The evolving molecular genetics of low-grade glioma

Single-cell transcriptomic analysis identifies downregulated phosphodiesterase 8B as a novel oncogene in IDH-mutant glioma

Introduction

Glioma, a prevalent and deadly brain tumor, is marked by significant cellular heterogeneity and metabolic alterations. However, the comprehensive cell-of-origin and metabolic landscape in high-grade (Glioblastoma Multiforme, WHO grade IV) and low-grade (Oligoastrocytoma, WHO grade II) gliomas remains elusive.

Methods

In this study, we undertook single-cell transcriptome sequencing of these glioma grades to elucidate their cellular and metabolic distinctions. Following the identification of cell types, we compared metabolic pathway activities and gene expressions between high-grade and low-grade gliomas.

Results

Notably, astrocytes and oligodendrocyte progenitor cells (OPCs) exhibited the most substantial differences in both metabolic pathways and gene expression, indicative of their distinct origins. The comprehensive analysis identified the most altered metabolic pathways (MCPs) and genes across all cell types, which were further validated against TCGA and CGGA datasets for clinical relevance.

Discussion

Crucially, the metabolic enzyme phosphodiesterase 8B (PDE8B) was found to be exclusively expressed and progressively downregulated in astrocytes and OPCs in higher-grade gliomas. This decreased expression identifies PDE8B as a metabolism-related oncogene in IDH-mutant glioma, marking its dual role as both a protective marker for glioma grading and prognosis and as a facilitator in glioma progression.

Multi-pool chemical exchange saturation transfer MRI in glioma grading, molecular subtyping and evaluating tumor proliferation

PURPOSE

To evaluate the performance of multi-pool Chemical exchange saturation transfer (CEST) MRI in prediction of glioma grade, isocitrate dehydrogenase (IDH) mutation, alpha-thalassemia/mental retardation syndrome X-linked (ATRX) loss and Ki-67 labeling index (LI), based on the fifth edition of the World Health Organization classification of central nervous system tumors (WHO CNS5).

METHODS

95 patients with adult-type diffuse gliomas were analyzed. The amide, direct water saturation (DS), nuclear Overhauser enhancement (NOE), semi-solid magnetization transfer (MT) and amine signals were derived using Lorentzian fitting, and asymmetry-based amide proton transfer-weighted (APTwasym) signal was calculated. The mean value of tumor region was measured and intergroup differences were estimated using student-t test. The receiver operating curve (ROC) and area under the curve (AUC) analysis were used to evaluate the diagnostic performance of signals and their combinations. Spearman correlation analysis was performed to evaluate tumor proliferation.

RESULTS

The amide and DS signals were significantly higher in high-grade gliomas compared to low-grade gliomas, as well as in IDH-wildtype gliomas compared to IDH-mutant gliomas (all p < 0.001). The DS, MT and amine signals showed significantly differences between ATRX loss and retention in grade 2/3 IDH-mutant gliomas (all p < 0.05). The combination of signals showed the highest AUC in prediction of grade (0.857), IDH mutation (0.814) and ATRX loss (0.769). Additionally, the amide and DS signals were positively correlated with Ki-67 LI (both p < 0.001).

CONCLUSION

Multi-pool CEST MRI demonstrated good potential to predict glioma grade, IDH mutation, ATRX loss and Ki-67 LI.

Case Report: Low-grade glioma with NF1 loss of function mimicking diffuse intrinsic pontine glioma

Intrinsic, expansile pontine tumors typically occur in the pediatric population. These tumors characteristically present as diffuse intrinsic pontine glioma (DIPG), which is now considered as diffuse midline glioma (DMG), H3K27-mutated of the pons. DIPG has limited treatment options and a poor prognosis, and the value of tissue diagnosis from an invasive biopsy remains controversial. This study presents the case of a 19-year-old female with clinical and imaging hallmarks of DIPG, who underwent a biopsy of a tumor in the region of the right middle cerebellar peduncle. Her lesional cells were negative for H3K27M alterations and had low-grade histologic features. Next-generation sequencing revealed a frameshift mutation in the NF1 gene as the likely driver mutation. These features suggest a diagnosis of a low-grade glioma associated with NF1 loss of function, with far-reaching consequences regarding both treatment strategy and prognosis. This case provides support for the utility of diagnostic tissue biopsy in cases of suspected DIPG.

Kinin Receptors and Kinin-Related Gene Expression in Astrocytic Brain Tumors

Kinins are a set of peptides present in tissues that are involved in the inflammatory response and cancer progression. However, studies showing the expression of kinin receptors in human glioma samples are still incomplete and contradictory. The aim of the present study was to ascertain the expression of BDKRB1 and BDKRB2 genes, as well as the level of B1R and B2R proteins in human gliomas, depending on the degree of malignancy. Additionally, representative kinin-dependent genes with altered expression were indicated. The expression profile of kinin-dependent genes was determined using oligonucleotide microarray technique. In addition, RT-qPCR was used to assess the expression level of selected differentiating genes. The location of kinin receptors in brain gliomas was assessed using immunohistochemical methods. The oligonucleotide microarray method was used to identify 12 mRNA IDs of kinin-related genes whose expression was upregulated or downregulated in gliomas of different grades. In immunohistochemically stained samples, the concentrations of BR1 and BR2 proteins, measured by optical density, were statistically significantly higher in grade G3 vs. G2 and G4 vs. G3. Increased expression of kinin receptors BDKRB1 and BDKRB2 in brain gliomas, depending on the degree of malignancy, suggests the involvement of kinins and their receptors in the disease's pathogenesis. Quantitative assessment of mRNA BDKRB1, PRKAR1A, MAP2K, and EGFR in patients with brain tumors may hold diagnostic and therapeutic significance.

Brain tumour genetic network signatures of survival

Tumour heterogeneity is increasingly recognized as a major obstacle to therapeutic success across neuro-oncology. Gliomas are characterized by distinct combinations of genetic and epigenetic alterations, resulting in complex interactions across multiple molecular pathways. Predicting disease evolution and prescribing individually optimal treatment requires statistical models complex enough to capture the intricate (epi)genetic structure underpinning oncogenesis. Here, we formalize this task as the inference of distinct patterns of connectivity within hierarchical latent representations of genetic networks. Evaluating multi-institutional clinical, genetic and outcome data from 4023 glioma patients over 14 years, across 12 countries, we employ Bayesian generative stochastic block modelling to reveal a hierarchical network structure of tumour genetics spanning molecularly confirmed glioblastoma, IDH-wildtype; oligodendroglioma, IDH-mutant and 1p/19q codeleted; and astrocytoma, IDH-mutant. Our findings illuminate the complex dependence between features across the genetic landscape of brain tumours and show that generative network models reveal distinct signatures of survival with better prognostic fidelity than current gold standard diagnostic categories.

Pediatric Central Nervous System Tumor Overview and Emerging Treatment Considerations

Pediatric central nervous system (CNS) tumors are the most common solid tumor in children, with the majority being glial in origin. These tumors are classified by the World Health Organization (WHO) as either being low grade (WHO grade 1 and 2) or high grade (WHO grade 3 and 4). Our knowledge of the molecular landscape of pediatric brain tumors has advanced over the last decade, which has led to newer categorizations along with an expansion of therapeutic targets and options. In this review, we will give an overview of common CNS tumors seen in children along with a focus on treatment options and future considerations.

Deep Learning-Assisted Quantitative Susceptibility Mapping as a Tool for Grading and Molecular Subtyping of Gliomas

This study aimed to explore the value of deep learning (DL)-assisted quantitative susceptibility mapping (QSM) in glioma grading and molecular subtyping. Forty-two patients with gliomas, who underwent preoperative T2 fluid-attenuated inversion recovery (T2 FLAIR), contrast-enhanced T1-weighted imaging (T1WI + C), and QSM scanning at 3.0T magnetic resonance imaging (MRI) were included in this study. Histopathology and immunohistochemistry staining were used to determine glioma grades, and isocitrate dehydrogenase (IDH) 1 and alpha thalassemia/mental retardation syndrome X-linked gene (ATRX) subtypes. Tumor segmentation was performed manually using Insight Toolkit-SNAP program (www.itksnap.org). An inception convolutional neural network (CNN) with a subsequent linear layer was employed as the training encoder to capture multi-scale features from MRI slices. Fivefold cross-validation was utilized as the training strategy (seven samples for each fold), and the ratio of sample size of the training, validation, and test dataset was 4:1:1. The performance was evaluated by the accuracy and area under the curve (AUC). With the inception CNN, single modal of QSM showed better performance in differentiating glioblastomas (GBM) and other grade gliomas (OGG, grade II-III), and predicting IDH1 mutation and ATRX loss (accuracy: 0.80, 0.77, 0.60) than either T2 FLAIR (0.69, 0.57, 0.54) or T1WI + C (0.74, 0.57, 0.46). When combining three modalities, compared with any single modality, the best AUC/accuracy/F1-scores were reached in grading gliomas (OGG and GBM: 0.91/0.89/0.87, low-grade and high-grade gliomas: 0.83/0.86/0.81), predicting IDH1 mutation (0.88/0.89/0.85), and predicting ATRX loss (0.78/0.71/0.67). As a supplement to conventional MRI, DL-assisted QSM is a promising molecular imaging method to evaluate glioma grades, IDH1 mutation, and ATRX loss.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-022-00087-6.

BRAF-mediated brain tumors in adults and children: A review and the Australian and New Zealand experience

The mitogen-activated protein kinase (MAPK) pathway signaling pathway is one of the most commonly mutated pathways in human cancers. In particular, BRAF alterations result in constitutive activation of the rapidly accelerating fibrosarcoma-extracellular signal-regulated kinase-MAPK significant pathway, leading to cellular proliferation, survival, and dedifferentiation. The role of BRAF mutations in oncogenesis and tumorigenesis has spurred the development of targeted agents, which have been successful in treating many adult cancers. Despite advances in other cancer types, the morbidity and survival outcomes of patients with glioma have remained relatively stagnant. Recently, there has been recognition that MAPK dysregulation is almost universally present in paediatric and adult gliomas. These findings, accompanying broad molecular characterization of gliomas, has aided prognostication and offered opportunities for clinical trials testing targeted agents. The use of targeted therapies in this disease represents a paradigm shift, although the biochemical complexities has resulted in unexpected challenges in the development of effective BRAF inhibitors. Despite these challenges, there are promising data to support the use of BRAF inhibitors alone and in combination with MEK inhibitors for patients with both low-grade and high-grade glioma across age groups. Safety and efficacy data demonstrate that many of the toxicities of these targeted agents are tolerable while offering objective responses. Newer clinical trials will examine the use of these therapies in the upfront setting. Appropriate duration of therapy and durability of response remains unclear in the glioma patient cohort. Longitudinal efficacy and toxicity data are needed. Furthermore, access to these medications remains challenging outside of clinical trials in Australia and New Zealand. Compassionate access is limited, and advocacy for mechanism of action-based drug approval is ongoing.

Development of a Hallmark Pathway-Related Gene Signature Associated with Immune Response for Lower Grade Gliomas

Although some biomarkers have been used to predict prognosis of lower-grade gliomas (LGGs), a pathway-related signature associated with immune response has not been developed. A key signaling pathway was determined according to the lowest adjusted p value among 50 hallmark pathways. The least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox analyses were performed to construct a pathway-related gene signature. Somatic mutation, drug sensitivity and prediction of immunotherapy analyses were conducted to reveal the value of this signature in targeted therapies. In this study, an allograft rejection (AR) pathway was considered as a crucial signaling pathway, and we constructed an AR-related five-gene signature, which can independently predict the prognosis of LGGs. High-AR LGG patients had higher tumor mutation burden (TMB), Immunophenscore (IPS), IMmuno-PREdictive Score (IMPRES), T cell-inflamed gene expression profile (GEP) score and MHC I association immunoscore (MIAS) than low-AR patients. Most importantly, our signature can be validated in four immunotherapy cohorts. Furthermore, IC50 values of the six classic chemotherapeutic drugs were significantly elevated in the low-AR group compared with the high-AR group. This signature might be regarded as an underlying biomarker in predicting prognosis for LGGs, possibly providing more therapeutic strategies for future clinical research.

Growth differentiation factor-15 overexpression promotes cell proliferation and predicts poor prognosis in cerebral lower-grade gliomas correlated with hypoxia and glycolysis signature

AIMS

Growth differentiation factor-15 (GDF15) plays complex and controversial roles in cancer. In this study, the prognostic value and the exact biological function of GDF15 in cerebral lower-grade gliomas (LGGs) and its potential molecular targets were examined.

MAIN METHODS

Wilcoxon signed-rank test and logistic regression were applied to analyze associations between GDF15 expression and clinical characteristics using the Cancer Genome Atlas (TCGA) database. Overall survival was analyzed using Kaplan-Meier and Cox analyses. Gene set enrichment analysis (GSEA) and the hypoxia risk model was conducted to identify the potential molecular mechanisms underlying the effects of GDF15 on LGGs tumorigenesis. The biological function of GDF15 was examined using gain- and loss-of-function experiments, and a recombinant hGDF15 protein in LGG SW1783 cells in vitro.

KEY FINDINGS

We found that higher GDF15 expression is associated with poor clinical features in LGG patients, and an independent risk factor for overall survival among LGG patients. GSEA results showed that the poor prognostic role of GDF15 in LGGs is related to hypoxia and glycolysis signatures, which was further validated using the hypoxia risk model. Furthermore, GDF15 overexpression facilitated cell proliferation, while GDF15 siRNA inhibits cell proliferation in LGG SW1783 cells. In addition, GDF15 was upregulated upon CoCl2 treatment which induces hypoxia, correlating with the upregulation of the expressions of HIF-1α and glycolysis-related key genes in SW1783 cells.

SIGNIFICANCE

GDF15 may promote LGG tumorigenesis that is associated with the hypoxia and glycolysis pathways, and thus could serve as a promising molecular target for LGG prevention and therapy.

GALNT12 is associated with the malignancy of glioma and promotes glioblastoma multiforme in vitro by activating Akt signaling

Abnormal expression of mucin-type O-glycosylation has been reported to be associated with a variety of human cancers including gliomas. However, little is known about its contribution to the malignancy of Glioblastoma Multiforme (GBM), the deadliest form of brain tumors. Here, we conducted a detailed analysis of the expression profiles of GALNT gene family, which encode polypeptide-N-acetyl-galactosaminyltransferases (GalNAc-Ts) and are responsible for initiating O-glycans, both in the Cancer Genome Atlas (TCGA) and in the Chinese Glioma Genome Atlas (CGGA) databases. We discovered that GALNT12 is the only member within the GALNT family, whose expression demonstrated significant correlation with a worse prognosis of GBM. Genetic knockdown (KD) and knockout (KO) of GALNT12 in U87 MG, a representative GBM cell line with high GALNT12 expression, confirmed that GALNT12 deficiency leads to decreased cell proliferation, migration and invasion. Mechanism study revealed that GALNT12 KD and KO decreased the level of epidermal growth factor (EGF) and consequently attenuated Akt signaling within the cell. In summary, our results indicated that GALNT12 facilitates the malignant characteristics of GBM by influencing the PI3K/Akt/mTOR axis and may serve as a novel prognosis biomarker and a potential therapeutic target of GBM.

Long-Term Follow-Up of Pediatric CNS Tumor Survivors—A Selection of Relevant Long-Term Issues

Introduction: Survivors of pediatric central nervous system (CNS) tumors are at high risk for late effects and long-term morbidity. The quality of survival became increasingly important, as advances in diagnostics, multimodal treatment strategies, and supportive care have led to significant increases in long-term survival. Aim: This review aims to provide a global overview of the potential late effects and long-term follow-up care of CNS tumor survivors, directed to trainees and practitioners with less targeted training in pediatric oncology. Late effects in CNS tumor survivors: A specific focus on CNS tumor survivors relies on cognitive and psychosocial late effects, as they may have an impact on education, professional career, independent living, and quality of life. Further important late effects in CNS tumor survivors include endocrine, metabolic, cardiovascular, and cerebrovascular diseases. Conclusions: Comprehensive long-term follow-up care is essential for pediatric CNS tumor survivors to improve their quality of survival and quality of life. An individualized approach, taking all potential late effects into account, and carried out by an interdisciplinary team, is recommended, and should continue into adulthood. Existing recommendations and guidelines on long-term follow-up care guide the multidisciplinary teams.

Management and outcomes of low-grade gliomas in Africa: A scoping review

Introduction

Methods

Results

Conclusion

•

Highlights for ‘Management and Outcomes of Low Grade Gliomas in Africa’.

•

The burden of low-grade gliomas in Africa is underreported.

•

There was no reported use of molecular pathology testing or intraoperative adjuncts.

•

There were low rates of awake surgery for patients with supratentorial tumours.

•

There was a lag in the uptake of techniques and technologies used in the management of low-grade gliomas.

Novel RAF Fusions in Pediatric Low-Grade Gliomas Demonstrate MAPK Pathway Activation

Brain tumors are the most common solid tumor in children, and low-grade gliomas (LGGs) are the most common childhood brain tumor. Here, we report on 3 patients with LGG harboring previously unreported or rarely reported RAF fusions: FYCO1-RAF1, CTTNBP2-BRAF, and SLC44A1-BRAF. We hypothesized that these tumors would show molecular similarity to the canonical KIAA1549-BRAF fusion that is the most widely seen alteration in pilocytic astrocytoma (PA), the most common pediatric LGG variant, and that this similarity would include mitogen-activated protein kinase (MAPK) pathway activation. To test our hypothesis, we utilized immunofluorescent imaging and RNA-sequencing in normal brain, KIAA1549-BRAF-harboring tumors, and our 3 tumors with novel fusions. We performed immunofluorescent staining of ERK and phosphorylated ERK (p-ERK), identifying increased p-ERK expression in KIAA1549-BRAF fused PA and the novel fusion samples, indicative of MAPK pathway activation. Geneset enrichment analysis further confirmed upregulated downstream MAPK activation. These results suggest that MAPK activation is the oncogenic mechanism in noncanonical RAF fusion-driven LGG. Similarity in the oncogenic mechanism suggests that LGGs with noncanonical RAF fusions are likely to respond to MEK inhibitors.

Transcription Factor Signatures May Predict the Prognosis and Status of the Immune Microenvironment of Primary Lower-Grade Gliomas

Aim

Transcription factor (TF) in glioma, including proliferation, invasion/migration, and tumor microenvironment, has been receiving increasing attention. However, there are still no systematical analyses based on global TF. Herein, using global TF target gene sets, we comprehensively investigated their relationship with prognosis and potential biological effect in lower-grade glioma (LGG). We aimed to develop a less-biased prognostic model and provide new insight for personalized management of this disease.

Methods

TF target gene sets were collected from MSigDB and GRID database followed by ssGSEA calculating normalized enrichment score. Comprehensive survival analysis was combined with Kaplan-Meier and Cox algorithms. Consensus cluster and lasso regression were performed to develop prognostic signatures with validation of ROC and independent external cohort. Approaches of xCell/CIBERSORT/TIMER were involved in analyzing the immune microenvironment. We also correlated identified prognostic signatures with tumor mutational burden (TMB) and m6A genes.

Results

Fourteen TFs were significantly screened based on survival. Patients were classified into 2 prognosis-related clusters based on 14-TFs features. The function of differentially expressed TF target genes between Cluster1/2 was enriched mostly on glioma invasion/migration. The prognostic model was trained by 6 out of 14-TFs followed by generating risk-score as an independent prognostic indicator. We found differences between the high/low-risk group in TMB and the immune microenvironment, where the high-risk group represented "hot-tumor". Besides, 6-TFs were correlated with m6A regulation genes.

Conclusion

Our findings suggested that the 6-TFs model could be used to predict prognosis and predict the status of the immune microenvironment in LGG.

Myeloid-derived suppressor cells (MDSCs) in brain cancer: challenges and therapeutic strategies

The most fatal malignancy of the central nervous system (CNS) is glioblastoma. Brain cancer is a 'cold' tumor because of fewer immunoregulatory cells and more immunosuppressive cells. Due to the cold nature of brain cancers, conventional treatments which are used to manage glioma patients show little effectiveness. Glioma patients even showed resistance to immune checkpoint blockade (ICB) and no significant efficacy. It has been shown that myeloid-derived suppressor cells (MDSCs) account for approximately 30-50% of the tumor mass in glioma. This study aimed to review MDSC function in brain cancer, as well as possible treatments and related challenges. In brain cancer and glioma, several differences in the context of MDSCs have been reported, including disagreements about the MDSC subtype that has the most inhibitory function in the brain, or inhibitory function of regulatory B cells (Bregs). There are also serious challenges in treating glioma patients. In addition to the cold nature of glioma, there are reports of an increase in MDSCs following conventional chemotherapy treatments. As a result, targeting MDSCs in combination with other therapies, such as ICB, is essential, and recent studies with the combination therapy approach have shown promising therapeutic effects in brain cancer.

Characterisation of isocitrate dehydrogenase gene mutant WHO grade 2 and 3 gliomas: MRI predictors of 1p/19q co-deletion and tumour grade

AIM

To identify imaging predictors of molecular subtype and tumour grade in patients with isocitrate dehydrogenase (IDH) gene mutant (IDH_mut) World Health Organization (WHO) grade 2 or 3 gliomas.

MATERIALS AND METHODS

Patients with histologically confirmed WHO grade 2 or 3 IDH_mut gliomas between 2016 and 2019 were included in the study. Magnetic resonance imaging (MRI) images were evaluated for the presence or absence of potential imaging predictors of tumour subtype, such as T2/fluid attenuated inversion recovery (FLAIR) signal match, and these factors were examined using regression analysis. On perfusion imaging, the maximum relative cerebral blood volume (rCBV_max) was evaluated as a potential predictor of tumour grade. The performance of two experienced neuroradiologists in correctly predicting tumour type on MRI was evaluated.

RESULTS

Eighty-five patients were included in the study. The presence of T2/FLAIR signal match >50% of tumour volume (p<0.01) and intratumoural susceptibility (p=0.02) were independent predictors of 1p/19q co-deletion. Mean rCBV max was significantly higher in WHO grade 3 astrocytomas (p=0.04) than WHO grade 2 astrocytomas. The consensus prediction of 1p/19q co-deletion status by two neuroradiologists of tumour was 95% sensitive and 86% specific.

CONCLUSION

The presence of matched T2/FLAIR signal could be used to identify tumour subtype when biopsy is inconclusive or genetic analysis is unavailable. rCBV_max predicted astrocytoma grade. Experienced neuroradiologists predict tumour subtype with good sensitivity and specificity.

Pediatric brain tumors: the era of molecular diagnostics, targeted and immune-based therapeutics, and a focus on long term neurologic sequelae

Pediatric brain tumors are the second most common malignancy of childhood after acute leukemia and the number one cause of cancer-related mortality¹. Over the past decade, advanced molecular diagnostics have led to the discovery of new molecularly-defined tumor types with prognostic and therapeutic implications. Methylation profiles, whole genome sequencing, and transcriptomics have defined subgroups and revealed heterogeneity within commonly defined tumor entities^2,3. These findings have also revealed important differences between adult and pediatric brain tumors of similar histology. The majority of pediatric low grade gliomas (pLGG) are defined by alterations in the mitogen-activated protein kinase (MAPK) pathway including BRAFV600E point mutation, K1AA1549-BRAF fusion, and FGFR1 alterations as opposed to IDH1/2 mutations and 1p/19q co-deletion seen more frequently in adult low grade gliomas⁴. These findings have led to targeted therapies, namely BRAF and MEK inhibitors, which are currently being evaluated in phase III clinical trials and may soon supplant chemotherapy as standard of care for pLGG's. While targeted therapy trials for pediatric brain tumors have had significant success, immunotherapy remains a challenge in a group of tumors with generally lower mutational burden compared to adult tumors and relatively "cold" immune microenvironment. Despite this, a wide array of immunotherapy trials including vaccine therapies, immune checkpoint blockade, chimeric antigen receptor (CAR) T cells, and viral therapies are on-going. Unique to pediatrics, multiple clinical trials have sought to answer the question of whether the most malignant pediatric brain tumors in the youngest patients can be successfully treated with high dose chemotherapy in lieu of radiation to avoid devastating long-term neurocognitive deficits. Due to the collaborative work of multiple pediatric neuro-oncology consortiums, the recent history of pediatric brain tumor research is one of efficient translation from bench to bedside in a rare group of tumors resulting in significant progress in the field. Here, advances in the areas of molecular characterization, targeted and immune-based therapies, and reduction in long term co-morbidities will be reviewed.

Racial/ethnic, socioeconomic, and geographic survival disparities in adolescents and young adults with primary central nervous system tumors

BACKGROUND

Disparities in survival by race/ethnicity, socioeconomic status (SES), and geography in adolescent and young adult (AYA) patients with central nervous system (CNS) tumors have not been well studied.

PROCEDURE

A retrospective cohort study utilizing the Surveillance, Epidemiology, and End Results (SEER) database was conducted for AYA patients diagnosed with primary CNS tumors. Adjusted hazard ratios (aHR) were calculated using a multivariate Cox proportional hazard model to evaluate the association between race/ethnicity, SES, rurality, and hazard of death.

RESULTS

All minority groups showed an increased hazard of death with greatest disparities in the high-grade glioma cohort. Lower SES was associated with an increased hazard of death in non-Hispanic White (NHW) patients (aHR 1.12; 95% confidence interval [CI] 1.01-1.24), non-Hispanic Black (NHB) patients (aHR 1.34; 95% CI 1.00-1.80), and patients aged 25-29 years (aHR 1.29; 95% CI 1.07-1.55). Mediation analysis showed an indirect effect of SES on the effect of race/ethnicity on the hazard of death only among NHB patients, with SES accounting for 33.7% of the association between NHB and hazard of death. Rurality was associated with an increased hazard of death for patients in the lowest SES tertile (aHR 1.31; 95% CI 1.08-1.59) and NHW patients (aHR 1.20; 95% CI 1.08-1.34).

CONCLUSIONS

Patients identified as a racial/ethnic minority, patients with a lower SES, and patients residing in rural areas had an increased hazard of death. Further studies are needed to understand and address the biological, psychosocial, societal, and economic factors that impact AYA neuro-oncology patients at highest risk of experiencing poorer outcomes.

Machine learning applications to neuroimaging for glioma detection and classification: An artificial intelligence augmented systematic review

Glioma is the most common primary intraparenchymal tumor of the brain and the 5-year survival rate of high-grade glioma is poor. Magnetic resonance imaging (MRI) is essential for detecting, characterizing and monitoring brain tumors but definitive diagnosis still relies on surgical pathology. Machine learning has been applied to the analysis of MRI data in glioma research and has the potential to change clinical practice and improve patient outcomes. This systematic review synthesizes and analyzes the current state of machine learning applications to glioma MRI data and explores the use of machine learning for systematic review automation. Various datapoints were extracted from the 153 studies that met inclusion criteria and analyzed. Natural language processing (NLP) analysis involved keyword extraction, topic modeling and document classification. Machine learning has been applied to tumor grading and diagnosis, tumor segmentation, non-invasive genomic biomarker identification, detection of progression and patient survival prediction. Model performance was generally strong (AUC = 0.87 ± 0.09; sensitivity = 0.87 ± 0.10; specificity = 0.0.86 ± 0.10; precision = 0.88 ± 0.11). Convolutional neural network, support vector machine and random forest algorithms were top performers. Deep learning document classifiers yielded acceptable performance (mean 5-fold cross-validation AUC = 0.71). Machine learning tools and data resources were synthesized and summarized to facilitate future research. Machine learning has been widely applied to the processing of MRI data in glioma research and has demonstrated substantial utility. NLP and transfer learning resources enabled the successful development of a replicable method for automating the systematic review article screening process, which has potential for shortening the time from discovery to clinical application in medicine.

New Insights into the Multifaceted Role of Myeloid-Derived Suppressor Cells (MDSCs) in High-Grade Gliomas: From Metabolic Reprograming, Immunosuppression, and Therapeutic Resistance to Current Strategies for Targeting MDSCs

Cancer cells “hijack” host immune cells to promote growth, survival, and metastasis. The immune microenvironment of high-grade gliomas (HGG) is a complex and heterogeneous system, consisting of diverse cell types such as microglia, bone marrow-derived macrophages (BMDMs), myeloid-derived suppressor cells (MDSCs), dendritic cells, natural killer (NK) cells, and T-cells. Of these, MDSCs are one of the major tumor-infiltrating immune cells and are correlated not only with overall worse prognosis but also poor clinical outcomes. Upon entry from the bone marrow into the peripheral blood, spleen, as well as in tumor microenvironment (TME) in HGG patients, MDSCs deploy an array of mechanisms to perform their immune and non-immune suppressive functions. Here, we highlight the origin, function, and characterization of MDSCs and how they are recruited and metabolically reprogrammed in HGG. Furthermore, we discuss the mechanisms by which MDSCs contribute to immunosuppression and resistance to current therapies. Finally, we conclude by summarizing the emerging approaches for targeting MDSCs alone as a monotherapy or in combination with other standard-of-care therapies to improve the current treatment of high-grade glioma patients.

Transcriptome analysis revealed CENPF associated with glioma prognosis

Gliomas are common malignant tumors of the central nervous system. Despite the surgical resection and postoperative radiotherapy and chemotherapy, the prognosis of glioma remains poor. Therefore, it is important to reveal the molecular mechanisms that promotes glioma progression. Microarray datasets were obtained from the Gene Expression Omnibus (GEO) database. The GEO2R tool was used to identify 428 differentially expressed genes (DEGs) and a core module from three microarray datasets. Heat maps were drawn based on DEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using the DAVID database. The core module was significantly involved in several KEGG pathways, such as "cell cycle", "viral carcinogenesis", "progesterone-mediated oocyte maturation", "p53 signaling pathway". The protein-protein interaction (PPI) networks and modules were built using the STRING database and the MCODE plugin, respectively, which were visualized using Cytoscape software. Identification of hub genes in the core module using the CytoHubba plugin. The top modular genes AURKA, CDC20, CDK1, CENPF, and TOP2A were associated with glioma development and prognosis. In the Human Protein Atlas (HPA) database, CDC20, CENPF and TOP2A have significant protein expression. Univariate and multivariate cox regression analysis showed that only CENPF had independent influencing factors in the CGGA database. GSEA analysis found that CENPF was significantly enriched in the cell cycle, P53 signaling pathway, MAPK signaling pathway, DNA replication, spliceosome, ubiquitin-mediated proteolysis, focal adhesion, pathway in cancer, glioma, which was highly consistent with previous studies. Our study revealed a core module that was highly correlated with glioma development. The key gene CENPF and signaling pathways were identified through a series of bioinformatics analysis. CENPF was identified as a candidate biomarker molecule.

Prediction and analysis of hub genes between glioblastoma and low-grade glioma using bioinformatics analysis

ABSTRACT

Gliomas are an intractable tumor in the central nervous system. The present study aimed to identify the differentially expressed genes (DEGs) between glioblastoma multiforme (GBM) and low-grade gliomas (LGG) in order to investigate the mechanisms of different grades of gliomas. The Cancer Genome Atlas (TCGA) database was used to identify DEGs between GBM and LGG, and 2641 genes have been found differentially expressed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to determine the related functions and pathways of DEGs. Protein-protein interaction (PPI) network extracted a total of 444 nodes and 1953 interactions, and identified the top 6 hub genes in gliomas. The microarray data of the datasets GSE52009 and GSE4412, which were obtained from Gene Expression Omnibus (GEO) database, were used to externally validate DEGs expression levels. Gene Expression Profiling Interactive Analysis (GEPIA) database which was based on TCGA was used to explore the survival of hub genes in LGG and GBM. Additionally, the Oncomine database and Chinese Glioma Genome Atlas (CGGA) database were used to validate the mRNA expression level and prognostic value of hub genes. Gene Set Enrichment Analysis (GSEA) identified further hub genes-related pathways. In summary, through biological information and survival analysis, 6 hub genes may be new biomarkers for diagnosis and for guiding the choice of treatment strategies for different grades of gliomas.

Hippo Signaling Pathway in Gliomas

The Hippo signaling pathway is a highly conserved pathway involved in tissue development and regeneration that controls organ size through the regulation of cell proliferation and apoptosis. The core Hippo pathway is composed of a block of kinases, MST1/2 (Mammalian STE20-like protein kinase 1/2) and LATS1/2 (Large tumor suppressor 1/2), which inhibits nuclear translocation of YAP/TAZ (Yes-Associated Protein 1/Transcriptional co-activator with PDZ-binding motif) and its downstream association with the TEAD (TEA domain) family of transcription factors. This pathway was recently shown to be involved in tumorigenesis and metastasis in several cancers such as lung, breast, or colorectal cancers but is still poorly investigated in brain tumors. Gliomas are the most common and the most lethal primary brain tumors representing about 80% of malignant central nervous system neoplasms. Despite intensive clinical protocol, the prognosis for patients remains very poor due to systematic relapse and treatment failure. Growing evidence demonstrating the role of Hippo signaling in cancer biology and the lack of efficient treatments for malignant gliomas support the idea that this pathway could represent a potential target paving the way for alternative therapeutics. Based on recent advances in the Hippo pathway deciphering, the main goal of this review is to highlight the role of this pathway in gliomas by a state-of-the-art synthesis.

annoFuse: an R Package to annotate, prioritize, and interactively explore putative oncogenic RNA fusions

BACKGROUND

Gene fusion events are significant sources of somatic variation across adult and pediatric cancers and are some of the most clinically-effective therapeutic targets, yet low consensus of RNA-Seq fusion prediction algorithms makes therapeutic prioritization difficult. In addition, events such as polymerase read-throughs, mis-mapping due to gene homology, and fusions occurring in healthy normal tissue require informed filtering, making it difficult for researchers and clinicians to rapidly discern gene fusions that might be true underlying oncogenic drivers of a tumor and in some cases, appropriate targets for therapy.

RESULTS

We developed annoFuse, an R package, and shinyFuse, a companion web application, to annotate, prioritize, and explore biologically-relevant expressed gene fusions, downstream of fusion calling. We validated annoFuse using a random cohort of TCGA RNA-Seq samples (N = 160) and achieved a 96% sensitivity for retention of high-confidence fusions (N = 603). annoFuse uses FusionAnnotator annotations to filter non-oncogenic and/or artifactual fusions. Then, fusions are prioritized if previously reported in TCGA and/or fusions containing gene partners that are known oncogenes, tumor suppressor genes, COSMIC genes, and/or transcription factors. We applied annoFuse to fusion calls from pediatric brain tumor RNA-Seq samples (N = 1028) provided as part of the Open Pediatric Brain Tumor Atlas (OpenPBTA) Project to determine recurrent fusions and recurrently-fused genes within different brain tumor histologies. annoFuse annotates protein domains using the PFAM database, assesses reciprocality, and annotates gene partners for kinase domain retention. As a standard function, reportFuse enables generation of a reproducible R Markdown report to summarize filtered fusions, visualize breakpoints and protein domains by transcript, and plot recurrent fusions within cohorts. Finally, we created shinyFuse for algorithm-agnostic interactive exploration and plotting of gene fusions.

CONCLUSIONS

annoFuse provides standardized filtering and annotation for gene fusion calls from STAR-Fusion and Arriba by merging, filtering, and prioritizing putative oncogenic fusions across large cancer datasets, as demonstrated here with data from the OpenPBTA project. We are expanding the package to be widely-applicable to other fusion algorithms and expect annoFuse to provide researchers a method for rapidly evaluating, prioritizing, and translating fusion findings in patient tumors.

Long-term outcome of stereotactic brachytherapy with temporary Iodine-125 seeds in patients with WHO grade II gliomas

BACKGROUND

This long-term retrospective analysis aimed to investigate the outcome and toxicity profile of stereotactic brachytherapy (SBT) in selected low-grade gliomas WHO grade II (LGGII) in a large patient series.

METHODS

This analysis comprised 106 consecutive patients who received SBT with temporary Iodine-125 seeds for histologically verified LGGII at the University of Munich between March 1997 and July 2011. Investigation included clinical characteristics, technical aspects of SBT, the application of other treatments, outcome analyses including malignization rates, and prognostic factors with special focus on molecular biomarkers.

RESULTS

For the entire study population, the 5- and 10-years overall survival (OS) rates were 79% and 62%, respectively, with a median follow-up of 115.9 months. No prognostic factors could be identified. Interstitial radiotherapy was applied in 51 cases as first-line treatment with a median number of two seeds (range 1-5), and a median total implanted activity of 21.8 mCi (range 4.2-43.4). The reference dose average was 54.0 Gy. Five- and ten-years OS and progression-free survival rates after SBT were 72% and 43%, and 40% and 23%, respectively, with a median follow-up of 86.7 months. The procedure-related mortality rate was zero, although an overall complication rate of 16% was registered. Patients with complications had a significantly larger tumor volume (p = 0.029).

CONCLUSION

SBT is a minimally invasive treatment modality with a favorable outcome and toxicity profile. It is both an alternative primary treatment method as well as an adjunct to open tumor resection in selected low-grade gliomas.

Advances in Targeted Therapies for Pediatric Brain Tumors

Purpose of Review

Over the last years, our understanding of the molecular biology of pediatric brain tumors has vastly improved. This has led to more narrowly defined subgroups of these tumors and has created new potential targets for molecularly driven therapies. This review presents an overview of the latest advances and challenges of implementing targeted therapies into the clinical management of pediatric brain tumors, with a focus on gliomas, craniopharyngiomas, and medulloblastomas.

Recent Findings

Pediatric low-grade gliomas (pLGG) show generally a low mutational burden with the mitogen-activated protein kinase (MAPK) signaling presenting a key driver for these tumors. Direct inhibition of this pathway through BRAF and/or MEK inhibitors has proven to be a clinically relevant strategy. More recently, MEK and IL-6 receptor inhibitors have started to be evaluated in the treatment for craniopharyngiomas. Aside these low-grade tumors, pediatric high-grade gliomas (pHGG) and medulloblastomas exhibit substantially greater molecular heterogeneity with various and sometimes unknown tumor driver alterations. The clinical benefit of different targeted therapy approaches to interfere with altered signaling pathways and restore epigenetic dysregulation is undergoing active clinical testing. For these multiple pathway-driven tumors, combination strategies will most likely be required to achieve clinical benefit.

Summary

The field of pediatric neuro-oncology made tremendous progress with regard to improved diagnosis setting the stage for precision medicine approaches over the last decades. The potential of targeted therapies has been clearly demonstrated for a subset of pediatric brain tumors. However, despite clear response rates, questions of sufficient blood-brain barrier penetration, optimal dosing, treatment duration as well as mechanisms of resistance and how these can be overcome with potential combination strategies need to be addressed in future investigations. Along this line, it is critical for future trials to define appropriate endpoints to assess therapy responses as well as short and long-term toxicities in the growing and developing child.

Clinical trials using molecular stratification of pediatric brain tumors

Brain cancer is now the leading cause of cancer death in children and adolescents, surpassing leukemia. The heterogeneity and invasiveness of pediatric brain tumors have historically made them difficult to treat. Although surgical intervention and standard of care therapies such as radiation and chemotherapy have improved the outlook for those affected, results are often transient and lend themselves to tumor recurrence or resistance. There also still exists a subset of brain tumors which remain unresponsive to treatment altogether. Therefore, there is great need for new therapeutic approaches. With the recent advent of molecularly-driven technologies, many of these complex tumors can now be classified by integrating molecular profiling data with clinical information such as demographics and outcomes. This new knowledge has allowed for the molecular stratification of pediatric brain tumors into distinct subgroups and the identification of molecular targets, which is changing how these children are treated, namely in the setting of clinical trials. Notable examples include reduced doses of radiation and chemotherapy in the wingless-activated subgroup of medulloblastoma, which has a favorable prognosis, and novel experimental drugs targeting BRAF alterations in low-grade gliomas and dopamine receptors in high-grade gliomas. In this review, we highlight several key previous and ongoing clinical trials that utilize molecular stratifications and targets for the treatment of pediatric brain tumors.

Copy number assessment in the genomic analysis of CNS neoplasia: An evidence-based review from the cancer genomics consortium (CGC) working group on primary CNS tumors

The period from the 1990s to the 2010s has witnessed a burgeoning sea change in the practice of surgical neuropathology due to the incorporation of genomic data into the assessment of a range of central nervous system (CNS) neoplasms. This change has since matured into the adoption of genomic information into the definition of several World Health Organization (WHO)-established diagnostic entities. The data needed to accomplish the modern diagnosis of CNS neoplasia includes DNA copy number aberrations that may be assessed through a variety of mechanisms. Through a review of the relevant literature and professional practice guidelines, here we provide a condensed and scored overview of the most critical DNA copy number aberrations to assess for a selection of primary CNS neoplasms.

High-order radiomics features based on T2 FLAIR MRI predict multiple glioma immunohistochemical features: A more precise and personalized gliomas management

Objective

To investigate the performance of high-order radiomics features and models based on T2-weighted fluid-attenuated inversion recovery (T2 FLAIR) in predicting the immunohistochemical biomarkers of glioma, in order to execute a non-invasive, more precise and personalized glioma disease management.

Methods

51 pathologically confirmed gliomas patients committed in our hospital from March 2015 to June 2018 were retrospective analysis, and Ki-67, vimentin, S-100 and CD34 immunohistochemical data were collected. The volumes of interest (VOIs) were manually sketched and the radiomics features were extracted. Feature reduction was performed by ANOVA+ Mann-Whiney, spearman correlation analysis, least absolute shrinkage and selection operator (LASSO) and Gradient descent algorithm (GBDT). SMOTE technique was used to solve the data bias between two groups. Comprehensive binary logistic regression models were established. Area under the ROC curves (AUC), sensitivity, specificity and accuracy were used to evaluate the predict performance of models. Models reliability were decided according to the standard net benefit of the decision curves.

Results

Four clusters of significant features were screened out and four predicting models were constructed. AUC of Ki-67, S-100, vimentin and CD34 models were 0.713, 0.923, 0.854 and 0.745, respectively. The sensitivities were 0.692, 0.893, 0.875 and 0.556, respectively. The specificities were: 0.667, 0.905, 0.722, and 0.875, with accuracy of 0.660, 0.898, 0.738, and 0.667, respectively. According to the decision curves, the Ki-67, S-100 and vimentin models had reference values.

Conclusion

The radiomics features based on T2 FLAIR can potentially predict the Ki-67, S-100, vimentin and CD34 expression. Radiomics model were expected to be a computer-intelligent, non-invasive, accurate and personalized management method for gliomas.

Pan-Cancer and Single-Cell Modeling of Genomic Alterations Through Gene Expression

Cancer is a disease often characterized by the presence of multiple genomic alterations, which trigger altered transcriptional patterns and gene expression, which in turn sustain the processes of tumorigenesis, tumor progression, and tumor maintenance. The links between genomic alterations and gene expression profiles can be utilized as the basis to build specific molecular tumorigenic relationships. In this study, we perform pan-cancer predictions of the presence of single somatic mutations and copy number variations using machine learning approaches on gene expression profiles. We show that gene expression can be used to predict genomic alterations in every tumor type, where some alterations are more predictable than others. We propose gene aggregation as a tool to improve the accuracy of alteration prediction models from gene expression profiles. Ultimately, we show how this principle can be beneficial in intrinsically noisy datasets, such as those based on single-cell sequencing.

Changing paradigms for targeted therapies against diffuse infiltrative gliomas: tackling a moving target

Introduction: Gliomas are highly heterogeneous primary brain tumors which result in a disproportionately high degree of morbidity and mortality despite their locoregional occurrence. Advances in the understanding of the biological makeup of these malignancies have yielded a number of potential tumor-driving pathways which have been identified as rational targets for therapy. However, early trials of agents that target these pathways have uniformly failed to yield improvement in outcomes in patients with malignant gliomas. Areas covered: This review provides an overview of the most common biological features of gliomas and the strategies to target the same; in addition, the current status of immunotherapy and biological therapies are outlined and the future directions to tackle the challenges of therapy for gliomas are examined. Expert opinion: The limitations of current treatments are attributed to the inability of most of these agents to cross the blood-brain barrier and to the intrinsic heterogeneity of the tumors that result in treatment resistance. The recent emergence of immune-mediated and biological therapies and of agents that target metabolic pathways in gliomas have provided strategies that may overcome tumor heterogeneity and ongoing trials of such agents are anticipated to yield improved outcomes.

A Multiplex Quantitative Reverse Transcription Polymerase Chain Reaction Assay for the Detection of KIAA1549-BRAF Fusion Transcripts in Formalin-Fixed Paraffin-Embedded Pilocytic Astrocytomas

BACKGROUND AND OBJECTIVE

Genomic duplications and fusion involving BRAF and KIAA1549 that create fusion proteins with constitutive B-RAF kinase activity are a hallmark of pilocytic astrocytomas (PAs). The detection of KIAA1549-BRAF fusion transcripts is of paramount importance to classify these tumors and to identify patients who could benefit from BRAF inhibitors. In a clinical setting, the available material for molecular analysis from these pediatric tumors is often limited to formalin-fixed paraffin-embedded (FFPE) tissue. The aim of the present study was to develop a new method to detect the three most frequent KIAA1549-BRAF fusion transcripts, 15-9, 16-11, and 16-9, where numbers refer to the exons fused together, using a FFPE-compatible multiplex quantitative reverse transcription polymerase chain reaction (qRT-PCR).

METHODS

We compared performance of the assay to a reference singleplex method on a collection of 46 FFPE PAs.

RESULTS

The results showed that both methods are comparable. The multiplex method had an overall 97% sensitivity and 100% specificity compared to the singleplex method, and agreement between the two techniques was almost perfect (Cohen's kappa: 0.97). There was no evidence of a significant difference between the qRT-PCR efficiencies of the multiplex technique and of the singleplex assay for all fusion transcripts and for GAPDH, the latter used as a reference gene. The multiplex method consumed four times less complementary DNA (cDNA), cost less, and required half the hands-on technical time.

CONCLUSION

The results show that it could be beneficial to implement the multiplex method in a clinical setting, where samples presenting low quantity of degraded RNA are not unusual.

von Willebrand Factor Gene Expression in Primary Lower Grade Glioma: Mutually Co-Occurring Mutations in von Willebrand Factor, ATRX, and TP53

BACKGROUND

Venous thromboembolism is a common complication in patients with glioma. The clotting factor von Willebrand factor (VWF) is a highly adhesive procoagulant molecule that mediates platelet adhesion to endothelial and subendothelial surfaces. In the current analysis, we examined The Cancer Genome Atlas (TCGA) data to assess the VWF gene in patients with lower grade gliomas.

METHODS

For newly diagnosed gliomas, we evaluated the association between VWF and overall survival in the Genomic Data Commons TCGA Lower Grade Glioma (LGG) dataset in TCGA. Simple statistics were calculated to identify patterns of mutual exclusivity or co-occurrence of VWF mutations. For each pair of query genes an odds ratio was calculated that indicates the likelihood that the mutations in the two genes are mutually exclusive or co-occurrent across the selected cases. To determine whether the identified relationship was significant for a gene pair, Fisher's exact test was performed.

RESULTS

Lower grade gliomas with less VWF gene expression had significantly better survival than those with more VWF gene expression (hazard ratio 0.64, 95% confidence interval 0.44 to 0.92, p=0.015 log rank test). When we analyzed the data with Cox regression, VWF expression had a significant effect on survival (p=0.02) that was unrelated to the effect of IDH1 expression (p=0.062), TP53 expression (p=0.135), independent of ATRX expression (p=0.021) and histology (astrocytoma versus oligoastrocytoma and oligodendroglioma, p=0.002). VWF mutations significantly co-occur with mutations in TP53 and ATRX (p<0.001).

CONCLUSION

The deleterious prognostic effect of VWF expression and its co-occurrent mutations with TP53 and ATRX in lower grade gliomas are not surprising, given VWF's role in other cancers. Therefore, VWF gene expression may be a clinically important risk marker in lower grade glioma.

The promising novel biomarkers and candidate small molecule drugs in lower-grade glioma: Evidence from bioinformatics analysis of high-throughput data

Overall survival of patients with low-grade glioma (LGG) has shown no significant improvement over the past 30 years, with survival averaging approximately 7 years. This study aimed to identify novel promising biomarkers of LGG and reveal its potential molecular mechanisms by integrated bioinformatics analysis. The microarray datasets of GSE68848 and GSE4290 were selected from GEO database for integrated analysis. In total, 293 overlapping differentially expressed genes (DEGs) were detected using the limma package. One hundred and eighty-eight nodes with 603 interactions were obtained from the establishment of protein-protein interaction (PPI) network. Functional and signaling pathway enriched were significantly correlated with the synapse and calcium signaling pathway, respectively. Module analysis revealed eight hub genes with high connectivity, which included CHRM1, DLG2, GABRD, GRIN1, HTR2A, KCNJ3, KCNJ9, and NUSAP1, and they were markedly correlated with patients' prognosis. The mining of the Gene Expression Profiling Interactive Analysis database and qPCR further confirmed the abnormal expression of these key genes with their prognostic value in LGG. We eventually predicted the 20 most vital small molecule drugs, which potentially reverse the carcinogenic state of LGG, as per the CMap (connectivity map) database and these DEGs, and MS-275 (enrichment score = -0.939) was considered as the most promising small molecule to treat LGG. In conclusion, our study provided eight reliable novel molecular biomarkers for diagnosis, prognosis prediction, and treatment targets for LGG. These conclusions will contribute to a better comprehension of molecular mechanisms fundamental to LGG occurrence and progression, and providing new insights for future development of genomic individualized treatment in LGG.

Integrative analysis of KIF4A, 9, 18A, and 23 and their clinical significance in low-grade glioma and glioblastoma

To determine the prognostic significance of kinesin superfamily gene (KIF) expression in patients with brain cancer, including low-grade glioma (LGG) and glioblastoma (GBM), we comprehensively analyzed KIFs in 515 LGG and 595 GBM patients. Among KIFs, KIF4A, 9, 18A, and 23 showed significant clinical implications in both LGG and GBM. The mRNA and protein expression levels of KIF4A, 9, 18A, and 23 were significantly increased in LGG and GBM compared with those in the normal control groups. The mRNA expression levels of KIF4A, 9, 18A, and 23 in LGG were significantly increased in the high-histologic-grade group compared with those with a low histologic grade. Genomic analysis showed that the percent of mRNA upregulation of KIF4A, 9, 18A, and 23 was higher than that of other gene alterations, including gene amplification, deep deletion, and missense mutation. In addition, LGG patients with KIF4A, 18A, and 23 gene alterations were significantly associated with a poor prognosis. In survival analysis, the group with high expression of KIF4A, 9, 18A, and 23 mRNA was significantly associated with a poor prognosis in both LGG and GBM patients. Gene Set Enrichment Analysis (GSEA) revealed that high mRNA expression of KIF4A, 18A, and 23 in LGG and GBM patients showed significant positive correlations with the cell cycle, E2F targets, G₂M checkpoint, Myc target, and mitotic spindle. By contrast, high mRNA expression of KIF9 in both LGG and GBM patients was significantly negatively correlated with the cell cycle, G₂M checkpoint, and mitotic spindle pathway. However, it was significantly positively correlated with EMT and angiogenesis. This study has extended our knowledge of KIF4A, 9, 18A, and 23 in LGG and GBM and shed light on their clinical relevance, which should help to improve the treatment and prognosis of LGG and GBM.

Identification of differentially expressed key genes between glioblastoma and low-grade glioma by bioinformatics analysis

Gliomas are a very diverse group of brain tumors that are most commonly primary tumor and difficult to cure in central nervous system. It’s necessary to distinguish low-grade tumors from high-grade tumors by understanding the molecular basis of different grades of glioma, which is an important step in defining new biomarkers and therapeutic strategies. We have chosen the gene expression profile GSE52009 from gene expression omnibus (GEO) database to detect important differential genes. GSE52009 contains 120 samples, including 60 WHO II samples and 24 WHO IV samples that were selected in our analysis. We used the GEO2R tool to pick out differently expressed genes (DEGs) between low-grade glioma and high-grade glioma, and then we used the database for annotation, visualization and integrated discovery to perform gene ontology analysis and Kyoto encyclopedia of gene and genome pathway analysis. Furthermore, we used the Cytoscape search tool for the retrieval of interacting genes with molecular complex detection plug-in applied to achieve the visualization of protein–protein interaction (PPI). We selected 15 hub genes with higher degrees of connectivity, including tissue inhibitors metalloproteinases-1 and serum amyloid A1; additionally, we used GSE53733 containing 70 glioblastoma samples to conduct Gene Set Enrichment Analysis. In conclusion, our bioinformatics analysis showed that DEGs and hub genes may be defined as new biomarkers for diagnosis and for guiding the therapeutic strategies of glioblastoma.

Brain Tumors of Glial Origin

Gliomas are a heterogeneous group of tumors with evolving classification based on genotype. Isocitrate dehydrogenase (IDH) mutation is an early event in the formation of some diffuse gliomas, and is the best understood mechanism of their epigenetic dysregulation. Glioblastoma may evolve from lower-grade lesions with IDH mutations, or arise independently from copy number changes in platelet-derived growth factor receptor alpha (PDGFRA) and phosphatase and tensin homolog (PTEN). Several molecular subtypes of glioblastoma arise from a common proneural precursor with a tendency toward transition to a mesenchymal subtype. Following oncogenic transformation, gliomas escape growth arrest through a distinct step of aberrant telomere reverse transcriptase (TERT) expression, or mutations in either alpha thalassemia/mental retardation syndrome (ATRX) or death-domain associated protein (DAXX) genes. Metabolic reprogramming allows gliomas to thrive in harsh microenvironments such as hypoxia, acidity, and nutrient depletion, which contribute to tumor initiation, maintenance, and treatment resistance.

Radiotherapy in the Management of Paediatric Low-Grade Gliomas

Paediatric low-grade (World Health Organization grade I-II) gliomas (LGGs) represent a spectrum of primary central nervous system tumours. Local tumour control is the cornerstone in the general management of childhood gliomas. Surgery is the primary treatment of choice in the majority. Non-surgical treatments are recommended for progressive or symptomatic inoperable disease. Although chemotherapy is increasingly used as first non-surgical treatment, radiotherapy remains standard as salvage treatment or as primary treatment in selected cases in which surrounding normal tissue can be optimally preserved. The role of targeted therapies is currently under investigation in clinical trials. Modern high-precision radiotherapy techniques, including proton therapy, have the potential to improve long-term toxicities. There is therefore an urgent need for prospective studies to compare the efficacy and safety of modern radiotherapy with systemic treatment in children with LGGs. New information on molecular genetic patterns in LGGs may also have an impact on the selection and sequencing of radiotherapy.

Significance of TERT and ATRX mutations in glioma

Mutations of telomerase reverse transcriptase (TERT) and the α thalassemia/mental retardation syndrome X-linked (ATRX) genes have been the subject of numerous studies on the classification and prognosis of glioma. However, the association between TERT and ATRX in World Health Organization (WHO) grade II to IV glioma remains unclear. The present study utilized Sanger sequencing and immunohistochemical methods to detect the expression of the TERT promoter region, ATRX mutations and proliferation marker protein Ki-67 (Ki-67) protein expression in 179 cases of glioma. The current study analyzed these variables and their association with clinicopathological characteristics to further basic research and provide a theoretical basis for the clinical diagnosis and treatment of this type of tumor (1). The results demonstrated that TERT promoter mutations were negatively associated with ATRX. Additionally, Ki-67 protein expression in TERT wild-type samples was higher compared with samples with ATRX deletion. Overall, the results demonstrated, for the first time to the best of the authors' knowledge, that TERT promoter mutations are negatively associated with ATRX expression in WHO grade II to IV gliomas. These findings provide a theoretical basis for further basic research and may improve clinical diagnosis and treatment of glioma in the future.

Pleomorphic xanthoastrocytomas of adults: MRI features, molecular markers, and clinical outcomes

Fifty adult patients with pathologically-confirmed pleomorphic xanthoastrocytomas (PXAs) were retrospectively analyzed. Adult PXAs appeared as a single lesion in 47 patients and multiple lesions in 3 patients. Temporal lobe was the most common location (17/50). Twenty-two cases were superficial with obvious meningeal contact and 9 were closely adjacent to lateral ventricles. Three imaging patterns were differentiated, including a predominantly solid mass with or without cystic changes (n = 33), a predominantly cystic mass with an obvious mural nodule (n = 14), and a predominantly cystic mass with an uneven wall thickness (n = 3). The mean tumoral apparent diffusion coefficient (ADC) was 0.83 ± 0.17 × 10⁻³ mm²/s, and the mean ADC ratio was 1.02 ± 0.22. The V-raf murine sarcoma viral oncogenes homolog B1 (BRAF)^V600E mutation was found in 12 of 29 patients. In 36 patients with isocitrate dehydrogenases 1 and 2 (IDH1/2) data, only one had IDH1 mutation and no patient had IDH2 mutation. Anaplastic features were common (24/50) and significantly associated with high rates of recurrence or progression (P < 0.001). In conclusion, this study expands our knowledge on the MRI features, molecular markers, and clinical outcomes of adult PXAs, to some extent different from pediatric PXAs.

A comparative analysis of clinicopathological features and survival among early adolescents/young adults and children with low-grade glioma: a report from the Children's Oncology Group

BACKGROUND

For several types of cancer, biological differences and outcome disparities have been documented in adolescents/young adults (AYAs, 15-39 years old) versus children. This study compared clinicopathological features and survival between younger AYAs and children with low-grade glioma (LGG), a common brain tumor among AYAs.

METHODS

This was a secondary analysis of Children's Oncology Group legacy study CCG-9891/POG-9130, which enrolled participants 0-21 years of age with newly-diagnosed LGG treated with surgery alone. For analysis, participants were categorized as children (0-14 years old) or early AYAs (eAYAs, 15-21 years old) and compared on demographics, clinical presentation, tumor characteristics, surgical outcomes, progression-free survival (PFS) and overall survival (OS).

RESULTS

Among 468 children and 50 eAYAs, more eAYAs presented with seizures (34.0% vs. 19.2%; p = 0.015), without other significant differences in clinicopathological features. 5-year PFS rates for children and eAYA were 80.2% (95% confidence interval [95% CI], 76.1-83.7) and 83.0% (95% CI 68.8-91.1), respectively; 5-year OS rates were 97.3% (95% CI 95.2-98.5) and 95.4% (95% CI 82.7-98.8), respectively. Multivariable analysis including all participants showed presence of residual tumor to be an independent predictor of PFS (< 1.5 cm³, hazard ratio [HR] 5.93 [95% CI 3.45-10.18]) and (≥ 1.5 cm³, HR 8.38 [95% CI 4.75-14.79]) (p < 0.001), while midline-chiasmatic location (HR 9.69 [95% CI 3.05-30.75], p < 0.001) and non-pilocytic astrocytoma histology (HR 6.77 [95% CI 2.35-19.49], p < 0.001) were independent predictors of OS.

CONCLUSION

Unlike several other cancers, LGG has similar presenting features and survival for both eAYAs and children. This support continuing a unified treatment approach and enrollment of eAYAs in pediatric clinical trials for LGGs.

Increased expression of von Willebrand factor gene is associated with poorer survival in primary lower grade glioma

Background

Venous thromboembolism is a common complication in patients with glioma. The clotting factor von Willebrand factor (VWF) is a highly adhesive procoagulant molecule that mediates platelet adhesion to endothelial and subendothelial surfaces. In the current analysis, we examined The Cancer Genome Atlas (TCGA) data to assess the effect of VWF gene expression on prognosis in patients with lower grade gliomas (LGGs).

Methods

For newly diagnosed gliomas, we evaluated the association between and overall survival in the genomic data commons TCGA LGG dataset in TCGA. Survival data of the glioma subgroup were extracted for analysis and generation of Kaplan-Meier curves for overall survival.

Results

Lower grade gliomas with less VWF gene expression had significantly better survival than those with more VWF gene expression (hazard ratio 0.64, 95% confidence interval 0.44-0.92, P 0.015 log rank test). The effect of VWF gene expression on survival was even more evident when the sample was analyzed as three groups (P = 0.00019). IDH1, TP53, and ATRX mutations are present in 40% or more adult LGGs.

Conclusion

The deleterious prognostic effect of VWF expression in LGGs is not surprising, given its role in other cancers. Therefore, VWF gene expression may be a clinically important risk marker in LGG.

Paediatric gliomas: diagnosis, molecular biology and management

Paediatric gliomas represent the most common brain tumour in children. Early diagnosis and treatment greatly improve survival. Histological grade is the most significant classification system affecting treatment planning and prognosis. Paediatric gliomas depend on pathways and genes responsible for mitotic activity and cell proliferation as well as angiogenesis (MAPK, VEGF, EFGR pathways). Symptoms such as focal neurologic deficit or seizures can facilitate diagnosis, but they are not always present and therefore diagnosis is occasionally delayed. Imaging has adequate diagnostic accuracy (surpassing 90%), and novel imaging techniques such as MR spectroscopy and PET increase only slightly this percentage. Low grade gliomas (LGG) can be approached conservatively but most authors suggest surgical excision. High grade gliomas (HGG) are always operated with exception of specific contradictions including butterfly or extensive dominant hemisphere gliomas. Surgical excision is universally followed by radiotherapy and chemotherapy, which slightly increase survival. Inoperable cases can be managed with or without radiosurgery depending on location and size, with adjunctive use of radiotherapy and chemotherapy. Surgical excision must be aggressive and gross total resection (GTR) should be attempted, if possible, since it can triple survival. Radiosurgery is effective on smaller tumours of <2 cm2. Surgical excision is always the treatment of choice, but glioma recurrences, and residual tumours in non-critical locations are candidates for radiosurgery especially if tumour volume is low. Management of recurrences includes surgery, radiosurgery and chemoradiotherapy and it should be individualized according to location and size. In combination with molecular targeted therapeutic schemes, glioma management will be immensely improved in the next years.

Incorporating Advances in Molecular Pathology Into Brain Tumor Diagnostics

Recent advances in molecular pathology have reshaped the practice of brain tumor diagnostics. The classification of gliomas has been restructured with the discovery of isocitrate dehydrogenase (IDH) 1/2 mutations in the vast majority of lower grade infiltrating gliomas and secondary glioblastomas (GBM), with IDH-mutant astrocytomas further characterized by TP53 and ATRX mutations. Whole-arm 1p/19q codeletion in conjunction with IDH mutations now define oligodendrogliomas, which are also enriched for CIC, FUBP1, PI3K, NOTCH1, and TERT-p mutations. IDH-wild-type (wt) infiltrating astrocytomas are mostly primary GBMs and are characterized by EGFR, PTEN, TP53, NF1, RB1, PDGFRA, and CDKN2A/B alterations, TERT-p mutations, and characteristic copy number alterations including gains of chromosome 7 and losses of 10. Other clinically and genetically distinct infiltrating astrocytomas include the aggressive H3K27M-mutant midline gliomas, and smaller subsets that occur in the setting of NF1 or have BRAF V600E mutations. Low-grade pediatric gliomas are both genetically and biologically distinct from their adult counterparts and often harbor a single driver event often involving BRAF, FGFR1, or MYB/MYBL1 genes. Large scale genomic and epigenomic analyses have identified distinct subgroups of ependymomas tightly linked to tumor location and clinical behavior. The diagnosis of embryonal neoplasms also integrates molecular testing: (I) 4 molecularly defined, biologically distinct subtypes of medulloblastomas are now recognized; (II) 3 histologic entities have now been reclassified under a diagnosis of "embryonal tumor with multilayered rosettes (ETMR), C19MC-altered"; and (III) atypical teratoid/rhabdoid tumors (AT/RT) now require SMARCB1 (INI1) or SMARCA4 (BRG1) alterations for their diagnosis. We discuss the practical use of contemporary biomarkers for an integrative diagnosis of central nervous system neoplasia.

Overexpression of FZD7 promotes glioma cell proliferation by upregulating TAZ

Gliomas are the most prevalent type of primary brain tumors in adults, accounting for more than 40% of neoplasm in the central nervous system. Frizzled-7 (FZD7) is a seven-pass trans-membrane Wnt receptor that plays a critical role in the development of various tumors. In this study, we detected high-level FZD7 expression in glioma and its overexpression was associated with advanced tumor stage. In vitro functional assays showed that forced overexpression of FZD7 promoted proliferation of gliomas cells, whereas knockdown of endogenous FZD7 significantly suppressed proliferation ability of these cells. In a xenograft assay, FZD7 was also found to promote the growth of glioma cells. We further found that FZD7 could activate transcriptional coactivator with PDZ-binding motif (TAZ), and TAZ was required for FZD7 to promote cell proliferation in glioma. Furthermore, the univariate analysis of survival shows that glioma patients with high FZD7 expression have a shorter survival. In conclusion, our findings demonstrate that FZD7 may promote glioma cell proliferation via upregulation of TAZ.