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Altered DNA methylation is ubiquitous in human cancers and specific methylation changes are often correlated with clinical features. DNA methylation biomarkers, which use those specific methylation changes, provide a range of opportunities for early detection, diagnosis, prognosis, therapeutic stratification and post-therapeutic monitoring. Here we review current approaches to developing and applying DNA methylation biomarkers in cancer therapy. We discuss the obstacles that have so far limited the routine use of DNA methylation biomarkers in clinical settings and describe ways in which these obstacles can be overcome. Finally, we summarize the current state of clinical implementation for some of the most widely studied and well-validated DNA methylation biomarkers, including SEPT9, VIM, SHOX2, PITX2 and MGMT.

The authors identify Irf7 and associated interferon signaling as an important factor suppressing bone metastasis of breast cancers. Irf7 is lost in experimental metastasis and human bone metastastic tissue, and this fosters an immunosuppressive environment that facilitates metastasis. Manipulating this innate immune signaling pathway emerging from tumor cells by interferon administration had beneficial effects in mouse models by reducing bone metastasis and increasing survival time. Breast cancer metastasis is a key determinant of long-term patient survival. By comparing the transcriptomes of primary and metastatic tumor cells in a mouse model of spontaneous bone metastasis, we found that a substantial number of genes suppressed in bone metastases are targets of the interferon regulatory factor Irf7. Restoration of Irf7 in tumor cells or administration of interferon led to reduced bone metastases and prolonged survival time. In mice deficient in the interferon (IFN) receptor or in natural killer (NK) and CD8 + T cell responses, metastasis was accelerated, indicating that Irf7-driven suppression of metastasis was reliant on IFN signaling to host immune cells. We confirmed the clinical relevance of these findings in over 800 patients in which high expression of Irf7-regulated genes in primary tumors was associated with prolonged bone metastasis–free survival. This gene signature may identify patients that could benefit from IFN-based therapies. Thus, we have identified an innate immune pathway intrinsic to breast cancer cells, the suppression of which restricts immunosurveillance to enable metastasis.

DNA methylation based biomarkers have considerable potential for molecular diagnostics, both as tumor specific biomarkers for the early detection or post-therapeutic monitoring of cancer as well as prognostic and predictive biomarkers for therapeutic stratification. Particularly in the former, the accurate estimation of DNA methylation is of compelling importance. However, quantification of DNA methylation has many traps for the unwary, especially when heterogeneous methylation comprising multiple alleles with varied DNA methylation patterns (epialleles) is present. The frequent occurrence of heterogeneous methylation as distinct from a simple mixture of fully methylated and unmethylated alleles is generally not taken into account when DNA methylation is considered as a cancer biomarker. When heterogeneous DNA methylation is present, the proportion of methylated molecules is difficult to quantify without a method that allows the measurement of individual epialleles. In this article, we critically assess the methodologies frequently used to investigate DNA methylation, with an emphasis on the detection and measurement of heterogeneous DNA methylation. The adoption of digital approaches will enable the effective use of heterogeneous DNA methylation as a cancer biomarker.

Background The development of reverse transcription – quantitative real-time PCR (RT-qPCR) platforms that can simultaneously measure the expression of multiple genes is dependent on robust assays that function under identical thermal cycling conditions. The use of a primer optimisation matrix to improve the performance of RT-qPCR assays is often recommended in technical bulletins and manuals. Despite this recommendation, a comprehensive introduction to and evaluation of this approach has been absent from the literature. Therefore, we investigated the impact of varying the primer concentration, leaving all the other reaction conditions unchanged, on a large number of RT-qPCR assays which in this case were designed to be monitored using hydrolysis probes from the Universal Probe Library (UPL) library. Findings Optimal RT-qPCR conditions were determined for 60 newly designed assays. The calculated C q (Quantification Cycle) difference, non-specific amplification, and primer dimer formation for a given assay was often dependent on primer concentration. The chosen conditions were further optimised by testing two different probe concentrations. Varying the primer concentrations had a greater effect on the performance of a RT-qPCR assay than varying the probe concentrations. Conclusion Primer optimisation is important for improving the performance of RT-qPCR assays monitored by UPL probes. This approach would also be beneficial to the performance of other RT-qPCR assays such as those using other types of probes or fluorescent intercalating dyes.

Background Determining the role of DNA methylation in various biological processes is dependent on the accurate representation of often highly complex patterns. Accurate representation is dependent on unbiased PCR amplification post bisulfite modification, regardless of methylation status of any given epiallele. This is highly dependent on primer design. Particular difficulties are raised by the analysis of CpG-rich regions, which are the usual regions of interest. Here, it is often difficult or impossible to avoid placing primers in CpG-free regions, particularly if one wants to target a specific part of a CpG-rich region. This can cause biased amplification of methylated sequences if the C is placed at those positions or to unmethylated sequences if a T is placed at those positions. Methods We examined the effect of various base substitutions at the cytosine position of primer CpGs on the representational amplification of templates and also examined the role of the annealing temperature during PCR. These were evaluated using methylation-sensitive high-resolution melting and Pyrosequencing. Results For a mixture of fully methylated and unmethylated templates, amplification using the C-, C/T (Y-) and inosine-containing primers was biased towards amplification of methylated DNA. The bias towards methylated sequences increased with annealing temperature. Amplification using primers with an A/C/G/T (N) degeneracy at the cytosine positions was not biased at the lowest temperature used but became increasingly biased towards methylated DNA with increased annealing temperature. Using primers matching neither C nor T was in the main unbiased but at the cost of poor PCR amplification efficiency. Primers with abasic sites were also unbiased but could only amplify DNA for one out of the two assays tested. However, with heterogeneous methylation, it appeared that both the primer type and stringency used have a minimal influence on PCR bias. Conclusions This is the first comprehensive analysis of base substitutions at CpG sites in primers and their effect on PCR bias for the analysis of DNA methylation. Our findings are relevant to the appropriate design of a wide range of assays, including amplicon-based next-generation sequencing approaches that need to measure DNA methylation.

Background RNA extracted from formalin-fixed paraffin-embedded (FFPE) samples is chemically modified and degraded, which compromises its use in gene expression studies. Most of the current approaches for RNA quality assessment are not suitable for FFPE derived RNA. Results We have developed a single-tube multiplex endpoint RT-PCR assay specifically designed to evaluate RNA extracted from FFPE tissues for mRNA integrity and performance in reverse transcription - quantitative real-time PCR (RT-qPCR) assays. This single-tube quality control (QC) assay minimises the amount of RNA used in quality control. mRNA integrity and the suitability of RNA for RT-PCR is evaluated by the multiplex endpoint RT-PCR assay using the TBP gene mRNA as the target sequence. The RT-PCR amplicon sizes, 92, 161, 252 and 300 bp, cover a range of amplicon sizes suitable for a wide range of RT-qPCR assays. The QC assay was used to evaluate RNA prepared by two different protocols for extracting total RNA from needle microdissected FFPE breast tumour samples. The amplification products were analysed by gel electrophoresis where the spectrum of amplicon sizes indicated the level of RNA degradation and thus the suitability of the RNA for PCR. The ability of the multiplex endpoint RT-PCR QC assay to identify FFPE samples with an adequate RNA quality was validated by examining the C q values of an RT-qPCR assay with an 87 bp amplicon. Conclusions The multiplex endpoint RT-PCR assay is well suited for the determination of the quality of FFPE derived RNAs, to identify which RT-PCR assays they are suitable for, and is also applicable to assess non-FFPE RNA for gene expression studies. Furthermore, the assay can also be used for the evaluation of RNA extraction protocols from FFPE samples.

CpG island methylation plays an important role in epigenetic gene control during mammalian development and is frequently altered in disease situations such as cancer. The majority of CpG islands is normally unmethylated, but a sizeable fraction is prone to become methylated in various cell types and pathological situations. The goal of this study is to show that a computational epigenetics approach can discriminate between CpG islands that are prone to methylation from those that remain unmethylated. We develop a bioinformatics scoring and prediction method on the basis of a set of 1,184 DNA attributes, which refer to sequence, repeats, predicted structure, CpG islands, genes, predicted binding sites, conservation, and single nucleotide polymorphisms. These attributes are scored on 132 CpG islands across the entire human Chromosome 21, whose methylation status was previously established for normal human lymphocytes. Our results show that three groups of DNA attributes, namely certain sequence patterns, specific DNA repeats, and a particular DNA structure, are each highly correlated with CpG island methylation (correlation coefficients of 0.64, 0.66, and 0.49, respectively). We predicted, and subsequently experimentally examined 12 CpG islands from human Chromosome 21 with unknown methylation patterns and found more than 90% of our predictions to be correct. In addition, we applied our prediction method to analyzing Human Epigenome Project methylation data on human Chromosome 6 and again observed high prediction accuracy. In summary, our results suggest that DNA composition of CpG islands (sequence, repeats, and structure) plays a significant role in predisposing CpG islands for DNA methylation. This finding may have a strong impact on our understanding of changes in CpG island methylation in development and disease.

Background DNA methylation at a gene promoter region has the potential to regulate gene transcription. Patterns of methylation over multiple CpG sites in a region are often complex and cell type specific, with the region showing multiple allelic patterns in a sample. This complexity is commonly obscured when DNA methylation data is summarised as an average percentage value for each CpG site (or aggregated across CpG sites). True representation of methylation patterns can only be fully characterised by clonal analysis. Deep sequencing provides the ability to investigate clonal DNA methylation patterns in unprecedented detail and scale, enabling the proper characterisation of the heterogeneity of methylation patterns. However, the sheer amount and complexity of sequencing data requires new synoptic approaches to visualise the distribution of allelic patterns. Results We have developed a new analysis and visualisation software tool “Methpat”, that extracts and displays clonal DNA methylation patterns from massively parallel sequencing data aligned using Bismark. Methpat was used to analyse multiplex bisulfite amplicon sequencing on a range of CpG island targets across a panel of human cell lines and primary tissues. Methpat was able to represent the clonal diversity of epialleles analysed at specific gene promoter regions. We also used Methpat to describe epiallelic DNA methylation within the mitochondrial genome. Conclusions Methpat can summarise and visualise epiallelic DNA methylation results from targeted amplicon, massively parallel sequencing of bisulfite converted DNA in a compact and interpretable format. Unlike currently available tools, Methpat can visualise the diversity of epiallelic DNA methylation patterns in a sample.

Background Patients with breast cancer have an increased risk of developing subsequent breast cancers. It is important to distinguish whether these tumours are de novo or recurrences of the primary tumour in order to guide the appropriate therapy. Our aim was to investigate the use of DNA methylation profiling and array comparative genomic hybridization (aCGH) to determine whether the second tumour is clonally related to the first tumour. Methods Methylation-sensitive high-resolution melting was used to screen promoter methylation in a panel of 13 genes reported as methylated in breast cancer ( RASSF1A , TWIST1 , APC , WIF1 , MGMT , MAL , CDH13 , RARβ , BRCA1 , CDH1 , CDKN2A , TP73 , and GSTP1 ) in 29 tumour pairs (16 ipsilateral and 13 contralateral). Using the methylation profile of these genes, we employed a Bayesian and an empirical statistical approach to estimate clonal relationship. Copy number alterations were analysed using aCGH on the same set of tumour pairs. Results There is a higher probability of the second tumour being recurrent in ipsilateral tumours compared with contralateral tumours (38 % versus 8 %; p  <0.05) based on the methylation profile. Using previously reported recurrence rates as Bayesian prior probabilities, we classified 69 % of ipsilateral and 15 % of contralateral tumours as recurrent. The inferred clonal relationship results of the tumour pairs were generally concordant between methylation profiling and aCGH. Conclusion Our results show that DNA methylation profiling as well as aCGH have potential as diagnostic tools in improving the clinical decisions to differentiate recurrences from a second de novo tumour.

CBP/p300-interacting transactivator with ED-rich carboxy-terminal domain 4 (CITED4) inhibits HIF-1α transactivation by binding to CBP/p300. We hypothesised that either somatic mutation or hypermethylation of the CITED4 gene underlies CITED4 down-regulation and thus enhanced HIF-1α expression in some breast tumours. DNA sequencing was used to screen for somatic mutations. Methylation-sensitive high resolution melting was performed to identify CITED4 methylation. RT-qPCR was carried out to measure the expression of CITED4 and selected HIF downstream targets. HIF-1α and downstream gene expression was assessed with immunohistochemistry. No somatic mutations of CITED4 were identified in 10 tumour cell lines and 100 breast carcinomas. However, CITED4 promoter methylation was identified in 5/168 breast carcinomas (four infiltrating ductal carcinomas and one infiltrating lobular carcinoma) and in 3/10 breast cancer cell lines (MDA-MB-453, MDA-MB-231 and Hs578T). CITED4 mRNA expression in cell lines was inversely correlated with DNA methylation. CITED4 mRNA expression was significantly increased in all three cell lines after 5-aza-2-deoxycytidine (DAC) treatment. Treatment of the MDA-MB-231 cell line with DAC followed by hypoxia (0.1% O 2 ) resulted in down-regulation of expression of the HIF-1α downstream genes VEGFA and SLC2A1 ( P  = 0.0029). HIF-1α downstream SLC2A1 was decreased ( P  = 0.021) after CITED4 was re-expressed under hypoxia. Loss of expression of CITED4 in breast cancer may be due to DNA methylation but is unlikely to be due to mutation. Demethylation and histone modification can potentially reactivate CITED4 gene expression in some breast cancers and lead to changes in tumour behaviour. Strategies such as HDAC inhibitors may overcome this effect.