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Genomic profiling of resistant tumor samples following progression on EGF816, a third generation, mutant-selective EGFR tyrosine kinase inhibitor (TKI), in advanced non-small cell lung cancer (NSCLC).

2017· article· en· W2756994529 on OpenAlexaff
Daniel Shao-Weng Tan, Dong‐Wan Kim, Natasha B. Leighl, Gregory J. Riely, James Chih‐Hsin Yang, Juergen Wolf, Takashi Seto, Enriqueta Felip, Santiago Ponce Aix, Maud Jonnaert, Chun Pan, Sinead Dolan, Jordi Barretina, Susan E. Moody, Lecia V. Sequist

Bibliographic record

VenueJournal of Clinical Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsT790MMedicineOsimertinibLung cancerCancer researchTumor progressionOncologyInternal medicineTolerabilityCancerGefitinibEpidermal growth factor receptorErlotinibAdverse effect

Abstract

fetched live from OpenAlex

11506 Background: Up to 60% of patients (pts) with NSCLC harboring an activating EGFR mutation (mut) and treated with a 1st generation EGFR TKI develop a secondary gatekeeper T790M mut. EGF816 is an irreversible EGFR TKI that is highly potent against activating mut (L858R, ex19del) and T790M mut, while sparing wild-type EGFR. As previously reported, in a Phase I dose escalation study, the overall response rate to EGF816 in pts with advanced EGFR T790M mut NSCLC was 47% and the disease control rate was 87%. However, pts ultimately develop disease progression. Tumor biopsies were obtained from pts who had progressed on EGF816 to identify mechanisms of resistance. Methods: Pts with NSCLC with locally or centrally confirmed T790M status were enrolled in this multicenter, dose escalation study to determine the safety, tolerability and antitumor activity of EGF816 (NCT02108964). EGF816 was administered at 7 dose levels ranging from of 75-350 mg QD. Following disease progression, a tumor sample was obtained and was analyzed by the Foundation Medicine next-generation sequencing (NGS) T7 panel, which interrogates 395 cancer-related genes for base substitutions, insertion-deletions, and copy number changes, as well as introns of 31 genes involved in rearrangements. Results: Tumor samples taken following disease progression on EGF816 were analyzed from 9 pts. Of the 8 pts whose tumors were T790M+ at baseline, this was detected in only 3 pts’ post-EGF816 progression samples. One patient developed an EGFR C797S mut and concurrent deletion in mTOR. Other identified alterations include BRAF fusions (n = 2) and c-MET amplification (n = 1). Only one patient was found to have concurrent TP53 mutation and RB1 truncating mutation. Individual patient response data, including duration of response, will be presented along with detailed genomic parameters. Conclusions: NGS analysis of tumors that developed resistance to EGF816 revealed multiple potential mechanisms of resistance. These data are hypothesis-generating and could lead to rational combination studies with EGF816 to improve the depth and/or duration of response to EGF816. Clinical trial information: NCT02108964.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 head0.062
GPT teacher head0.463
Teacher spread0.402 · 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".

Quick stats

Citations13
Published2017
Admission routes1
Has abstractyes

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