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1.  Using high-density DNA methylation arrays to profile copy number alterations 
Genome Biology  2014;15(2):R30.
The integration of genomic and epigenomic data is an increasingly popular approach for studying the complex mechanisms driving cancer development. We have developed a method for evaluating both methylation and copy number from high-density DNA methylation arrays. Comparing copy number data from Infinium HumanMethylation450 BeadChips and SNP arrays, we demonstrate that Infinium arrays detect copy number alterations with the sensitivity of SNP platforms. These results show that high-density methylation arrays provide a robust and economic platform for detecting copy number and methylation changes in a single experiment. Our method is available in the ChAMP Bioconductor package:
PMCID: PMC4054098  PMID: 24490765
2.  Integrated virus-host methylome analysis in head and neck squamous cell carcinoma 
Epigenetics  2013;8(9):953-961.
One in six cancers worldwide is caused by infection and human papillomavirus (HPV) is one of the main culprits. To better understand the dynamics of HPV integration and its effect on both the viral and host methylomes, we conducted whole-genome DNA methylation analysis using MeDIP-seq of HPV+ and HPV- head and neck squamous cell carcinoma (HNSCC). We determined the viral subtype to be HPV-16 in all cases and show that HPV-16 integrates into the host genome at multiple random sites and that this process predominantly involves the transcriptional repressor gene (E2) in the viral genome. Comparative analysis identified 453 (FDR ≤ 0.01) differentially methylated regions (DMRs) in the HPV+ host methylome. Bioinformatics characterization of these DMRs confirmed the previously reported cadherin genes to be affected but also revealed new targets for HPV-mediated methylation changes at regions not covered by array-based platforms, including the recently identified super-enhancers.
PMCID: PMC3883772  PMID: 23867721
human papillomavirus (HPV); head and neck squamous cell carcinoma (HNSCC); DNA methylation; methylome; epigenome
3.  Targeted next-generation sequencing of head and neck squamous cell carcinoma identifies novel genetic alterations in HPV+ and HPV- tumors 
Genome Medicine  2013;5(5):49.
Human papillomavirus positive (HPV+) head and neck squamous cell carcinoma (HNSCC) is an emerging disease, representing a distinct clinical and epidemiological entity. Understanding the genetic basis of this specific subtype of cancer could allow therapeutic targeting of affected pathways for a stratified medicine approach.
Twenty HPV+ and 20 HPV- laser-capture microdissected oropharyngeal carcinomas were used for paired-end sequencing of hybrid-captured DNA, targeting 3,230 exons in 182 genes often mutated in cancer. Copy number alteration (CNA) profiling, Sequenom MassArray sequencing and immunohistochemistry were used to further validate findings.
HPV+ and HPV- oropharyngeal carcinomas cluster into two distinct subgroups. TP53 mutations are detected in 100% of HPV negative cases and abrogation of the G1/S checkpoint by CDKN2A/B deletion and/or CCND1 amplification occurs in the majority of HPV- tumors.
These findings strongly support a causal role for HPV, acting via p53 and RB pathway inhibition, in the pathogenesis of a subset of oropharyngeal cancers and suggest that studies of CDK inhibitors in HPV- disease may be warranted. Mutation and copy number alteration of PI3 kinase (PI3K) pathway components appears particularly prevalent in HPV+ tumors and assessment of these alterations may aid in the interpretation of current clinical trials of PI3K, AKT, and mTOR inhibitors in HNSCC.
PMCID: PMC4064312  PMID: 23718828
4.  Identification and functional validation of HPV-mediated hypermethylation in head and neck squamous cell carcinoma 
Genome Medicine  2013;5(2):15.
Human papillomavirus-positive (HPV+) head and neck squamous cell carcinoma (HNSCC) represents a distinct clinical and epidemiological condition compared with HPV-negative (HPV-) HNSCC. To test the possible involvement of epigenetic modulation by HPV in HNSCC, we conducted a genome-wide DNA-methylation analysis.
Using laser-capture microdissection of 42 formalin-fixed paraffin wax-embedded (FFPE) HNSCCs, we generated DNA-methylation profiles of 18 HPV+ and 14 HPV- samples, using Infinium 450 k BeadArray technology. Methylation data were validated in two sets of independent HPV+/HPV- HNSCC samples (fresh-frozen samples and cell lines) using two independent methods (Infinium 450 k and whole-genome methylated DNA immunoprecipitation sequencing (MeDIP-seq)). For the functional analysis, an HPV- HNSCC cell line was transduced with lentiviral constructs containing the two HPV oncogenes (E6 and E7), and effects on methylation were assayed using the Infinium 450 k technology.
Results and discussion
Unsupervised clustering over the methylation variable positions (MVPs) with greatest variation showed that samples segregated in accordance with HPV status, but also that HPV+ tumors are heterogeneous. MVPs were significantly enriched at transcriptional start sites, leading to the identification of a candidate CpG island methylator phenotype in a sub-group of the HPV+ tumors. Supervised analysis identified a strong preponderance (87%) of MVPs towards hypermethylation in HPV+ HNSCC. Meta-analysis of our HNSCC and publicly available methylation data in cervical and lung cancers confirmed the observed DNA-methylation signature to be HPV-specific and tissue-independent. Grouping of MVPs into functionally more significant differentially methylated regions identified 43 hypermethylated promoter DMRs, including for three cadherins of the Polycomb group target genes. Integration with independent expression data showed strong negative correlation, especially for the cadherin gene-family members. Combinatorial ectopic expression of the two HPV oncogenes (E6 and E7) in an HPV- HNSCC cell line partially phenocopied the hypermethylation signature seen in HPV+ HNSCC tumors, and established E6 as the main viral effector gene.
Our data establish that archival FFPE tissue is very suitable for this type of methylome analysis, and suggest that HPV modulates the HNSCC epigenome through hypermethylation of Polycomb repressive complex 2 target genes such as cadherins, which are implicated in tumor progression and metastasis.
PMCID: PMC3706778  PMID: 23419152
5.  A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data 
Bioinformatics  2012;29(2):189-196.
Motivation: The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distributions and dynamic range, which may bias downstream analyses. A key statistical issue is therefore how best to adjust for the two different probe designs.
Results: Here we propose a novel model-based intra-array normalization strategy for 450 k data, called BMIQ (Beta MIxture Quantile dilation), to adjust the beta-values of type2 design probes into a statistical distribution characteristic of type1 probes. The strategy involves application of a three-state beta-mixture model to assign probes to methylation states, subsequent transformation of probabilities into quantiles and finally a methylation-dependent dilation transformation to preserve the monotonicity and continuity of the data. We validate our method on cell-line data, fresh frozen and paraffin-embedded tumour tissue samples and demonstrate that BMIQ compares favourably with two competing methods. Specifically, we show that BMIQ improves the robustness of the normalization procedure, reduces the technical variation and bias of type2 probe values and successfully eliminates the type1 enrichment bias caused by the lower dynamic range of type2 probes. BMIQ will be useful as a preprocessing step for any study using the Illumina Infinium 450 k platform.
Availability: BMIQ is freely available from
Supplementary information: Supplementary data are available at Bioinformatics online
PMCID: PMC3546795  PMID: 23175756
6.  Comments on: Interpretation of genome-wide infinium methylation data from ligated DNA in formalin-fixed paraffin-embedded paired tumor and normal tissue 
BMC Research Notes  2012;5:631.
BMC Research Notes recently published a research article regarding the use of ligated DNA extracted from formalin-fixed paraffin embedded (FFPE) tissue on the Illumina Infinium methylation platform - “Interpretation of genome-wide infinium methylation data from ligated DNA in formalin-fixed, paraffin-embedded paired tumor and normal tissue” Jasmine et al. BMC Research Notes 2012, 5:117. This article repeatedly refers to our previous work and concludes that methylation data obtained from ligated FFPE extracted DNA should be used with great caution. In this Discussion we review the data analysis performed in Jasmine et al’s paper and suggest limitations which subsequently lead the authors to draw what we believe are incorrect conclusions. Moreover, we continue to analyse genome-wide methylation data from DNA extracted from FFPE tissue successfully on both the HumMeth27 and 450 K arrays.
PMCID: PMC3531275  PMID: 23148593
7.  An Epigenetic Signature in Peripheral Blood Predicts Active Ovarian Cancer 
PLoS ONE  2009;4(12):e8274.
Recent studies have shown that DNA methylation (DNAm) markers in peripheral blood may hold promise as diagnostic or early detection/risk markers for epithelial cancers. However, to date no study has evaluated the diagnostic and predictive potential of such markers in a large case control cohort and on a genome-wide basis.
Principal Findings
By performing genome-wide DNAm profiling of a large ovarian cancer case control cohort, we here demonstrate that active ovarian cancer has a significant impact on the DNAm pattern in peripheral blood. Specifically, by measuring the methylation levels of over 27,000 CpGs in blood cells from 148 healthy individuals and 113 age-matched pre-treatment ovarian cancer cases, we derive a DNAm signature that can predict the presence of active ovarian cancer in blind test sets with an AUC of 0.8 (95% CI (0.74–0.87)). We further validate our findings in another independent set of 122 post-treatment cases (AUC = 0.76 (0.72–0.81)). In addition, we provide evidence for a significant number of candidate risk or early detection markers for ovarian cancer. Furthermore, by comparing the pattern of methylation with gene expression data from major blood cell types, we here demonstrate that age and cancer elicit common changes in the composition of peripheral blood, with a myeloid skewing that increases with age and which is further aggravated in the presence of ovarian cancer. Finally, we show that most cancer and age associated methylation variability is found at CpGs located outside of CpG islands.
Our results underscore the potential of DNAm profiling in peripheral blood as a tool for detection or risk-prediction of epithelial cancers, and warrants further in-depth and higher CpG coverage studies to further elucidate this role.
PMCID: PMC2793425  PMID: 20019873

Results 1-7 (7)