MétaCan
Menu
← Back to cohort
Record W2955408701 · doi:10.1073/pnas.1821863116

Interspecies analysis of MYC targets identifies tRNA synthetases as mediators of growth and survival in MYC-overexpressing cells

2019· article· en· W2955408701 on OpenAlexfundno aff
Jonathan Zirin, Xiaochun Ni, Laura M. Sack, Donghui Yang‐Zhou, Yanhui Hu, Roderick Brathwaite, Martha L. Bulyk, Stephen J. Elledge, Norbert Perrimon

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsnot available
FundersInstitute of GeneticsNational Institute of General Medical SciencesNational Institutes of HealthNational Cancer InstituteNational Institute of Arthritis and Musculoskeletal and Skin DiseasesLudwig Institute for Cancer ResearchHoward Hughes Medical Institute
KeywordsBiologyNucleolusGeneAminoacyl tRNA synthetaseCell biologyProto-Oncogene Proteins c-mycOncogeneGeneticsCancer researchRegulation of gene expressionTransfer RNARNACytoplasmCell cycle

Abstract

fetched live from OpenAlex

Aberrant MYC oncogene activation is one of the most prevalent characteristics of cancer. By overlapping datasets of Drosophila genes that are insulin-responsive and also regulate nucleolus size, we enriched for Myc target genes required for cellular biosynthesis. Among these, we identified the aminoacyl tRNA synthetases (aaRSs) as essential mediators of Myc growth control in Drosophila and found that their pharmacologic inhibition is sufficient to kill MYC-overexpressing human cells, indicating that aaRS inhibitors might be used to selectively target MYC-driven cancers. We suggest a general principle in which oncogenic increases in cellular biosynthesis sensitize cells to disruption of protein homeostasis.

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 score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.014
GPT teacher head0.266
Teacher spread0.252 · 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

Citations18
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of Sciences→Same topicRNA and protein synthesis mechanisms→French-language works237,207→