MicroRNA expression in high‐grade B‐cell lymphoma with 11q aberration

Mature aggressive B-cell lymphomas, such as Burkitt lymphoma (BL) and Diffuse large B-cell lymphoma (DLBCL), show variations in microRNA (miRNA) expression. The entity of High-grade B-cell lymphoma with 11q aberration (HGBCL-11q) shares several biological features with both BL and DLBCL but data on its miRNA expression profile are yet scarce. Hence, this study aims to analyze the potential differences in miRNA expression of HGBCL-11q compared to BL and DLBCL. We evaluated the expression profiles of 2083 miRNAs in 25 HGCBL-11q, 7 BL, 131 DLBCL, and tonsils using the HTG EdgeSeq miRNA whole transcriptome assay. Uniform manifold approximation and projection (UMAP) and differential gene expression analyses based on DESeq2 were carried out. UMAP analysis of miRNA expression did not reveal distinct groups among the studied lymphomas. However, differential gene expression investigations detected sets of overexpressed miRNAs in HGBCL-11q when compared to BL (miR-9-3p, miR-9-5p, miR-3919, miR-129-1-3p, miR-129-2-3p, miR-331-3p, miR-196b-5p, and miR-28-5p) and DLBCL (miR-3919, miR-1290, miR-4538, and miR-4791), respectively. Notably, miR-3919 showed heterogeneous but significantly higher expression (p-value < 0.001) in HGBCL-11q than in both, BL and DLBCL. We identified a group of differentially expressed miRNAs between HGBCL-11q vs. BL and DLBCL, with miR-3919 as the most commonly and recurrently overexpressed miRNA in HGBCL-11q

Epstein-Barr virus status of sporadic Burkitt lymphoma is associated with patient age and mutational features

Sporadic Burkitt lymphoma (BL) is the most frequent tumour of children and adolescents but a rare subtype of lymphomas in adults. To date most molecular data have been obtained from lymphomas arising in the young. Recently, Epstein-Barr virus (EBV) positive and negative BL in young patients was shown to differ in molecular features. In the present study, we present a large age-overarching cohort of sporadic BL (n = 162) analysed by immunohistochemistry, translocations of MYC proto-oncogene, basic helix-loop-helix transcription factor (MYC), B-cell leukaemia/lymphoma 2 (BCL2) and B-cell leukaemia/lymphoma 6 (BCL6) and by targeted sequencing. We illustrate an age-associated inter-tumoral molecular heterogeneity in this disease. Mutations affecting inhibitor of DNA binding 3, HLH protein (ID3), transcription factor 3 (TCF3) and cyclin D3 (CCND3), which are highly recurrent in paediatric BL, and expression of sex determining region Y-box transcription factor 11 (SOX11) declined with patient age at diagnosis (P = 0·0204 and P = 0·0197 respectively). In contrast, EBV was more frequently detected in adult patients (P = 0·0262). Irrespective of age, EBV-positive sporadic BL showed significantly less frequent mutations in ID3/TCF3/CCND3 (P = 0·0088) but more often mutations of G protein subunit alpha 13 (GNA13; P = 0·0368) and forkhead box O1 (FOXO1; P = 0·0044) compared to EBV-negative tumours. Our findings suggest that among sporadic BL an EBV-positive subgroup of lymphomas increases with patient age that shows distinct pathogenic features reminiscent of EBV-positive endemic BL

Identification of genetic elements in metabolism by high-throughput mouse phenotyping.

Metabolic diseases are a worldwide problem but the underlying genetic factors and their relevance to metabolic disease remain incompletely understood. Genome-wide research is needed to characterize so-far unannotated mammalian metabolic genes. Here, we generate and analyze metabolic phenotypic data of 2016 knockout mouse strains under the aegis of the International Mouse Phenotyping Consortium (IMPC) and find 974 gene knockouts with strong metabolic phenotypes. 429 of those had no previous link to metabolism and 51 genes remain functionally completely unannotated. We compared human orthologues of these uncharacterized genes in five GWAS consortia and indeed 23 candidate genes are associated with metabolic disease. We further identify common regulatory elements in promoters of candidate genes. As each regulatory element is composed of several transcription factor binding sites, our data reveal an extensive metabolic phenotype-associated network of co-regulated genes. Our systematic mouse phenotype analysis thus paves the way for full functional annotation of the genome

Identification of genetic elements in metabolism by high-throughput mouse phenotyping

Metabolic diseases are a worldwide problem but the underlying genetic factors and their relevance to metabolic disease remain incompletely understood. Genome-wide research is needed to characterize so-far unannotated mammalian metabolic genes. Here, we generate and analyze metabolic phenotypic data of 2016 knockout mouse strains under the aegis of the International Mouse Phenotyping Consortium (IMPC) and find 974 gene knockouts with strong metabolic phenotypes. 429 of those had no previous link to metabolism and 51 genes remain functionally completely unannotated. We compared human orthologues of these uncharacterized genes in five GWAS consortia and indeed 23 candidate genes are associated with metabolic disease. We further identify common regulatory elements in promoters of candidate genes. As each regulatory element is composed of several transcription factor binding sites, our data reveal an extensive metabolic phenotype-associated network of co-regulated genes. Our systematic mouse phenotype analysis thus paves the way for full functional annotation of the genome