Cyclin A1 promoter hypermethylation in human papillomavirus-associated cervical cancer

BACKGROUND: The aim of this study was to evaluate epigenetic status of cyclin A1 in human papillomavirus-associated cervical cancer. Y. Tokumaru et al., Cancer Res 64, 5982-7 (Sep 1, 2004)demonstrated in head and neck squamous-cell cancer an inverse correlation between cyclin A1 promoter hypermethylation and TP53 mutation. Human papillomavirus-associated cervical cancer, however, is deprived of TP53 function by a different mechanism. Therefore, it was of interest to investigate the epigenetic alterations during multistep cervical cancer development. METHODS: In this study, we performed duplex methylation-specific PCR and reverse transcriptase PCR on several cervical cancer cell lines and microdissected cervical cancers. Furthermore, the incidence of cyclin A1 methylation was studied in 43 samples of white blood cells, 25 normal cervices, and 24, 5 and 30 human papillomavirus-associated premalignant, microinvasive and invasive cervical lesions, respectively. RESULTS: We demonstrated cyclin A1 methylation to be commonly found in cervical cancer, both in vitro and in vivo, with its physiological role being to decrease gene expression. More important, this study demonstrated that not only is cyclin A1 promoter hypermethylation strikingly common in cervical cancer, but is also specific to the invasive phenotype in comparison with other histopathological stages during multistep carcinogenesis. None of the normal cells and low-grade squamous intraepithelial lesions exhibited methylation. In contrast, 36.6%, 60% and 93.3% of high-grade squamous intraepithelial lesions, microinvasive and invasive cancers, respectively, showed methylation. CONCLUSION: This methylation study indicated that cyclin A1 is a potential tumor marker for early diagnosis of invasive cervical cancer

Hypomethylation of Intragenic LINE-1 Represses Transcription in Cancer Cells through AGO2

In human cancers, the methylation of long interspersed nuclear element -1 (LINE-1 or L1) retrotransposons is reduced. This occurs within the context of genome wide hypomethylation, and although it is common, its role is poorly understood. L1s are widely distributed both inside and outside of genes, intragenic and intergenic, respectively. Interestingly, the insertion of active full-length L1 sequences into host gene introns disrupts gene expression. Here, we evaluated if intragenic L1 hypomethylation influences their host gene expression in cancer. First, we extracted data from L1base (http://l1base.molgen.mpg.de), a database containing putatively active L1 insertions, and compared intragenic and intergenic L1 characters. We found that intragenic L1 sequences have been conserved across evolutionary time with respect to transcriptional activity and CpG dinucleotide sites for mammalian DNA methylation. Then, we compared regulated mRNA levels of cells from two different experiments available from Gene Expression Omnibus (GEO), a database repository of high throughput gene expression data, (http://www.ncbi.nlm.nih.gov/geo) by chi-square. The odds ratio of down-regulated genes between demethylated normal bronchial epithelium and lung cancer was high (p<1E−27; OR = 3.14; 95% CI = 2.54–3.88), suggesting cancer genome wide hypomethylation down-regulating gene expression. Comprehensive analysis between L1 locations and gene expression showed that expression of genes containing L1s had a significantly higher likelihood to be repressed in cancer and hypomethylated normal cells. In contrast, many mRNAs derived from genes containing L1s are elevated in Argonaute 2 (AGO2 or EIF2C2)-depleted cells. Hypomethylated L1s increase L1 mRNA levels. Finally, we found that AGO2 targets intronic L1 pre-mRNA complexes and represses cancer genes. These findings represent one of the mechanisms of cancer genome wide hypomethylation altering gene expression. Hypomethylated intragenic L1s are a nuclear siRNA mediated cis-regulatory element that can repress genes. This epigenetic regulation of retrotransposons likely influences many aspects of genomic biology

Global DNA Hypomethylation in Peripheral Blood Leukocytes as a Biomarker for Cancer Risk: A Meta-Analysis

BACKGROUND: Good biomarkers for early detection of cancer lead to better prognosis. However, harvesting tumor tissue is invasive and cannot be routinely performed. Global DNA methylation of peripheral blood leukocyte DNA was evaluated as a biomarker for cancer risk. METHODS: We performed a meta-analysis to estimate overall cancer risk according to global DNA hypomethylation levels among studies with various cancer types and analytical methods used to measure DNA methylation. Studies were systemically searched via PubMed with no language limitation up to July 2011. Summary estimates were calculated using a fixed effects model. RESULTS: The subgroup analyses by experimental methods to determine DNA methylation level were performed due to heterogeneity within the selected studies (p<0.001, I(2): 80%). Heterogeneity was not found in the subgroup of %5-mC (p = 0.393, I(2): 0%) and LINE-1 used same target sequence (p = 0.097, I(2): 49%), whereas considerable variance remained in LINE-1 (p<0.001, I(2): 80%) and bladder cancer studies (p = 0.016, I(2): 76%). These results suggest that experimental methods used to quantify global DNA methylation levels are important factors in the association study between hypomethylation levels and cancer risk. Overall, cancer risks of the group with the lowest DNA methylation levels were significantly higher compared to the group with the highest methylation levels [OR (95% CI): 1.48 (1.28-1.70)]. CONCLUSIONS: Global DNA hypomethylation in peripheral blood leukocytes may be a suitable biomarker for cancer risk. However, the association between global DNA methylation and cancer risk may be different based on experimental methods, and region of DNA targeted for measuring global hypomethylation levels as well as the cancer type. Therefore, it is important to select a precise and accurate surrogate marker for global DNA methylation levels in the association studies between global DNA methylation levels in peripheral leukocyte and cancer risk

Hypomethylation of a LINE-1 Promoter Activates an Alternate Transcript of the MET Oncogene in Bladders with Cancer

It was recently shown that a large portion of the human transcriptome can originate from within repetitive elements, leading to ectopic expression of protein-coding genes. However the mechanism of transcriptional activation of repetitive elements has not been definitively elucidated. For the first time, we directly demonstrate that hypomethylation of retrotransposons can cause altered gene expression in humans. We also reveal that active LINE-1s switch from a tetranucleosome to dinucleosome structure, acquiring H2A.Z- and nucleosome-free regions upstream of TSSs, previously shown only at active single-copy genes. Hypomethylation of a specific LINE-1 promoter was also found to induce an alternate transcript of the MET oncogene in bladder tumors and across the entire urothelium of tumor-bearing bladders. These data show that, in addition to contributing to chromosomal instability, hypomethylation of LINE-1s can alter the functional transcriptome and plays a role not only in human disease but also in disease predisposition

Many LINE1 elements contribute to the transcriptome of human somatic cells

Over 600 LINE 1 elements are shown to be transcribed in humans; 400 of these are full-length elements in the reference genome

Long interspersed nuclear element-1 hypomethylation in cancer: biology and clinical applications

Epigenetic changes in long interspersed nuclear element-1s (LINE-1s or L1s) occur early during the process of carcinogenesis. A lower methylation level (hypomethylation) of LINE-1 is common in most cancers, and the methylation level is further decreased in more advanced cancers. Consequently, several previous studies have suggested the use of LINE-1 hypomethylation levels in cancer screening, risk assessment, tumor staging, and prognostic prediction. Epigenomic changes are complex, and global hypomethylation influences LINE-1s in a generalized fashion. However, the methylation levels of some loci are dependent on their locations. The consequences of LINE-1 hypomethylation are genomic instability and alteration of gene expression. There are several mechanisms that promote both of these consequences in cis. Therefore, the methylation levels of different sets of LINE-1s may represent certain phenotypes. Furthermore, the methylation levels of specific sets of LINE-1s may indicate carcinogenesis-dependent hypomethylation. LINE-1 methylation pattern analysis can classify LINE-1s into one of three classes based on the number of methylated CpG dinucleotides. These classes include hypermethylation, partial methylation, and hypomethylation. The number of partial and hypermethylated loci, but not hypomethylated LINE-1s, is different among normal cell types. Consequently, the number of hypomethylated loci is a more promising marker than methylation level in the detection of cancer DNA. Further genome-wide studies to measure the methylation level of each LINE-1 locus may improve PCR-based methylation analysis to allow for a more specific and sensitive detection of cancer DNA or for an analysis of certain cancer phenotypes

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease