Overexpression of the histone methyltransferase MMSET in t(4;14)+ multiple myeloma patients is believed to be the driving factor in the pathogenesis of this subtype of myeloma. MMSET catalyzes dimethylation of lysine 36 on histone H3 (H3K36me2), and its overexpression causes a global increase in H3K36me2, redistributing this mark in a broad, elevated level across the genome. Here, we demonstrate that an increased level of MMSET also induces a global reduction of lysine 27 trimethylation on histone H3 (H3K27me3). Despite the net decrease in H3K27 methylation, specific genomic loci exhibit enhanced recruitment of the EZH2 histone methyltransferase and become hypermethylated on this residue. These effects likely contribute to the myeloma phenotype since MMSET-overexpressing cells displayed increased sensitivity to EZH2 inhibition. Furthermore, we demonstrate that such MMSET-mediated epigenetic changes require a number of functional domains within the protein, including PHD domains that mediate MMSET recruitment to chromatin. In vivo, targeting of MMSET by an inducible shRNA reversed histone methylation changes and led to regression of established tumors in athymic mice. Together, our work elucidates previously unrecognized interplay between MMSET and EZH2 in myeloma oncogenesis and identifies domains to be considered when designing inhibitors of MMSET function. Precise spatial and temporal gene expression is required for normal development, and aberrant regulation of gene expression is a common factor in many diseases, including cancer. Histone modifications contribute to the control of gene expression by altering chromatin structure and affecting the recruitment of transcriptional regulators. In this study, we demonstrate interplay between two oncogenic proteins, MMSET and EZH2, known to methylate histone H3 on lysine 36 (H3K36) and lysine 27 (H3K27), respectively. Overexpression of MMSET in myeloma cells increases global levels of H3K36 methylation, alters its normal distribution throughout the genome and decreases global levels of H3K27 methylation. We found that while the majority of the genome loses H3K27 methylation in the presence of MMSET, certain loci have augmented recruitment of EZH2 and enhanced H3K27 methylation, leading to transcriptional repression. Repression of these genes likely plays an important role in the disease because MMSET-overexpressing cells show higher sensitivity to small molecule inhibitors targeting EZH2-mediated methylation. Thus, our study suggests that the specific local changes may outweigh the gross global changes we frequently observe in cancer and implicates EZH2 as a novel therapeutic target in myeloma cells.

Background. Gene fusions arising from chromosomal translocations have been implicated in cancer. RNA-seq has the potential to discover such rearrangements generating functional proteins (chimera/fusion). Recently, many methods for chimeras detection have been published. However, specificity and sensitivity of those tools were not extensively investigated in a comparative way. Results. We tested eight fusion-detection tools (FusionHunter, FusionMap, FusionFinder, MapSplice, deFuse, Bellerophontes, ChimeraScan, and TopHat-fusion) to detect fusion events using synthetic and real datasets encompassing chimeras. The comparison analysis run only on synthetic data could generate misleading results since we found no counterpart on real dataset. Furthermore, most tools report a very high number of false positive chimeras. In particular, the most sensitive tool, ChimeraScan, reports a large number of false positives that we were able to significantly reduce by devising and applying two filters to remove fusions not supported by fusion junction-spanning reads or encompassing large intronic regions. Conclusions. The discordant results obtained using synthetic and real datasets suggest that synthetic datasets encompassing fusion events may not fully catch the complexity of RNA-seq experiment. Moreover, fusion detection tools are still limited in sensitivity or specificity; thus, there is space for further improvement in the fusion-finder algorithms.

Antisense long noncoding RNAs (ncRNAs) are transcripts emerging from the opposite strand of a coding-RNA region and their role in heart failure (HF) is largely unknown. Additionally, HF and Alzheimer’s disease (AD) share several non-genetic effectors and risk factors. We investigated the regulation of the β-secretase-1 (BACE1) gene and of its antisense transcript BACE1-AS in ischaemic HF. BACE1 and BACE1-AS expression was measured in left ventricle biopsies from 18 patients affected by non-end stage ischaemic HF and 17 matched controls. The levels of both transcripts were increased in HF patients. Likewise, both transcripts increased also in a mouse model of ischaemic HF, and their expression was directly correlated. BACE1-AS was expressed by all cardiac cell types and BACE1-AS up- or down-modulation in cultured cardiomyocytes and endothelial cells induced a concordant regulation of the cognate BACE1 transcript. Interestingly, BACE1 increase also induced the intracellular accumulation of its product β-amyloid. In keeping with these findings, higher BACE1 protein and β-amyloid peptide levels were also observed in HF. Moreover, increased β-amyloid 1-40 was also found in the plasma of HF patients. Transcriptomic changes of BACE1-AS overexpressing and β-amyloid 1-40 treated cells were largely overlapping and indicated changes of relevant biological process such as ‘cell cycle and proliferation’, ‘apoptosis’, and ‘DNA repair’ as well as ‘TGFβ-, TNFα-, p38-, EGFR-signalling’, suggesting a potential maladaptive role of the BACE1-AS/BACE1/β-amyloid axis. Accordingly, the administration of β-amyloid peptides decreased the cell viability in endothelial cells and in both human IPS-derived and mouse cardiomyocytes. Moreover, both β-amyloid treatment and BACE1-AS overexpression increased endothelial cell apoptosis, and this effect was prevented by BACE1 silencing. Given the neurotoxic role of β-amyloid in AD, dysregulation of the BACE1/BACE1-AS/β-amyloid axis might be relevant in HF pathogenesis, further implicating ncRNAs in the complex scenario of proteotoxicity in cardiac dysfunction.

Circular RNAs are generated by back‐splicing of precursor‐mRNAs. Although they have been known for many years, only recently we have started to appreciate their widespread expression and their regulatory functions in a variety of biological processes. Not surprisingly, circular RNA dysregulation and participation in the pathogenic mechanisms have started to emerge in many instances, including cardiovascular diseases. Detection, differential expression analysis and validation are the three critical points for the characterization of any RNA, and circular RNAs are no exception. Their characteristics, however, generate several problems that are yet to be completely addressed, and literature still lacks comprehensive definitions of well‐defined best practices. We present a map of the current knowledge regarding circular RNAs and the critical issues limiting our understanding of their regulation and function. The goal was to provide the readers with the tools to critically decide which of the many approaches available is most suitable to their experimental plan. Although particularly focused on cardiovascular diseases, most critical issues concerning circular RNAs are common to many other fields of investigation.