Assessment of patient-derived tumour xenografts (PDXs) as a discovery tool for cancer epigenomics

Background: The use of tumour xenografts is a well-established research tool in cancer genomics but has not yet been comprehensively evaluated for cancer epigenomics. Methods: In this study, we assessed the suitability of patient-derived tumour xenografts (PDXs) for methylome analysis using Infinium 450 K Beadchips and MeDIP-seq. Results: Controlled for confounding host (mouse) sequences, comparison of primary PDXs and matching patient tumours in a rare (osteosarcoma) and common (colon) cancer revealed that an average 2.7% of the assayed CpG sites undergo major (Δβ ≥ 0.51) methylation changes in a cancer-specific manner as a result of the xenografting procedure. No significant subsequent methylation changes were observed after a second round of xenografting between primary and secondary PDXs. Based on computational simulation using publically available methylation data, we additionally show that future studies comparing two groups of PDXs should use 15 or more samples in each group to minimise the impact of xenografting-associated changes in methylation on comparison results. Conclusions: Our results from rare and common cancers indicate that PDXs are a suitable discovery tool for cancer epigenomics and we provide guidance on how to overcome the observed limitations

oxBS-450K: A method for analysing hydroxymethylation using 450K BeadChips

DNA methylation analysis has become an integral part of biomedical research. For high-throughput applications such as epigenome-wide association studies, the Infinium HumanMethylation450 (450K) BeadChip is currently the platform of choice. However, BeadChip processing relies on traditional bisulfite (BS) based protocols which cannot discriminate between 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC). Here, we report the adaptation of the recently developed oxidative bisulfite (oxBS) chemistry to specifically detect both 5mC and 5hmC in a single workflow using 450K BeadChips, termed oxBS-450K. Supported by validation using mass spectrometry and pyrosequencing, we demonstrate reproducible (R(2)>0.99) detection of 5hmC in human brain tissue using the optimised oxBS-450K protocol described here

Assessment of RainDrop BS-seq as a method for large-scale, targeted bisulfite sequencing.

We present a systematic assessment of RainDrop BS-seq, a novel method for large-scale, targeted bisulfite sequencing using microdroplet-based PCR amplification coupled with next-generation sequencing. We compared DNA methylation levels at 498 target loci (1001 PCR amplicons) in human whole blood, osteosarcoma cells and an archived tumor tissue sample. We assessed the ability of RainDrop BS-seq to accurately measure DNA methylation over a range of DNA quantities (from 10 to 1500 ng), both with and without whole-genome amplification (WGA) following bisulfite conversion. DNA methylation profiles generated using at least 100 ng correlated well (median R = 0.92) with those generated on Illumina Infinium HumanMethylation450 BeadChips, currently the platform of choice for epigenome-wide association studies (EWAS). WGA allowed for testing of samples with a starting DNA amount of 10 and 50 ng, although a reduced correlation was observed (median R = 0.79). We conclude that RainDrop BS-seq is suitable for measuring DNA methylation levels using nanogram quantities of DNA, and can be used to study candidate epigenetic biomarker loci in an accurate and high-throughput manner, paving the way for its application to routine clinical diagnostics

Using high-density DNA methylation arrays to profile copy number alterations.

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: http://www.bioconductor.org/packages/2.13/bioc/html/ChAMP.html

Genome-wide analysis of differential transcriptional and epigenetic variability across human immune cell types

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

Fate mapping of human glioblastoma reveals an invariant stem cell hierarchy

Human glioblastomas (GBMs) harbour a subpopulation of glioblastoma stem cells (GSCs) that drive tumourigenesis. However, the origin of intra-tumoural functional heterogeneity between GBM cells remains poorly understood. Here we study the clonal evolution of barcoded GBM cells in an unbiased way following serial xenotransplantation to define their individual fate behaviours. Independent of an evolving mutational signature, we show that the growth of GBM clones in vivo is consistent with a remarkably neutral process involving a conserved proliferative hierarchy rooted in GSCs. In this model, slow-cycling stem-like cells give rise to a more rapidly cycling progenitor population with extensive self-maintenance capacity, that in turn generates non-proliferative cells. We also identify rare “outlier” clones that deviate from these dynamics, and further show that chemotherapy facilitates the expansion of pre-existing drug-resistant GSCs. Finally, we show that functionally distinct GSCs can be separately targeted using epigenetic compounds, suggesting new avenues for GBM targeted therapy.This study was supported by the Canadian Institutes of Health Research (funding reference number 142434), the Ontario Institute for Cancer Research through funding provided by the Government of Ontario, and Stand Up To Cancer (SU2C) Canada. P.B.D. is also supported by the Terry Fox Research Institute, the Canadian Cancer Society, the Hospital for Sick Children Foundation, Jessica’s Footprint Foundation, the Hopeful Minds Foundation, the Bresler family, and B.R.A.I.N. Child. P.B.D. holds a Garron Family Chair in Childhood Cancer Research at The Hospital for Sick Children. B.D.S. acknowledges the support of the Wellcome Trust (grant number 098357/Z/12/Z). C.J.E. acknowledges grant support from the Canadian Cancer Society and the Terry Fox Run. Research was supported by SU2C Canada Cancer Stem Cell Dream Team Research Funding (SU2C-AACR-DT-19-15) provided by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, with supplementary support from the Ontario Institute for Cancer Research through funding provided by the Government of Ontario. Stand Up To Cancer Canada is a program of the Entertainment Industry Foundation Canada. Research funding is administered by the American Association for Cancer Research International – Canada, the scientific partner of SU2C Canada. The Structural Genomics Consortium is funded by AbbVie, Bayer, Boehringer Ingelheim, GSK, Genome Canada, Ontario Genomics Institute, Janssen, Lilly, Merck, Novartis, the government of Ontario, Pfizer, Takeda, and the Wellcome Trust

Statistical and integrative system-level analysis of DNA methylation data

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