MétaCan
Menu
Back to cohort
Record W2653933210 · doi:10.1158/0008-5472.can-16-2224

<i>EIF1AX</i> and <i>NRAS</i> Mutations Co-occur and Cooperate in Low-Grade Serous Ovarian Carcinomas

2017· article· en· W2653933210 on OpenAlexaff
Dariush Etemadmoghadam, Walid J. Azar, Ying Lei, Tania Moujaber, Dale W. Garsed, Catherine J. Kennedy, Sián Fereday, Thomas J. Mitchell, Yoke-Eng Chiew, Joy Hendley, Raghwa Sharma, Paul R. Harnett, Jason Li, Elizabeth L. Christie, Ann‐Marie Patch, Joshy George, George Au‐Yeung, Gisela Mir Arnau, Timothy P. Holloway, Timothy Semple, John V. Pearson, Nicola Waddell, Sean M. Grimmond, Martin Köbel, Helen Rizos, Ivan B. Lomakin, David D.L. Bowtell, Anna DeFazio

Bibliographic record

VenueCancer Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsFoothills Medical Centre
Fundersnot available
KeywordsNeuroblastoma RAS viral oncogene homologKRASOvarian cancerCancer researchSerous fluidMissense mutationBiologyExomeCancerExome sequencingMutationMedicineInternal medicineGeneticsGeneColorectal cancer

Abstract

fetched live from OpenAlex

Abstract Low-grade serous ovarian carcinomas (LGSC) are associated with a poor response to chemotherapy and are molecularly characterized by RAS pathway activation. Using exome and whole genome sequencing, we identified recurrent mutations in the protein translational regulator EIF1AX and in NF1, USP9X, KRAS, BRAF, and NRAS. RAS pathway mutations were mutually exclusive; however, we found significant co-occurrence of mutations in NRAS and EIF1AX. Missense EIF1AX mutations were clustered at the N-terminus of the protein in a region associated with its role in ensuring translational initiation fidelity. Coexpression of mutant NRAS and EIF1AX proteins promoted proliferation and clonogenic survival in LGSC cells, providing the first example of co-occurring, growth-promoting mutational events in ovarian cancer. Cancer Res; 77(16); 4268–78. ©2017 AACR.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.052
GPT teacher head0.398
Teacher spread0.347 · 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

Citations90
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueCancer ResearchSame topicRNA Research and SplicingFrench-language works237,207