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Record W2885576714 · doi:10.1158/1538-7445.am2018-5423

Abstract 5423: Lysine-52 stabilizes the MYC oncoprotein through a SCFFBXW7-independent mechanism

2018· article· en· W2885576714 on OpenAlexaff
Jason De Melo, Sam S. Kim, Corey Lourenco, Diana Resetca, Maria Sunnerhagen, Brian Raught, Linda Z. Penn

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsUbiquitin ligaseCullinSUMO proteinUbiquitinTranscription factorBiologyProtein degradationLysineCancer researchProteasomeCell biologyGeneticsGeneAmino acid

Abstract

fetched live from OpenAlex

Abstract The oncogenic transcription factor c-MYC (MYC) is deregulated, and often overexpressed, in more than 50% of cancers. MYC deregulation is associated with poor prognosis and aggressive disease, suggesting that the development of therapeutic inhibitors targeting MYC would dramatically impact patient care and outcome. MYC is a highly regulated transcription factor, with a protein and mRNA half-life of approximately 30 min. The most extensively studied pathway regulating MYC protein stability involves ubiquitylation and proteasomal degradation mediated by the E3-ligase, SCFFBXW7. Here we provide evidence for a SCFFBXW7-independent regulatory mechanism centered on Lysine 52 (K52) within MYC Box I (MBI) of the MYC protein. This residue has been shown to be post-translationally modified by both ubiquitylation and SUMOylation, hinting at the interplay of post-translational modifications at this site, and the importance of this residue. We demonstrate that mutation of K52 to arginine (R) renders the MYC protein more labile. Mechanistically, we show that the degradation pathway regulated by K52 is independent of the Cullin-Ring-Ligase (CRL) family of E3-ligases, which includes not only the canonical SCFFBXW7, but also a number of other known MYC-targeting E3-ligases, such as SCFSKP2, SCFβTCRP, SCFFBXO28 and DCXTRUSS. To characterize this degradation pathway further we will utilize unbiased and targeted experiments to elucidate the proteins involved. Taken together, our data identifies a novel regulatory pathway centred on K52 that may be exploited for the development of anti-MYC therapeutics. Citation Format: Jason De Melo, Sam S. Kim, Corey Lourenco, Diana Resetca, Maria Sunnerhagen, Brian Raught, Linda Z. Penn. Lysine-52 stabilizes the MYC oncoprotein through a SCFFBXW7-independent mechanism [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5423.

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 score0.005
Threshold uncertainty score0.016

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)0.0050.002

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 head0.087
GPT teacher head0.398
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
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
Published2018
Admission routes1
Has abstractyes

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