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Record W4379984948 · doi:10.1158/1538-7445.am2023-1558

Abstract 1558: Targeting CDK9 via the small-molecule inhibitor enitociclib as a therapeutic strategy to treat <i>MYCN</i>-amplified rhabdomyosarcoma and neuroblastoma in children

2023· article· en· W4379984948 on OpenAlexaff
Son Tran, Patrick Sipila, Melanie M. Frigault, Amy J. Johnson, Joseph Birkett, Raquel Izumi, Ahmed Hamdy, Beatrix Stelte‐Ludwig, David P. Douglass, Anne‐Marie Langevin, Norman J. Lacayo, Aru Narendran

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldMedicine
TopicNeuroblastoma Research and Treatments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNeuroblastomaCancer researchViability assayBiologyMolecular biologyApoptosisChemistryCell cultureGenetics

Abstract

fetched live from OpenAlex

Abstract Introduction: MYCN amplification is the genetic aberration most consistently associated with poor outcomes in alveolar rhabdomyosarcomas (aRMS) and neuroblastoma (NBL). It regulates key oncogenic processes including tumor cell survival, proliferation and metastasis. In aRMS, MYCN transcription is driven by the PAX3-FOXO1 gene fusion. MYCN and other short half-life mRNA transcripts depend on CDK9 to drive transcription of target genes to initiate and maintain the oncogenic program, making CDK9 blockade an effective therapeutic route against MYC-driven cancers. We have previously shown the activity and tolerability of enitociclib in tumor xenograft models. In this study, we investigated the activity of the selective small-molecule CDK9 inhibitor enitociclib (VIP152/BAY1521152) in preclinical models of pediatric MYCN-amplified aRMS and NBL. Methods: Cell-based viability assays were performed in aRMS (Rh30 and Rh41) and NBL (LAN1, SK-N-AS, SK-N-BE(2) and SK-N-MC) cell lines. Enitociclib antitumor activity was measured by Alamar Blue cell viability assay after 96 h exposure at 9 dose levels (8 nM-2 μM) with DMSO used as control. We performed combination screens of enitociclib with several FDA-approved drugs (n=215). Selected agents with IC50 values <1 μM were analyzed at constant dilution ratios of two inhibitors. Drug synergy was calculated by established methods using SynergyFinder 3.0. Target modulation was determined for RNA polymerase II (RNAPII), MYCN and apoptosis inducers caspase-3 and PARP, in addition to PAX3-FOXO1 and PLK1 protein levels in aRMS cells, by western blotting after continuous exposure with enitociclib for 24 h. Results: Significant cytotoxic activity, with IC50 values ranging from 48-182 nM and 39-123 nM was seen for aRMS cells and NBL cells, respectively. SynergyFinder found synergistic effects of enitociclib with irinotecan, carfilzomib, etoposide, bortezomib, selinexor or topotecan tested at clinically relevant concentrations in the aRMS cell line Rh41. Enitociclib induced apoptosis with cleavage of caspase-3 and PARP by western blotting in a dose- and time-dependent manner in addition to the depletion of phosphorylated RNAPII (Ser2) and MYCN protein levels. In aRMS cells, PAX3-FOXO1 fusion and PLK1 proteins were downregulated. Annexin V/propidium iodide staining confirmed a dose-dependent increase in apoptosis after enitociclib exposure. Conclusions: Our results suggest that CDK9 inhibition is potentially clinically relevant for MYCN-amplified solid tumors such as aRMS and NBL due to its significant antitumor activity and pharmacologic targetability. The data provide essential information on the distinct targets, biomarkers of activity and clinically feasible drug combinations for the development of enitociclib in clinical trials addressing an unmet need in pediatric oncology. Citation Format: Son Tran, Patrick Sipila, Melanie M. Frigault, Amy J. Johnson, Joseph Birkett, Raquel Izumi, Ahmed Hamdy, Beatrix Stelte-Ludwig, David P. Douglass, Anne-Marie Langevin, Norman J. Lacayo, Aru Narendran. Targeting CDK9 via the small-molecule inhibitor enitociclib as a therapeutic strategy to treat MYCN-amplified rhabdomyosarcoma and neuroblastoma in children [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1558.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.062
GPT teacher head0.388
Teacher spread0.326 · 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".

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Citations1
Published2023
Admission routes1
Has abstractyes

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