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Record W4296253011 · doi:10.3390/curroncol29090520

Acquired G2032R Resistance Mutation in ROS1 to Lorlatinib Therapy Detected with Liquid Biopsy

2022· article· en· W4296253011 on OpenAlexvenueno aff
Balázs Jóri, Markus Falk, Iris Hövel, Peggy Weist, Markus Tiemann, Lukas C. Heukamp, Frank Griesinger

Bibliographic record

VenueCurrent Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsnot available
Fundersnot available
KeywordsROS1Anaplastic lymphoma kinaseMedicineCancer researchContext (archaeology)MutationTyrosine kinaseLung cancerCrizotinibTyrosine-kinase inhibitorTargeted therapyInternal medicineCancerGeneAdenocarcinomaReceptorBiologyGenetics

Abstract

fetched live from OpenAlex

Lorlatinib, a third-generation anaplastic lymphoma kinase (ALK)/receptor tyrosine kinase inhibitor (ROS1), demonstrated efficacy in ROS1 positive (ROS1+) non-small cell lung cancer (NSCLC), although approval is currently limited to the treatment of ALK+ patients. However, lorlatinib-induced resistance mechanisms, and its efficacy against the resistance mutation G2032R in ROS1, respectively, have not yet been fully understood. Furthermore, concomitant tumor suppressor gene p53 (TP53) mutations occur in driver alteration positive NSCLC, but their prognostic contribution in the context of ROS1 inhibition remains unclear. Here we report a ROS1+ NSCLC patient who developed an on target G2032R resistance mutation during second-line lorlatinib treatment, indicating the lack of activity of lorlatinib against ROS1 G2032R. The resistance mutation was detected in plasma-derived ctDNA, signifying the clinical utility of liquid biopsies.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0010.001
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 head0.059
GPT teacher head0.419
Teacher spread0.360 · 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 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

Citations13
Published2022
Admission routes1
Has abstractyes

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