Shen, Hongbing

Abstract Background Lung adenocarcinoma in never-smokers is a major public health burden, especially among East Asian women. Polygenic risk scores (PRSs) are promising for risk stratification but are primarily developed in European-ancestry populations. We aimed to develop and validate single- and multi-ancestry PRSs for East Asian never-smokers to improve lung adenocarcinoma risk prediction. Methods PRSs were developed using genome-wide association study summary statistics from East Asian (8002 cases; 20 782 controls) and European (2058 cases; 5575 controls) populations. Single-ancestry models included a PRS with 25 single nucleotide variants (PRS-25), PRS clumping and thresholding (CT), and LDpred2; multi-ancestry models included LDpred2 plus European PRS-128, PRS-CSx, and clumping and thresholding, super learning, empirical Bayes (CT-SLEB). Performance was evaluated in independent East Asian data from the Female Lung Cancer Consortium and externally validated in the Nanjing Lung Cancer Cohort. We assessed predictive accuracy via area under the curve operating procedure (AUC), with 10-year and (ages 30-80 years) absolute risks estimates. Results The best multi-ancestry PRS, using East Asian and European data via CT-SLEB, outperformed the best East Asian-only (LDpred2; AUC = 0.629, 95% confidence interval [CI] = 0.618 to 0.641), achieving an AUC of 0.640 (95% CI = 0.629 to 0.653) and odds ratio of 1.71 (95% CI = 1.61 to 1.82) per standard deviation increase. Nanjing Lung Cancer Cohort validation confirmed robust performance (AUC = 0.649, 95% CI = 0.623 to 0.676). The top 20% PRS group had a 3.92-fold higher lung adenocarcinoma risk than the bottom 20%. Further, the top 5% PRS group reached a 6.69% lifetime absolute risk. Notably, this group reached the average population 10-year lung adenocarcinoma risk at age 50 years (0.42%) by age 41 years, 9 years earlier. Conclusions Multi-ancestry PRS approaches enhance lung adenocarcinoma risk stratification in East Asian never-smokers, with consistent external validation, suggesting future clinical utility.

Abstract Background: Clinical, molecular, and genetic epidemiology studies displayed remarkable differences between ever- and never-smoking lung cancer. Methods: We conducted a stratified multi-population (European, East Asian, and African descent) association study on 44,823 ever-smokers and 20,074 never-smokers to identify novel variants that were missed in the non-stratified analysis. Functional analysis including expression quantitative trait loci (eQTL) colocalization and DNA damage assays, and annotation studies were conducted to evaluate the functional roles of the variants. We further evaluated the impact of smoking quantity on lung cancer risk for the variants associated with ever-smoking lung cancer. Results: Five novel independent loci, GABRA4, intergenic region 12q24.33, LRRC4C, LINC01088, and LCNL1 were identified with the association at two or three populations (P < 5 × 10−8). Further functional analysis provided multiple lines of evidence suggesting the variants affect lung cancer risk through excessive DNA damage (GABRA4) or cis-regulation of gene expression (LCNL1). The risk of variants from 12 independent regions, including the well-known CHRNA5, associated with ever-smoking lung cancer was evaluated for never-smokers, light-smokers (packyear ≤ 20), and moderate-to-heavy-smokers (packyear > 20). Different risk patterns were observed for the variants among the different groups by smoking behavior. Conclusions: We identified novel variants associated with lung cancer in only ever- or never-smoking groups that were missed by prior main-effect association studies. Impact: Our study highlights the genetic heterogeneity between ever- and never-smoking lung cancer and provides etiologic insights into the complicated genetic architecture of this deadly cancer.

Abstract Differences by sex in lung cancer incidence and mortality have been reported which cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene–sex interaction analysis using genotypes from a lung cancer cohort including ~ 47 000 individuals with European ancestry. Three low-frequency variants (minor allele frequency < 0.05), rs17662871 [odds ratio (OR) = 0.71, P = 4.29×10−8); rs79942605 (OR = 2.17, P = 2.81×10−8) and rs208908 (OR = 0.70, P = 4.54×10−8) were identified with different risk effect of lung cancer between men and women. Further expression quantitative trait loci and functional annotation analysis suggested rs208908 affects lung cancer risk through differential regulation of Coxsackie virus and adenovirus receptor gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.

Abstract Background: 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.

Abstract There is growing evidence showing that sex disparity in lung cancer risk cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene-sex interaction analysis using genotype from a lung cancer cohort including ~ 47,000 individuals with European ancestry. Three low-frequency variants (minor allele frequency < 0.05), rs17662871 (OR=0.71, p=4.29x10-8); rs79942605 (OR=2.17, p=2.81x10-8); and rs208908 (OR=0.70, p=4.54x10-8), were identified with different risk effect of lung cancer between men and women. Further eQTL and functional annotation analysis suggested rs208908 affect lung cancer risk through differential regulation of CXADR (Coxsackie Virus And Adenovirus Receptor) gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.

1512 Background: Tobacco smoking profoundly impacts LC risk; however, data are limited as to what extent SC prior to diagnosis impacts LC overall survival (OS) and lung cancer specific survival (LCSS). LC screening offers a possible teachable moment, but there is uncertainty of SC benefits after a lifetime of smoking. We use the ILCCO database to answer if SC prior to LC dx is associated with better OS and LCSS, considering time since smoking cessation (TSSC). Methods: Using individual data, analysis was performed on 17 ILCCO studies with available TSSC to estimate survival using univariable analysis and models of stage-adjusted and cumulative smoking-adjusted multivariable analysis. Adjusted Hazard Ratios (aHR) from Cox models, cubic spline smooth curves and Kaplan-Meier curves were created. Sensitivity analysis was performed for TSSC and LCSS on 13 studies. Results: Of 34649 patients, 14322 (41%) were current smokers 14273 (41%) ex-smokers and 6054 (18%) never smokers at diagnosis. We confirmed that ex-smokers (aHR 0.88 CI 0.86-0.91) and never smokers (aHR 0.76 CI 0.73-0.8) improved OS compared to current smokers. Amongst ex-smokers, < 2y TSSC (aHR 0.88 CI 0.82-0.94), 2-5y TSSC (aHR 0.83 CI 0.77-0.90) and > 5y TSSC (aHR 0.8 CI 0.76-0.84) had improved OS compared to CS. Sensitivity analysis showed a trend towards improved LCSS survival for < 2y TSSC (aHR 0.95 CI 0.86-1.05) and 2-5y TSSC (aHR 0.93 CI 0.83-1.04), whereas > 5y TSSC significantly improved LCSS by 15% (aHR 0.85 CI 0.78-0.92). To mimic the LC screening participants, in analysis of > 30 pack-years individuals, associations were strikingly strong: < 2y TSSC had improved OS by 14% (aHR 0.86 CI 0.80-0.93); 2-5y TSSC by 17% (aHR 0.83 CI 0.76-0.90); and > 5 TSSC by 22% (aHR 0.78 CI 0.74-0.83), compared to current smokers; for < 30 packs-years, a trend towards better OS was observed for < 2y TSSC (aHR 0.95 CI 0.92-1.02) and 2-5y TSSC (aHR 0.86 CI 0.74-1.01), whereas > 5y TSSC improved OS by 23% (aHR 0.77 CI 0.72-0.82). Conclusions: Among ex-smokers, the risk of overall death was reduced by 12% on < 2y TSSC, 17% on 2-5y TSSC and 20% > 5y TSSC, whereas for LCSS, the benefit was significant only for > 5y TSCC, compared to current smokers at time of diagnosis. Here we demonstrate that convincing screening participants to quit smoking at any point of their trajectory, even just prior to dx such as < 2y TSSC, improved OS, and LCSS benefit was present beyond 5y of quitting. These relationships are independent of pack-years, age, across all stages and other prognostic variables.

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.

Telomeres cap chromosome ends, protecting them from degradation, double‐strand breaks, and end‐to‐end fusions. Telomeres are maintained by telomerase, a reverse transcriptase encoded by TERT, and an RNA template encoded by TERC. Loci in the TERT and adjoining CLPTM1L region are associated with risk of multiple cancers. We therefore investigated associations between variants in 22 telomere structure and maintenance gene regions and colorectal, breast, prostate, ovarian, and lung cancer risk. We performed subset‐based meta‐analyses of 204,993 directly‐measured and imputed SNPs among 61,851 cancer cases and 74,457 controls of European descent. Independent associations for SNP minor alleles were identified using sequential conditional analysis (with gene‐level p value cutoffs ≤3.08 × 10−5). Of the thirteen independent SNPs observed to be associated with cancer risk, novel findings were observed for seven loci. Across the DCLRE1B region, rs974494 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Across the TERC region, rs75316749 was positively associated with colorectal, breast, ovarian, and lung cancers. Across the DCLRE1B region, rs974404 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Near POT1, rs116895242 was inversely associated with colorectal, ovarian, and lung cancers, and RTEL1 rs34978822 was inversely associated with prostate and lung cancers. The complex association patterns in telomere‐related genes across cancer types may provide insight into mechanisms through which telomere dysfunction in different tissues influences cancer risk.

Abstract Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer, and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. Cancer Res; 76(17); 5103–14. ©2016 AACR.

Abstract Telomeres are complex structures that cap chromosome ends, protecting them from degradation, double strand breaks and end-to-end fusions. Telomeres are maintained by the enzyme telomerase, which is made up of a reverse transcriptase encoded by TERT, and an RNA template encoded by TERC. The telomere structure itself is composed of proteins encoded by ACD, ACYP2, BICD1, DKC1, DCLRE1B, MPHOSPH6, NAF1, NOLA1, NOLA2, NOLA3, OBFC1, PIK3C3, POT1, RTEL1, TEP1, TERF1, TERF2, TERF21P, TINF2, TNKS/PINX1, TPP1 and ZNF208. Several single nucleotide polymorphisms (SNPs) in the TERT and adjoining CLPTM1L gene region are associated with multiple cancer types, and some are associated with both increased and decreased risks across different cancer types. We systematically characterized the patterns of association between variants in these 25 telomere structure and maintenance genes and risk across five cancer types in the Genetic Association and Mechanisms in Oncology (GAME-ON) consortium. We performed a subset-based meta-analysis (ASSET) of 209,367 directly measured and imputed SNPs, one megabase up- and downstream of these genes, across genome-wide association studies of colorectal (5,100 cases, 4,831 controls), lung (12,160 cases, 16,838 controls), breast (15,748 cases, 18,084 controls), ovarian (4,369 cases, 9,123 controls) and prostate (14,160 cases, 12,724 controls) cancers. Correlations (r2) between SNPs were examined in Haploview using the 1000 Genomes Project CEU population. A total of 87 TERT, 123 TERC and 26 DCLRE1B SNPs were associated with cancer risk at gene-level Bonferroni-corrected p-values of 4.2-7.8×10−6. Patterns of association were similar for prostate and colorectal cancers in DCLRE1B. Much stronger associations were observed in TERT and TERC, with 63 and 24 SNPs reaching genome-wide significance (p&lt;5.0×10−8), respectively. Of these, 9 TERT and 9 TERC SNPs were correlated at r2&lt;0.75. The most strongly associated SNPs in TERT (rs37004, p = 2.6×10−11) and TERC (rs76925190, p = 1.5×10−15) are in regions containing documented risk loci for lung and prostate cancers, respectively. TERT rs37004 (p = 1.2×10−13) and 6 of the other 9 SNPs in TERT were associated only with lung cancer risk. For the other 2 SNPs, there was a suggestion that patterns of risk were opposite for lung and prostate cancers. While TERC rs76925190 was strongly associated with prostate cancer risk (p = 5.4 x10−17), it was also suggestively associated with colorectal cancer risk (p&lt;0.005). This pattern was similar for another 2 of the 9 SNPs, while for the rest, associations were limited to prostate cancer. The complex patterns of association in telomere structure and maintenance genes observed across cancer types may provide insight about the mechanisms through which telomere dysfunction in different tissues influences cancer risk. Citation Format: Sara Karami, Younghun Han, Fredrick R. Schumacher, Zsofia Kote-Jarai, Sara Lindstrom, John S. Witte, Iona Cheng, Shenying Fang, Jiali Han, Peter Kraft, Fengju Song, Rayjean J. Hung, James McKay, Stephen J. Chanock, Mala Pande, Angela Risch, Hongbing Shen, Christopher A. Haiman, Lisa Boardman, Cornelia M. Ulrich, Graham Casey, Ulrike Peters, Nilanjan Chatterjee, Brandon Pierce, Wei Zheng, Christopher I. Amos, Jennifer A. Doherty. Risk loci in telomere structure and maintenance genes across five cancer types: GAME-ON Consortium. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4609. doi:10.1158/1538-7445.AM2015-4609