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Aims: Targeting tumor metabolism may improve the outcomes for patients with glioblastoma (GBM). To further preclinical efforts targeting metabolism in GBM, we tested the hypothesis that brain tumors can be stratified into distinct metabolic groups with different patient outcomes. Therefore, to determine if tumor metabolites relate to patient survival, we profiled the metabolomes of human gliomas and correlated metabolic information with clinical data. Results: We found that isocitrate dehydrogenase-wildtype (IDHwt) GBMs are metabolically distinguishable from IDH mutated (IDHmut) astrocytomas and oligodendrogliomas. Survival of patients with IDHmut gliomas was expectedly more favorable than those with IDHwt GBM, and metabolic signatures can stratify IDHwt GBMs subtypes with varying prognoses. Patients whose GBMs were enriched in amino acids had improved survival, while those whose tumors were enriched for nucleotides, redox molecules, and lipid metabolites fared more poorly. These findings were recapitulated in validation cohorts using both metabolomic and transcriptomic data. Innovation: Our results suggest the existence of metabolic subtypes of GBM with differing prognoses, and further support the concept that metabolism may drive the aggressiveness of human gliomas. Conclusions: Our data show that metabolic signatures of human gliomas can inform patient survival. These findings may be used clinically to tailor novel metabolically targeted agents for GBM patients with different metabolic phenotypes. Antioxid. Redox Signal. 39, 942-956.

We present an integromic analysis of gene alterations that modulate transforming growth factor β (TGF-β)-Smad-mediated signaling in 9,125 tumor samples across 33 cancer types in The Cancer Genome Atlas (TCGA). Focusing on genes that encode mediators and regulators of TGF-β signaling, we found at least one genomic alteration (mutation, homozygous deletion, or amplification) in 39% of samples, with highest frequencies in gastrointestinal cancers. We identified mutation hotspots in genes that encode TGF-β ligands (BMP5), receptors (TGFBR2, AVCR2A, and BMPR2), and Smads (SMAD2 and SMAD4). Alterations in the TGF-β superfamily correlated positively with expression of metastasis-associated genes and with decreased survival. Correlation analyses showed the contributions of mutation, amplification, deletion, DNA methylation, and miRNA expression to transcriptional activity of TGF-β signaling in each cancer type. This study provides a broad molecular perspective relevant for future functional and therapeutic studies of the diverse cancer pathways mediated by the TGF-β superfamily.

We analyzed molecular data on 2,579 tumors from The Cancer Genome Atlas (TCGA) of four gynecological types plus breast. Our aims were to identify shared and unique molecular features, clinically significant subtypes, and potential therapeutic targets. We found 61 somatic copy-number alterations (SCNAs) and 46 significantly mutated genes (SMGs). Eleven SCNAs and 11 SMGs had not been identified in previous TCGA studies of the individual tumor types. We found functionally significant estrogen receptor-regulated long non-coding RNAs (lncRNAs) and gene/lncRNA interaction networks. Pathway analysis identified subtypes with high leukocyte infiltration, raising potential implications for immunotherapy. Using 16 key molecular features, we identified five prognostic subtypes and developed a decision tree that classified patients into the subtypes based on just six features that are assessable in clinical laboratories.

Lipid-rich myelin forms electrically insulating, axon-wrapping multilayers that are essential for neural function, and mature myelin is traditionally considered metabolically inert. Surprisingly, we discovered that mature myelin lipids undergo rapid turnover, and quaking (Qki) is a major regulator of myelin lipid homeostasis. Oligodendrocyte-specific Qki depletion, without affecting oligodendrocyte survival, resulted in rapid demyelination, within 1 week, and gradually neurological deficits in adult mice. Myelin lipids, especially the monounsaturated fatty acids and very-long-chain fatty acids, were dramatically reduced by Qki depletion, whereas the major myelin proteins remained intact, and the demyelinating phenotypes of Qki-depleted mice were alleviated by a high-fat diet. Mechanistically, Qki serves as a coactivator of the PPAR[beta]-RXR[alpha] complex, which controls the transcription of lipid-metabolism genes, particularly those involved in fatty acid desaturation and elongation. Treatment of Qki-depleted mice with PPAR[beta]/RXR agonists significantly alleviated neurological disability and extended survival durations. Furthermore, a subset of lesions from patients with primary progressive multiple sclerosis were characterized by preferential reductions in myelin lipid contents, activities of various lipid metabolism pathways, and expression level of QKI-5 in human oligodendrocytes. Together, our results demonstrate that continuous lipid synthesis is indispensable for mature myelin maintenance and highlight an underappreciated role of lipid metabolism in demyelinating diseases., Introduction Myelin is a specialized multilayer membrane structure that enables rapid saltatory nerve conduction, and it is assembled by oligodendrocytes in the central nervous system (CNS) (1). To sustain the [...]

CD4+ T-cell response is vital for successful clearance of Salmonella Typhimurium infection. Efficient antigen presentation is crucial for effective CD4+ T-cell response. Previous study has reported that Salmonella abrogates antigen presentation capacity of dendritic cells in order to escape host adaptive immune response. In this study, we have elucidated the mechanism of Salmonella-mediated downregulation of the total cellular Major Histocompatibility Complex (MHC) II pool in dendritic cells. Infected dendritic cells show upregulation of E3 ubiquitin ligase, MARCH1 expression and K63-linked ubiquitination of MHC II. Salmonella infection also enhances the internalisation of ubiquitin-tagged MHC II molecules that are subsequently degraded by endosomal proteases. In addition, Salmonella regulates the activation of endosomal proteases by lowering the pH of endosomes. In infected dendritic cells, Salmonella delays NOX2 recruitment to the phagosomes thereby preventing its alkalinisation. NOX2 is a significant part of innate immune response against pathogens as it is responsible for Reactive Oxygen Species (ROS) production. In this study, we have demonstrated how Salmonella evades MHC II-mediated adaptive immune response in dendritic cells through enhanced endosomal proteolysis. To escape host CD4+T response, Salmonella delays NOX2 recruitment, an innate immune response element to the phagosomes. [ABSTRACT FROM AUTHOR]

Lipid-rich myelin forms electrically insulating, axon-wrapping multilayers that are essential for neural function, and mature myelin is traditionally considered metabolically inert. Surprisingly, we discovered that mature myelin lipids undergo rapid turnover, and quaking (Qki) is a major regulator of myelin lipid homeostasis. Oligodendrocyte-specific Qki depletion, without affecting oligodendrocyte survival, resulted in rapid demyelination, within 1 week, and gradually neurological deficits in adult mice. Myelin lipids, especially the monounsaturated fatty acids and very-long-chain fatty acids, were dramatically reduced by Qki depletion, whereas the major myelin proteins remained intact, and the demyelinating phenotypes of Qki-depleted mice were alleviated by a high-fat diet. Mechanistically, Qki serves as a coactivator of the PPARβ-RXRα complex, which controls the transcription of lipid-metabolism genes, particularly those involved in fatty acid desaturation and elongation. Treatment of Qki-depleted mice with PPARβ/RXR agonists significantly alleviated neurological disability and extended survival durations. Furthermore, a subset of lesions from patients with primary progressive multiple sclerosis were characterized by preferential reductions in myelin lipid contents, activities of various lipid metabolism pathways, and expression level of QKI-5 in human oligodendrocytes. Together, our results demonstrate that continuous lipid synthesis is indispensable for mature myelin maintenance and highlight an underappreciated role of lipid metabolism in demyelinating diseases. [ABSTRACT FROM AUTHOR]

Glioma, characterized by neoplastic growth in the brain, is a life-threatening condition that, in most cases, ultimately leads to death. Typical analysis of glioma development involves observation of brain tissue in the form of a histology slide under a microscope. Although brain histology images have much potential for predicting patient outcomes such as overall survival (OS), they are rarely used as the sole predictors due challenges presented by unique characteristics of brain tissue histology. However, utilizing histology in predicting overall survival can be useful for treatment and quality-of-life for patients with early-stage glioma. In this study, we investigate the use of deep learning models on histology slides combined with simple descriptor data (age and glioma subtype) as a predictor of (OS) in patients with low-grade glioma (LGG). Using novel clinical data, we show that models which are more attentive to discriminative features of the image will confer better predictions than generic models (82.7 and 65.3 AUC RFD-Net and Baseline VGG16 model, respectively). Additionally, we show that adding age and subtype information to a histology image-based model may provide greater robustness in the model than using the image alone (3.8 and 4.3 stds for RFD-Net and Baseline VGG16 model with 3-fold CV, respectively), while a model based on image and age but not subtype may confer the best predictive results (83.7 and 82.0 AUC for RFD-Net + age and RFD-Net + age + subtype, respectively). Clinical relevance- This study establishes important criteria for deep learning models which predict OS using histology and basic clinical data from LGG patients.

Background: Imaging features derived from MRI scans can be used for not only breast cancer detection and measuring disease extent, but can also determine gene expression and patient outcomes. The relationships between imaging features, gene/protein expression, and response to therapy hold potential to guide personalized medicine. We aim to characterize the relationship between radiologist-annotated tumor phenotypic features (based on MRI) and the underlying biological processes (based on proteomic profiling) in the tumor., Methods: Multiple-response regression of the image-derived, radiologist-scored features with reverse-phase protein array expression levels generated association coefficients for each combination of image-feature and protein in the RPPA dataset. Significantly-associated proteins for features were analyzed with Ingenuity Pathway Analysis software. Hierarchical clustering of the results of the pathway analysis determined which features were most strongly correlated with pathway activity and cellular functions., Results: Each of the twenty-nine imaging features was found to have a set of significantly correlated molecules, associated biological functions, and pathways., Conclusions: We interrogated the pathway alterations represented by the protein expression associated with each imaging feature. Our study demonstrates the relationships between biological processes (via proteomic measurements) and MRI features within breast tumors., Competing Interests: CONFLICT OF INTEREST The authors have no conflict of interest to declare.