ArticleESMO open2026
APOBEC mutational signatures predict immune checkpoint inhibitor benefit in TMB-low metastatic NSCLC independent of PD-L1 status.
Article in ESMO open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background∼60%-70% of patients with metastatic non-small cell lung cancer (NSCLC) have relatively low tumor mutational burden (TMB), with limited biomarker-guided immunotherapy options beyond programmed death-ligand 1 (PD-L1) expression. APOBEC (apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like) mutational signatures, defined by characteristic genomic footprints, are associated with higher TMB and a better response to immune checkpoint inhibitors (ICIs). However, whether APOBEC independently predicts ICI response in TMB-low tumors has not been established. MATERIALS AND
methodsWe analyzed 857 ICI-treated and 1328 ICI-untreated TMB-low (<10 mut/Mb) patients with metastatic NSCLC from the MSK-CHORD cohort. APOBEC status was classified using MESiCA, a machine-learning algorithm for mutational signature detection from targeted gene panels. Predictive value was established through treatment interaction testing, multivariate adjustment, propensity score weighting, and landmark analyses. External validation included 82 TMB-low patients from published whole-exome sequencing studies.
resultsAPOBEC-positive patients (n = 52, 6.1%) had significantly improved overall survival [median 33.7 versus 17.4 months; hazard ratio (HR) 0.60, 95% confidence interval (CI) 0.42-0.85, P = 0.004]. No such benefit was observed in ICI-untreated patients (HR 0.98, P = 0.85), with significant treatment interaction (P = 0.032), confirming a predictive rather than prognostic effect. APOBEC remained independently predictive after adjustment for PD-L1 status and age (adjusted HR 0.57, P = 0.002). The benefit was particularly pronounced in PD-L1-negative ICI-treated patients (HR 0.51, P = 0.002). The effect was robust across propensity score, landmark, and bootstrap analyses. External validation confirmed independent APOBEC benefit (adjusted HR 0.23, P = 0.020).
conclusionsAPOBEC mutational signatures represent a robust predictive biomarker for ICI response in TMB-low metastatic NSCLC, identifying responders particularly among PD-L1-negative patients where biomarker guidance is most needed, detectable from targeted gene panels used in routine clinical practice.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.