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Despite advances in molecularly characterizing glioblastoma (GBM), metabolic alterations driving its aggressive phenotype are only beginning to be recognized. Integrative cross-platform analysis coupling global metabolomic and gene expression profiling on patient-derived glioma identified fatty acid β-oxidation (FAO) as a metabolic node in GBM. We determined that the biologic consequence of enhanced FAO is directly dependent upon tumor microenvironment. FAO serves as a metabolic cue to drive proliferation in a β-HB/GPR109A dependent autocrine manner in nutrient favorable conditions, while providing an efficient, alternate source of ATP only in nutrient unfavorable conditions. Rational combinatorial strategies designed to target these dynamic roles FAO plays in gliomagenesis resulted in necroptosis-mediated metabolic synthetic lethality in GBM. In summary, we identified FAO as a dominant metabolic node in GBM that provides metabolic plasticity, allowing these cells to adapt to their dynamic microenvironment. Combinatorial strategies designed to target these diverse roles FAO plays in gliomagenesis offers therapeutic potential in GBM.

Glioblastoma (GBM) is one of the most aggressive tumors. Numerous studies in the field of immunotherapy have focused their efforts on identifying various pathways linked with tumor-induced immunosuppression. Recent research has demonstrated that metabolic reprogramming in a tumor can contribute towards immune tolerance. To begin to understand the interface between metabolic remodeling and the immune-suppressive state in GBM, we performed a focused, integrative analysis coupling metabolomics with gene-expression profiling in patient-derived GBM (n = 80) and compared them to low-grade astrocytoma (LGA; n = 28). Metabolic intermediates of tryptophan, arginine, prostaglandin, and adenosine emerged as immuno-metabolic nodes in GBM specific to the mesenchymal and classical molecular subtypes of GBM. Integrative analyses emphasized the importance of downstream metabolism of several of these metabolic pathways in GBM. Using CIBERSORT to analyze immune components from the transcriptional profiles of individual tumors, we demonstrated that tryptophan and adenosine metabolism resulted in an accumulation of Tregs and M2 macrophages, respectively, and was recapitulated in mouse models. Furthermore, we extended these findings to preclinical models to determine their potential utility in defining the biologic and/or immunologic consequences of the identified metabolic programs. Collectively, through integrative analysis, we uncovered multifaceted ways by which metabolic reprogramming may contribute towards immune tolerance in GBM, providing the framework for further investigations designed to determine the specific immunologic consequence of these metabolic programs and their therapeutic potential.

There has been considerable scientific effort dedicated to understanding the biologic consequence and therapeutic implications of aberrant tryptophan metabolism in brain tumors and neurodegenerative diseases. A majority of this work has focused on the upstream metabolism of tryptophan; however, this has resulted in limited clinical application. Using global metabolomic profiling of patient-derived brain tumors, we identify the downstream metabolism of tryptophan and accumulation of quinolinate (QA) as a metabolic node in glioblastoma and demonstrate its critical role in promoting immune tolerance. QA acts as a metabolic checkpoint in glioblastoma by inducing NMDA receptor activation and Foxo1/PPARγ signaling in macrophages, resulting in a tumor supportive phenotype. Using a genetically-engineered mouse model designed to inhibit production of QA, we identify kynureninase as a promising therapeutic target to revert the potent immune suppressive microenvironment in glioblastoma. These findings offer an opportunity to revisit the biologic consequence of this pathway as it relates to oncogenesis and neurodegenerative disease and a framework for developing immune modulatory agents to further clinical gains in these otherwise incurable diseases. The upstream metabolism of tryptophan has been described as a metabolic node in glioblastoma. Here the authors show that the downstream metabolism of tryptophan, resulting in the accumulation of quinolinate in glioblastoma, contributes to pro-tumorigenic immune suppressive activation of macrophages.

Whole brain radiotherapy (WBRT) is a mainstay of treatment in patients with both identifiable brain metastases and prophylaxis for microscopic disease. The use of WBRT has decreased somewhat in recent years due to both advances in radiation technology, allowing for a more localized delivery of radiation, and growing concerns regarding the late toxicity profile associated with WBRT. This has prompted the development of several recent and ongoing prospective studies designed to provide Level I evidence to guide optimal treatment approaches for patients with intracranial metastases. In addition to defining the role of WBRT in patients with brain metastases, identifying methods to improve WBRT is an active area of investigation, and can be classified into two general categories: Those designed to decrease the morbidity of WBRT, primarily by reducing late toxicity, and those designed to improve the efficacy of WBRT. Both of these areas of research show diversity and promise, and it seems feasible that in the near future, the efficacy/toxicity ratio may be improved, allowing for a more diverse clinical application of WBRT.

There is a significant body of evidence demonstrating that radiation therapy (XRT) enhances the effect of immune therapy. However, the precise mechanisms by which XRT potentiates the immunotherapy of cancer remain elusive. Here, we report that XRT potentiates the effect of immune therapy via induction of autophagy and resultant trafficking of mannose-6-phopsphate receptor (MPR) to the cell surface. Irradiation of different tumor cells caused substantial up-regulation of MPR on the cell surface in vitro and in vivo. Down-regulation of MPR in tumor cells with shRNA completely abrogated the combined effect of XRT and immunotherapy (CTLA4 antibody) in B16F10-bearing mice without changes in the tumor-specific responses of T cells. Radiation-induced MPR up-regulation was the result of redistribution of the receptor to the cell surface. This effect was caused by autophagy with redirection of MPR to autophagosomes in a clathrin-dependent manner. In autophagosomes, MPR lost its natural ligands, which resulted in subsequent trafficking of empty receptor(s) back to the surface. Together, our data demonstrated a novel mechanism by which XRT can enhance the effect of immunotherapy and the molecular mechanism of this process.

Rapidly growing tumors require efficient means to allow them to adapt to fluctuating microenvironments consisting of hypoxia, nutrient deprivation, and acidosis. The unfolded protein response (UPR) represents a defense mechanism allowing cells to respond to these adverse conditions. The chaperone protein GRP78 serves as a master UPR regulator that is aberrantly expressed in a variety of cancers, including glioma. Therefore, cancer cells may be particularly reliant upon the adaptive mechanisms offered by the UPR and targeting GRP78 may represent a unique therapeutic strategy. Here we report that diffuse expression of GRP78 protein is present in Grade III-IV, but not Grade I-II glioma. To determine the role GRP78 plays in glioblastoma tumorigenesis, we explored the anti-tumor activity of the novel fusion protein EGF-SubA, which combines EGF with the cytotoxin SubA that has been recently shown to selectively cleave GRP78. EGF-SubA demonstrated potent tumor-specific proteolytic activity and cytotoxicity in glioblastoma lines and potentiated the anti-tumor activity of both temozolomide and ionizing radiation. To determine if the tumor microenvironment influences EGF-SubA activity, we maintained cells in acidic conditions that led to both UPR activation and increased EGF-SubA induced cytotoxicity. EGF-SubA was well tolerated in mice and led to a significant tumor growth delay in a glioma xenograft mouse model. The UPR is emerging as an important adaptive pathway contributing to glioma tumorigenesis. Targeting its primary mediator, the chaperone protein GRP78, through specific, proteolytic cleavage with the immunotoxin EGF-SubA represents a novel and promising multi-targeted approach to cancer therapy.

This study is on photocatalytic degradation of pharmaceutical residues of atenolol (ATL) and acetaminophen (ACT) present in secondary effluent under visible light irradiation stimulated by Ag doped ZnO (Ag-ZnO) photocatalyst. Lawsonia inermis leaf extract was used for reduction of Zinc sulphate to ZnO nanoparticles (NPs). Further, ZnO NPs were doped with Ag and characterized by XRD, FT-IR, SEM-EDX, surface area analyzer, UV-Vis, and photoluminescence spectrometry to analyze the structure, morphology, chemical composition, and optical property. FT-IR analysis revealed major functional groups such as OH, C=O, and SEM analysis depicted the polyhedron shape of the NPs with size range of 100 nm. Ag-ZnO NPs were used in the photocatalytic degradation of ATL and ACT, and its removal was evaluated by varying initial contaminant concentration, catalyst dosage, and initial pH. Findings indicate that Ag-ZnO NPs demonstrated relative narrow bandgap and efficient charge separation that resulted in enhanced photocatalytic activity under visible light illumination. The photocatalytic degradation of ATL and ACT fitted well with pseudo-first-order kinetic model. Further, it was found that under optimal conditions of 5 mg/L of contaminants, pH of 8.5, and catalyst dose of 1 g/L, degradation efficiency of 70.2% (ATL) and 90.8% (ACT) was achieved for a reaction time of 120 min. More than 60% reduction in TOC was observed for both contaminants and OH• pathway was found to be the major removal process. Ag-ZnO photocatalyst showed good recycling performance, and these findings indicate that it could be cost effectively employed for removing emerging contaminants under visible light radiation.

Since the discovery of tumour initiating cells (TICs) in solid tumours, studies focussing on their role in cancer initiation and progression have abounded. The biological interrogation of these cells continues to yield volumes of information on their pro-tumourigenic behaviour, but actionable generalised conclusions have been scarce. Further, new information suggesting a dependence of tumour composition and growth on the microenvironment has yet to be studied theoretically. To address this point, we created a hybrid, discrete/continuous computational cellular automaton model of a generalised stem-cell driven tissue with a simple microenvironment. Using the model we explored the phenotypic traits inherent to the tumour initiating cells and the effect of the microenvironment on tissue growth. We identify the regions in phenotype parameter space where TICs are able to cause a disruption in homeostasis, leading to tissue overgrowth and tumour maintenance. As our parameters and model are non-specific, they could apply to any tissue TIC and do not assume specific genetic mutations. Targeting these phenotypic traits could represent a generalizable therapeutic strategy across cancer types. Further, we find that the microenvironmental variable does not strongly affect the outcomes, suggesting a need for direct feedback from the microenvironment onto stem-cell behaviour in future modelling endeavours.

Glioblastoma continues to be an invariably fatal malignancy. The established approach for understanding the biology of these aggressive tumors in an effort to identify novel molecular targets has largely been genotype-based. Unfortunately, clinical gains offered by this level of understanding have been limited, largely based on the complex nature of signaling networks associated with tumorigenesis and the inability to delineate the key “functional” signaling pathways actually driving growth in an individual tumor. Metabolomics is the global quantitative assessment of endogenous metabolites within a biological system, taking into account genetic regulation, altered kinetic activity of enzymes, and changes in metabolic reactions. Thus, compared to genomics and proteomics, metabolomics reflects changes in phenotype and therefore function. In this review, we highlight some of the key advancements that have been made in applying metabolomics to understand the aggressive phenotype of glioblastoma. Collectively, these studies have provided a previously unrecognized window into the underlying biology of these tumors. Current and future efforts are designed to determine how this technology may be applied to improve diagnosis and predict the aggressiveness of glioblastoma, and more importantly, identify novel, therapeutic strategies designed to improve clinical outcomes.