Hou, Lifang

Abstract Hepatocellular carcinoma (HCC) is the second most common cause of cancer deaths worldwide. Hepatitis C virus (HCV) infection is a major risk factor for HCC in the US. HCV infection may cause cancer by suppressing host defense that controls the propagation of repetitive element (RE) sequences, including LINE-1 and Alu, the most representative REs in the human genome. DNA methylation of RE helps stabilize the genome, while reduced RE methylation, also referred as global hypomethylation, leads to genomic instability and is known as a hallmark of cancer. However, current available high-throughput technology for DNA methylation profiling only enables genomewide RE methylation study on a global scale. The role of individual RE methylation in cancer is largely understudied. In this study, using our recently developed and published machine learning algorithm to enhance the RE coverage of the Illumina methylation array platform, we examined the role of individual RE methylation in HCV-induced HCC across the entire genome. We conducted an epigenome-wide association study on 22 HCC, 20 cirrhotic, and 44 normal liver tissues. We included equal numbers of HCV-induced and alcohol-induced HCC/cirrhosis cases. The Illumina 450k array profiled 1939 REs and we computationally predicted 33184 REs; correlations between the overlapping 1541 profiled and predicted RE methylation were > 0.91. Sex, tumor differentiation, and tumor stage were similarly distributed across the HCV and alcohol groups. We adjusted for batch effects and used Benjamini-Hochberg adjusted false discovery rate (FDR) to account for multiple testing. Relative to normal liver tissue, we observed over twice as many differentially methylated (FDR < 0.05) REs in HCV-HCC compared to alcohol-HCC tissue (2911 vs 1304, 749 in common). We validated our results in The Cancer Genome Atlas (TCGA) (325 vs 129, 74 in common) with high correlation (r = 0.90). We also observed that 169 REs were significantly altered in HCV-cirrhosis tissue (compared to none in alcohol-cirrhosis tissue), of which, 17 REs in 13 genes, including PIK3CD, LY9, GCK, NLRC3, and PRKCZ, were consistently hypomethylated in both HCC and cirrhotic liver tissue induced by HCV (r = 0.87). Using TCGA RNA sequencing data, we found that these REs were located in gene body and their hypomethylation was associated with lower expression of their host genes (r > 0.3, p < 0.05). Gene Ontology Enrichment analysis showed that these genes were enriched in T-cell activation & differentiation and cytokine production (FDR < 0.05). Our findings indicate that HCV infection has a more extensive impact on the DNA methylation landscape in RE than alcohol consumption, and that HCV infection may also induce similar hypomethylation in cirrhotic liver. Hypomethylated RE may alter local chromatin environment and disrupt expression of genes involved in immune and inflammatory responses, both of which may promote HCC development. RE hypomethylation in specific genomic locus may serve as early detection biomarker of HCC in patients with HCV-induced cirrhosis. Citation Format: Yinan Zheng, Jimmy Ren, Ryan A. Hlady, Keith D. Robertson, Robert L. Murphy, Lewis R. Roberts, Lifang Hou. DNA methylation of individual repetitive elements in HCV infection-induced HCC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-235.

Abstract Researchers hypothesized that telomere shortening facilitates carcinogenesis. Previous studies found inconsistent associations between blood leukocyte telomere length (LTL) and cancer. Epigenetic reprogramming of telomere maintenance mechanisms may help explain this inconsistency. We examined associations between DNA methylation in telomere-related genes (TRG) and cancer. We analyzed 475 participants providing 889 samples 1 to 3 times (median follow-up, 10.1 years) from 1999 to 2013 in the Normative Aging Study. All participants were cancer-free at each visit and blood leukocytes profiled using the Illumina 450K array. Of 121 participants who developed cancer, 34 had prostate cancer, 10 melanoma, 34 unknown skin malignancies, and 43 another cancer. We examined 2,651 CpGs from 80 TRGs and applied a combination of Cox and mixed models to identify CpGs prospectively associated with cancer (at FDR < 0.05). We also explored trajectories of DNA methylation, logistic regression stratified by time to diagnosis/censoring, and cross-sectional models of LTL at first blood draw. We identified 30 CpGs on 23 TRGs whose methylation was positively associated with cancer incidence (β = 1.0–6.93) and one protective CpG in MAD1L1 (β = −0.65), of which 87% were located in TRG promoters. Methylation trajectories of 21 CpGs increased in cancer cases relative to controls; at 4 to 8 years prediagnosis/censoring, 17 CpGs were positively associated with cancer. Three CpGs were cross-sectionally associated with LTL. TRG methylation may be a mechanism through which LTL dynamics reflect cancer risk. Future research should confirm these findings and explore potential mechanisms underlying these findings, including telomere maintenance and DNA repair dysfunction. Cancer Prev Res; 11(8); 511–22. ©2018 AACR.

Abstract Summary: The development of the Infinium HumanMethylation450 BeadChip enables epigenome-wide association studies at a reduced cost. One observation of the 450K data is that many CpG sites the beadchip interrogates have very large measurement errors. Including these noisy CpGs will decrease the statistical power of detecting relevant associations due to multiple testing correction. We propose to use intra-class correlation coefficient (ICC), which characterizes the relative contribution of the biological variability to the total variability, to filter CpGs when technical replicates are available. We estimate the ICC based on a linear mixed effects model by pooling all the samples instead of using the technical replicates only. An ultra-fast algorithm has been developed to address the computational complexity and CpG filtering can be completed in minutes on a desktop computer for a 450K data set of over 1000 samples. Our method is very flexible and can accommodate any replicate design. Simulations and a real data application demonstrate that our whole-sample ICC method performs better than replicate-sample ICC or variance-based method. Availability and implementation: CpGFilter is implemented in R and publicly available under CRAN via the R package ‘CpGFilter’. Contact: chen.jun2@mayo.edu or xlin@hsph.harvard.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Objective Genome-wide association studies have identified a large number of single nucleotide polymorphisms (SNPs) associated with a wide array of cancer sites. Several of these variants demonstrate associations with multiple cancers, suggesting pleiotropic effects and shared biological mechanisms across some cancers. We hypothesised that SNPs previously associated with other cancers may additionally be associated with colorectal cancer. In a large-scale study, we examined 171 SNPs previously associated with 18 different cancers for their associations with colorectal cancer. Design We examined 13 338 colorectal cancer cases and 40 967 controls from three consortia: Population Architecture using Genomics and Epidemiology (PAGE), Genetic Epidemiology of Colorectal Cancer (GECCO), and the Colon Cancer Family Registry (CCFR). Study-specific logistic regression results, adjusted for age, sex, principal components of genetic ancestry, and/or study specific factors (as relevant) were combined using fixed-effect meta-analyses to evaluate the association between each SNP and colorectal cancer risk. A Bonferroni-corrected p value of 2.92×10 −4 was used to determine statistical significance of the associations. Results Two correlated SNPs—rs10090154 and rs4242382—in Region 1 of chromosome 8q24, a prostate cancer susceptibility region, demonstrated statistically significant associations with colorectal cancer risk. The most significant association was observed with rs4242382 (meta-analysis OR=1.12; 95% CI 1.07 to 1.18; p=1.74×10 −5 ), which also demonstrated similar associations across racial/ethnic populations and anatomical sub-sites. Conclusions This is the first study to clearly demonstrate Region 1 of chromosome 8q24 as a susceptibility locus for colorectal cancer; thus, adding colorectal cancer to the list of cancer sites linked to this particular multicancer risk region at 8q24.