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Record W2782376830

Abstract #3559: A quantitative survey of tyrosine phosphorylation changes with erlotinib treatment in EGFR mutant and wildtype NSCLC cell lines

2009· article· en· W2782376830 on OpenAlexaboutno aff
Warren Shih, Jiefei Tong, Paul Taylor, Akira Sakurada, Kevin M. Brown, Michael F. Moran, Ming‐Sound Tsao

Bibliographic record

VenueCancer Research · 2009
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsnot available
Fundersnot available
KeywordsErlotinibEpidermal growth factor receptorCancer researchT790MErlotinib HydrochlorideTyrosine kinaseEGFR inhibitorsLung cancerWild typeGefitinibCancerBiologyChemistryOncologyMedicineMutantInternal medicineReceptorGeneGenetics
DOInot available

Abstract

fetched live from OpenAlex

The Epidermal Growth Factor Receptor (EGFR) is a transmembrane receptor that is frequently expressed in carcinoma. Erlotinib is a small molecule inhibitor of EGFR preventing the receptor9s autophosphorylation and downstream signaling. Erlotinib has been approved for second line treatment of advanced stage non-small-cell lung cancer (NSCLC) patients. NSCLC patients with mutations in the kinase domain of EGFR (L858R and exon 19 deletion) and/or EGFR gene amplifications demonstrate greater response rates and improved survival when treated by erlotinib. However, not all molecular factors that influence the clinical response to this drug are as yet identified. Greater understanding on how erlotinib influences EGFR induced cellular signaling in wild type or EGFR mutant/amplified NSCLC cells lines may provide insights on potential novel biomarkers for predicting response to erlotinib treatment, and/or novel downstream targets that may be developed against lung cancer that are resistant to erlotinib. A general quantitative survey of tyrosine phosphorylation comparing EGFR mutant, EGFR amplified wild type and EGFR low copy number wild-type NSCLC cell lines using tandem mass spectrometry (LTQ Orbitrap) was generated following erlotinib treatment, to probe differences in the impact of erlotinib on cellular phosphotyrosine targets in erlotinib-sensitive and erlotinib-resistant cell lines. Preliminary downstream effectors of erlotinib have been identified and quantified by analysis of high resolution extracted ion currents. A subset of these will be subject to validation and quantification in xenograft tumor models by using Selected Reaction Monitoring (SRM) with a triple quadrupole instrument (TSQ Quantum Ultra). (Supported by the Ontario Institute of Cancer Research Grant 07NOV-78) Citation Information: In: Proc Am Assoc Cancer Res; 2009 Apr 18-22; Denver, CO. Philadelphia (PA): AACR; 2009. Abstract nr 3559.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.112
GPT teacher head0.454
Teacher spread0.341 · 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
Published2009
Admission routes1
Has abstractyes

Explore more

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