Malignant melanoma (MM) can spread to other organs and is resistant in part due to the presence of cancer stem cell subpopulations (CSCs). While a controversial high dose of interferon-alpha (IFN-α) has been used to treat non-metastatic high-risk melanoma, it comes with undesirable side effects. In this study, we evaluated the effect of low and high doses of IFN-α on CSCs by analyzing ALDH activity, side population and specific surface markers in established and patient-derived primary cell lines. We also assessed the clonogenicity, migration and tumor initiation capacities of IFN-α treated CSCs. Additionally, we investigated genomic modulations related to stemness properties using microRNA sequencing and microarrays. The effect of IFN-α on CSCs-derived exosomes was also analyzed using NanoSight and liquid chromatography (LC-HRMS)-based metabolomic analysis, among others. Our results showed that even low doses of IFN-α reduced CSC formation and stemness properties, and led to a significant decrease in the ability to form tumors in mice xenotransplants. IFN-α also modulated the expression of genes and microRNAs involved in several cancer processes and metabolomics of released exosomes. Our work suggests the utility of low doses of interferon, combined with the analysis of metabolic biomarkers, as a potential clinical approach against the aggressiveness of CSCs in melanoma.

The prediction of novel miRNA genes generally requires the availability of genome sequences in order to assess important properties such as the characteristic hairpinshaped secondary structure. However, although the sequencing costs have decreased over the last years, still many important species lack an assembled genome of certain quality. We implemented an algorithm which for the first time exploits characteristic biogenesis features like the 5' homogeneity that can be assessed without genome sequences. We used a phylogenetically broad spectrum of well annotated animal genomes for benchmarking. We found that between 90-100% of the most expressed miRNA candidates (top quartile) corresponded to known miRNA sequences.

BACKGROUND Diffuse lower grade gliomas (LGGs) are generally slow growing primary central nervous system tumors that occur in early adult life. The prevalence of isocitrate dehydrogenase (IDH) mutations is high in LGG, and induces excess production of the oncometabolite 2-hydroxyglutarate (2-HG). These gain-of-function mutations play a key role in promoting metabolic reprogramming of the cancer cell that affects activity of α-KG dependent demethylases. Inhibition of DNA demethylase activity leads to glioma with a CpG island methylator phenotype (G-CIMP). Whether the activity of RNA demethylases and methylation status of tRNAs in LGG are modulated by changes in IDH-status is unknown. AIM: To investigate whether IDH mutations play a role in reprogramming of tRNA modifications in adult glioma. MATERIALS AND METHODS We combined small RNAseq and LC-MS/MS analysis to identify distinct tRNA processing patterns and methylation signatures in LGG tissues. To address important experimental bottlenecks that limit RNAseq-based detection of tRNA and possibly other modified small noncoding RNAs, we employed a tailored small RNAseq method with validation of specific methylation sites by mass-spectrometry. RESULTS Our customized small RNAseq approach yielded >100 fold increase in sequencing reads per tRNA type, thereby dramatically improving tRNA detection when compared to currently used small RNAseq approaches. Moreover, LC-MS/MS analysis revealed a higher abundance of modified nucleosides in tRNA from IDH-mutant LGG compared to IDH-wildtype LGG. Analysis of tRNA from IDH-mutant and IDH-wildtype LGG using the combination of our tailored small RNAseq and LC-MS/MS methodology demonstrated strong differential tRNA expression, tRFs processing and tRNA methylation. CONCLUSION We described an approach that makes use of tailored small RNA sequencing combined with mass-spectrometry that enables insights into cancer driven alterations in tRNA methylation patterns and differential tRNA processing signatures. Our data implies that tumor metabolic reprogramming deregulates tRNA methylation, contributing to an altered epitranscriptomic code in IDH-mutant LGG.