Irradiation to Improve the Response to Immunotherapeutic Agents in Glioblastomas.

PurposeGlioblastoma (GBM) remains an incurable disease despite extensive treatment with surgical resection, irradiation, and temozolomide. In line with many other forms of aggressive cancers, GBM is currently under consideration as a target for immunotherapy. However, GBM tends to be nonimmunogenic and exhibits a microenvironment with few or no effector T cells, a relatively low nonsynonymous somatic mutational load, and a low predicted neoantigen burden. GBM also exploits a multitude of immunosuppressive strategies.Methods and materialsA number of immunotherapeutic approaches have been tested with disappointing results. A rationale exists to combine immunotherapy and radiation therapy, which can induce an immunogenic form of cell death with T-cell activation and tumor infiltration.ResultsVarious immunotherapy agents, including immune checkpoint modulators, transforming growth factor beta receptor inhibitors, and indoleamine-2,3-dioxygenase inhibitors, have been evaluated with irradiation in preclinical GBM models, with promising results, and are being further tested in clinical trials.ConclusionsThis review aims to present the basic rationale behind this emerging complementary therapeutic approach in GBM, appraise the current preclinical and clinical data, and discuss the future challenges in improving the antitumor immune response

A novel multilayer immunoisolating encapsulation system overcoming protrusion of cells

Application of alginate-microencapsulated therapeutic cells is a promising approach for diseases that require a local and constant supply of therapeutic molecules. However most conventional alginate microencapsulation systems are associated with low mechanical stability and protrusion of cells which is associated with higher surface roughness and limits their clinical application. Here we have developed a novel multilayer encapsulation system that prevents cells from protruding from capsules. The system was tested using a therapeutic protein with anti-tumor activity overexpressed in mammalian cells. The cell containing core of the multilayer capsule was formed by flexible alginate, creating a cell sustaining environment. Surrounded by a poly-L-lysine layer the flexible core was enveloped in a high-G alginate matrix that is less flexible and has higher mechanical stability, which does not support cell survival. The cells in the core of the multilayer capsule did not show growth impairment and protein production was normal for periods up to 70 days in vitro. The additional alginate layer also lowered the surface roughness compared to conventional cell containing alginate-PLL capsules. Our system provides a solution for two important, often overlooked phenomena in cell encapsulation: preventing cell protrusion and improving surface roughness

Fisetin protects against cardiac cell death through reduction of ROS production and caspases activity

Myocardial infarction (MI) is a leading cause of death worldwide. Reperfusion is considered as an optimal therapy following cardiac ischemia. However, the promotion of a rapid elevation of O2 levels in ischemic cells produces high amounts of reactive oxygen species (ROS) leading to myocardial tissue injury. This phenomenon is called ischemia reperfusion injury (IRI). We aimed at identifying new and effective compounds to treat MI and minimize IRI. We previously studied heart regeneration following myocardial injury in zebrafish and described each step of the regeneration process, from the day of injury until complete recovery, in terms of transcriptional responses. Here, we mined the data and performed a deep in silico analysis to identify drugs highly likely to induce cardiac regeneration. Fisetin was identified as the top candidate. We validated its effects in an in vitro model of MI/IRI in mammalian cardiac cells. Fisetin enhances viability of rat cardiomyocytes following hypoxia/starvation - reoxygenation. It inhibits apoptosis, decreases ROS generation and caspase activation and protects from DNA damage. Interestingly, fisetin also activates genes involved in cell proliferation. Fisetin is thus a highly promising candidate drug with clinical potential to protect from ischemic damage following MI and to overcome IRI.This work was supported by FNR, the Luxembourg National Research Fund, FNR-CORE INFUSED project. At the NorLux Laboratory and the Proteome and Genome Research Unit of LIH, it was also supported by funding from Luxembourg’s Ministry of Higher Education and Research (MESR).S

Hub genes in a pan-cancer co-expression network show potential for predicting drug responses [version 2; referees: 2 approved]

Background: The topological analysis of networks extracted from different types of “omics” data is a useful strategy for characterizing biologically meaningful properties of the complex systems underlying these networks. In particular, the biological significance of highly connected genes in diverse molecular networks has been previously determined using data from several model organisms and phenotypes. Despite such insights, the predictive potential of candidate hubs in gene co-expression networks in the specific context of cancer-related drug experiments remains to be deeply investigated. The examination of such associations may offer opportunities for the accurate prediction of anticancer drug responses.  Methods: Here, we address this problem by: a) analyzing a co-expression network obtained from thousands of cancer cell lines, b) detecting significant network hubs, and c) assessing their capacity to predict drug sensitivity using data from thousands of drug experiments. We investigated the prediction capability of those genes using a multiple linear regression model, independent datasets, comparisons with other models and our own in vitro experiments. Results: These analyses led to the identification of 47 hub genes, which are implicated in a diverse range of cancer-relevant processes and pathways. Overall, encouraging agreements between predicted and observed drug sensitivities were observed in public datasets, as well as in our in vitro validations for four glioblastoma cell lines and four drugs. To facilitate further research, we share our hub-based drug sensitivity prediction model as an online tool. Conclusions: Our research shows that co-expression network hubs are biologically interesting and exhibit potential for predicting drug responses in vitro. These findings motivate further investigations about the relevance and application of our unbiased discovery approach in pre-clinical, translationally-oriented research

Altered metabolic landscape in IDH‐mutant gliomas affects phospholipid, energy, and oxidative stress pathways

Heterozygous mutations in NADP‐dependent isocitrate dehydrogenases (IDH) define the large majority of diffuse gliomas and are associated with hypermethylation of DNA and chromatin. The metabolic dysregulations imposed by these mutations, whether dependent or not on the oncometabolite D‐2‐hydroxyglutarate (D2HG), are less well understood. Here, we applied mass spectrometry imaging on intracranial patient‐derived xenografts of IDH‐mutant versus IDH wild‐type glioma to profile the distribution of metabolites at high anatomical resolution in situ. This approach was complemented by in vivo tracing of labeled nutrients followed by liquid chromatography–mass spectrometry (LC‐MS) analysis. Selected metabolites were verified on clinical specimen. Our data identify remarkable differences in the phospholipid composition of gliomas harboring the IDH1 mutation. Moreover, we show that these tumors are characterized by reduced glucose turnover and a lower energy potential, correlating with their reduced aggressivity. Despite these differences, our data also show that D2HG overproduction does not result in a global aberration of the central carbon metabolism, indicating strong adaptive mechanisms at hand. Intriguingly, D2HG shows no quantitatively important glucose‐derived label in IDH‐mutant tumors, which suggests that the synthesis of this oncometabolite may rely on alternative carbon sources. Despite a reduction in NADPH, glutathione levels are maintained. We found that genes coding for key enzymes in de novo glutathione synthesis are highly expressed in IDH‐mutant gliomas and the expression of cystathionine‐β‐synthase (CBS) correlates with patient survival in the oligodendroglial subtype. This study provides a detailed and clinically relevant insight into the in vivo metabolism of IDH1‐mutant gliomas and points to novel metabolic vulnerabilities in these tumors

Increased mitochondrial activity in a novel IDH1-R132H mutant human oligodendroglioma xenograft model: in situ detection of 2-HG and α-KG

Background: Point mutations in genes encoding NADP+-dependent isocitrate dehydrogenases (especially IDH1) are common in lower grade diffuse gliomas and secondary glioblastomas and occur early during tumor development. The contribution of these mutations to gliomagenesis is not completely understood and research is hampered by the lack of relevant tumor models. We previously described the development of the patient-derived high-grade oligodendroglioma xenograft model E478 that carries the commonly occurring IDH1-R132H mutation. We here report on the analyses of E478 xenografts at the genetic, histologic and metabolic level. Results: LC-MS and in situ mass spectrometric imaging by LESA-nano ESI-FTICR revealed high levels of the proposed oncometabolite D-2-hydroxyglutarate (D-2HG), the product of enzymatic conversion of α-ketoglutarate (α-KG) by IDH1-R132H, in the tumor but not in surrounding brain parenchyma. α-KG levels and total NADP+-dependent IDH activity were similar in IDH1-mutant and -wildtype xenografts, demonstrating that IDH1-mutated cancer cells maintain α-KG levels. Interestingly, IDH1-mutant tumor cells in vivo present with high densities of mitochondria and increased levels of mitochondrial activity as compared to IDH1-wildtype xenografts. It is not yet clear whether this altered mitochondrial activity is a driver or a consequence of tumorigenesis. Conclusions: The oligodendroglioma model presented here is a valuable model for further functional elucidation of the effects of IDH1 mutations on tumor metabolism and may aid in the rational development of novel therapeutic strategies for the large subgroup of gliomas carrying IDH1 mutations

Glioma Through the Looking GLASS: Molecular Evolution of Diffuse Gliomas and the Glioma Longitudinal AnalySiS Consortium

Adult diffuse gliomas are a diverse group of brain neoplasms that inflict a high emotional toll on patients and their families. The Cancer Genome Atlas (TCGA) and similar projects have provided a comprehensive understanding of the somatic alterations and molecular subtypes of glioma at diagnosis. However, gliomas undergo significant cellular and molecular evolution during disease progression. We review the current knowledge on the genomic and epigenetic abnormalities in primary tumors and after disease recurrence, highlight the gaps in the literature, and elaborate on the need for a new multi-institutional effort to bridge these knowledge gaps and how the Glioma Longitudinal AnalySiS Consortium (GLASS) aims to systemically catalog the longitudinal changes in gliomas. The GLASS initiative will provide essential insights into the evolution of glioma toward a lethal phenotype, with the potential to reveal targetable vulnerabilities, and ultimately, improved outcomes for a patient population in need

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing