Environment And Genetics in Lung cancer Etiology (EAGLE) study: An integrative population-based case-control study of lung cancer

Landi, Maria Teresa; Consonni, Dario; Rotunno, Melissa; Bergen, Andrew W.; Goldstein, Alisa M.; Lubin, Jay H.; Goldin, Lynn R.; Alavanja, Michael C.R.; Morgan, Glen D.; Subar, Amy F.; Linnoila, Ilona; Previdi, Fabrizio; Corno, Massimo; Rubagotti, Maurizia; Marinelli, Barbara; Albetti, Benedetta; Colombi, A; Tucker, Margaret A.; Wacholder, Sholom; Pesatori, Angela Cecilia; Caporaso, Neil E.; Bertazzi, Pier Alberto

doi:10.1186/1471-2458-8-203

Cited by 120 publications

(156 citation statements)

References 16 publications

(14 reference statements)

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“…Since ExAC-nonTCGA comprises a subset of 1000G and ESP data, we also obtained DICER1 variation from 1000G phase 3 (2,504 exomes, accessed 12/28/16) 13 and ESP (6,503 exomes, accessed 12/28/16) to analyze datasets individually 14 . In addition to the publicly available databases, we utilized the whole exome sequencing controls (998 exomes) 18–20 . To capture all variants found in general populations, we did not filter any variants by minor allele frequency (MAF).…”

Section: Methodsmentioning

confidence: 99%

The prevalence of DICER1 pathogenic variation in population databases

Kim

Field

Schultz

et al. 2017

Intl Journal of Cancer

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The DICER1 syndrome is associated with a variety of rare benign and malignant tumors, including pleuropulmonary blastoma (PPB), cystic nephroma (CN) and Sertoli-Leydig cell tumor (SLCT). The prevalence and penetrance of pathogenic DICER1 variation in the general population is unknown. We examined three publicly-available germline whole exome sequence datasets: Exome Aggregation Consortium (ExAC), 1000 Genomes (1000G), and the Exome Sequencing Project (ESP). To avoid over-estimation of pathogenic DICER1 variation from cancer-associated exomes, we excluded The Cancer Genome Atlas (TCGA) variants from ExAC. All datasets were annotated with snpEFF and ANNOVAR and variants were classified into four categories: likely benign (LB), unknown significance (VUS), likely pathogenic (LP), or pathogenic (P). The prevalence of DICER1 P/LP variants was 1:870 to 1:2,529 in ExAC-nonTCGA (53,105 exomes) estimated by metaSVM and REVEL/CADD, respectively. A more stringent prevalence calculation considering only loss-of-function and previously-published pathogenic variants detected in ExAC-nonTCGA, yielded a prevalence of 1:10,600. Despite the rarity of most DICER1 syndrome tumors, pathogenic DICER1 variation is more common than expected. If confirmed, these findings may inform future sequencing-based newborn screening programs for PPB, CN and SLCT, in which early detection improves prognosis.

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Section: Methodsmentioning

confidence: 99%

The prevalence of DICER1 pathogenic variation in population databases

Kim

Field

Schultz

et al. 2017

Intl Journal of Cancer

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“…The overall study design and methods for TRICL have been described in detail elsewhere for most studies (17). The meta-analysis was based on summary data from 19 GWAS undertaken by eight analytic centers providing genotype data on 13,479 patients with lung cancer and 43,218 controls of European descent: the MD Anderson Cancer Center lung cancer study (24); the NCI lung cancer GWAS including the Environment and Genetics in Lung Cancer Etiology (EAGLE) study (25) and the Prostate, Lung, Colon, Ovary Screening Trial (PLCO) (26); the IARC lung cancer GWAS (5) including Central Europe GWAS (27); the Carotene and Retinol Efficacy Trial (CARET) cohort lung cancer GWAS (28); the HUNT2/Tromso 4 study (29); several lung cancer GWAS studies from Central Europe and France (30); the lung cancer study from Estonia (31); the German Lung Cancer Study (GLC) (32); the Greater Toronto Area lung cancer study (5) (331 cases and 499 controls); and the Icelandic Lung Cancer Study (deCODE) (1,319 cases and 26,380 controls) (33). Each TRICL study requested from each smoker (defined as individuals who smoked at least 100 cigarettes in their life) the number of cigarettes smoked per day and the number of years smoked.…”

Section: Methods For the Tricl Lung Cancer Gwas Consortiummentioning

confidence: 99%

Novel Association of Genetic Markers Affecting CYP2A6 Activity and Lung Cancer Risk

et al. 2016

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Metabolism of nicotine by cytochrome CYP2A6 is a suspected determinant of smoking dose and, consequently, lung cancer risk. We conducted a genome-wide association study (GWAS) of CYP2A6 activity, as measured by the urinary ratio of trans-3′-hydroxycotinine and its glucuronide conjugate over cotinine (total 3HCOT/COT), among 2,239 smokers in the Multiethnic Cohort (MEC) study. We identified 248 CYP2A6 variants associated with CYP2A6 activity (p<5×10−8). CYP2A6 activity was correlated (r=0.32, p<0.0001) with total nicotine equivalents (a measure of nicotine uptake). When we examined the effect of these variants on lung cancer risk in the Transdisciplinary Research in Cancer of the Lung (TRICL) consortium GWAS dataset (13,479 cases, 43,218 controls), we found that the vast majority of these individual effects were directionally consistent and associated with an increased lung cancer risk. 226 of the 248 variants associated with CYP2A6 activity in the MEC were available in TRICL. Of them, 81% had directionally consistent risk estimates and six were globally significantly associated with lung cancer. When conditioning on nine known functional variants and two deletions, the top two SNPs (rs56113850 in MEC and rs35755165 in TRICL) remained significantly associated with CYP2A6 activity in MEC and lung cancer in TRICL. The present data support the hypothesis that a greater CYP2A6 activity causes smokers to smoke more extensively and be exposed to higher levels of carcinogens, resulting in an increased risk for lung cancer. Although the variants identified in these studies may be used as risk prediction markers, the exact causal variants remain to be identified.

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“…In the current study, we sequenced the exome of tumor/blood sample pairs of 101 LUAD patients and the transcriptome of 80 LUAD tumor tissue samples from the Environment And Genetics in Lung cancer Etiology (EAGLE) study [15], in which a cohort of patients with LUAD were followed up for several years and comprehensive data on demographic, behavioral, and clinical characteristics were collected. Most patients were heavy smokers and were diagnosed at an early disease stage.…”

Section: Introductionmentioning

confidence: 99%

Somatic Genomics and Clinical Features of Lung Adenocarcinoma: A Retrospective Study

et al. 2016

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BackgroundLung 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.Methods and FindingsWe 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.ConclusionsThese 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.

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Environment And Genetics in Lung cancer Etiology (EAGLE) study: An integrative population-based case-control study of lung cancer

Cited by 120 publications

References 16 publications

The prevalence of DICER1 pathogenic variation in population databases

The prevalence of DICER1 pathogenic variation in population databases

Novel Association of Genetic Markers Affecting CYP2A6 Activity and Lung Cancer Risk

Somatic Genomics and Clinical Features of Lung Adenocarcinoma: A Retrospective Study

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