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Abstract B32: CRLX101, an investigational camptothecin-containing nanoparticle-drug conjugate, combined with DDR agents provides a novel approach to increasing therapeutic index

2017· article· en· W2605264042 on OpenAlexaboutno aff
Lenka Oplustil O’Connor, Anderson T. Wang, D. I. Jones, Rajesh Odedra, Michael Spreadborough, Joanne Wilson, Aaron Smith, Peter Cotton, Jaimini Reens, Jen Barnes, Victoria Sheridan, Andres Tellez, Alan Lau, C Sadler, Mark J. O’Connor, Scott Eliasof

Bibliographic record

VenueMolecular Cancer Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer therapeutics and mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsOlaparibCamptothecinPARP inhibitorCancer researchPARP1CHEK1PharmacologyMedicineCancerCell cycleCell cycle checkpointBiologyPoly ADP ribose polymeraseInternal medicinePolymeraseBiochemistryDNA

Abstract

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Abstract Topoisomerase I inhibitors are used as standard-of-care chemotherapy in many types of cancer but are associated with significant toxicities. There is potential to improve their efficacy further by combining with inhibitors of the DNA damage response, such as the poly ADP ribose polymerase (PARP) inhibitor olaparib. However, while preclinical data highlight the improved efficacy of this combination, subsequent clinical trials have struggled due to dose limiting myelotoxicity. CRLX101 is an investigational nanoparticle-drug conjugate (NDC) containing the payload camptothecin, a potent topoisomerase I inhibitor. This agent is preferentially targeted to tumours and demonstrated a generally favorable toxicity profile in the clinic. Here, we explored the molecular mechanism and therapeutic potential of combining CRLX101 with either olaparib or the WEE1 G2 checkpoint kinase inhibitor AZD1775, by testing both efficacy and safety in preclinical models. In vitro studies using NCI-H417a small cell lung cancer (SCLC) cells demonstrated that combination with both olaparib and AZD1775 potentiated the efficacy of CRLX101 although by different mechanisms. Cellular analyses revealed that CRLX101 treatment alone predominantly activated ATM-mediated DNA damage response and resulted in late S/G2 cell cycle arrest. Combination with a PARP inhibitor further enhanced the CRLX101-induced DNA damage response and prolonged cell cycle arrest in late S/G2 phase. In contrast, WEE1 inhibition abrogated late S/G2 cell cycle arrest induced by CRLX101, resulting in aberrant mitotic entry and enhanced cell death. Our in vivo studies using wild type Wistar rat model showed that CRLX101, olaparib and AZD1775, are well tolerated as single agents. However, concurrent combination of CRLX101 with either olaparib or AZD1775 resulted in a dose-dependent decrease in hematological parameters. We investigated sequenced schedules and demonstrated that at a 24h delay between the CRLX101 and olaparib mitigates much of the combined bone marrow toxicity, while improving the efficacy above CRLX101 alone in xenograft tumors from NCI-H417a cells. Collectively, these preclinical data demonstrate increased anti-tumor efficacy of CRLX101 when combined with DDR inhibitors. The combination schedule for CRLX101 and olaparib identified in our preclinical models as providing an increased therapeutic index has been used to develop protocols to test this combination in a relapsed (2nd line) SCLC human clinical trial (in collaboration with NCI). Citation Format: Lenka Oplustil O'Connor, Anderson T. Wang, David Jones, Rajesh Odedra, Michael Spreadborough, Joanne Wilson, Aaron Smith, Peter Cotton, Jaimini Reens, Jen Barnes, Victoria Sheridan, Andres Tellez, Alan Lau, Claire Sadler, Mark J. O'Connor, Scott Eliasof. CRLX101, an investigational camptothecin-containing nanoparticle-drug conjugate, combined with DDR agents provides a novel approach to increasing therapeutic index [abstract]. In: Proceedings of the AACR Special Conference on DNA Repair: Tumor Development and Therapeutic Response; 2016 Nov 2-5; Montreal, QC, Canada. Philadelphia (PA): AACR; Mol Cancer Res 2017;15(4_Suppl):Abstract nr B32.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.088
GPT teacher head0.369
Teacher spread0.281 · 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 teacher head, not a consensus.

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

Citations1
Published2017
Admission routes1
Has abstractyes

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