Detailed DNA methylation characterisation of phyllodes tumours identifies a signature of malignancy and distinguishes phyllodes from metaplastic breast carcinoma.

Phyllodes tumours (PTs) are rare fibroepithelial lesions of the breast that are classified as benign, borderline, or malignant. As little is known about the molecular underpinnings of PTs, current diagnosis relies on histological examination. However, accurate classification is often difficult, particularly for distinguishing borderline from malignant PTs. Furthermore, PTs can be misdiagnosed as other tumour types with shared histological features, such as fibroadenoma and metaplastic breast cancers. As DNA methylation is a recognised hallmark of many cancers, we hypothesised that DNA methylation could provide novel biomarkers for diagnosis and tumour stratification in PTs, whilst also allowing insight into the molecular aetiology of this otherwise understudied tumour. We generated whole-genome methylation data using the Illumina EPIC microarray in a novel PT cohort (n = 33) and curated methylation microarray data from published datasets including PTs and other potentially histopathologically similar tumours (total n = 817 samples). Analyses revealed that PTs have a unique methylome compared to normal breast tissue and to potentially histopathologically similar tumours (metaplastic breast cancer, fibroadenoma and sarcomas), with PT-specific methylation changes enriched in gene sets involved in KRAS signalling and epithelial-mesenchymal transition. Next, we identified 53 differentially methylated regions (DMRs) (false discovery rate < 0.05) that specifically delineated malignant from non-malignant PTs. The top DMR in both discovery and validation cohorts was hypermethylation at the HSD17B8 CpG island promoter. Matched PT single-cell expression data showed that HSD17B8 had minimal expression in fibroblast (putative tumour) cells. Finally, we created a methylation classifier to distinguish PTs from metaplastic breast cancer samples, where we revealed a likely misdiagnosis for two TCGA metaplastic breast cancer samples. In conclusion, DNA methylation alterations are associated with PT histopathology and hold the potential to improve our understanding of PT molecular aetiology, diagnostics, and risk stratification. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Characterisation and reproducibility of the HumanMethylationEPIC v2.0 BeadChip for DNA methylation profiling.

BACKGROUND: The Illumina family of Infinium Methylation BeadChip microarrays has been widely used over the last 15 years for genome-wide DNA methylation profiling, including large-scale and population-based studies, due to their ease of use and cost effectiveness. Succeeding the popular HumanMethylationEPIC BeadChip (EPICv1), the recently released Infinium MethylationEPIC v2.0 BeadChip (EPICv2) claims to extend genomic coverage to more than 935,000 CpG sites. Here, we comprehensively characterise the reproducibility, reliability and annotation of the EPICv2 array, based on bioinformatic analysis of both manifest data and new EPICv2 data from diverse biological samples. RESULTS: We find a high degree of reproducibility with EPICv1, evidenced by comparable sensitivity and precision from empirical cross-platform comparison incorporating whole genome bisulphite sequencing (WGBS), and high correlation between technical sample replicates, including between samples with DNA input levels below the manufacturer's recommendation. We provide a full assessment of probe content, evaluating genomic distribution and changes from previous array versions. We characterise EPICv2's new feature of replicated probes and provide recommendations as to the superior probes. In silico analysis of probe sequences demonstrates that probe cross-hybridisation remains a significant problem in EPICv2. By mapping the off-target sites at single nucleotide resolution and comparing with WGBS we show empirical evidence for preferential off-target binding. CONCLUSIONS: Overall, we find EPICv2 a worthy successor to the previous Infinium methylation microarrays, however some technical issues remain. To support optimal EPICv2 data analysis we provide an expanded version of the EPICv2 manifest to aid researchers in understanding probe design, data processing, choosing appropriate probes for analysis and for integration with methylation datasets from previous versions of the Infinium Methylation BeadChip.

DNA methylation profiling identifies epigenetic differences between early versus late stages of diabetic chronic kidney disease.

BACKGROUND: We investigated a cross-sectional epigenome-wide association study of patients with early and late diabetes-associated chronic kidney disease (CKD) to identify possible epigenetic differences between the two groups as well as changes in methylation across all stages of diabetic CKD. We also evaluated the potential of using a panel of identified 5'-C-phosphate-G-3' (CpG) sites from this cohort to predict the progression of diabetic CKD. METHODS: This cross-sectional study recruited 119 adults. DNA was extracted from blood using the Qiagen QIAampDNA Mini Spin Kit. Genome-wide methylation analysis was performed using Illumina Infinium MethylationEPIC BeadChips (HM850K). Intensity data files were processed and analysed using the minfi and MissMethyl packages for R. We examined the degree of methylation of CpG sites in early versus late diabetic CKD patients for CpG sites with an unadjusted P-value <0.01 and an absolute change in methylation of 5% (n = 239 CpG sites). RESULTS: Hierarchical clustering of the 239 CpG sites largely separated the two groups. A heat map for all 239 CpG sites demonstrated distinct methylation patterns in the early versus late groups, with CpG sites showing evidence of progressive change. Based on our differentially methylated region (DMR) analysis of the 239 CpG sites, we highlighted two DMRs, namely the cysteine-rich secretory protein 2 (CRISP2) and piwi-like RNA-mediated gene silencing 1 (PIWIL1) genes. The best predictability for the two groups involved a receiver operating characteristics curve of eight CpG sites alone and achieved an area under the curve of 0.976. CONCLUSIONS: We have identified distinct DNA methylation patterns between early and late diabetic CKD patients as well as demonstrated novel findings of potential progressive methylation changes across all stages (1-5) of diabetic CKD at specific CpG sites. We have also identified associated genes CRISP2 and PIWIL1, which may have the potential to act as stage-specific diabetes-associated CKD markers, and showed that the use of a panel of eight identified CpG sites alone helps to increase the predictability for the two groups.

The potential of epigenetic therapy to target the 3D epigenome in endocrine-resistant breast cancer.

Three-dimensional (3D) epigenome remodeling is an important mechanism of gene deregulation in cancer. However, its potential as a target to counteract therapy resistance remains largely unaddressed. Here, we show that epigenetic therapy with decitabine (5-Aza-mC) suppresses tumor growth in xenograft models of pre-clinical metastatic estrogen receptor positive (ER+) breast tumor. Decitabine-induced genome-wide DNA hypomethylation results in large-scale 3D epigenome deregulation, including de-compaction of higher-order chromatin structure and loss of boundary insulation of topologically associated domains. Significant DNA hypomethylation associates with ectopic activation of ER-enhancers, gain in ER binding, creation of new 3D enhancer-promoter interactions and concordant up-regulation of ER-mediated transcription pathways. Importantly, long-term withdrawal of epigenetic therapy partially restores methylation at ER-enhancer elements, resulting in a loss of ectopic 3D enhancer-promoter interactions and associated gene repression. Our study illustrates the potential of epigenetic therapy to target ER+ endocrine-resistant breast cancer by DNA methylation-dependent rewiring of 3D chromatin interactions, which are associated with the suppression of tumor growth.

Identification of DNA methylation biomarkers with potential to predict response to neoadjuvant chemotherapy in triple-negative breast cancer.

Neoadjuvant chemotherapy (NAC) is used to treat triple-negative breast cancer (TNBC) prior to resection. Biomarkers that accurately predict a patient's response to NAC are needed to individualise therapy and avoid chemotoxicity from unnecessary chemotherapy. We performed whole-genome DNA methylation profiling on diagnostic TNBC biopsy samples from the Sequential Evaluation of Tumours Undergoing Preoperative (SETUP) NAC study. We found 9 significantly differentially methylated regions (DMRs) at diagnosis which were associated with response to NAC. We show that 4 of these DMRs are associated with TNBC overall survival (P < 0.05). Our results highlight the potential of DNA methylation biomarkers for predicting NAC response in TNBC.

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry.

Complex diseases are often underpinned by multiple common genetic variants that contribute to disease susceptibility. Here, we describe a cost-effective tag single nucleotide polymorphism (SNP) approach using a multiplexed genotyping assay with mass spectrometry, to investigate gene pathway associations in clinical cohorts. We investigate the food allergy candidate locus Interleukin13 (IL13) as an example. This method efficiently maximizes the coverage by taking advantage of shared linkage disequilibrium (LD) within a region. Selected LD SNPs are then designed into a multiplexed assay, enabling up to 40 different SNPs to be analyzed simultaneously, boosting cost-effectiveness. Polymerase chain reaction (PCR) is used to amplify the target loci, followed by single nucleotide extension, and the amplicons are then measured using matrix-assisted laser desorption/ionization-time of flight(MALDI-TOF) mass spectrometry. The raw output is analyzed with the genotype calling software, using stringent quality control definitions and cut-offs, and high probability genotypes are determined and output for data analysis.

DNA methylation at IL32 in juvenile idiopathic arthritis.

Juvenile idiopathic arthritis (JIA) is the most common autoimmune rheumatic disease of childhood. We recently showed that DNA methylation at the gene encoding the pro-inflammatory cytokine interleukin-32 (IL32) is reduced in JIA CD4+ T cells. To extend this finding, we measured IL32 methylation in CD4+ T-cells from an additional sample of JIA cases and age- and sex-matched controls, and found a reduction in methylation associated with JIA consistent with the prior data (combined case-control dataset: 25.0% vs 37.7%, p = 0.0045). Further, JIA was associated with reduced IL32 methylation in CD8+ T cells (15.2% vs 25.5%, p = 0.034), suggesting disease-associated changes to a T cell precursor. Additionally, we measured regional SNPs, along with CD4+ T cell expression of total IL32, and the γ and ß isoforms. Several SNPs were associated with methylation. Two SNPs were also associated with JIA, and we found evidence of interaction such that methylation was only associated with JIA in minor allele carriers (e.g. rs10431961 p(interaction) = 0.011). Methylation at one measured CpG was inversely correlated with total IL32 expression (Spearman r = -0.73, p = 0.0009), but this was not a JIA-associated CpG. Overall, our data further confirms that reduced IL32 methylation is associated with JIA, and that SNPs play an interactive role.