Tumors have aberrant proteomes that often do not match their corresponding transcriptome profiles. One possible cause of this discrepancy is the existence of aberrant RNA modification landscapes in the so-called epitranscriptome. Here, we report that human glioma cells undergo DNA methylation-associated epigenetic silencing of NSUN5, a candidate RNA methyltransferase for 5-methylcytosine. In this setting, NSUN5 exhibits tumor-suppressor characteristics in vivo glioma models. We also found that NSUN5 loss generates an unmethylated status at the C3782 position of 28S rRNA that drives an overall depletion of protein synthesis, and leads to the emergence of an adaptive translational program for survival under conditions of cellular stress. Interestingly, NSUN5 epigenetic inactivation also renders these gliomas sensitive to bioactivatable substrates of the stress-related enzyme NQO1. Most importantly, NSUN5 epigenetic inactivation is a hallmark of glioma patients with long-term survival for this otherwise devastating disease.Electronic supplementary materialThe online version of this article (10.1007/s00401-019-02062-4) contains supplementary material, which is available to authorized users.

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Background Chimeric antigen receptor (CAR) T-cells directed against CD19 (CART19) are effective in B-cell malignancies, but little is known about the molecular factors predicting clinical outcome of CART19 therapy. The increasingly recognized relevance of epigenetic changes in cancer immunology prompted us to determine the impact of the DNA methylation profiles of CART19 cells on the clinical course. Methods We recruited 114 patients with B-cell malignancies, comprising 77 acute lymphoblastic leukemia (ALL) and 37 non-Hodgkin lymphoma (NHL) patients, who were treated with CART19 cells. Using a comprehensive DNA methylation microarray, we determined the epigenomic changes that occur in the patient T-cells upon transduction of the CAR vector. The effects of the identified DNA methylation sites on clinical response, cytokine release syndrome (CRS), immune effector cell-associated neurotoxicity syndrome (ICANS), event-free survival (EFS) and overall survival (OS) were assessed. All statistical tests were 2-sided. Results We identified 984 genomic sites with differential DNA methylation between CAR-untransduced and CAR-transduced T-cells before infusion into the patient. Eighteen of these distinct epigenetic loci were associated with complete response (CR) adjusting by multiple testing. Using the sites linked to CR, the EPICART signature was established in the initial discovery cohort (n = 79), which was associated with CR (Fisher’s exact test, P<.001) and enhanced EFS (HR = 0.36, 95% CI = 0.19 to 0.70, P=.002; log-rank P=.003) and OS (HR = 0.45, 95% CI = 0.20 to 0.99, P=.047; log-rank P=.04;). Most important the EPICART profile maintained its clinical course predictive value in the validation cohort (n = 35) where it was associated with CR (Fisher’s exact test, P<.001) and enhanced OS (HR = 0.31, 95% CI = 0.11 to 0.84, P=.02; log-rank P=.02). Conclusions We show that the DNA methylation landscape of patient CART19 cells influences the efficacy of the cellular immunotherapy treatment in patients with B-cell malignancy.

Noncoding RNAs (ncRNAs), such as microRNAs and long noncoding RNAs (lncRNAs), participate in cellular transformation. Work done in the last decade has also demonstrated that ncRNAs with growth-inhibitory functions can undergo promoter CpG island hypermethylation-associated silencing in tumorigenesis. Herein, we wondered whether circular RNAs (circRNAs), a type of RNA transcripts lacking 5′-3′ ends and forming closed loops that are gaining relevance in cancer biology, are also a target of epigenetic inactivation in tumors. To tackle this issue, we have used cancer cells genetically deficient for the DNA methyltransferase enzymes in conjuction with circRNA expression microarrays. We have found that the loss of DNA methylation provokes a release of circRNA silencing. In particular, we have identified that promoter CpG island hypermethylation of the genes TUSC3 (tumor suppressor candidate 3), POMT1 (protein O-mannosyltransferase 1), ATRNL1 (attractin-like 1) and SAMD4A (sterile alpha motif domain containing 4A) is linked to the transcriptional downregulation of both linear mRNA and the hosted circRNA. Although some circRNAs regulate the linear transcript, we did not observe changes in TUSC3 mRNA levels upon TUSC3 circ104557 overexpression. Interestingly, we found circRNA-mediated regulation of target miRNAs and an in vivo growth inhibitory effect upon TUSC3 circ104557 transduction. Data mining for 5′-end CpG island methylation of TUSC3, ATRNL1, POMT1 and SAMD4A in cancer cell lines and primary tumors showed that the epigenetic defect was commonly observed among different tumor types in association with the diminished expression of the corresponding transcript. Our findings support a role for circRNA DNA methylation-associated loss in human cancer.

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Mouse has been extensively used as a model organism in many studies to characterize biological pathways and drug effects and to mimic human diseases. Similar DNA sequences between both species facilitate these types of experiments. However, much less is known about the mouse epigenome, particularly for DNA methylation. Progress in delivering mouse DNA methylomes has been slow due to the currently available time-consuming and expensive methodologies. Following the great acceptance of the human DNA methylation microarrays, we have herein validated a newly developed DNA methylation microarray (Infinium Mouse Methylation BeadChip) that interrogates 280,754 unique CpG sites within the mouse genome. The CpGs included in the platform cover CpG Islands, shores, shelves and open sea sequences, and loci surrounding transcription start sites and gene bodies. From a functional standpoint, mouse ENCODE representative DNase hypersensitivity sites (rDHSs) and candidate cis-Regulatory Elements (cCREs) are also included. Herein, we show that the profiled mouse DNA methylation microarray provides reliable values among technical replicates; matched results from fresh frozen versus formalin-fixed samples; detects hemimethylated X-chromosome and imprinted CpG sites; and is able to determine CpG methylation changes in mouse cell lines treated with a DNA demethylating agent or upon genetic disruption of a DNA methyltransferase. Most important, using unsupervised hierarchical clustering and t-SNE approaches, the platform is able to classify all types of normal mouse tissues and organs. These data underscore the great features of the assessed microarray to obtain comprehensive DNA methylation profiles of the mouse genome.