM149PT and MDA-MB-231 with intact BRCA1, both models demonstrated that the combination treatment has a significant (p<0.05) survival advantage, compared to control (vehicle), AZA (0.5mg/kg) or BMN (0.3 mg/kg) alone. Likewise in AML xenografts of MOLM14 and MV411 cell lines with poor prognosis marker, FMS-like 3 internal tandem duplication (FLT3/ITD), the drug combination show (p<0.05) significantly decreased leukemia burden, as measured by luciferase imaging. Our data suggest a novel use of both DNMTi's and PARPi's in a compelling therapeutic strategy for TNBCs independent of BRCA mutations and poor prognosis AML; the latter will be investigated in a clinical trial funded by Van Andel-SU2C. Citation Format: Feyruz V. Rassool, Nidal Muvarak, Khadiza Chowdury, Carine Robert, Limin Xia, Eun Yong Choi, Yi Cai, Marina Bellani, Ying Zou, Michael Seidman, Søren Bentzen, Maria Baer, Rena Lapidus, Stephen B. Baylin. Combination of DNA methyltransferase and PARP inhibitors as a novel therapy strategy for poor prognosis acute myeloid leukemia and triple-negative breast cancers. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-205.
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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".