Genomic comparison of malignant melanoma and atypical Spitz tumor in the pediatric population.

BACKGROUND/OBJECTIVES: The diagnostic distinction between atypical Spitz tumor (AST) and malignant melanoma (MM) in pediatric tumors is challenging. Molecular tests are increasingly used to characterize these neoplasms; however, limited studies are available in pediatric patients. This study aimed to provide a genomic comparison of pediatric MM and AST in the context of comprehensive clinical annotation. METHODS: Pediatric patients diagnosed with MM (n=11) and AST (n=12) were compared to a cohort of 693 adult melanoma patients. DNA next-generation sequencing assessed kinase gene fusions, tumor mutational burden, sequence variants, copy number alterations, structural variants, microsatellite instability, and mutational signatures. RESULTS: Seven AST cases and eight MM cases were successfully sequenced. Kinase gene fusions were identified in both the MM and AST cohorts (NTRK1, ROS1, and MET). MM cases had TERT, BRAF, and CDKN2A alterations, which were not identified in the AST cohort. Tumor mutational burden (TMB) analysis showed pediatric ASTs had an average of 2.82 mutations/Mb, pediatric MM had an average of 5.7 mutations/Mb, and adult MM cases averaged 18.8 mut/Mb. One pediatric MM case had an elevated TMB of 15 mutations/Mb and a UV mutational signature. CONCLUSIONS: These data expand our understanding of pediatric malignant melanoma. The differences between the molecular signatures for AST and MM are not statistically significant, and histopathology remains the gold standard for the diagnosis of pediatric AST and MM at this time. With more data, molecular studies may provide additional support for diagnosis and targeted therapeutics.

Metabolic characterization of the chitinolytic bacterium Serratia marcescens using a genome-scale metabolic model.

BACKGROUND: Serratia marcescens is a chitinolytic bacterium that can potentially be used for consolidated bioprocessing to convert chitin to value-added chemicals. Currently, S. marcescens is poorly characterized and studies on intracellular metabolic and regulatory mechanisms would expedite development of bioprocessing applications. RESULTS: In this study, our goal was to characterize the metabolic profile of S. marcescens to provide insight for metabolic engineering applications and fundamental biological studies. Hereby, we constructed a constraint-based genome-scale metabolic model (iSR929) including 929 genes, 1185 reactions and 1164 metabolites based on genomic annotation of S. marcescens Db11. The model was tested by comparing model predictions with experimental data and analyzed to identify essential aspects of the metabolic network (e.g. 138 essential genes predicted). The model iSR929 was refined by integrating RNAseq data of S. marcescens growth on three different carbon sources (glucose, N-acetylglucosamine, and glycerol). Significant differences in TCA cycle utilization were found for growth on the different carbon substrates, For example, for growth on N-acetylglucosamine, S. marcescens exhibits high pentose phosphate pathway activity and nucleotide synthesis but low activity of the TCA cycle. CONCLUSIONS: Our results show that S. marcescens model iSR929 can provide reasonable predictions and can be constrained to fit with experimental values. Thus, our model may be used to guide strain designs for metabolic engineering to produce chemicals such as 2,3-butanediol, N-acetylneuraminic acid, and n-butanol using S. marcescens.