MétaCan
Menu
Back to cohort

Abstract IA13: Combination of DNA methyltransferase and PARP inhibitors as a novel therapy strategy for multiple cancers: Key data in AML and triple negative breast cancer

2017· article· en· W2772948229 on OpenAlexaff
Nidal Muvarak, Khadiza Chowdhury, Carine Robert, Eun Yong Choi, Yi Cai, Marina A. Bellani, Michael M. Seidman, Maria R. Baer, Rena Lapidus, Stephen B. Baylin, Feyruz V. Rassool

Bibliographic record

VenueCancer Research · 2017
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsPARP1DecitabineCancer researchPoly ADP ribose polymeraseTriple-negative breast cancerPARP inhibitorBreast cancerOlaparibAzacitidineCancerDNA damageBiologySynthetic lethalityDNA repairPolymeraseDNA methylationDNAGeneticsGene expressionGene

Abstract

fetched live from OpenAlex

Abstract Poly (ADP-ribose) polymerase (PARP) inhibitors represent one of the most exciting recent developments in cancer therapy. While substantial efficacy has been shown with clinically available PARP inhibitors (PARPis), to date, in treatment of hereditary deletions of BRCA1/2 in breast and ovarian cancers, 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 (DNMTis), such as decitabine (DAC) and 5-Azacytidine (5-AZA), with PARP inhibitors (PARPis) as a treatment strategy for acute myelogenous leukemias (AML) and 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 PARPis 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 DNMTs led us to hypothesize that these drugs might also increase PARP trapping at DNA damage sites; and 3) the cytotoxicity of the most potent PARPis (e.g. BMN 673) appears to correlate with the degree of trapping of PARP1 in chromatin. We first find that in cultured human AML and TNBC cells, the DNMTis (5 to 20 nM DAC or 100 to 200nM 5-AZA) and PARPis (1 to 10 nM BMN 673) alone trap PARP into chromatin, and this effect is enhanced when the drugs are combined. In addition, the PARPi-DNMTi combination treatment of TNBC cell line MDA-MB-231 resulted in significantly enhanced retention of PARP1 and DNMT1 at sites of double strand breaks (DSBs) induced by laser microirradiation. Concomitant with this, the combined doses resulted in significant increases in cytotoxic DSBs, observed 4-24 hours after DSB induction, when compared to single-drug treatments. Homologous recombination (HR) DSB repair activity also appears decreased, as measured by GFP reporter assays. In keeping with these findings, colony survival assays demonstrated that the combination treatment, compared to either drug alone, strongly inhibited colony formation of TNBC cell lines (N=4). Notably non-tumorigenic MCF10A cells showed no significant differences in colony numbers with single or combination drug treatments. Similar to TNBCs, AML cell lines (N=3) as well as primary AML cells (N=8) showed dramatic decreases in colonies in combination vs single agent drug treatments. In the most important translational implications of the preliminary studies, in in vivo therapy TNBC and AML models in immune-deficient mice, our low dose combinations of DNMTis and PARPis provide for potent anti-tumor responses. Mouse xenograft experiments using BRCA mutant TNBC cell line SUM149PT 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. Importantly, mouse MDA-MB-231 xenografts with intact BRCA1 showed significant survival with the combined drug treatment. Likewise in AML xenografts of MOLM14 and MV411 cell lines treated with the drug combination show significantly decrease leukemia burden, as measured by luciferase imaging. Our data suggest a novel use of both DNMTis and PARPis in a compelling therapeutic strategy for TNBCs independent of BRCA mutations and poor prognosis AML; the latter will be investigated in a clinical trial to be based at the University of Maryland and funded by Van Andel-SU2C. Citation Format: Nidal Muvarak, Khadiza Chowdhury, Carine Robert, Xia Limin, Eun Yong Choi, Yi Cai, Marina Bellani, Michael Seidman, Maria R. Baer, Rena Lapidus, Stephen B. Baylin, Feyruz V. Rassool. Combination of DNA methyltransferase and PARP inhibitors as a novel therapy strategy for multiple cancers: Key data in AML and triple negative breast cancer [abstract]. In: Proceedings of the AACR International Conference: New Frontiers in Cancer Research; 2017 Jan 18-22; Cape Town, South Africa. Philadelphia (PA): AACR; Cancer Res 2017;77(22 Suppl):Abstract nr IA13.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.236
GPT teacher head0.482
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueCancer ResearchSame topicPARP inhibition in cancer therapyFrench-language works237,207