Eukaryotic translation initiation factor 2 (eIF2) is a G protein that delivers the methionyl initiator tRNA to the small ribosomal subunit and releases it upon GTP hydrolysis after the recognition of the initiation codon. eIF2 is composed of three subunits, alpha, beta, and gamma. Subunit gamma shows the strongest conservation, and it confers both tRNA and GTP/GDP binding. Using intron positioning and protein sequence alignment, here we show that eIF2gamma is a suitable phylogenetic marker for eukaryotes. We determined or completed the sequences of 13 arthropod eIF2gamma genes. Analyzing the phylogenetic distribution of 52 different intron positions in 55 distantly related eIF2gamma genes, we identified ancient ones and shared derived introns in our data set. Obviously, intron positioning in eIF2gamma is evolutionarily conserved. However, there were episodes of complete and partial intron losses followed by intron gains. We identified 17 clusters of intron positions based on their distribution. The evolution of these clusters appears to be connected with preferred exon length and can be used to estimate the relative timing of intron gain because nearby precursor introns had to be erased from the gene before the new introns could be inserted. Moreover, we identified a putative case of intron sliding that constitutes a synapomorphic character state supporting monophyly of Coleoptera, Lepidoptera, and Diptera excluding Hymenoptera. We also performed tree reconstructions using the eIF2gamma protein sequences and intron positioning as phylogenetic information. Our results support the monophyly of Viridoplantae, Ascomycota, Homobasidiomyceta, and Apicomplexa.

Promoter hypermethylation occurs in various tumors and leads to silencing of tumor-relevant genes. Thus, promoter methylation analysis (MA) has been established as an important tool in cancer research and diagnostics. Here we present MethyQESD (methylation-quantification of endonuclease-resistant DNA) as a fast, easy, precise and reliable method for quantitative MA without the need of bisulfite-treatment or fluorescent probes. Though MethyQESD principally works with any gene promoter we established MethyQESD for the mismatch repair gene MLH1 and tested its utility to differentiate between sporadic microsatellite unstable (MSI-H) colorectal cancer and hereditary nonpolyposis colorectal cancer (HNPCC) by quantitative MLH1 MA. We investigated formalin-fixed and paraffin-embedded tissue samples from a previously published, well-characterized tumor collective comprising 25 HNPCC, 14 sporadic MSI-H CRC and 16 sporadic microsatellite stable (MSS) CRC. We found a high accuracy of MethyQESD by spiking experiments with dilution series of methylated (SW48 cancer cell line) and unmethylated (blood) DNA (Pearson's r ¼ 0.9997 (proximal MLH1 promoter region), r ¼ 0.9976 (distal MLH1 promoter region)). MethyQESD and conventional quantitative MA using of 96 formalinfixed and paraffin-embedded CRC showed a high degree of concordance of both methods (Pearson's r ¼ 0.885). HNPCC tumors showed either null MLH1 methylation or a significantly lower degree of MLH1 methylation than sporadic MSI-H CRC (Po0.001). MLH1 methylation was negative in all MSS tumors. Receiver operating characteristic (ROC) curve analyses defined a cutoff value of 16.5% MLH1 methylation for specific and sensitive identification of sporadic MSI-H CRC (area under ROC curve: 1.000; asymptotic significance: Po0.001). Thus, quantitative MLH1 MA by MethyQESD provides a simple, fast and valuable tool to identify HNPCC candidates. Furthermore, MethyQESD works reliably with formalin-fixed paraffin-embedded tissue and simplifies DNA MA both for research and diagnostic purposes.

Epstein-Barr virus (EBV) associated diffuse large B-cell lymphoma (DLBCL) represents a rare aggressive B-cell lymphoma subtype characterized by an adverse clinical outcome. EBV infection of lymphoma cells has been associated with different lymphoma subtypes while the precise role of EBV in lymphomagenesis and specific molecular characteristics of these lymphomas remain elusive. To further unravel the biology of EBV associated DLBCL, we present a comprehensive molecular analysis of overall 60 primary EBV positive (EBV+) DLBCLs using targeted sequencing of cancer candidate genes (CCGs) and genome-wide determination of recurrent somatic copy number alterations (SCNAs) in 46 cases, respectively. Applying the LymphGen classifier 2.0, we found that less than 20% of primary EBV + DLBCLs correspond to one of the established molecular DLBCL subtypes underscoring the unique biology of this entity. We have identified recurrent mutations activating the oncogenic JAK-STAT and NOTCH pathways as well as frequent amplifications of 9p24.1 contributing to immune escape by PD-L1 overexpression. Our findings enable further functional preclinical and clinical studies exploring the therapeutic potential of targeting these aberrations in patients with EBV + DLBCL to improve outcome.

Thymomas and thymic carcinomas (TC) are malignant thymic epithelial tumors (TETs) with poor outcome, if non-resectable. Metabolic signatures of TETs have not yet been studied and may offer new therapeutic options. Metabolic profiles of snap-frozen thymomas (WHO types A, AB, B1, B2, B3, n = 12) and TCs (n = 3) were determined by high resolution magic angle spinning 1H nuclear magnetic resonance (HRMAS 1H-NMR) spectroscopy. Metabolite-based prediction of active KEGG metabolic pathways was achieved with MetPA. In relation to metabolite-based metabolic pathways, gene expression signatures of TETs (n = 115) were investigated in the public “The Cancer Genome Atlas” (TCGA) dataset using gene set enrichment analysis. Overall, thirty-seven metabolites were quantified in TETs, including acetylcholine that was not previously detected in other non-endocrine cancers. Metabolite-based cluster analysis distinguished clinically indolent (A, AB, B1) and aggressive TETs (B2, B3, TCs). Using MetPA, six KEGG metabolic pathways were predicted to be activated, including proline/arginine, glycolysis and glutathione pathways. The activated pathways as predicted by metabolite-profiling were generally enriched transcriptionally in the independent TCGA dataset. Shared high lactic acid and glutamine levels, together with associated gene expression signatures suggested a strong “Warburg effect”, glutaminolysis and redox homeostasis as potential vulnerabilities that need validation in a large, independent cohort of aggressive TETs. If confirmed, targeting metabolic pathways may eventually prove as adjunct therapeutic options in TETs, since the metabolic features identified here are known to confer resistance to cisplatin-based chemotherapy, kinase inhibitors and immune checkpoint blockers, i.e., currently used therapies for non-resectable TETs.