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Record W2740388256 · doi:10.1158/1538-7445.am2017-4035

Abstract 4035: A novel combi-molecule engineered to target the putative synthetic lethal interactions between the epidermal growth factor receptor (EGFR) and poly(ADP-ribose)polymerase (PARP)

2017· article· en· W2740388256 on OpenAlexaff
Zhor Senhaji Mouhri, Martin Rupp, Bertrand J. Jean‐Claude

Bibliographic record

VenueCancer Research · 2017
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsSynthetic lethalityCancer researchOlaparibPoly ADP ribose polymeraseEpidermal growth factor receptorPARP inhibitorBiologyDNA repairCancerPolymeraseBiochemistryGeneticsEnzymeDNA

Abstract

fetched live from OpenAlex

Abstract Over the past decade, PARP inhibition has been actively pursued as a novel approach for the selective therapy of tumors with BRCA1/2 mutations. The therapeutic benefits of PARP inhibitors have now been proven in the clinic against BRCA1/2 mutant ovarian cancers. This is hitherto limited to BRCA1/2 mutations, which only accounts for 5-10% of all cancers with hereditary mutations in the homologous recombination pathway. Therefore, new strategies are not only required to enhance the potency of PARP inhibitors but also to expand their use beyond BRCA mutation. While several combination modalities have been reported for PARP inhibitors, the concept of targeted PARP inhibitor has not yet been explored. Here using our novel combi-targeting approach, we report on the design of PARP inhibitors targeted to EGFR, a tyrosine kinase receptor overexpressed in several solid tumors. Recently, reports on the relationship between EGFR, PARP and BRCA have begun to emerge, one of which described a contextual synthetic lethality between EGFR and PARP (PloS one 7.10 (2012)). Here we report on the design and synthesis of novel PARP-EGFR combi-molecule based on structural modification of olaparib as a PARP inhibitor warhead and the quinazoline moiety for targeting EGFR. The results showed that: (a) it is capable of inducing a dose-dependent inhibition of PARP in isolated enzyme assay, (b) it induced a dose-dependent inhibition of EGFR in an isolated kinase assay, (c) it showed a dose-dependent inhibition of EGFR phosphorylation and downstream signaling in whole-cell assay, (d) it was selectively potent towards BRCA2 mutant and also EGFR-overexpressing cell lines, (d) it was extremely potent with activities superior to that of olaparib or gefitinib alone and their corresponding equimolar combination in three established triple negative breast cancer cell lines, (e) subcellular distribution analysis showed that it was abundantly localized in the perinuclear region. These results in toto suggest that this new combi-molecule could be developed as a single drug modality emulating the combination of PARP and EGFR inhibitors with the added benefit of being targeted to EGFR-expressing tumor cells. Citation Format: Zhor Senhaji Mouhri, Martin Rupp, Bertrand J. Jean-Claude. A novel combi-molecule engineered to target the putative synthetic lethal interactions between the epidermal growth factor receptor (EGFR) and poly(ADP-ribose)polymerase (PARP) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4035. doi:10.1158/1538-7445.AM2017-4035

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)0.000
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: Bench or experimental
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.130
GPT teacher head0.441
Teacher spread0.311 · 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
GenreOther

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

Citations0
Published2017
Admission routes1
Has abstractyes

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