IDH mutation status is associated with distinct vascular gene expression signatures in lower-grade gliomas

Low- and High-Grade Glioma-Associated Vascular Cells Differentially Regulate Tumor Growth

A key feature distinguishing high-grade glioma (HG) from low-grade glioma (LG) is the extensive neovascularization and endothelial hyperproliferation. Prior work has shown that tumor-associated vasculature from HG is molecularly and functionally distinct from normal brain vasculature and expresses higher levels of protumorigenic factors that promote glioma growth and progression. However, it remains unclear whether vessels from LG also express protumorigenic factors, and to what extent they functionally contribute to glioma growth. Here, we profile the transcriptomes of glioma-associated vascular cells (GVC) from IDH-mutant (mIDH) LG and IDH-wild-type (wIDH) HG and show that they exhibit significant molecular and functional differences. LG-GVC show enrichment of extracellular matrix-related gene sets and sensitivity to antiangiogenic drugs, whereas HG-GVC display an increase in immune response-related gene sets and antiangiogenic resistance. Strikingly, conditioned media from LG-GVC inhibits the growth of wIDH glioblastoma cells, whereas HG-GVC promotes growth. In vivo cotransplantation of LG-GVC with tumor cells reduces growth, whereas HG-GVC enhances tumor growth in orthotopic xenografts. We identify ASPORIN (ASPN), a small leucine-rich repeat proteoglycan, highly enriched in LG-GVC as a growth suppressor of wIDH glioblastoma cells in vitro and in vivo. Together, these findings indicate that GVC from LG and HG are molecularly and functionally distinct and differentially regulate tumor growth. Implications: This study demonstrated that vascular cells from IDH-mutant LG and IDH-wild-type HG exhibit distinct molecular signatures and have differential effects on tumor growth via regulation of ASPN-TGFβ1-GPM6A signaling.

CD93 maintains endothelial barrier function and limits metastatic dissemination

Compromised vascular integrity facilitates extravasation of cancer cells and promotes metastatic dissemination. CD93 has emerged as a target for antiangiogenic therapy, but its importance for vascular integrity in metastatic cancers has not been evaluated. Here, we demonstrate that CD93 participates in maintaining the endothelial barrier and reducing metastatic dissemination. Primary melanoma growth was hampered in CD93-/- mice, but metastatic dissemination was increased and associated with disruption of adherens and tight junctions in tumor endothelial cells and elevated expression of matrix metalloprotease 9 at the metastatic site. CD93 directly interacted with vascular endothelial growth factor receptor 2 (VEGFR2) and its absence led to VEGF-induced hyperphosphorylation of VEGFR2 in endothelial cells. Antagonistic anti-VEGFR2 antibody therapy rescued endothelial barrier function and reduced the metastatic burden in CD93-/- mice to wild-type levels. These findings reveal a key role of CD93 in maintaining vascular integrity, which has implications for pathological angiogenesis and endothelial barrier function in metastatic cancer.

Low- and high-grade glioma endothelial cells differentially regulate tumor growth

Background

A key feature distinguishing high-grade glioma (HGG) from low-grade glioma (LGG) is the extensive neovascularization and endothelial hyperproliferation. Prior work has shown that tumor endothelial cells (TEC) from HGG are molecularly and functionally distinct from normal brain EC and secrete higher levels of pro-tumorigenic factors that promote glioma growth and progression. However, it remains unclear whether TEC from LGG also express pro-tumorigenic factors, and to what extent they functionally contribute to glioma growth.

Methods

Transcriptomic profiling was conducted on tumor endothelial cells (TEC) from grade II/III (LGG, IDH-mutant) and grade IV HGG (IDH-wildtype). Functional differences between LGG- and HGG-TEC were evaluated using growth assays, resistance to anti-angiogenic drugs and radiation therapy. Conditioned media and specific factors from LGG- and HGG-TEC were tested on patient-derived gliomasphere lines using growth assays in vitro and in co-transplantation studies in vivo in orthotopic xenograft models.

Results

LGG-TEC showed enrichment of extracellular matrix and cell cycle-related gene sets and sensitivity to anti-angiogenic therapy whereas HGG-TEC displayed an increase in immune response-related gene sets and anti-angiogenic resistance. LGG- and HGG-TEC displayed opposing effects on growth and proliferation of IDH-wildtype and mutant tumor cells. Asporin (ASPN), a small leucine rich proteoglycan enriched in LGG-TEC was identified as a growth suppressor of IDH-wildtype GBM by modulating TGFΒ1-GPM6A signaling.

Conclusions

Our findings indicate that TEC from LGG and HGG are molecularly and functionally heterogeneous and differentially regulate the growth of IDH-wildtype and mutant tumors.

Tumor collagens predict genetic features and patient outcomes

The extracellular matrix (ECM) is a critical determinant of tumor fate that reflects the output from myriad cell types in the tumor. Collagens constitute the principal components of the tumor ECM. The changing collagen composition in tumors along with their impact on patient outcomes and possible biomarkers remains largely unknown. The RNA expression of the 43 collagen genes from solid tumors in The Cancer Genome Atlas (TCGA) was clustered to classify tumors. PanCancer analysis revealed how collagens by themselves can identify the tissue of origin. Clustering by collagens in each cancer type demonstrated strong associations with survival, specific immunoenvironments, somatic gene mutations, copy number variations, and aneuploidy. We developed a machine learning classifier that predicts aneuploidy, and chromosome arm copy number alteration (CNA) status based on collagen expression alone with high accuracy in many cancer types with somatic mutations, suggesting a strong relationship between the collagen ECM context and specific molecular alterations. These findings have broad implications in defining the relationship between cancer-related genetic defects and the tumor microenvironment to improve prognosis and therapeutic targeting for patient care, opening new avenues of investigation to define tumor ecosystems.

Whole-tumor histogram analysis of diffusion and perfusion metrics for noninvasive pediatric glioma grading

PURPOSE

An accurate assessment of the World Health Organization grade is vital for patients with pediatric gliomas to direct treatment planning. We aim to evaluate the diagnostic performance of whole-tumor histogram analysis of diffusion-weighted imaging (DWI) and dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC-PWI) for differentiating pediatric high-grade gliomas from pediatric low-grade gliomas.

METHODS

Sixty-eight pediatric patients (mean age, 10.47 ± 4.37 years; 42 boys) with histologically confirmed gliomas underwent preoperative MR examination. The conventional MRI features and whole-tumor histogram features extracted from apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) maps were analyzed, respectively. Receiver operating characteristic curves and the binary logistic regression analysis were performed to determine the diagnostic performance of parameters.

RESULTS

For conventional MRI features, location, hemorrhage and tumor margin showed significant difference between pediatric high- and low-grade gliomas (all, P < .05). For advanced MRI parameters, ten histogram features of ADC and CBV showed significant differences between pediatric high- and low-grade gliomas (all, P < .05). The diagnostic performance of the combination of DSC-PWI and DWI (AUC = 0.976, sensitivity = 100%, NPV = 100%) is superior to conventional MRI or DWI model, respectively (AUC_cMRI = 0.700, AUC_DWI = 0.830; both, P < .05).

CONCLUSION

The whole-tumor histogram analysis of DWI and DSC-PWI is a promising method for grading pediatric gliomas.

Radiomic features from dynamic susceptibility contrast perfusion-weighted imaging improve the three-class prediction of molecular subtypes in patients with adult diffuse gliomas

OBJECTIVES

To investigate whether radiomic features extracted from dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) can improve the prediction of the molecular subtypes of adult diffuse gliomas, and to further develop and validate a multimodal radiomic model by integrating radiomic features from conventional and perfusion MRI.

METHODS

We extracted 1197 radiomic features from each sequence of conventional MRI and DSC-PWI, respectively. The Boruta algorithm was used for feature selection and combination, and a three-class random forest method was applied to construct the models. We also constructed a combined model by integrating radiomic features and clinical metrics. The models' diagnostic performance for discriminating the molecular subtypes (IDH wild type [IDHwt], IDH mutant and 1p/19q-noncodeleted [IDHmut-noncodel], and IDH mutant and 1p/19q-codeleted [IDHmut-codel]) was compared using AUCs in the validation set.

RESULTS

We included 272 patients (training set, n = 166; validation set, n = 106) with grade II-IV gliomas (mean age, 48.7 years; range, 19-77 years). The proportions of the molecular subtypes were 66.2% IDHwt, 15.1% IDHmut-noncodel, and 18.8% IDHmut-codel. Nineteen radiomic features (13 from conventional MRI and 6 from DSC-PWI) were selected to build the multimodal radiomic model. In the validation set, the multimodal radiomic model showed better performance than the conventional radiomic model did in predicting the IDHwt and IDHmut-codel subtypes, which was comparable to the conventional radiomic model in predicting the IDHmut-noncodel subtype. The multimodal radiomic model yielded similar performance as the combined model in predicting the three molecular subtypes.

CONCLUSIONS

Adding DSC-PWI to conventional MRI can improve molecular subtype prediction in patients with diffuse gliomas.

KEY POINTS

• The multimodal radiomic model outperformed conventional MRI when predicting both the IDH wild type and IDH mutant and 1p/19q-codeleted subtypes of gliomas. • The multimodal radiomic model showed comparable performance to the combined model in the prediction of the three molecular subtypes. • Radiomic features from T1-weighted gadolinium contrast-enhanced and relative cerebral blood volume images played an important role in the prediction of molecular subtypes.

Anti-Vascular Endothelial Growth Factor Therapy Abolishes Glioma-Associated Endothelial Cell-Induced Tumor Invasion

Tumor-remodeled endothelial cells not only facilitate the formation of tumor angiogenesis but also promote tumorigenesis. In this study, we aimed to explore the interaction between glioma-associated endothelial cells (GAEs) and glioma cells. We found that different subtypes of glioma owned distinct GAE abundance. Glioma patients with high GAE abundance exhibited poor prognosis. Both the results of the bioinformatics analysis and the in vitro co-culture system assay revealed that GAE promoted glioma cell invasion. Besides, anti-vascular endothelial growth factor (VEGF) therapy partially abolished the effects of GAE on gliomas. Moreover, anti-VEGF therapy upregulated IL-2 expression in GAE, and exogenous IL-2 administration inhibits GAE-induced glioma cell invasion. Collectively, our present study provides a novel outstanding of the interaction between GAE and glioma cells.

Effects of metabolic cancer therapy on tumor microenvironment

Targeting tumor metabolism for cancer therapy is an old strategy. In fact, historically the first effective cancer therapeutics were directed at nucleotide metabolism. The spectrum of metabolic drugs considered in cancer increases rapidly - clinical trials are in progress for agents directed at glycolysis, oxidative phosphorylation, glutaminolysis and several others. These pathways are essential for cancer cell proliferation and redox homeostasis, but are also required, to various degrees, in other cell types present in the tumor microenvironment, including immune cells, endothelial cells and fibroblasts. How metabolism-targeted treatments impact these tumor-associated cell types is not fully understood, even though their response may co-determine the overall effectivity of therapy. Indeed, the metabolic dependencies of stromal cells have been overlooked for a long time. Therefore, it is important that metabolic therapy is considered in the context of tumor microenvironment, as understanding the metabolic vulnerabilities of both cancer and stromal cells can guide new treatment concepts and help better understand treatment resistance. In this review we discuss recent findings covering the impact of metabolic interventions on cellular components of the tumor microenvironment and their implications for metabolic cancer therapy.

Expression of hub genes of endothelial cells in glioblastoma-A prognostic model for GBM patients integrating single-cell RNA sequencing and bulk RNA sequencing

BACKGROUND

This study aimed to use single-cell RNA-seq (scRNA-seq) to discover marker genes in endothelial cells (ECs) and construct a prognostic model for glioblastoma multiforme (GBM) patients in combination with traditional high-throughput RNA sequencing (bulk RNA-seq).

METHODS

Bulk RNA-seq data was downloaded from The Cancer Genome Atlas (TCGA) and The China Glioma Genome Atlas (CGGA) databases. 10x scRNA-seq data for GBM were obtained from the Gene Expression Omnibus (GEO) database. The uniform manifold approximation and projection (UMAP) were used for downscaling and cluster identification. Key modules and differentially expressed genes (DEGs) were identified by weighted gene correlation network analysis (WGCNA). A non-negative matrix decomposition (NMF) algorithm was used to identify the different subtypes based on DEGs, and multivariate cox regression analysis to model the prognosis. Finally, differences in mutational landscape, immune cell abundance, immune checkpoint inhibitors (ICIs)-associated genes, immunotherapy effects, and enriched pathways were investigated between different risk groups.

RESULTS

The analysis of scRNA-seq data from eight samples revealed 13 clusters and four cell types. After applying Fisher's exact test, ECs were identified as the most important cell type. The NMF algorithm identified two clusters with different prognostic and immunological features based on DEGs. We finally built a prognostic model based on the expression levels of four key genes. Higher risk scores were significantly associated with poorer survival outcomes, low mutation rates in IDH genes, and upregulation of immune checkpoints such as PD-L1 and CD276.

CONCLUSION

We built and validated a 4-gene signature for GBM using 10 scRNA-seq and bulk RNA-seq data in this work.

High levels of TIMP1 are associated with increased extracellular matrix stiffness in isocitrate dehydrogenase 1-wild type gliomas

Glioma progression is accompanied with increased tumor tissue stiffness, yet the underlying mechanisms are unclear. Herein, we employed atomic force microscopy analysis to show that tissue stiffness was higher in isocitrate dehydrogenase (IDH)-wild type gliomas than IDH-mutant gliomas. Bioinformatic analyses revealed that tissue inhibitor of metalloproteinase-1 (TIMP1) was one of the preferentially upregulated genes in IDH-wild type gliomas as compared to IDH-mutant gliomas, and its higher expression indicated worse prognosis of glioma patients. TIMP1 intensity determined by immunofluorescence staining on glioma tissues positively correlated with glioma tissue stiffness. Mechanistically, TIMP1 expression was positively correlated with the gene expression of two predominant extracellular matrix components, tenascin C and fibronectin, both of which were also highly expressed in IDH-wild type gliomas. By introducing IDH1-R132H-containing vectors into human IDH1-wild type glioma cells to obtain an IDH1-mutant cell line, we found that IDH1 mutation increased the TIMP1 promoter methylation through methylation-specific PCR. More importantly, IDH1-R132H mutation decreased both the expression of TIMP1, fibronectin, tenascin C, and the tumor tissue stiffness in IDH1-mutant glioma xenografts in contrast to IDH1-wild type counterparts. Moreover, TIMP1 knockdown in IDH-wild type glioma cells inhibited the expression of tenascin C and fibronectin, and decreased tissue stiffness in intracranial glioma xenografts. Conclusively, we revealed an IDH mutation status-mediated mechanism in regulating glioma tissue stiffness through modulating TIMP1 and downstream extracellular matrix components.

Factors Involved in Preoperative Edema in High-Grade Gliomas

Background Expansion of preoperative edema (PE) is an independent poor prognostic factor in high-grade gliomas. Evaluation of PE provides important information that can be readily obtained from magnetic resonance imaging (MRI), but there are few reports on factors associated with PE. The goal of this study was to identify factors contributing to PE in Grade 3 (G3) and Grade 4 (G4) gliomas. Methodology PE was measured in 141 pathologically proven G3 and G4 gliomas, and factors with a potential relationship with PE were examined in univariate and multivariate analyses. The following eight explanatory variables were used: age, sex, Karnofsky performance status (KPS), location of the glioma, tumor diameter, pathological grade, isocitrate dehydrogenase (IDH)-1-R132H status, and Ki-67 index. Overall survival (OS) and progression-free survival (PFS) were calculated in groups divided by PE (<1 vs. ≥1 cm) and by factors with a significant correlation with PE in multivariate analysis. Results In univariate analysis, age (p = 0.013), KPS (p = 0.012), pathology grade (p = 0.004), and IDH1-R132H status (p = 0.0003) were significantly correlated with PE. In multivariate analysis, only IDH1-R132H status showed a significant correlation (p = 0.036), with a regression coefficient of -0.42. The median follow-up period in survivors was 38.9 months (range: 1.2-131.7 months). The one-, two-, and three-year OS rates for PE <1 vs. ≥1 cm were 77% vs. 68%, 67% vs. 44%, and 63% vs. 24% (p = 0.0001), respectively, and those for IDH1-R132H mutated vs. wild-type cases were 85% vs. 67%, 85% vs. 40%, and 81% vs. 21% (p < 0.0001), respectively. The one-, two-, and three-year PFS rates for PE <1 vs. ≥1 cm were 77% vs. 49%, 64% vs. 24%, and 50% vs. 18% (p = 0.0002), respectively, and those for IDH1-R132H mutated vs. wild-type cases were 85% vs. 48%, 77% vs. 23%, and 73% vs. 14% (p < 0.0001), respectively. Conclusions IDH1-R132H status was found to be a significant contributor to PE. Cases with PE <1 cm and those with the IDH1-R132H mutation clearly had a better prognosis.

Recent insights into the microRNA-dependent modulation of gliomas from pathogenesis to diagnosis and treatment

Gliomas are the most lethal primary brain tumors in adults. These highly invasive tumors have poor 5-year survival for patients. Gliomas are principally characterized by rapid diffusion as well as high levels of cellular heterogeneity. However, to date, the exact pathogenic mechanisms, contributing to gliomas remain ambiguous. MicroRNAs (miRNAs), as small noncoding RNAs of about 20 nucleotides in length, are known as chief modulators of different biological processes at both transcriptional and posttranscriptional levels. More recently, it has been revealed that these noncoding RNA molecules have essential roles in tumorigenesis and progression of multiple cancers, including gliomas. Interestingly, miRNAs are able to modulate diverse cancer-related processes such as cell proliferation and apoptosis, invasion and migration, differentiation and stemness, angiogenesis, and drug resistance; thus, impaired miRNAs may result in deterioration of gliomas. Additionally, miRNAs can be secreted into cerebrospinal fluid (CSF), as well as the bloodstream, and transported between normal and tumor cells freely or by exosomes, converting them into potential diagnostic and/or prognostic biomarkers for gliomas. They would also be great therapeutic agents, especially if they could cross the blood–brain barrier (BBB). Accordingly, in the current review, the contribution of miRNAs to glioma pathogenesis is first discussed, then their glioma-related diagnostic/prognostic and therapeutic potential is highlighted briefly.

Dynamic Interactions between Tumor Cells and Brain Microvascular Endothelial Cells in Glioblastoma

Simple Summary

In glioblastoma (GBM), tumor cells develop a symbiotic relation with brain microvascular endothelial cells (BMECs) to shift tissue homeostasis toward a tumor-supporting context. Disentangling the molecular mechanisms that govern this dynamic interaction in the context of GBM represents an exciting challenge for the update of conventional treatment and for the development of novel therapeutic targets for this aggressive and lethal brain tumor.

Abstract

GBM is the most aggressive brain tumor among adults. It is characterized by extensive vascularization, and its further growth and recurrence depend on the formation of new blood vessels. In GBM, tumor angiogenesis is a multi-step process involving the proliferation, migration and differentiation of BMECs under the stimulation of specific signals derived from the cancer cells through a wide variety of communication routes. In this review, we discuss the dynamic interaction between BMECs and tumor cells by providing evidence of how tumor cells hijack the BMECs for the formation of new vessels. Tumor cell–BMECs interplay involves multiple routes of communication, including soluble factors, such as chemokines and cytokines, direct cell–cell contact and extracellular vesicles that participate in and fuel this cooperation. We also describe how this interaction is able to modify the BMECs structure, metabolism and physiology in a way that favors tumor growth and invasiveness. Finally, we briefly reviewed the recent advances and the potential future implications of some high-throughput 3D models to better understanding the complexity of BMECs–tumor cell interaction.

Paradoxical role of β8 integrin on angiogenesis and vasculogenic mimicry in glioblastoma

Glioblastoma multiforme (GBM) is the most aggressive and highly vascularized brain tumor with poor prognosis. Endothelial cell-dependent angiogenesis and tumor cell-dependent Vasculogenic mimicry (VM) synergistically contribute to glioma vascularization and progression. However, the mechanism underlying GBM vascularization remains unclear. In this study, GBM stem cells (GSCs) were divided into high and low β8 integrin (ITGB8) subpopulations. Co-culture assays followed by Cell Counting Kit-8 (CCK-8), migration, Matrigel tube formation, and sprouting assays were conducted to assess the proliferative, migratory and angiogenic capacity of GBM cells and human brain microvascular endothelial cells (hBMECs). An intracranial glioma model was constructed to assess the effect of ITGB8 on tumor vascularization in vivo. Our results indicated that ITGB8 expression was elevated in GSCs and positively associated with stem cell markers in glioma tissues, and could be induced by hypoxia and p38 activation. ITGB8 in GSCs inhibited the angiogenesis of hBMECs in vitro, while it promoted the ability of network formation and expression of VM-related proteins. The orthotopic GBM model showed that ITGB8 contributed to decreased angiogenesis, meanwhile enhanced invasiveness and VM formation. Mechanistic studies indicated that ITGB8-TGFβ1 axis modulates VM and epithelial-mesenchymal transition (EMT) process via Smad2/3-RhoA signaling. Together, our findings demonstrated a differential role for ITGB8 in the regulation of angiogenesis and VM formation in GBM, and suggest that pharmacological inhibition of ITGB8 may represent a promising therapeutic strategy for treatment of GBM.

A systematic review and meta-analysis on the differentiation of glioma grade and mutational status by use of perfusion-based magnetic resonance imaging

Background

Molecular characterization plays a crucial role in glioma classification which impacts treatment strategy and patient outcome. Dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) perfusion imaging have been suggested as methods to help characterize glioma in a non-invasive fashion. This study set out to review and meta-analyze the evidence on the accuracy of DSC and/or DCE perfusion MRI in predicting IDH genotype and 1p/19q integrity status.

Methods

After systematic literature search on Medline, EMBASE, Web of Science and the Cochrane Library, a qualitative meta-synthesis and quantitative meta-analysis were conducted. Meta-analysis was carried out on aggregated AUC data for different perfusion metrics.

Results

Of 680 papers, twelve were included for the qualitative meta-synthesis, totaling 1384 patients. It was observed that CBV, ktrans, Ve and Vp values were, in general, significantly higher in IDH wildtype compared to IDH mutated glioma. Meta-analysis comprising of five papers (totaling 316 patients) showed that the AUC of CBV, ktrans, Ve and Vp were 0.85 (95%-CI 0.75–0.93), 0.81 (95%-CI 0.74–0.89), 0.84 (95%-CI 0.71–0.97) and 0.76 (95%-CI 0.61–0.90), respectively. No conclusive data on the prediction of 1p/19q integrity was available from these studies.

Conclusions

Future research should aim to predict 1p/19q integrity based on perfusion MRI data. Additionally, correlations with other clinically relevant outcomes should be further investigated, including patient stratification for treatment and overall survival.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13244-022-01230-7.

Prediction of IDH Mutation Status in High-grade Gliomas Using DWI and High T1-weight DSC-MRI

RATIONALE AND OBJECTIVES

We aimed to evaluate the diagnostic performance of diffusion-weighted imaging (DWI) and dynamic susceptibility contrast-enhanced (DSC) magnetic resonance imaging (MRI) parameters in the noninvasive prediction of the isocitrate dehydrogenase (IDH) mutation status in high-grade gliomas (HGGs).

MATERIALS AND METHODS

A total of 58 patients with histopathologically proved HGGs were included in this retrospective study. All patients underwent multiparametric MRI on 3-T, including DSC-MRI and DWI before surgery. The mean apparent diffusion coefficient (ADC), relative maximum cerebral blood volume (rCBV), and percentage signal recovery (PSR) of the tumor core were measured and compared depending on the IDH mutation status and tumor grade. The Mann-Whitney U test was used to detect statistically significant differences in parameters between IDH-mutant-type (IDH-m-type) and IDH-wild-type (IDH-w-type) HGGs. Receiver operating characteristic curve (ROC) analysis was performed to evaluate the diagnostic performance.

RESULTS

The rCBV was significantly higher, and the PSR value was significantly lower in IDH-w-type tumors than in the IDH-m group (p = 0.002 and <0.001, respectively).The ADC value in IDH-w-type tumors was significantly lower compared with the one in IDH-m types (p = 0.023), but remarkable overlaps were found between the groups. The PSR showed the best diagnostic performance with an AUC of 0.938 and with an accuracy rate of 0.87 at the optimal cutoff value of 86.85. The combination of the PSR and the rCBV for the identification of the IDH mutation status increased the discrimination ability at the AUC level of 0.955. In terms of each tumor grade, the PSR and rCBV showed significant differences between the IDH-m and IDH-w groups (p ≤0.001).

CONCLUSION

The rCBV and PSR from DSC-MRI may be feasible noninvasive imaging parameters for predicting the IDH mutation status in HGGs. The standardization of the imaging protocol is indispensable to the utility of DSC perfusion MRI in wider clinical usage.

Nanomedicine for brain cancer

CNS tumors remain among the deadliest forms of cancer, resisting conventional and new treatment approaches, with mortality rates staying practically unchanged over the past 30 years. One of the primary hurdles for treating these cancers is delivering drugs to the brain tumor site in therapeutic concentration, evading the blood-brain (tumor) barrier (BBB/BBTB). Supramolecular nanomedicines (NMs) are increasingly demonstrating noteworthy prospects for addressing these challenges utilizing their unique characteristics, such as improving the bioavailability of the payloadsviacontrolled pharmacokinetics and pharmacodynamics, BBB/BBTB crossing functions, superior distribution in the brain tumor site, and tumor-specific drug activation profiles. Here, we review NM-based brain tumor targeting approaches to demonstrate their applicability and translation potential from different perspectives. To this end, we provide a general overview of brain tumor and their treatments, the incidence of the BBB and BBTB, and their role on NM targeting, as well as the potential of NMs for promoting superior therapeutic effects. Additionally, we discuss critical issues of NMs and their clinical trials, aiming to bolster the potential clinical applications of NMs in treating these life-threatening diseases.

Uncovering a Key Role of ETS1 on Vascular Abnormality in Glioblastoma

Glioblastoma (GBM) is the most aggressive type of brain tumor. Microvascular proliferation and abnormal vasculature are the hallmarks of the GBM, aggravating disease progression and increasing patient morbidity. Here, we uncovered a key role of ETS1 on vascular abnormality in glioblastoma. ETS1 was upregulated in endothelial cells from human tumors compared to endothelial cells from paired control brain tissue. Knockdown of Ets1 in mouse brain endothelial cells inhibited cell migration and proliferation, and suppressed expression of genes associated with vascular abnormality in GBM. ETS1 upregulation in tumor ECs was dependent on TGFβ signaling, and targeting TGFβ signaling by inhibitor decreased tumor angiogenesis and vascular abnormality in CT-2A glioma model. Our results identified ETS1 as a key factor regulating tumor angiogenesis, and suggested that TGFβ inhibition may suppress the vascular abnormality driven by ETS1.

Prognostic Model and Nomogram Construction Based on a Novel Ferroptosis-Related Gene Signature in Lower-Grade Glioma

Background: Low-grade glioma (LGG) is considered a fatal disease for young adults, with overall survival widely ranging from 1 to 15 years depending on histopathologic and molecular subtypes. As a novel type of programmed cell death, ferroptosis was reported to be involved in tumorigenesis and development, which has been intensively studied in recent years.

Methods: For the discovery cohort, data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) were used to identify the differentially expressed and prognostic ferroptosis-related genes (FRGs). The least absolute shrinkage and selection operator (LASSO) and multivariate Cox were used to establish a prognostic signature with the above-selected FRGs. Then, the signature was developed and validated in TCGA and Chinese Glioma Genome Atlas (CGGA) databases. By combining clinicopathological features and the FRG signature, a nomogram was established to predict individuals’ one-, three-, and five-year survival probability, and its predictive performance was evaluated by Harrell’s concordance index (C-index) and calibration curves. Enrichment analysis was performed to explore the signaling pathways regulated by the signature.

Results: A novel risk signature contains seven FRGs that were constructed and were used to divide patients into two groups. Kaplan–Meier (K−M) survival curve and receiver-operating characteristic (ROC) curve analyses confirmed the prognostic performance of the risk model, followed by external validation based on data from the CGGA. The nomogram based on the risk signature and clinical traits was validated to perform well for predicting the survival rate of LGG. Finally, functional analysis revealed that the immune statuses were different between the two risk groups, which might help explain the underlying mechanisms of ferroptosis in LGG.

Conclusion: In conclusion, this study constructed a novel and robust seven-FRG signature and established a prognostic nomogram for LGG survival prediction.

Multicenter DSC-MRI-Based Radiomics Predict IDH Mutation in Gliomas

Simple Summary

Significant efforts have been put toward developing MRI-based radiogenomics for IDH status subtyping predictions; however, in the vast majority of these approaches, the external validation sets are absent. Another limitation in current studies is the lack of explainability in radiomics models, which hampers clinical trust and translation. Motivated by these challenges, we proposed a multicenter DSC–MRI-based radiomics study based on an independent exploratory set, which was externally validated on two independent cohorts, for IDH mutation status prediction. Our results demonstrated that DSC–MRI radiogenomics in gliomas, coupled with dynamic-based image standardization techniques, hold the potential to provide (a) increased predictive performance by offering models that generalize well, (b) reasoning behind the IDH mutation status predictions, and (c) interpretability of the radiomics features’ impacts in model performance.

Abstract

To address the current lack of dynamic susceptibility contrast magnetic resonance imaging (DSC–MRI)-based radiomics to predict isocitrate dehydrogenase (IDH) mutations in gliomas, we present a multicenter study that featured an independent exploratory set for radiomics model development and external validation using two independent cohorts. The maximum performance of the IDH mutation status prediction on the validation set had an accuracy of 0.544 (Cohen’s kappa: 0.145, F1-score: 0.415, area under the curve-AUC: 0.639, sensitivity: 0.733, specificity: 0.491), which significantly improved to an accuracy of 0.706 (Cohen’s kappa: 0.282, F1-score: 0.474, AUC: 0.667, sensitivity: 0.6, specificity: 0.736) when dynamic-based standardization of the images was performed prior to the radiomics. Model explainability using local interpretable model-agnostic explanations (LIME) and Shapley additive explanations (SHAP) revealed potential intuitive correlations between the IDH–wildtype increased heterogeneity and the texture complexity. These results strengthened our hypothesis that DSC–MRI radiogenomics in gliomas hold the potential to provide increased predictive performance from models that generalize well and provide understandable patterns between IDH mutation status and the extracted features toward enabling the clinical translation of radiogenomics in neuro-oncology.

ELTD1-deletion reduces vascular abnormality and improves T-cell recruitment after PD-1 blockade in glioma

Background

Tumor vessels in glioma are molecularly and functionally abnormal, contributing to treatment resistance. Proteins differentially expressed in glioma vessels can change vessel phenotype and be targeted for therapy. ELTD1 (Adgrl4) is an orphan member of the adhesion G-protein-coupled receptor family upregulated in glioma vessels and has been suggested as a potential therapeutic target. However, the role of ELTD1 in regulating vessel function in glioblastoma is poorly understood.

Methods

ELTD1 expression in human gliomas and its association with patient survival was determined using tissue microarrays and public databases. The role of ELTD1 in regulating tumor vessel phenotype was analyzed using orthotopic glioma models and ELTD1^−/− mice. Endothelial cells isolated from murine gliomas were transcriptionally profiled to determine differentially expressed genes and pathways. The consequence of ELTD1 deletion on glioma immunity was determined by treating tumor-bearing mice with PD-1-blocking antibodies.

Results

ELTD1 levels were upregulated in human glioma vessels, increased with tumor malignancy, and were associated with poor patient survival. Progression of orthotopic gliomas was not affected by ELTD1 deletion, however, tumor vascular function was improved in ELTD1^−/− mice. Bioinformatic analysis of differentially expressed genes indicated increased inflammatory response and decreased proliferation in tumor endothelium in ELTD1^−/− mice. Consistent with an enhanced inflammatory response, ELTD1 deletion improved T-cell infiltration in GL261-bearing mice after PD-1 checkpoint blockade.

Conclusion

Our data demonstrate that ELTD1 participates in inducing vascular dysfunction in glioma, and suggest that targeting of ELTD1 may normalize the vessels and improve the response to immunotherapy.

Multi-parametric Z-spectral MRI may have a good performance for glioma stratification in clinical patients

OBJECTIVES

To comprehensively and noninvasively risk-stratify glioma grade, isocitrate dehydrogenase (IDH) genotype, and 1p/19q codeletion status using multi-contrast Z-spectral magnetic resonance imaging (MRI).

METHODS

One hundred and thirteen patients with glioma were retrospectively included. Multiple contrasts contributing to Z-spectra, including direct saturation of water (DSW), semi-solid magnetization transfer contrast (MTC), amide proton transfer (APT) effect, aliphatic nuclear Overhauser effect, and the 2-ppm chemical exchange saturation transfer peak (CEST@2ppm), were fitted with five individual Lorentzian functions. Z-spectral contrasts were compared according to the three most important risk stratifications: tumor grade, IDH genotype, and 1p/19q codeletion status. We further investigated the differentiation of 1p/19q codeletion status within IDH mutant gliomas. The stratification performance of individual Z-spectral contrasts and their combination was quantified using receiver operating characteristic (ROC) analyses.

RESULTS

DSW was significantly different within grade, IDH genotypes, and 1p/19q codeletion status. APT was significantly different with grade and IDH mutation, but not with 1p/19q subtypes. CEST@2ppm was only significantly different with 1p/19q codeletion subtypes. DSW and CEST@2ppm were the two Z-spectral contrasts able to differentiate 1p/19q codeletion subtypes within IDH mutant gliomas. For differentiating glioma grades using ROC analyses, DSW achieved the largest AUC. For differentiating IDH genotypes, DSW and APT achieved comparable AUCs. DSW was the best metric for differentiating 1p/19q codeletion status within all patients and within the IDH mutant patients. Combining all Z-spectral contrasts improved sensitivity and specificity for all risk stratifications.

CONCLUSIONS

Multi-parametric Z-spectral MRI serves as a useful, comprehensive, and noninvasive imaging technique for glioma stratification in clinical patients.

KEY POINTS

• Multiple contrasts contributing to Z-spectra were separately fitted with Lorentzian functions. • Z-spectral contrasts were compared within the three most important and common tumor risk stratifications for gliomas: tumor grade, IDH genotype, and 1p/19q codeletion status. • The stratification performance of individual Z-spectral contrasts and their combination was quantified using receiver operating characteristic analyses, which found Z-spectral MRI to be a useful and comprehensive imaging biomarker for glioma stratification.

Tumor Vessels Fuel the Fire in Glioblastoma

Glioblastoma, a subset of aggressive brain tumors, deploy several means to increase blood vessel supply dedicated to the tumor mass. This includes typical program borrowed from embryonic development, such as vasculogenesis and sprouting angiogenesis, as well as unconventional processes, including co-option, vascular mimicry, and transdifferentiation, in which tumor cells are pro-actively engaged. However, these neo-generated vascular networks are morphologically and functionally abnormal, suggesting that the vascularization processes are rather inefficient in the tumor ecosystem. In this review, we reiterate the specificities of each neovascularization modality in glioblastoma, and, how they can be hampered mechanistically in the perspective of anti-cancer therapies.

Identification of Novel Transcriptome Signature as a Potential Prognostic Biomarker for Anti-Angiogenic Therapy in Glioblastoma Multiforme

Glioblastoma multiforme (GBM) is the most common and devastating type of primary brain tumor, with a median survival time of only 15 months. Having a clinically applicable genetic biomarker would lead to a paradigm shift in precise diagnosis, personalized therapeutic decisions, and prognostic prediction for GBM. Radiogenomic profiling connecting radiological imaging features with molecular alterations will offer a noninvasive method for genomic studies of GBM. To this end, we analyzed over 3800 glioma and GBM cases across four independent datasets. The Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases were employed for RNA-Seq analysis, whereas the Ivy Glioblastoma Atlas Project (Ivy-GAP) and The Cancer Imaging Archive (TCIA) provided clinicopathological data. The Clinical Proteomic Tumor Analysis Consortium Glioblastoma Multiforme (CPTAC-GBM) was used for proteomic analysis. We identified a simple three-gene transcriptome signature—SOCS3, VEGFA, and TEK—that can connect GBM’s overall prognosis with genes’ expression and simultaneously correlate radiographical features of perfusion imaging with SOCS3 expression levels. More importantly, the rampant development of neovascularization in GBM offers a promising target for therapeutic intervention. However, treatment with bevacizumab failed to improve overall survival. We identified SOCS3 expression levels as a potential selection marker for patients who may benefit from early initiation of angiogenesis inhibitors.

Tumor-Derived Pericytes Driven by EGFR Mutations Govern the Vascular and Immune Microenvironment of Gliomas

The extraordinary plasticity of glioma cells allows them to contribute to different cellular compartments in tumor vessels, reinforcing the vascular architecture. It was recently revealed that targeting glioma-derived pericytes, which represent a big percentage of the mural cell population in aggressive tumors, increases the permeability of the vessels and improves the efficiency of chemotherapy. However, the molecular determinants of this transdifferentiation process have not been elucidated. Here we show that mutations in EGFR stimulate the capacity of glioma cells to function as pericytes in a BMX- (bone marrow and X-linked) and SOX9-dependent manner. Subsequent activation of platelet-derived growth factor receptor beta in the vessel walls of EGFR-mutant gliomas stabilized the vasculature and facilitated the recruitment of immune cells. These changes in the tumor microenvironment conferred a growth advantage to the tumors but also rendered them sensitive to pericyte-targeting molecules such as ibrutinib or sunitinib. In the absence of EGFR mutations, high-grade gliomas were enriched in blood vessels, but showed a highly disrupted blood-brain barrier due to the decreased BMX/SOX9 activation and pericyte coverage, which led to poor oxygenation, necrosis, and hypoxia. Overall, these findings identify EGFR mutations as key regulators of the glioma-to-pericyte transdifferentiation, highlighting the intricate relationship between the tumor cells and their vascular and immune milieu. Our results lay the foundations for a vascular-dependent stratification of gliomas and suggest different therapeutic vulnerabilities determined by the genetic status of EGFR. SIGNIFICANCE: This study identifies the EGFR-related mechanisms that govern the capacity of glioma cells to transdifferentiate into pericytes, regulating the vascular and immune phenotypes of the tumors. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/81/8/2142/F1.large.jpg.

The presence of TIM-3 positive cells in WHO grade III and IV astrocytic gliomas correlates with isocitrate dehydrogenase mutation status

Diffuse gliomas are aggressive brain tumors that respond poorly to immunotherapy including immune checkpoint inhibition. This resistance may arise from an immunocompromised microenvironment and deficient immune recognition of tumor cells because of low mutational burden. The most prominent genetic alterations in diffuse glioma are mutations in the isocitrate dehydrogenase (IDH) genes that generate the immunosuppressive oncometabolite d-2-hydroxyglutarate. Our objective was to explore the association between IDH mutation and presence of cells expressing the immune checkpoint proteins galectin-9 and/or T cell immunoglobulin and mucin-domain containing-3 (TIM-3). Astrocytic gliomas of World Health Organization (WHO) grades III or IV (36 IDH-mutant and 36 IDH-wild-type) from 72 patients were included in this study. A novel multiplex chromogenic immunohistochemistry panel was applied using antibodies against galectin-9, TIM-3, and the oligodendrocyte transcription factor 2 (OLIG2). Validation studies were performed using data from The Cancer Genome Atlas (TCGA) project. IDH mutation was associated with decreased levels of TIM-3⁺ cells (p < 0.05). No significant association was found between galectin-9 and IDH status (p = 0.10). Most TIM-3⁺ and galectin-9⁺ cells resembled microglia/macrophages, and very few TIM-3⁺ and/or galectin-9⁺ cells co-expressed OLIG2. The percentage of TIM-3⁺ T cells was generally low, however, IDH-mutant tumors contained significantly fewer TIM-3⁺ T cells (p < 0.01) and had a lower interaction rate between TIM-3⁺ T cells and galectin-9⁺ microglia/macrophages (p < 0.05). TCGA data confirmed lower TIM-3 mRNA expression in IDH-mutant compared to IDH-wild-type astrocytic gliomas (p = 0.013). Our results show that IDH mutation is associated with diminished levels of TIM-3⁺ cells and fewer interactions between TIM-3⁺ T cells and galectin-9⁺ microglia/macrophages, suggesting reduced activity of the galectin-9/TIM-3 immune checkpoint pathway in IDH-mutant astrocytic gliomas.

Pre-operative Neurocognitive Function Was More Susceptible to Decline in Isocitrate Dehydrogenase Wild-Type Subgroups of Lower-Grade Glioma Patients

Background: Neuropsychological deficits frequently occur in diffuse lower-grade glioma (DLGG) patients, but their relationship with molecular subgroups based on the 2016 World Health Organization (WHO) Classification of Tumors of the Central Nervous System (CNS) is unclear. Methods: All patients enrolled for this study were divided into different subgroups according to the molecular-integrated 2016 CNS WHO and morphology-centric 2007 CNS WHO to compare their neurocognitive function (NCF) dysfunction. Univariate and multivariate analyses were used to assess the independent factors for NCF decline. The performance of NCF changes for discrimination of IDH and 1p19q status was evaluated by receiver operating characteristic (ROC). Results: There was no significant difference in the clinical characteristics among the molecular and morphologic subgroups. In the molecular subgroups, significant differences in NCF alterations were found in terms of attention function, working memory and executive function in grade II glioma patients; in addition to these changes in NCF, memory function and abstract thinking were also significantly different in grade III glioma patients. The pairwise comparison further confirmed that patients with astrocytoma (A)/anaplastic astrocytoma (AA) with isocitrate dehydrogenase wild-type (IDHwt) glioma were more susceptible to severe cognitive decline in terms of the NCF performance described above. For the morphologic subgroups, only working memory was significantly different in grade III glioma patients. The distribution proportion was significantly different among each subgroup of DLGG (grade II, P = 0.001; grade III, P = 0.002). The proportion of extensive NCF decline (≥5 tests) was 4, 12, and 50% in the IDH mutant oligodendroglioma (IDHm-O), IDHm-A, and IDHwt-A subgroups, and this proportion was 33, 60, and 93% in the IDHm-AO, IDHm-AA, and IDHwt-AA subgroups, respectively. In multivariate regression analysis, molecular types were independent factors for NCF alterations after adjusted the factors of tumor and demographics (p < 0.05). ROC curves suggested combined NCF tests model showed an advantage in the differentiation of IDH status. Conclusions: NCF alteration is closely related to molecular-integrated subgroups with varying degrees and frequencies in DLGG. Patients with IDHwt gliomas are more susceptible to suffer from severe and extensive NCF decline than other subgroups.

Multiple positron emission tomography tracers for use in the classification of gliomas according to the 2016 World Health Organization criteria

Background

The molecular diagnosis of gliomas such as isocitrate dehydrogenase (IDH) status (wild-type [wt] or mutation [mut]) is especially important in the 2016 World Health Organization (WHO) classification. Positron emission tomography (PET) has afforded molecular and metabolic diagnostic imaging. The present study aimed to define the interrelationship between the 2016 WHO classification of gliomas and the integrated data from PET images using multiple tracers, including ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG), ¹¹C-methionine (¹¹C-MET), ¹⁸F-fluorothymidine (¹⁸F-FLT), and ¹⁸F-fluoromisonidazole (¹⁸F-FMISO).

Methods

This retrospective, single-center study comprised 113 patients with newly diagnosed glioma based on the 2016 WHO criteria. Patients were divided into 4 glioma subtypes (Mut, Codel, Wt, and glioblastoma multiforme [GBM]). Tumor standardized uptake value (SUV) divided by mean normal cortical SUV (tumor–normal tissue ratio [TNR]) was calculated for ¹⁸F-FDG, ¹¹C-MET, and ¹⁸F-FLT. Tumor–blood SUV ratio (TBR) was calculated for ¹⁸F-FMISO. To assess the diagnostic accuracy of PET tracers in distinguishing glioma subtypes, a comparative analysis of TNRs and TBR as well as the metabolic tumor volume (MTV) were calculated by Scheffe's multiple comparison procedure for each PET tracer following the Kruskal–Wallis test.

Results

The differences in mean ¹⁸F-FLT TNR and ¹⁸F-FMISO TBR were significant between GBM and other glioma subtypes (P < .001). Regarding the comparison between Gd-T1WI volumes and ¹⁸F-FLT MTVs or ¹⁸F-FMISO MTVs, we identified significant differences between Wt and Mut or Codel (P < .01).

Conclusion

Combined administration of 4 PET tracers might aid in the preoperative differential diagnosis of gliomas according to the 2016 WHO criteria.

Prediction of IDH genotype in gliomas with dynamic susceptibility contrast perfusion MR imaging using an explainable recurrent neural network

BACKGROUND

The aim of this study was to predict isocitrate dehydrogenase (IDH) genotypes of gliomas using an interpretable deep learning application for dynamic susceptibility contrast (DSC) perfusion MRI.

METHODS

Four hundred sixty-three patients with gliomas who underwent preoperative MRI were enrolled in the study. All the patients had immunohistopathologic diagnoses of either IDH-wildtype or IDH-mutant gliomas. Tumor subregions were segmented using a convolutional neural network followed by manual correction. DSC perfusion MRI was performed to obtain T2* susceptibility signal intensity-time curves from each subregion of the tumors: enhancing tumor, non-enhancing tumor, peritumoral edema, and whole tumor. These, with arterial input functions, were fed into a neural network as multidimensional inputs. A convolutional long short-term memory model with an attention mechanism was developed to predict IDH genotypes. Receiver operating characteristics analysis was performed to evaluate the model.

RESULTS

The IDH genotype predictions had an accuracy, sensitivity, and specificity of 92.8%, 92.6%, and 93.1%, respectively, in the validation set (area under the curve [AUC], 0.98; 95% confidence interval [CI], 0.969-0.991) and 91.7%, 92.1%, and 91.5%, respectively, in the test set (AUC, 0.95; 95% CI, 0.898-0.982). In temporal feature analysis, T2* susceptibility signal intensity-time curves obtained from DSC perfusion MRI with attention weights demonstrated high attention on the combination of the end of the pre-contrast baseline, up/downslopes of signal drops, and/or post-bolus plateaus for the curves used to predict IDH genotype.

CONCLUSIONS

We developed an explainable recurrent neural network model based on DSC perfusion MRI to predict IDH genotypes in gliomas.

Metabolic Cancer-Macrophage Crosstalk in the Tumor Microenvironment

Tumors consist of a wide variety of cells, including immune cells, that affect tumor progression. Macrophages are abundant innate immune cells in the tumor microenvironment (TME) and are crucial in regulating tumorigenicity. Specific metabolic conditions in the TME can alter the phenotype of tumor-associated macrophages (TAMs) in a direction that supports their pro-tumor functions. One of these conditions is the accumulation of metabolites, also known as oncometabolites. Interactions of oncometabolites with TAMs can promote a pro-tumorigenic phenotype, thereby sustaining cancer cell growth and decreasing the chance of eradication. This review focuses on the metabolic cancer-macrophage crosstalk in the TME. We discuss how cancer cell metabolism and oncometabolites affect macrophage phenotype and function, and conversely how macrophage metabolism can impact tumor progression. Lastly, we propose tumor-secreted exosome-mediated metabolic signaling as a potential factor in tumorigenesis. Insight in these processes may contribute to the development of novel cancer therapies.

Vessel Size Imaging is Associated with IDH Mutation and Patient Survival in Diffuse Lower-Grade Glioma

Background

Patients with isocitrate dehydrogenase (IDH) mutant gliomas have better survival and appear to be more sensitive to chemotherapy than their IDH wild-type counterparts. We attempted to assess the correlations of vessel size imaging (VSI) values with IDH mutation status and patient survival in diffuse lower-grade glioma (LGG).

Methods

We enrolled 60 patients with diffuse LGGs, among which 43 had IDH-mutant tumors. All patients underwent VSI examination and VSI values for active tumors were calculated. Receiver operating characteristic (ROC) curves were established to evaluate the detection efficiency. Logistic regression was employed to determine the ability of variables to discriminate IDH mutational status. Kaplan–Meier survival analysis and Cox proportional hazards models were utilized to estimate the correlations of VSI values and other risk factors with patient survival.

Results

We observed that VSI values were lower in IDH-mutant LGGs than IDH wild-type LGGs. The VSImax and VSImean values had AUC values of 0.7305 and 0.7401, respectively, in distinguishing IDH-mutant LGGs from IDH wild-type LGGs. Logistic regression showed that VSImean values, age and tumor location were associated with IDH-mutant status, and the formula integrating the three factors had an AUC value of 0.7798 when distinguishing IDH-mutant LGGs from IDH wild-type LGGs. Moreover, LGG patients with high VSI values exhibited worse survival rates than those with low VSI values for both progression-free survival (PFS) and overall survival (OS). Multivariate Cox proportional hazards regression analysis suggested that IDH mutation status, VSImean values and multiple lesions or lobes were risk factors for PFS of LGG patients.

Conclusion

VSI value is associated with IDH genotype and maybe an independent predictor of the survival of patients with LGGs.

Deep Sequencing of Small RNAs from Neurosurgical Extracellular Vesicles Substantiates miR-486-3p as a Circulating Biomarker that Distinguishes Glioblastoma from Lower-Grade Astrocytoma Patients

Extracellular vesicles (EVs) play key roles in glioblastoma (GBM; astrocytoma grade IV) biology and are novel sources of biomarkers. EVs released from GBM tumors can cross the blood-brain-barrier into the periphery carrying GBM molecules, including small non-coding RNA (sncRNA). Biomarkers cargoed in circulating EVs have shown great promise for assessing the molecular state of brain tumors in situ. Neurosurgical aspirate fluids captured during tumor resections are a rich source of GBM-EVs isolated directly from tumor microenvironments. Using density gradient ultracentrifugation, EVs were purified from cavitron ultrasonic surgical aspirate (CUSA) washings from GBM (n = 12) and astrocytoma II-III (GII-III, n = 5) surgeries. The sncRNA contents of surgically captured EVs were profiled using the Illumina^® NextSeq^TM 500 NGS System. Differential expression analysis identified 27 miRNA and 10 piRNA species in GBM relative to GII-III CUSA-EVs. Resolved CUSA-EV sncRNAs could discriminate serum-EV sncRNA profiles from GBM and GII-III patients and healthy controls and 14 miRNAs (including miR-486-3p and miR-106b-3p) and cancer-associated piRNAs (piR_016658, _016659, _020829 and _204090) were also significantly expressed in serum-EVs. Circulating EV markers that correlate with histological, neuroradiographic and clinical parameters will provide objective measures of tumor activity and improve the accuracy of GBM tumor surveillance.

Vascular habitat analysis based on dynamic susceptibility contrast perfusion MRI predicts IDH mutation status and prognosis in high-grade gliomas

OBJECTIVE

The current study aimed to evaluate the clinical practice for hemodynamic tissue signature (HTS) method in IDH genotype prediction in three groups derived from high-grade gliomas.

METHODS

Preoperative MRI examinations of 44 patients with known grade and IDH genotype were assigned into three study groups: glioblastoma multiforme, grade III, and high-grade gliomas. Perfusion parameters were analyzed and were used to automatically draw the four reproducible habitats (high-angiogenic enhancing tumor habitats, low-angiogenic enhancing tumor habitats, infiltrated peripheral edema habitats, vasogenic peripheral edema habitats) related to vascular heterogeneity. These four habitats were then compared between inter-patient with IDH mutation and their wild-type counterparts at these three groups, respectively. The discriminating potential for HTS in assessing IDH mutation status prediction was assessed by ROC curves.

RESULTS

Compared with IDH wild type, IDH mutation had significantly decreased relative cerebral blood volume (rCBV) at the high-angiogenic enhancing tumor habitats and low-angiogenic enhancing tumor habitats. ROC analysis revealed that the rCBVs in habitats had great ability to discriminate IDH mutation from their wild type in all groups. In addition, the Kaplan-Meier survival analysis yielded significant differences for the survival times observed from the populations dichotomized by low (< 4.31) and high (> 4.31) rCBV in the low-angiogenic enhancing tumor habitat.

CONCLUSIONS

The HTS method has been proven to have high prediction capabilities for IDH mutation status in high-grade glioma patients, providing a set of quantifiable habitats associated with tumor vascular heterogeneity.

KEY POINTS

• The HTS method has a high accuracy for molecular stratification prediction for all subsets of HGG. • The HTS method can give IDH mutation-related hemodynamic information of tumor-infiltrated and vasogenic edema. • IDH-relevant rCBV difference in habitats will be a great prognosis factor in HGG.

NAMPT, GRN, and SERPINE1 signature as predictor of disease progression and survival in gliomas

Adipose tissue is an important source of adipokines involved in anti- and pro-inflammatory effects. Their involvement in certain cancers such as breast and colon cancer is known but in gliomas it remains unexplored till date. The aim of this study was to assess the status of adipokines as prognostic markers of gliomas (low grade gliomas [LGG] and glioblastoma mutiforme [GBM]). Expression status (messenger RNA [mRNA]), overall survival (OS) and disease-free survival (DFS) was identified using gene expression profiling interactive analysis server. Clinicopathological analysis and correlation between different adipokines was performed using Xena server. Protein expression status was analyzed using tissue sections from the Human Protein Atlas. Out of 11 adipokines studied visfatin (NAMPT), apelin (APLN), granulin (GRN), serpin peptidase inhibitor/plasminogen activator inhibitor type 1 (PAI-1) member 1 (SERPINE1), and chemokine (C-C motif) ligand 2 (CCL2) mRNA levels were significantly upregulated in both LGG and GBM. Interleukin 6 (IL6) mRNA was found be significantly upregulated only in GBM. NAMPT, GRN, SERPINE1, and IL6 showed reduced OS as well as worst DFS for patients having higher mRNA expression in LGG. Increased expression of CCL2 showed worst OS in LGG patients while resistin (RETN) and GRN showed the worst OS in GBM patients. Higher expression of RETN, GRN, IL6, SERPINE1, and CCL2 were found to be positively correlated with shorter DFS in GBM. In the clinicopathological analysis, NAMPT, GRN, IL6, SERPINE1, and CCL2 expressions were significantly associated between the neoplasm histological G2 and G3 grades. Furthermore, expression of NAMPT, GRN, tumor necrosis factor, IL6, SERPINE1, and CCL2 were significantly associated with histological type in LGG patients. NAMPT, GRN, SERPINE1, CCL2, and RETN expression were found to be correlated with each other in gliomas. Finally, NAMPT, GRN, and SERPINE1 were also found to be upregulated using immunohistochemistry in a lower grade and high grade gliomas as compared to normal cells. In conclusion, we have identified key adipokines, namely NAMPT, GRN, and SERPINE1 as potential diagnostic and prognostic markers that might be instrumental in the development and progression of gliomas.

Tumor angiogenesis: causes, consequences, challenges and opportunities

Tumor vascularization occurs through several distinct biological processes, which not only vary between tumor type and anatomic location, but also occur simultaneously within the same cancer tissue. These processes are orchestrated by a range of secreted factors and signaling pathways and can involve participation of non-endothelial cells, such as progenitors or cancer stem cells. Anti-angiogenic therapies using either antibodies or tyrosine kinase inhibitors have been approved to treat several types of cancer. However, the benefit of treatment has so far been modest, some patients not responding at all and others acquiring resistance. It is becoming increasingly clear that blocking tumors from accessing the circulation is not an easy task to accomplish. Tumor vessel functionality and gene expression often differ vastly when comparing different cancer subtypes, and vessel phenotype can be markedly heterogeneous within a single tumor. Here, we summarize the current understanding of cellular and molecular mechanisms involved in tumor angiogenesis and discuss challenges and opportunities associated with vascular targeting.

Pre-surgical connectome features predict IDH status in diffuse gliomas

Background

Gliomas are the most common type of malignant brain tumor. Clinical outcomes depend on many factors including tumor molecular characteristics. Mutation of the isocitrate dehydrogenase (IDH) gene confers significant benefits in terms of survival and quality of life. Preoperative determination of IDH genotype can facilitate surgical planning, allow for novel clinical trial designs, and assist clinical counseling surrounding the individual patient’s disease.

Methods

In this study, we aimed to evaluate a novel approach for non-invasively predicting IDH status from conventional MRI via connectomics, a whole-brain network-based technique. We retrospectively extracted 93 connectome features from the preoperative, T1-weighted MRI data of 234 adult patients (148 IDH mutated) and evaluated the performance of four common machine learning models to predict IDH genotype.

Results

Area under the curve (AUC) of the receiver operator characteristic were 0.76 to 0.94 with random forest (RF) showing significantly higher performance (p < 0.01) than other algorithms. Feature selection schemes and the addition of age and tumor location did not change RF performance.

Conclusions

Our findings suggest that connectomics is a feasible approach for preoperatively predicting IDH genotype in patients with gliomas. Our results support prior evidence that RF is an ideal machine learning method for this area of research. Additionally, connectomics provides unique insights regarding potential mechanisms of tumor genotype on large-scale brain network organization.

Microenvironmental Heterogeneity in Brain Malignancies

Brain tumors are among the deadliest malignancies. The brain tumor microenvironment (TME) hosts a unique collection of cells, soluble factors, and extracellular matrix components that regulate disease evolution of both primary and metastatic brain malignancies. It is established that macrophages and other myeloid cells are abundant in the brain TME and strongly correlate with aggressive phenotypes and distinct genetic signatures, while lymphoid cells are less frequent but are now known to have a pronounced effect on disease progression. Different types of brain tumors vary widely in their microenvironmental contexture, and the proportion of various stromal components impacts tumor biology. Indeed, emerging evidence suggests an intimate link between the molecular signature of tumor cells and the composition of the TME, shedding light on the mechanisms which underlie microenvironmental heterogeneity in brain cancer. In this review, we discuss the association between TME composition and the diverse molecular profiles of primary gliomas and brain metastases. We also discuss the implications of these associations on the efficacy of immunotherapy in brain malignancies. An appreciation for the causes and functional consequences of microenvironmental heterogeneity in brain cancer will be of crucial importance to the rational design of microenvironment-targeted therapies for these deadly diseases.

Patient-Derived Glioma Models: From Patients to Dish to Animals

Glioblastoma (GBM) is the most common and malignant primary brain tumor in adults associated with a poor survival. Current standard of care consists of surgical resection followed by radiation and chemotherapy. GBMs are highly heterogeneous, having a complex interaction among different cells within the tumor as well as the tumor microenvironment. One of the main challenges in the neuro-oncology field in general, and GBM in particular, is to find an optimum culture condition that maintains the molecular genotype and phenotype as well as heterogeneity of the original tumor in vitro and in vivo. Established cell lines were shown to be a poor model of the disease, failing to recapitulate the phenotype and harboring non-parental genotypic mutations. Given the growing understanding of GBM biology, the discovery of glioma cancer stem-like cells (GSCs), and their role in tumor formation and therapeutic resistance, scientists are turning more towards patient-derived cells and xenografts as a more representative model. In this review, we will discuss the current state of patient-derived GSCs and their xenografts; and provide an overview of different established models to study GBM biology and to identify novel therapeutics in the pre-clinical phase.

RNA processing genes characterize RNA splicing and further stratify lower-grade glioma

BACKGROUND

Aberrant expression of RNA processing genes may drive the alterative RNA profile in lower-grade gliomas (LGGs). Thus, we aimed to further stratify LGGs based on the expression of RNA processing genes.

METHODS

This study included 446 LGGs from The Cancer Genome Atlas (TCGA, training set) and 171 LGGs from the Chinese Glioma Genome Atlas (CGGA, validation set). The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was conducted to develop a risk-signature. The receiver operating characteristic (ROC) curves and Kaplan-Meier curves were used to study the prognosis value of the risk-signature.

RESULTS

Among the tested 784 RNA processing genes, 276 were significantly correlated with the OS of LGGs. Further LASSO Cox regression identified a 19-gene risk-signature, whose risk score was also an independently prognosis factor (P<0.0001, multiplex Cox regression) in the validation dataset. The signature had better prognostic value than the traditional factors "age", "grade" and "WHO 2016 classification" for 3- and 5-year survival both two datasets (AUCs > 85%). Importantly, the risk-signature could further stratify the survival of LGGs in specific subgroups of WHO 2016 classification. Furthermore, alternative splicing events for genes such as EGFR and FGFR were found to be associated with the risk score. mRNA expression levels for genes, which participated in cell proliferation and other processes, were significantly correlated to the risk score.

CONCLUSIONS

Our results highlight the role of RNA processing genes for further stratifying the survival of patients with LGGs and provide insight into the alternative splicing events underlying this role.

Consequences of IDH1/2 Mutations in Gliomas and an Assessment of Inhibitors Targeting Mutated IDH Proteins

Isocitrate dehydrogenases (IDH) 1 and 2 are key metabolic enzymes that generate reduced nicotinamide adenine dinucleotide phosphate (NADPH) to maintain a pool of reduced glutathione and peroxiredoxin, and produce α-ketoglutarate, a co-factor of numerous enzymes. IDH1/2 is mutated in ~70–80% of lower-grade gliomas and the majority of secondary glioblastomas. The mutant IDH1 (R132H), in addition to losing its normal catalytic activity, gains the function of producing the d-(R)-2-hydroxyglutarate (2-HG). Overproduction of 2-HG in cancer cells interferes with cellular metabolism and inhibits histone and DNA demethylases, which results in histone and DNA hypermethylation and the blockade of cellular differentiation. We summarize recent findings characterizing molecular mechanisms underlying oncogenic alterations associated with mutated IDH1/2, and their impact on tumor microenvironment and antitumor immunity. Isoform-selective IDH inhibitors which suppress 2-HG production and induce antitumor responses in cells with IDH1 and IDH2 mutations were developed and validated in preclinical settings. Inhibitors of mutated IDH1/2 enzymes entered clinical trials and represent a novel drug class for targeted therapy of gliomas. We describe the development of small-molecule compounds and peptide vaccines targeting IDH-mutant gliomas and the results of their testing in preclinical and clinical studies. All those results support the translational potential of strategies targeting gliomas carrying IDH1 mutations.

Vascular Targeting to Increase the Efficiency of Immune Checkpoint Blockade in Cancer

Boosting natural immunity against malignant cells has had a major breakthrough in clinical cancer therapy. This is mainly due to the successful development of immune checkpoint blocking antibodies, which release a break on cytolytic anti-tumor-directed T-lymphocytes. However, immune checkpoint blockade is only effective for a proportion of cancer patients, and a major challenge in the field is to understand and overcome treatment resistance. Immune checkpoint blockade relies on successful trafficking of tumor-targeted T-lymphocytes from the secondary lymphoid organs, through the blood stream and into the tumor tissue. Resistance to therapy is often associated with a low density of T-lymphocytes residing within the tumor tissue prior to treatment. The recruitment of leukocytes to the tumor tissue relies on up-regulation of adhesion molecules and chemokines by the tumor vasculature, which is denoted as endothelial activation. Tumor vessels are often poorly activated due to constitutive pro-angiogenic signaling in the tumor microenvironment, and therefore constitute barriers to efficient leukocyte recruitment. An emerging possibility to enhance the efficiency of cancer immunotherapy is to combine pro-inflammatory drugs with anti-angiogenic therapy, which can enable tumor-targeted T-lymphocytes to access the tumor tissue by relieving endothelial anergy and increasing adhesion molecule expression. This would pave the way for efficient immune checkpoint blockade. Here, we review the current understanding of the biological basis of endothelial anergy within the tumor microenvironment, and discuss the challenges and opportunities of combining vascular targeting with immunotherapeutic drugs as suggested by data from key pre-clinical and clinical studies.

AHIF promotes glioblastoma progression and radioresistance via exosomes

Glioblastoma multiforme (GBM) has the highest mortality rate among patients with brain tumors, and radiotherapy forms an important part of its treatment. Thus, there is an urgent requirement to elucidate the mechanisms conferring GBM progression and radioresistance. In the present study, it was identified that antisense transcript of hypoxia‑inducible factor‑1α (AHIF) was significantly upregulated in GBM cancerous tissues, as well as in radioresistant GBM cells. The expression of AHIF was also upregulated in response to radiation. Knockdown of AHIF in GBM cells decreased viability and invasive capacities, and increased the proportion of apoptotic cells. By contrast, overexpression of AHIF in GBM cells increased viability and invasive capacities, and decreased the proportion of apoptotic cells. Furthermore, exosomes derived from AHIF‑knockdown GBM cells inhibited viability, invasion and radioresistance, whereas exosomes derived from AHIF‑overexpressing GBM cells promoted viability, invasion and radioresistance. Further biochemical analysis identified that AHIF regulates factors associated with migration and angiogenesis in exosomes. To the best of our knowledge, the present study is the first to establish that AHIF promotes glioblastoma progression and radioresistance via exosomes, which suggests that AHIF is a potential therapeutic target for GBM.