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Lung adenocarcinoma (LUAD) is the most common histologic subtype of lung cancer and has a high risk of distant metastasis at every disease stage. We aimed to characterize the genomic landscape of LUAD and identify mutation signatures associated with tumor progression.
We performed an integrative genomic analysis, incorporating whole exome sequencing (WES), determination of DNA copy number and DNA methylation, and transcriptome sequencing for 101 LUAD samples from the Environment And Genetics in Lung cancer Etiology (EAGLE) study. We detected driver genes by testing whether the nonsynonymous mutation rate was significantly higher than the background mutation rate and replicated our findings in public datasets with 724 samples. We performed subclonality analysis for mutations based on mutant allele data and copy number alteration data. We also tested the association between mutation signatures and clinical outcomes, including distant metastasis, survival, and tumor grade. We identified and replicated two novel candidate driver genes, POU class 4 homeobox 2 ( POU4F2) (mutated in 9 [8.9%] samples) and ZKSCAN1 (mutated in 6 [5.9%] samples), and characterized their major deleterious mutations. ZKSCAN1 was part of a mutually exclusive gene set that included the RTK/RAS/RAF pathway genes BRAF, EGFR, KRAS, MET, and NF1, indicating an important driver role for this gene. Moreover, we observed strong associations between methylation in specific genomic regions and somatic mutation patterns. In the tumor evolution analysis, four driver genes had a significantly lower fraction of subclonal mutations (FSM), including TP53 (p = 0.007), KEAP1 ( p = 0.012), STK11 ( p = 0.0076), and EGFR ( p = 0.0078), suggesting a tumor initiation role for these genes. Subclonal mutations were significantly enriched in APOBEC-related signatures ( p < 2.5×10 −50). The total number of somatic mutations ( p = 0.0039) and the fraction of transitions ( p = 5.5×10 −4) were associated with increased risk of distant metastasis. Our study’s limitations include a small number of LUAD patients for subgroup analyses and a single-sample design for investigation of subclonality.
These data provide a genomic characterization of LUAD pathogenesis and progression. The distinct clonal and subclonal mutation signatures suggest possible diverse carcinogenesis pathways for endogenous and exogenous exposures, and may serve as a foundation for more effective treatments for this lethal disease. LUAD’s high heterogeneity emphasizes the need to further study this tumor type and to associate genomic findings with clinical outcomes.
Maria Teresa Landi and colleagues report genomic tumor data for a cohort of patients with lung adenocarcinoma, focusing on implications for tumor initiation and distant metastasis.
We performed an integrative genomic analysis, incorporating whole exome sequencing (WES), DNA copy number and DNA methylation determination, and transcriptome sequencing in 101 LUAD samples. We replicated major findings using public genomic resources and combined all existing genomic data for an overall analysis of 825 LUAD samples.
We identified two novel driver genes and characterized the driver events and types of mutations that have a stronger role in tumor initiation versus tumor progression.
We found strong associations between DNA methylation and somatic mutation patterns.
The total number of somatic mutations and the fraction of C→T transitions were associated with increased risk of distant metastasis.
We characterized LUAD genomic architecture and linked major genomic features with clinical outcomes.
Tobacco smoking-related mutations appear to have a stronger role in tumor initiation, while mutations associated with endogenous processes are more prominent at a later stage of tumor development and are associated with tumor progression.
Our findings highlight the complexity and heterogeneity of LUAD. In addition to new driver genes, we found some tumors with no exonic mutations in known lung cancer driver genes. This suggests that there are further drivers (genetic or epigenetic) to be identified, and larger numbers of samples need to be studied to fully capture LUAD genomic characteristics.