MYCN-driven fatty acid uptake is a metabolic vulnerability in neuroblastoma

Half of high-risk neuroblastoma patients have MYCN amplification. Here, the authors show that MYCN induces fatty acid uptake and synthesis to support neuroblastoma and inhibition of a fatty acid transporter impairs tumor progression in preclinical models.Neuroblastoma (NB) is a childhood cancer arising from sympatho-adrenal neural crest cells. MYCN amplification is found in half of high-risk NB patients; however, no available therapies directly target MYCN. Using multi-dimensional metabolic profiling in MYCN expression systems and primary patient tumors, we comprehensively characterized the metabolic landscape driven by MYCN in NB. MYCN amplification leads to glycerolipid accumulation by promoting fatty acid (FA) uptake and biosynthesis. We found that cells expressing amplified MYCN depend highly on FA uptake for survival. Mechanistically, MYCN directly upregulates FA transport protein 2 (FATP2), encoded by SLC27A2. Genetic depletion of SLC27A2 impairs NB survival, and pharmacological SLC27A2 inhibition selectively suppresses tumor growth, prolongs animal survival, and exerts synergistic anti-tumor effects when combined with conventional chemotherapies in multiple preclinical NB models. This study identifies FA uptake as a critical metabolic dependency for MYCN-amplified tumors. Inhibiting FA uptake is an effective approach for improving current treatment regimens

Phase stability of the earth-abundant tin sulfides SnS, SnS2, and Sn2S3

The various phases of tin sulfide have been studied as semiconductors since the 1960s and are now being investigated as potential earth-abundant photovoltaic and photocatalytic materials. Of particular note is the recent isolation of zincblende SnS in particles and thin-films. Herein, first-principles calculations are employed to better understand this novel geometry and its place within the tin sulfide multiphasic system. We report the enthalpies of formation for the known phases of SnS, SnS2, and Sn2S3, with good agreement between theory and experiment for the ground-state structures of each. While theoretical X-ray diffraction patterns do agree with the assignment of the zincblende phase demonstrated in the literature, the structure is not stable close to the lattice parameters observed experimentally, exhibiting an unfeasibly large pressure and a formation enthalpy much higher than any other phase. Ab initio molecular dynamics simulations reveal spontaneous degradation to an amorphous phase much lower in energy, as Sn(II) is inherently unstable in a regular tetrahedral environment. We conclude that the known rocksalt phase of SnS has been mis-assigned as zincblende in the recent literature

Image-guided subject-specific modeling of glymphatic transport and amyloid deposition

The glymphatic system is a brain-wide system of perivascular networks that facilitate exchange of cerebrospinal fluid (CSF) and interstitial fluid (ISF) to remove waste products from the brain. A greater understanding of the mechanisms for glymphatic transport may provide insight into how amyloid beta (Aβ) and tau agglomerates, key biomarkers for Alzheimer's disease and other neurodegenerative diseases, accumulate and drive disease progression. In this study, we develop an image-guided computational model to describe glymphatic transport and Aβ deposition throughout the brain. Aβ transport and deposition are modeled using an advection–diffusion equation coupled with an irreversible amyloid accumulation (damage) model. We use immersed isogeometric analysis, stabilized using the streamline upwind Petrov–Galerkin (SUPG) method, where the transport model is constructed using parameters inferred from brain imaging data resulting in a subject-specific model that accounts for anatomical geometry and heterogeneous material properties. Both short-term (30-min) and long-term (12-month) 3D simulations of soluble amyloid transport within a mouse brain model were constructed from diffusion weighted magnetic resonance imaging (DW-MRI) data. In addition to matching short-term patterns of tracer deposition, we found that transport parameters such as CSF flow velocity play a large role in amyloid plaque deposition. The computational tools developed in this work will facilitate investigation of various hypotheses related to glymphatic transport and fundamentally advance our understanding of its role in neurodegeneration, which is crucial for the development of preventive and therapeutic interventions.</p