Explore the vast range of titles available.

DNA methylation is a widely investigated epigenetic mark with important roles in development and disease. High-throughput assays enable genome-scale DNA methylation analysis in large numbers of samples. Here, we describe a new version of our RnBeads software - an R/Bioconductor package that implements start-to-finish analysis workflows for Infinium microarrays and various types of bisulfite sequencing. RnBeads 2.0 ( https://rnbeads.org/ ) provides additional data types and analysis methods, new functionality for interpreting DNA methylation differences, improved usability with a novel graphical user interface, and better use of computational resources. We demonstrate RnBeads 2.0 in four re-runnable use cases focusing on cell differentiation and cancer.

Cancer of unknown primary ranks in the top ten cancer presentations and has an extremely poor prognosis. Identification of the primary tumour and development of a tailored site-specific therapy could improve the survival of these patients. We examined the feasability of using DNA methylation profiles to determine the occult original cancer in cases of cancer of unknown primary. We established a classifier of cancer type based on the microarray DNA methylation signatures (EPICUP) in a training set of 2790 tumour samples of known origin representing 38 tumour types and including 85 metastases. To validate the classifier, we used an independent set of 7691 known tumour samples from the same tumour types that included 534 metastases. We applied the developed diagnostic test to predict the tumour type of 216 well-characterised cases of cancer of unknown primary. We validated the accuracy of the predictions from the EPICUP assay using autopsy examination, follow-up for subsequent clinical detection of the primary sites months after the initial presentation, light microscopy, and comprehensive immunohistochemistry profiling. The tumour type classifier based on the DNA methylation profiles showed a 99·6% specificity (95% CI 99·5–99·7), 97·7% sensitivity (96·1–99·2), 88·6% positive predictive value (85·8–91·3), and 99·9% negative predictive value (99·9–100·0) in the validation set of 7691 tumours. DNA methylation profiling predicted a primary cancer of origin in 188 (87%) of 216 patients with cancer with unknown primary. Patients with EPICUP diagnoses who received a tumour type-specific therapy showed improved overall survival compared with that in patients who received empiric therapy (hazard ratio [HR] 3·24, p=0·0051 [95% CI 1·42–7·38]; log-rank p=0·0029). We show that the development of a DNA methylation based assay can significantly improve diagnoses of cancer of unknown primary and guide more precise therapies associated with better outcomes. Epigenetic profiling could be a useful approach to unmask the original primary tumour site of cancer of unknown primary cases and a step towards the improvement of the clinical management of these patients. European Research Council (ERC), Cellex Foundation, the Institute of Health Carlos III (ISCIII), Cancer Australia, Victorian Cancer Agency, Samuel Waxman Cancer Research Foundation, the Health and Science Departments of the Generalitat de Catalunya, and Ferrer.

Computational analysis and interactive visualization of biological networks and protein structures are common tasks for gaining insight into biological processes. This protocol describes three workflows based on the NetworkAnalyzer and RINalyzer plug-ins for Cytoscape, a popular software platform for networks. NetworkAnalyzer has become a standard Cytoscape tool for comprehensive network topology analysis. In addition, RINalyzer provides methods for exploring residue interaction networks derived from protein structures. The first workflow uses NetworkAnalyzer to perform a topological analysis of biological networks. The second workflow applies RINalyzer to study protein structure and function and to compute network centrality measures. The third workflow combines NetworkAnalyzer and RINalyzer to compare residue networks. The full protocol can be completed in ∼2 h.

Christoph Plass and colleagues investigate the transcriptomic and epigenomic changes induced by treatment with inhibitors of DNMT and HDAC in cancer cell lines. They observe large numbers of treatment-induced non-annotated TSSs (TINATs) encoded in long-terminal repeats that are normally repressed in most cell types. Several mechanisms of action have been proposed for DNA methyltransferase and histone deacetylase inhibitors (DNMTi and HDACi), primarily based on candidate-gene approaches. However, less is known about their genome-wide transcriptional and epigenomic consequences. By mapping global transcription start site (TSS) and chromatin dynamics, we observed the cryptic transcription of thousands of treatment-induced non-annotated TSSs (TINATs) following DNMTi and HDACi treatment. The resulting transcripts frequently splice into protein-coding exons and encode truncated or chimeric ORFs translated into products with predicted abnormal or immunogenic functions. TINAT transcription after DNMTi treatment coincided with DNA hypomethylation and gain of classical promoter histone marks, while HDACi specifically induced a subset of TINATs in association with H2AK9ac, H3K14ac, and H3K23ac. Despite this mechanistic difference, both inhibitors convergently induced transcription from identical sites, as we found TINATs to be encoded in solitary long terminal repeats of the ERV9/LTR12 family, which are epigenetically repressed in virtually all normal cells.

Christoph Plass, Christopher Oakes and colleagues study genome-wide DNA methylation dynamics during B cell maturation and the pathogenic role of transcription factor dysregulation in chronic lymphocytic leukemia (CLL). By comparing normal and malignant B cells, they find that tumors derive from a continuum of maturation states, which correlate with different clinical outcomes. Charting differences between tumors and normal tissue is a mainstay of cancer research. However, clonal tumor expansion from complex normal tissue architectures potentially obscures cancer-specific events, including divergent epigenetic patterns. Using whole-genome bisulfite sequencing of normal B cell subsets, we observed broad epigenetic programming of selective transcription factor binding sites coincident with the degree of B cell maturation. By comparing normal B cells to malignant B cells from 268 patients with chronic lymphocytic leukemia (CLL), we showed that tumors derive largely from a continuum of maturation states reflected in normal developmental stages. Epigenetic maturation in CLL was associated with an indolent gene expression pattern and increasingly favorable clinical outcomes. We further uncovered that most previously reported tumor-specific methylation events are normally present in non-malignant B cells. Instead, we identified a potential pathogenic role for transcription factor dysregulation in CLL, where excess programming by EGR and NFAT with reduced EBF and AP-1 programming imbalances the normal B cell epigenetic program.

A multicenter comparison of DNA methylation assays identifies robust methods for translational research and clinical diagnostics. DNA methylation patterns are altered in numerous diseases and often correlate with clinically relevant information such as disease subtypes, prognosis and drug response. With suitable assays and after validation in large cohorts, such associations can be exploited for clinical diagnostics and personalized treatment decisions. Here we describe the results of a community-wide benchmarking study comparing the performance of all widely used methods for DNA methylation analysis that are compatible with routine clinical use. We shipped 32 reference samples to 18 laboratories in seven different countries. Researchers in those laboratories collectively contributed 21 locus-specific assays for an average of 27 predefined genomic regions, as well as six global assays. We evaluated assay sensitivity on low-input samples and assessed the assays' ability to discriminate between cell types. Good agreement was observed across all tested methods, with amplicon bisulfite sequencing and bisulfite pyrosequencing showing the best all-round performance. Our technology comparison can inform the selection, optimization and use of DNA methylation assays in large-scale validation studies, biomarker development and clinical diagnostics.

Alexander Schramm, Johannes Schulte and colleagues characterize 16 paired samples from patients with neuroblastoma at diagnosis and relapse using whole-exome sequencing, mRNA expression profiling, array CGH and DNA methylation analysis. Their data show the frequency, identity and evolution of genetic alterations in neuroblastoma. Neuroblastoma is a malignancy of the developing sympathetic nervous system that is often lethal when relapse occurs. We here used whole-exome sequencing, mRNA expression profiling, array CGH and DNA methylation analysis to characterize 16 paired samples at diagnosis and relapse from individuals with neuroblastoma. The mutational burden significantly increased in relapsing tumors, accompanied by altered mutational signatures and reduced subclonal heterogeneity. Global allele frequencies at relapse indicated clonal mutation selection during disease progression. Promoter methylation patterns were consistent over disease course and were patient specific. Recurrent alterations at relapse included mutations in the putative CHD5 neuroblastoma tumor suppressor, chromosome 9p losses, DOCK8 mutations, inactivating mutations in PTPN14 and a relapse-specific activity pattern for the PTPN14 target YAP. Recurrent new mutations in HRAS , KRAS and genes mediating cell-cell interaction in 13 of 16 relapse tumors indicate disturbances in signaling pathways mediating mesenchymal transition. Our data shed light on genetic alteration frequency, identity and evolution in neuroblastoma.

ObjectiveA detailed understanding of the molecular alterations in different forms of cholangiocarcinogenesis is crucial for a better understanding of cholangiocarcinoma (CCA) and may pave the way to early diagnosis and better treatment options.DesignWe analysed a clinicopathologically well-characterised patient cohort (n=54) with high-grade intraductal papillary (IPNB) or tubulopapillary (ITPN) neoplastic precursor lesions of the biliary tract and correlated the results with an independent non-IPNB/ITPN associated CCA cohort (n=294). The triplet sample set of non-neoplastic biliary epithelium, precursor and invasive CCA was analysed by next generation sequencing, DNA copy number and genome-wide methylation profiling.ResultsPatients with invasive CCA arising from IPNB/ITPN had better prognosis than patients with CCA not associated with IPNB/ITPN. ITPN was localised mostly intrahepatic, whereas IPNB was mostly of extrahepatic origin. IPNB/ITPN were equally associated with small-duct and large-duct type intrahepatic CCA. IPNB exhibited mutational profiles of extrahepatic CCA, while ITPN had significantly fewer mutations. Most mutations were shared between precursor lesions and corresponding invasive CCA but ROBO2 mutations occurred exclusively in invasive CCA and CTNNB1 mutations were mainly present in precursor lesions. In addition, IPNB and ITPN differed in their DNA methylation profiles and analyses of latent methylation components suggested that IPNB and ITPN may have different cells-of-origin.ConclusionIntegrative analysis revealed that IPNB and ITPN harbour distinct early genetic alterations, IPNB are enriched in mutations typical for extrahepatic CCA, whereas ITPN exhibited few genetic alterations and showed distinct epigenetic profiles. In conclusion, IPNB/ITPN may represent a distinctive, intermediate form of intrahepatic and extrahepatic cholangiocarcinogenesis.

Juvenile myelomonocytic leukemia (JMML) is an aggressive myeloproliferative disorder of early childhood characterized by mutations activating RAS signaling. Established clinical and genetic markers fail to fully recapitulate the clinical and biological heterogeneity of this disease. Here we report DNA methylome analysis and mutation profiling of 167 JMML samples. We identify three JMML subgroups with unique molecular and clinical characteristics. The high methylation group (HM) is characterized by somatic PTPN11 mutations and poor clinical outcome. The low methylation group is enriched for somatic NRAS and CBL mutations, as well as for Noonan patients, and has a good prognosis. The intermediate methylation group (IM) shows enrichment for monosomy 7 and somatic KRAS mutations. Hypermethylation is associated with repressed chromatin, genes regulated by RAS signaling, frequent co-occurrence of RAS pathway mutations and upregulation of DNMT1 and DNMT3B , suggesting a link between activation of the DNA methylation machinery and mutational patterns in JMML. Juvenile myelomonocytic leukemia (JMML) is an aggressive disease with limited options for treatment. Here, the authors analyse the DNA methylome and mutational profile of JMML to define three subgroups with unique molecular and clinical characteristics.

Pancreatic acinar cell carcinoma (ACC) is an aggressive exocrine tumor with largely unknown biology. Here, to identify potential targets for personalized treatment, we perform integrative genome-wide and epigenome-wide analyses. The results show frequently aberrant DNA methylation, abundant chromosomal amplifications and deletions, and mutational signatures suggesting defective DNA repair. In contrast to pancreatic ductal adenocarcinoma, no recurrent point mutations are detected. The tumor suppressors ID3 , ARID1A , APC , and CDKN2A are frequently impaired also on the protein level and thus potentially affect ACC tumorigenesis. Consequently, this work identifies promising therapeutic targets in ACC for drugs recently approved for precision cancer therapy. Pancreatic acinar cell carcinoma (ACC) is an aggressive exocrine tumor with largely unknown biology. Here, the authors perform genome- and epigenome-wide analyses from normal and ACC pancreatic tissue that identify aberrations in genome stability and cell cycle control.