Gautier, E. L. | Search bioRxiv

bioRxiv2021

Neural crest-related NXPH1/α-NRXN signaling opposes neuroblastoma malignancy by inhibiting metastasis

Neuroblastoma is a pediatric cancer that can present as low- or high-risk tumors (LR-NBs and HR-NBs), the latter group showing poor prognosis due to metastasis and strong resistance to current therapy. NBs are known to originate from alterations to cells in the sympatho-adrenal lineage derived from the neural crest, but whether LR-NBs and HR-NBs differ in the way they exploit the transcriptional program underlying their developmental origin remains unclear. Here, we compared the transcriptional landscapes of primary samples of LR-NBs, HR-NBs and human fetal adrenal gland, and thereby identified the transcriptional signature associated to NB formation that further distinguishes LR-NBs from HR-NBs. The majority of the genes comprising this signature belong to the core sympatho-adrenal developmental program, are associated with favorable patient prognosis and with diminished disease progression. The top candidate gene of this list, Neurexophilin-1 (NXPH1), encodes a ligand of the transmembrane receptors -Neurexins (-NRXNs). Our functional in vivo and in vitro assays reveal that NXPH1/-NRXN signaling has a dual impact on NB behavior: whereas NXPH1 and -NRXN1 promote NB tumor growth by stimulating cell proliferation, they conversely inhibit the ability of NB cells to form metastases. Our findings uncover a module of the neural crest-derived sympatho-adrenal developmental program that opposes neuroblastoma malignancy by impeding metastasis, and pinpoint NXPH1/-NRXN signaling as a promising target to treat HR-NBs.

neuroscience↗

bioRxiv2020

Open Source ImmGen: network perspective on metabolic diversity among mononuclear phagocytes

We dissect metabolic variability of mononuclear phagocyte (MNP) subpopulations across different tissues through integrative analysis of three large scale datasets. Specifically, we introduce ImmGen MNP Open Source dataset that profiled 337 samples and extended previous ImmGen effort which included 202 samples of mononuclear phagocytes and their progenitors. Next, we analysed Tabula Muris Senis dataset to extract data for 51,364 myeloid cells from 18 tissues. Taken together, a compendium of data assembled in this work covers phagocytic populations found across 38 different tissues. To analyse common metabolic features, we developed novel network-based computational approach for unbiased identification of key metabolic subnetworks based on cellular transcriptional profiles in large-scale datasets. Using ImmGen MNP Open Source dataset as baseline, we define 9 metabolic subnetworks that encapsulate the metabolic differences within mononuclear phagocytes, and demonstrate that these features are robustly found across all three datasets, including lipid metabolism, cholesterol biosynthesis, glycolysis, and a set of fatty acid related metabolic pathways, as well as nucleotide and folate metabolism. We systematically define major features specific to macrophage and dendritic cell subpopulations. Among other things, we find that cholesterol synthesis appears particularly active within the migratory dendritic cells. We demonstrate that interference with this pathway through statins administration diminishes migratory capacity of the dendritic cells in vivo. This result demonstrates the power of our approach and highlights importance of metabolic diversity among mononuclear phagocytes.

immunology↗