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Record W4229454790 · doi:10.1159/000523734

Complex Germline K757N Mutation in Non-Small-Cell Lung Cancer: A Case Report

2022· article· en· W4229454790 on OpenAlexaff
Boaz Wong, Sara Moore, Paul Wheatley‐Price

Bibliographic record

VenueCase Reports in Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineGermline mutationLung cancerGermlineOncologyEpidermal growth factor receptorMutationCancer researchTargeted therapyPembrolizumabCarboplatinCancerInternal medicineGeneticsBiologyChemotherapyImmunotherapyGene

Abstract

fetched live from OpenAlex

Epidermal growth factor receptor (EGFR) mutations are usually oncogenic drivers of lung tumor development and progression. While common sensitizing mutations respond well to targeted therapy, the relevance of germline EGFR mutations is less clear. We describe a 65-year-old, previously healthy, male diagnosed with non-small-cell lung cancer. Familial history for lung cancer is negative. Targeted next-generation sequencing on the tumor biopsy sample revealed an atypical EGFR K757N mutation at 50% allele frequency and genetic review of a previously acquired gastric sample confirms the mutation as a germline change. He received standard first-line chemoimmunotherapy with carboplatin, pemetrexed, and pembrolizumab, and after 8 months therapy continues, with stable disease, to receive maintenance pemetrexed and pembrolizumab. To our knowledge, this is the first report of an atypical, germline K757N EGFR mutation. While the clinical relevance of this mutation is unclear, standard reporting of the allelic frequency of novel, atypical mutations can detect potential germline changes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.027
GPT teacher head0.397
Teacher spread0.369 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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
Published2022
Admission routes1
Has abstractyes

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