Lung Cancer Genome-wide Association Studies Research Articles

Integrative Multi-Omics Approach for Improving Causal Gene Identification.

Transcriptome-wide association studies (TWAS) have been widely used to identify thousands of likely causal genes for diseases and complex traits using predicted expression models. However, most existing TWAS methods rely on gene expression alone and overlook other regulatory mechanisms of gene expression, including DNA methylation and splicing, that contribute to the genetic basis of these complex traits and diseases. Here we introduce a multi-omics method that integrates gene expression, DNA methylation, and splicing data to improve the identification of associated genes with our traits of interest. Through simulations and by analyzing genome-wide association study (GWAS) summary statistics for 24 complex traits, we show that our integrated method, which leverages these complementary omics biomarkers, achieves higher statistical power, and improves the accuracy of likely causal gene identification in blood tissues over individual omics methods. Finally, we apply our integrated model to a lung cancer GWAS data set, demonstrating the integrated models improved identification of prioritized genes for lung cancer risk.

High-throughput characterization of functional variants highlights heterogeneity and polygenicity underlying lung cancer susceptibility

Genome-wide association studies (GWASs) have identified numerous lung cancer risk-associated loci. However, decoding molecular mechanisms of these associations is challenging since most of these genetic variants are non-protein-coding with unknown function. Here, we implemented massively parallel reporter assays (MPRAs) to simultaneously measure the allelic transcriptional activity of risk-associated variants. We tested 2,245 variants at 42 loci from 3 recent GWASs in East Asian and European populations in the context of two major lung cancer histological types and exposure to benzo(a)pyrene. This MPRA approach identified one or more variants (median 11 variants) with significant effects on transcriptional activity at 88% of GWAS loci. Multimodal integration of lung-specific epigenomic data demonstrated that 63% of the loci harbored multiple potentially functional variants in linkage disequilibrium. While 22% of the significant variants showed allelic effects in both A549 (adenocarcinoma) and H520 (squamous cell carcinoma) cell lines, a subset of the functional variants displayed a significant cell-type interaction. Transcription factor analyses nominated potential regulators of the functional variants, including those with cell-type-specific expression and those predicted to bind multiple potentially functional variants across the GWAS loci. Linking functional variants to target genes based on four complementary approaches identified candidate susceptibility genes, including those affecting lung cancer cell growth. CRISPR interference of the top functional variant at 20q13.33 validated variant-to-gene connections, including RTEL1, SOX18, and ARFRP1. Our data provide a comprehensive functional analysis of lung cancer GWAS loci and help elucidate the molecular basis of heterogeneity and polygenicity underlying lung cancer susceptibility.

Abstract 7331: Establishing a single-cell eQTL dataset of lung tissues from Asian never-smokers to identify cell-type specific lung cancer susceptibility genes

Abstract Lung cancer is one of the most prevalent and deadly forms of cancer worldwide. Whilst smoking is the main determinant, genetic factors also play a crucial role as genome-wide association studies (GWAS) have identified >50 loci associated with lung cancer risk. Yet, for most of these loci, it is still unknown how they contribute to lung cancer risk. Expression quantitative trait loci (eQTL) studies have been powerful in linking GWAS variants to potential target genes, providing genetic mechanisms underlying common diseases such as cancers. However, the current eQTL resources lack ancestral diversity and are primarily based on bulk tissues. Emerging single-cell eQTL (sc-eQTL) approaches can detect context-specific gene regulation but are mainly of blood samples or cultured cells and still representing European populations. This limits our abilities to test GWAS variants in cancer-relevant cell types as well as in diverse populations. To generate a resource to characterize lung cancer GWAS loci, we are building a lung sc-eQTL dataset of Asian population while addressing common challenges of tissue sc-eQTL. Namely, processing fresh tissue in a population scale is logistically challenging and costly, and epithelial cells (including cell types of lung cancer origin) are vulnerable to the dissociation and freezing/thawing process. To address these issues, we incorporated sample multiplexing and cell type balancing. We collected fresh tumor-distant normal lung tissues from 131 never-smoking Korean women and dissociated them before cryopreservation. We then performed single-cell RNA sequencing (scRNA-seq) using 10x Chromium Single Cell 3’ v3.1 chemistry with multiplexing of ~6 samples/batch. To enrich for epithelial cells, we utilized flow cytometry with surface markers of four major lung cell types (epithelial: EpCAM+/CD45-, immune: EpCAM-/CD45+, endothelial and stromal: EpCAM-/CD45-) before 10X library preparation. Concurrently, we performed DNA genotyping and imputation using matched blood samples. Following scRNA-seq (~36,000 reads/cell) we performed a genotype-based sample demultiplexing using Demuxlet. By integrating Demuxlet and Scrublet, we identified ~89% of the detected cells as singlets. After applying QC to filter empty droplets and low-quality cells, we obtained 428,619 cells or 3,272 cells/patient. Cell annotation guided by Azimuth label transfer using the Human Lung Cell Atlas, identified 28 cell types including 7 of epithelial origins. We will further perform eQTL analyses for individual cell types using pseudo-bulk and LIMIX (linear mixed model) or SAIGE-qtl (poisson regression) methods followed by aggregation across the cell types. By incorporating lung cancer GWAS data, we will identify cell-type specific susceptibility genes. Our dataset will provide a unique resource for lung cancer research. Citation Format: Thong Luong, Erping Long, Jinhu Yin, Bolun Li, Ju Hye Shin, Elelta Sisay, Alexander Kane, Alyxandra Golden, Yoon Soo Chang, Nicholas Banovich, Nathaniel Rothman, Jinyoung Byun, Qing Lan, Christopher Amos, Jianxin Shi, Jin Gu Lee, Eun Young Kim, Jiyeon Choi. Establishing a single-cell eQTL dataset of lung tissues from Asian never-smokers to identify cell-type specific lung cancer susceptibility genes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7331.

Abstract 7327: Investigating the cell-type specific regulation of IRF4 and its role in lung cancer via a lung cancer risk-associated pleiotropic variant

Abstract Although smoking is a main risk factor for lung cancer, genetic factors also contribute to the risk, as shown by over 50 genomic loci identified by genome-wide association studies (GWAS). A recent cross-ancestry lung cancer GWAS identified a common germline variant, rs12203592 (C/T), in chr6p25.3 as a new signal, and quantitative trait loci (eQTL) colocalization analysis using lung and blood tissues (GTEx v8) identified IRF4 as a likely target of rs12203592. rs12203592 has previously been linked with diverse traits, including pigmentation phenotypes, smoking cessation, lymphoblastic leukemia, melanoma, and other skin cancers. rs12203592 also appears to have varied allelic effects in different cell types. Namely, the lung cancer risk-associated T allele is correlated with higher IRF4 expression in lung tissue and blood cells (GTEx v8) but lower expression in primary melanocytes (n = 106; Zhang et al). Since previous studies established the melanocyte-specific allelic function of this SNP through lineage-specific transcription factors (TFs), we hypothesized that cell-type-specific TFs mediate the observed allelic effect in different tissue/cell types and further contribute to the unique role of IRF4 in lung tumorigenesis. To identify these potential cell-type-specific regulators, we performed mass spectrometry using the nuclear extracts from three cell lines representing lung, blood, and melanocyte lineage. The results nominated the NF-kB and ZEB protein families as the most prominent T-specific binders in the A549 lung cancer cell line, which was validated by electromobility shift assays. Consistent with these findings, tissue-based SNP-gene interaction analysis demonstrated that the mRNA levels of NF-kB and ZEB family members (4 of 7 genes) were correlated with IRF4 expression with a significant interaction with rs12203592 in GTEx lung tissue (P < 0.017), where the correlation is mainly observed with the T allele. Notably, the SNP interaction was less pronounced in whole blood or melanocytes, and the correlation of these TFs and IRF4 expression was mainly observed with the C allele in melanocytes. To begin to establish the roles of these TFs and IRF4 in lung tumorigenesis and given that IRF4 was shown to promote endogenous DNA damage and proliferation of lung-lineage cell lines, we will investigate the roles of NF-kB and ZEB in IRF4 regulation in these contexts using knockdown and overexpression of these TFs. To further investigate lung cancer-specific IRF4 function, we will identify potential targets of IRF4 among lung cancer-associated functional variants established through our previous studies. This data will help elucidate the context-specific roles of IRF4 in lung cancer development and provide clues to gene regulation in a pleiotropic GWAS locus. Citation Format: Alexander Kane, Jinhu Yin, Erping Long, James Feng, Cathrin Gräwe, Harsh Patel, Jinyoung Byun, Christopher Amos, Kevin Brown, Jun Xia, Michiel Vermeulen, Jiyeon Choi. Investigating the cell-type specific regulation of IRF4 and its role in lung cancer via a lung cancer risk-associated pleiotropic variant [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7327.

Germline variants of the genes involved in NF-kB activation are associated with the risk of COPD and lung cancer development.

Chronic obstructive pulmonary disease (COPD) and lung cancer (LC) are closely related diseases associated with smoking history and dysregulated immune response. However, not all smokers develop the disease, indicating that genetic susceptibility could be important. Therefore, the aim of this study was to search for the potential overlapping genetic biomarkers, with a focus on single nucleotide polymorphisms (SNPs) located in the regulatory regions of immune-related genes. Additionally, the aim was to see if an identified SNP has potentially an effect on proinflamma-tory cytokine concentration in the serum of COPD patients. We extracted summary data of variants in 1511 immune-related genes from COPD and LC genome-wide association studies (GWAS) from the UK Biobank. The LC data had 203 cases, patients diagnosed with LC, and 360 938 controls, while COPD data had 1 897 cases and 359 297 controls. Assuming 1 association/gene, SNPs with a p-value < 3.3 × 10-5 were considered statistically significantly associated with the disease. We identified seven SNPs located in different genes (BAG6, BTNL2, TNF, HCP5, MICB, NCR3, ABCF1, TCF7L1) to be associated with the COPD risk and two with the LC risk (HLA-C, HLA-B), with statistical significance. We also identified two SNPs located in the IL2RA gene associated with LC (rs2386841; p = 1.86 × 10-4) and COPD (rs11256442; p = 9.79 × 10-3) but with lower significance. Functional studies conducted on COPD patients showed that RNA expression of IL2RA, IFNγ and related proinflammatory cytokines in blood serum did not correlate with a specific genotype. Although results presented in this study do not fully support our hypothesis, it is worth to mention that the identified genes/SNPs that were associated with either COPD or LC risk, all were involved in the activation of the NF-κB transcription factor which is closely related to the regulation of the inflammatory response, a condition associated with both pathologies.

Abstract 5218: Genome-wide association study of African Americans reveals new susceptibility loci contributing to lung cancer and mechanisms of population-specific etiology

Abstract Lung cancer incidence and mortality in the U.S. have substantial ethnic disparities. African Americans of both sexes have the high incidence rate at 56.8 and the highest death rate at 38.1 per 100,000 people from 2015 to 2019. Non-Hispanic black men have the highest incidence at 73.9 and the highest death rate at 56.3 per 100,000 people. While many genome-wide association studies (GWAS) of lung cancer have discovered ~45 putative risk loci, a large proportion of the heritability of lung cancer remains unexplained. To date, most single population-based GWAS have been performed in Europeans while there are a few Asian ancestry-specific genetic studies and two cross-ancestry studies. Non-European GWAS of lung cancer has been underrepresented. Although African Americans have higher lung cancer incidence and poorer lung cancer survival rate, and smoke fewer cigarettes per day compared to Europeans, few comprehensive GWAS of lung cancer in African Americans has been conducted. This study aims to decipher the genetic component of predisposition to lung cancer among African Americans. This study aims to decipher the genetic component of predisposition to lung cancer among African Americans. We conducted an African-ancestry GWAS comprising 2,280 lung cancer cases and 4,301 controls to comprehensively characterize common and low-frequency lung cancer genetic susceptibility loci using HRC imputed lung cancer data. The novel variants in or near VWF on 12p13.31 (OR=1.29, P=6.93 × 10−9) for overall lung cancer and GACAT3 on 2p24.3 (0.65, 1.24 × 10−9), TRIP13 on 5p15.33 (3.49, 1.00 × 10−8), ERC1 on 12p13.33 (4.64, 6.08 × 10−9), LMAN1L (near CYP1A1) on 15q24.1 (4.25, 8.71 × 10−9) for lung squamous cell cancer were identified at a genome-wide significance level. Our GWAS of lung cancer identified five novel genetic susceptibility associations and confirmed several variants on 15q25 and 19q13. Further works are required to elucidate the possible biological mechanisms underlying these associations among lung cancer and histological subtypes in African Americans. Citation Format: Jinyoung Byun, Younghun Han, Xiangjun Xiao, Christine Lusk, Hoda J. Badr, Rayjean Hung, Ann G. Schwartz, Christopher I. Amos, INTEGRAL Consortium. Genome-wide association study of African Americans reveals new susceptibility loci contributing to lung cancer and mechanisms of population-specific etiology. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5218.

A Functional Polymorphism in Accessible Chromatin Region Confers Risk of Non-Small Cell Lung Cancer in Chinese Population.

BackgroundThe disease-associated non-coding variants identified by genome-wide association studies (GWASs) were enriched in open chromatin regions (OCRs) and implicated in gene regulation. Genetic variants in OCRs thus may exert regulatory functions and contribute to non-small cell lung cancer (NSCLC) susceptibility.ObjectiveTo fine map potential functional variants in GWAS loci that contribute to NSCLC predisposition using chromatin accessibility and histone modification data and explore their functions by population study and biochemical experimental analyses.MethodsWe mapped the chromatin accessible regions of lung tissues using data of assay for transposase-accessible chromatin using sequencing (ATAC-seq) in The Cancer Genome Atlas (TCGA) and prioritized potential regulatory variants within lung cancer GWAS loci by aligning with histone signatures using data of chromatin immunoprecipitation assays followed by sequencing (ChIP-seq) in the Encyclopedia of DNA Elements (ENCODE). A two-stage case–control study with 1,830 cases and 2,001 controls was conducted to explore the associations between candidate variants and NSCLC risk in Chinese population. Bioinformatic annotations and biochemical experiments were performed to further reveal the potential functions of significant variants.ResultsSixteen potential functional single-nucleotide polymorphisms (SNPs) were selected as candidates from bioinformatics analyses. Three variants out of the 16 candidate SNPs survived after genotyping in stage 1 case–control study, and only the results of SNP rs13064999 were successfully validated in the analyses of stage 2 case–control study. In combined analyses, rs13064999 was significantly associated with NSCLC risk [additive model; odds ratio (OR) = 1.17; 95%CI, 1.07–1.29; p = 0.001]. Functional annotations indicated its potential enhancer bioactivity, and dual-luciferase reporter assays revealed a significant increase in luciferase activity for the reconstructed plasmid with rs13064999 A allele, when compared to the one with wild-type G allele (pA549 < 0.001, pSK-MES-1 = 0.004). Further electrophoretic mobility shift assays (EMSA) and super-shift assays confirmed a stronger affinity of HP1γ for the binding motif containing SNP rs13064999 A allele.ConclusionThese findings suggested that the functional variant rs13064999, identified by the integration of ATAC-seq and ChIP-seq data, contributes to the susceptibility of NSCLC by affecting HP1γ binding, while the exact biological mechanism awaits further exploration.

Cannabis Use, Pulmonary Function, and Lung Cancer Susceptibility: A Mendelian Randomization Study

IntroductionBecause of widespread use, understanding the pulmonary effects of cannabis use is important; but its role independent from tobacco smoking is yet to be elucidated. We used Mendelian randomization (MR) to assess the effect of genetic liability to lifetime cannabis use and cannabis use disorder on pulmonary function and lung cancer. MethodsWe used four single nucleotide polymorphisms associated with lifetime cannabis use (p value <5 × 10−8) from a genome-wide association study (GWAS) of 184,765 individuals of European descent from the International Cannabis Consortium, 23andme, and U.K. Biobank as instrumental variables. Seven single nucleotide polymorphisms (p value <5 × 10−8) were selected as instruments for cannabis use disorder from a GWAS meta-analysis of 17,068 European ancestry cases and 357,219 controls of European descent from Psychiatric Genomics Consortium Substance Use Disorders working group, Lundbeck Foundation Initiative for Integrative PsychiatricResearch, and deCode. To assess lung function, GWAS included 79,055 study participants of the SpiroMeta Consortium, and for lung cancer GWAS from the International Lung Cancer Consortium contained 29,266 cases and 56,450 controls. ResultsMR revealed that genetic liability to lifetime cannabis use was associated with increased risk of squamous cell carcinoma (OR = 1.22, 95%, confidence interval = 1.07–1.39, p value = 0.003, q value = 0.025). Pleiotropy-robust methods and positive and negative control analyses did not indicate bias in the primary analysis. ConclusionsThe findings of this MR analysis suggest evidence for a potential causal association between genetic liability for cannabis use and the risk of squamous cell carcinoma. Triangulating MR and observational studies and addressing orthogonal sources of bias are necessary to confirm this finding.

Abstract 3532: Post-GWAS in lung cancer: From transcriptome-wide association to the DNA damageome by Integrative functional screens

Abstract We recently finished the largest transcriptome-wide association study (TWAS) analysis of the lung cancer genome-wide association studies (GWAS)-nominated loci, which revealed 18 new candidate causal genes for lung cancer. The recent discovery of the DNA damageome proteins (DDPs) predicts that many GWAS/TWAS genes are driving cancer by DNA damage-promoting mechanisms. Here, we have screened all 18 candidates and validated the DDP activities for at least five of these genes. We also developed a series of single-cell assays to profile cancer-relevant properties and assign their cancer-driving roles to genome instability. Last, we have demonstrated a reactive oxygen species (ROS)-dependent role of AQP3 overproduction-induced DNA damage, a pan-cancer mechanism. Methods: We measured endogenous DNA damage levels for all TWAS-nominated candidates using high-throughput single cell-based flow cytometric assays. Additional high-throughput single-cell assays were developed to quantify reactive oxygen species, replication fork stalling, and other DNA-related cancer properties, which allowed us to rapidly harvest functional information. Results: We screened 18 lung cancer TWAS-nominated genes for DNA damage in a lung cell line, and five showed increased DNA damage, including recently confirmed AQP3 overproduction, IREB2 knockdown, newly identified RNASET2 overproduction, TRIM38 knockdown, and JAML knockdown cells. None of these genes has been previously reported to be associated with DNA damage, prioritizing these lung cancer genes for further genome-destabilizing mechanistic studies. AQP3 overproduction promotes DNA damage in a variety of cell lines with different tissues of origin, including lung, kidney, and colon, supporting the hypothesis that DNA damage induced by AQP3 overproduction is universal. Moreover, we have shown that AQP3 overproduction causes high ROS at a level higher than 2mM H2O2 treatment, and ROS quencher N-acetyl-l-cysteine (NAC) can reduce AQP3 overproduction-induced DNA damage, supporting the conclusion that AQP3 overproduction induces ROS-dependent DNA damage. Furthermore, additional functional dissections revealed a high replication fork-stalling phenotype for a previously uncharacterized lung cancer risk protein, KIAA0930, providing the first-ever functional annotation of this uncharacterized protein. Conclusions: We established a high-throughput functional validation platform that measures endogenous DNA damage and other cancer genome-related properties for lung cancer susceptibility genes. More importantly, the strategy for predicting DNA damageome genes and the functional validation platform are transferable to other cancers. Citation Format: Jun Xia, Zhuoyi Song, Chris Amos. Post-GWAS in lung cancer: From transcriptome-wide association to the DNA damageome by Integrative functional screens [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3532.

Cross-Cancer Pleiotropic Analysis Reveals Novel Susceptibility Loci for Lung Cancer.

Genome-wide association studies (GWASs) have identified hundreds of single nucleotide polymorphisms (SNPs) associated with cancer risk, several of which have shown pleiotropic effects across cancers. Therefore, we performed a systematic cross-cancer pleiotropic analysis to detect the effects of GWAS-identified variants from non-lung cancers on lung cancer risk in 12,843 cases and 12,639 controls from four lung cancer GWASs. The overall association between variants in each cancer and risk of lung cancer was explored using sequential kernel association test (SKAT) analysis. For single variant analysis, we combined the result of specific study using fixed-effect meta-analysis. We performed functional exploration of significant associations based on features from public databases. To further detect the biological mechanism underlying identified observations, pathway enrichment analysis were conducted with R package “clusterProfiler.” SNP-set analysis revealed the overall associations between variants of 8 cancer types and lung cancer risk. Single variant analysis identified 6 novel SNPs related to lung cancer risk after multiple correction (Pfdr < 0.10), including rs1707302 (1p34.1, OR = 0.93, 95% CI: 0.90–0.97, P = 7.60 × 10−4), rs2516448 (6p21.33, OR = 1.07, 95% CI: 1.03–1.11, P = 1.00 × 10−3), rs3869062 (6p22.1, OR = 0.91, 95% CI: 0.86–0.96, P = 7.10 × 10−4), rs174549 (11q12.2, OR = 0.90, 95% CI: 0.87–0.94, P = 1.00 × 10−7), rs7193541 (16q23.1, OR = 0.93, 95% CI: 0.90–0.96, P = 1.20 × 10−4), and rs8064454 (17q12, OR = 1.07, 95% CI: 1.03–1.11, P = 4.30 × 10−4). The eQTL analysis and functional annotation suggested that these variants might modify lung cancer susceptibility through regulating the expression of related genes. Pathway enrichment analysis showed that genes modulated by these variants play important roles in cancer carcinogenesis. Our findings demonstrate the pleiotropic associations between non-lung cancer susceptibility loci and lung cancer risk, providing important insights into the shared mechanisms of carcinogenesis across cancers.

Systematic analysis of genetic variants in cancer-testis genes identified two novel lung cancer susceptibility loci in Chinese population.

Cancer-testis (CT) genes played important roles in the progression of malignant tumors and were recognized as promising therapeutic targets. However, the roles of genetic variants in CT genes in lung cancer susceptibility have not been well depicted. This study aimed to evaluate the associations between genetic variants in CT genes and lung cancer risk in Chinese population. A total of 22,556 qualified SNPs from 268 lung cancer associated CT genes were initially evaluated based on our previous lung cancer GWAS (Genome-wide association studies) with 2,331 cases and 3,077 controls. As a result, 17 candidate SNPs were further genotyped in 1,056 cases and 1,053 controls using Sequenom platform. Two variants (rs6941653, OPRM1, T > C, screening: OR = 1.24, 95%CI: 1.12-1.38, P = 2.40×10-5; validation: OR = 1.18, 95%CI: 1.01-1.37, P = 0.039 and rs402969, NLRP8, C > T, screening: OR = 1.15, 95%CI: 1.04-1.26, P = 0.006; validation: OR = 1.16, 95%CI: 1.02-1.33, P = 0.028) were identified as novel lung cancer susceptibility variants. Stratification analysis indicated that the effect of rs6941653 was stronger in lung squamous cell carcinoma (OR = 1.36) than that in lung adenocarcinoma (OR = 1.15, I2 = 77%, P = 0.04). Finally, functional annotations, differential gene expression analysis, pathway and gene ontology analyses were performed to suggest the potential functions of our identified variants and genes. In conclusion, this study identified two novel lung cancer risk variants in Chinese population and provided deeper insight into the roles of CT genes in lung tumorigenesis.

COPD-dependent effects of genetic variation in key inflammation pathway genes on lung cancer risk.

Genome-wide association studies (GWAS) have identified several loci contributing to lung cancer and COPD risk independently; however, inflammation-related pathways likely harbor additional lung cancer risk-associated variants in biologically relevant immune genes that differ dependent on COPD. We selected single nucleotide polymorphisms (SNPs) proximal to 2,069 genes within 48 immune pathways. We modeled the contribution of these variants to lung cancer risk in a discovery sample of 1,932 lung cancer cases and controls stratified by COPD status and validation sample of 953 cases and controls also stratified by COPD. There were 43 validated SNPs in those with COPD and 60 SNPs in those without COPD associated with lung cancer risk. Furthermore, 29 of 43 and 28 of 60 SNPs demonstrated a statistically significant interaction with COPD in the pooled sample. These variants demonstrated tissue-dependent effects on proximal gene expression, enhanced network connectivity and resided together in specific immune pathways. These results reveal that key inflammatory related genes and pathways, not found in prior GWAS, impact lung cancer risk in a COPD-dependent manner. Genetic variation identified in our study supplements prior lung cancer GWAS and serves as a foundation to further interrogate risk relationships in smoking and COPD populations.

Integrating germline and somatic genetics to identify genes associated with lung cancer.

Genome-wide association studies (GWAS) have successfully identified many genetic variants associated with complex traits. However, GWAS experience power issues, resulting in the failure to detect certain associated variants. Additionally, GWAS are often unable to parse the biological mechanisms of driving associations. An existing gene-based association test framework, Transcriptome-Wide Association Studies (TWAS), leverages expression quantitative trait loci data to increase the power of association tests and illuminate the biological mechanisms by which genetic variants modulate complex traits. We extend the TWAS methodology to incorporate somatic information from tumors. By integrating germline and somatic data we are able to leverage information from the nuanced somatic landscape of tumors. Thus we can augment the power of TWAS-type tests to detect germline genetic variants associated with cancer phenotypes. We use somatic and germline data on lung adenocarcinomas from The Cancer Genome Atlas in conjunction with a meta-analyzed lung cancer GWAS to identify novel genes associated with lung cancer.

Abstract 1572: Inherited truncating RAD52 variant discovered using integrated germline- somatic analysis predicts clinical outcome in patients with lung cancers

Abstract Most of the heritability of lung cancer, estimated at 18% in population studies, remains unexplained. We employed a framework for variant interpretation utilizing integrated germline and somatic data.The lung cancer patients(pts) enrolled between 01/2014 and 05/2016 underwent sequencing analysis for 468 genes using MSK IMPACT with pathogenicity assessment performed using ACMG guidelines. Loss of heterozygosity (LOH) in tumor was inferred using the FACETS algorithm. A poorly characterized truncating variant was classified as “potential pathogenic variant” if we observed LOH of the relevant allele in the tumor and the gene was previously reported co-segregating in family studies or significant in genome wide association studies (GWAS). Frequencies of pathogenic germline variants were compared to population frequencies in the genome aggregation database (gnomAD).As per IRB protocol, germline results were anonymized for all cases. 2686 pts consented to tumor-normal sequencing of whom, 80% had lung adenocarcinoma, 10% squamous cell carcinoma and 5% small cell lung cancer diagnosis. We discovered a new truncating RAD52 p.Ser346Ter variant in 89 (3.3%) lung cancer patients; 47(53%) patients had LOH in tumor (23 pts with wild type allele loss and 24 patients with mutant allele loss). Previous lung cancer GWAS had reported common variants at the RAD52 locus as lung cancer susceptibility loci. The identified RAD52 truncating mutation may represent the functional variant within the risk haplotype. Clinico-pathological association with the RAD52 variant suggested that the mutation was more common in patients who had &amp;lt;5 pack years of smoking history (5% in non-smokers versus 2.8% in smokers; OR=1.8, 95%CI=1-3.2,p-value=0.03), more commonly associated with EGFR oncogenic mutations (5.4% vs 2.8%; p-value=0.01) or MYC amplification (8.3% vs 3%; p=0.001) and had a poorer prognosis compared to patients without the variant (adjusted for smoking status; HR=1.5, 95%CI=1-2.4,p-value=0.04). We also identified 237 (8.8%) pts harboring pathogen germline variants in 28 cancer predisposition genes based on ACMG criteria, including 3 DNA repair genes significantly enriched in lung cancer cases compared to gnomAD controls; BRCA2 (OR=2, 95% CI= 1.3- 4.9), TP53 (OR=10.7, 95% CI=2.9-32.7)and NBN (OR= 9.6; 95% CI= 3-26.1) . Notably, 4/5 (80%) TP53variants and 9 /19 (47%) BRCA2 variants showed loss of heterozygosity (LOH) of the wild-type allele in tumor. In conclusion, we discovered a novel truncating RAD52 variant associated with clinical characteristics and poor prognosis, supporting the biological role of pathogenic mutations in DNA repair genes, including BRCA2, in the pathogenesis of a subset of hereditary lung tumors. These data warrant follow-up to refine the scope of germline genetic testing for lung cancer patients. Citation Format: Semanti Mukherjee, Preethi Srinivasan, Chaitanya Bandlamudi, Matthew D. Hellmann, Vignesh Ravichandran, Myvizhi Esai Selvan, Yelena Kemel, Diana Mandelker, Marjorie Zauderer, Michael Walsh, Ahmet Zehir, Maria I Carlo, Karen Cadoo, Steven M Lipkin, Marc Ladanyi, David Solit, Mark Robson, Liying Zhang, David Jones, Charles Rudin, Robert Klein, Zsofia Stadler, Joseph Vijai, Zeynep Gumus, Barry Taylor, Michael Berger, Kenneth Kenneth. Inherited truncating RAD52 variant discovered using integrated germline- somatic analysis predicts clinical outcome in patients with lung cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1572.

Fine Mapping in Chromosome 3q28 Identified Two Variants Associated with Lung Cancer Risk in Asian Population.

Genome-wide association studies (GWASs) have consistently identified chromosome 3q28 as a lung cancer susceptibility region. To further characterize the potential genetic mechanism of the variants in this region, we conducted a fine-mapping study on chromosome 3q28 region. We performed a target resequencing in 200 lung cancer cases and 300 controls in the screening and followed by validation in multi-ethnic lung cancer GWASs with 12,843 cases and 12,639 controls. For our identified novel variants, we conducted expression quantitative trait loci (eQTL) analysis to reveal the potential target genes. Two susceptibility variants were identified (rs4396880: G>A, OR = 0.35, 95%CI: 0.20-0.62, P = 3.01×10-4; and rs3856776: C>T, OR = 2.05, 95%CI: 1.32-3.18, P = 1.49×10-3) and further supported in Asian population (rs4396880: OR = 0.88, P = 7.43×10-6; and rs3856776: OR =1.17, P = 1.64×10-4). The eQTL analysis showed the A allele of rs4396880 was significantly associated with higher mRNA expression of TP63 (P = 1.70×10-4) in lung tissues, while rs3856776 showed significant association with the expression of LEPREL1-AS1 (P = 6.90×10-3), which was the antisense RNA of LEPREL1 and could suppress the translation of LEPREL1. Notably, LEPREL1 was aberrantly downregulated (P = 2.54×10-18) in lung tumor tissues based on TCGA database. In conclusion, this is the first fine-mapping analysis of 3q28 region in Han Chinese, and we found two variants associated with lung cancer susceptibility in Asian population. What's more, rs3856776 was newly identified and might modulate lung cancer susceptibility by suppressing the function of LEPREL1.

The Relationship Between Population Attributable Fraction and Heritability in Genetic Studies

Population attributable fraction (PAF) has been widely used to quantify the proportion of disease risk in a population that can be attributed to risk factors in epidemiological studies. However, the use of PAF has been limited in assessing the contribution of genetic variants. Most notably, the PAF estimate is typically much larger than other commonly used measures, such as heritability, thereby raising the concern that PAF may overestimate the genetic contribution. In this paper, we show that PAF is a one-to-one function of heritability, and explain why PAF is larger than heritability. Further, we present an estimation procedure based on the summary statistics from genome-wide association studies (GWAS) to estimate the PAF of multiple correlated genetic variants for a binary outcome. Currently available estimation procedures only apply to a single variant or to multiple genetic variants that are independent from each other. Our simulation studies verified the relationship between PAF and heritability, and showed that the proposed estimation procedure for these two measures performed well. Finally, we applied the proposed method to the published data of two lung cancer GWAS to estimate the PAF and heritability of several newly identified variants. Our results demonstrate that the PAF estimate is a useful measure of the genetic contribution to the development of the disease. We hope this paper serves as an advocate for a wider use of PAF in genetic studies.

Fine mapping in TERT-CLPTM1L region identified three independent lung cancer susceptibility signals: A large-scale multi-ethnic population study.

Genome-wide association studies (GWAS) and fine mapping studies have identified multiple lung cancer susceptibility variants in TERT-CLPTM1L region. However, it is still unclear about the relationship between these risk variants and the independent lung cancer risk signals in this region. Therefore, we evaluated the independent susceptibility signals for lung cancer and explored the potential functional variants in this region. Sequential conditional analysis was used to detect the independent susceptibility loci based on four lung cancer GWAS datasets with 12 843 lung cases and 12 639 controls. Comprehensively functional annotations were performed for each independent signal. Three independent susceptibility signals were identified in multi-ethnic population. For the first signal, rs2736100 showed the most significant association with lung cancer risk (C > A, OR = 0.82, 95%CI: 0.79-0.85, P = 1.98 × 10-25 ). Rs36019446 was the top-ranked site (A > G, OR = 0.88, 95%CI: 0.84-0.92, P = 1.74 × 10-9 ) in the second signal. For the third signal, rs326048 was the leading SNP (A > G, OR = 0.91, 95%CI: 0.87-0.95, P = 1.38 × 10-5 ). The following subgroup analysis found the same three loci among Asian population. Further, we compared the difference between various subgroup populations. Functional annotations revealed that rs2736100, rs27996 (r2 = 0.85 with rs36019446) and rs326049 (r2 = 0.73 with rs326048) could be potential functional variants in these three risk signals, respectively. In conclusion, although multiple variants have been found associated with lung cancer risk in TERT-CLPTM1L region, our findings indicated that there are three independent lung cancer susceptibility signals in this region.

Integrating expression-related SNPs into genome-wide gene- and pathway-based analyses identified novel lung cancer susceptibility genes.

Traditional pathway analysis map single nucleotide polymorphisms (SNPs) to genes according to physical position, which lacks sufficient biological bases. Here, we incorporated genetics of gene expression into gene- and pathway-based analysis to identify genes and pathways associated with lung cancer risk. We identified expression-related SNPs (eSNPs) in lung tissues and integrated these eSNPs into three lung cancer genome-wide association studies (GWASs), including 12,843 lung cancer cases and 12,639 controls. We used SKAT-C for gene-based analysis, and conditional analysis to identify independent eSNPs of each gene. ARTP algorithm was used for pathway analysis. A total of 374,382 eSNPs in the GWAS datasets survived quality control, which were mapped to 5,084 genes and 2,752 pathways. In the gene-based analysis, nine genes showed significant associations with lung cancer risk. Among them, TP63 (3q28), RP11-650L12.2 (15q25.1) and CHRNA5 (15q25.1) were located in known lung cancer susceptibility loci. We also validated two newly identified susceptibility loci (RNASET2 and AL133458.1 in 6q27, and MPZL3 in 11q23.3). Besides, DVL3 (3q27.1), RP11-522I20.3 (9q21.32) and CCDC116 (22q11.21) were identified as novel lung cancer susceptibility genes. Pathway analysis showed that pathways involved in protein structure, the Notch signaling pathway and the nicotinic acetylcholine receptor-related pathways were associated with lung cancer risk. Combing eSNPs, gene- and pathway-based analysis identifies novel lung cancer susceptibility genes, which serves as a powerful approach to decipher biological mechanisms underlying GWAS findings.

Using imputed genotype data in the joint score tests for genetic association and gene-environment interactions in case-control studies.

Genome-wide association studies (GWAS) are now routinely imputed for untyped single nucleotide polymorphisms (SNPs) based on various powerful statistical algorithms for imputation trained on reference datasets. The use of predicted allele counts for imputed SNPs as the dosage variable is known to produce valid score test for genetic association. In this paper, we investigate how to best handle imputed SNPs in various modern complex tests for genetic associations incorporating gene-environment interactions. We focus on case-control association studies where inference for an underlying logistic regression model can be performed using alternative methods that rely on varying degree on an assumption of gene-environment independence in the underlying population. As increasingly large-scale GWAS are being performed through consortia effort where it is preferable to share only summary-level information across studies, we also describe simple mechanisms for implementing score tests based on standard meta-analysis of "one-step" maximum-likelihood estimates across studies. Applications of the methods in simulation studies and a dataset from GWAS of lung cancer illustrate ability of the proposed methods to maintain type-I error rates for the underlying testing procedures. For analysis of imputed SNPs, similar to typed SNPs, the retrospective methods can lead to considerable efficiency gain for modeling of gene-environment interactions under the assumption of gene-environment independence. Methods are made available for public use through CGEN R software package.

Polymorphisms in genes related to epithelial-mesenchymal transition and risk of non-small cell lung cancer.

The epithelial-mesenchymal transition (EMT) process is a crucial step for tumor invasion and metastasis. Previous research investigating EMT has mostly focused on its role in cancer progression. Recent studies showed that EMT and EMT-driving transcription factor (EMT-TF) expression are early events in lung cancer pathogenesis, implying a potential association between EMT and lung cancer risk. In this study, we examined whether genetic variants in EMT-related genes are associated with risk of non-small cell lung cancer (NSCLC). We used data from a genome-wide association study of 1482 NSCLC cases and 1544 healthy controls as the discovery phase, in which we analyzed 1602 single-nucleotide polymorphisms (SNPs) within 159 EMT-related genes. We then validated the significant SNPs in another 5699 cases and 5815 controls from the National Cancer Institute lung cancer genome-wide association study. Cumulative effects were evaluated for validated SNPs, and a gene-based test was performed to explore gene-level association with disease risk. In the discovery phase, 174 SNPs demonstrated significant associations with NSCLC risk. In the validation phase, seven SNPs mapped to EGFR, NOTCH3, ADGRF1 and SMAD3 were confirmed. Cumulative effect analysis of the significant SNPs demonstrated increasing risk with the number of unfavorable genotypes in the discovery and validation datasets. Gene-based analysis implicated ADGRF1, NOTCH3 and CDH1 as significant for NSCLC risk. Functional prediction revealed several potential mechanisms underlying these associations. Our results suggest that EMT-related gene variants may be involved in susceptibility to NSCLC; if confirmed, they might help identify higher-risk individuals.