Project description:Giant cell granulomas of the jaws often occur sporadically as single central or peripheral lesions. They are characterized by KRAS, FGFR1, or TRPV4 somatic mutations, the latter occurring exclusively in the central form. Less commonly, multiple giant cell lesions can develop in the context of syndromes such as cherubism, which is an autosomal dominant bone disease. Morphologically, giant cell granulomas can closely resemble other giant cell-rich lesions such as non-ossifying fibroma and aneurysmal bone cyst, and to a minor extent giant cell tumour of bone and chondroblastoma. The epigenetic basis of these giant cell-rich tumours is unclear and, recently, DNA methylation profile has been shown to be clinically useful for the diagnosis of other tumour types, including brain tumours as well as bone and soft tissue sarcomas. Therefore, we aimed to assess the DNA methylation profile of central and peripheral sporadic giant cell granulomas of the jaws and cherubism to test whether DNA methylation patterns can help to distinguish these entities. Additionally, we further compared the DNA methylation profile of these lesions with those of other giant cell-rich mimics to investigate if the microscopic similarities extend to the epigenetic level. Our results showed that central and peripheral sporadic giant cell granulomas of the jaws and cherubism share a related DNA methylation pattern with that of peripheral sporadic giant cell granulomas and cherubism appearing slightly distinct, while central sporadic giant cell granulomas show overlap with both of the former. Non-ossifying fibroma, aneurysmal bone cyst, giant cell tumour of bone, and chondroblastoma, on the other hand, have distinct methylation patterns. Therefore, DNA methylation profiling is currently not capable of clearly distinguishing sporadic and cherubism-associated giant cell lesions of the jaws. Conversely, it could discriminate sporadic giant cell granulomas from their giant cell-rich mimics.
Project description:Large and giant congenital melanocytic nevi (CMN) are rare melanocytic lesions mostly caused by post-zygotic acquisition of NRAS alteration. However, large/giant CMN may exhibit phenotypic differences among distinct areas patients and in addition, patients differ in features such as presence of multiple CMN or Spilus-like lesions. Overall, 50 fresh-frozen biopsies corresponding to 37 phenotypically characterized areas of large/giant CMNs, 9 satellite lesions, 1 acquired nevus and 3 healthy skin biopsies were analyzed by a multigene panel and RNA sequencing (RNA-seq). Mutational screening showed mutations in 76.2% of large/giant CMN. NRAS mutation was found in 57.1% of cases, and mutations in other genes such as BRAF, KRAS, APC and MET were detected in 14.3% of patients. RNA-seq revealed the fusion transcript ZEB2-ALK and SOX5-RAF1 in large/giant CMN from two patients without point mutations. Both alterations were not detected in unaffected skin and were detected in different affected skin. These findings suggest that large/giant CMN may result from distinct molecular events in addition to NRAS mutations including point mutations and fusions transcripts.
Project description:The gut microbiome is a complex ecosystem stratified that varies along different sections of the gut. It comprises a wide array of metabolites originating from both food, host, and microbes. Microbially-derived metabolites, such as bile acids, short-chain fatty acids, and indole derivatives, are of significant interest due to their direct interactions with host physiology and regulating function. Most current studies on the gut microbiome focus on fecal samples, which do not fully represent the upper parts of the gut due to its stratification. To collect microbiome samples from the proximal gut microbiome, endoscopic methods or new non-invasive medical devices can be used. To enable comprehensive profiling of the gut metabolome and analyze key metabolites, we developed a combined approach combining untargeted and semi-targeted metabolomics using a Q-Exactive Plus Orbitrap mass spectrometer. Initially, we selected 49 metabolites of interest for the gut metabolome based on four distinct criteria. We validated these metabolites through repeatability and linearity tests and created a compound database using the software TraceFinder (ThermoFisher Scientific). For untargeted metabolomics, we established a workflow for the annotation and discovery of molecules. Finally, 37 metabolites were validated for semi-targeted metabolomics, and we conducted a proof of concept on small intestinal and fecal samples form a clinical trial (NCT05477069). Our combined approach, facilitated by molecular networking, demonstrated the potential to discover new metabolites.