Deciphering associations for lung cancer risk through imputation and analysis of 12,316 cases and 16,831 controls

The associations between dysregulation of human blood metabolites and lung cancer risk: evidence from genetic data

BACKGROUND

Metabolic dysregulation is recognized as a significant hallmark of cancer progression. Although numerous studies have linked specific metabolic pathways to cancer incidence, the causal relationship between blood metabolites and lung cancer risk remains unclear.

METHODS

Genomic data from 29,266 lung cancer patients and 56,450 control individuals from the Transdisciplinary Research in Cancer of the Lung and the International Lung Cancer Consortium (TRICL-ILCCO) were utilized, and findings were replicated using additional data from the FinnGen consortium. The analysis focused on the associations between 486 blood metabolites and the susceptibility to overall lung cancer and its three major clinical subtypes. Various Mendelian randomization methods, including inverse-variance weighting, weighted median estimation, and MR-Egger regression, were employed to ensure the robustness of our findings.

RESULTS

A total of 19 blood metabolites were identified with significant associations with lung cancer risk. Specifically, oleate (OR per SD = 2.56, 95% CI: 1.51 to 4.36), 1-arachidonoylglyceropholine (OR = 1.79, 95% CI: 1.22 to 2.65), and arachidonate (OR = 1.67, 95% CI: 1.16 to 2.40) were associated with a higher risk of lung cancer. Conversely, 1-linoleoylglycerophosphoethanolamine (OR = 0.57, 95% CI: 0.40 to 0.82), ADpSGEGDFXAEGGGVR, a fibrinogen cleavage peptide (OR = 0.60, 95% CI: 0.47 to 0.77), and isovalerylcarnitine (OR = 0.62, 95% CI: 0.49 to 0.78) were associated with a lower risk of lung cancer. Notably, isoleucine (OR = 9.64, 95% CI: 2.55 to 36.38) was associated with a significantly higher risk of lung squamous cell cancer, while acetyl phosphate (OR = 0.11, 95% CI: 0.01 to 0.89) was associated with a significantly lower risk of small cell lung cancer.

CONCLUSION

This study reveals the complex relationships between specific blood metabolites and lung cancer risk, highlighting their potential as biomarkers for lung cancer prevention, screening, and treatment. The findings not only deepen our understanding of the metabolic mechanisms of lung cancer but also provide new insights for future treatment strategies.

Causal Estimation of Long-term Intervention Cost-effectiveness Using Genetic Instrumental Variables: An Application to Cancer

BACKGROUND

This article demonstrates a means of assessing long-term intervention cost-effectiveness in the absence of data from randomized controlled trials and without recourse to Markov simulation or similar types of cohort simulation.

METHODS

Using a Mendelian randomization study design, we developed causal estimates of the genetically predicted effect of bladder, breast, colorectal, lung, multiple myeloma, ovarian, prostate, and thyroid cancers on health care costs and quality-adjusted life-years (QALYs) using outcome data drawn from the UK Biobank cohort. We then used these estimates in a simulation model to estimate the cost-effectiveness of a hypothetical population-wide preventative intervention based on a repurposed class of antidiabetic drugs known as sodium-glucose cotransporter-2 (SGLT2) inhibitors very recently shown to reduce the odds of incident prostate cancer.

RESULTS

Genetic liability to prostate cancer and breast cancer had material causal impacts on either or both health care costs and QALYs. Mendelian randomization results for the less common cancers were associated with considerable uncertainty. SGLT2 inhibition was unlikely to be a cost-effective preventative intervention for prostate cancer, although this conclusion depended on the price at which these drugs would be offered for a novel anticancer indication.

IMPLICATIONS

Our new causal estimates of cancer exposures on health economic outcomes may be used as inputs into decision-analytic models of cancer interventions such as screening programs or simulations of longer-term outcomes associated with therapies investigated in randomized controlled trials with short follow-ups. Our method allowed us to rapidly and efficiently estimate the cost-effectiveness of a hypothetical population-scale anticancer intervention to inform and complement other means of assessing long-term intervention value.

HIGHLIGHTS

The article demonstrates a novel method of assessing long-term intervention cost-effectiveness without relying on randomized controlled trials or cohort simulations.Mendelian randomization was used to estimate the causal effects of certain cancers on health care costs and quality-adjusted life-years (QALYs) using data from the UK Biobank cohort.Given causal data on the association of different cancer exposures on costs and QALYs, it was possible to simulate the cost-effectiveness of an anticancer intervention.Genetic liability to prostate cancer and breast cancer significantly affected health care costs and QALYs, but the hypothetical intervention using SGLT2 inhibitors for prostate cancer may not be cost-effective, depending on the drug's price for the new anticancer indication. The methods we propose and implement can be used to efficiently estimate intervention cost-effectiveness and to inform decision making in all manner of preventative and therapeutic contexts.

The causal relationship between severe mental illness and risk of lung carcinoma

Observational studies have suggested a link between severe mental illness (SMI) and risk of lung carcinoma (LC); however, causality has not been established. In this study, we conducted a two-sample, two-step Mendelian randomization (MR) investigation to uncover the etiological influence of SMI on LC risk and quantify the mediating effects of known modifiable risk factors. We obtained summary-level datasets for schizophrenia, major depressive disorder (MDD), and bipolar disorder (BD) from the Psychiatric Genomics Consortium (PGC). Data on single nucleotide polymorphisms (SNPs) associated with lung carcinoma (LC) were sourced from a recent large meta-analysis by McKay et al. We employed two-sample MR and two-step MR utilizing the inverse variance weighted method for causal estimation. Sensitivity tests were conducted to validate causal relationships. In two-sample MR, we identified schizophrenia as a risk factor for LC (OR = 1.06, 95% CI 1.02-1.11, P = 3.48E-03), while MDD (OR = 1.18, 95% CI 0.98-1.42, P = .07) and BD (OR = 1.07, 95% CI 0.99-1.15, P = .09) showed no significant association with LC. In the two-step MR, smoking accounted for 24.66% of the schizophrenia-LC risk association, and alcohol consumption explained 7.59% of the effect. Schizophrenia is a risk factor for lung carcinoma, and smoking and alcohol consumption are the mediating factors in this causal relationship. LC screening should be emphasized in individuals with schizophrenia, particularly in those who smoke and consume alcohol regularly.

Impact of individual level uncertainty of lung cancer polygenic risk score (PRS) on risk stratification

BACKGROUND

Although polygenic risk score (PRS) has emerged as a promising tool for predicting cancer risk from genome-wide association studies (GWAS), the individual-level accuracy of lung cancer PRS and the extent to which its impact on subsequent clinical applications remains largely unexplored.

METHODS

Lung cancer PRSs and confidence/credible interval (CI) were constructed using two statistical approaches for each individual: (1) the weighted sum of 16 GWAS-derived significant SNP loci and the CI through the bootstrapping method (PRS-16-CV) and (2) LDpred2 and the CI through posteriors sampling (PRS-Bayes), among 17,166 lung cancer cases and 12,894 controls with European ancestry from the International Lung Cancer Consortium. Individuals were classified into different genetic risk subgroups based on the relationship between their own PRS mean/PRS CI and the population level threshold.

RESULTS

Considerable variances in PRS point estimates at the individual level were observed for both methods, with an average standard deviation (s.d.) of 0.12 for PRS-16-CV and a much larger s.d. of 0.88 for PRS-Bayes. Using PRS-16-CV, only 25.0% of individuals with PRS point estimates in the lowest decile of PRS and 16.8% in the highest decile have their entire 95% CI fully contained in the lowest and highest decile, respectively, while PRS-Bayes was unable to find any eligible individuals. Only 19% of the individuals were concordantly identified as having high genetic risk (> 90th percentile) using the two PRS estimators. An increased relative risk of lung cancer comparing the highest PRS percentile to the lowest was observed when taking the CI into account (OR = 2.73, 95% CI: 2.12-3.50, P-value = 4.13 × 10-15) compared to using PRS-16-CV mean (OR = 2.23, 95% CI: 1.99-2.49, P-value = 5.70 × 10-46). Improved risk prediction performance with higher AUC was consistently observed in individuals identified by PRS-16-CV CI, and the best performance was achieved by incorporating age, gender, and detailed smoking pack-years (AUC: 0.73, 95% CI = 0.72-0.74).

CONCLUSIONS

Lung cancer PRS estimates using different methods have modest correlations at the individual level, highlighting the importance of considering individual-level uncertainty when evaluating the practical utility of PRS.

Associations between diet and incidence risk of lung cancer: A Mendelian randomization study

Background

Observational studies have revealed associations between diet and lung cancer. However, it is unclear whether the association is disturbed by confounding factors. We used a two-sample Mendelian randomization (MR) method to characterize the associations between diet and the lung cancer risk (including 3 subtypes: lung adenocarcinoma (LA), squamous cell lung carcinoma (SqCLC), and small cell lung cancer (SCLC)).

Materials and methods

Data on 20 diets were screened from the UK Biobank. Lung cancer data came from a large meta-analysis of 85,716 individuals. The inverse-variance weighted method was used as the main analysis. Sensitivity analysis was also used to explain the different multiplicity patterns of the final model.

Results

Our results showed significant evidence that 3 diets were associated with lung cancer [odds ratio (OR): 0.271, 95% confidence interval (CI): 0.150–0.488, p = 1.46 × 10−4, dried fruit; OR: 3.010, 95% CI: 1.608–5.632, p = 5.70 × 10−4, beer] and SqCLC (OR: 0.135, 95% CI: 0.062–0.293, p = 2.33 × 10−5, dried fruit; OR: 0.485, 95% CI: 0.328–0.717, p = 2.9 × 10−4, cheese). There were also suggestive correlations between 5 dietary intakes and lung cancer (OR: 0.441, 95% CI: 0.250–0.778, p = 0.008, cereal; OR: 2.267, 95% CI: 1.126–4.564, p = 0.022, beef), LA (OR: 0.494, 95% CI: 0.285–0.858, p = 0.012, dried fruit; OR: 3.536, 95% CI: 1.546–8.085, p = 0.003, beer) and SCLC (OR: 0.006, 95% CI: 0.000–0.222, p = 0.039, non-oily fish; OR: 0.239, 95% CI: 0.086–0.664, p = 0.006, dried fruit). No other association between diet and lung cancer was observed.

Conclusion

Our study preliminary found that cheese, dried fruit, and beer intake were significantly associated with the risk of lung cancer or its subtypes, while cereal, beef, and non-oily fish intake were suggestively associated with the risk of lung cancer or its subtypes. Well-designed prospective studies are still needed to confirm our findings in the future.

The role of smoking and alcohol in mediating the effect of gastroesophageal reflux disease on lung cancer: A Mendelian randomization study

Observational studies have suggested a positive association between gastroesophageal reflux disease and lung cancer, but due to the existence of confounders, it remains undetermined whether gastroesophageal reflux disease (GERD) has a causal association with lung cancer. Therefore, Mendelian randomization (MR) analyses were applied to investigate the relationship between the two conditions. Two-sample Mendelian randomization analysis was utilized with summary genetic data from the European Bioinformatics Institute (602,604 individuals) and International Lung Cancer Consortium, which provides information on lung cancer and its histological subgroups. Furthermore, we used two-step Mendelian randomization and multivariable Mendelian randomization to estimate whether smoking initiation (311,629 cases and 321,173 controls) and alcohol intake frequency (n = 462,346) mediate any effect of gastroesophageal reflux disease on lung cancer risk. The Mendelian randomization analyses indicated that gastroesophageal reflux disease was associated with and significantly increased the risk of lung cancer (ORIVW = 1.35, 95% CI = 1.18-1.54; p = 1.36 × 10-5). Smoking initiation and alcohol intake frequency mediated 35% and 3% of the total effect of gastroesophageal reflux disease on lung cancer, respectively. The combined effect of these two factors accounted for 60% of the total effect. In conclusion, gastroesophageal reflux disease is associated with an increased risk of lung cancer, and interventions to reduce smoking and alcohol intake may reduce the incidence of lung cancer.

Investigating Causal Associations of Circulating Micronutrients Concentrations with the Risk of Lung Cancer: A Mendelian Randomization Study

Previous observational studies have suggested that the effect of diet-derived circulating micronutrient concentrations on lung cancer (LC) risk is controversial. We conducted a two-sample Mendelian randomization (MR) analysis to investigate the causal relationship between circulating micronutrient concentrations and the overall risk of LC and three LC subtypes (namely lung adenocarcinoma (LA), squamous cell lung cancer (SqCLC), and small cell lung cancer (SCLC)). The instrumental variables (IVs) of 11 micronutrients (beta-carotene, calcium, copper, folate, lycopene, magnesium, phosphorus, retinol, selenium, zinc, and vitamin B6) were screened from the published genome-wide association studies (GWAS). Summary statistics related to LC and its subtypes came from the largest meta-analysis, including 29,266 cases and 56,450 controls. Inverse-variance weighted (IVW) method is used as the main MR analysis, and the sensitivity analysis is carried out to ensure the MR assumptions. This MR study found suggestive evidence that genetically predicted 6 circulating micronutrient concentrations was correlated with the risk of overall LC (odds ratio (OR): 1.394, 95% confidence interval (CI): 1.041–1.868, p = 0.026, phosphorus), LA (OR: 0.794, 95% CI: 0.634–0.995, p = 0.045, beta-carotene; OR: 0.687, 95%CI: 0.494–0.957, p = 0.026, calcium), SqCLC (OR: 0.354, 95% CI: 0.145–0.865, p = 0.023, retinol), and SCLC (OR: 1.267, 95% CI: 1.040–1.543, p = 0.019, copper; OR: 0.801, 95% CI: 0.679–0.944, p = 0.008, zinc). We found no evidence that other micronutrients are associated with the risk of overall LC or its subtypes. Our study suggested that the increase in circulating beta-carotene, calcium, retinol, and zinc concentration may reduce the risk of LC; the increase in circulating copper and phosphorus concentration may be related to the increased risk of LC. In the future, larger replication samples of LC genetic data and larger micronutrient-related GWAS will be needed to verify our findings.

Cumulative Evidence for Relationships Between Multiple Variants in the TERT and CLPTM1L Region and Risk of Cancer and Non-Cancer Disease

Background

Genetic studies previously reported that variants in TERT-CLPTM1L genes were related to susceptibility of cancer and non-cancer diseases. However, conclusions were not always concordant.

Methods

We performed meta-analyses to assess correlations between 23 variants within TERT-CLPTM1L region and susceptibility to 12 cancers and 1 non-cancer disease based on data in 109 papers (involving 139,510 cases and 208,530 controls). Two approaches (false-positive report probability test and Venice criteria) were adopted for assessing the cumulative evidence of significant associations. Current study evaluated the potential role of these variants based on data in Encyclopedia of DNA Elements (ENCODE) Project.

Results

Thirteen variants were statistically associated with susceptibility to 11 cancers and 1 non-cancer disease (p < 0.05). Besides, 12 variants with eight cancers and one non-cancer disease were rated as strong evidence (rs2736098, rs401681, and rs402710 in bladder cancer; rs2736100, rs2853691, and rs401681 in esophageal cancer; rs10069690 in gastric cancer; rs2736100 and rs2853676 in glioma; rs2242652, rs2736098, rs2736100, rs2853677, rs31489, rs401681, rs402710, rs465498, and rs4975616 in lung cancer; rs2736100 in idiopathic pulmonary fibrosis and myeloproliferative neoplasms; and rs401681 in pancreatic and skin cancer). According to data from ENCODE and other public databases, 12 variants with strong evidence might fall within putative functional regions.

Conclusions

This paper demonstrated that common variants of TERT-CLPTM1L genes were related to susceptibility to bladder, esophageal, gastric, lung, pancreatic, and skin cancer, as well as to glioma, myeloproliferative neoplasms, and idiopathic pulmonary fibrosis, and, besides, the crucial function of the TERT-CLPTM1L region in the genetic predisposition to human diseases is elucidated.

Deciphering associations between three RNA splicing-related genetic variants and lung cancer risk

Limited efforts have been made in assessing the effect of genome-wide profiling of RNA splicing-related variation on lung cancer risk. In the present study, we first identified RNA splicing-related genetic variants linked to lung cancer in a genome-wide profiling analysis and then conducted a two-stage (discovery and replication) association study in populations of European ancestry. Discovery and validation were conducted sequentially with a total of 29,266 cases and 56,450 controls from both the Transdisciplinary Research in Cancer of the Lung and the International Lung Cancer Consortium as well as the OncoArray database. For those variants identified as significant in the two datasets, we further performed stratified analyses by smoking status and histological type and investigated their effects on gene expression and potential regulatory mechanisms. We identified three genetic variants significantly associated with lung cancer risk: rs329118 in JADE2 (P = 8.80E-09), rs2285521 in GGA2 (P = 4.43E-08), and rs198459 in MYRF (P = 1.60E-06). The combined effects of all three SNPs were more evident in lung squamous cell carcinomas (P = 1.81E-08, P = 6.21E-08, and P = 7.93E-04, respectively) than in lung adenocarcinomas and in ever smokers (P = 9.80E-05, P = 2.70E-04, and P = 2.90E-05, respectively) than in never smokers. Gene expression quantitative trait analysis suggested a role for the SNPs in regulating transcriptional expression of the corresponding target genes. In conclusion, we report that three RNA splicing-related genetic variants contribute to lung cancer susceptibility in European populations. However, additional validation is needed, and specific splicing mechanisms of the target genes underlying the observed associations also warrants further exploration.

Gene-gene interaction of AhRwith and within the Wntcascade affects susceptibility to lung cancer

BACKGROUND

Aberrant Wnt signalling, regulating cell development and stemness, influences the development of many cancer types. The Aryl hydrocarbon receptor (AhR) mediates tumorigenesis of environmental pollutants. Complex interaction patterns of genes assigned to AhR/Wnt-signalling were recently associated with lung cancer susceptibility.

AIM

To assess the association and predictive ability of AhR/Wnt-genes with lung cancer in cases and controls of European descent.

METHODS

Odds ratios (OR) were estimated for genomic variants assigned to the Wnt agonist and the antagonistic genes DKK2, DKK3, DKK4, FRZB, SFRP4 and Axin2. Logistic regression models with variable selection were trained, validated and tested to predict lung cancer, at which other previously identified SNPs that have been robustly associated with lung cancer risk could also enter the model. Furthermore, decision trees were created to investigate variant × variant interaction. All analyses were performed for overall lung cancer and for subgroups.

RESULTS

No genome-wide significant association of AhR/Wnt-genes with overall lung cancer was observed, but within the subgroups of ever smokers (e.g., maker rs2722278 SFRP4; OR  = 1.20; 95% CI 1.13-1.27; p  = 5.6 × 10-10) and never smokers (e.g., maker rs1133683 Axin2; OR  = 1.27; 95% CI 1.19-1.35; p  = 1.0 × 10-12). Although predictability is poor, AhR/Wnt-variants are unexpectedly overrepresented in optimized prediction scores for overall lung cancer and for small cell lung cancer. Remarkably, the score for never-smokers contained solely two AhR/Wnt-variants. The optimal decision tree for never smokers consists of 7 AhR/Wnt-variants and only two lung cancer variants.

CONCLUSIONS

The role of variants belonging to Wnt/AhR-pathways in lung cancer susceptibility may be underrated in main-effects association analysis. Complex interaction patterns in individuals of European descent have moderate predictive capacity for lung cancer or subgroups thereof, especially in never smokers.

Rare deleterious germline variants and risk of lung cancer

Recent studies suggest that rare variants exhibit stronger effect sizes and might play a crucial role in the etiology of lung cancers (LC). Whole exome plus targeted sequencing of germline DNA was performed on 1045 LC cases and 885 controls in the discovery set. To unveil the inherited causal variants, we focused on rare and predicted deleterious variants and small indels enriched in cases or controls. Promising candidates were further validated in a series of 26,803 LCs and 555,107 controls. During discovery, we identified 25 rare deleterious variants associated with LC susceptibility, including 13 reported in ClinVar. Of the five validated candidates, we discovered two pathogenic variants in known LC susceptibility loci, ATM p.V2716A (Odds Ratio [OR] 19.55, 95%CI 5.04-75.6) and MPZL2 p.I24M frameshift deletion (OR 3.88, 95%CI 1.71-8.8); and three in novel LC susceptibility genes, POMC c.*28delT at 3' UTR (OR 4.33, 95%CI 2.03-9.24), STAU2 p.N364M frameshift deletion (OR 4.48, 95%CI 1.73-11.55), and MLNR p.Q334V frameshift deletion (OR 2.69, 95%CI 1.33-5.43). The potential cancer-promoting role of selected candidate genes and variants was further supported by endogenous DNA damage assays. Our analyses led to the identification of new rare deleterious variants with LC susceptibility. However, in-depth mechanistic studies are still needed to evaluate the pathogenic effects of these specific alleles.

Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer

Clinical trial results have recently demonstrated that inhibiting inflammation by targeting the interleukin-1β pathway can offer a significant reduction in lung cancer incidence and mortality, highlighting a pressing and unmet need to understand the benefits of inflammation-focused lung cancer therapies at the genetic level. While numerous genome-wide association studies (GWAS) have explored the genetic etiology of lung cancer, there remains a large gap between the type of information that may be gleaned from an association study and the depth of understanding necessary to explain and drive translational findings. Thus, in this study we jointly model and integrate extensive multiomics data sources, utilizing a total of 40 genome-wide functional annotations that augment previously published results from the International Lung Cancer Consortium (ILCCO) GWAS, to prioritize and characterize single nucleotide polymorphisms (SNPs) that increase risk of squamous cell lung cancer through the inflammatory and immune responses. Our work bridges the gap between correlative analysis and translational follow-up research, refining GWAS association measures in an interpretable and systematic manner. In particular, reanalysis of the ILCCO data highlights the impact of highly associated SNPs from nuclear factor-κB signaling pathway genes as well as major histocompatibility complex mediated variation in immune responses. One consequence of prioritizing likely functional SNPs is the pruning of variants that might be selected for follow-up work by over an order of magnitude, from potentially tens of thousands to hundreds. The strategies we introduce provide informative and interpretable approaches for incorporating extensive genome-wide annotation data in analysis of genetic association studies.

Multi-Omics Analysis Reveals a HIF Network and Hub Gene EPAS1 Associated with Lung Adenocarcinoma

Recent technological advancements have permitted high-throughput measurement of the human genome, epigenome, metabolome, transcriptome, and proteome at the population level. We hypothesized that subsets of genes identified from omic studies might have closely related biological functions and thus might interact directly at the network level. Therefore, we conducted an integrative analysis of multi-omic datasets of non-small cell lung cancer (NSCLC) to search for association patterns beyond the genome and transcriptome. A large, complex, and robust gene network containing well-known lung cancer-related genes, including EGFR and TERT, was identified from combined gene lists for lung adenocarcinoma. Members of the hypoxia-inducible factor (HIF) gene family were at the center of this network. Subsequent sequencing of network hub genes within a subset of samples from the Transdisciplinary Research in Cancer of the Lung-International Lung Cancer Consortium (TRICL-ILCCO) consortium revealed a SNP (rs12614710) in EPAS1 associated with NSCLC that reached genome-wide significance (OR = 1.50; 95% CI: 1.31-1.72; p = 7.75 × 10^-9). Using imputed data, we found that this SNP remained significant in the entire TRICL-ILCCO consortium (p = .03). Additional functional studies are warranted to better understand interrelationships among genetic polymorphisms, DNA methylation status, and EPAS1 expression.

A Decade of GWAS Results in Lung Cancer

Genome-wide association studies (GWAS) were successful to identify genetic factors robustly associated with lung cancer. This review aims to synthesize the literature in this field and accelerate the translation of GWAS discoveries into results that are closer to clinical applications. A chronologic presentation of published GWAS on lung cancer susceptibility, survival, and response to treatment is presented. The most important results are tabulated to provide a concise overview in one read. GWAS have reported 45 lung cancer susceptibility loci with varying strength of evidence and highlighted suspected causal genes at each locus. Some genetic risk loci have been refined to more homogeneous subgroups of lung cancer patients in terms of histologic subtypes, smoking status, gender, and ethnicity. Overall, these discoveries are an important step for future development of new therapeutic targets and biomarkers to personalize and improve the quality of care for patients. GWAS results are on the edge of offering new tools for targeted screening in high-risk individuals, but more research is needed if GWAS are to pay off the investment. Complementary genomic datasets and functional studies are needed to refine the underlying molecular mechanisms of lung cancer preliminarily revealed by GWAS and reach results that are medically actionable. Cancer Epidemiol Biomarkers Prev; 27(4); 363-79. ©2018 AACRSee all articles in this CEBP Focus section, "Genome-Wide Association Studies in Cancer."

Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes

Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genome-wide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450 controls. We identified 18 susceptibility loci achieving genome-wide significance, including 10 new loci. The new loci highlight the striking heterogeneity in genetic susceptibility across the histological subtypes of lung cancer, with four loci associated with lung cancer overall and six loci associated with lung adenocarcinoma. Gene expression quantitative trait locus (eQTL) analysis in 1,425 normal lung tissue samples highlights RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer.

Functional variants in DCAF4 associated with lung cancer risk in European populations

Cullin-RING ubiquitin ligases (CRLs) responsible for substrate specificity of ubiquitination play a key role in cell-cycle control and DNA damage response. In this study, we assessed associations between 16 599 SNPs in 115 CRL genes and lung cancer risk by using summary data of six published genome-wide association studies (GWASs) of 12 160 cases and 16 838 cases of European ancestry. As a result, we identified three independent SNPs in DCAF4 (rs117781739, rs12587742 and rs2240980) associated with lung cancer risk (odds ratio = 0.91, 1.09 and 1.09, respectively; 95% confidence interval = 0.88-0.95, 1.05-1.14 and 1.05-1.13, respectively; and P = 3.99 × 10-6, 4.97 × 10-5 and 1.44 × 10-5, respectively) after multiple comparison correction by a false discovery rate <0.05. Since SNP rs12587742 is located within the promoter region and one CpG island of DCAF4, we further performed in silico functional analyses and found that the rs12587742 variant A allele was associated with an increased mRNA expression (P = 2.20 × 10-16, 1.79 × 10-13 and 0.001 in blood cells, normal lung tissues and tumor tissues of lung squamous carcinoma, respectively) and a decreased methylation status (P = 2.48 × 10-9 and 0.032 in adipose and lung tumor tissues, respectively). Moreover, evidence from differential expression analyses further supported an oncogenic effect of DCAF4 on lung cancer, with higher mRNA levels in both lung squamous carcinoma and adenocarcinoma (P = 4.48 × 10-11 and 1.22 × 10-9, respectively) than in adjacent normal tissues. Taken together, our results suggest that rs12587742 is associated with an increased lung cancer risk, possibly by up-regulating mRNA expression and decreasing methylation status of DCAF4.

The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers

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.

Telomere structure and maintenance gene variants and risk of five cancer types

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.

Relation between Established Glioma Risk Variants and DNA Methylation in the Tumor

Genome-wide association studies and candidate gene studies have identified several genetic variants that increase glioma risk. The majority of these variants are non-coding and the mechanisms behind the increased risk in carriers are not known. In this study, we hypothesize that some of the established glioma risk variants induce aberrant DNA methylation in the developing tumor, either locally (gene-specific) or globally (genome-wide). In a pilot data set including 77 glioma patients, we used Illumina beadchip technology to analyze genetic variants in blood and DNA methylation in matched tumor samples. To validate our findings, we used data from the Cancer Genome Atlas, including 401 glioblastoma patients. Consensus clustering identified the glioma CpG island methylator phenotype (gCIMP) and two additional subgroups with distinct patterns of global DNA methylation. In the pilot dataset, gCIMP was associated with two genetic variants in CDKN2B-AS1, rs1412829 and rs4977756 (9p21.3, p = 8.1 x 10-7 and 4.8 x 10-5, respectively). The association was in the same direction in the TCGA dataset, although statistically significant only when combining individuals with AG and GG genotypes. We also investigated the relation between glioma risk variants and DNA methylation in the promoter region of genes located within 30 kb of each variant. One association in the pilot dataset, between the TERT risk variant rs2736100 and lower methylation of cg23827991 (in TERT; p = 0.001), was confirmed in the TCGA dataset (p = 0.001). In conclusion, we found an association between rs1412829 and rs4977756 (9p21.3, CDKN2B-AS1) and global DNA methylation pattern in glioma, for which a trend was seen also in the TCGA glioblastoma dataset. We also found an association between rs2736100 (in TERT) and levels of methylation at cg23827991 (localized in the same gene, 3.3 kbp downstream of the risk variant), which was validated in the TCGA dataset. Except for this one association, we did not find strong evidence for gene-specific DNA methylation mediated by glioma risk variants.

Polymorphisms of the centrosomal gene (FGFR1OP) and lung cancer risk: a meta-analysis of 14,463 cases and 44,188 controls

Centrosome abnormalities are often observed in premalignant lesions and in situ tumors and have been associated with aneuploidy and tumor development. We investigated the associations of 9354 single-nucleotide polymorphisms (SNPs) in 106 centrosomal genes with lung cancer risk by first using the summary data from six published genome-wide association studies (GWASs) of the Transdisciplinary Research in Cancer of the Lung (TRICL) (12,160 cases and 16 838 controls) and then conducted in silico replication in two additional independent lung cancer GWASs of Harvard University (984 cases and 970 controls) and deCODE (1319 cases and 26,380 controls). A total of 44 significant SNPs with false discovery rate (FDR) ≤ 0.05 were mapped to one novel gene FGFR1OP and two previously reported genes (TUBB and BRCA2). After combined the results from TRICL with those from Harvard and deCODE, the most significant association (P combined = 8.032 × 10(-6)) was with rs151606 within FGFR1OP. The rs151606 T>G was associated with an increased risk of lung cancer [odds ratio (OR) = 1.10, 95% confidence interval (95% CI) = 1.05-1.14]. Another significant tagSNP rs12212247 T>C (P combined = 9.589 × 10(-6)) was associated with a decreased risk of lung cancer (OR = 0.93, 95% CI = 0.90-0.96). Further in silico functional analyzes revealed that rs151606 might affect transcriptional regulation and result in decreased FGFR1OP expression (P trend = 0.022). The findings shed some new light on the role of centrosome abnormalities in the susceptibility to lung carcinogenesis.

Gene by Environment Investigation of Incident Lung Cancer Risk in African-Americans

BACKGROUND

Genome-wide association studies have identified polymorphisms linked to both smoking exposure and risk of lung cancer. The degree to which lung cancer risk is driven by increased smoking, genetics, or gene-environment interactions is not well understood.

METHODS

We analyzed associations between 28 single nucleotide polymorphisms (SNPs) previously associated with smoking quantity and lung cancer in 7156 African-American females in the Women's Health Initiative (WHI), then analyzed main effects of top nominally significant SNPs and interactions between SNPs, cigarettes per day (CPD) and pack-years for lung cancer in an independent, multi-center case-control study of African-American females and males (1078 lung cancer cases and 822 controls).

FINDINGS

Nine nominally significant SNPs for CPD in WHI were associated with incident lung cancer (corrected p-values from 0.027 to 6.09 × 10(-5)). CPD was found to be a nominally significant effect modifier between SNP and lung cancer for six SNPs, including CHRNA5 rs2036527[A](betaSNP*CPD = - 0.017, p = 0.0061, corrected p = 0.054), which was associated with CPD in a previous genome-wide meta-analysis of African-Americans.

INTERPRETATION

These results suggest that chromosome 15q25.1 variants are robustly associated with CPD and lung cancer in African-Americans and that the allelic dose effect of these polymorphisms on lung cancer risk is most pronounced in lighter smokers.

Fine mapping of chromosome 5p15.33 based on a targeted deep sequencing and high density genotyping identifies novel lung cancer susceptibility loci

Chromosome 5p15.33 has been identified as a lung cancer susceptibility locus, however the underlying causal mechanisms were not fully elucidated. Previous fine-mapping studies of this locus have relied on imputation or investigated a small number of known, common variants. This study represents a significant advance over previous research by investigating a large number of novel, rare variants, as well as their underlying mechanisms through telomere length. Variants for this fine-mapping study were identified through a targeted deep sequencing (average depth of coverage greater than 4000×) of 576 individuals. Subsequently, 4652 SNPs, including 1108 novel SNPs, were genotyped in 5164 cases and 5716 controls of European ancestry. After adjusting for known risk loci, rs2736100 and rs401681, we identified a new, independent lung cancer susceptibility variant in LPCAT1: rs139852726 (OR = 0.46, P = 4.73×10(-9)), and three new adenocarcinoma risk variants in TERT: rs61748181 (OR = 0.53, P = 2.64×10(-6)), rs112290073 (OR = 1.85, P = 1.27×10(-5)), rs138895564 (OR = 2.16, P = 2.06×10(-5); among young cases, OR = 3.77, P = 8.41×10(-4)). In addition, we found that rs139852726 (P = 1.44×10(-3)) was associated with telomere length in a sample of 922 healthy individuals. The gene-based SKAT-O analysis implicated TERT as the most relevant gene in the 5p15.33 region for adenocarcinoma (P = 7.84×10(-7)) and lung cancer (P = 2.37×10(-5)) risk. In this largest fine-mapping study to investigate a large number of rare and novel variants within 5p15.33, we identified novel lung and adenocarcinoma susceptibility loci with large effects and provided support for the role of telomere length as the potential underlying mechanism.