Next-generation sequencing technologies for DNA methylation analyses in cancer genomics

Enrichment of Cis-Acting Regulatory Elements in Differentially Methylated Regions Following Lipopolysaccharide Treatment of Bovine Endometrial Epithelial Cells

Endometritis is an inflammatory disease that negatively influences fertility and is common in milk-producing cows. An in vitro model for bovine endometrial inflammation was used to identify enrichment of cis-acting regulatory elements in differentially methylated regions (DMRs) in the genome of in vitro-cultured primary bovine endometrial epithelial cells (bEECs) before and after treatment with lipopolysaccharide (LPS) from E. coli, a key player in the development of endometritis. The enriched regulatory elements contain binding sites for transcription factors with established roles in inflammation and hypoxia including NFKB and Hif-1α. We further showed co-localization of certain enriched cis-acting regulatory motifs including ARNT, Hif-1α, and NRF1. Our results show an intriguing interplay between increased mRNA levels in LPS-treated bEECs of the mRNAs encoding the key transcription factors such as AHR, EGR2, and STAT1, whose binding sites were enriched in the DMRs. Our results demonstrate an extraordinary cis-regulatory complexity in these DMRs having binding sites for both inflammatory and hypoxia-dependent transcription factors. Obtained data using this in vitro model for bacterial-induced endometrial inflammation have provided valuable information regarding key transcription factors relevant for clinical endometritis in both cattle and humans.

Positional effects revealed in Illumina methylation array and the impact on analysis

AIM

We aimed to prove the existence of positional effects in the Illumina methylation beadchip data and to find an optimal correction method.

MATERIALS & METHODS

Three HumanMethylation450, three HumanMethylation27 datasets and two EPIC datasets were analyzed. ComBat, linear regression, functional normalization and single-sample Noob were used for minimizing positional effects. The corrected results were evaluated by four methods.

RESULTS

We detected 52,988 CpG loci significantly associated with sample positions, 112 remained after ComBat correction in the primary dataset. The pre- and postcorrection comparisons indicate the positional effects could alter the measured methylation values and downstream analysis results.

CONCLUSION

Positional effects exist in the Illumina methylation array and may bias the analyses. Using ComBat to correct positional effects is recommended.

Object-oriented regression for building predictive models with high dimensional omics data from translational studies

Maturing omics technologies enable researchers to generate high dimension omics data (HDOD) routinely in translational clinical studies. In the field of oncology, The Cancer Genome Atlas (TCGA) provided funding support to researchers to generate different types of omics data on a common set of biospecimens with accompanying clinical data and has made the data available for the research community to mine. One important application, and the focus of this manuscript, is to build predictive models for prognostic outcomes based on HDOD. To complement prevailing regression-based approaches, we propose to use an object-oriented regression (OOR) methodology to identify exemplars specified by HDOD patterns and to assess their associations with prognostic outcome. Through computing patient's similarities to these exemplars, the OOR-based predictive model produces a risk estimate using a patient's HDOD. The primary advantages of OOR are twofold: reducing the penalty of high dimensionality and retaining the interpretability to clinical practitioners. To illustrate its utility, we apply OOR to gene expression data from non-small cell lung cancer patients in TCGA and build a predictive model for prognostic survivorship among stage I patients, i.e., we stratify these patients by their prognostic survival risks beyond histological classifications. Identification of these high-risk patients helps oncologists to develop effective treatment protocols and post-treatment disease management plans. Using the TCGA data, the total sample is divided into training and validation data sets. After building up a predictive model in the training set, we compute risk scores from the predictive model, and validate associations of risk scores with prognostic outcome in the validation data (P-value=0.015).

Oral benzo[a]pyrene: understanding pharmacokinetics, detoxication, and consequences--Cyp1 knockout mouse lines as a paradigm

Benzo[a]pyrene (BaP) is a prototypical polycyclic aromatic hydrocarbon (PAH); this ubiquitous environmental carcinogenic agent is found in tobacco smoke, charcoal-grilled foods, and PAH-contaminated surfaces of roofs, playgrounds, and highways. Cytochrome P450 1 wild-type, Cyp1a2(-/-), Cyp1b1(-/-), or Cyp1a2/1b1(-/-) knockouts, and mice with Cyp1a1 expression deleted in hepatocytes can ingest large oral BaP doses (125 mg/kg/d) without apparent toxicity. Cyp1a1(-/-) and Cyp1a1/1a2(-/-) knockouts and mice with Cyp1a1 expression deleted in gastrointestinal (GI) tract epithelial cells develop immunotoxicity and die within 32 days, indicating that GI tract inducible CYP1A1 is absolutely required for detoxication of oral BaP. Cyp1a1/1b1(-/-) and Cyp1a1/1a2/1b1(-/-) mice are rescued from immunosuppression and early death due to absent metabolic activation of BaP by CYP1B1 in immune cells. Ten-fold lower oral BaP doses result in adenocarcinoma of the proximal small intestine (PSI) in Cyp1a1(-/-) mice; Cyp1a1/1b1(-/-) double-knockout mice show no PSI cancer but develop squamous cell carcinoma of the preputial gland duct (PGD). BaP-metabolizing CYP1B1 in the PSI and CYP3A59 in the PGD are the most likely candidates to participate in tumor initiation in the epithelial cells of these two tissues; oncogenes and tumor-suppressor genes upregulated and downregulated during tumorigenesis are completely different between these tissues. This "oral BaP Cyp1" mouse paradigm represents a powerful teaching tool, showing that gene-environment interactions depend on route-of-administration: the same oral, but not intraperitoneal, BaP exposure leads to dramatic differences in target-organ toxicity and tumor type as a function of dose and Cyp1 genotype.

Reverse vaccinology in the 21st century: improvements over the original design

Reverse vaccinology (RV), the first application of genomic technologies in vaccine research, represented a major revolution in the process of discovering novel vaccines. By determining their entire antigenic repertoire, researchers could identify protective targets and design efficacious vaccines for pathogens where conventional approaches had failed. Bexsero, the first vaccine developed using RV, has recently received positive opinion from the European Medicines Agency. The use of RV initiated a cascade of changes that affected the entire vaccine development process, shifting the focus from the identification of a list of vaccine candidates to the definition of a set of high throughput screens to reduce the need for costly and labor intensive tests in animal models. It is now clear that a deep understanding of the epidemiology of vaccine candidates, and their regulation and role in host-pathogen interactions, must become an integral component of the screening workflow. Far from being outdated by technological advancements, RV still represents a paradigm of how high-throughput technologies and scientific insight can be integrated into biotechnology research.

Targeted DNA methylation analysis by high throughput sequencing in porcine peri-attachment embryos

The purpose of this experiment was to implement and evaluate the effectiveness of a next-generation sequencing-based method for DNA methylation analysis in porcine embryonic samples. Fourteen discrete genomic regions were amplified by PCR using bisulfite-converted genomic DNA derived from day 14 in vivo-derived (IVV) and parthenogenetic (PA) porcine embryos as template DNA. Resulting PCR products were subjected to high-throughput sequencing using the Illumina Genome Analyzer IIx platform. The average depth of sequencing coverage was 14,611 for IVV and 17,068 for PA. Quantitative analysis of the methylation profiles of both input samples for each genomic locus showed distinct differences in methylation profiles between IVV and PA samples for six of the target loci, and subtle differences in four loci. It was concluded that high throughput sequencing technologies can be effectively applied to provide a powerful, cost-effective approach to targeted DNA methylation analysis of embryonic and other reproductive tissues.

Genomics and epigenomics of colorectal cancer

Colorectal cancer is one of the most common cancer types worldwide and accounts for approximately 600,000 deaths annually. Work over the last decades has uncovered a number of tumor-suppressor and oncogenes which are frequently mutated and might thus be responsible for the malignant transformation. However, only with the development of new high-throughput technologies systematic analyses of the genome and epigenomes became feasible. While data generation has increased exponential, we are now faced with new challenges to transform these data into useful models that help predicting the outcome of genomic aberrations and to develop novel diagnostic and therapeutic strategies. As a basis for the modeling it is essential to understand and integrate current knowledge. We review previous and current ideas in colorectal cancer development and focus on a pathway oriented view. We show that colorectal cancer is a multilayer complex disease affecting the genome as well as the epigenome with direct consequences on the gene and microRNA (miRNA) expression signatures. The goal is to illustrate the current principles of colorectal cancer pathogenesis and to illustrate the need for elaborate computer modeling systems.

Complete pipeline for Infinium(®) Human Methylation 450K BeadChip data processing using subset quantile normalization for accurate DNA methylation estimation

BACKGROUND

Huge progress has been made in the development of array- or sequencing-based technologies for DNA methylation analysis. The Illumina Infinium(®) Human Methylation 450K BeadChip (Illumina Inc., CA, USA) allows the simultaneous quantitative monitoring of more than 480,000 CpG positions, enabling large-scale epigenotyping studies. However, the assay combines two different assay chemistries, which may cause a bias in the analysis if all signals are merged as a unique source of methylation measurement.

MATERIALS & METHODS

We confirm in three 450K data sets that Infinium I signals are more stable and cover a wider dynamic range of methylation values than Infinium II signals. We evaluated the methylation profile of Infinium I and II probes obtained with different normalization protocols and compared these results with the methylation values of a subset of CpGs analyzed by pyrosequencing.

RESULTS

We developed a subset quantile normalization approach for the processing of 450K BeadChips. The Infinium I signals were used as 'anchors' to normalize Infinium II signals at the level of probe coverage categories. Our normalization approach outperformed alternative normalization or correction approaches in terms of bias correction and methylation signal estimation. We further implemented a complete preprocessing protocol that solves most of the issues currently raised by 450K array users.

CONCLUSION

We developed a complete preprocessing pipeline for 450K BeadChip data using an original subset quantile normalization approach that performs both sample normalization and efficient Infinium I/II shift correction. The scripts, being freely available from the authors, will allow researchers to concentrate on the biological analysis of data, such as the identification of DNA methylation signatures.

Formalin fixation in the '-omics' era: a primer for the surgeon-scientist

Formalin is the most commonly used tissue fixative worldwide. While it offers excellent morphological preservation for routine histology, it has detrimental effects on nucleic acids. Most studies of nucleic acids have therefore used fresh frozen tissue, the collection and storage of which is resource intensive. The ability to use modern genomic, transcriptomic and epigenomic methods with nucleic acids derived from formalin-fixed, paraffin-embedded (FFPE) tissues would allow enormous archives of routinely stored tissues (usually with well-annotated clinical data) to be used for translational research. This paper outlines the effects of formalin on nucleic acids, describes ways of minimizing nucleic acid degradation and optimizing extraction, and reviews recent studies that have used contemporary techniques to analyse FFPE-derived nucleic acids (with a focus on malignant tissue sources). Simple tips are also offered to ensure the utility of your institution's samples for future studies, and broadly applicable guidelines are listed for those contemplating their own study using FFPE-derived material.