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Molecular determinants of outcome with mTOR inhibition in endometrial cancer (EC).

2012· article· en· W2949754698 on OpenAlexaff
Helen Mackay, Elizabeth A. Eisenhauer, Suzanne Kamel‐Reid, Blaise Clarke, Wendy Walsh, Katherine Karakasis, Helga B. Salvesen, Amit M. Oza

Bibliographic record

VenueJournal of Clinical Oncology · 2012
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsToronto General HospitalUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsPTENKRASNeuroblastoma RAS viral oncogene homologMedicineTemsirolimusPI3K/AKT/mTOR pathwayCancer researchSelumetinibPDGFRAOncologyInternal medicineCDKN2ACancerDiscovery and development of mTOR inhibitorsGeneticsBiologySignal transduction

Abstract

fetched live from OpenAlex

5010 Background: Deregulation of PI3K/AKT/mTOR signaling plays a significant role in EC biology. NCIC CTG has completed three phase II trials of 2 mTOR inhibitors (temsirolimus and ridaforolimus) in EC (IND 160A, IND 160B, IND192) demonstrating anti-tumor activity. PTEN expression, however, was not associated with response. In this study we are conducting additional molecular analyses on samples obtained from patients (pts) participating in these trials to identify mutations or other findings associated with mTOR response. Methods: Formalin fixed paraffin embedded (FFPE) tumor samples were collected from pts treated on the three trials. Tumor DNA was isolated and mutational profiling (MP) was performed using theOncoCarta Panel v1.0 which can detect 238 mutations in 19 oncogenes including AKT1, 2, BRAF, CDK-4, EGFR, ERBB2, MET, H-, K-, N- RAS, PDGFRA, PIK3CA, RET. All mutations were verified by Sanger sequencing. For each gene found to be mutated in at least 1 patient, the relationship between presence/absence of mutations in that gene and objective anti-tumor response (RR) was assessed (RR vs. no response; early progression (PD) vs. no PD) using Fisher's exact test. In addition, the presence of any mutation vs. no mutations was assessed in relationship to the same clinical outcomes. Results: MP was feasible in 73 of the 94 eligible pts treated on the three trials. 44% (32 pts) had a mutation in at least one gene: 21 pts (29%) in PIK3CA, 10 (14%) KRAS, 4 (5%) MET, 3 (4%) NRAS, 3 (4%) AKT and 1(1%) EGFR. 9 pts (12%) had > 1 mutation. No significant correlations were seen, in individual trials or within the pooled data set of 3 studies, between the presence/absence of any mutation and RR (p=1.0) or early PD (p=1.0). No significant association was seen between the presence of mutations within individual genes and RR or PD (including PIK3CA). Of interest, no response was observed in any of the 13 pts with a Ras mutation (non-significant). Additional analyses involving gene expression (including stathmin) and correlation of MP with tumor morphology are underway. Conclusions: Mutations are common in EC but we have not identified a statistical association between presence of mutations in PIK3CA or any other gene and response to mTOR inhibition. Further analyses are ongoing.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0020.000

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 head0.180
GPT teacher head0.489
Teacher spread0.308 · 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 designObservational
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".

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Citations7
Published2012
Admission routes1
Has abstractyes

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