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  • American Association for Cancer Research (AACR)  (6)
  • 1
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 26, No. 1 ( 2017-01-01), p. 126-135
    Abstract: Background: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. Methods: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. Results: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Conclusions: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures. Impact: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126–35. ©2016 AACR.
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2017
    detail.hit.zdb_id: 2036781-8
    detail.hit.zdb_id: 1153420-5
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  • 2
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 28, No. 5 ( 2019-05-01), p. 935-942
    Abstract: Platelets are a critical element in coagulation and inflammation, and activated platelets are linked to cancer risk through diverse mechanisms. However, a causal relationship between platelets and risk of lung cancer remains unclear. Methods: We performed single and combined multiple instrumental variable Mendelian randomization analysis by an inverse-weighted method, in addition to a series of sensitivity analyses. Summary data for associations between SNPs and platelet count are from a recent publication that included 48,666 Caucasian Europeans, and the International Lung Cancer Consortium and Transdisciplinary Research in Cancer of the Lung data consisting of 29,266 cases and 56,450 controls to analyze associations between candidate SNPs and lung cancer risk. Results: Multiple instrumental variable analysis incorporating six SNPs showed a 62% increased risk of overall non–small cell lung cancer [NSCLC; OR, 1.62; 95% confidence interval (CI), 1.15–2.27; P = 0.005] and a 200% increased risk for small-cell lung cancer (OR, 3.00; 95% CI, 1.27–7.06; P = 0.01). Results showed only a trending association with NSCLC histologic subtypes, which may be due to insufficient sample size and/or weak effect size. A series of sensitivity analysis retained these findings. Conclusions: Our findings suggest a causal relationship between elevated platelet count and increased risk of lung cancer and provide evidence of possible antiplatelet interventions for lung cancer prevention. Impact: These findings provide a better understanding of lung cancer etiology and potential evidence for antiplatelet interventions for lung cancer prevention.
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
    detail.hit.zdb_id: 2036781-8
    detail.hit.zdb_id: 1153420-5
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  • 3
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 31, No. 3 ( 2022-03-01), p. 679-687
    Abstract: Somatic EGFR mutations define a subset of non–small cell lung cancers (NSCLC) that have clinical impact on NSCLC risk and outcome. However, EGFR-mutation-status is often missing in epidemiologic datasets. We developed and tested pragmatic approaches to account for EGFR-mutation-status based on variables commonly included in epidemiologic datasets and evaluated the clinical utility of these approaches. Methods: Through analysis of the International Lung Cancer Consortium (ILCCO) epidemiologic datasets, we developed a regression model for EGFR-status; we then applied a clinical-restriction approach using the optimal cut-point, and a second epidemiologic, multiple imputation approach to ILCCO survival analyses that did and did not account for EGFR-status. Results: Of 35,356 ILCCO patients with NSCLC, EGFR-mutation-status was available in 4,231 patients. A model regressing known EGFR-mutation-status on clinical and demographic variables achieved a concordance index of 0.75 (95% CI, 0.74–0.77) in the training and 0.77 (95% CI, 0.74–0.79) in the testing dataset. At an optimal cut-point of probability-score = 0.335, sensitivity = 69% and specificity = 72.5% for determining EGFR-wildtype status. In both restriction-based and imputation-based regression analyses of the individual roles of BMI on overall survival of patients with NSCLC, similar results were observed between overall and EGFR-mutation-negative cohort analyses of patients of all ancestries. However, our approach identified some differences: EGFR-mutated Asian patients did not incur a survival benefit from being obese, as observed in EGFR-wildtype Asian patients. Conclusions: We introduce a pragmatic method to evaluate the potential impact of EGFR-status on epidemiological analyses of NSCLC. Impact: The proposed method is generalizable in the common occurrence in which EGFR-status data are missing.
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2022
    detail.hit.zdb_id: 2036781-8
    detail.hit.zdb_id: 1153420-5
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  • 4
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 29, No. 7 ( 2020-07-01), p. 1423-1429
    Abstract: A substantial proportion of cancer driver genes (CDG) are also cancer predisposition genes. However, the associations between genetic variants in lung CDGs and the susceptibility to lung cancer have rarely been investigated. Methods: We selected expression-related single-nucleotide polymorphisms (eSNP) and nonsynonymous variants of lung CDGs, and tested their associations with lung cancer risk in two large-scale genome-wide association studies (20,871 cases and 15,971 controls of European descent). Conditional and joint association analysis was performed to identify independent risk variants. The associations of independent risk variants with somatic alterations in lung CDGs or recurrently altered pathways were investigated using data from The Cancer Genome Atlas (TCGA) project. Results: We identified seven independent SNPs in five lung CDGs that were consistently associated with lung cancer risk in discovery (P & lt; 0.001) and validation (P & lt; 0.05) stages. Among these loci, rs78062588 in TPM3 (1q21.3) was a new lung cancer susceptibility locus (OR = 0.86, P = 1.65 × 10−6). Subgroup analysis by histologic types further identified nine lung CDGs. Analysis of somatic alterations found that in lung adenocarcinomas, rs78062588[C] allele (TPM3 in 1q21.3) was associated with elevated somatic copy number of TPM3 (OR = 1.16, P = 0.02). In lung adenocarcinomas, rs1611182 (HLA-A in 6p22.1) was associated with truncation mutations of the transcriptional misregulation in cancer pathway (OR = 0.66, P = 1.76 × 10−3). Conclusions: Genetic variants can regulate functions of lung CDGs and influence lung cancer susceptibility. Impact: Our findings might help unravel biological mechanisms underlying lung cancer susceptibility.
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2020
    detail.hit.zdb_id: 2036781-8
    detail.hit.zdb_id: 1153420-5
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  • 5
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 77, No. 13_Supplement ( 2017-07-01), p. 2292-2292
    Abstract: Background: Impaired lung function (LF) is strongly associated with increased lung cancer risk. However, since airflow obstruction is a diagnostic criterion for obstructive lung disease, and a consequence of tobacco smoking, isolating the causal relationship between LF and lung cancer has remained a challenge. Methods: We investigated 3 standardized (mean=0, standard deviation=1) LF metrics: forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), and FEV1/FVC. To evaluate the causal relevance of LF in lung cancer etiology we conducted: i) survival analyses in the UK Biobank cohort (UKB); and ii) Mendelian Randomization (MR) analyses using genetic instrumental variables (IVs) developed in UKB and tested using individual-level data from the OncoArray, a genome-wide array with in-depth coverage for common cancers. Results: 702 incident lung cancers were diagnosed in 484,194 UKB participants during follow-up. Cox regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI), adjusted for age, sex, smoking status, socioeconomic status, and assessment center. Adjustment for other smoking metrics yielded similar results. Lung cancer risk increased per 1 unit decrease in FEV1 (HR=1.80, 95% CI: 1.64-1.98, p=3.3×10-34), FVC (HR=1.45, 1.30-1.60, p=2.3×10-12), and FEV1/FVC (HR=1.39, 1.33-1.46, p=1.3×10-38). This pattern was observed for adenocarcinoma (n=300): FEV1 (HR=1.77, p=6.0×10-12), FVC (HR=1.48, p=1.4×10-5), FEV1/FVC (HR=1.34, p=8.3×10-11); and squamous cell carcinoma (n=166): FEV1 (HR=1.97, p=9.9×10-10), FVC (HR=1.60, p=1.0×10-4), FEV1/FVC (HR=1.38, p=5.9×10-8). Next, a genome-wide association study of 67,708 UKB participants and 12.6 million variants was carried out to develop genetic IVs for LF. Results were filtered to retain independent variants (R2 & lt;0.2) associated with each LF phenotype (p & lt;5×10-8). The following IVs were developed: FEV1 (n=28 variants, 0.72% of variation explained), FVC (n=44, 1.08%), and FEV1/FVC (n=45, 1.85%). Odds ratios (OR) for each IV and lung cancer were estimated for 18,686 cases 15,190 controls ( & gt;80% European ancestry) from 23 studies. Effect estimates were combined using maximum-likelihood MR models to estimate causal ORs. MR results indicate that genetic scores associated with improved airflow are unrelated to lung cancer risk: FEV1 (OR=1.00, 95% CI: 0.96-1.03, p=0.86), FVC (OR=1.00, 0.97-1.03, p=0.93) and FEV1/FVC (OR=1.00, 0.91-1.10, p=0.95). The null association observed for the genetic determinants of FEV1, FVC and FEV1/FVC was not modified by tumor histology or smoking status. Conclusions: LF is a robust predictor of lung cancer risk, however, our findings do not support the existence of causal pathways that are independent of obstructive lung disease or smoking. This apparent lack of a causal relationship should be interpreted with caution since pleiotropic effects of LF loci cannot be ruled out. Citation Format: Linda Kachuri, Mattias Johansson, Paul Brennan, Phillip Haycock, Geoffrey Liu, Maria Teresa Landi, David C. Christiani, Neil E. Caporaso, Xifeng Wu, Melinda C. Aldrich, Demetrius Albanes, Adonina Tardón, Gad Rennert, Chu Chen, Gary E. Goodman, Jennifer A. Doherty, Heike Bickeböller, Dawn Teare, Lambertus A. Kiemeney, Stig E. Bojesen, John K. Field, Aage Haugen, Stephen Lam, Loic Le Marchand, Matthew B. Schabath, Angeline S. Andrew, Jonas Manjer, Philip Lazarus, Susanne M. Arnold, Valérie Gaborieau, Richard Martin, Caroline Relton, George Davey Smith, Christopher I. Amos, James D. McKay, Rayjean J. Hung. Lung function and lung cancer risk: a Mendelian randomization study of UK Biobank cohort and the International Lung Cancer Consortium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2292. doi:10.1158/1538-7445.AM2017-2292
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2017
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 6
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 81, No. 6 ( 2021-03-15), p. 1607-1615
    Abstract: Lung cancer is the leading cause of cancer-related death globally. An improved risk stratification strategy can increase efficiency of low-dose CT (LDCT) screening. Here we assessed whether individual's genetic background has clinical utility for risk stratification in the context of LDCT screening. On the basis of 13,119 patients with lung cancer and 10,008 controls with European ancestry in the International Lung Cancer Consortium, we constructed a polygenic risk score (PRS) via 10-fold cross-validation with regularized penalized regression. The performance of risk model integrating PRS, including calibration and ability to discriminate, was assessed using UK Biobank data (N = 335,931). Absolute risk was estimated on the basis of age-specific lung cancer incidence and all-cause mortality as competing risk. To evaluate its potential clinical utility, the PRS distribution was simulated in the National Lung Screening Trial (N = 50,772 participants). The lung cancer ORs for individuals at the top decile of the PRS distribution versus those at bottom 10% was 2.39 [95% confidence interval (CI) = 1.92–3.00; P = 1.80 × 10−14] in the validation set (Ptrend = 5.26 × 10−20). The OR per SD of PRS increase was 1.26 (95% CI = 1.20–1.32; P = 9.69 × 10−23) for overall lung cancer risk in the validation set. When considering absolute risks, individuals at different PRS deciles showed differential trajectories of 5-year and cumulative absolute risk. The age reaching the LDCT screening recommendation threshold can vary by 4 to 8 years, depending on the individual's genetic background, smoking status, and family history. Collectively, these results suggest that individual's genetic background may inform the optimal lung cancer LDCT screening strategy. Significance: Three large-scale datasets reveal that, after accounting for risk factors, an individual's genetics can affect their lung cancer risk trajectory, thus may inform the optimal timing for LDCT screening.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2021
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
    Location Call Number Limitation Availability
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