516P Co-mutational analysis of lung carcinoma across early and advanced stages: Evidence from the LANTERN project cohort

Background: Biomarker testing is essential for identifying lung cancer (LC) patients with actionable oncogenic drivers.In this perspective, early stage settings remain less explored.Co-occurring mutations involving established drivers (eg, EGFR) may modulate responses to targeted therapies.This study aimed to define the complex co-mutational landscape of LC and highlight stage-specific differences from the large cohort the LANTERN study. Methods:The genomic cohort included 271 patients (137 stage I-III; 134 stage IV).Tumor samples underwent comprehensive genomic profiling (CGP) (Illumina TruSight Oncology500).Raw genomic data were analyzed using the maftools package in R. Stage specific co-occurrence and mutual exclusivity of genomic alterations were evaluated using the somaticInteractions function.Pair-wise Fisher's exact tests were performed.All statistical tests were two-sided, with p-values <0.05 considered statistically significant and p-values <0.01 highlighting particularly robust associations within the co-mutational landscape. Results:In early stage, significant co-occurrences were observed: TP53 with KRAS, ARID1A, PTEN, ATRX, RBM10; KRAS with DNMT3A, STK11, ATRX, RBM10; PTEN and ARID1A; ATM with RBM10, NF1.In adv stage, enriched additional co-mutations included: TP53 and EGFR, CCNE1, APC, ARID1A, BRCA1, KRAS; KRAS and SMARCA4, KEAP1, STK11, LRP1B, FANCE, RBM10, ARID1A; STK11 and FANCE, DNMT3A, KEAP1.The absence of overlap between EGFR and KRAS confirmed their mutual exclusivity (all stages).A mutual exclusivity of EGFR and STK11 was identified only in adv group.The role of EGFR amplification and KEAP1 mutations emerged only in adv cohort. Conclusions:Early stage LC exhibits a complex molecular architecture, in which the most common altered gene TP53 facilitates the accumulation of multiple mutational events.Persistent co-mutation patterns in adv disease confirm the existence of core oncogenic pathways across stages.The emergence of additional associations among DNA repair, chromatin-remodelling, and metabolic genes reflects clonal evolution and selective pressures in aggressive disease, with implications for prognosis and early implementation of targeted therapies.Clinical trial identification: NCT05802771.

Authors

Institutions

Publication Details

Journal
ESMO Open
Published
2026-03-17
DOI
https://doi.org/10.1016/j.esmoop.2026.106831
Primary Topic
Lung Cancer Treatments and Mutations
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

516P Co-mutational analysis of lung carcinoma across early and advanced stages: Evidence from the LANTERN project cohort

Davide Dalfovo, Núria Farré, Rocco Trisolini, E. Troost et al.
ESMO Open
Lung Cancer Treatments and Mutations
article

516P Co-mutational analysis of lung carcinoma across early and advanced stages: Evidence from the LANTERN project cohort

Davide Dalfovo, Núria Farré, Rocco Trisolini, E. Troost, Carolina Sassorossi, Annalisa Campanella, Steffen Löck, L. Boldrini, J. Evangelista, A. Urbani, E. De Paolis, E. Ozturk, S. Margaritora, A. Minucci, E. Bria, E. Vita, A. Piermattei, F. Lococo, A. Cancellieri
article en

Abstract

Background: Biomarker testing is essential for identifying lung cancer (LC) patients with actionable oncogenic drivers.In this perspective, early stage settings remain less explored.Co-occurring mutations involving established drivers (eg, EGFR) may modulate responses to targeted therapies.This study aimed to define the complex co-mutational landscape of LC and highlight stage-specific differences from the large cohort the LANTERN study. Methods:The genomic cohort included 271 patients (137 stage I-III; 134 stage IV).Tumor samples underwent comprehensive genomic profiling (CGP) (Illumina TruSight Oncology500).Raw genomic data were analyzed using the maftools package in R. Stage specific co-occurrence and mutual exclusivity of genomic alterations were evaluated using the somaticInteractions function.Pair-wise Fisher's exact tests were performed.All statistical tests were two-sided, with p-values <0.05 considered statistically significant and p-values <0.01 highlighting particularly robust associations within the co-mutational landscape. Results:In early stage, significant co-occurrences were observed: TP53 with KRAS, ARID1A, PTEN, ATRX, RBM10; KRAS with DNMT3A, STK11, ATRX, RBM10; PTEN and ARID1A; ATM with RBM10, NF1.In adv stage, enriched additional co-mutations included: TP53 and EGFR, CCNE1, APC, ARID1A, BRCA1, KRAS; KRAS and SMARCA4, KEAP1, STK11, LRP1B, FANCE, RBM10, ARID1A; STK11 and FANCE, DNMT3A, KEAP1.The absence of overlap between EGFR and KRAS confirmed their mutual exclusivity (all stages).A mutual exclusivity of EGFR and STK11 was identified only in adv group.The role of EGFR amplification and KEAP1 mutations emerged only in adv cohort. Conclusions:Early stage LC exhibits a complex molecular architecture, in which the most common altered gene TP53 facilitates the accumulation of multiple mutational events.Persistent co-mutation patterns in adv disease confirm the existence of core oncogenic pathways across stages.The emergence of additional associations among DNA repair, chromatin-remodelling, and metabolic genes reflects clonal evolution and selective pressures in aggressive disease, with implications for prognosis and early implementation of targeted therapies.Clinical trial identification: NCT05802771.

ESMO OpenVol. 11
Koç University (TR), Helmholtz-Zentrum Dresden-Rossendorf (DE), Agostino Gemelli University Polyclinic (IT), Parc de Salut (ES), Istituti di Ricovero e Cura a Carattere Scientifico (IT), University Hospital Carl Gustav Carus (DE)
Good health and well-being
Openalex Percentile: Top 19%
Lung Cancer Treatments and Mutations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.