👤 Jean-Claude Guillemot

The wide application of RNA sequencing in clinical practice has allowed the discovery of novel fusion genes, which have contributed to a refined molecular classification of rhabdomyosarcoma (RMS). Most fusions in RMS result in aberrant transcription factors, such as PAX3/7::FOXO1 in alveolar RMS (ARMS) and fusions involving VGLL2 or NCOA2 in infantile spindle cell RMS. However, recurrent fusions driving oncogenic kinase activation have not been reported in RMS. Triggered by an index case of an unclassified RMS (overlapping features between ARMS and sclerosing RMS) with a novel FGFR1::ANK1 fusion, we reviewed our molecular files for cases harboring FGFR1-related fusions. One additional case with an FGFR1::TACC1 fusion was identified in a tumor resembling embryonal RMS (ERMS) with anaplasia, but with no pathogenic variants in TP53 or DICER1 on germline testing. Both cases occurred in males, aged 7 and 24, and in the pelvis. The 2nd case also harbored additional alterations, including somatic TP53 and TET2 mutations. Two additional RMS cases (one unclassified, one ERMS) with FGFR1 overexpression but lacking FGFR1 fusions were identified by RNA sequencing. These two cases and the FGFR1::TACC1-positive case clustered together with the ERMS group by RNAseq. This is the first report of RMS harboring recurrent FGFR1 fusions. However, it remains unclear if FGFR1 fusions define a novel subset of RMS or alternatively, whether this alteration can sporadically drive the pathogenesis of known RMS subtypes, such as ERMS. Additional larger series with integrated genomic and epigenetic datasets are needed for better subclassification, as the resulting oncogenic kinase activation underscores the potential for targeted therapy. Show less

To test specific mono-agonists to the glucagon-like peptide-1 receptor (GLP-1R), glucagon receptor (GCGR) and glucose-dependent insulinotropic peptide receptor (GIPR), individually and in combination, in a mouse model of diet-induced non-alcoholic steatohepatitis (NASH) and fibrosis in order to decipher the contribution of their activities and potential additive effects to improving systemic and hepatic metabolism. We induced NASH by pre-feeding C57BL/6J mice a diet rich in fat, fructose and cholesterol for 36 weeks. This was followed by 8 weeks of treatment with the receptor-specific agonists 1-GCG (20 μg/kg twice daily), 2-GLP1 (3 μg/kg twice daily) or 3-GIP (30 μg/kg twice daily), or the dual (1 + 2) or triple (1 + 2 + 3) combinations thereof. A dual GLP-1R/GCGR agonistic peptide, 4-dual-GLP1/GCGR (30 μg/kg twice daily), and liraglutide (100 μg/kg twice daily) were included as references. Whereas low-dose 1-GCG or 3-GIP alone did not influence body weight, liver lipids and histology, their combination with 2-GLP1 provided additional weight loss, reduction in liver triglycerides and improvement in histological disease activity score. Notably, 4-dual-GLP-1R/GCGR and the triple combination of selective mono-agonists led to a significantly stronger reduction in the histological non-alcoholic fatty liver disease activity score compared to high-dose liraglutide, at the same extent of body weight loss. GCGR and GIPR agonism provide additional, body weight-independent improvements on top of GLP-1R agonism in a murine model of manifest NASH with fibrosis. Show less

SPINE (Structural Proteomics In Europe) was established in 2002 as an integrated research project to develop new methods and technologies for high-throughput structural biology. Development areas were broken down into workpackages and this article gives an overview of ongoing activity in the bioinformatics workpackage. Developments cover target selection, target registration, wet and dry laboratory data management and structure annotation as they pertain to high-throughput studies. Some individual projects and developments are discussed in detail, while those that are covered elsewhere in this issue are treated more briefly. In particular, this overview focuses on the infrastructure of the software that allows the experimentalist to move projects through different areas that are crucial to high-throughput studies, leading to the collation of large data sets which are managed and eventually archived and/or deposited. Show less