Cancer Genome-wide Association Studies Research Articles

Identification of Genetic Factors Related With Nonhereditary Colorectal Polyposis and Its Recurrence Through Genome-Wide Association Study.

Many patients with colorectal polyposis demonstrate negative results in germline mutation test. This study aimed to uncover genetic variants associated with nonhereditary colorectal polyposis using a genome-wide association study (GWAS). At a single referral university hospital, between January 2012 and September 2021, 638 patients with ≥ 10 biopsy-proven cumulative polyps on colonoscopy without germline mutations related to hereditary colorectal cancer or polyposis were included. The control group comprised 1863 individuals from the Korea Medical Institute, each having undergone at least two colonoscopies, all of which were normal. This study utilized GWAS to identify susceptibility loci for nonhereditary colorectal polyposis. Genetic differences between patients with and without ≥ 10 polyp recurrences were analyzed using Cox proportional hazards models. GWAS revealed 71 novel risk single-nucleotide polymorphisms (SNPs) not seen in previous colorectal cancer and polyp GWAS. Five genes (UPF3A, BICRA, CBWD6, PDE4DIP, and ABCC4) overlapping seven SNPs (rs566295755, rs2770288, rs1012003, rs201270202, rs71264659, rs1699813, and rs149368557), previously linked to colorectal cancer, were identified as significant risk factors for nonhereditary colorectal polyposis. Two novel genes (CNTN4 and CNTNAP3B), not previously associated with colorectal diseases, were identified. Three SNPs (rs149368557, rs12438834, and rs9707935) were significantly associated with higher risk of recurrence of polyposis. The gene overlapping with rs149368557 was ABCC4, which was also significantly associated with an increased risk of nonhereditary colorectal polyposis. This study identified 71 novel risk variants for nonhereditary colorectal polyposis, with three SNPs (rs149368557, rs12438834, and rs9707935) indicating significant associations with increased risk of polyposis recurrence.

Leveraging genome-wide association studies to better understand the etiology of cancers.

Genome-wide association studies (GWAS) statistically assess the association between tens of millions of genetic variants in the whole genome and a phenotype of interest. Genome-wide association studies enable the elucidation of polygenic inheritance of cancer, in which myriad low-penetrance genetic variants collectively contribute to a substantial proportion of the heritable susceptibility. In addition to the robust genotype-phenotype associations provided by GWAS, combining GWAS data with functional genomic datasets or sophisticated statistical genetic methods unlocks deeper insights. Integrating genotype and molecular phenotyping data facilitates functional characterization of GWAS association signals through molecular quantitative trait loci mapping and transcriptome-wide association studies. Furthermore, aggregating genome-wide polygenic signals, including subthreshold associations, enables one to estimate genetic correlations across diverse phenotypes and helps in clinical risk predictions by evaluating polygenic risk scores. In this review, we begin by summarizing the rationale for GWAS of cancer, introduce recent methodological updates in the GWAS-derived downstream analyses, and demonstrate their applications to GWAS of cancers.

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.

Genetically predicted 486 blood metabolites in relation to risk of esophageal cancer: a Mendelian randomization study.

Enhancing therapy choices for varying stages of esophageal cancer and improving patient survival depend on timely and precise diagnosis. Blood metabolites may play a role in either causing or preventing esophageal cancer, but further research is needed to determine whether blood metabolites constitute a genetic risk factor for the disease. In order to tackle these problems, we evaluated the causal association between esophageal cancer and 486 blood metabolites that functioned as genetic proxies using a two-sample Mendelian randomization (MR) study. We utilized two-sample MR analyses to evaluate the causal links between blood metabolites and esophageal cancer. For the exposure, we used a genome-wide association study (GWAS) of 486 metabolites, and a GWAS study on esophageal cancer from Sakaue et al. was used for preliminary analyses. Causal analyses employed randomized inverse variance weighted (IVW) as the main method, supplemented by MR-Egger and weighted median (WM) analyses. Sensitivity analyses included the MR-Egger intercept test, Cochran Q test, MR-PRESSO, and leave-one-out analysis. Additionally, independent esophageal cancer GWAS data were utilized for replication and meta-analysis. FDR correction was applied to discern features with causal relationships. For conclusive metabolite identification, we conducted Steiger tests, linkage disequilibrium score regression, and colocalization analyses. Moreover, we utilized the program MetaboAnalyst 5.0 to analyze metabolic pathways. This study found an important association between esophageal cancer and three metabolites: 1-linoleoylglycerophosphoethanolamine* [odds ratio (OR) = 3.21, 95% confidence interval (CI): 1.42-7.26, p < 0.01], pyroglutamine* (OR = 1.92, 95% CI: 1.17-3.17, p < 0.01), and laurate (12:0) (OR = 3.06, 95% CI: 1.38-6.78, p < 0.01). This study establishes a causal link between three defined blood metabolites and esophageal cancer, offering fresh insights into its pathogenesis.

Causal relationship between circulating immune cells and gastric cancer: a bidirectional Mendelian randomization analysis using UK Biobank and FinnGen datasets.

The role of immune cells in cancer pathogenesis remains controversial due to conflicting reports, potentially arising from various confounding factors. Emerging evidence suggests that cancer can also influence immune cell populations and functions, making it challenging to investigate their causal relationship. Traditional observational studies often fail to eliminate all confounding factors and are prone to reverse causality. Therefore, we employ Mendelian randomization (MR) to determine the causal relationship between immune cells and cancer, as this method can identify causal relationships independent of confounding factors and avoid reverse causality. Genome-wide association study (GWAS) summary statistics on immune traits, encompassing 310 immune cell phenotypes, were obtained from 3,757 European individuals, with peripheral blood immune cells tested using flow cytometry. GWAS summary statistics for gastric cancer were derived from 476,116 European individuals across two large-scale biobanks: the UK Biobank and FinnGen. Gastric cancer was identified by the International Classification of Diseases, 9th Revision (ICD-9), and 10th Revision (ICD-10) codes. Significant single nucleotide polymorphisms (SNPs) for immune traits were extracted at a threshold of P<1×10-5, while a threshold of P<5×10-8 was used for gastric cancer GWAS data. Linkage imbalance-based clumping was performed to obtain independent SNPs, and those with F<10 were excluded to mitigate weak instrument bias. Phenoscanner V2 was used to exclude SNPs directly associated with potential confounders or outcomes. Two-sample MR was conducted using five MR methods, with inverse-variance-weighted (IVW) as the primary analysis method. A false discovery rate (FDR) correction was used to reduce the likelihood of type 1 errors. In addition, we conducted MR-Egger intercept tests and Cochran's Q tests. The numbers of CD4-CD8- T cells and IgD-CD27- B cells were positively correlated with the development of gastric cancer, with odds ratios (ORs) of 1.15 [95% confidence interval (CI), 1.07-1.24; P<0.001; PFDR=0.041; IVW method] and 1.07 (95% CI, 1.03-1.11; P=0.001; PFDR=0.187; IVW method), respectively. However, the percentage of IgD+CD24- B cells in lymphocytes were negatively associated with the development of gastric cancer (OR =0.90; 95% CI, 0.84-0.96; P=0.002; PFDR=0.187; IVW method). MR analysis of the above three immune cell phenotypes showed no significant heterogeneity or horizontal pleiotropy. In the reverse MR analysis, gastric cancer was not causally associated with any of the immune cell phenotypes. Circulating CD4-CD8- T cells and IgD-CD27- B cells are positively correlated with the development of gastric cancer, while the percentage of IgD+CD24- B cells in lymphocytes are negatively correlated. These findings provide insight into the relationship between immune cells and gastric cancer pathogenesis and may serve as a basis for the development of immunotherapies for gastric cancer.

Abstract C055: Unraveling pancreatic cancer susceptibility at 5p15.33: Functional characterization of a novel VNTR element

Abstract Genome-wide association studies (GWAS) have identified independent signals at 5p15.33 across numerous cancers, with protective alleles for one cancer often conferring risk for another. Many of these associations are thought to act via allele-specific alterations in the cis- regulation of target genes. Transcriptomic analyses in multiple tissue types implicate two plausible target genes: TERT and CLPTM1L. However, the mechanisms linking cancer susceptibility alleles to their presumed target genes, along with the observed antagonistic pleiotropy between different cancers remain elusive. With this in mind, we employed a comprehensive approach, integrating statistical fine-mapping of GWAS summary statistics with massively parallel reporter assays (MPRA) and a densely tiled CRISPRi screen performed across eight cell lines, representative of four distinct cancers associated with 5p15.33 alleles – pancreatic, melanoma, lung, and bladder cancer. Integrative screening identified up to 30 variants across multiple signals in the locus with putative allele-specific transcriptional activity. Furthermore, a variable number tandem repeat (VNTR) in intron 9 of CLPTM1L emerged as a potent transcriptional enhancer in CRISPRi screening. Leveraging PacBio sequencing, VNTR alleles of European ancestry samples from the 1000 Genomes Project were genotyped and found to be highly polymorphic, with longer VNTRs linked to the haplotype tagged by rs31490-A (risk increasing for pancreatic cancer). Subsequent imputation into a pancreatic cancer GWAS of 9,040 cases and 12,496 controls revealed an association between longer VNTRs and risk of pancreatic cancer (OR for VNTR in the 75th percentile = 1.17, 95% CI = 1.13-1.22, P = 2.21x10-12). The significance of the association for the lead SNP rs31490 after conditioning on the VNTR genotype dropped to P= 2.20x10-5, suggesting that VNTR alleles merit consideration as part of the credible variant set for pancreatic cancer. Targeted CRISPRi assays suggested VNTR-mediated cis-regulation of both TERT and CLPTM1L in PANC-1 and MIA PaCa-2 pancreatic cancer cell lines, while dual luciferase reporter assays in the same cell lines revealed that VNTR enhancer activity is mediated by Hippo pathway transcription factors. In ongoing experiments, we aim to expand on luciferase reporter assays and DNA-protein binding assays in relevant cell lines with the aim of not only deciphering how longer VNTRs differentially exert their transcriptional effects compared to shorter alleles but also characterizing the divergent directions of effect between different cancer types. These findings underscore the proposition that pancreatic cancer susceptibility at the 5p15.33 locus may be mediated by both SNPs and an uncharted class of variants, yet to be characterized in the post-GWAS landscape. Citation Format: Aidan O'Brien, Hyunkyung Kong, Minal Patel, Katelyn E Connelly, Mai Xu, Irene Collins, Jun Zhong, Jason Hoskins, Michelle Ho, Brenen Papenburg, Mark M Iles, Matthew H Law, Maria-Teresa Landi, Rachael Stolzenber- Solomon, Brian M Wolpin, Alison P Klein, Nick Orr, Stephen J Chanock, Sara Lindström, Marc-Henri Stern, Ludmila Prokunina-Olsson, Jieyon Choi, Kevin M Brown, Laufey T Amundadottir. Unraveling pancreatic cancer susceptibility at 5p15.33: Functional characterization of a novel VNTR element [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr C055.

Validation and functional follow-up of cervical cancer risk variants at the HLA locus.

Cervical cancer is the fourth most common cancer in females. Genome-wide association studies (GWASs) have proposed cervical cancer susceptibility variants at the HLA locus on chromosome 6p21. To corroborate these findings and investigate their functional impact in cervical tissues and cell lines, we genotyped nine variants from cervical cancer GWASs (rs17190106, rs535777, rs1056429, rs2763979, rs143954678, rs113937848, rs3117027, rs3130214, and rs9477610) in a German hospital-based series of 1122 invasive cervical cancers, 1408 dysplasias, and 1196 healthy controls. rs17190106, rs1056429 and rs143954678/rs113937848 associated with cervical malignancies overall, while rs17190106 and rs535777 associated specifically with invasive cancer (OR = 0.69, 95% CI = 0.55-0.86, p = 0.001) or adenocarcinomas (OR = 1.63, 95%CI = 1.17-2.27, p = 0.004), respectively. We tested these and one previously genotyped GWAS variant, rs9272117, for potential eQTL effects on 36 gene transcripts at the HLA locus in 280 cervical epithelial tissues. The strongest eQTL pairs were rs9272117 and HLA-DRB6 (p = 1.9x10E-5), rs1056429 and HLA-DRB5 (p = 2.5x10E-4), and rs535777 and HLA-DRB1 (p = 2.7x10E-4). We also identified transcripts that were specifically upregulated (DDX39B, HCP5, HLA-B, LTB, NFKBIL1) or downregulated (HLA-C, HLA-DPB2) in HPV+ or HPV16+ samples. In comparison, treating cervical epithelial cells with proinflammatory cytokine γ-IFN led to a dose-dependent induction of HCP5, HLA-B, HLA-C, HLA-DQB1, HLA-DRB1, HLA-DRB6, and repression of HSPA1L. Taken together, these results identify relevant genes from both the MHC class I and II regions that are inflammation-responsive in cervical epithelium and associate with HPV (HCP5, HLA-B, HLA-C) and/or with genomic cervical cancer risk variants (HLA-DRB1, HLA-DRB6). They may thus constitute important contributors to the immune escape of precancerous cells after HPV-infection.

Co-expression in tissue-specific gene networks links genes in cancer-susceptibility loci to known somatic driver genes

BackgroundThe genetic background of cancer remains complex and challenging to integrate. Many somatic mutations within genes are known to cause and drive cancer, while genome-wide association studies (GWAS) of cancer have revealed many germline risk factors associated with cancer. However, the overlap between known somatic driver genes and positional candidate genes from GWAS loci is surprisingly small. We hypothesised that genes from multiple independent cancer GWAS loci should show tissue-specific co-regulation patterns that converge on cancer-specific driver genes.ResultsWe studied recent well-powered GWAS of breast, prostate, colorectal and skin cancer by estimating co-expression between genes and subsequently prioritising genes that show significant co-expression with genes mapping within susceptibility loci from cancer GWAS. We observed that the prioritised genes were strongly enriched for cancer drivers defined by COSMIC, IntOGen and Dietlein et al. The enrichment of known cancer driver genes was most significant when using co-expression networks derived from non-cancer samples of the relevant tissue of origin.ConclusionWe show how genes within risk loci identified by cancer GWAS can be linked to known cancer driver genes through tissue-specific co-expression networks. This provides an important explanation for why seemingly unrelated sets of genes that harbour either germline risk factors or somatic mutations can eventually cause the same type of disease.

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.

Exploring the protective association between COVID-19 infection and laryngeal cancer: insights from a Mendelian randomization study.

Viral infections have been implicated as a risk factor for laryngeal cancer. Given the possible effects of Corona virus disease 2019 (COVID-19) on the laryngeal tissue, we investigated the causal link between COVID-19 and laryngeal cancer using a two-sample Mendelian randomization (MR) approach. We utilized genetic data from the 5th Genome-wide association studies (GWAS) edition of the COVID-19 Host Genetics Initiative (published on January 18, 2021) and a large-scale laryngeal cancer GWAS comprising 180 cases and 218,612 controls of European ancestry. We applied inverse variance weighting, MR Egger, and weighted median methods to infer causality. We performed sensitivity analysis using the "leave-one-out" method to verify robustness. We found no evidence of a causal association between gene-predicted COVID-19 and laryngeal cancer [Odds ratio (OR)=0.24 (95% Confidence intervals (CI), 0.05-1.26), P=0.09]. However, we observed significant inverse associations between gene-predicted COVID-19 hospitalization [OR=0.51 (95% CI, 0.28-0.95), P=0.03] and severe patients [OR=0.62 (95% CI, 0.43-0.90), P=0.01] and laryngeal cancer. Notably, the study detected important genetic variants, such as rs13050728, that modulate the expression of interferon alpha receptor 2 (IFNAR2), indicating possible roles for immune response pathways in both COVID-19 and cancer. This study reveals a potential interaction between COVID-19 severity, genetic factors, and laryngeal cancer, underscoring the importance of investigating the immune response mechanisms in both conditions. These findings contribute to the understanding of the complex interactions between COVID-19 and laryngeal cancer and may guide future research on the role of immune response, particularly involving IFNAR2.

Gut Microbiota, Human Blood Metabolites, and Esophageal Cancer: A Mendelian Randomization Study.

Unbalances in the gut microbiota have been proposed as a possible cause of esophageal cancer (ESCA), yet the exact causal relationship remains unclear. To investigate the potential causal relationship between the gut microbiota and ESCA with Mendelian randomization (MR) analysis. Genome-wide association studies (GWASs) of 207 gut microbial taxa (5 phyla, 10 classes, 13 orders, 26 families, 48 genera, and 105 species) and 205 gut microbiota metabolic pathways conducted by the Dutch Microbiome Project (DMP) and a FinnGen cohort GWAS of esophageal cancer specified the summary statistics. To investigate the possibility of a mediation effect between the gut microbiota and ESCA, mediation MR analyses were performed for 1091 blood metabolites and 309 metabolite ratios. MR analysis indicated that the relative abundance of 10 gut microbial taxa was associated with ESCA but all the 12 gut microbiota metabolic pathways with ESCA indicated no statistically significant association existing. Two blood metabolites and a metabolite ratio were discovered to be mediating factors in the pathway from gut microbiota to ESCA. This research indicated the potential mediating effects of blood metabolites and offered genetic evidence in favor of a causal correlation between gut microbiota and ESCA.

Hierarchical joint analysis of marginal summary statistics-Part I: Multipopulation fine mapping and credible set construction.

Recent advancement in genome-wide association studies (GWAS) comes from not only increasingly larger sample sizes but also the shift in focus towards underrepresented populations. Multipopulation GWAS increase power to detect novel risk variants and improve fine-mapping resolution by leveraging evidence and differences in linkage disequilibrium (LD) from diverse populations. Here, we expand upon our previous approach for single-population fine-mapping through Joint Analysis of Marginal SNP Effects (JAM) to a multipopulation analysis (mJAM). Under the assumption that true causal variants are common across studies, we implement a hierarchical model framework that conditions on multiple SNPs while explicitly incorporating the different LD structures across populations. The mJAM framework can be used to first select index variants using the mJAM likelihood with different feature selection approaches. In addition, we present a novel approach leveraging the ideas of mediation to construct credible sets for these index variants. Construction of such credible sets can be performed given any existing index variants. We illustrate the implementation of the mJAM likelihood through two implementations: mJAM-SuSiE (a Bayesian approach) and mJAM-Forward selection. Through simulation studies based on realistic effect sizes and levels of LD, we demonstrated that mJAM performs well for constructing concise credible sets that include the underlying causal variants. In real data examples taken from the most recent multipopulation prostate cancer GWAS, we showed several practical advantages of mJAM over other existing multipopulation methods.

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 &amp;gt;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 &amp;lt; 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.

Abstract 6140: Gene-environment interactions for lifetime water arsenic exposure and bladder cancer risk in the New England Bladder Cancer study

Abstract Environmental arsenic and genetic susceptibility have both been shown to increase bladder cancer risk, yet little is known about their respective interaction. We conducted a gene-environment interaction (GxE) study to characterize lifetime arsenic exposure from drinking water, inherited susceptibility, and bladder cancer risk in the New England Bladder Cancer Study. Exposures were estimated from arsenic measured in water samples collected at home and workplace. We evaluated common single-nucleotide polymorphisms (SNPs) i) from the latest bladder cancer genome-wide association study (n= 28), ii) from candidate gene studies of arsenic or bladder cancer (n= 16 SNPs), and iii) SNPs from a large genome-wide association study of arsenic metabolism (n = 4 SNPs) as potential effect modifiers of the arsenic-bladder cancer relationship. We coded SNPs as the absence or presence of a risk/effect allele for bladder cancer or arsenic metabolism in 2,019 adults (928 bladder cancer cases and 1,091 controls) and arsenic exposures as tertiles. Odds ratios (OR) with 95% confidence intervals (CI) adjusted for age, sex, smoking status, high-risk occupation, and principal components of genetic ancestry were estimated using logistic regression models. P-values for multiplicative interaction were calculated. Out of 48 SNPs, we found evidence of interaction for 7 SNPs at the statistical significance level of P&amp;lt;0.05. Most SNPs involved in GxE interactions are mapped to genomic regions known or suspected to function in arsenic metabolism. For the association between cumulative lifetime water arsenic (mg) and bladder cancer, the strongest evidence of an interaction was with rs1046428 (near GSTZ1 on 14q23); among those with one or two copies of the T risk allele, ORT2vsT1: 1.52, CI: 1.11 - 2.07; ORT3 vsT1: 1.44, CI: 1.05 - 1.98, Pinteraction = 0.01; among those with no risk allele copy, ORT2vsT1: 0.91, CI: 0.62 - 1.35; ORT3 vsT1: 0.97, CI: 0.65 - 1.44. For average daily water arsenic (µg/day), we found evidence of interaction among those with risk allele for rs1801133 (A/A, A/G; MTHFR on 1p36) ORT2 vsT1: 1.70, CI: 1.18 - 2.44; ORT3 vsT1: 1.53, CI: 1.06 - 2.23, Pinteraction = 0.02, in those with no copies of risk allele ORT2vsT1: 0.85, CI: 0.61 - 1.17; ORT3 vsT1: 1.11, CI: 0.79 - 1.54; and rs1801131 (G/G; G/T; MTHFR ) ORT2 vsT1: 1.59, CI: 1.14 - 2.22; ORT3 vsT1: 1.63, CI: 1.16 - 2.29, Pinteraction = 0.01, whereas in those with no risk allele ORT2vsT1: 0.84, CI: 0.59 - 1.19; ORT3 vsT1: 1, CI: 0.69 - 1.44. For 40-year lagged cumulative lifetime water arsenic (mg) and average daily water arsenic (µg/day), we found suggestive interactions with rs2234636 (SLC39A2 on 14q11), and rs1495741 (NAT2 on 8p22). Our study provides evidence of interactions between lifetime arsenic exposure and genetic variants that function in xenobiotic metabolism on bladder cancer occurrence. Citation Format: Hugo Pomares-Millan, Stella Koutros, Nathaniel Rothman, Dalsu Baris, Molly Schwenn, Alison Johnson, Debra T. Silverman, Margaret R. Karagas, Michael N. Passarelli. Gene-environment interactions for lifetime water arsenic exposure and bladder cancer risk in the New England Bladder Cancer study [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 6140.

Abstract PR001: Highlighting the combined effects of BMI and polygenic risk score on endometrial cancer risk

Abstract Obesity is more strongly associated with endometrial cancer risk than any other cancer type. However, the extent to which genetic susceptibility influences the risk of endometrial cancer independent of obesity remains unknown. Thus, this study aimed to evaluate the predictive performance of polygenic risk score (PRS), body mass index (BMI) and other factors in determining endometrial cancer risk, as well as to explore joint effects on endometrial cancer. PRS was generated using 1.1 million HapMap3 variants from the largest published endometrial cancer genome-wide association study. An endometrial cancer prediction model was constructed using established endometrial cancer risk factors (age, BMI, number of live births, ever taken oral contraceptive pill, age of menarche, and predicted age of menopause). Additionally, an integrated prediction model was constructed, combining the endometrial cancer PRS with established risk factors. The ability of models to predict endometrial cancer status was assessed in unrelated participants of European ancestry from the UK Biobank cohort, encompassing 1,867 participants with endometrial cancer (860 incident cases) and 133,322 cancer-free controls. The integrated model including PRS and risk factors had a modest yet statistically significant improvement in prediction of endometrial cancer status, compared with the model using risk factors alone (AUC 0.752 versus 0.741; P = 1.28 × 10−7). When examining incident cases, participants in the middle and top tertiles of the PRS distribution had a 1.96- (95% CI 1.39-2.77; P = 1.28 × 10−4) and 3.03-fold (95% CI 2.01-4.58; P = 1.60 × 10−8) elevated risk of developing endometrial cancer, respectively, in contrast to those in the lowest tertile. As expected, elevated BMI was associated with increased endometrial cancer risk. Compared to participants with a normal BMI, overweight participants (25kg/m2 ≤ BMI &amp;lt; 30kg/m2) had a 1.58-fold increased hazard ratio (HR; 95% CI 1.32-1.90; P = 8.43 × 10−7), while obese participants (BMI ≥ 30kg/m2) a 3.23-fold increased HR (95% CI 2.71-3.85; P &amp;lt; 2.00 × 10−16). Notably, we observed multiplying effects of BMI and PRS on endometrial cancer risk, with obese participants in the top tertile of the PRS distribution having a 7.53-fold increased HR (95% CI 3.78-14.99; P = 9.41 × 10−9). In summary, these findings indicate that higher PRS was associated with endometrial cancer risk, irrespective of BMI. Moreover, the integration of PRS with established risk factors may aid in better stratifying the general population for their susceptibility to endometrial cancer. Citation Format: Tracy A. O'Mara, Xuemin Wang, Laure Dossus, Marc J. Gunter, Emma J. Crosbie, Dylan M. Glubb. Highlighting the combined effects of BMI and polygenic risk score on endometrial cancer risk [abstract]. In: Proceedings of the AACR Special Conference on Endometrial Cancer: Transforming Care through Science; 2023 Nov 16-18; Boston, Massachusetts. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(5_Suppl):Abstract nr PR001.

The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men.

American men of African ancestry (AA) have higher prostate cancer incidence and mortality rates compared with American men of European ancestry (EA). Differences in genetic susceptibility mechanisms may contribute to this disparity. To gain insights into the regulatory mechanisms of prostate cancer susceptibility variants, we tested the association between SNPs and DNA methylation (DNAm) at nearby CpG sites across the genome in benign and cancer prostate tissue from 74 AA and 74 EA men. Genome-wide SNP data (from benign tissue) and DNAm were generated using Illumina arrays. Among AA men, we identified 6,298 and 2,641 cis-methylation QTLs (meQTL; FDR of 0.05) in benign and tumor tissue, respectively, with 6,960 and 1,700 detected in EA men. We leveraged genome-wide association study (GWAS) summary statistics to identify previously reported prostate cancer GWAS signals likely to share a common causal variant with a detected meQTL. We identified nine GWAS-meQTL pairs with strong evidence of colocalization (four in EA benign, three in EA tumor, two in AA benign, and three in AA tumor). Among these colocalized GWAS-meQTL pairs, we identified colocalizing expression quantitative trait loci (eQTL) impacting four eGenes with known roles in tumorigenesis. These findings highlight epigenetic regulatory mechanisms by which prostate cancer-risk SNPs can modify local DNAm and/or gene expression in prostate tissue. Overall, our findings showed general consistency in the meQTL landscape of AA and EA men, but meQTLs often differ by tissue type (normal vs. cancer). Ancestry-based linkage disequilibrium differences and lack of AA representation in GWAS decrease statistical power to detect colocalization for some regions.

Leisure time television watching, computer use and risks of breast, colorectal and prostate cancer: A Mendelian randomisation analysis.

Sedentary behaviours have been associated with increased risks of some common cancers in epidemiological studies; however, it is unclear if these associations are causal. We used univariable and multivariable two-sample Mendelian randomisation (MR) to examine potential causal relationships between sedentary behaviours and risks of breast, colorectal and prostate cancer. Genetic variants associated with self-reported leisure television watching and computer use were identified from a recent genome-wide association study (GWAS). Data related to cancer risk were obtained from cancer GWAS consortia. A series of sensitivity analyses were applied to examine the robustness of the results to the presence of confounding. A 1-standard deviation (SD: 1.5 h/day) increment in hours of television watching increased risk of breast cancer (OR per 1-SD: 1.15, 95% confidence interval [CI]: 1.05-1.26) and colorectal cancer (OR per 1-SD: 1.32, 95% CI: 1.16-1.49) while there was little evidence of an association for prostate cancer risk (OR per 1-SD: 0.94, 95% CI: 0.84-1.06). After adjusting for years of education, the effect estimates for television watching were attenuated (breast cancer, OR per 1-SD: 1.08, 95% CI: 0.92-1.27; colorectal cancer, OR per 1-SD: 1.08, 95% CI: 0.90-1.31). Post hoc analyses showed that years of education might have a possible confounding and mediating role in the association between television watching with breast and colorectal cancer. Consistent results were observed for each cancer site according to sex (colorectal cancer), anatomical subsites and cancer subtypes. There was little evidence of associations between genetically predicted computer use and cancer risk. Our univariable analysis identified some positive associations between hours of television watching and risks of breast and colorectal cancer. However, further adjustment for additional lifestyle factors especially years of education attenuated these results. Future studies using objective measures of exposure can provide new insights into the possible role of sedentary behaviour in cancer development.

XQTLbiolinks: a comprehensive and scalable tool for integrative analysis of molecular QTLs.

Genome-wide association studies (GWAS) have identified thousands of disease-associated non-coding variants, posing urgent needs for functional interpretation. Molecular Quantitative Trait Loci (xQTLs) such as eQTLs serve as an essential intermediate link between these non-coding variants and disease phenotypes and have been widely used to discover disease-risk genes from many population-scale studies. However, mining and analyzing the xQTLs data presents several significant bioinformatics challenges, particularly when it comes to integration with GWAS data. Here, we developed xQTLbiolinks as the first comprehensive and scalable tool for bulk and single-cell xQTLs data retrieval, quality control and pre-processing from public repositories and our integrated resource. In addition, xQTLbiolinks provided a robust colocalization module through integration with GWAS summary statistics. The result generated by xQTLbiolinks can be flexibly visualized or stored in standard R objects that can easily be integrated with other R packages and custom pipelines. We applied xQTLbiolinks to cancer GWAS summary statistics as case studies and demonstrated its robust utility and reproducibility. xQTLbiolinks will profoundly accelerate the interpretation of disease-associated variants, thus promoting a better understanding of disease etiologies. xQTLbiolinks is available at https://github.com/lilab-bioinfo/xQTLbiolinks.

Causal association between inflammatory bowel disease and 32 site-specific extracolonic cancers: a Mendelian randomization study

BackgroundThe risk of extracolonic cancer is increased in inflammatory bowel disease (IBD) patients, but it is not clear whether there is a causal relationship. We aimed to systematically estimate the causal relationship between IBD and extracolonic cancers.MethodsIndependent genetic variants strongly associated with IBD were extracted as instrumental variables from genome-wide association study (GWAS) conducted by the International IBD Genetics Consortium including 12,882 IBD patients, 5956 Crohn’s disease (CD) patients, and 6968 ulcerative colitis (UC) patients. Three sources of cancer GWAS were selected as outcome data. Two-sample Mendelian randomization (MR) analysis was conducted to assess the causal effects of IBD on 32 extracolonic cancers. The meta-analysis was applied to assess the combined causal effect with multiple MR results.ResultsIBD, CD, and UC have potential causal associations with oral cavity cancer (IBD: OR = 1.180, 95% CI: 1.059 to 1.316, P = 0.003; CD: OR = 1.112, 95% CI: 1.008 to 1.227, P = 0.034; UC: OR = 1.158, 95% CI: 1.041 to 1.288, P = 0.007). Meta-analysis showed a significant positive causal relationship between IBD and breast cancer (OR = 1.059; 95% CI: 1.033 to 1.086; P < 0.0001) as well as a potential causal relationship between CD and breast cancer (OR = 1.029; 95% CI: 1.002 to 1.055; P = 0.032) based on combining multiple MR results.ConclusionsThis comprehensive MR analysis suggested that genetically predicted IBD, as well as its subtypes, may be a risk factor in the development of oral cavity and breast cancer.