Macrophage-derived IL-1β and TNF-α regulate arginine metabolism in neuroblastoma

© 2018 American Association for Cancer Research. Neuroblastoma is the most common childhood solid tumor, yet the prognosis for high-risk disease remains poor. We demonstrate here that arginase 2 (ARG2) drives neuroblastoma cell proliferation via regulation of arginine metabolism. Targeting arginine metabolism, either by blocking cationic amino acid transporter 1 (CAT-1)-dependent arginine uptake in vitro or therapeutic depletion of arginine by pegylated recombinant arginase BCT-100, significantly delayed tumor development and prolonged murine survival. Tumor cells polarized infiltrating monocytes to an M1-macrophage phenotype, which released IL1b and TNFa in a RAC-alpha serine/threonine-protein kinase (AKT)-dependent manner. IL1b and TNFa established a feedback loop to upregulate ARG2 expression via p38 and extracellular regulated kinases 1/2 (ERK1/2) signaling in neuroblastoma and neural crest-derived cells. Proteomic analysis revealed that enrichment of IL1b and TNFa in stage IV human tumor microenvironments was associated with a worse prognosis. These data thus describe an immune-metabolic regulatory loop between tumor cells and infiltrating myeloid cells regulating ARG2, which can be clinically exploited

Metabolite profiling in retinoblastoma identifies novel clinicopathological subgroups

BACKGROUND: Tumour classification, based on histopathology or molecular pathology, is of value to predict tumour behaviour and to select appropriate treatment. In retinoblastoma, pathology information is not available at diagnosis and only exists for enucleated tumours. Alternative methods of tumour classification, using noninvasive techniques such as magnetic resonance spectroscopy, are urgently required to guide treatment decisions at the time of diagnosis. METHODS: High-resolution magic-angle spinning magnetic resonance spectroscopy (HR-MAS MRS) was undertaken on enucleated retinoblastomas. Principal component analysis and cluster analysis of the HR-MAS MRS data was used to identify tumour subgroups. Individual metabolite concentrations were determined and were correlated with histopathological risk factors for each group. RESULTS: Multivariate analysis identified three metabolic subgroups of retinoblastoma, with the most discriminatory metabolites being taurine, hypotaurine, total-choline and creatine. Metabolite concentrations correlated with specific histopathological features: taurine was correlated with differentiation, total-choline and phosphocholine with retrolaminar optic nerve invasion, and total lipids with necrosis. CONCLUSIONS: We have demonstrated that a metabolite-based classification of retinoblastoma can be obtained using ex vivo magnetic resonance spectroscopy, and that the subgroups identified correlate with histopathological features. This result justifies future studies to validate the clinical relevance of these subgroups and highlights the potential of in vivo MRS as a noninvasive diagnostic tool for retinoblastoma patient stratification