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Graw S, Henn R, Thompson JA, Koestler DC. pwrEWAS: a user-friendly tool for comprehensive power estimation for epigenome wide association studies (EWAS). BMC Bioinformatics 2019; 20:218. [PMID: 31035919 PMCID: PMC6489300 DOI: 10.1186/s12859-019-2804-7] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Accepted: 04/10/2019] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND When designing an epigenome-wide association study (EWAS) to investigate the relationship between DNA methylation (DNAm) and some exposure(s) or phenotype(s), it is critically important to assess the sample size needed to detect a hypothesized difference with adequate statistical power. However, the complex and nuanced nature of DNAm data makes direct assessment of statistical power challenging. To circumvent these challenges and to address the outstanding need for a user-friendly interface for EWAS power evaluation, we have developed pwrEWAS. RESULTS The current implementation of pwrEWAS accommodates power estimation for two-group comparisons of DNAm (e.g. case vs control, exposed vs non-exposed, etc.), where methylation assessment is carried out using the Illumina Human Methylation BeadChip technology. Power is calculated using a semi-parametric simulation-based approach in which DNAm data is randomly generated from beta-distributions using CpG-specific means and variances estimated from one of several different existing DNAm data sets, chosen to cover the most common tissue-types used in EWAS. In addition to specifying the tissue type to be used for DNAm profiling, users are required to specify the sample size, number of differentially methylated CpGs, effect size(s) (Δβ), target false discovery rate (FDR) and the number of simulated data sets, and have the option of selecting from several different statistical methods to perform differential methylation analyses. pwrEWAS reports the marginal power, marginal type I error rate, marginal FDR, and false discovery cost (FDC). Here, we demonstrate how pwrEWAS can be applied in practice using a hypothetical EWAS. In addition, we report its computational efficiency across a variety of user settings. CONCLUSION Both under- and overpowered studies unnecessarily deplete resources and even risk failure of a study. With pwrEWAS, we provide a user-friendly tool to help researchers circumvent these risks and to assist in the design and planning of EWAS. AVAILABILITY The web interface is written in the R statistical programming language using Shiny (RStudio Inc., 2016) and is available at https://biostats-shinyr.kumc.edu/pwrEWAS/ . The R package for pwrEWAS is publicly available at GitHub ( https://github.com/stefangraw/pwrEWAS ).
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Affiliation(s)
- Stefan Graw
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS USA
| | - Rosalyn Henn
- Department of Cancer Biology, University of Kansas Medical Center, Kansas City, KS USA
| | - Jeffrey A. Thompson
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS USA
| | - Devin C. Koestler
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS USA
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Huo Z, Zhu Y, Yu L, Yang J, De Jager P, Bennett DA, Zhao J. DNA methylation variability in Alzheimer's disease. Neurobiol Aging 2019; 76:35-44. [PMID: 30660039 PMCID: PMC6436841 DOI: 10.1016/j.neurobiolaging.2018.12.003] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2018] [Revised: 11/07/2018] [Accepted: 12/12/2018] [Indexed: 12/11/2022]
Abstract
DNA methylation plays a critical role in brain aging and Alzheimer's disease (AD). While prior studies have largely focused on testing mean DNA methylation, DNA methylation instability (quantified by DNA methylation variability) may also affect disease susceptibility. Using DNA methylation data collected by the Religious Orders Study and the Rush Memory and Aging Project, we identified 249 and 115 variably methylated probes (VMPs) associated with amyloid-β and neurofibrillary tangles, respectively. These VMPs clustered into 133 and 14 regions, respectively. Notably, we found that most of these VMPs did not overlap with differentially methylated probes, indicating that VMPs and differentially methylated probes may capture different sets of genes associated with AD pathology. Overall, our results demonstrated that DNA methylation instability affects AD neuropathology and highlights the importance of testing methylation variability in epigenetic research.
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Affiliation(s)
- Zhiguang Huo
- Department of Biostatistics, University of Florida, Gainesville, FL, USA
| | - Yun Zhu
- Department of Epidemiology, University of Florida, Gainesville, FL, USA
| | - Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Jingyun Yang
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Philip De Jager
- Department of Neurology, College of Physicians & Surgeons, Columbia University, NY, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Jinying Zhao
- Department of Epidemiology, University of Florida, Gainesville, FL, USA.
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Li G, Liu KY, Qiu ZP. An integrative module analysis of DNA methylation landscape in aging. Exp Ther Med 2019; 17:3411-3416. [PMID: 30988719 PMCID: PMC6447821 DOI: 10.3892/etm.2019.7334] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2018] [Accepted: 02/06/2019] [Indexed: 02/02/2023] Open
Abstract
To investigate the molecular mechanism of aging, the combination of module analysis and DNA methylation data was used to detect dynamically controlled modules for aging. Multiple differential expression networks (DENs) were constructed based on the microarray profiles across different aging groups (<70 years, 70–80 years, and >80 years). Next, a module-based approach was utilized to extract the common candidate modules across all age groups. We used Module Connectivity Dynamic Score (MCDS) to quantify the connectivity change of the common modules among the different age groups. Functional analyses were implemented for the genes in the common modules to further identify the significant biological processes. A total of two DENs were constructed. Overall 657 informative genes were screened out. When false discovery rate (FDR) was set as 0.05, we found that 148 modules were significant. Only 1 significant 2-differential modules (DMs) (module 493) with dynamic changes was discovered. Significantly, the genes in the module 493 participated in 7 significant pathways, including pentose phosphate pathway, carbon metabolism, and citrate cycle (TCA cycle). In conclusion, pathway functions [pentose phosphate pathway, carbon metabolism, citrate cycle (TCA cycle), chromosomal instability, ateroid biosynthesis, PPAR signaling pathway, and immune response] may serve as potential therapeutic targets in aging.
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Affiliation(s)
- Gang Li
- Department of Orthopedics, School of Medicine, Shihezi University, Shihezi, Xinjiang 832000, P.R. China
| | - Ke-Yu Liu
- Department of Orthopedics, School of Medicine, Shihezi University, Shihezi, Xinjiang 832000, P.R. China
| | - Zhong-Peng Qiu
- Department of Orthopedics, School of Medicine, Shihezi University, Shihezi, Xinjiang 832000, P.R. China
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Ghosh J, Schultz B, Coutifaris C, Sapienza C. Highly variant DNA methylation in normal tissues identifies a distinct subclass of cancer patients. Adv Cancer Res 2019; 142:1-22. [PMID: 30885359 DOI: 10.1016/bs.acr.2019.01.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The "CpG Island Methylator Phenotype" (CIMP) has been found to be a useful concept in stratifying several types of human cancer into molecularly and clinically distinguishable subgroups. We have identified an additional epigenetic stratification category, the "Outlier Methylation Phenotype" (OMP). Whereas CIMP is defined on the basis of hyper-methylation in tumor genomes, OMP is defined on the basis of highly variant (either or both hyper- and hypo-methylation) methylation at many sites in normal tissues. OMP was identified and defined, originally, as being more common among low birth weight individuals conceived in vitro but we have also identified OMP individuals among colon cancer patients profiled by us, as well as multiple types of cancer patients in the TCGA database. The cause(s) of OMP are unknown, as is whether these individuals identify a clinically useful subgroup of patients, but both the causes of, and potential consequences to, this epigenetically distinct group are of great interest.
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Affiliation(s)
- Jayashri Ghosh
- Fels Institute of Cancer Research and Molecular Biology, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, United States
| | - Bryant Schultz
- Fels Institute of Cancer Research and Molecular Biology, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, United States
| | - Christos Coutifaris
- Department of Obstetrics & Gynecology, University of Pennsylvania School of Medicine, Philadelphia, PA, United States
| | - Carmen Sapienza
- Fels Institute of Cancer Research and Molecular Biology, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, United States; Department of Pathology and Laboratory Medicine, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, United States.
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Chen L, Wu X, Xie H, Yao N, Xia Y, Ma G, Qian M, Ge H, Cui Y, Huang Y, Wang S, Zheng M. ZFP57 suppress proliferation of breast cancer cells through down-regulation of MEST-mediated Wnt/β-catenin signalling pathway. Cell Death Dis 2019; 10:169. [PMID: 30787268 PMCID: PMC6382817 DOI: 10.1038/s41419-019-1335-5] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Accepted: 12/20/2018] [Indexed: 12/27/2022]
Abstract
Activation of oncogenes by promoter hypomethylation plays an important role in tumorigenesis. Zinc finger protein 57 (ZFP57), a member of KRAB-ZFPs, could maintain DNA methylation in embryonic stem cells (ESCs), although its role and underlying mechanisms in breast cancer are not well understood. In this study, we found that ZFP57 had low expression in breast cancer, and overexpression of ZFP57 could inhibit the proliferation of breast cancer cells by inhibiting the Wnt/β-catenin pathway. MEST was validated as the direct target gene of ZFP57 and MEST may be down-regulated by ZFP57 through conserving DNA methylation. Furthermore, overexpression of MEST could restore the tumour-suppressed and the Wnt/β-catenin pathway inactivated effects of ZFP57. ZFP57-MEST and the Wnt/β-catenin pathway axis are involved in breast tumorigenesis, which may represent a potential diagnostic biomarker, and provide a new insight into a novel therapeutic strategy for breast cancer patients.
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Affiliation(s)
- Lie Chen
- Department of Breast Surgery, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu, 210029, China
| | - Xiaowei Wu
- Department of Breast Surgery, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu, 210029, China
| | - Hui Xie
- Department of Breast Surgery, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu, 210029, China
| | - Na Yao
- Department of Breast Surgery, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu, 210029, China
| | - Yiqin Xia
- Department of Breast Surgery, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu, 210029, China
| | - Ge Ma
- Department of Breast Surgery, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu, 210029, China
| | - Mengjia Qian
- Department of Breast Surgery, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu, 210029, China
| | - Han Ge
- Department of Breast Surgery, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu, 210029, China
| | - Yangyang Cui
- Department of Breast Surgery, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu, 210029, China
| | - Yue Huang
- Department of Breast Surgery, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu, 210029, China
| | - Shui Wang
- Department of Breast Surgery, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu, 210029, China.
| | - Mingjie Zheng
- Department of Breast Surgery, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu, 210029, China.
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Hentze JL, Høgdall CK, Høgdall EV. Methylation and ovarian cancer: Can DNA methylation be of diagnostic use? Mol Clin Oncol 2019; 10:323-330. [PMID: 30847169 DOI: 10.3892/mco.2019.1800] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Accepted: 12/04/2018] [Indexed: 12/31/2022] Open
Abstract
Ovarian cancer is a silent killer and, due to late diagnosis and frequent chemo resistance in patients, the primary cause of fatality amongst the various types of gynecological cancer. The discovery of a specific and sensitive biomarker for ovarian cancer could improve early diagnosis, thereby saving lives. Biomarkers could also improve treatment, by predicting which patients will benefit from specific treatment strategies. DNA methylation is an epigenetic mechanism, and 'methylation imbalance' is characteristic of cancer. Previous research suggests that changes in DNA methylation can be used diagnostically, and that they may predict resistance to treatment. This paper gives an up-to-date overview of research investigating the potential of DNA methylation-based markers for diagnostics, prognostics, screening and prediction of drug resistance for ovarian cancer patients. DNA methylation cancer-biomarkers may be useful for cancer treatment, particularly since they are chemically stable and since cancer-associated changes in methylation typically precedes tumor growth. DNA methylation markers could improve diagnosis and treatment and might even be used for screening in the future. Furthermore, DNA methylation biomarkers could facilitate the development of precision medicine. However, at this point no biomarkers for ovarian cancer have a sufficient combination of sensitivity and specificity in a clinical setting. A reason for this is that most studies have focused on a single or a few methylation sites. More large screenings and genome-wide studies must be performed to increase the chance of identifying a DNA methylation marker which can identify ovarian cancer.
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Affiliation(s)
- Julie L Hentze
- Department of Pathology, Herlev Hospital, University of Copenhagen, 2730 Herlev, Denmark
| | - Claus K Høgdall
- Department of Gynecology, The Juliane Marie Centre, Rigshospitalet, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Estrid V Høgdall
- Department of Pathology, Herlev Hospital, University of Copenhagen, 2730 Herlev, Denmark
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57
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Novel epigenetic markers for gastric cancer risk stratification in individuals after Helicobacter pylori eradication. Gastric Cancer 2018; 21:745-755. [PMID: 29427040 DOI: 10.1007/s10120-018-0803-4] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Accepted: 01/27/2018] [Indexed: 02/07/2023]
Abstract
BACKGROUND The risk stratification of healthy individuals after Helicobacter pylori eradication is an urgent issue. The assessment of aberrant DNA methylation accumulated in gastric tissues with normal appearance, which can reflect overall epigenomic damage, is a promising strategy. We aimed to establish novel epigenetic cancer risk markers for H. pylori-eradicated individuals. METHODS Gastric mucosa was collected from eight healthy volunteers without H. pylori infection (G1), 75 healthy individuals with gastric atrophy (G2), and 94 gastric cancer patients (G3) after H. pylori eradication. Genome-wide analysis was conducted using Infinium 450 K and differentially methylated probes were screened using large difference and iEVORA-based methods. Bisulfite pyrosequencing was used for validation. RESULTS Screening, using 8 G1, 12 G2, and 12 G3 samples, isolated 57 candidates unmethylated in G1 and differentially methylated in G3 compared with G2. Validation for nine candidate markers (FLT3, LINC00643, RPRM, JAM2, ELMO1, BHLHE22, RIMS1, GUSBP5, and ZNF3) in 63 G2 and 82 G3 samples showed that all of them had significantly higher methylation levels in G3 than in G2 (P < 0.0001). Their methylation levels were highly correlated, which indicated that they reflect overall epigenomic damage. The candidates had sufficient performance (AUC: 0.70-0. 80) and high odds ratios (5.43-23.41), some of which were superior to a previous marker, miR-124a-3. The methylation levels of our novel markers were not associated with gastric atrophy, gender, or age. CONCLUSIONS Novel epigenetic markers for gastric cancer risk optimized for H. pylori-eradicated individuals were established.
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Wang XB, Cui NH, Liu XN, Ma JF, Zhu QH, Guo SR, Zhao JW, Ming L. Identification of DAPK1 Promoter Hypermethylation as a Biomarker for Intra-Epithelial Lesion and Cervical Cancer: A Meta-Analysis of Published Studies, TCGA, and GEO Datasets. Front Genet 2018; 9:258. [PMID: 30065752 PMCID: PMC6056635 DOI: 10.3389/fgene.2018.00258] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Accepted: 06/26/2018] [Indexed: 12/26/2022] Open
Abstract
Background: Promoter hypermethylation in death-associated protein kinase 1 (DAPK1) gene has been long linked to cervical neoplasia, but the established results remained controversial. Here, we performed a meta-analysis to assess the associations of DAPK1 promoter hypermethylation with low-grade intra-epithelial lesion (HSIL), high-grade intra-epithelial lesion (HSIL), cervical cancer (CC), and clinicopathological features of CC. Methods: Published studies with qualitative methylation data were initially searched from PubMed, Web of Science, EMBASE, and China National Knowledge Infrastructure databases (up to March 2018). Then, quantitative methylation datasets, retrieved from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, were pooled to validate the results of published studies. Results: In a meta-analysis of 37 published studies, DAPK1 promoter hypermethylation progressively increased the risk of LSIL by 2.41-fold (P = 0.012), HSIL by 7.62-fold (P < 0.001), and CC by 23.17-fold (P < 0.001). Summary receiver operating characteristic curves suggested a potential diagnostic value of DAPK1 promoter hypermethylation in CC, with a large area-under-the-curve of 0.83, a high specificity of 97%, and a moderate sensitivity of 59%. There were significant impacts of DAPK1 promoter hypermethylation on histological type (odds ratio (OR) = 3.53, P < 0.001) and FIGO stage of CC (OR = 2.15, P = 0.003). Then, a pooled analysis of nine TCGA and GEO datasets, covering 13 CPG sites within DAPK1 promoter, identified eight CC-associated sites, six sites with diagnostic values for CC (pooled specificities: 74–90%; pooled sensitivities: 70–81%), nine loci associated with the histological type of CC, and all 13 loci with down-regulated effects on DAPK1 mRNA expression. Conclusion: The meta-analysis suggests that DAPK1 promoter hypermethylation is significantly associated with the disease severity of cervical neoplasia. DAPK1 methylation detection exhibits a promising ability to discriminate CC from cancer-free controls.
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Affiliation(s)
- Xue-Bin Wang
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Ning-Hua Cui
- Department of Clinical Laboratory, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, China
| | - Xia-Nan Liu
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jun-Fen Ma
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Qing-Hua Zhu
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Shu-Ren Guo
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jun-Wei Zhao
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Liang Ming
- Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Zheng SC, Webster AP, Dong D, Feber A, Graham DG, Sullivan R, Jevons S, Lovat LB, Beck S, Widschwendter M, Teschendorff AE. A novel cell-type deconvolution algorithm reveals substantial contamination by immune cells in saliva, buccal and cervix. Epigenomics 2018; 10:925-940. [DOI: 10.2217/epi-2018-0037] [Citation(s) in RCA: 82] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Aim: An outstanding challenge in epigenome studies is the estimation of cell-type proportions in complex epithelial tissues. Materials & methods: Here, we construct and validate a DNA methylation reference and algorithm for complex tissues that contain epithelial, immune and nonimmune stromal cells. Results: Using this reference, we show that easily accessible tissues such as saliva, buccal and cervix exhibit substantial variation in immune cell (IC) contamination. We further validate our reference in the context of oral cancer, where it correctly predicts an increased IC infiltration in cancer but suppressed in patients with highest smoking exposure. Finally, our method can improve the specificity of differentially methylated CpG calls in epithelial cancer. Conclusion: The degree and variation of IC contamination in complex epithelial tissues is substantial. We provide a valuable resource and tool for assessing the epithelial purity and IC contamination of samples and for identifying differential methylation in such complex tissues.
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Affiliation(s)
- Shijie C Zheng
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, 320 Yue Yang Road, Shanghai 200031, PR China
- University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, PR China
| | - Amy P Webster
- UCL Cancer Institute, Paul O'Gorman Building, University College London, 72 Huntley Street, London WC1E 6BT, UK
| | - Danyue Dong
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, 320 Yue Yang Road, Shanghai 200031, PR China
- University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, PR China
| | - Andy Feber
- Division of Surgery & Interventional Science, UCL, London WC1E 6BT, UK
| | - David G Graham
- Division of Surgery & Interventional Science, UCL, London WC1E 6BT, UK
| | - Roisin Sullivan
- Division of Surgery & Interventional Science, UCL, London WC1E 6BT, UK
| | - Sarah Jevons
- Division of Surgery & Interventional Science, UCL, London WC1E 6BT, UK
| | - Laurence B Lovat
- Division of Surgery & Interventional Science, UCL, London WC1E 6BT, UK
| | - Stephan Beck
- UCL Cancer Institute, Paul O'Gorman Building, University College London, 72 Huntley Street, London WC1E 6BT, UK
| | - Martin Widschwendter
- Department of Women's Cancer, University College London, 74 Huntley Street, London WC1E 6AU, UK
| | - Andrew E Teschendorff
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, 320 Yue Yang Road, Shanghai 200031, PR China
- Department of Women's Cancer, University College London, 74 Huntley Street, London WC1E 6AU, UK
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60
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Li X, Fu Y, Wang X, Qiu W. Robust joint score tests in the application of DNA methylation data analysis. BMC Bioinformatics 2018; 19:174. [PMID: 29776330 PMCID: PMC5960098 DOI: 10.1186/s12859-018-2185-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Accepted: 05/02/2018] [Indexed: 12/27/2022] Open
Abstract
Background Recently differential variability has been showed to be valuable in evaluating the association of DNA methylation to the risks of complex human diseases. The statistical tests based on both differential methylation level and differential variability can be more powerful than those based only on differential methylation level. Anh and Wang (2013) proposed a joint score test (AW) to simultaneously detect for differential methylation and differential variability. However, AW’s method seems to be quite conservative and has not been fully compared with existing joint tests. Results We proposed three improved joint score tests, namely iAW.Lev, iAW.BF, and iAW.TM, and have made extensive comparisons with the joint likelihood ratio test (jointLRT), the Kolmogorov-Smirnov (KS) test, and the AW test. Systematic simulation studies showed that: 1) the three improved tests performed better (i.e., having larger power, while keeping nominal Type I error rates) than the other three tests for data with outliers and having different variances between cases and controls; 2) for data from normal distributions, the three improved tests had slightly lower power than jointLRT and AW. The analyses of two Illumina HumanMethylation27 data sets GSE37020 and GSE20080 and one Illumina Infinium MethylationEPIC data set GSE107080 demonstrated that three improved tests had higher true validation rates than those from jointLRT, KS, and AW. Conclusions The three proposed joint score tests are robust against the violation of normality assumption and presence of outlying observations in comparison with other three existing tests. Among the three proposed tests, iAW.BF seems to be the most robust and effective one for all simulated scenarios and also in real data analyses. Electronic supplementary material The online version of this article (10.1186/s12859-018-2185-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Xuan Li
- Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, M3J1P3, Canada
| | - Yuejiao Fu
- Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, M3J1P3, Canada.
| | - Xiaogang Wang
- Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, M3J1P3, Canada
| | - Weiliang Qiu
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Avenue, Boston, 02115, USA
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Gao Y, Widschwendter M, Teschendorff AE. DNA Methylation Patterns in Normal Tissue Correlate more Strongly with Breast Cancer Status than Copy-Number Variants. EBioMedicine 2018; 31:243-252. [PMID: 29735413 PMCID: PMC6013931 DOI: 10.1016/j.ebiom.2018.04.025] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Revised: 04/25/2018] [Accepted: 04/27/2018] [Indexed: 02/07/2023] Open
Abstract
Normal tissue at risk of neoplastic transformation is characterized by somatic mutations, copy-number variation and DNA methylation changes. It is unclear however, which type of alteration may be more informative of cancer risk. We analyzed genome-wide DNA methylation and copy-number calls from the same DNA assay in a cohort of healthy breast samples and age-matched normal samples collected adjacent to breast cancer. Using statistical methods to adjust for cell type heterogeneity, we show that DNA methylation changes can discriminate normal-adjacent from normal samples better than somatic copy-number variants. We validate this important finding in an independent dataset. These results suggest that DNA methylation alterations in the normal cell of origin may offer better cancer risk prediction and early detection markers than copy-number changes.
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Affiliation(s)
- Yang Gao
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China
| | - Martin Widschwendter
- Department of Women's Cancer, University College London, 74 Huntley Street, London WC1E 6AU, United Kingdom
| | - Andrew E Teschendorff
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China; Department of Women's Cancer, University College London, 74 Huntley Street, London WC1E 6AU, United Kingdom; UCL Cancer Institute, Paul O'Gorman Building, University College London, 72 Huntley Street, London WC1E 6BT, United Kingdom.
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62
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Wijetunga NA, Ben-Dayan M, Tozour J, Burk RD, Schlecht NF, Einstein MH, Greally JM. A polycomb-mediated epigenetic field defect precedes invasive cervical carcinoma. Oncotarget 2018; 7:62133-62143. [PMID: 27557505 PMCID: PMC5308716 DOI: 10.18632/oncotarget.11390] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2016] [Accepted: 07/28/2016] [Indexed: 11/30/2022] Open
Abstract
Human papillomavirus (HPV)-associated cervical carcinoma is preceded by stages of cervical intra-epithelial neoplasia (CIN) that can variably progress to malignancy. Understanding the different molecular processes involved in the progression of pre-malignant CIN is critical to the development of improved predictive and interventional capabilities. We tested the role of regulators of transcription in both the development and the progression of HPV-associated CIN, performing the most comprehensive genomic survey to date of DNA methylation in HPV-associated cervical neoplasia, testing ~2 million loci throughout the human genome in biopsies from 78 HPV+ women, identifying changes starting in early CIN and maintained through carcinogenesis. We identified loci at which DNA methylation is consistently altered, beginning early in the course of neoplastic disease and progressing with disease advancement. While the loss of DNA methylation occurs mostly at intergenic regions, acquisition of DNA methylation is at sites involved in transcriptional regulation, with strong enrichment for targets of polycomb repression. Using an independent cohort from The Cancer Genome Atlas, we validated the loci with increased DNA methylation and found that these regulatory changes were associated with locally decreased gene expression. Secondary validation using immunohistochemistry showed that the progression of neoplasia was associated with increasing polycomb protein expression specifically in the cervical epithelium. We find that perturbations of genomic regulatory processes occur early and persist in cervical carcinoma. The results indicate a polycomb-mediated epigenetic field defect in cervical neoplasia that may represent a target for early, topical interventions using polycomb inhibitors.
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Affiliation(s)
- Neil Ari Wijetunga
- Department of Genetics and Center for Epigenomics, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Miriam Ben-Dayan
- Department of Genetics and Center for Epigenomics, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Jessica Tozour
- Department of Genetics and Center for Epigenomics, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Robert D Burk
- Department of Pediatrics (Genetics), Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Nicolas F Schlecht
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA.,Department of Medicine (Oncology), Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Mark H Einstein
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA.,Department of Obstetrics & Gynecology and Women's Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - John M Greally
- Department of Genetics and Center for Epigenomics, Albert Einstein College of Medicine, Bronx, NY 10461, USA.,Department of Pediatrics (Genetics), Albert Einstein College of Medicine, Bronx, NY 10461, USA
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63
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Cai Y, Lin JR, Zhang Q, O'Brien K, Montagna C, Zhang ZD. Epigenetic alterations to Polycomb targets precede malignant transition in a mouse model of breast cancer. Sci Rep 2018; 8:5535. [PMID: 29615825 PMCID: PMC5882905 DOI: 10.1038/s41598-018-24005-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2017] [Accepted: 03/26/2018] [Indexed: 12/16/2022] Open
Abstract
Malignant breast cancer remains a major health threat to women of all ages worldwide and epigenetic variations on DNA methylation have been widely reported in cancers of different types. We profiled DNA methylation with ERRBS (Enhanced Reduced Representation Bisulfite Sequencing) across four main stages of tumor progression in the MMTV-PyMT mouse model (hyperplasia, adenoma/mammary intraepithelial neoplasia, early carcinoma and late carcinoma), during which malignant transition occurs. We identified a large number of differentially methylated cytosines (DMCs) in tumors relative to age-matched normal mammary glands from FVB mice. Despite similarities, the methylation differences of the premalignant stages were distinct from the malignant ones. Many differentially methylated loci were preserved from the first to the last stage throughout tumor progression. Genes affected by methylation gains were enriched in Polycomb repressive complex 2 (PRC2) targets, which may present biomarkers for early diagnosis and targets for treatment.
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Affiliation(s)
- Ying Cai
- Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Jhih-Rong Lin
- Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Quanwei Zhang
- Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Kelly O'Brien
- Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Cristina Montagna
- Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, USA.,Department of Pathology, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Zhengdong D Zhang
- Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, USA.
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64
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Konno H, Yamauchi S, Berglund A, Putney RM, Mulé JJ, Barber GN. Suppression of STING signaling through epigenetic silencing and missense mutation impedes DNA damage mediated cytokine production. Oncogene 2018; 37:2037-2051. [PMID: 29367762 PMCID: PMC6029885 DOI: 10.1038/s41388-017-0120-0] [Citation(s) in RCA: 155] [Impact Index Per Article: 25.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Revised: 11/21/2017] [Accepted: 12/14/2017] [Indexed: 12/19/2022]
Abstract
The production of cytokines in response to DNA-damage events may be an important host defense response to help prevent the escape of pre-cancerous cells. The innate immune pathways involved in these events are known to be regulated by cellular molecules such as stimulator of interferon genes (STING), which controls type I interferon and pro-inflammatory cytokine production in response to the presence of microbial DNA or cytosolic DNA that has escaped from the nucleus. STING signaling has been shown to be defective in a variety of cancers, such as colon cancer and melanoma, actions that may enable damaged cells to escape the immunosurveillance system. Here, we report through examination of databases that STING signaling may be commonly suppressed in a greater variety of tumors due to loss-of-function mutation or epigenetic silencing of the STING/cGAS promoter regions. In comparison, RNA activated innate immune pathways controlled by RIG-I/MDA5 were significantly less affected. Examination of reported missense STING variants confirmed that many exhibited a loss-of-function phenotype and could not activate cytokine production following exposure to cytosolic DNA or DNA-damage events. Our data imply that the STING signaling pathway may be recurrently suppressed by a number of mechanisms in a considerable variety of malignant disease and be a requirement for cellular transformation.
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Affiliation(s)
- Hiroyasu Konno
- Department of Cell Biology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Shota Yamauchi
- Department of Cell Biology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Anders Berglund
- Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA
| | - Ryan M Putney
- Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA
| | - James J Mulé
- Cutaneous Oncology, Moffitt Cancer Center, Tampa, FL, USA
- Immunology Programs, Moffitt Cancer Center, Tampa, FL, USA
| | - Glen N Barber
- Department of Cell Biology, University of Miami Miller School of Medicine, Miami, FL, USA.
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65
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Widschwendter M, Jones A, Evans I, Reisel D, Dillner J, Sundström K, Steyerberg EW, Vergouwe Y, Wegwarth O, Rebitschek FG, Siebert U, Sroczynski G, de Beaufort ID, Bolt I, Cibula D, Zikan M, Bjørge L, Colombo N, Harbeck N, Dudbridge F, Tasse AM, Knoppers BM, Joly Y, Teschendorff AE, Pashayan N. Epigenome-based cancer risk prediction: rationale, opportunities and challenges. Nat Rev Clin Oncol 2018; 15:292-309. [PMID: 29485132 DOI: 10.1038/nrclinonc.2018.30] [Citation(s) in RCA: 103] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The incidence of cancer is continuing to rise and risk-tailored early diagnostic and/or primary prevention strategies are urgently required. The ideal risk-predictive test should: integrate the effects of both genetic and nongenetic factors and aim to capture these effects using an approach that is both biologically stable and technically reproducible; derive a score from easily accessible biological samples that acts as a surrogate for the organ in question; and enable the effectiveness of risk-reducing measures to be monitored. Substantial evidence has accumulated suggesting that the epigenome and, in particular, DNA methylation-based tests meet all of these requirements. However, the development and implementation of DNA methylation-based risk-prediction tests poses considerable challenges. In particular, the cell type specificity of DNA methylation and the extensive cellular heterogeneity of the easily accessible surrogate cells that might contain information relevant to less accessible tissues necessitates the use of novel methods in order to account for these confounding issues. Furthermore, the engagement of the scientific community with health-care professionals, policymakers and the public is required in order to identify and address the organizational, ethical, legal, social and economic challenges associated with the routine use of epigenetic testing.
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Affiliation(s)
- Martin Widschwendter
- Department of Women's Cancer, Institute for Women's Health, University College London, London, UK
| | - Allison Jones
- Department of Women's Cancer, Institute for Women's Health, University College London, London, UK
| | - Iona Evans
- Department of Women's Cancer, Institute for Women's Health, University College London, London, UK
| | - Daniel Reisel
- Department of Women's Cancer, Institute for Women's Health, University College London, London, UK
| | - Joakim Dillner
- Department of Laboratory Medicine, Karolinska Institutet, Stockholm, Sweden.,Karolinska University Laboratory, Karolinska University Hospital, Stockholm, Sweden
| | - Karin Sundström
- Department of Laboratory Medicine, Karolinska Institutet, Stockholm, Sweden.,Karolinska University Laboratory, Karolinska University Hospital, Stockholm, Sweden
| | - Ewout W Steyerberg
- Center for Medical Decision Sciences, Department of Public Health, Erasmus MC, Rotterdam, Netherlands.,Department of Biomedical Data Sciences, LUMC, Leiden, Netherlands
| | - Yvonne Vergouwe
- Center for Medical Decision Sciences, Department of Public Health, Erasmus MC, Rotterdam, Netherlands
| | - Odette Wegwarth
- Max Planck Institute for Human Development, Harding Center for Risk Literacy, Berlin, Germany.,Max Planck Institute for Human Development, Center for Adaptive Rationality, Berlin, Germany
| | - Felix G Rebitschek
- Max Planck Institute for Human Development, Harding Center for Risk Literacy, Berlin, Germany
| | - Uwe Siebert
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research, and HTA, UMIT-University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria.,Harvard T. C. Chan School of Public Health, Center for Health Decision Science, Department of Health Policy and Management, Boston, MA, USA.,Oncotyrol: Center for Personalized Medicine, Innsbruck, Austria
| | - Gaby Sroczynski
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research, and HTA, UMIT-University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
| | - Inez D de Beaufort
- Department of Medical Ethics and Philosophy of Medicine, Erasmus Medical Center, Rotterdam, Netherlands
| | - Ineke Bolt
- Department of Medical Ethics and Philosophy of Medicine, Erasmus Medical Center, Rotterdam, Netherlands
| | - David Cibula
- Department of Obstetrics and Gynaecology, First Medical Faculty of the Charles University and General Faculty Hospital, Prague, Czech Republic
| | - Michal Zikan
- Department of Obstetrics and Gynaecology, First Medical Faculty of the Charles University and General Faculty Hospital, Prague, Czech Republic
| | - Line Bjørge
- Department of Obstetrics and Gynecology, Haukeland University Hospital, and Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Nicoletta Colombo
- European Institute of Oncology and University Milan-Bicocca, Milan, Italy
| | - Nadia Harbeck
- Breast Center, Department of Gynaecology and Obstetrics, University of Munich (LMU), Munich, Germany
| | - Frank Dudbridge
- Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.,Department of Health Sciences, University of Leicester, Leicester, UK
| | - Anne-Marie Tasse
- Public Population Project in Genomics and Society, McGill University and Genome Quebec Innovation Centre, Montreal, Canada
| | | | - Yann Joly
- Centre of Genomics and Policy, McGill University, Montreal, Canada
| | - Andrew E Teschendorff
- Department of Women's Cancer, Institute for Women's Health, University College London, London, UK
| | - Nora Pashayan
- Department of Applied Health Research, Institute of Epidemiology and Healthcare, University College London, UK
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Joyce BT, Zheng Y, Zhang Z, Liu L, Kocherginsky M, Murphy R, Achenbach CJ, Musa J, Wehbe F, Just A, Shen J, Vokonas P, Schwartz J, Baccarelli AA, Hou L. miRNA-Processing Gene Methylation and Cancer Risk. Cancer Epidemiol Biomarkers Prev 2018; 27:550-557. [PMID: 29475968 DOI: 10.1158/1055-9965.epi-17-0849] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2017] [Revised: 12/06/2017] [Accepted: 02/02/2018] [Indexed: 12/20/2022] Open
Abstract
Background: Dysregulation of miRNA and methylation levels are epigenetic hallmarks of cancer, potentially linked via miRNA-processing genes. Studies have found genetic alterations to miRNA-processing genes in cancer cells and human population studies. Our objective was to prospectively examine changes in DNA methylation of miRNA-processing genes and their associations with cancer risk.Methods: We examined cohort data from the Department of Veterans' Affairs Normative Aging Study. Participants were assessed every 3 to 5 years starting in 1999 through 2013 including questionnaires, medical record review, and blood collection. Blood from 686 consenting participants was analyzed using the Illumina 450K BeadChip array to measure methylation at CpG sites throughout the genome. We selected 19 genes based on a literature review, with 519 corresponding CpG sites. We then used Cox proportional hazards models to examine associations with cancer incidence, and generalized estimating equations to examine associations with cancer prevalence. Associations at false discovery rate < 0.05 were considered statistically significant.Results: Methylation of three CpGs (DROSHA: cg23230564, TNRC6B: cg06751583, and TNRC6B: cg21034183) was prospectively associated with time to cancer development (positively for cg06751583, inversely for cg23230564 and cg21034183), whereas methylation of one CpG site (DROSHA: cg16131300) was positively associated with cancer prevalence.Conclusions: DNA methylation of DROSHA, a key miRNA-processing gene, and TNRC6B may play a role in early carcinogenesis.Impact: Changes in miRNA processing may exert multiple effects on cancer development, including protecting against it via altered global miRNAs, and may be a useful early detection biomarker of cancer. Cancer Epidemiol Biomarkers Prev; 27(5); 550-7. ©2018 AACR.
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Affiliation(s)
- Brian T Joyce
- Center for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
| | - Yinan Zheng
- Center for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.,Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Zhou Zhang
- Center for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Lei Liu
- Center for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.,Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Masha Kocherginsky
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Robert Murphy
- Center for Global Health, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Chad J Achenbach
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Jonah Musa
- Center for Global Health, Northwestern University Feinberg School of Medicine, Chicago, Illinois.,Health Sciences Integrated Program, Center for Healthcare Studies, Institute of Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.,Department of Obstetrics and Gynecology, Faculty of Medical Sciences, University of Jos, Plateau State, Nigeria
| | - Firas Wehbe
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Allan Just
- Department of Preventive Medicine, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Jincheng Shen
- Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, Utah
| | - Pantel Vokonas
- VA Normative Aging Study, Veterans Affairs Boston Healthcare System and the Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Andrea A Baccarelli
- Departments of Epidemiology and Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York
| | - Lifang Hou
- Center for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.,Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois
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67
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Genetic and epigenetic alterations in normal tissues have differential impacts on cancer risk among tissues. Proc Natl Acad Sci U S A 2018; 115:1328-1333. [PMID: 29358395 DOI: 10.1073/pnas.1717340115] [Citation(s) in RCA: 62] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Genetic and epigenetic alterations are both involved in carcinogenesis, and their low-level accumulation in normal tissues constitutes cancer risk. However, their relative importance has never been examined, as measurement of low-level mutations has been difficult. Here, we measured low-level accumulations of genetic and epigenetic alterations in normal tissues with low, intermediate, and high cancer risk and analyzed their relative effects on cancer risk in the esophagus and stomach. Accumulation of genetic alterations, estimated as a frequency of rare base substitution mutations, significantly increased according to cancer risk in esophageal mucosae, but not in gastric mucosae. The mutation patterns reflected the exposure to lifestyle risk factors. In contrast, the accumulation of epigenetic alterations, measured as DNA methylation levels of marker genes, significantly increased according to cancer risk in both tissues. Patients with cancer (high-risk individuals) were precisely discriminated from healthy individuals with exposure to risk factors (intermediate-risk individuals) by a combination of alterations in the esophagus (odds ratio, 18.2; 95% confidence interval, 3.69-89.9) and by only epigenetic alterations in the stomach (odds ratio, 7.67; 95% confidence interval, 2.52-23.3). The relative importance of epigenetic alterations upon genetic alterations was 1.04 in the esophagus and 2.31 in the stomach. The differential impacts among tissues will be critically important for effective cancer prevention and precision cancer risk diagnosis.
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68
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Beeravolu N, Brougham J, Khan I, McKee C, Perez-Cruet M, Chaudhry GR. Human umbilical cord derivatives regenerate intervertebral disc. J Tissue Eng Regen Med 2018; 12:e579-e591. [PMID: 27690334 DOI: 10.1002/term.2330] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Revised: 08/03/2016] [Accepted: 09/26/2016] [Indexed: 09/11/2024]
Abstract
Intervertebral disc (IVD) degeneration is characterized by the loss of nucleus pulposus (NP), which is a common cause for lower back pain. Although, currently, there is no cure for the degenerative disc disease, stem cell therapy is increasingly being considered for its treatment. In this study, we investigated the feasibility and efficacy of human umbilical cord mesenchymal stem cells (MSCs) and chondroprogenitor cells (CPCs) derived from those cells to regenerate damaged IVD in a rabbit model. Transplanted cells survived, engrafted and dispersed into NP in situ. Significant improvement in the histology, cellularity, extracellular matrix proteins, and water and glycosaminoglycan contents in IVD recipients of CPCs was observed compared to MSCs. In addition, IVDs receiving CPCs exhibited higher expression of NP-specific human markers, SOX9, aggrecan, collagen 2, FOXF1 and KRT19. The novelty of the study is that in vitro differentiated CPCs derived from umbilical cord MSCs, demonstrated far greater capacity to regenerate damaged IVDs, which provides basis and impetus for stem cell based clinical studies to treat degenerative disc disease. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Naimisha Beeravolu
- Department of Biological Sciences, Oakland University, Rochester, Michigan, USA
- OUWB Institute for Stem Cell and Regenerative Medicine, Rochester, Michigan, USA
| | - Jared Brougham
- OUWB School of Medicine, Oakland University, Rochester, Michigan, USA
| | - Irfan Khan
- Department of Biological Sciences, Oakland University, Rochester, Michigan, USA
- OUWB Institute for Stem Cell and Regenerative Medicine, Rochester, Michigan, USA
- Dr Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, Pakistan
| | - Christina McKee
- Department of Biological Sciences, Oakland University, Rochester, Michigan, USA
- OUWB Institute for Stem Cell and Regenerative Medicine, Rochester, Michigan, USA
| | - Mick Perez-Cruet
- OUWB Institute for Stem Cell and Regenerative Medicine, Rochester, Michigan, USA
- Beaumont Health System, Royal Oak, Michigan, USA
| | - G Rasul Chaudhry
- Department of Biological Sciences, Oakland University, Rochester, Michigan, USA
- OUWB Institute for Stem Cell and Regenerative Medicine, Rochester, Michigan, USA
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Widschwendter M, Zikan M, Wahl B, Lempiäinen H, Paprotka T, Evans I, Jones A, Ghazali S, Reisel D, Eichner J, Rujan T, Yang Z, Teschendorff AE, Ryan A, Cibula D, Menon U, Wittenberger T. The potential of circulating tumor DNA methylation analysis for the early detection and management of ovarian cancer. Genome Med 2017; 9:116. [PMID: 29268796 PMCID: PMC5740748 DOI: 10.1186/s13073-017-0500-7] [Citation(s) in RCA: 109] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2017] [Accepted: 11/24/2017] [Indexed: 02/07/2023] Open
Abstract
Background Despite a myriad of attempts in the last three decades to diagnose ovarian cancer (OC) earlier, this clinical aim still remains a significant challenge. Aberrant methylation patterns of linked CpGs analyzed in DNA fragments shed by cancers into the bloodstream (i.e. cell-free DNA) can provide highly specific signals indicating cancer presence. Methods We analyzed 699 cancerous and non-cancerous tissues using a methylation array or reduced representation bisulfite sequencing to discover the most specific OC methylation patterns. A three-DNA-methylation-serum-marker panel was developed using targeted ultra-high coverage bisulfite sequencing in 151 women and validated in 250 women with various conditions, particularly in those associated with high CA125 levels (endometriosis and other benign pelvic masses), serial samples from 25 patients undergoing neoadjuvant chemotherapy, and a nested case control study of 172 UKCTOCS control arm participants which included serum samples up to two years before OC diagnosis. Results The cell-free DNA amount and average fragment size in the serum samples was up to ten times higher than average published values (based on samples that were immediately processed) due to leakage of DNA from white blood cells owing to delayed time to serum separation. Despite this, the marker panel discriminated high grade serous OC patients from healthy women or patients with a benign pelvic mass with specificity/sensitivity of 90.7% (95% confidence interval [CI] = 84.3–94.8%) and 41.4% (95% CI = 24.1–60.9%), respectively. Levels of all three markers plummeted after exposure to chemotherapy and correctly identified 78% and 86% responders and non-responders (Fisher’s exact test, p = 0.04), respectively, which was superior to a CA125 cut-off of 35 IU/mL (20% and 75%). 57.9% (95% CI 34.0–78.9%) of women who developed OC within two years of sample collection were identified with a specificity of 88.1% (95% CI = 77.3–94.3%). Sensitivity and specificity improved further when specifically analyzing CA125 negative samples only (63.6% and 87.5%, respectively). Conclusions Our data suggest that DNA methylation patterns in cell-free DNA have the potential to detect a proportion of OCs up to two years in advance of diagnosis and may potentially guide personalized treatment. The prospective use of novel collection vials, which stabilize blood cells and reduce background DNA contamination in serum/plasma samples, will facilitate clinical implementation of liquid biopsy analyses. Electronic supplementary material The online version of this article (doi:10.1186/s13073-017-0500-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Martin Widschwendter
- Department of Women's Cancer, UCL Elizabeth Garrett Anderson Institute for Women's Health, University College London, Medical School Building, Room 340, 74 Huntley Street, London, WC1E 6AU, UK.
| | - Michal Zikan
- Gynaecologic Oncology Center, Department of Obstetrics & Gynaecology, First Faculty of Medicine & General University Hospital, Charles University, Prague, Czech Republic
| | - Benjamin Wahl
- GATC Biotech AG, Jakob-Stadler-Platz 7, 78467, Konstanz, Germany
| | | | - Tobias Paprotka
- GATC Biotech AG, Jakob-Stadler-Platz 7, 78467, Konstanz, Germany
| | - Iona Evans
- Department of Women's Cancer, UCL Elizabeth Garrett Anderson Institute for Women's Health, University College London, Medical School Building, Room 340, 74 Huntley Street, London, WC1E 6AU, UK
| | - Allison Jones
- Department of Women's Cancer, UCL Elizabeth Garrett Anderson Institute for Women's Health, University College London, Medical School Building, Room 340, 74 Huntley Street, London, WC1E 6AU, UK
| | - Shohreh Ghazali
- Department of Women's Cancer, UCL Elizabeth Garrett Anderson Institute for Women's Health, University College London, Medical School Building, Room 340, 74 Huntley Street, London, WC1E 6AU, UK
| | - Daniel Reisel
- Department of Women's Cancer, UCL Elizabeth Garrett Anderson Institute for Women's Health, University College London, Medical School Building, Room 340, 74 Huntley Street, London, WC1E 6AU, UK
| | | | - Tamas Rujan
- Genedata AG, Margarethenstrasse 38, 4053, Basel, Switzerland
| | - Zhen Yang
- CAS Max-Planck Partner Institute for Computational Biology, Shanghai Institute of Biological Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Andrew E Teschendorff
- Department of Women's Cancer, UCL Elizabeth Garrett Anderson Institute for Women's Health, University College London, Medical School Building, Room 340, 74 Huntley Street, London, WC1E 6AU, UK.,CAS Max-Planck Partner Institute for Computational Biology, Shanghai Institute of Biological Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Andy Ryan
- Department of Women's Cancer, UCL Elizabeth Garrett Anderson Institute for Women's Health, University College London, Medical School Building, Room 340, 74 Huntley Street, London, WC1E 6AU, UK
| | - David Cibula
- Gynaecologic Oncology Center, Department of Obstetrics & Gynaecology, First Faculty of Medicine & General University Hospital, Charles University, Prague, Czech Republic
| | - Usha Menon
- Department of Women's Cancer, UCL Elizabeth Garrett Anderson Institute for Women's Health, University College London, Medical School Building, Room 340, 74 Huntley Street, London, WC1E 6AU, UK
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Ecker S, Pancaldi V, Valencia A, Beck S, Paul DS. Epigenetic and Transcriptional Variability Shape Phenotypic Plasticity. Bioessays 2017; 40. [PMID: 29251357 DOI: 10.1002/bies.201700148] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2017] [Revised: 10/31/2017] [Indexed: 12/15/2022]
Abstract
Epigenetic and transcriptional variability contribute to the vast diversity of cellular and organismal phenotypes and are key in human health and disease. In this review, we describe different types, sources, and determinants of epigenetic and transcriptional variability, enabling cells and organisms to adapt and evolve to a changing environment. We highlight the latest research and hypotheses on how chromatin structure and the epigenome influence gene expression variability. Further, we provide an overview of challenges in the analysis of biological variability. An improved understanding of the molecular mechanisms underlying epigenetic and transcriptional variability, at both the intra- and inter-individual level, provides great opportunity for disease prevention, better therapeutic approaches, and personalized medicine.
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Affiliation(s)
- Simone Ecker
- UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT, UK
| | - Vera Pancaldi
- Barcelona Supercomputing Center (BSC), C/ Jordi Girona 39-31, 08034, Barcelona, Spain
| | - Alfonso Valencia
- Barcelona Supercomputing Center (BSC), C/ Jordi Girona 39-31, 08034, Barcelona, Spain.,ICREA, Pg. Lluís Companys 23, 08010, Barcelona, Spain
| | - Stephan Beck
- UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT, UK
| | - Dirk S Paul
- MRC/BHF Cardiovascular Epidemiology Unit Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK.,Department of Human Genetics Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1HH, UK
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71
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Hentze JL, Høgdall C, Kjær SK, Blaakær J, Høgdall E. Searching for new biomarkers in ovarian cancer patients: Rationale and design of a retrospective study under the Mermaid III project. Contemp Clin Trials Commun 2017; 8:167-174. [PMID: 29696206 PMCID: PMC5898550 DOI: 10.1016/j.conctc.2017.10.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Revised: 09/28/2017] [Accepted: 10/04/2017] [Indexed: 02/06/2023] Open
Abstract
Ovarian cancer is a silent killer and, due to late diagnosis, the primary cause of death amongst gynecological cancers, killing approximately 376 women annually in Denmark. The discovery of a specific and sensitive biomarker for ovarian cancer could improve early diagnosis, but also treatment, by predicting which patients will benefit from specific treatment strategies. The Mermaid III project is consisting of 3 parts including "Early detection, screening and long-term survival," "Biomarkers and/or prognostic markers" and "The infection theory." The present paper gives an overview of the part regarding biomarkers and/or prognostic markers, with a focus on rationale and design. The study described has 3 major branches: microRNAs, epigenetics and Next Generation Sequencing. Tissue and blood from ovarian cancer patients, already enrolled in the prospective ongoing pelvic mass cohort, will be examined. Relevant microRNAs and DNA methylation patterns will be investigated using array technology. Patient exomes will be fully sequenced, and identified genetic variations will be validated with Next Generation Sequencing. In all cases, data will be correlated with clinical information on the patient, in order to identify possible biomarkers. A thorough investigation of biomarkers in ovarian cancer, including large numbers of different markers, has never been done before. Besides from improving diagnosis and treatment, other outcomes could be markers for screening, knowledge of the molecular aspects of cancer and the discovery of new drugs. Moreover, biomarkers are a prerequisite for the development of precision medicine. This study will attack the ovarian cancer problem from several angles, thereby increasing the chance of successfully contributing to saving lives.
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Key Words
- CA125, Cancer Antigen 125
- CPH-I, Copenhagen Index
- DGCD, Danish Gynecologic Cancer Database
- Diagnostic/prognostic biomarkers
- Epigenetics
- FFPE, Formalin fixed and paraffin embedded
- FIGO, International Federation of Gynecology and Obstetrics
- HE4, Human Epididymis Protein 4
- MALOVA, MALignant OVArian cancer study
- MicroRNA
- NGS, Next Generation Sequencing
- Next Generation Sequencing
- O.C.T., Optimal cutting temperature
- OC, Ovarian cancer
- OS, Overall survival
- Ovarian cancer
- PARP, poly(adenosine diphosphate [ADP]-ribose) polymerase
- PFS, Progression free survival
- RMI, Risk of Malignancy Index
- ROCA, Risk of Ovarian Cancer Algorithm
- ROMA, Risk of Ovarian Malignancy Algorithm
- UKCTOCS, UK Collaborative Trial of OC Screening
- miRNAs, MicroRNAs
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Affiliation(s)
- Julie L. Hentze
- Department of Pathology, Herlev Hospital, Herlev, Copenhagen University Hospital, Denmark
| | - Claus Høgdall
- Department of Gynecology, The Juliane Marie Centre, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Susanne K. Kjær
- Department of Gynecology, The Juliane Marie Centre, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
- Unit of Virus, Lifestyle, and Genes, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Jan Blaakær
- Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Estrid Høgdall
- Department of Pathology, Herlev Hospital, Herlev, Copenhagen University Hospital, Denmark
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72
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Statistical and integrative system-level analysis of DNA methylation data. Nat Rev Genet 2017; 19:129-147. [PMID: 29129922 DOI: 10.1038/nrg.2017.86] [Citation(s) in RCA: 168] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Epigenetics plays a key role in cellular development and function. Alterations to the epigenome are thought to capture and mediate the effects of genetic and environmental risk factors on complex disease. Currently, DNA methylation is the only epigenetic mark that can be measured reliably and genome-wide in large numbers of samples. This Review discusses some of the key statistical challenges and algorithms associated with drawing inferences from DNA methylation data, including cell-type heterogeneity, feature selection, reverse causation and system-level analyses that require integration with other data types such as gene expression, genotype, transcription factor binding and other epigenetic information.
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73
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Barrow TM, Klett H, Toth R, Böhm J, Gigic B, Habermann N, Scherer D, Schrotz-King P, Skender S, Abbenhardt-Martin C, Zielske L, Schneider M, Ulrich A, Schirmacher P, Herpel E, Brenner H, Busch H, Boerries M, Ulrich CM, Michels KB. Smoking is associated with hypermethylation of the APC 1A promoter in colorectal cancer: the ColoCare Study. J Pathol 2017; 243:366-375. [PMID: 28791728 DOI: 10.1002/path.4955] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2016] [Revised: 07/02/2017] [Accepted: 08/01/2017] [Indexed: 12/22/2022]
Abstract
Smoking tobacco is a known risk factor for the development of colorectal cancer and for mortality associated with the disease. Smoking has been reported to be associated with changes in DNA methylation in blood and in lung tumour tissues, although there has been scant investigation of how epigenetic factors may be implicated in the increased risk of developing colorectal cancer. To identify epigenetic changes associated with smoking behaviours, we performed epigenome-wide analysis of DNA methylation in colorectal tumours from 36 never-smokers, 47 former smokers, and 13 active smokers, and in adjacent mucosa from 49 never-smokers, 64 former smokers, and 18 active smokers. Our analyses identified 15 CpG sites within the APC 1A promoter that were significantly hypermethylated and 14 CpG loci within the NFATC1 gene body that were significantly hypomethylated (pLIS < 1 × 10-5 ) in the tumours of active smokers. The APC 1A promoter was hypermethylated in 7 of 36 tumours from never-smokers (19%), 12 of 47 tumours from former smokers (26%), and 8 of 13 tumours from active smokers (62%). Promoter hypermethylation was positively associated with duration of smoking (Spearman rank correlation, ρ = 0.26, p = 0.03) and was confined to tumours, with hypermethylation never being observed in adjacent mucosa. Further analysis of adjacent mucosa revealed significant hypomethylation of four loci associated with the TNXB gene in tissue from active smokers. Our findings provide exploratory evidence for hypermethylation of the key tumour suppressor gene APC being implicated in smoking-associated colorectal carcinogenesis. Further work is required to establish the validity of our observations in independent cohorts. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
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Affiliation(s)
- Timothy M Barrow
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Hagen Klett
- German Cancer Consortium (DKTK), Heidelberg, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany.,Institute of Molecular Medicine and Cell Research, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Reka Toth
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Division of Preventive Oncology, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jürgen Böhm
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Division of Preventive Oncology, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Biljana Gigic
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Division of Preventive Oncology, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Surgical Oncology, University Clinic Heidelberg, Heidelberg, Germany
| | - Nina Habermann
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Division of Preventive Oncology, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Dominique Scherer
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Division of Preventive Oncology, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Germany
| | - Petra Schrotz-King
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Division of Preventive Oncology, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stephanie Skender
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Division of Preventive Oncology, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Clare Abbenhardt-Martin
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Division of Preventive Oncology, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Lin Zielske
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Division of Preventive Oncology, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Martin Schneider
- Department of Surgical Oncology, University Clinic Heidelberg, Heidelberg, Germany
| | - Alexis Ulrich
- Department of Surgical Oncology, University Clinic Heidelberg, Heidelberg, Germany
| | - Peter Schirmacher
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Department of General Pathology, University Clinic Heidelberg, Heidelberg, Germany
| | - Esther Herpel
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Department of General Pathology, University Clinic Heidelberg, Heidelberg, Germany
| | - Hermann Brenner
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Division of Preventive Oncology, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Hauke Busch
- Institute of Molecular Medicine and Cell Research, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.,Lübeck Institute of Experimental Dermatology and Institute of Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Melanie Boerries
- German Cancer Consortium (DKTK), Heidelberg, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany.,Institute of Molecular Medicine and Cell Research, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Cornelia M Ulrich
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Division of Preventive Oncology, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Population Sciences, Huntsman Cancer Institute, Salt Lake City, Utah, USA
| | - Karin B Michels
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.,Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, California, USA
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74
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Wang Y, Teschendorff AE, Widschwendter M, Wang S. Accounting for differential variability in detecting differentially methylated regions. Brief Bioinform 2017; 20:47-57. [DOI: 10.1093/bib/bbx097] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2017] [Indexed: 12/11/2022] Open
Affiliation(s)
- Ya Wang
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Andrew E Teschendorff
- Department of Women's Cancer, University College London, London, UK
- CAS Key Lab of Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
- Statistical Cancer Genomics, UCL Cancer Institute, University College London, London, UK
| | | | - Shuang Wang
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
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75
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Establishment of a Strong Link Between Smoking and Cancer Pathogenesis through DNA Methylation Analysis. Sci Rep 2017; 7:1811. [PMID: 28500316 PMCID: PMC5431893 DOI: 10.1038/s41598-017-01856-4] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2016] [Accepted: 04/03/2017] [Indexed: 12/21/2022] Open
Abstract
Smoking is a well-documented risk factor in various cancers, especially lung cancer. In the current study, we tested the hypothesis that abnormal DNAm loci associated with smoking are enriched in genes and pathways that convey a risk of cancer by determining whether smoking-related methylated genes led to enrichment in cancer-related pathways. We analyzed two sets of smoking-related methylated genes from 28 studies originating from blood and buccal samples. By analyzing 320 methylated genes from 26 studies on blood samples (N = 17,675), we found 57 enriched pathways associated with different types of cancer (FDR < 0.05). Of these, 11 were also significantly overrepresented in the 661 methylated genes from two studies of buccal samples (N = 1,002). We further found the aryl hydrocarbon receptor signaling pathway plays an important role in the initiation of smoking-attributable cancer. Finally, we constructed a subnetwork of genes important for smoking-attributable cancer from the 48 non-redundant genes in the 11 oncogenic pathways. Of these, genes such as DUSP4 and AKT3 are well documented as being involved in smoking-related lung cancer. In summary, our findings provide robust and systematic evidence in support of smoking’s impact on the epigenome, which may be an important contributor to cancer.
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76
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Beeravolu N, McKee C, Alamri A, Mikhael S, Brown C, Perez-Cruet M, Chaudhry GR. Isolation and Characterization of Mesenchymal Stromal Cells from Human Umbilical Cord and Fetal Placenta. J Vis Exp 2017. [PMID: 28447991 PMCID: PMC5564456 DOI: 10.3791/55224] [Citation(s) in RCA: 56] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
The human umbilical cord (UC) and placenta are non-invasive, primitive and abundant sources of mesenchymal stromal cells (MSCs) that have increasingly gained attention because they do not pose any ethical or moral concerns. Current methods to isolate MSCs from UC yield low amounts of cells with variable proliferation potentials. Since UC is an anatomically-complex organ, differences in MSC properties may be due to the differences in the anatomical regions of their isolation. In this study, we first dissected the cord/placenta samples into three discrete anatomical regions: UC, cord-placenta junction (CPJ), and fetal placenta (FP). Second, two distinct zones, cord lining (CL) and Wharton's jelly (WJ), were separated. The explant culture technique was then used to isolate cells from the four sources. The time required for the primary culture of cells from the explants varied depending on the source of the tissue. Outgrowth of the cells occurred within 3 - 4 days of the CPJ explants, whereas growth was observed after 7 - 10 days and 11 - 14 days from CL/WJ and FP explants, respectively. The isolated cells were adherent to plastic and displayed fibroblastoid morphology and surface markers, such as CD29, CD44, CD73, CD90, and CD105, similarly to bone marrow (BM)-derived MSCs. However, the colony-forming efficiency of the cells varied, with CPJ-MSCs and WJ-MSCs showing higher efficiency than BM-MSCs. MSCs from all four sources differentiated into adipogenic, chondrogenic, and osteogenic lineages, indicating that they were multipotent. CPJ-MSCs differentiated more efficiently in comparison to other MSC sources. These results suggest that the CPJ is the most potent anatomical region and yields a higher number of cells, with greater proliferation and self-renewal capacities in vitro. In conclusion, the comparative analysis of the MSCs from the four sources indicated that CPJ is a more promising source of MSCs for cell therapy, regenerative medicine, and tissue engineering.
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Affiliation(s)
- Naimisha Beeravolu
- Department of Biological Sciences, Oakland University; OU-WB Institute for Stem Cell and Regenerative Medicine
| | - Christina McKee
- Department of Biological Sciences, Oakland University; OU-WB Institute for Stem Cell and Regenerative Medicine
| | - Ali Alamri
- Department of Biological Sciences, Oakland University; OU-WB Institute for Stem Cell and Regenerative Medicine
| | - Sasha Mikhael
- Department of Obstetrics and Gynecology, St. John Provindence - Providence Park Hospital
| | - Christina Brown
- Department of Biological Sciences, Oakland University; OU-WB Institute for Stem Cell and Regenerative Medicine
| | - Mick Perez-Cruet
- OU-WB Institute for Stem Cell and Regenerative Medicine; Department of Neurosurgery, Beaumont Health System
| | - G Rasul Chaudhry
- Department of Biological Sciences, Oakland University; OU-WB Institute for Stem Cell and Regenerative Medicine;
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77
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Hong C, Ning Y, Wang S, Wu H, Carroll RJ, Chen Y. PLMET: A Novel Pseudolikelihood-Based EM Test for Homogeneity in Generalilzed Exponential Tilt Mixture Models. J Am Stat Assoc 2017; 112:1393-1404. [PMID: 29416190 PMCID: PMC5798902 DOI: 10.1080/01621459.2017.1280405] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2014] [Revised: 10/01/2016] [Indexed: 10/20/2022]
Abstract
Motivated by analyses of DNA methylation data, we propose a semiparametric mixture model, namely the generalized exponential tilt mixture model, to account for heterogeneity between differentially methylated and non-differentially methylated subjects in the cancer group, and capture the differences in higher order moments (e.g. mean and variance) between subjects in cancer and normal groups. A pairwise pseudolikelihood is constructed to eliminate the unknown nuisance function. To circumvent boundary and non-identifiability problems as in parametric mixture models, we modify the pseudolikelihood by adding a penalty function. In addition, the test with simple asymptotic distribution has computational advantages compared with permutation-based test for high-dimensional genetic or epigenetic data. We propose a pseudolikelihood based expectation-maximization test, and show the proposed test follows a simple chi-squared limiting distribution. Simulation studies show that the proposed test controls Type I errors well and has better power compared to several current tests. In particular, the proposed test outperforms the commonly used tests under all simulation settings considered, especially when there are variance differences between two groups. The proposed test is applied to a real data set to identify differentially methylated sites between ovarian cancer subjects and normal subjects.
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Affiliation(s)
- Chuan Hong
- Department of Biostatistics, Harvard University School of Public Health,
Boston, MA 02115, USA
| | - Yang Ning
- Department of Statistical Science, Cornell University, Ithaca, NY 14853,
USA
| | - Shuang Wang
- Department of Biostatistics, Mailman School of Public Health, Columbia
University, New York, NY 10027, USA
| | - Hao Wu
- Department of Biostatistics and Bioinformatics, Rollins School of Public
Health, Emory University, Atlanta, GA 30322, USA
| | - Raymond J. Carroll
- Department of Statistics, Texas A&M University, College Station, TX
77843-3143, USA
| | - Yong Chen
- Department of Biostatistics and Epidemiology, University of Pennsylvania,
Philadelphia, PA 19104, USA
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78
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Ma X, Liu Z, Zhang Z, Huang X, Tang W. Multiple network algorithm for epigenetic modules via the integration of genome-wide DNA methylation and gene expression data. BMC Bioinformatics 2017; 18:72. [PMID: 28137264 PMCID: PMC5282853 DOI: 10.1186/s12859-017-1490-6] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2016] [Accepted: 01/20/2017] [Indexed: 02/05/2023] Open
Abstract
Background With the increase in the amount of DNA methylation and gene expression data, the epigenetic mechanisms of cancers can be extensively investigate. Available methods integrate the DNA methylation and gene expression data into a network by specifying the anti-correlation between them. However, the correlation between methylation and expression is usually unknown and difficult to determine. Results To address this issue, we present a novel multiple network framework for epigenetic modules, namely, Epigenetic Module based on Differential Networks (EMDN) algorithm, by simultaneously analyzing DNA methylation and gene expression data. The EMDN algorithm prevents the specification of the correlation between methylation and expression. The accuracy of EMDN algorithm is more efficient than that of modern approaches. On the basis of The Cancer Genome Atlas (TCGA) breast cancer data, we observe that the EMDN algorithm can recognize positively and negatively correlated modules and these modules are significantly more enriched in the known pathways than those obtained by other algorithms. These modules can serve as bio-markers to predict breast cancer subtypes by using methylation profiles, where positively and negatively correlated modules are of equal importance in the classification of cancer subtypes. Epigenetic modules also estimate the survival time of patients, and this factor is critical for cancer therapy. Conclusions The proposed model and algorithm provide an effective method for the integrative analysis of DNA methylation and gene expression. The algorithm is freely available as an R-package at https://github.com/william0701/EMDN. Electronic supplementary material The online version of this article (doi:10.1186/s12859-017-1490-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Xiaoke Ma
- School of Computer Science and Technology, Xidian University, No.2 South TaiBai Road, Xi'an, People's Republic of China.,Xidian-Ningbo Information Technology Institute, Xidian University, No. 777 Zhongguanxi Road, Ningbo, People's Republic of China
| | - Zaiyi Liu
- Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Zhongshan Road, Guangzhou, People's Republic of China
| | - Zhongyuan Zhang
- School of Statistics and Mathematics, Central University of Finance and Economics, 39 South College Road, Haidian District, Beijing, People's Republic of China
| | - Xiaotai Huang
- School of Computer Science and Technology, Xidian University, No.2 South TaiBai Road, Xi'an, People's Republic of China
| | - Wanxin Tang
- Department of Nephrology, West China Hospital, Sichuan University, Wuhou District, Chengdu, People's Republic of China.
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79
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Ecker S, Chen L, Pancaldi V, Bagger FO, Fernández JM, Carrillo de Santa Pau E, Juan D, Mann AL, Watt S, Casale FP, Sidiropoulos N, Rapin N, Merkel A, Stunnenberg HG, Stegle O, Frontini M, Downes K, Pastinen T, Kuijpers TW, Rico D, Valencia A, Beck S, Soranzo N, Paul DS. Genome-wide analysis of differential transcriptional and epigenetic variability across human immune cell types. Genome Biol 2017; 18:18. [PMID: 28126036 PMCID: PMC5270224 DOI: 10.1186/s13059-017-1156-8] [Citation(s) in RCA: 78] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Accepted: 01/17/2017] [Indexed: 12/11/2022] Open
Abstract
Background A healthy immune system requires immune cells that adapt rapidly to environmental challenges. This phenotypic plasticity can be mediated by transcriptional and epigenetic variability. Results We apply a novel analytical approach to measure and compare transcriptional and epigenetic variability genome-wide across CD14+CD16− monocytes, CD66b+CD16+ neutrophils, and CD4+CD45RA+ naïve T cells from the same 125 healthy individuals. We discover substantially increased variability in neutrophils compared to monocytes and T cells. In neutrophils, genes with hypervariable expression are found to be implicated in key immune pathways and are associated with cellular properties and environmental exposure. We also observe increased sex-specific gene expression differences in neutrophils. Neutrophil-specific DNA methylation hypervariable sites are enriched at dynamic chromatin regions and active enhancers. Conclusions Our data highlight the importance of transcriptional and epigenetic variability for the key role of neutrophils as the first responders to inflammatory stimuli. We provide a resource to enable further functional studies into the plasticity of immune cells, which can be accessed from: http://blueprint-dev.bioinfo.cnio.es/WP10/hypervariability. Electronic supplementary material The online version of this article (doi:10.1186/s13059-017-1156-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Simone Ecker
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro 3, 28029, Madrid, Spain. .,UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT, UK.
| | - Lu Chen
- Department of Human Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1HH, UK.,Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge, Hinxton, UK
| | - Vera Pancaldi
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro 3, 28029, Madrid, Spain
| | - Frederik O Bagger
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge, Hinxton, UK.,National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Long Road, Cambridge, CB2 0PT, UK.,European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - José María Fernández
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro 3, 28029, Madrid, Spain
| | - Enrique Carrillo de Santa Pau
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro 3, 28029, Madrid, Spain
| | - David Juan
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro 3, 28029, Madrid, Spain
| | - Alice L Mann
- Department of Human Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1HH, UK
| | - Stephen Watt
- Department of Human Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1HH, UK
| | - Francesco Paolo Casale
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Nikos Sidiropoulos
- The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark.,Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark.,The Bioinformatics Centre, Department of Biology, Faculty of Natural Sciences, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Nicolas Rapin
- The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark.,Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark.,The Bioinformatics Centre, Department of Biology, Faculty of Natural Sciences, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Angelika Merkel
- National Center for Genomic Analysis (CNAG), Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Carrer Baldiri i Reixac 4, 08028, Barcelona, Spain
| | | | - Hendrik G Stunnenberg
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen, 6525GA, The Netherlands
| | - Oliver Stegle
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Mattia Frontini
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge, Hinxton, UK.,National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Long Road, Cambridge, CB2 0PT, UK.,British Heart Foundation Centre of Excellence, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge, CB2 0PT, UK
| | - Kate Downes
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge, Hinxton, UK.,National Health Service (NHS) Blood and Transplant, Cambridge Biomedical Campus, Long Road, Cambridge, CB2 0PT, UK
| | - Tomi Pastinen
- Department of Human Genetics, McGill University, 740 Dr. Penfield, Montreal, H3A 0G1, Canada
| | - Taco W Kuijpers
- Blood Cell Research, Sanquin Research and Landsteiner Laboratory, Plesmanlaan 125, Amsterdam, 1066CX, The Netherlands.,Emma Children's Hospital, Academic Medical Center (AMC), University of Amsterdam, Location H7-230, Meibergdreef 9, Amsterdam, 1105AX, The Netherlands
| | - Daniel Rico
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro 3, 28029, Madrid, Spain.,Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK
| | - Alfonso Valencia
- Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro 3, 28029, Madrid, Spain
| | - Stephan Beck
- UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT, UK
| | - Nicole Soranzo
- Department of Human Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1HH, UK. .,Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Long Road, Cambridge, Hinxton, UK.
| | - Dirk S Paul
- UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT, UK. .,Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Wort's Causeway, Cambridge, CB1 8RN, UK.
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Parenclitic Network Analysis of Methylation Data for Cancer Identification. PLoS One 2017; 12:e0169661. [PMID: 28107365 PMCID: PMC5249089 DOI: 10.1371/journal.pone.0169661] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2016] [Accepted: 12/20/2016] [Indexed: 12/20/2022] Open
Abstract
We make use of ideas from the theory of complex networks to implement a machine learning classification of human DNA methylation data, that carry signatures of cancer development. The data were obtained from patients with various kinds of cancers and represented as parenclictic networks, wherein nodes correspond to genes, and edges are weighted according to pairwise variation from control group subjects. We demonstrate that for the 10 types of cancer under study, it is possible to obtain a high performance of binary classification between cancer-positive and negative samples based on network measures. Remarkably, an accuracy as high as 93−99% is achieved with only 12 network topology indices, in a dramatic reduction of complexity from the original 15295 gene methylation levels. Moreover, it was found that the parenclictic networks are scale-free in cancer-negative subjects, and deviate from the power-law node degree distribution in cancer. The node centrality ranking and arising modular structure could provide insights into the systems biology of cancer.
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81
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Dai L, Mehta A, Mordukhovich I, Just AC, Shen J, Hou L, Koutrakis P, Sparrow D, Vokonas PS, Baccarelli AA, Schwartz JD. Differential DNA methylation and PM 2.5 species in a 450K epigenome-wide association study. Epigenetics 2016; 12:139-148. [PMID: 27982729 DOI: 10.1080/15592294.2016.1271853] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Although there is growing evidence that exposure to ambient particulate matter is associated with global DNA methylation and gene-specific methylation, little is known regarding epigenome-wide changes in DNA methylation in relation to particles and, especially, particle components. Using the Illumina Infinium HumanMethylation450 BeadChip, we examined the relationship between one-year moving averages of PM2.5 species (Al, Ca, Cu, Fe, K, Na, Ni, S, Si, V, and Zn) and DNA methylation at 484,613 CpG probes in a longitudinal cohort that included 646 subjects. Bonferroni correction was applied to adjust for multiple comparisons. Bioinformatics analysis of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment was also performed. We observed 20 Bonferroni significant (P-value < 9.4× 10-9) CpGs for Fe, 8 for Ni, and 1 for V. Particularly, methylation at Schlafen Family Member 11 (SLFN11) cg10911913 was positively associated with measured levels of all 3 species. The SLFN11 gene codes for an interferon-induced protein that inhibits retroviruses and sensitizes cancer cells to DNA-damaging agents. Bioinformatics analysis suggests that gene targets may be relevant to pathways including cancers, signal transduction, and cell growth and death. Ours is the first study to examine the epigenome-wide association between ambient particles species and DNA methylation. We found that long-term exposures to specific components of ambient particle pollution, especially particles emitted during oil combustion, were associated with methylation changes in genes relevant to immune responses. Our findings provide insight into potential biologic mechanisms on an epigenetic level.
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Affiliation(s)
- Lingzhen Dai
- a Department of Environmental Health , Harvard T.H. Chan School of Public Health , Boston , MA , USA
| | - Amar Mehta
- a Department of Environmental Health , Harvard T.H. Chan School of Public Health , Boston , MA , USA
| | - Irina Mordukhovich
- a Department of Environmental Health , Harvard T.H. Chan School of Public Health , Boston , MA , USA
| | - Allan C Just
- b Department of Preventive Medicine , Icahn School of Medicine at Mount Sinai , New York , NY , USA
| | - Jincheng Shen
- c Department of Biostatistics , Harvard T.H. Chan School of Public Health , Boston , MA , USA
| | - Lifang Hou
- d Department of Preventive Medicine , Feinberg School of Medicine, Northwestern University , Chicago , IL , USA
| | - Petros Koutrakis
- a Department of Environmental Health , Harvard T.H. Chan School of Public Health , Boston , MA , USA
| | - David Sparrow
- e Veterans Affairs Normative Aging Study, Veterans Affairs Boston Healthcare System , Department of Medicine, Boston University School of Medicine , Boston , MA , USA
| | - Pantel S Vokonas
- e Veterans Affairs Normative Aging Study, Veterans Affairs Boston Healthcare System , Department of Medicine, Boston University School of Medicine , Boston , MA , USA
| | - Andrea A Baccarelli
- a Department of Environmental Health , Harvard T.H. Chan School of Public Health , Boston , MA , USA
| | - Joel D Schwartz
- a Department of Environmental Health , Harvard T.H. Chan School of Public Health , Boston , MA , USA
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Falco M, Palma G, Rea D, De Biase D, Scala S, D'Aiuto M, Facchini G, Perdonà S, Barbieri A, Arra C. Tumour biomarkers: homeostasis as a novel prognostic indicator. Open Biol 2016; 6:160254. [PMID: 27927793 PMCID: PMC5204124 DOI: 10.1098/rsob.160254] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2016] [Accepted: 11/10/2016] [Indexed: 12/15/2022] Open
Abstract
The term 'personalized medicine' refers to a medical procedure that consists in the grouping of patients based on their predicted individual response to therapy or risk of disease. In oncologic patients, a 'tailored' therapeutic approach may potentially improve their survival and well-being by not only reducing the tumour, but also enhancing therapeutic response and minimizing the adverse effects. Diagnostic tests are often used to select appropriate and optimal therapies that rely both on patient genome and other molecular/cellular analysis. Several studies have shown that lifestyle and environmental factors can influence the epigenome and that epigenetic events may be involved in carcinogenesis. Thus, in addition to traditional biomarkers, epigenetic factors are raising considerable interest, because they could potentially be used as an excellent tool for cancer diagnosis and prognosis. In this review, we summarize the role of conventional cancer genetic biomarkers and their association with epigenomics. Furthermore, we will focus on the so-called 'homeostatic biomarkers' that result from the physiological response to cancer, emphasizing the concept that an altered 'new' homeostasis influence not only tumour environment, but also the whole organism.
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Affiliation(s)
- Michela Falco
- Struttura Semplice Dipartimentale Sperimentazione Animale, Istituto Nazionale Tumori 'Fondazione G. Pascale', IRCCS, Via Mariano Semmola, 80131 Naples, Italy
| | - Giuseppe Palma
- Struttura Semplice Dipartimentale Sperimentazione Animale, Istituto Nazionale Tumori 'Fondazione G. Pascale', IRCCS, Via Mariano Semmola, 80131 Naples, Italy
| | - Domenica Rea
- Struttura Semplice Dipartimentale Sperimentazione Animale, Istituto Nazionale Tumori 'Fondazione G. Pascale', IRCCS, Via Mariano Semmola, 80131 Naples, Italy
| | - Davide De Biase
- Department of Veterinary Medicine and Animal Production, University of Naples 'Federico II', Via Delpino 1, 80137 Naples, Italy
| | - Stefania Scala
- Molecular lmmunology and Immuneregulation, Istituto Nazionale per lo Studio e la Cura dei Tumori, IRCCS Naples 'Fondazione G. Pascale', Naples, italy, Istituto Nazionale Tumori 'Fondazione G. Pascale', IRCCS, Via Mariano Semmola, 80131 Naples, Italy
| | - Massimiliano D'Aiuto
- Division of Breast Surgery, Department of Breast Disease, National Cancer Institute, IRCCS, 'Fondazione Pascale', Naples, Italy
| | - Gaetano Facchini
- Division of Medical Oncology, Department of Uro-Gynaecological Oncology, , Istituto Nazionale per lo Studio e la Cura dei Tumori 'Fondazione G. Pascale', IRCCS, 80131 Naples, Italy
| | - Sisto Perdonà
- Department of Urology, Istituto Nazionale per lo Studio e la Cura dei Tumori 'Fondazione G. Pascale', IRCCS, 80131 Naples, Italy
| | - Antonio Barbieri
- Struttura Semplice Dipartimentale Sperimentazione Animale, Istituto Nazionale Tumori 'Fondazione G. Pascale', IRCCS, Via Mariano Semmola, 80131 Naples, Italy
| | - Claudio Arra
- Struttura Semplice Dipartimentale Sperimentazione Animale, Istituto Nazionale Tumori 'Fondazione G. Pascale', IRCCS, Via Mariano Semmola, 80131 Naples, Italy
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83
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Paul DS, Teschendorff AE, Dang MA, Lowe R, Hawa MI, Ecker S, Beyan H, Cunningham S, Fouts AR, Ramelius A, Burden F, Farrow S, Rowlston S, Rehnstrom K, Frontini M, Downes K, Busche S, Cheung WA, Ge B, Simon MM, Bujold D, Kwan T, Bourque G, Datta A, Lowy E, Clarke L, Flicek P, Libertini E, Heath S, Gut M, Gut IG, Ouwehand WH, Pastinen T, Soranzo N, Hofer SE, Karges B, Meissner T, Boehm BO, Cilio C, Elding Larsson H, Lernmark Å, Steck AK, Rakyan VK, Beck S, Leslie RD. Increased DNA methylation variability in type 1 diabetes across three immune effector cell types. Nat Commun 2016; 7:13555. [PMID: 27898055 PMCID: PMC5141286 DOI: 10.1038/ncomms13555] [Citation(s) in RCA: 111] [Impact Index Per Article: 13.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2016] [Accepted: 10/04/2016] [Indexed: 02/06/2023] Open
Abstract
The incidence of type 1 diabetes (T1D) has substantially increased over the past decade, suggesting a role for non-genetic factors such as epigenetic mechanisms in disease development. Here we present an epigenome-wide association study across 406,365 CpGs in 52 monozygotic twin pairs discordant for T1D in three immune effector cell types. We observe a substantial enrichment of differentially variable CpG positions (DVPs) in T1D twins when compared with their healthy co-twins and when compared with healthy, unrelated individuals. These T1D-associated DVPs are found to be temporally stable and enriched at gene regulatory elements. Integration with cell type-specific gene regulatory circuits highlight pathways involved in immune cell metabolism and the cell cycle, including mTOR signalling. Evidence from cord blood of newborns who progress to overt T1D suggests that the DVPs likely emerge after birth. Our findings, based on 772 methylomes, implicate epigenetic changes that could contribute to disease pathogenesis in T1D.
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Affiliation(s)
- Dirk S. Paul
- Medical Genomics, UCL Cancer Institute, University College London, London WC1E 6BT, UK
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge CB1 8RN, UK
| | - Andrew E. Teschendorff
- CAS Key Lab of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
- Statistical Cancer Genomics, UCL Cancer Institute, University College London, London WC1E 6BT, UK
| | - Mary A.N. Dang
- The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Robert Lowe
- The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Mohammed I. Hawa
- The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Simone Ecker
- Medical Genomics, UCL Cancer Institute, University College London, London WC1E 6BT, UK
| | - Huriya Beyan
- The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Stephanie Cunningham
- The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Alexandra R. Fouts
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, Colorado 80045, USA
| | - Anita Ramelius
- Department of Clinical Sciences, Lund University, Skåne University Hospital, SE-20502 Malmö, Sweden
| | - Frances Burden
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
- National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
| | - Samantha Farrow
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
- National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
| | - Sophia Rowlston
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
- National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
| | - Karola Rehnstrom
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
- National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
| | - Mattia Frontini
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
- National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
- British Heart Foundation Centre of Excellence, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Kate Downes
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
- National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
| | - Stephan Busche
- Department of Human Genetics, McGill University, Montreal, Québec, Canada H3A 0G1
- McGill University and Genome Quebec Innovation Centre, Montreal, Québec, Canada H3A 0G1
| | - Warren A. Cheung
- Department of Human Genetics, McGill University, Montreal, Québec, Canada H3A 0G1
- McGill University and Genome Quebec Innovation Centre, Montreal, Québec, Canada H3A 0G1
| | - Bing Ge
- Department of Human Genetics, McGill University, Montreal, Québec, Canada H3A 0G1
- McGill University and Genome Quebec Innovation Centre, Montreal, Québec, Canada H3A 0G1
| | - Marie-Michelle Simon
- Department of Human Genetics, McGill University, Montreal, Québec, Canada H3A 0G1
- McGill University and Genome Quebec Innovation Centre, Montreal, Québec, Canada H3A 0G1
| | - David Bujold
- Department of Human Genetics, McGill University, Montreal, Québec, Canada H3A 0G1
- McGill University and Genome Quebec Innovation Centre, Montreal, Québec, Canada H3A 0G1
| | - Tony Kwan
- Department of Human Genetics, McGill University, Montreal, Québec, Canada H3A 0G1
- McGill University and Genome Quebec Innovation Centre, Montreal, Québec, Canada H3A 0G1
| | - Guillaume Bourque
- Department of Human Genetics, McGill University, Montreal, Québec, Canada H3A 0G1
- McGill University and Genome Quebec Innovation Centre, Montreal, Québec, Canada H3A 0G1
| | - Avik Datta
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Ernesto Lowy
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Laura Clarke
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Emanuele Libertini
- Medical Genomics, UCL Cancer Institute, University College London, London WC1E 6BT, UK
| | - Simon Heath
- CNAG-CRG, Centre for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), Baldiri Reixac 4, 08028 Barcelona, Spain
- Universitat Pompeu Fabra, Plaça de la Mercè 10, 08002 Barcelona, Spain
| | - Marta Gut
- CNAG-CRG, Centre for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), Baldiri Reixac 4, 08028 Barcelona, Spain
- Universitat Pompeu Fabra, Plaça de la Mercè 10, 08002 Barcelona, Spain
| | - Ivo G Gut
- CNAG-CRG, Centre for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), Baldiri Reixac 4, 08028 Barcelona, Spain
- Universitat Pompeu Fabra, Plaça de la Mercè 10, 08002 Barcelona, Spain
| | - Willem H. Ouwehand
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
- National Health Service Blood and Transplant, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
- British Heart Foundation Centre of Excellence, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
- Human Genetics, Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Tomi Pastinen
- Department of Human Genetics, McGill University, Montreal, Québec, Canada H3A 0G1
- McGill University and Genome Quebec Innovation Centre, Montreal, Québec, Canada H3A 0G1
| | - Nicole Soranzo
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0PT, UK
- Human Genetics, Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Sabine E. Hofer
- Department of Pediatrics, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Beate Karges
- Division of Endocrinology and Diabetes, RWTH Aachen University, 52074 Aachen, Germany
- German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany
| | - Thomas Meissner
- German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany
- Department of General Pediatrics, Neonatology and Pediatric Cardiology, University Children's Hospital, Heinrich Heine University of Düsseldorf, 40225 Düsseldorf, Germany
| | - Bernhard O. Boehm
- Division of Endocrinology, Department of Internal Medicine I, Ulm University Medical Centre, 89081 Ulm, Germany
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
- Imperial College London, London SW7 2AZ, UK
| | - Corrado Cilio
- Department of Clinical Sciences, Lund University, Skåne University Hospital, SE-20502 Malmö, Sweden
| | - Helena Elding Larsson
- Department of Clinical Sciences, Lund University, Skåne University Hospital, SE-20502 Malmö, Sweden
| | - Åke Lernmark
- Department of Clinical Sciences, Lund University, Skåne University Hospital, SE-20502 Malmö, Sweden
| | - Andrea K. Steck
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, Colorado 80045, USA
| | - Vardhman K. Rakyan
- The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Stephan Beck
- Medical Genomics, UCL Cancer Institute, University College London, London WC1E 6BT, UK
| | - R. David Leslie
- The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
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84
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Yang Z, Wong A, Kuh D, Paul DS, Rakyan VK, Leslie RD, Zheng SC, Widschwendter M, Beck S, Teschendorff AE. Correlation of an epigenetic mitotic clock with cancer risk. Genome Biol 2016; 17:205. [PMID: 27716309 PMCID: PMC5046977 DOI: 10.1186/s13059-016-1064-3] [Citation(s) in RCA: 178] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Background Variation in cancer risk among somatic tissues has been attributed to variations in the underlying rate of stem cell division. For a given tissue type, variable cancer risk between individuals is thought to be influenced by extrinsic factors which modulate this rate of stem cell division. To date, no molecular mitotic clock has been developed to approximate the number of stem cell divisions in a tissue of an individual and which is correlated with cancer risk. Results Here, we integrate mathematical modeling with prior biological knowledge to construct a DNA methylation-based age-correlative model which approximates a mitotic clock in both normal and cancer tissue. By focusing on promoter CpG sites that localize to Polycomb group target genes that are unmethylated in 11 different fetal tissue types, we show that increases in DNA methylation at these sites defines a tick rate which correlates with the estimated rate of stem cell division in normal tissues. Using matched DNA methylation and RNA-seq data, we further show that it correlates with an expression-based mitotic index in cancer tissue. We demonstrate that this mitotic-like clock is universally accelerated in cancer, including pre-cancerous lesions, and that it is also accelerated in normal epithelial cells exposed to a major carcinogen. Conclusions Unlike other epigenetic and mutational clocks or the telomere clock, the epigenetic clock proposed here provides a concrete example of a mitotic-like clock which is universally accelerated in cancer and precancerous lesions. Electronic supplementary material The online version of this article (doi:10.1186/s13059-016-1064-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Zhen Yang
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, 320 Yue Yang Road, Shanghai, 200031, China
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at University College London, London, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at University College London, London, UK
| | - Dirk S Paul
- Medical Genomics, UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT, UK
| | - Vardhman K Rakyan
- The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, E1 2AT, UK
| | - R David Leslie
- The Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, E1 2AT, UK
| | - Shijie C Zheng
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, 320 Yue Yang Road, Shanghai, 200031, China
| | - Martin Widschwendter
- Department of Women's Cancer, University College London, 74 Huntley Street, London, WC1E 6AU, UK
| | - Stephan Beck
- Medical Genomics, UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT, UK
| | - Andrew E Teschendorff
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, 320 Yue Yang Road, Shanghai, 200031, China. .,Department of Women's Cancer, University College London, 74 Huntley Street, London, WC1E 6AU, UK. .,Statistical Cancer Genomics, Paul O'Gorman Building, UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT, UK.
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85
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Vidaki A, Giangasparo F, Syndercombe Court D. Discovery of potential DNA methylation markers for forensic tissue identification using bisulphite pyrosequencing. Electrophoresis 2016; 37:2767-2779. [DOI: 10.1002/elps.201600261] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2016] [Revised: 08/21/2016] [Accepted: 08/22/2016] [Indexed: 11/11/2022]
Affiliation(s)
- Athina Vidaki
- Department of Pharmacy and Forensic Science; King's College London; Franklin-Wilkins Building London UK
| | - Federica Giangasparo
- Department of Pharmacy and Forensic Science; King's College London; Franklin-Wilkins Building London UK
| | - Denise Syndercombe Court
- Department of Pharmacy and Forensic Science; King's College London; Franklin-Wilkins Building London UK
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86
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Defining, distinguishing and detecting the contribution of heterogeneous methylation to cancer heterogeneity. Semin Cell Dev Biol 2016; 64:5-17. [PMID: 27582426 DOI: 10.1016/j.semcdb.2016.08.030] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2016] [Accepted: 08/24/2016] [Indexed: 01/07/2023]
Abstract
DNA methylation is a fundamental means of epigenetic gene regulation that occurs in virtually all cell types. In many higher organisms, including humans, it plays vital roles in cell differentiation and homeostatic maintenance of cell phenotype. The control of DNA methylation has traditionally been attributed to a highly coordinated, linear process, whose dysregulation has been associated with numerous pathologies including cancer, where it occurs early in, and even prior to, the development of neoplastic tissues. Recent experimental evidence has demonstrated that, contrary to prevailing paradigms, methylation patterns are actually maintained through inexact, dynamic processes. These processes normally result in minor stochastic differences between cells that accumulate with age. However, various factors, including cancer itself, can lead to substantial differences in intercellular methylation patterns, viz. methylation heterogeneity. Advancements in molecular biology techniques are just now beginning to allow insight into how this heterogeneity contributes to clonal evolution and overall cancer heterogeneity. In the current review, we begin by presenting a didactic overview of how the basal bimodal methylome is established and maintained. We then provide a synopsis of some of the factors that lead to the accrual of heterogeneous methylation and how this heterogeneity may lead to gene silencing and impact the development of cancerous phenotypes. Lastly, we highlight currently available methylation assessment techniques and discuss their suitability to the study of heterogeneous methylation.
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87
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Ambatipudi S, Cuenin C, Hernandez-Vargas H, Ghantous A, Le Calvez-Kelm F, Kaaks R, Barrdahl M, Boeing H, Aleksandrova K, Trichopoulou A, Lagiou P, Naska A, Palli D, Krogh V, Polidoro S, Tumino R, Panico S, Bueno-de-Mesquita B, Peeters PH, Quirós JR, Navarro C, Ardanaz E, Dorronsoro M, Key T, Vineis P, Murphy N, Riboli E, Romieu I, Herceg Z. Tobacco smoking-associated genome-wide DNA methylation changes in the EPIC study. Epigenomics 2016; 8:599-618. [PMID: 26864933 DOI: 10.2217/epi-2016-0001] [Citation(s) in RCA: 160] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
AIM Epigenetic changes may occur in response to environmental stressors, and an altered epigenome pattern may represent a stable signature of environmental exposure. MATERIALS & METHODS Here, we examined the potential of DNA methylation changes in 910 prediagnostic peripheral blood samples as a marker of exposure to tobacco smoke in a large multinational cohort. RESULTS We identified 748 CpG sites that were differentially methylated between smokers and nonsmokers, among which we identified novel regionally clustered CpGs associated with active smoking. Importantly, we found a marked reversibility of methylation changes after smoking cessation, although specific genes remained differentially methylated up to 22 years after cessation. CONCLUSION Our study has comprehensively cataloged the smoking-associated DNA methylation alterations and showed that these alterations are reversible after smoking cessation.
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Affiliation(s)
| | - Cyrille Cuenin
- International Agency for Research on Cancer (IARC), Lyon, France
| | | | - Akram Ghantous
- International Agency for Research on Cancer (IARC), Lyon, France
| | | | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Myrto Barrdahl
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany
| | - Krasimira Aleksandrova
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany
| | - Antonia Trichopoulou
- Hellenic Health Foundation, Athens, Greece
- WHO Collaborating Center for Nutrition & Health, Unit of Nutritional Epidemiology & Nutrition in Public Health, Department of Hygiene, Epidemiology & Medical Statistics, University of Athens Medical School, Athens, Greece
| | - Pagona Lagiou
- Hellenic Health Foundation, Athens, Greece
- WHO Collaborating Center for Nutrition & Health, Unit of Nutritional Epidemiology & Nutrition in Public Health, Department of Hygiene, Epidemiology & Medical Statistics, University of Athens Medical School, Athens, Greece
| | - Androniki Naska
- Hellenic Health Foundation, Athens, Greece
- WHO Collaborating Center for Nutrition & Health, Unit of Nutritional Epidemiology & Nutrition in Public Health, Department of Hygiene, Epidemiology & Medical Statistics, University of Athens Medical School, Athens, Greece
| | - Domenico Palli
- Molecular & Nutritional Epidemiology Unit, Cancer Research & Prevention Institute-ISPO, Florence, Italy
| | - Vittorio Krogh
- Epidemiology & Prevention Unit, Fondazione IRCCS Istituto Nazionale Tumori, Milano, Italy
| | | | - Rosario Tumino
- Cancer Registry & Histopathology Unit, 'Civic MP Arezzo' Hospital, ASP Ragusa, Italy
| | - Salvatore Panico
- Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy
| | - Bas Bueno-de-Mesquita
- Department of Determinants of Chronic Diseases (DCD), National Institute for Public Health & the Environment (RIVM), Bilthoven, The Netherlands
- Department of Gastroenterology & Hepatology, University Medical Centre, Utrecht, The Netherlands
- Department of Epidemiology & Biostatistics, The School of Public Health, Imperial College London, London, UK
- Department of Social & Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Petra Hm Peeters
- Department of Epidemiology, Julius Center for Health Sciences & Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- MRC-PHE Centre for Environment & Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, UK
| | | | - Carmen Navarro
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Spain
- Department of Health & Social Sciences, Universidad de Murcia, Spain
| | - Eva Ardanaz
- CIBER Epidemiología y Salud Pública (CIBERESP), Spain
- Public Health Institute of Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Miren Dorronsoro
- Public Health Direction and Biodonostia-Ciberesp, Basque Regional Health Department, San Sebastian, Spain
| | - Tim Key
- Cancer Epidemiology Unit, University of Oxford, Oxford, UK
| | - Paolo Vineis
- School of Public Health, Imperial College London, London, UK
| | - Neil Murphy
- School of Public Health, Imperial College London, London, UK
| | - Elio Riboli
- School of Public Health, Imperial College London, London, UK
| | - Isabelle Romieu
- International Agency for Research on Cancer (IARC), Lyon, France
| | - Zdenko Herceg
- International Agency for Research on Cancer (IARC), Lyon, France
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88
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Teschendorff AE, Jones A, Widschwendter M. Stochastic epigenetic outliers can define field defects in cancer. BMC Bioinformatics 2016; 17:178. [PMID: 27103033 PMCID: PMC4840974 DOI: 10.1186/s12859-016-1056-z] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2015] [Accepted: 04/16/2016] [Indexed: 12/14/2022] Open
Abstract
Background There is growing evidence that DNA methylation alterations may contribute to carcinogenesis. Recent data also suggest that DNA methylation field defects in normal pre-neoplastic tissue represent infrequent stochastic “outlier” events. This presents a statistical challenge for standard feature selection algorithms, which assume frequent alterations in a disease phenotype. Although differential variability has emerged as a novel feature selection paradigm for the discovery of outliers, a growing concern is that these could result from technical confounders, in principle thus favouring algorithms which are robust to outliers. Results Here we evaluate five differential variability algorithms in over 700 DNA methylomes, including two of the largest cohorts profiling precursor cancer lesions, and demonstrate that most of the novel proposed algorithms lack the sensitivity to detect epigenetic field defects at genome-wide significance. In contrast, algorithms which recognise heterogeneous outlier DNA methylation patterns are able to identify many sites in pre-neoplastic lesions, which display progression in invasive cancer. Thus, we show that many DNA methylation outliers are not technical artefacts, but define epigenetic field defects which are selected for during cancer progression. Conclusions Given that cancer studies aiming to find epigenetic field defects are likely to be limited by sample size, adopting the novel feature selection paradigm advocated here will be critical to increase assay sensitivity. Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-1056-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Andrew E Teschendorff
- CAS Key Lab of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China. .,Statistical Cancer Genomics, Paul O'Gorman Building, UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT, UK. .,Department of Women's Cancer, University College London, 74 Huntley Street, London, WC1E 6AU, UK.
| | - Allison Jones
- Department of Women's Cancer, University College London, 74 Huntley Street, London, WC1E 6AU, UK
| | - Martin Widschwendter
- Department of Women's Cancer, University College London, 74 Huntley Street, London, WC1E 6AU, UK.
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89
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Zheng SC, Widschwendter M, Teschendorff AE. Epigenetic drift, epigenetic clocks and cancer risk. Epigenomics 2016; 8:705-19. [PMID: 27104983 DOI: 10.2217/epi-2015-0017] [Citation(s) in RCA: 81] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
It is well-established that the DNA methylation landscape of normal cells undergoes a gradual modification with age, termed as 'epigenetic drift'. Here, we review the current state of knowledge of epigenetic drift and its potential role in cancer etiology. We propose a new terminology to help distinguish the different components of epigenetic drift, with the aim of clarifying the role of the epigenetic clock, mitotic clocks and active changes, which accumulate in response to environmental disease risk factors. We further highlight the growing evidence that epigenetic changes associated with cancer risk factors may play an important causal role in cancer development, and that monitoring these molecular changes in normal cells may offer novel risk prediction and disease prevention strategies.
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Affiliation(s)
- Shijie C Zheng
- CAS Key Lab of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.,University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, China
| | - Martin Widschwendter
- Department of Women's Cancer, University College London, 74 Huntley Street, London, WC1E 6AU, UK
| | - Andrew E Teschendorff
- CAS Key Lab of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.,Department of Women's Cancer, University College London, 74 Huntley Street, London, WC1E 6AU, UK.,Statistical Cancer Genomics, UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT, UK
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90
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91
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Feinberg AP, Koldobskiy MA, Göndör A. Epigenetic modulators, modifiers and mediators in cancer aetiology and progression. Nat Rev Genet 2016; 17:284-99. [PMID: 26972587 DOI: 10.1038/nrg.2016.13] [Citation(s) in RCA: 582] [Impact Index Per Article: 72.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
This year is the tenth anniversary of the publication in this journal of a model suggesting the existence of 'tumour progenitor genes'. These genes are epigenetically disrupted at the earliest stages of malignancies, even before mutations, and thus cause altered differentiation throughout tumour evolution. The past decade of discovery in cancer epigenetics has revealed a number of similarities between cancer genes and stem cell reprogramming genes, widespread mutations in epigenetic regulators, and the part played by chromatin structure in cellular plasticity in both development and cancer. In the light of these discoveries, we suggest here a framework for cancer epigenetics involving three types of genes: 'epigenetic mediators', corresponding to the tumour progenitor genes suggested earlier; 'epigenetic modifiers' of the mediators, which are frequently mutated in cancer; and 'epigenetic modulators' upstream of the modifiers, which are responsive to changes in the cellular environment and often linked to the nuclear architecture. We suggest that this classification is helpful in framing new diagnostic and therapeutic approaches to cancer.
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Affiliation(s)
- Andrew P Feinberg
- Center for Epigenetics, Johns Hopkins University School of Medicine, 855 N. Wolfe Street, Rangos 570, Baltimore, Maryland 21205, USA
| | - Michael A Koldobskiy
- Center for Epigenetics, Johns Hopkins University School of Medicine, 855 N. Wolfe Street, Rangos 570, Baltimore, Maryland 21205, USA
| | - Anita Göndör
- Department of Microbiology, Tumour and Cell Biology, Nobels väg 16, Karolinska Institutet, S-171 77 Stockholm, Sweden
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92
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Pashayan N, Reisel D, Widschwendter M. Integration of genetic and epigenetic markers for risk stratification: opportunities and challenges. Per Med 2016; 13:93-95. [PMID: 27053939 DOI: 10.2217/pme.15.53] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Common genetic susceptibility variants could be used for risk stratification in risk-tailored cancer screening and prevention programmes. Combining genetic variants with environmental risk factors would improve risk stratification. Epigenetic changes are surrogate markers of environmental exposures during individual's lifetime. Integrating epigenetic markers, in lieu of environmental exposure data, with genetic markers would potentially improve risk stratification. Epigenetic changes are reversible and acquired gradually, providing potentials for prevention and early detection strategies. The epigenetic changes are tissue-specific and stage-of-development-specific, raising challenges in choice of sample and timing for evaluation of cancer-associated changes. The Horizon 2020 funded research programme, FORECEE, using empirical data, will investigate the value of integration of epigenomics with genomics for risk prediction and prevention of women-specific cancers.
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Affiliation(s)
- Nora Pashayan
- University College London, Department of Applied Health Research, London, UK
| | - Daniel Reisel
- University College London, Department of Women's Cancer, London, UK
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93
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DNA methylation outliers in normal breast tissue identify field defects that are enriched in cancer. Nat Commun 2016; 7:10478. [PMID: 26823093 PMCID: PMC4740178 DOI: 10.1038/ncomms10478] [Citation(s) in RCA: 154] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2015] [Accepted: 12/16/2015] [Indexed: 12/11/2022] Open
Abstract
Identifying molecular alterations in normal tissue adjacent to cancer is important for understanding cancer aetiology and designing preventive measures. Here we analyse the DNA methylome of 569 breast tissue samples, including 50 from cancer-free women and 84 from matched normal cancer pairs. We use statistical algorithms for dissecting intra- and inter-sample cellular heterogeneity and demonstrate that normal tissue adjacent to breast cancer is characterized by tens to thousands of epigenetic alterations. We show that their genomic distribution is non-random, being strongly enriched for binding sites of transcription factors specifying chromatin architecture. We validate the field defects in an independent cohort and demonstrate that over 30% of the alterations exhibit increased enrichment within matched cancer samples. Breast cancers highly enriched for epigenetic field defects, exhibit adverse clinical outcome. Our data support a model where clonal epigenetic reprogramming towards reduced differentiation in normal tissue is an important step in breast carcinogenesis. Altered epigenetics is a feature of cancer but whether these changes occur early in tumour development is unclear. Here, the authors analyse methylation events in breast cancer and adjacent normal pairs, and show that methylation changes in the normal tissue are also found in the tumour, suggesting that some of these events occur early in cancer.
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94
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Polovinkin AN, Krylov IB, Druzhkov PN, Ivanchenko MV, Meyerov IB, Zaikin AA, Zolotykh NY. Solving problems of clustering and classification of cancer diseases based on DNA methylation data. PATTERN RECOGNITION AND IMAGE ANALYSIS 2016. [DOI: 10.1134/s1054661816010181] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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95
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Li X, Qiu W, Morrow J, DeMeo DL, Weiss ST, Fu Y, Wang X. A Comparative Study of Tests for Homogeneity of Variances with Application to DNA Methylation Data. PLoS One 2015; 10:e0145295. [PMID: 26683022 PMCID: PMC4684215 DOI: 10.1371/journal.pone.0145295] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2015] [Accepted: 12/02/2015] [Indexed: 12/18/2022] Open
Abstract
Variable DNA methylation has been associated with cancers and complex diseases. Researchers have identified many DNA methylation markers that have different mean methylation levels between diseased subjects and normal subjects. Recently, researchers found that DNA methylation markers with different variabilities between subject groups could also have biological meaning. In this article, we aimed to help researchers choose the right test of equal variance in DNA methylation data analysis. We performed systematic simulation studies and a real data analysis to compare the performances of 7 equal-variance tests, including 2 tests recently proposed in the DNA methylation analysis literature. Our results showed that the Brown-Forsythe test and trimmed-mean-based Levene's test had good performance in testing for equality of variance in our simulation studies and real data analyses. Our results also showed that outlier profiles could be biologically very important.
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Affiliation(s)
- Xuan Li
- Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON, M3J1P3, Canada
| | - Weiliang Qiu
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, United States of America
- * E-mail:
| | - Jarrett Morrow
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, United States of America
| | - Dawn L. DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, United States of America
| | - Scott T. Weiss
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, United States of America
| | - Yuejiao Fu
- Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON, M3J1P3, Canada
| | - Xiaogang Wang
- Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON, M3J1P3, Canada
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96
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Abstract
The process of aging results in a host of changes at the cellular and molecular levels, which include senescence, telomere shortening, and changes in gene expression. Epigenetic patterns also change over the lifespan, suggesting that epigenetic changes may constitute an important component of the aging process. The epigenetic mark that has been most highly studied is DNA methylation, the presence of methyl groups at CpG dinucleotides. These dinucleotides are often located near gene promoters and associate with gene expression levels. Early studies indicated that global levels of DNA methylation increase over the first few years of life and then decrease beginning in late adulthood. Recently, with the advent of microarray and next‐generation sequencing technologies, increases in variability of DNA methylation with age have been observed, and a number of site‐specific patterns have been identified. It has also been shown that certain CpG sites are highly associated with age, to the extent that prediction models using a small number of these sites can accurately predict the chronological age of the donor. Together, these observations point to the existence of two phenomena that both contribute to age‐related DNA methylation changes: epigenetic drift and the epigenetic clock. In this review, we focus on healthy human aging throughout the lifetime and discuss the dynamics of DNA methylation as well as how interactions between the genome, environment, and the epigenome influence aging rates. We also discuss the impact of determining ‘epigenetic age’ for human health and outline some important caveats to existing and future studies.
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Affiliation(s)
- Meaghan J. Jones
- Centre for Molecular Medicine and Therapeutics Child and Family Research InstituteUniversity of British Columbia Vancouver BC Canada
- Department of Medical Genetics University of British ColumbiaVancouver BC Canada
| | - Sarah J. Goodman
- Centre for Molecular Medicine and Therapeutics Child and Family Research InstituteUniversity of British Columbia Vancouver BC Canada
- Department of Medical Genetics University of British ColumbiaVancouver BC Canada
| | - Michael S. Kobor
- Centre for Molecular Medicine and Therapeutics Child and Family Research InstituteUniversity of British Columbia Vancouver BC Canada
- Department of Medical Genetics University of British ColumbiaVancouver BC Canada
- Human Early Learning Partnership School of Population and Public Health University of British Columbia Vancouver BC Canada
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97
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Tsaprouni LG, Yang TP, Bell J, Dick KJ, Kanoni S, Nisbet J, Viñuela A, Grundberg E, Nelson CP, Meduri E, Buil A, Cambien F, Hengstenberg C, Erdmann J, Schunkert H, Goodall AH, Ouwehand WH, Dermitzakis E, Spector TD, Samani NJ, Deloukas P. Cigarette smoking reduces DNA methylation levels at multiple genomic loci but the effect is partially reversible upon cessation. Epigenetics 2015; 9:1382-96. [PMID: 25424692 DOI: 10.4161/15592294.2014.969637] [Citation(s) in RCA: 243] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Smoking is a major risk factor in many diseases. Genome wide association studies have linked genes for nicotine dependence and smoking behavior to increased risk of cardiovascular, pulmonary, and malignant diseases. We conducted an epigenome wide association study in peripheral-blood DNA in 464 individuals (22 current smokers and 263 ex-smokers), using the Human Methylation 450 K array. Upon replication in an independent sample of 356 twins (41 current and 104 ex-smokers), we identified 30 probes in 15 distinct loci, all of which reached genome-wide significance in the combined analysis P < 5 × 10(-8). All but one probe (cg17024919) remained significant after adjusting for blood cell counts. We replicated all 9 known loci and found an independent signal at CPOX near GPR15. In addition, we found 6 new loci at PRSS23, AVPR1B, PSEN2, LINC00299, RPS6KA2, and KIAA0087. Most of the lead probes (13 out of 15) associated with cigarette smoking, overlapped regions of open chromatin (FAIRE and DNaseI hypersensitive sites) or/and H3K27Ac peaks (ENCODE data set), which mark regulatory elements. The effect of smoking on DNA methylation was partially reversible upon smoking cessation for longer than 3 months. We report the first statistically significant interaction between a SNP (rs2697768) and cigarette smoking on DNA methylation (cg03329539). We provide evidence that the metSNP for cg03329539 regulates expression of the CHRND gene located circa 95 Kb downstream of the methylation site. Our findings suggest the existence of dynamic, reversible site-specific methylation changes in response to cigarette smoking , which may contribute to the extended health risks associated with cigarette smoking.
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Key Words
- AHRR, aryl-hydrocarbon receptor repressor
- ALPP, alkaline phosphatase, placental
- AVPR1B, arginine vasopressin
- CHRND
- CHRND, cholinergic nicotinic receptor
- COPD, chronic obstructive pulmonary disease
- CPOX
- CPOX, coproporphyrinogen oxidase
- DNA methylation
- DNMT, DNA methyltransferase
- EWAS, epigenome wide association study
- FDR, false discovery rate
- GWAS, genome-wide association studies
- PRSS23, serine protease 23
- PSEN2, presenilin-2 gene
- RPS6KA2, ribosomal protein S6 kinase
- epigenome-wide screen
- gene network
- metQTL, methylation quantitative trait loci
- metQTLs
- rs2697768
- smoking
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98
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Dinalankara W, Bravo HC. Gene Expression Signatures Based on Variability can Robustly Predict Tumor Progression and Prognosis. Cancer Inform 2015; 14:71-81. [PMID: 26078586 PMCID: PMC4460970 DOI: 10.4137/cin.s23862] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2015] [Revised: 03/22/2015] [Accepted: 03/29/2015] [Indexed: 01/11/2023] Open
Abstract
Gene expression signatures are commonly used to create cancer prognosis and diagnosis methods, yet only a small number of them are successfully deployed in the clinic since many fail to replicate performance on subsequent validation. A primary reason for this lack of reproducibility is the fact that these signatures attempt to model the highly variable and unstable genomic behavior of cancer. Our group recently introduced gene expression anti-profiles as a robust methodology to derive gene expression signatures based on the observation that while gene expression measurements are highly heterogeneous across tumors of a specific cancer type relative to the normal tissue, their degree of deviation from normal tissue expression in specific genes involved in tissue differentiation is a stable tumor mark that is reproducible across experiments and cancer types. Here we show that constructing gene expression signatures based on variability and the anti-profile approach yields classifiers capable of successfully distinguishing benign growths from cancerous growths based on deviation from normal expression. We then show that this same approach generates stable and reproducible signatures that predict probability of relapse and survival based on tumor gene expression. These results suggest that using the anti-profile framework for the discovery of genomic signatures is an avenue leading to the development of reproducible signatures suitable for adoption in clinical settings.
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Affiliation(s)
- Wikum Dinalankara
- Center for Bioinformatics and Computational Biology, Department of Computer Science and UMIACS, University of Maryland, College Park, MD, USA
| | - Héctor Corrada Bravo
- Center for Bioinformatics and Computational Biology, Department of Computer Science and UMIACS, University of Maryland, College Park, MD, USA
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99
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Cazaly E, Charlesworth J, Dickinson JL, Holloway AF. Genetic Determinants of Epigenetic Patterns: Providing Insight into Disease. Mol Med 2015; 21:400-9. [PMID: 25822796 DOI: 10.2119/molmed.2015.00001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2015] [Accepted: 03/26/2015] [Indexed: 02/06/2023] Open
Abstract
The field of epigenetics and our understanding of the mechanisms that regulate the establishment, maintenance and heritability of epigenetic patterns continue to grow at a remarkable rate. This information is providing increased understanding of the role of epigenetic changes in disease, insight into the underlying causes of these epigenetic changes and revealing new avenues for therapeutic intervention. Epigenetic modifiers are increasingly being pursued as therapeutic targets in a range of diseases, with a number of agents targeting epigenetic modifications already proving effective in diseases such as cancer. Although it is well established that DNA mutations and aberrant expression of epigenetic modifiers play a key role in disease, attention is now turning to the interplay between genetic and epigenetic factors in complex disease etiology. The role of genetic variability in determining epigenetic profiles, which can then be modified by environmental and stochastic factors, is becoming more apparent. Understanding the interplay between genetic and epigenetic factors is likely to aid in identifying individuals most likely to benefit from epigenetic therapies. This goal is coming closer to realization because of continual advances in laboratory and statistical tools enabling improvements in the integration of genomic, epigenomic and phenotypic data.
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Affiliation(s)
- Emma Cazaly
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Jac Charlesworth
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Joanne L Dickinson
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Adele F Holloway
- School of Medicine, University of Tasmania, Hobart, Tasmania, Australia
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100
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Yuan T, Jiao Y, de Jong S, Ophoff RA, Beck S, Teschendorff AE. An integrative multi-scale analysis of the dynamic DNA methylation landscape in aging. PLoS Genet 2015; 11:e1004996. [PMID: 25692570 PMCID: PMC4334892 DOI: 10.1371/journal.pgen.1004996] [Citation(s) in RCA: 110] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2014] [Accepted: 01/10/2015] [Indexed: 12/21/2022] Open
Abstract
Recent studies have demonstrated that the DNA methylome changes with age. This epigenetic drift may have deep implications for cellular differentiation and disease development. However, it remains unclear how much of this drift is functional or caused by underlying changes in cell subtype composition. Moreover, no study has yet comprehensively explored epigenetic drift at different genomic length scales and in relation to regulatory elements. Here we conduct an in-depth analysis of epigenetic drift in blood tissue. We demonstrate that most of the age-associated drift is independent of the increase in the granulocyte to lymphocyte ratio that accompanies aging and that enrichment of age-hypermethylated CpG islands increases upon adjustment for cellular composition. We further find that drift has only a minimal impact on in-cis gene expression, acting primarily to stabilize pre-existing baseline expression levels. By studying epigenetic drift at different genomic length scales, we demonstrate the existence of mega-base scale age-associated hypomethylated blocks, covering approximately 14% of the human genome, and which exhibit preferential hypomethylation in age-matched cancer tissue. Importantly, we demonstrate the feasibility of integrating Illumina 450k DNA methylation with ENCODE data to identify transcription factors with key roles in cellular development and aging. Specifically, we identify REST and regulatory factors of the histone methyltransferase MLL complex, whose function may be disrupted in aging. In summary, most of the epigenetic drift seen in blood is independent of changes in blood cell type composition, and exhibits patterns at different genomic length scales reminiscent of those seen in cancer. Integration of Illumina 450k with appropriate ENCODE data may represent a fruitful approach to identify transcription factors with key roles in aging and disease. Two well-known features of aging are the gradual decline of the body’s ability to regenerate tissues, as well as an increased incidence of diseases like cancer and Alzheimers. One of the most recent exciting findings which may underlie the aging process is a gradual modification of DNA, called epigenetic drift, which is effected by the covalent addition and removal of methyl groups, which in turn can deregulate the activity of nearby genes. However, this study presents the most convincing evidence to date that epigenetic drift acts to stabilize the activity levels of nearby genes. This study shows that instead, epigenetic drift may act primarly to disrupt DNA binding patterns of proteins which regulate the activity of many genes, and moreover identifies specific regulatory proteins with key roles in cancer and Alzheimers. The study also performs the most comprehensive analysis of epigenetic drift at different spatial scales, demonstrating that epigenetic drift on the largest length scales is highly reminiscent of those seen in cancer. In summary, this work substantially supports the view that epigenetic drift may contribute to the age-associated increased risk of diseases like cancer and Alzheimers, by disrupting master regulators of genomewide gene activity.
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Affiliation(s)
- Tian Yuan
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Chinese Academy of Sciences, Shanghai Institute for Biological Sciences, Shanghai, China
| | - Yinming Jiao
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Chinese Academy of Sciences, Shanghai Institute for Biological Sciences, Shanghai, China
| | - Simone de Jong
- Center for Neurobehavioral Genetics, Los Angeles, California, USA
| | - Roel A. Ophoff
- Center for Neurobehavioral Genetics, Los Angeles, California, USA
| | - Stephan Beck
- Medical Genomics Group, UCL Cancer Institute, University College London, London, United Kingdom
| | - Andrew E. Teschendorff
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Chinese Academy of Sciences, Shanghai Institute for Biological Sciences, Shanghai, China
- Statistical Genomics Group, UCL Cancer Institute, University College London, London, United Kingdom
- * E-mail: (AET), (AET)
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