Excessive Lipid Production Shapes Glioma Tumor Microenvironment

Disrupted lipid metabolism is a characteristic of gliomas. This study utilizes an ultrastructural approach to characterize the prevalence and distribution of lipids within gliomas. This study made use of tissue from IDH1 wild type (IDH1-wt) glioblastoma (n = 18) and IDH1 mutant (IDH1-mt) astrocytoma (n = 12) tumors. We uncover a prevalent and intriguing surplus of lipids. The bulk of the lipids manifested as sizable cytoplasmic inclusions and extracellular deposits in the tumor microenvironment (TME); in some tumors the lipids were stored in the classical membraneless spheroidal lipid droplets (LDs). Frequently, lipids accumulated inside mitochondria, suggesting possible dysfunction of the beta-oxidation pathway. Additionally, the tumor vasculature have lipid deposits in their lumen and vessel walls; this lipid could have shifted in from the tumor microenvironment or have been produced by the vessel-invading tumor cells. Lipid excess in gliomas stems from disrupted beta-oxidation and dysfunctional oxidative phosphorylation pathways. The implications of this lipid-driven environment include structural support for the tumor cells and protection against immune responses, non-lipophilic drugs, and free radicals.

Profile Characterization of Biogenic Amines in Glioblastoma Patients Undergoing Standard-of-Care Treatment

INTRODUCTION

Biogenic amines play important roles throughout cellular metabolism. This study explores a role of biogenic amines in glioblastoma pathogenesis. Here, we characterize the plasma levels of biogenic amines in glioblastoma patients undergoing standard-of-care treatment.

METHODS

We examined 138 plasma samples from 36 patients with isocitrate dehydrogenase (IDH) wild-type glioblastoma at multiple stages of treatment. Untargeted gas chromatography-time of flight mass spectrometry (GC-TOF MS) was used to measure metabolite levels. Machine learning approaches were then used to develop a predictive tool based on these datasets.

RESULTS

Surgery was associated with increased levels of 12 metabolites and decreased levels of 11 metabolites. Chemoradiation was associated with increased levels of three metabolites and decreased levels of three other metabolites. Ensemble learning models, specifically random forest (RF) and AdaBoost (AB), accurately classified treatment phases with high accuracy (RF: 0.81 ± 0.04, AB: 0.78 ± 0.05). The metabolites sorbitol and N-methylisoleucine were identified as important predictive features and confirmed via SHAP.

CONCLUSION

To our knowledge, this is the first study to describe plasma biogenic amine signatures throughout the treatment of patients with glioblastoma. A larger study is needed to confirm these results with hopes of developing a diagnostic algorithm.

Sequential perturbations to mouse corticogenesis following in utero maternal immune activation

In utero exposure to maternal immune activation (MIA) is an environmental risk factor for neurodevelopmental and neuropsychiatric disorders. Animal models provide an opportunity to identify mechanisms driving neuropathology associated with MIA. We performed time-course transcriptional profiling of mouse cortical development following induced MIA via poly(I:C) injection at E12.5. MIA-driven transcriptional changes were validated via protein analysis, and parallel perturbations to cortical neuroanatomy were identified via imaging. MIA-induced acute upregulation of genes associated with hypoxia, immune signaling, and angiogenesis, by 6 hr following exposure. This acute response was followed by changes in proliferation, neuronal and glial specification, and cortical lamination that emerged at E14.5 and peaked at E17.5. Decreased numbers of proliferative cells in germinal zones and alterations in neuronal and glial populations were identified in the MIA-exposed cortex. Overall, paired transcriptomic and neuroanatomical characterization revealed a sequence of perturbations to corticogenesis driven by mid-gestational MIA.

Baseline immunoreactivity before pregnancy and poly(I:C) dose combine to dictate susceptibility and resilience of offspring to maternal immune activation

Despite the potential of rodent models of maternal immune activation (MIA) to identify new biomarkers and therapeutic interventions for a range of psychiatric disorders, current approaches using these models ignore two of the most important aspects of this risk factor for human disease: (i) most pregnancies are resilient to maternal viral infection and (ii) susceptible pregnancies can lead to different combinations of phenotypes in offspring. Here, we report two new sources of variability-the baseline immunoreactivity (BIR) of isogenic females prior to pregnancy and differences in immune responses in C57BL/6 dams across vendors-that contribute to resilience and susceptibility to distinct combinations of behavioral and biological outcomes in offspring. Similar to the variable effects of human maternal infection, MIA in mice does not cause disease-related phenotypes in all pregnancies and a combination of poly(I:C) dose and BIR predicts susceptibility and resilience of pregnancies to aberrant repetitive behaviors and alterations in striatal protein levels in offspring. Even more surprising is that the intermediate levels of BIR and poly(I:C) dose are most detrimental to offspring, with higher BIR and poly(I:C) doses conferring resilience to measured phenotypes in offspring. Importantly, we identify the BIR of female mice as a biomarker before pregnancy that predicts which dams will be most at risk as well as biomarkers in the brains of newborn offspring that correlate with changes in repetitive behaviors. Together, our results highlight considerations for optimizing MIA protocols to enhance rigor and reproducibility and reveal new factors that drive susceptibility of some pregnancies and resilience of others to MIA-induced abnormalities in offspring.