Using the molecular classification of glioblastoma to inform personalized treatment

Integrative analysis of immunogenic PANoptosis and experimental validation of cinobufagin-induced activation to enhance glioma immunotherapy

BACKGROUND

Glioma, particularly glioblastoma (GBM), is a highly aggressive tumor with limited responsiveness to immunotherapy. PANoptosis, a form of programmed cell death merging pyroptosis, apoptosis, and necroptosis, plays an important role in reshaping the tumor microenvironment (TME) and enhancing immunotherapy effectiveness. This study investigates PANoptosis dynamics in glioma and explores the therapeutic potential of its activation, particularly through natural compounds such as cinobufagin.

METHODS

We comprehensively analyzed PANoptosis-related genes (PANoRGs) in multiple glioma cohorts, identifying different PANoptosis patterns and constructing the PANoptosis enrichment score (PANoScore) to evaluate its relationship with patient prognosis and immune activity. Cinobufagin, identified as a PANoptosis activator, was evaluated for its ability to induce PANoptosis and enhance anti-tumor immune responses both in vitro and in vivo GBM models.

RESULTS

Our findings indicate that high PANoScore gliomas showed increased immune cell infiltration, particularly effector T cells, and enhanced sensitivity to immunotherapies. Cinobufagin effectively induced PANoptosis, leading to increased immunogenic cell death, facilitated tumor-associated microglia/macrophages (TAMs) polarization towards an M1-like phenotype while augmenting CD4+/CD8 + T cell infiltration and activation. Importantly, cinobufagin combined with anti-PD-1 therapy exhibited significant synergistic effects and prolonged survival in GBM models.

CONCLUSIONS

These findings highlight the therapeutic potential of PANoptosis-targeting agents, such as cinobufagin, in combination with immunotherapy, offering a promising approach to convert "cold" tumors into "hot" ones and improving glioma treatment outcomes.

Proteomic and cytokine profiling of a CTRP8-RXFP1 glioma mouse model

Glioblastoma (GB) is the most prevalent and aggressive primary brain tumor with fatal outcome due to a lack of effective treatments. We previously identified C1q-tumor necrosis factor-related protein 8 (CTRP8), a new member of the adiponectin family, as a novel agonist of the relaxin family peptide receptor 1 (RXFP1) and showed that the CTRP8-RXFP1 ligand-receptor system facilitates increased invasiveness and chemoresistance in GB cells. In the present study, we have investigated the role of the CTRP8-RXFP1 signaling axis in glioma progression using an orthotopic mouse model xenografted with human U251 glioma cells stably expressing CTRP8 and RXFP1. Our results demonstrate that this in-vivo U251-CTRP8/RXFP1 glioma model promoted the formation of aggressive, highly proliferative glioma that resulted in significantly shorter survival times of xenografted mice. CTRP8/RXFP1 xenografts showed strongly elevated mitotic activity, increased expression of cathepsin B at the migrating front and promoted a pro-inflammatory tumor microenvironment characterized by a strong upregulation of cytokines, among them eotaxin-2 and-3, interleukin (IL)-6, IL-18 and others. Proteomic analysis of xenografted mouse brain identified both human and mouse proteome signatures unique to CTRP8/RXFP1 xenografts compared to U251 xenografts. In conclusion, our results suggest that co-expression of CTRP8 and RXFP1 promotes signaling pathways that generate unique tissue proteomic and inflammatory cytokine signatures which promote glioma aggressiveness. The CTRP-RXFP1 signaling pathway may represent an effective therapeutic target for the treatment of fast-progressing and currently untreatable GB.

BRAT1 - a new therapeutic target for glioblastoma

Glioblastoma (GBM), the most malignant primary brain tumor in adults, has poor prognosis irrespective of therapeutic advances due to its radio-resistance and infiltrative growth into brain tissue. The present study assessed functions and putative druggability of BRCA1-associated ATM activator 1 (BRAT1) as a crucial factor driving key aspects of GBM, including enhanced DNA damage response and tumor migration. By a stable depletion of BRAT1 in GBM and glioma stem-like (GSC) cell lines, we observed a delay in DNA double-strand break repair and increased sensitivity to radiation treatment, corroborated by in vitro and in vivo studies demonstrating impaired tumor growth and invasion. Proteomic and phosphoproteomic analyses further emphasize the role of BRAT1's cell migration and invasion capacity, with a notable proportion of downregulated proteins associated with these processes. In line with the genetic manipulation, we found that treatment with the BRAT1 inhibitor Curcusone D (CurD) significantly reduced GSC migration and invasion in an ex vivo slice culture model, particularly when combined with irradiation, resulting in a synergistic inhibition of tumor growth and infiltration. Our results reveal that BRAT1 contributes to GBM growth and invasion and suggest that therapeutic inhibition of BRAT1 with CurD or similar compounds might constitute a novel approach for anti-GBM directed treatments.

Probing the glioma micro-environment: Analysis using biopsy in combination with ultra-fast cyclic immunolabeling

The interaction between gliomas and the immune system is poorly understood and thus hindering development of effective immunotherapies for glioma patients. The immune response is highly variable during tumor development, and affected by therapies such as surgery, radiation, and chemotherapy. Currently, analysis of these local changes is difficult due to poor accessibility of the tumor and high-morbidity of sampling. In this study, we developed a model for repeat-biopsy in mice to study these local immunological changes over time. Using fine needle biopsy we were able to safely and repeatedly collect cells from intracranial tumors in mice. Ultra-fast cycling technology (FAST) was used for multi-cycle immunofluorescence of retrieved cells, and provided insights in the changing immune response over time. The combination of these techniques can be utilized to study changes in the immune response in glioma or other intracranial diseases over time, and in response to treatment within the same animal.

Radiogenomics as an Integrated Approach to Glioblastoma Precision Medicine

PURPOSE OF REVIEW

Isocitrate dehydrogenase wild-type glioblastoma is the most aggressive primary brain tumour in adults. Its infiltrative nature and heterogeneity confer a dismal prognosis, despite multimodal treatment. Precision medicine is increasingly advocated to improve survival rates in glioblastoma management; however, conventional neuroimaging techniques are insufficient in providing the detail required for accurate diagnosis of this complex condition.

RECENT FINDINGS

Advanced magnetic resonance imaging allows more comprehensive understanding of the tumour microenvironment. Combining diffusion and perfusion magnetic resonance imaging to create a multiparametric scan enhances diagnostic power and can overcome the unreliability of tumour characterisation by standard imaging. Recent progress in deep learning algorithms establishes their remarkable ability in image-recognition tasks. Integrating these with multiparametric scans could transform the diagnosis and monitoring of patients by ensuring that the entire tumour is captured. As a corollary, radiomics has emerged as a powerful approach to offer insights into diagnosis, prognosis, treatment, and tumour response through extraction of information from radiological scans, and transformation of these tumour characteristics into quantitative data. Radiogenomics, which links imaging features with genomic profiles, has exhibited its ability in characterising glioblastoma, and determining therapeutic response, with the potential to revolutionise management of glioblastoma. The integration of deep learning algorithms into radiogenomic models has established an automated, highly reproducible means to predict glioblastoma molecular signatures, further aiding prognosis and targeted therapy. However, challenges including lack of large cohorts, absence of standardised guidelines and the 'black-box' nature of deep learning algorithms, must first be overcome before this workflow can be applied in clinical practice.

Prognostic significance of oligodendrocyte transcription factor 2 expression in glioma patients: A systematic review and meta-analysis

BACKGROUND

Gliomas are the most common primary central nervous system neoplasm. Despite recent advances in the diagnosis and treatment of gliomas, patient prognosis remains dismal. Therefore, it is imperative to identify novel diagnostic biomarkers and therapeutic targets of glioma to effectively improve treatment outcomes.

AIM

To investigate the association between oligodendrocyte transcription factor 2 (Olig2) expression and the outcomes of glioma patients.

METHODS

The PubMed, Embase, Cochrane Library, and China National Knowledge Infrastructure databases were searched for studies (published up to October 2023) that investigated the relationship between Olig2 expression and prognosis of glioma patients. The quality of the studies was assessed using the Newcastle Ottawa Scale. Data analyses were performed using Stata Version 12.0 software.

RESULTS

A total of 1205 glioma patients from six studies were included in the meta-analysis. High Olig2 expression was associated with better outcomes in glioma patients [hazard ratio (HR): 0.81; 95% (confidence interval) CI: 0.51-1.27; P = 0.000]. Furthermore, the results of subgroup meta-analysis showed that high expression of Olig2 was associated with poor overall survival in European patients (HR: 1.34; 95%CI: 0.79-2.27) and better prognosis in Asian patients (HR: 0.43; 95%CI: 0.22-0.84). The sensitivity analysis showed that no single study had a significant effect on pooled HR, and there was also no indication of publication bias according to the Egger's and Begger's P value test or funnel plot test.

CONCLUSION

High Olig2 expression may have a positive impact on the prognosis of glioma patients, and should be investigated further as a prognostic biomarker and therapeutic target for glioma.

Intratumoral Cell Heterogeneity in Patient-Derived Glioblastoma Cell Lines Revealed by Single-Cell RNA-Sequencing

Glioblastoma cell lines derived from different patients are widely used in tumor biology research and drug screening. A key feature of glioblastoma is the high level of inter- and intratumor heterogeneity that accounts for treatment resistance. Our aim was to investigate whether intratumor heterogeneity is maintained in cell models. Single-cell RNA sequencing was used to investigate the cellular composition of a tumor sample and six patient-derived glioblastoma cell lines. Three cell lines preserved the mutational profile of the original tumor, whereas three others differed from their precursors. Copy-number variation analysis showed significantly rearranged genomes in all the cell lines and in the tumor sample. The tumor had the most complex cell composition, including cancer cells and microenvironmental cells. Cell lines with a conserved genome had less diverse cellularity, and during cultivation, a relative increase in the stem-cell-derived progenitors was noticed. Cell lines with genomes different from those of the primary tumors mainly contained neural progenitor cells and microenvironmental cells. The establishment of cell lines without the driver mutations that are intrinsic to the original tumors may be related to the selection of clones or cell populations during cultivation. Thus, patient-derived glioblastoma cell lines differ substantially in their cellular profile, which should be taken into account in translational studies.

Probing the glioma micro-environment: analysis using biopsy in combination with ultra-fast cyclic immunolabeling

The interaction between gliomas and the immune system is poorly understood and thus hindering development of effective immunotherapies for glioma patients. The immune response is highly variable during tumor development, and affected by therapies such as surgery, radiation, and chemotherapy. Currently, analysis of these local changes is difficult due to poor accessibility of the tumor and high-morbidity of sampling. In this study, we developed a model for repeat-biopsy in mice to study these local immunological changes over time. Using fine needle biopsy we were able to safely and repeatedly collect cells from intracranial tumors in mice. Ultra-fast cycling technology (FAST) was used for multi-cycle immunofluorescence of retrieved cells, and provided insights in the changing immune response over time. The combination of these techniques can be utilized to study changes in the immune response in glioma or other intracranial diseases over time, and in response to treatment within the same animal.

Multiplexed single-cell lineage tracing of mitotic kinesin inhibitor resistance in glioblastoma

Glioblastoma (GBM) is a deadly brain tumor, and the kinesin motor KIF11 is an attractive therapeutic target with roles in proliferation and invasion. Resistance to KIF11 inhibitors, which has mainly been studied in animal models, presents significant challenges. We use lineage-tracing barcodes and single-cell RNA sequencing to analyze resistance in patient-derived GBM neurospheres treated with ispinesib, a potent KIF11 inhibitor. Similar to GBM progression in patients, untreated cells lose their neural lineage identity and become mesenchymal, which is associated with poor prognosis. Conversely, cells subjected to long-term ispinesib treatment exhibit a proneural phenotype. We generate patient-derived xenografts and show that ispinesib-resistant cells form less aggressive tumors in vivo, even in the absence of drug. Moreover, treatment of human ex vivo GBM slices with ispinesib demonstrates phenotypic alignment with in vitro responses, underscoring the clinical relevance of our findings. Finally, using retrospective lineage tracing, we identify drugs that are synergistic with ispinesib.

Comprehensive understanding of glioblastoma molecular phenotypes: classification, characteristics, and transition

Among central nervous system-associated malignancies, glioblastoma (GBM) is the most common and has the highest mortality rate. The high heterogeneity of GBM cell types and the complex tumor microenvironment frequently lead to tumor recurrence and sudden relapse in patients treated with temozolomide. In precision medicine, research on GBM treatment is increasingly focusing on molecular subtyping to precisely characterize the cellular and molecular heterogeneity, as well as the refractory nature of GBM toward therapy. Deep understanding of the different molecular expression patterns of GBM subtypes is critical. Researchers have recently proposed tetra fractional or tripartite methods for detecting GBM molecular subtypes. The various molecular subtypes of GBM show significant differences in gene expression patterns and biological behaviors. These subtypes also exhibit high plasticity in their regulatory pathways, oncogene expression, tumor microenvironment alterations, and differential responses to standard therapy. Herein, we summarize the current molecular typing scheme of GBM and the major molecular/genetic characteristics of each subtype. Furthermore, we review the mesenchymal transition mechanisms of GBM under various regulators.

Promoter hypomethylated PDZK1 acts as a tumorigenic gene in glioma by interacting with AKT1

Glioma is the most frequently diagnosed primary brain tumor and typically has a poor prognosis because of malignant proliferation and invasion. It is urgent to elucidate the mechanisms driving glioma tumorigenesis and develop novel treatments to address this deadly disease. Here, we first revealed that PDZK1 is expressed at high levels in gliomas. Promoter hypomethylation may cause high expression of PDZK1 in glioma. Knockdown of PDZK1 inhibits glioma cell proliferation and invasion in vitro. Mechanistically, further investigations revealed that the loss of PDZK1 expression by siRNA inhibited the activation of the AKT/mTOR signaling pathway, leading to cell cycle arrest and apoptosis. Clinically, high expression of PDZK1 predicts a poorer prognosis for glioma patients than low expression of PDZK1. Overall, our study revealed that PDZK1 acts as a novel oncogene in glioma by binding to AKT1 and maintaining the activation of the AKT/mTOR signaling pathway. Thus, PDZK1 may be a potential therapeutic target for glioma.

Changes in the Concentrations of Proangiogenic Cytokines in Human Brain Glioma and Acute Lymphoblastic Leukemia

Acute lymphoblastic leukemia (ALL) and glioma are some of the most common malignancies, with ALL most often affecting children and glioma affecting adult men. Proangiogenic cytokines and growth factors play an important role in the development of both of these tumors. Glioma is characterized by an extremely extensive network of blood vessels, which continues to expand mainly in the process of neoangiogenesis, the direct inducers of which are cytokines from the family of vascular endothelial growth factors, i.e., vascular endothelial growth factor (VEGF-A) and its receptor vascular endothelial growth factor receptor 2 (VEGF-R2), as well as a cytokine from the fibroblast growth factor family, fibroblast growth factor 2 (FGF-2 or bFGF). Growth factors are known primarily for their involvement in the progression and development of solid tumors, but there is evidence that local bone marrow angiogenesis and increased blood vessel density are also present in hematological malignancies, including leukemias. The aim of this study was to examine changes in the concentrations of VEGF-A, VEGF-R2, and FGF-2 (with a molecular weight of 17 kDa) in a group of patients divided into specific grades of malignancy (glioma) and a control group; changes of VEGF-A and FGF-2 concentrations in childhood acute lymphoblastic leukemia and a control group; and to determine correlations between the individual proteins as well as the influence of the patient's age, diet, and other conditions that may place the patient in the risk group. During the statistical analysis, significant differences in concentrations were found between the patient and control groups in samples from people with diagnosed glioma and from children with acute lymphoblastic leukemia, but in general, there are no significant differences in the concentrations of VEGF-A, VEGF-R2, and FGF-2 between different grades of glioma malignancy. Among individuals treated for glioma, there was no significant impact from the patient's gender and age, consumption of food from plastic packaging, frequency of eating vegetables and fruit, smoking of tobacco products, the intensity of physical exercise, or the general condition of the body (Karnofsky score) on the concentrations of the determined cytokines and receptor. The listed factors do not bring about an actual increase in the risk of developing brain glioma.

Characterization of prevalent tyrosine kinase inhibitors and their challenges in glioblastoma treatment

Glioblastoma multiforme (GBM) is a highly aggressive malignant primary tumor in the central nervous system. Despite extensive efforts in radiotherapy, chemotherapy, and neurosurgery, there remains an inadequate level of improvement in treatment outcomes. The development of large-scale genomic and proteomic analysis suggests that GBMs are characterized by transcriptional heterogeneity, which is responsible for therapy resistance. Hence, knowledge about the genetic and epigenetic heterogeneity of GBM is crucial for developing effective treatments for this aggressive form of brain cancer. Tyrosine kinases (TKs) can act as signal transducers, regulate important cellular processes like differentiation, proliferation, apoptosis and metabolism. Therefore, TK inhibitors (TKIs) have been developed to specifically target these kinases. TKIs are categorized into allosteric and non-allosteric inhibitors. Irreversible inhibitors form covalent bonds, which can lead to longer-lasting effects. However, this can also increase the risk of off-target effects and toxicity. The development of TKIs as therapeutics through computer-aided drug design (CADD) and bioinformatic techniques enhance the potential to improve patients' survival rates. Therefore, the continued exploration of TKIs as drug targets is expected to lead to even more effective and specific therapeutics in the future.

Intranasal delivery of sunitinib: A new therapeutic approach for targeting angiogenesis of glioblastoma

Glioblastoma multiforme (GBM) is one of the most vascular among solid tumors, and despite the use of multimodal therapies, the survival of these patients is poor. In order to target angiogenesis in GBM as a promising strategy, an antiangiogenic drug is required. This study was designed to evaluate the effects of sunitinib, a multityrosine kinase inhibitor with tumor proliferation and angiogenesis inhibitory properties, on GBM-bearing rats. Given the ineffective drug delivery to the brain due to the presence of the blood-brain barrier (BBB), intra-nasal (IN) drug delivery has recently been considered as a non-invasive method to bypass BBB. Therefore, in the current study, IN was used as an ideal method for the delivery of sunitinib to the brain, and the effects of this method were also compared to the OR administration of the sunitinib. GBM was induced in the brain of male Wistar rats, and they were randomly divided into 4 groups; IN-STB (sunitinib intranasal delivery), IN-sham (placebo intranasal delivery), OR-STB (sunitinib oral delivery) and OR-sham (placebo oral delivery). After the end of the treatment period, an MRI of animals' brains showed a reduction in tumor growth in the treatment groups. Immunohistochemistry revealed that sunitinib inhibits angiogenesis in GBM in both OR and IN delivery methods. Analysis of liver tissue and enzymes showed that IN delivery of sunitinib had less hepatotoxicity than the OR method. Overall, it was found that IN sunitinib delivery could be used as a potential non-hepatotoxic alternative for the treatment of GBM.

Artificial intelligence in neuroimaging of brain tumors: reality or still promise?

PURPOSE OF REVIEW

To provide an updated overview of artificial intelligence (AI) applications in neuro-oncologic imaging and discuss current barriers to wider clinical adoption.

RECENT FINDINGS

A wide variety of AI applications in neuro-oncologic imaging have been developed and researched, spanning tasks from pretreatment brain tumor classification and segmentation, preoperative planning, radiogenomics, prognostication and survival prediction, posttreatment surveillance, and differentiating between pseudoprogression and true disease progression. While earlier studies were largely based on data from a single institution, more recent studies have demonstrated that the performance of these algorithms are also effective on external data from other institutions. Nevertheless, most of these algorithms have yet to see widespread clinical adoption, given the lack of prospective studies demonstrating their efficacy and the logistical difficulties involved in clinical implementation.

SUMMARY

While there has been significant progress in AI and neuro-oncologic imaging, clinical utility remains to be demonstrated. The next wave of progress in this area will be driven by prospective studies measuring outcomes relevant to clinical practice and go beyond retrospective studies which primarily aim to demonstrate high performance.

Development of a "Geo-Tagged" tumor sample registry: intra-operative linkage of sample location to imaging

PURPOSE

There is a growing body of literature documenting glioma heterogeneity in terms of radiographic, histologic, molecular, and genetic characteristics. Incomplete spatial specification of intraoperative tumor samples may contribute to variability in the results of pathological and biological investigations. We have developed a system, termed geo-tagging, for routine intraoperative linkage of each tumor sample to its location via neuronavigation.

METHODS

This is a single-institution, IRB approved, prospective database of undergoing clinically indicated surgery. We evaluated relevant factors affecting data collection by this registry, including tumor and surgical factors (e.g. tumor volume, location, grade and surgeon).

RESULTS

Over a 2-year period, 487 patients underwent craniotomy for an intra-axial tumor. Of those, 214 underwent surgery for a newly diagnosed or recurrent glioma. There was significant variation in the average number of samples collected per registered case, with a range of samples from 2.53 to 4.75 per tumor type. Histology and grade impacted on sampling with a range of 2.0 samples per tumor in Grade four, IDH-WT gliomas to 4.5 samples in grade four, IDH-mutant gliomas. The range of cases with sampling per surgeon was 6 to 99 with a mean of 47.6 cases and there was a statistically significant differences between surgeons. Tumor grade did not have a statistically significant impact on number of samples per case. No significant correlation was found between the number of samples collected and enhancing tumor volume, EOR, or volume of tumor resected.

CONCLUSION

We are using the results of this analysis to develop a prospective sample collection protocol.

The Role of Non-Coding RNAs in Epigenetic Dysregulation in Glioblastoma Development

Glioblastoma (GBM) is a primary brain tumor arising from glial cells. The tumor is highly aggressive, the reason for which it has become the deadliest brain tumor type with the poorest prognosis. Like other cancers, it compromises molecular alteration on genetic and epigenetic levels. Epigenetics refers to changes in gene expression or cellular phenotype without the occurrence of any genetic mutations or DNA sequence alterations in the driver tumor-related genes. These epigenetic changes are reversible, making them convenient targets in cancer therapy. Therefore, we aim to review critical epigenetic dysregulation processes in glioblastoma. We will highlight the significant affected tumor-related pathways and their outcomes, such as regulation of cell cycle progression, cell growth, apoptosis, angiogenesis, cell invasiveness, immune evasion, or acquirement of drug resistance. Examples of molecular changes induced by epigenetic modifications, such as DNA epigenetic alterations, histone post-translational modifications (PTMs), and non-coding RNA (ncRNA) regulation, are highlighted. As understanding the role of epigenetic regulators and underlying molecular mechanisms in the overall pro-tumorigenic landscape of glioblastoma is essential, this literature study will provide valuable insights for establishing the prognostic or diagnostic value of various non-coding transcripts, including miRNAs.

Redox Homeostasis and Beyond: The Role of Wild-Type Isocitrate Dehydrogenases for the Pathogenesis of Glioblastoma

Significance: Glioblastoma is an aggressive and devastating brain tumor characterized by a dismal prognosis and resistance to therapeutic intervention. To support catabolic processes critical for unabated cellular growth and defend against harmful reactive oxygen species, glioblastoma tumors upregulate the expression of wild-type isocitrate dehydrogenases (IDHs). IDH enzymes catalyze the oxidative decarboxylation of isocitrate to α-ketoglutarate (α-KG), NAD(P)H, and CO2. On molecular levels, IDHs epigenetically control gene expression through effects on α-KG-dependent dioxygenases, maintain redox balance, and promote anaplerosis by providing cells with NADPH and precursor substrates for macromolecular synthesis. Recent Advances: While gain-of-function mutations in IDH1 and IDH2 represent one of the most comprehensively studied mechanisms of IDH pathogenic effects, recent studies identified wild-type IDHs as critical regulators of normal organ physiology and, when transcriptionally induced or down regulated, as contributing to glioblastoma progression. Critical Issues: Here, we will discuss molecular mechanisms of how wild-type IDHs control glioma pathogenesis, including the regulation of oxidative stress and de novo lipid biosynthesis, and provide an overview of current and future research directives that aim to fully characterize wild-type IDH-driven metabolic reprogramming and its contribution to the pathogenesis of glioblastoma. Future Directions: Future studies are required to further dissect mechanisms of metabolic and epigenomic reprogramming in tumors and the tumor microenvironment, and to develop pharmacological approaches to inhibit wild-type IDH function. Antioxid. Redox Signal. 39, 923-941.

Advancements in dendritic cell vaccination: enhancing efficacy and optimizing combinatorial strategies for the treatment of glioblastoma

Glioblastomas (GBM) are highly invasive, malignant primary brain tumors. The overall prognosis is poor, and management of GBMs remains a formidable challenge, necessitating novel therapeutic strategies such as dendritic cell vaccinations (DCVs). While many early clinical trials demonstrate an induction of an antitumoral immune response, outcomes are mixed and dependent on numerous factors that vary between trials. Optimization of DCVs is essential; the selection of GBM-specific antigens and the utilization of 18F-fludeoxyglucose Positron Emission Tomography (FDG-PET) may add significant value and ultimately improve outcomes for patients undergoing treatment for glioblastoma. This review provides an overview of the mechanism of DCV, assesses previous clinical trials, and discusses future strategies for the integration of DCV into glioblastoma treatment protocols. To conclude, the review discusses challenges associated with the use of DCVs and highlights the potential of integrating DCV with standard therapies.

Systematic Literature Review of Machine Learning Algorithms Using Pretherapy Radiologic Imaging for Glioma Molecular Subtype Prediction

BACKGROUND

The molecular profile of gliomas is a prognostic indicator for survival, driving clinical decision-making for treatment. Pathology-based molecular diagnosis is challenging because of the invasiveness of the procedure, exclusion from neoadjuvant therapy options, and the heterogeneous nature of the tumor.

PURPOSE

We performed a systematic review of algorithms that predict molecular subtypes of gliomas from MR Imaging.

DATA SOURCES

Data sources were Ovid Embase, Ovid MEDLINE, Cochrane Central Register of Controlled Trials, Web of Science.

STUDY SELECTION

Per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 12,318 abstracts were screened and 1323 underwent full-text review, with 85 articles meeting the inclusion criteria.

DATA ANALYSIS

We compared prediction results from different machine learning approaches for predicting molecular subtypes of gliomas. Bias analysis was conducted for each study, following the Prediction model Risk Of Bias Assessment Tool (PROBAST) guidelines.

DATA SYNTHESIS

Isocitrate dehydrogenase mutation status was reported with an area under the curve and accuracy of 0.88 and 85% in internal validation and 0.86 and 87% in limited external validation data sets, respectively. For the prediction of O6-methylguanine-DNA methyltransferase promoter methylation, the area under the curve and accuracy in internal validation data sets were 0.79 and 77%, and in limited external validation, 0.89 and 83%, respectively. PROBAST scoring demonstrated high bias in all articles.

LIMITATIONS

The low number of external validation and studies with incomplete data resulted in unequal data analysis. Comparing the best prediction pipelines of each study may introduce bias.

CONCLUSIONS

While the high area under the curve and accuracy for the prediction of molecular subtypes of gliomas are reported in internal and external validation data sets, limited use of external validation and the increased risk of bias in all articles may present obstacles for clinical translation of these techniques.

Interleukin-6-controlled, mesenchymal stem cell-based sodium/iodide symporter gene therapy improves survival of glioblastoma-bearing mice

New treatment strategies are urgently needed for glioblastoma (GBM)-a tumor resistant to standard-of-care treatment with a high risk of recurrence and extremely poor prognosis. Based on their intrinsic tumor tropism, adoptively applied mesenchymal stem cells (MSCs) can be harnessed to deliver the theranostic sodium/iodide symporter (NIS) deep into the tumor microenvironment. Interleukin-6 (IL-6) is a multifunctional, highly expressed cytokine in the GBM microenvironment including recruited MSCs. MSCs engineered to drive NIS expression in response to IL-6 promoter activation offer the possibility of a new tumor-targeted gene therapy approach of GBM. Therefore, MSCs were stably transfected with an NIS-expressing plasmid controlled by the human IL-6 promoter (IL-6-NIS-MSCs) and systemically applied in mice carrying orthotopic GBM. Enhanced radiotracer uptake by 18F-Tetrafluoroborate-PET/magnetic resonance imaging (MRI) was detected in tumors after IL-6-NIS-MSC application as compared with mice that received wild-type MSCs. Ex vivo analysis of tumors and non-target organs showed tumor-specific NIS protein expression. Subsequent 131I therapy after IL-6-NIS-MSC application resulted in significantly delayed tumor growth assessed by MRI and improved median survival up to 60% of GBM-bearing mice as compared with controls. In conclusion, the application of MSC-mediated NIS gene therapy focusing on IL-6 biology-induced NIS transgene expression represents a promising approach for GBM treatment.

Multiplexed single-cell lineage tracing of mitotic kinesin inhibitor resistance in glioblastoma

Glioblastoma (GBM) is a deadly brain tumor, and the kinesin motor KIF11 is an attractive therapeutic target because of its dual roles in proliferation and invasion. The clinical utility of KIF11 inhibitors has been limited by drug resistance, which has mainly been studied in animal models. We used multiplexed lineage tracing barcodes and scRNA-seq to analyze drug resistance time courses for patient-derived GBM neurospheres treated with ispinesib, a potent KIF11 inhibitor. Similar to GBM progression in patients, untreated cells lost their neural lineage identity and transitioned to a mesenchymal phenotype, which is associated with poor prognosis. In contrast, cells subjected to long-term ispinesib treatment exhibited a proneural phenotype. We generated patient-derived xenografts to show that ispinesib-resistant cells form less aggressive tumors in vivo, even in the absence of drug. Finally, we used lineage barcodes to nominate drug combination targets by retrospective analysis of ispinesib-resistant clones in the drug-naïve setting and identified drugs that are synergistic with ispinesib.

Intradural Intramedullary Spinal Cord Glioblastoma: A Case Report

Primary spinal cord glioblastoma multiforme (GBM) remains uncommon and typically affects males and patients during their fifth decade of life. Our case demonstrates a 77-year-old woman who initially presented with right arm paresthesia and limited range of motion and was subsequently diagnosed with primary spinal cord GBM. Our case illustrates an atypical and nonspecific neurological presentation highlighting that spinal cord GBM can have a more indolent course, unlike what current literature suggests. It also emphasizes the importance of considering a multimodal approach when managing atypical neurological symptoms and considering an early intervention, including magnetic resonance imaging, to rule out occult neoplasm in an appropriate clinical setting, thus preventing delay in the diagnosis. This case further emphasizes the role of molecular biomarkers of tumors, including isocitrate dehydrogenase mutation as well as methylguanine-DNA methyltransferase promoter methylation status, that can independently guide and affect the treatment outcomes in this patient population.

The role of chromatin remodeler SMARCA4/BRG1 in brain cancers: a potential therapeutic target

The chromatin remodeler SMARCA4/BRG1 is a key epigenetic regulator with diverse roles in coordinating the molecular programs that underlie brain tumour development. BRG1 function in brain cancer is largely specific to the tumour type and varies further between tumour subtypes, highlighting its complexity. Altered SMARCA4 expression has been linked to medulloblastoma, low-grade gliomas such as oligodendroglioma, high-grade gliomas such as glioblastoma and atypical/teratoid rhabdoid tumours. SMARCA4 mutations in brain cancer predominantly occur in the crucial catalytic ATPase domain, which is associated with tumour suppressor activity. However, SMARCA4 is opposingly seen to promote tumourigenesis in the absence of mutation and through overexpression in other brain tumours. This review explores the multifaceted interaction between SMARCA4 and various brain cancer types, highlighting its roles in tumour pathogenesis, the pathways it regulates, and the advances that have been made in understanding the functional relevance of mutations. We discuss developments made in targeting SMARCA4 and the potential to translate these to adjuvant therapies able to enhance current methods of brain cancer treatment.

Interactions of Nanoscale Self-Assembled Peptide-Based Assemblies with Glioblastoma Cell Models and Spheroids

Peptide nanoassemblies have garnered remarkable importance in the development of novel nanoscale biomaterials for drug delivery into tumor cells. Taking advantage of receptor mediated recognition of two known peptides, angiopep-2 (TFFYGGSRGKRNNFKTEEY) and A-COOP-K (ACGLSGLC10 VAK) that bind to the over-expressed receptors low density lipoprotein (LRP-1) and fatty acid binding protein (FABP3) respectively, we have developed new peptide conjugates by combining the anti-inflammatory, antitumor compound azelaic acid with angiopep-2, which efficiently self-assembled into nanofibers. Those nanofibers were then functionalized with the A-COOP-K sequence and formed supramolecular hierarchical structures that were found to entrap the chemotherapeutic drug doxorubicin efficaciously. Furthermore, the nanoassemblies were found to release the drug in a dose-dependent manner and showed a stepwise increase over a period of 2 weeks under acidic conditions. Two cell lines (U-87-MG and U-138-MG) were utilized as models for glioblastoma cells grown in the presence of serum and under serum-free conditions to mimic the growth conditions of natural tumors. The drug entrapped assemblies were found to inhibit the cell proliferation of both U-87 and U-138MG glioblastoma cells. Three dimensional spheroids of different sizes were grown to mimic the tumors and evaluate the efficacy of drug release and internalization. Our results indicated that the nanoassemblies were found to have higher internalization of DOX and were well-spread throughout the spheroids grown, particularly under serum-free conditions. The nanoassemblies also displayed blood-brain barrier penetration when tested with a multicellular in vitro model. Such self-assembled nanostructures with targeting ability may provide a suitable platform for the development of new peptide-based biomaterials that can provide more insights about the mechanistic approach for drug delivery for not only 2D cell cultures but also 3D tumoroids that mimic the tumor microenvironments.

Oligodendrocyte Transcription Factor 2 as a Potential Prognostic Biomarker of Glioblastoma: Kaplan-Meier Analysis and the Development of a Binary Predictive Model Based on Visually Accessible Rembrandt Image and Magnetic Resonance Imaging Radiomic Features

OBJECTIVE

Oligodendrocyte transcription factor 2 (OLIG2) is universally expressed in human glioblastoma (GB). Our study explores whether OLIG2 expression impacts GB patients' overall survival and establishes a machine learning model for OLIG2 level prediction in patients with GB based on clinical, semantic, and magnetic resonance imaging radiomic features.

METHODS

Kaplan-Meier analysis was used to determine the optimal cutoff value of the OLIG2 in 168 GB patients. Three hundred thirteen patients enrolled in the OLIG2 prediction model were randomly divided into training and testing sets in a ratio of 7:3. The radiomic, semantic, and clinical features were collected for each patient. Recursive feature elimination (RFE) was used for feature selection. The random forest (RF) model was built and fine-tuned, and the area under the curve was calculated to evaluate the performance. Finally, a new testing set excluding IDH-mutant patients was built and tested in a predictive model using the fifth edition of the central nervous system tumor classification criteria.

RESULTS

One hundred nineteen patients were included in the survival analysis. Oligodendrocyte transcription factor 2 was positively associated with GB survival, with an optimal cutoff of 10% (P = 0.00093). One hundred thirty-four patients were eligible for the OLIG2 prediction model. An RFE-RF model based on 2 semantic and 21 radiomic signatures achieved areas under the curve of 0.854 in the training set, 0.819 in the testing set, and 0.825 in the new testing set.

CONCLUSIONS

Glioblastoma patients with ≤10% OLIG2 expression tended to have worse overall survival. An RFE-RF model integrating 23 features can predict the OLIG2 level of GB patients preoperatively, irrespective of the central nervous system classification criteria, further guiding individualized treatment.

The Pathological Activation of Microglia Is Modulated by Sexually Dimorphic Pathways

Microglia are the primary immunocompetent cells of the central nervous system (CNS). Their ability to survey, assess and respond to perturbations in their local environment is critical in their role of maintaining CNS homeostasis in health and disease. Microglia also have the capability of functioning in a heterogeneous manner depending on the nature of their local cues, as they can become activated on a spectrum from pro-inflammatory neurotoxic responses to anti-inflammatory protective responses. This review seeks to define the developmental and environmental cues that support microglial polarization towards these phenotypes, as well as discuss sexually dimorphic factors that can influence this process. Further, we describe a variety of CNS disorders including autoimmune disease, infection, and cancer that demonstrate disparities in disease severity or diagnosis rates between males and females, and posit that microglial sexual dimorphism underlies these differences. Understanding the mechanism behind differential CNS disease outcomes between men and women is crucial in the development of more effective targeted therapies.

Identification and validation of a novel prognostic signature based on mitochondria and oxidative stress related genes for glioblastoma

BACKGROUND

Mitochondria represent a major source of reactive oxygen species (ROS) in cells, and the direct increase in ROS content is the primary cause of oxidative stress, which plays an important role in tumor proliferation, invasion, angiogenesis, and treatment. However, the relationship between mitochondrial oxidative stress-related genes and glioblastoma (GBM) remains unclear. This study aimed to investigate the value of mitochondria and oxidative stress-related genes in the prognosis and therapeutic targets of GBM.

METHODS

We retrieved mitochondria and oxidative stress-related genes from several public databases. The LASSO regression and Cox analyses were utilized to build a risk model and the ROC curve was used to assess its performance. Then, we analyzed the correlation between the model and immunity and mutation. Furthermore, CCK8 and EdU assays were utilized to verify the proliferative capacity of GBM cells and flow cytometry was used to analyze apoptosis rates. Finally, the JC-1 assay and ATP levels were utilized to detect mitochondrial function, and the intracellular ROS levels were determined using MitoSOX and BODIPY 581/591 C11.

RESULTS

5 mitochondrial oxidative stress-related genes (CTSL, TXNRD2, NUDT1, STOX1, CYP2E1) were screened by differential expression analysis and Cox analysis and incorporated in a risk model which yielded a strong prediction accuracy (AUC value = 0.967). Furthermore, this model was strongly related to immune cell infiltration and mutation status and could identify potential targeted therapeutic drugs for GBM. Finally, we selected NUDT1 for further validation in vitro. The results showed that NUDT1 was elevated in GBM, and knockdown of NUDT1 inhibited the proliferation and induced apoptosis of GBM cells, while knockdown of NUDT1 damaged mitochondrial homeostasis and induced oxidative stress in GBM cells.

CONCLUSION

Our study was the first to propose a prognostic model of mitochondria and oxidative stress-related genes, which provided potential therapeutic strategies for GBM patients.

Lessons learned from evolving frameworks in adult glioblastoma

Glioblastoma (GBM) is the most common and aggressive malignant adult brain tumor. Significant effort has been directed to achieve a molecular subtyping of GBM to impact treatment. The discovery of new unique molecular alterations has resulted in a more effective classification of tumors and has opened the door to subtype-specific therapeutic targets. Morphologically identical GBM may have different genetic, epigenetic, and transcriptomic alterations and therefore different progression trajectories and response to treatments. With a transition to molecularly guided diagnosis, there is now a potential to personalize and successfully manage this tumor type to improve outcomes. The steps to achieve subtype-specific molecular signatures can be extrapolated to other neuroproliferative as well as neurodegenerative disorders.

Development of a novel angiogenesis-related lncRNA signature to predict the prognosis and immunotherapy of glioblastoma multiforme

Background

Long noncoding RNA (lncRNA) can regulate tumorigenesis, angiogenesis, proliferation, and other tumor biological behaviors, and is closely related to the growth and progression of glioma. The purpose of this research was to investigate the role of angiogenesis-related lncRNA in the prognosis and immunotherapy of glioblastoma multiforme (GBM).

Methods

Differential analysis was carried out to acquire angiogenesis-related differentially expressed lncRNAs (AR-DElncRNAs). The AR-DElncRNAs were then subjected to univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses to construct a prognostic model. Based on the median risk score, patients were classified into high-risk and low-risk groups. Kaplan-Meier survival analysis was conducted to estimate the prognostic value of the prognostic model. In addition, a nomogram was built to predict individual survival probabilities by combining clinicopathological characteristics and a prognostic model. Furthermore, immune infiltration, immunotherapy, and drug sensitivity analyses were administered to investigate the differences between the high- and low-risk groups.

Results

We identified 3 lncRNAs (DGCR5, PRKAG2-AS1, and ACAP2-IT1) that were significantly associated with the survival of GBM patients from the 255 AR-DElncRNAs based on univariate Cox and LASSO analyses. Then, a prognostic model was structured according to these 3 lncRNAs, from which we found that high-risk GBM patients had a worse prognosis than that of low-risk patients. Moreover, the risk score was determined to be an independent prognostic factor [hazard ratio (HR) =1.444; 95% confidence interval (CI): 1.014-2.057; P<0.05]. The immune microenvironment analysis revealed that the immune score, stromal score, and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) score were significantly higher in the high-risk group than in the low-risk group. Neutrophils, macrophages, immature dendritic cells (iDCs), natural killer (NK) CD56dim cells, activated DCs (aDCs), and uncharacterized cells were different in the high- and low-risk groups. In addition, the high-risk group had a stronger sensitivity to immunotherapy. Furthermore, the sensitivity of 28 potential chemotherapeutic drugs differed significantly between the high- and low-risk groups.

Conclusions

A novel angiogenesis-related lncRNA signature could be used to predict the prognosis and treatment of GBM.

Imaging phenotypes from MRI for the prediction of glioma immune subtypes from RNA sequencing: A multicenter study

Tumor subtyping based on its immune landscape may guide precision immunotherapy. The aims of this study were to identify immune subtypes of adult diffuse gliomas with RNA sequencing data, and to noninvasively predict this subtype using a biologically interpretable radiomic signature from MRI. A subtype discovery dataset (n = 210) from a public database and two radiogenomic datasets (n = 130 and 55, respectively) from two local hospitals were included. Brain tumor microenvironment-specific signatures were constructed from RNA sequencing to identify the immune types. A radiomic signature was built from MRI to predict the identified immune subtypes. The pathways underlying the radiomic signature were identified to annotate their biological meanings. The reproducibility of the findings was verified externally in multicenter datasets. Three distinctive immune subtypes were identified, including an inflamed subtype marked by elevated hypoxia-induced immunosuppression, a "cold" subtype that exhibited scarce immune infiltration with downregulated antigen presentation, and an intermediate subtype that showed medium immune infiltration. A 10-feature radiomic signature was developed to predict immune subtypes, achieving an AUC of 0.924 in the validation dataset. The radiomic features correlated with biological functions underpinning immune suppression, which substantiated the hypothesis that molecular changes can be reflected by radiomic features. The immune subtypes, predictive radiomic signature, and radiomics-correlated biological pathways were validated externally. Our data suggest that adult-type diffuse gliomas harbor three distinctive immune subtypes that can be predicted by MRI radiomic features with clear biological significance. The immune subtypes, radiomic signature, and radiogenomic links can be replicated externally.

Hypoxia-induced ROS aggravate tumor progression through HIF-1α-SERPINE1 signaling in glioblastoma

Hypoxia, as an important hallmark of the tumor microenvironment, is a major cause of oxidative stress and plays a central role in various malignant tumors, including glioblastoma. Elevated reactive oxygen species (ROS) in a hypoxic microenvironment promote glioblastoma progression; however, the underlying mechanism has not been clarified. Herein, we found that hypoxia promoted ROS production, and the proliferation, migration, and invasion of glioblastoma cells, while this promotion was restrained by ROS scavengers N-acetyl-L-cysteine (NAC) and diphenyleneiodonium chloride (DPI). Hypoxia-induced ROS activated hypoxia-inducible factor-1α (HIF-1α) signaling, which enhanced cell migration and invasion by epithelial-mesenchymal transition (EMT). Furthermore, the induction of serine protease inhibitor family E member 1 (SERPINE1) was ROS-dependent under hypoxia, and HIF-1α mediated SERPINE1 increase induced by ROS via binding to the SERPINE1 promoter region, thereby facilitating glioblastoma migration and invasion. Taken together, our data revealed that hypoxia-induced ROS reinforce the hypoxic adaptation of glioblastoma by driving the HIF-1α-SERPINE1 signaling pathway, and that targeting ROS may be a promising therapeutic strategy for glioblastoma.

OLIG2 expression level could be used as an independent prognostic factor for patients with cerebellar Glioblastoma (cGBM)

OBJECTIVES

The incidence of cerebellar Glioblastoma Multiforme (cGBM) is rare. Database like TCGA have not distinguish cGBM from GBM, our knowledge on cGBM gene expression characteristics is limited. The expression status of Oligodendrocyte Lineage Transcription factor 2 (OLIG2) and its clinical significance in cGBM is still unclear.

METHODS

The clinical data and tissue specimens of 73 cGBM patients were retrospectively studied. The association between OLIG2 expression level and the demographic characteristics of cGBM patients was identified by the Chi-Square test. The survival curves were drawn by Kaplan-Meier analysis. The independent prognostic factors was calculated according to Cox regression analysis.

RESULTS

The OLIG2 high expression was observed in about 57.5% (42/73) of the cGBM patients. Patients with high OLIG2 expression levels had a higher alive ratio at the end of follow-up (alive ratio: 70.6% vs. 29.4%, p = 0.04). The median survival time was 21 months and 13 months for high and low expression of OLIG2 (p < 0 .05). Univariate analysis and Multivariate analysis indicated that EOR (HR = 3.89, 95% CI 1.23‒12.26, p = 0.02), low OLIG2 expression (HR = 5.26, 95% CI 1.13‒24.59, p = 0.04), and without adjuvant therapy (HR = 4.95, 95% CI 1.22‒20.00, p = 0.03) were independent risk factors for the OS of cGBM patients.

CONCLUSION

High expression level of OLIG2 could be used as an independent favorable prognosis indicator in cGBM patients and be recognized as a characteristic biomarker of cGBM.

Machine learning can aid in prediction of IDH mutation from H&E-stained histology slides in infiltrating gliomas

While Machine Learning (ML) models have been increasingly applied to a range of histopathology tasks, there has been little emphasis on characterizing these models and contrasting them with human experts. We present a detailed empirical analysis comparing expert neuropathologists and ML models at predicting IDH mutation status in H&E-stained histology slides of infiltrating gliomas, both independently and synergistically. We find that errors made by neuropathologists and ML models trained using the TCGA dataset are distinct, representing modest agreement between predictions (human-vs.-human κ = 0.656; human-vs.-ML model κ = 0.598). While no ML model surpassed human performance on an independent institutional test dataset (human AUC = 0.901, max ML AUC = 0.881), a hybrid model aggregating human and ML predictions demonstrates predictive performance comparable to the consensus of two expert neuropathologists (hybrid classifier AUC = 0.921 vs. two-neuropathologist consensus AUC = 0.920). We also show that models trained at different levels of magnification exhibit different types of errors, supporting the value of aggregation across spatial scales in the ML approach. Finally, we present a detailed interpretation of our multi-scale ML ensemble model which reveals that predictions are driven by human-identifiable features at the patch-level.

Beyond Imaging and Genetic Signature in Glioblastoma: Radiogenomic Holistic Approach in Neuro-Oncology

Glioblastoma (GBM) is a malignant brain tumor exhibiting rapid and infiltrative growth, with less than 10% of patients surviving over 5 years, despite aggressive and multimodal treatments. The poor prognosis and the lack of effective pharmacological treatments are imputable to a remarkable histological and molecular heterogeneity of GBM, which has led, to date, to the failure of precision oncology and targeted therapies. Identification of molecular biomarkers is a paradigm for comprehensive and tailored treatments; nevertheless, biopsy sampling has proved to be invasive and limited. Radiogenomics is an emerging translational field of research aiming to study the correlation between radiographic signature and underlying gene expression. Although a research field still under development, not yet incorporated into routine clinical practice, it promises to be a useful non-invasive tool for future personalized/adaptive neuro-oncology. This review provides an up-to-date summary of the recent advancements in the use of magnetic resonance imaging (MRI) radiogenomics for the assessment of molecular markers of interest in GBM regarding prognosis and response to treatments, for monitoring recurrence, also providing insights into the potential efficacy of such an approach for survival prognostication. Despite a high sensitivity and specificity in almost all studies, accuracy, reproducibility and clinical value of radiomic features are the Achilles heel of this newborn tool. Looking into the future, investigators' efforts should be directed towards standardization and a disciplined approach to data collection, algorithms, and statistical analysis.

Dexamethasone and compliance affect TTFields efficacy to glioblastoma patients: a systematic review and meta-analysis

TTFields is a novel treating modality of glioblastoma (GBM) which can significantly prolong the overall survival (OS) of newly diagnosed or recurrent glioblastoma. Some researchers have revealed that a variety of factors can affect the efficacy of TTFields. So, we review the available literature about the influencing factors on efficacy of TTFields and then choose two experimentally supported factors: the dose of dexamethasone and compliance of TTFields to perform a meta-analysis. The PubMed, Embase, and the Cochrane Library are searched. Five articles are identified between 2014 and 2017. Three articles are about the compliance of TTFields. Two articles are about the dose of dexamethasone. The Newcastle-Ottawa Quality Assessment Scale (NOS) is used as an assessment tool to evaluate the methodological quality of all included trials. The scale’s range varies from 0 to 9 stars. According to the Cochrane Handbook for Systematic Reviews of Interventions, articles are graded in six items to evaluate the risk of bias. Two reviewers rate the studies independently and the final decision is reached by consensus.

Our data shows that the median OS is conspicuously longer in the TTFields group in which the dose of dexamethasone is ≤ 4.1 mg, WMD = 9.23 [95% CI 5.69–12.78]; P < 0.05). And the patients whose compliance of TTFields treatment ≥ 75% (≥ 18 h per day) have a significant lower overall survival risk than the patients whose compliance of TTFields treatment < 75% (HR = 0.57 [95% CI 0.46–0.70]; P < 0.00001).TTFields is a safe and efficient novel treatment modality. The dose of dexamethasone ≤ 4.1 mg of TTFields treatment and the compliance of TTFields treatment ≥ 75%, ≥ 18 h per day are beneficial to the prognosis of the glioblastoma patients.

Calcipotriol, a synthetic Vitamin D analog, promotes antitumor immunity via CD4+T-dependent CTL/NK cell activation

To overcome the hurdles of immunotherapy, we investigated whether calcipotriol, a synthetic vitamin D analog, could overcome the immune evasion of glioblastoma multiforme (GBM) by modulating immune responses and the immunosuppressive tumor microenvironment. Administration of calcipotriol considerably reduced tumor growth. Both in vivo and in vitro studies revealed that CD8+T and natural killer (NK) cell gene signatures were enriched and activated, producing high levels of IFN-γ and granzyme B. In contrast, regulatory T cells (Treg) were significantly reduced in the calcipotriol-treated group. The expression of CD127, the receptor for thymic stromal lymphopoietin (TSLP), is elevated in CD4+T cells and potentially supports T-cell priming. Depleting CD4+T cells, but not NK or CD8+T cells, completely abrogated the antitumor efficacy of calcipotriol. These data highlight that the calcipotriol/TSLP/CD4+T axis can activate CD8+T and NK cells with a concomitant reduction in the number of Tregs in GBM. Therefore, calcipotriol can be a novel therapeutic modality to overcome the immune resistance of GBM by converting immunologically "cold" tumors into "hot" tumors. DATA AVAILABILITY: Data are available upon reasonable request. The RNA-seq dataset comparing the transcriptomes of control and calcipotriol-treated GL261 tumors is available from the corresponding author upon request.

Cells and material-based strategies for regenerative endodontics

The carious process leads to inflammation of pulp tissue. Current care options include root canal treatment or apexification. These procedures, however, result in the loss of tooth vitality, sensitivity, and healing. Pulp capping and dental pulp regeneration are continually evolving techniques to regenerate pulp tissue, avoiding necrosis and loss of vitality. Many studies have successfully employed stem/progenitor cell populations, revascularization approaches, scaffolds or material-based strategies for pulp regeneration. Here we outline advantages and disadvantages of different methods and techniques which are currently being used in the field of regenerative endodontics. We also summarize recent findings on efficacious peptide-based materials which target the dental niche.

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Anti-Survival Effect of SI306 and Its Derivatives on Human Glioblastoma Cells

Glioblastoma (GBM) is the most common adult brain tumor and, although many efforts have been made to find valid therapies, the onset of resistance is the main cause of recurrence. Therefore, it is crucial to identify and target the molecular mediators responsible for GBM malignancy. In this context, the use of Src inhibitors such as SI306 (C1) and its prodrug (C2) showed promising results, suggesting that SI306 could be the lead compound useful to derivate new anti-GBM drugs. Therefore, a new prodrug of SI306 (C3) was synthesized and tested on CAS-1 and U87 human GBM cells by comparing its effect to that of C1 and C2. All compounds were more effective on CAS-1 than U87 cells, while C2 was the most active on both cell lines. Moreover, the anti-survival effect was associated with a reduction in the expression of epidermal growth factor receptor (EGFR)WT and EGFR-vIII in U87 and CAS-1 cells, respectively. Collectively, our findings demonstrate that all tested compounds are able to counteract GBM survival, further supporting the role of SI306 as progenitor of promising new drugs to treat malignant GBM.

Congress of neurological surgeons systematic review and evidence-based guidelines update on the role of neuropathology in the management of progressive glioblastoma in adults

TARGET POPULATION

These recommendations apply to adult patients with progressive or recurrent glioblastoma (GBM).

QUESTION

For adult patients with progressive glioblastoma does testing for Isocitrate Dehydrogenase (IDH) 1 or 2 mutations provide new additional management or prognostic information beyond that derived from the tumor at initial presentation?

RECOMMENDATION

Level III: Repeat IDH mutation testing is not necessary if the tumor is histologically similar to the primary tumor and the patient's clinical course is as expected.

QUESTION

For adult patients with progressive glioblastoma does repeat testing for MGMT promoter methylation provide new or additional management or prognostic information beyond that derived from the tumor at initial presentation and what methods of detection are optimal?

RECOMMENDATION

Level III: Repeat MGMT promoter methylation is not recommended.

QUESTION

For adult patients with progressive glioblastoma does EGFR amplification or mutation testing provide management or prognostic information beyond that provided by histologic analysis and if performed on previous tissue samples, does it need to be repeated?

RECOMMENDATION

Level III: In cases that are difficult to classify as glioblastoma on histologic features EGFR amplification testing may help in classification. If a previous EGFR amplification was detected, repeat testing is not necessary. Repeat EGFR amplification or mutational testing may be recommended in patients in which target therapy is being considered.

QUESTION

For adult patients with progressive glioblastoma does large panel or whole genome sequencing provide management or prognostic information beyond that derived from histologic analysis?

RECOMMENDATION

Level III: Primary or repeat large panel or whole genome sequencing may be considered in patients who are eligible or interested in molecularly guided therapy or clinical trials.

QUESTION

For adult patients with progressive glioblastoma should immune checkpoint biomarker testing be performed to provide management and prognostic information beyond that obtained from histologic analysis?

RECOMMENDATION

Level III: The current evidence does not support making PD-L1 or mismatch repair (MMR) enzyme activity a component of standard testing.

QUESTION

For adult patients with progressive glioblastoma are there meaningful biomarkers for bevacizumab responsiveness and does their assessment provide additional information for tumor management and prognosis beyond that learned by standard histologic analysis?

RECOMMENDATION

Level III: No established Bevacizumab biomarkers are currently available based upon the inclusion criteria of this guideline.

Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis

Cancer diagnosis, prognosis, mymargin and therapeutic response predictions are based on morphological information from histology slides and molecular profiles from genomic data. However, most deep learning-based objective outcome prediction and grading paradigms are based on histology or genomics alone and do not make use of the complementary information in an intuitive manner. In this work, we propose Pathomic Fusion, an interpretable strategy for end-to-end multimodal fusion of histology image and genomic (mutations, CNV, RNA-Seq) features for survival outcome prediction. Our approach models pairwise feature interactions across modalities by taking the Kronecker product of unimodal feature representations, and controls the expressiveness of each representation via a gating-based attention mechanism. Following supervised learning, we are able to interpret and saliently localize features across each modality, and understand how feature importance shifts when conditioning on multimodal input. We validate our approach using glioma and clear cell renal cell carcinoma datasets from the Cancer Genome Atlas (TCGA), which contains paired whole-slide image, genotype, and transcriptome data with ground truth survival and histologic grade labels. In a 15-fold cross-validation, our results demonstrate that the proposed multimodal fusion paradigm improves prognostic determinations from ground truth grading and molecular subtyping, as well as unimodal deep networks trained on histology and genomic data alone. The proposed method establishes insight and theory on how to train deep networks on multimodal biomedical data in an intuitive manner, which will be useful for other problems in medicine that seek to combine heterogeneous data streams for understanding diseases and predicting response and resistance to treatment. Code and trained models are made available at: https://github.com/mahmoodlab/PathomicFusion.

Controlled microwave-assisted reactions: A facile synthesis of polyfunctionally substituted phthalazines as dual EGFR and PI3K inhibitors in CNS SNB-75 cell line

Brain tumors are stubborn cancers with poor prognosis and disappointing survival rates. Targeted cancer therapeutics with higher efficacy and lower resistance are highly demanded. An efficient one-pot synthesis of polyfunctionalized phthalazines derivatives was developed by reacting ethyl 1-aryl-5-cyano-1,6-dihydro-4-methyl-6-oxo-3-pyridazine-carboxylates with cinnamonitrile derivatives and the cycloaddition reaction of thieno[3,4-d]pyridazines with activated double or triple bond systems under controlled microwave heating with high yields. The resultant synthesized phthalazines (5a-e, 9 and 13) were tested for their in vitro anti-cancer activities by using in vitro one dose assay at National Cancer institute, USA. Only phthalazine (5b) showed broad spectrum anti-tumor activity against most tested cancer cell lines from all subpanels with mean % GI = 22.61. Interestingly, all tested compounds showed varying growth inhibitory activity against a particular cell line, CNS SNB-75 cell line, but (5b) exhibited the highest growth inhibitory activity against CNS-SNB-75 cell line with (GI% = 108.81) and (IC₅₀ = 3.703 ± 0.2) compared to erlotinib; (IC₅₀ = 12.5 ± 0.68). It caused Pre-G1 apoptosis and growth arrest at S phase. It also increased percentage of the total apoptotic cells in CNS-SNB-75 cell line (39.26%) compared to control cells (2.17%) in the annexin V-FITC experiment. It revealed pronounced EGFR inhibitory activity (IC₅₀ = 47.27 ± 2.41 ng/mL) compared to erlotinib (IC₅₀ = 30.7 ± 1.56 ng/mL). It also inhibited the different PI3K isoforms α, β, γ and δ (with IC₅₀ of 4.39, 13.6, 12.5 and 3.11 μg/mL, respectively compared to LY294002 (with IC₅₀ of 12.7, 8.57, 6.89 and 5.7 μg/mL, respectively). It also caused significant lower protein expression levels of pPI3K, AKT, pAKT and Bcl2 and higher protein expression levels of BAX, Casp3 and Casp9 when compared to untreated cells. Conclusion: Phthalazine (5b) may be an effective, convenient and safe anti-cancer agent acting via proapoptotic and dual EGFR and PI3K kinase inhibitory actions in CNS SNB-75 cell line.

Necrotic reshaping of the glioma microenvironment drives disease progression

Glioblastoma is the most common primary brain tumor and has a dismal prognosis. The development of central necrosis represents a tipping point in the evolution of these tumors that foreshadows aggressive expansion, swiftly leading to mortality. The onset of necrosis, severe hypoxia and associated radial glioma expansion correlates with dramatic tumor microenvironment (TME) alterations that accelerate tumor growth. In the past, most have concluded that hypoxia and necrosis must arise due to "cancer outgrowing its blood supply" when rapid tumor growth outpaces metabolic supply, leading to diffusion-limited hypoxia. However, growing evidence suggests that microscopic intravascular thrombosis driven by the neoplastic overexpression of pro-coagulants attenuates glioma blood supply (perfusion-limited hypoxia), leading to TME restructuring that includes breakdown of the blood-brain barrier, immunosuppressive immune cell accumulation, microvascular hyperproliferation, glioma stem cell enrichment and tumor cell migration outward. Cumulatively, these adaptations result in rapid tumor expansion, resistance to therapeutic interventions and clinical progression. To inform future translational investigations, the complex interplay among environmental cues and myriad cell types that contribute to this aggressive phenotype requires better understanding. This review focuses on contributions from intratumoral thrombosis, the effects of hypoxia and necrosis, the adaptive and innate immune responses, and the current state of targeted therapeutic interventions.

TERT expression increases with tumor grade in a cohort of IDH-mutant gliomas

The molecular mechanisms underlying progression from astrocytoma to secondary glioblastoma are poorly understood. Telomerase reverse transcriptase (TERT), a gene encoding for the catalytic subunit of telomerase, is upregulated in various cancers. Upregulation of TERT is a likely mechanism by which malignant cells delay senescence and evade cell death. TERT activity is also the primary mechanism by which malignant cells replenish telomeres, with the other means of telomere replacement being the alternative lengthening of the telomeres (ALT) system. The ALT system is known to be upregulated in tumors harboring loss of function mutations in ATRX. This study analyzed aggregate data on TERT and ATRX expression in astrocytoma, anaplastic astrocytoma, and secondary glioblastoma and then supplemented the data with our findings. In data obtained from Oncomine, significantly higher TERT expression is seen in astrocytomas and secondary glioblastomas compared to normal brain tissue. Additionally, The Cancer Genome Atlas data shows that TERT expression is a significant predictor of overall survival in low-grade gliomas. However, studies comparing the expression of TERT across all grades of astrocytomas had not been performed to date. Using immunohistochemical staining, we showed that controlling for ATRX and IDH mutational status, TERT expression increased with tumor grade in a cohort of patient-derived astrocytoma, anaplastic astrocytoma, and secondary glioblastoma samples. These findings indicate that TERT expression increases as astrocytomas become more aggressive tumors, and probably plays a role in their progression.

Radiomics for precision medicine in glioblastoma

INTRODUCTION

Being the most common primary brain tumor, glioblastoma presents as an extremely challenging malignancy to treat with dismal outcomes despite treatment. Varying molecular epidemiology of glioblastoma between patients and intra-tumoral heterogeneity explains the failure of current one-size-fits-all treatment modalities. Radiomics uses machine learning to identify salient features of the tumor on brain imaging and promises patient-specific management in glioblastoma patients.

METHODS

We performed a comprehensive review of the available literature on studies investigating the role of radiomics and radiogenomics models for the diagnosis, stratification, prognostication as well as treatment planning and monitoring of glioblastoma.

RESULTS

Classifiers based on a combination of various MRI sequences, genetic information and clinical data can predict non-invasive tumor diagnosis, overall survival and treatment response with reasonable accuracy. However, the use of radiomics for glioblastoma treatment remains in infancy as larger sample sizes, standardized image acquisition and data extraction techniques are needed to develop machine learning models that can be translated effectively into clinical practice.

CONCLUSION

Radiomics has the potential to transform the scope of glioblastoma management through personalized medicine.

STAT3 Enhances Sensitivity of Glioblastoma to Drug-Induced Autophagy-Dependent Cell Death

Simple Summary

Glioblastoma is the most common primary brain cancer in adults. One reason for the development and malignancy of this tumor is the misregulation of certain cellular proteins. The oncoprotein STAT3 that is frequently overactive in glioblastoma cells is associated with more aggressive disease and decreased patient survival. Autophagy is a form of cellular self digestion that normally maintains cell integrity and provides nutrients and basic building blocks required for growth. While glioblastoma is known to be particularly resistant to conventional therapies, recent research has suggested that these tumors are more sensitive to excessive overactivation of autophagy, leading to autophagy-dependent tumor cell death. Here, we show a hitherto unknown role of STAT3 in sensitizing glioblastoma cells to excessive autophagy induced with the repurposed drug pimozide. These findings provide the basis for future research aimed at determining whether STAT3 can serve as a predictor for autophagy-proficient tumors and further support the notion of overactivating autophagy for cancer therapy.

Abstract

Glioblastoma (GBM) is a devastating disease and the most common primary brain malignancy of adults with a median survival barely exceeding one year. Recent findings suggest that the antipsychotic drug pimozide triggers an autophagy-dependent, lysosomal type of cell death in GBM cells with possible implications for GBM therapy. One oncoprotein that is often overactivated in these tumors and associated with a particularly dismal prognosis is Signal Transducer and Activator of Transcription 3 (STAT3). Here, we used isogenic human and murine GBM knockout cell lines, advanced fluorescence microscopy, transcriptomic analysis and FACS-based assessment of cell viability to show that STAT3 has an underappreciated, context-dependent role in drug-induced cell death. Specifically, we demonstrate that depletion of STAT3 significantly enhances cell survival after treatment with Pimozide, suggesting that STAT3 confers a particular vulnerability to GBM. Furthermore, we show that active STAT3 has no major influence on the early steps of the autophagy pathway, but exacerbates drug-induced lysosomal membrane permeabilization (LMP) and release of cathepsins into the cytosol. Collectively, our findings support the concept of exploiting the pro-death functions of autophagy and LMP for GBM therapy and to further determine whether STAT3 can be employed as a treatment predictor for highly apoptosis-resistant, but autophagy-proficient cancers.

Prognostic risk stratification of gliomas using deep learning in digital pathology images

Background

Evaluation of tumor-tissue images stained with hematoxylin and eosin (H&E) is pivotal in diagnosis, yet only a fraction of the rich phenotypic information is considered for clinical care. Here, we propose a survival deep learning (SDL) framework to extract this information to predict glioma survival.

Methods

Digitized whole slide images were downloaded from The Cancer Genome Atlas (TCGA) for 766 diffuse glioma patients, including isocitrate dehydrogenase (IDH)-mutant/1p19q-codeleted oligodendroglioma, IDH-mutant/1p19q-intact astrocytoma, and IDH-wildtype astrocytoma/glioblastoma. Our SDL framework employs a residual convolutional neural network with a survival model to predict patient risk from H&E-stained whole-slide images. We used statistical sampling techniques and randomized the transformation of images to address challenges in learning from histology images. The SDL risk score was evaluated in traditional and recursive partitioning (RPA) survival models.

Results

The SDL risk score demonstrated substantial univariate prognostic power (median concordance index of 0.79 [se: 0.01]). After adjusting for age and World Health Organization 2016 subtype, the SDL risk score was significantly associated with overall survival (OS; hazard ratio = 2.45; 95% CI: 2.01 to 3.00). Four distinct survival risk groups were characterized by RPA based on SDL risk score, IDH status, and age with markedly different median OS ranging from 1.03 years to 14.14 years.

Conclusions

The present study highlights the independent prognostic power of the SDL risk score for objective and accurate prediction of glioma outcomes. Further, we show that the RPA delineation of patient-specific risk scores and clinical prognostic factors can successfully demarcate the OS of glioma patients.

Hemodynamic molecular imaging of tumor-associated enzyme activity in the living brain

Molecular imaging could have great utility for detecting, classifying, and guiding treatment of brain disorders, but existing probes offer limited capability for assessing relevant physiological parameters. Here, we describe a potent approach for noninvasive mapping of cancer-associated enzyme activity using a molecular sensor that acts on the vasculature, providing a diagnostic readout via local changes in hemodynamic image contrast. The sensor is targeted at the fibroblast activation protein (FAP), an extracellular dipeptidase and clinically relevant biomarker of brain tumor biology. Optimal FAP sensor variants were identified by screening a series of prototypes for responsiveness in a cell-based bioassay. The best variant was then applied for quantitative neuroimaging of FAP activity in rats, where it reveals nanomolar-scale FAP expression by xenografted cells. The activated probe also induces robust hemodynamic contrast in nonhuman primate brain. This work thus demonstrates a potentially translatable strategy for ultrasensitive functional imaging of molecular targets in neuromedicine.

Transcriptional Regulation of Amino Acid Transport in Glioblastoma Multiforme

Simple Summary

Glioblastoma multiforme (GBM) is a highly invasive brain tumor that typically has poor patient outcomes. This is due in part to aggressive tumor expansion within the brain parenchyma. This process is aided by assiduous glutamate release via the System xc- (SXC) cystine–glutamate antiporter. SXC is over-expressed in roughly half of GBM tumors where it is responsible for glutamate-mediated neuronal cell death and provides excess glutamate to fuel tumor-associated epilepsy. Available pharmacological inhibitors have some promise, although they lack specificity and have poor bioavailability. Therefore, identifying regulators of SXC may provide a superior avenue to target GBM. In this study, we identify tumor protein 53 (TP53) as a molecular regulator of SXC in GBM.

Abstract

Glioblastoma multiforme (GBM) is a deadly brain tumor with a large unmet therapeutic need. Here, we tested the hypothesis that wild-type p53 is a negative transcriptional regulator of SLC7A11, the gene encoding the System xc- (SXC) catalytic subunit, xCT, in GBM. We demonstrate that xCT expression is inversely correlated with p53 expression in patient tissue. Using representative patient derived (PDX) tumor xenolines with wild-type, null, and mutant p53 we show that p53 expression negatively correlates with xCT expression. Using chromatin immunoprecipitation studies, we present a molecular interaction whereby p53 binds to the SLC7A11 promoter, suppressing gene expression in PDX GBM cells. Accordingly, genetic knockdown of p53 increases SLC7A11 transcript levels; conversely, over-expressing p53 in p53-null GBM cells downregulates xCT expression and glutamate release. Proof of principal studies in mice with flank gliomas demonstrate that daily treatment with the mutant p53 reactivator, PRIMA-1^Met, results in reduced tumor growth associated with reduced xCT expression. These findings suggest that p53 is a molecular switch for GBM glutamate biology, with potential therapeutic utility.

Cilium Expression Score Predicts Glioma Survival

The accurate classification, prognostication, and treatment of gliomas has been hindered by an existing cellular, genomic, and transcriptomic heterogeneity within individual tumors and their microenvironments. Traditional clustering is limited in its ability to distinguish heterogeneity in gliomas because the clusters are required to be exclusive and exhaustive. In contrast, biclustering can identify groups of co-regulated genes with respect to a subset of samples and vice versa. In this study, we analyzed 1,798 normal and tumor brain samples using an unsupervised biclustering approach. We identified co-regulated gene expression profiles that were linked to proximally located brain regions and detected upregulated genes in subsets of gliomas, associated with their histologic grade and clinical outcome. In particular, we present a cilium-associated signature that when upregulated in tumors is predictive of poor survival. We also introduce a risk score based on expression of 12 cilium-associated genes which is reproducibly informative of survival independent of other prognostic biomarkers. These results highlight the role of cilia in development and progression of gliomas and suggest potential therapeutic vulnerabilities for these highly aggressive tumors.