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Impact of <i>KRAS</i> mutational variant on response to immunotherapy in metastatic NSCLC.

2021· article· en· W3166078442 on OpenAlexafffund
Shelley Kuang, Sally C. M. Lau, Kieran Sharma, Juehea Lee, Malcolm Ryan, Sabine Schmid, Penelope Ann Bradbury, Geoffrey Liu, Frances A. Shepherd, Ming‐Sound Tsao, Natasha B. Leighl, Adrian G. Sacher

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsUniversity of TorontoUniversity Health NetworkPrincess Margaret Cancer Centre
FundersPrincess Margaret Cancer Foundation
KeywordsKRASMedicineMutationInternal medicineOncologyCancerCancer researchColorectal cancerGeneticsBiologyGene

Abstract

fetched live from OpenAlex

e21127 Background: KRAS alterations constitute the most common driver mutations in metastatic non-small cell lung cancers (mNSCLC) and occur in approximately 30% of patients. KRAS mutational subtype as well as the presence of co-mutations has been associated with altered activation of downstream signaling pathways in preclinical models. We hypothesize that different KRAS G12C mutational subsets will be associated with variable clinical outcome and response to therapy. To this end, we have performed a retrospective analysis of survival and treatment outcomes by KRAS mutation subtype (G12C vs non-G12C). Methods: A review of KRAS-mutated mNSCLC patients treated with immunotherapy between 2013 and 2020 was conducted. Patient demographics, smoking status, KRAS mutational subtype, co-mutations and PD-L1 status were collected. Overall response rate (ORR) and progression-free survival (PFS) were analyzed in each subgroup. Results: 98 KRAS mutant mNSCLC patients were treated with immune checkpoint inhibitors (ICI): 37% with a KRAS G12C mutation, 62% with a non-G12C mutation. Patients with a G12C mutation were more likely to be of Caucasian ancestry (86% vs 56%; p = 0.01) whereas all other characteristics were similar between the groups including smoking history, PD-L1 expression ≥50% (61% vs 40%) and the presence of a TP53 co-mutation (48% vs. 54%); all p > 0.05. Treatment patterns were similar between the groups, with PD-1 inhibitor monotherapy given in 86% vs 79% of KRAS G12C and non-G12C patients. Overall response rate was 51% vs 27% in G12C vs non-G12C (p = 0.03). PFS was superior in G12C mutants (19.6 months vs 4.0 months), even after adjusting for smoking history, TP53 co-mutation status and PD-L1 expression (adjusted HR 0.51; p = 0.02). In subgroup analyses, the superiority in PFS was driven by the G12C mutants with high PD-L1 expression (n = 19): 26.8 months in G12C, PD-L1 high vs 4.7 months in G12C, PD-L1 low vs. 4.7 months in KRAS transversion mutations, PD-L1 high vs 4.0 months in transversion mutations, PD-L1 low vs. 3.0 months in transition mutations; p < 0.001. Conclusions: The presence of a KRAS G12C mutation is associated with improved ORR and PFS after treatment with ICI compared to non-G12C mutations in mNSCLC. The greatest benefit in PFS was observed in the subgroup with G12C mutation and high PD-L1 expression. Differential activation of downstream signaling associated with specific KRAS codon 12 mutation variants may modulate the composition of the tumor immune microenvironment thereby contributing to the variable response to immunotherapy. Further understanding on these molecular mechanisms may direct the development of new treatment strategies in KRAS mutant lung cancers.

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)0.001
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
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.096
GPT teacher head0.556
Teacher spread0.460 · 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

Citations3
Published2021
Admission routes2
Has abstractyes

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