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Record W4282971362 · doi:10.1158/1538-7445.am2022-5731

Abstract 5731: Structure-based development of a novel MYC inhibitor for neuroendocrine prostate cancer

2022· article· en· W4282971362 on OpenAlexaff
Jane Foo, Anh‐Tien Ton, Kriti Singh, Fuqiang Ban, Hélène Morin, Joseph Lee, Eric Leblanc, Nada Lallous, Artem Cherkasov

Bibliographic record

VenueCancer Research · 2022
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Research Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLNCaPProstate cancerCancer researchIn silicoCancerDrug discoveryBiologyChemistryGeneComputational biologyBioinformaticsGenetics

Abstract

fetched live from OpenAlex

Abstract Background: MYC oncoproteins are important drivers of human cancers. More specifically, NMYC is amplified and overexpressed in neuroendocrine prostate cancer (NEPC). NMYC elicits its oncogenic effects by forming a heterodimer with MAX. This complex binds to regulating elements and activates the transcription of MYC target genes that play roles in tumor growth and progression. It is well known that members of the MYC family of proteins make compelling targets for cancer treatments. However, to this date, no tangible drug candidates have been developed into the clinics for MYC. In previous studies utilizing a rational computer-aided drug discovery (CADD) approach, we identified VPC-70551 as our most active hit. Subsequent optimization with the VPC-70551 scaffold has led to the identification of a new series of compounds. Using in silico drug screening followed by functional validation, we identified a small molecule inhibitor, VPC-70619, that exhibits higher microsomal stability and is better absorbed and tolerated orally than most MYC inhibitors described in the literature. Method: We used a transcriptional reporter assay to determine the effect of VPC-70619 on MYC-mediated transcription. To validate on-target effect, we evaluated the effect of VPC-70619 treatment on MYC-positive (LASCPC-01, NCIH660, LNCaP N-MYC, 22Rv1 N-MYC) and MYC-negative (HO15.19) cancer cells. We also evaluated the effect of VPC-70619 on MYC/MAX interaction by PLA and on DNA binding by BLI. The direct binding between recombinant MYC/MAX protein complex and VPC-70619 was evaluated by MST. Results: VPC-70619 inhibited MYC transcriptional activity in dose dependent manner and the proliferation of MYC-positive cell lines. VPC-70619 did not interfere with MYC/MAX interaction however it blocked the complex interaction with DNA. We confirmed the direct binding of VPC-70619 to the purified MYC/MAX complex by using MST. Conclusion: This project presents the identification of a new MYC inhibitor that blocks the transcriptional activity of this oncogene and elucidates the molecular mechanism of action of this inhibitor. Our findings help prelude the development and discovery of more effective treatments for NEPC patients. Citation Format: Jane Foo, Anh-Tien Ton, Kriti Singh, Fuqiang Ban, Helene Morin, Joseph Lee, Eric LeBlanc, Nada Lallous, Artem Cherkasov. Structure-based development of a novel MYC inhibitor for neuroendocrine prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5731.

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 categoriesInsufficient payload (model declined to judge)
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 score0.276
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
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.112
GPT teacher head0.457
Teacher spread0.345 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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