Beyond IDH-Mutation: Emerging Molecular Diagnostic and Prognostic Features in Adult Diffuse Gliomas

Biomarkers in Cancer Detection, Diagnosis, and Prognosis

Biomarkers are vital in healthcare as they provide valuable insights into disease diagnosis, prognosis, treatment response, and personalized medicine. They serve as objective indicators, enabling early detection and intervention, leading to improved patient outcomes and reduced costs. Biomarkers also guide treatment decisions by predicting disease outcomes and facilitating individualized treatment plans. They play a role in monitoring disease progression, adjusting treatments, and detecting early signs of recurrence. Furthermore, biomarkers enhance drug development and clinical trials by identifying suitable patients and accelerating the approval process. In this review paper, we described a variety of biomarkers applicable for cancer detection and diagnosis, such as imaging-based diagnosis (CT, SPECT, MRI, and PET), blood-based biomarkers (proteins, genes, mRNA, and peptides), cell imaging-based diagnosis (needle biopsy and CTC), tissue imaging-based diagnosis (IHC), and genetic-based biomarkers (RNAseq, scRNAseq, and spatial transcriptomics).

Vascular differences between IDH-wildtype glioblastoma and astrocytoma IDH-mutant grade 4 at imaging and transcriptomic levels

Global agreement in central nervous system (CNS) tumor classification is essential for predicting patient prognosis and determining the correct course of treatment, as well as for stratifying patients for clinical trials at international level. The last update by the World Health Organization of CNS tumor classification and grading in 2021 considered, for the first time, IDH-wildtype glioblastoma and astrocytoma IDH-mutant grade 4 as different tumors. Mutations in the genes isocitrate dehydrogenase (IDH) 1 and 2 occur early and, importantly, contribute to gliomagenesis. IDH mutation produces a metabolic reprogramming of tumor cells, thus affecting the processes of hypoxia and vascularity, resulting in a clear advantage for those patients who present with IDH-mutated astrocytomas. Despite the clinical relevance of IDH mutation, current protocols do not include full sequencing for every patient. Alternative biomarkers could be useful and complementary to obtain a more reliable classification. In this sense, magnetic resonance imaging (MRI)-perfusion biomarkers, such as relative cerebral blood volume and flow, could be useful from the moment of presurgery, without incurring additional financial costs or requiring extra effort. The main purpose of this work is to analyze the vascular and hemodynamic differences between IDH-wildtype glioblastoma and IDH-mutant astrocytoma. To achieve this, we evaluate and validate the association between dynamic susceptibility contrast-MRI perfusion biomarkers and IDH mutation status. In addition, to gain a deeper understanding of the vascular differences in astrocytomas depending on the IDH mutation, we analyze the transcriptomic bases of the vascular differences.

D-2-hydroxyglutarate regulates human brain vascular endothelial cell proliferation and barrier function

Gain-of-function mutations in isocitrate dehydrogenase (IDH) genes result in excessive production of (D)-2-hydroxyglutarate (D-2HG) which intrinsically modifies tumor cell epigenetics and impacts surrounding noncancerous cells through nonepigenetic pathways. However, whether D-2HG has a paracrine effect on endothelial cells in the tumor microenvironment needs further clarification. We quantified microvessel density by immunohistochemistry using tissue sections from 60 high-grade astrocytic gliomas with or without IDH mutation. Microvessel density was found to be reduced in tumors carrying an IDH mutation. Ex vivo experiments showed that D-2HG inhibited endothelial cell migration, wound healing, and tube formation by suppressing cell proliferation but not viability, possibly through reduced activation of the mTOR/STAT3 pathway. Further, D-2HG reduced fluorescent dextran permeability and decreased paracellular T-cell transendothelial migration by augmenting expression of junctional proteins thereby collectively increasing endothelial barrier function. These results indicate that D-2HG may influence the tumor vascular microenvironment by reducing the intratumoral vasculature density and by inhibiting the transport of metabolites and extravasation of circulating cells into the astrocytoma microenvironment. These observations provide a rationale for combining IDH inhibition with antitumor immunological/angiogenic approaches and suggest a molecular basis for resistance to antiangiogenic drugs in patients whose tumors express a mutant IDH allele.

GradWise: A Novel Application of a Rank-Based Weighted Hybrid Filter and Embedded Feature Selection Method for Glioma Grading with Clinical and Molecular Characteristics

Glioma grading plays a pivotal role in guiding treatment decisions, predicting patient outcomes, facilitating clinical trial participation and research, and tailoring treatment strategies. Current glioma grading in the clinic is based on tissue acquired at the time of resection, with tumor aggressiveness assessed from tumor morphology and molecular features. The increased emphasis on molecular characteristics as a guide for management and prognosis estimation underscores is driven by the need for accurate and standardized grading systems that integrate molecular and clinical information in the grading process and carry the expectation of the exposure of molecular markers that go beyond prognosis to increase understanding of tumor biology as a means of identifying druggable targets. In this study, we introduce a novel application (GradWise) that combines rank-based weighted hybrid filter (i.e., mRMR) and embedded (i.e., LASSO) feature selection methods to enhance the performance of feature selection and machine learning models for glioma grading using both clinical and molecular predictors. We utilized publicly available TCGA from the UCI ML Repository and CGGA datasets to identify the most effective scheme that allows for the selection of the minimum number of features with their names. Two popular feature selection methods with a rank-based weighting procedure were employed to conduct comprehensive experiments with the five supervised models. The computational results demonstrate that our proposed method achieves an accuracy rate of 87.007% with 13 features and an accuracy rate of 80.412% with five features on the TCGA and CGGA datasets, respectively. We also obtained four shared biomarkers for the glioma grading that emerged in both datasets and can be employed with transferable value to other datasets and data-based outcome analyses. These findings are a significant step toward highlighting the effectiveness of our approach by offering pioneering results with novel markers with prospects for understanding and targeting the biologic mechanisms of glioma progression to improve patient outcomes.

MUC17 mutations and methylation are associated with poor prognosis in adult-type diffuse glioma patients

Diffuse gliomas are tumors that arise from glial or glial progenitor cells. They are currently classified as astrocytoma isocitrate dehydrogenase (IDH)-mutant or oligodendroglioma IDH-mutant, and 1p/19q-codeleted, both slower-growing tumors, or glioblastoma (GBM), a more aggressive tumor. Despite advances in the diagnosis and treatment of gliomas, the median survival time after diagnosis of GBM remains low, approximately 15 months, with a 5-year overall survival rate of only 6.8%. Therefore, new biomarkers that could support the earlier diagnosis and prognosis of these tumors would be of great value. MUC17, a membrane-bound mucin, has been identified as a potential biomarker for several tumors. However, the role of this mucin in adult gliomas has not yet been explored. Here, we show for the first time, in a retrospective study and by in silico analysis that MUC17 is one of the relevant mutant genes in adult gliomas. Moreover, that an increase in MUC17 methylation correlates with an increase in glioma malignancy grade. Patients with MUC17 mutations had a poorer prognosis than their wild-type counterparts in both GBM and non-GBM glioma cohorts. We also analyzed mutational profiles that correlated strongly with poor survival. Therefore, in this study, we present a new potential biomarker for further investigation, especially for the prognosis of adult diffuse gliomas.

The role of immune subtyping in glioma mRNA vaccine development

Studies on the development of mRNA vaccines for central nervous system tumors have used gene expression profiles, clinical data and RNA sequencing from sources such as The Cancer Genome Atlas and Chinese Glioma Genome Atlas to identify effective antigens. These studies revealed several immune subtypes of glioma, each one linked to unique prognoses and genetic/immune-modulatory changes. Potential antigens include ARPC1B, BRCA2, COL6A1, ITGB3, IDH1, LILRB2, TP53 and KDR, among others. Patients with immune-active and immune-suppressive phenotypes were found to respond better to mRNA vaccines. While these findings indicate the potential of mRNA vaccines in cancer therapy, further research is required to optimize administration and adjuvant selection, and precisely identify target antigens.

Biological functions of the Olig gene family in brain cancer and therapeutic targeting

The Olig genes encode members of the basic helix-loop-helix (bHLH) family of transcription factors. Olig1, Olig2, and Olig3 are expressed in both the developing and mature central nervous system (CNS) and regulate cellular specification and differentiation. Over the past decade extensive studies have established functional roles of Olig1 and Olig2 in development as well as in cancer. Olig2 overexpression drives glioma proliferation and resistance to radiation and chemotherapy. In this review, we summarize the biological functions of the Olig family in brain cancer and how targeting Olig family genes may have therapeutic benefit.

Gemistocytic Differentiation in Isocitrate Dehydrogenase Mutant Astrocytomas: A Histopathological and Survival Analysis

Gemistocytic differentiation is a rare histological feature seen in IDH mutant Astrocytomas. The 2021 World Health Organization (WHO) retains the diagnosis of IDH mutant Astrocytoma with its classical histology and tumors with the rare histological pattern of gemistocytic differentiation. Gemistocytic differentiation has historically been associated with a worse prognosis and shorter survival, and this prognostic difference has not been investigated in detail in our population. A population-based retrospective study included 56 patients with IDH mutant Astrocytoma with Gemistocytic differentiation and IDH mutant Astrocytoma diagnosed between 2010 and 2018 in our hospital. Demographic, histopathological, and clinical parameters were compared between the two groups. Gemistocyte percentage, perivascular lymphoid infiltrates, and Ki-67 proliferation index were also analyzed. A Kaplan-Meier analysis was done to analyze any prognostic difference in the overall survival time between the two groups. Patients with an IDH mutant Astrocytoma having gemistocytic differentiation had an average survival period of 2 years, while patients diagnosed with an IDH mutant Astrocytoma had an average survival time of approximately 6 years. There was a statistically significant decrease in survival time (p = 0.005) for patients with tumors with gemistocytic differentiation. The percentage of gemistocytes and the presence of perivascular lymphoid aggregates did not correlate with survival time (p = 0.303 and 0.602, respectively). Tumors with gemistocytic morphology had a higher mean Ki-67 proliferation index (4.4%) than IDH mutant Astrocytoma (2.0%, p = 0.005). Our data suggest that IDH mutant Astrocytoma with Gemistocytic differentiation is an aggressive variant of IDH mutant Astrocytoma associated with a shorter survival time and an overall worse prognosis. This data might be helpful to clinicians in the future management of IDH mutant Astrocytoma with Gesmistocytic differentiation as an aggressive tumor.

Rational Computational Approaches in Drug Discovery: Potential Inhibitors for Allosteric Regulation of Mutant Isocitrate Dehydrogenase-1 Enzyme in Cancers

Mutations in homodimeric isocitrate dehydrogenase (IDH) enzymes at specific arginine residues result in the abnormal activity to overproduce D-2 hydroxyglutarate (D-2HG), which is often projected as solid oncometabolite in cancers and other disorders. As a result, depicting the potential inhibitor for D-2HG formation in mutant IDH enzymes is a challenging task in cancer research. The mutation in the cytosolic IDH1 enzyme at R132H, especially, may be associated with higher frequency of all types of cancers. So, the present work specifically focuses on the design and screening of allosteric site binders to the cytosolic mutant IDH1 enzyme. The 62 reported drug molecules were screened along with biological activity to identify the small molecular inhibitors using computer-aided drug design strategies. The designed molecules proposed in this work show better binding affinity, biological activity, bioavailability, and potency toward the inhibition of D-2HG formation compare to the reported drugs in the in silico approach.

The prognostic significance of tumor-associated neutrophils and circulating neutrophils in glioblastoma (WHO CNS5 classification)

BACKGROUND

Tumor-associated neutrophils (TANs) in the tumor microenvironment are prognostic biomarkers in many malignancies. However, it is unclear whether TANs can serve as a prognostic marker for clinical outcomes in patients with glioblastoma (GBM), as classified according to World Health Organization Classification of Tumors of the Central Nervous System, fifth edition (CNS5). In the present study, we analyzed correlations of TANs and peripheral blood neutrophils prior to radiotherapy with overall survival (OS) in GBM (CNS5).

METHODS

RNA-seq expression profiles of patients with newly diagnosed GBM (CNS5) were extracted from The Cancer Genome Atlas (TCGA), and The Chinese Glioma Genome Atlas (CGGA). TAN infiltration was inferred using CIBERSORTx algorithm. Neutrophil counts prior to radiotherapy in newly diagnosed GBM (CNS5) were obtained from the First Affiliated Hospital of Fujian Medical University. The prognostic value of TANs and peripheral blood neutrophils before radiotherapy was investigated using Kaplan-Meier analysis and Cox proportional hazards models. The robustness of these findings was evaluated by sensitivity analysis, and E values were calculated.

RESULTS

A total of 146 and 173 individuals with GBM (CNS5) were identified from the TCGA and CGGA cohorts, respectively. High infiltration of TANs was of prognostic of poor OS in TCGA (HR = 1.621, 95% CI: 1.004-2.619) and CGGA (HR = 1.546, 95% CI: 1.029-2.323). Levels of peripheral blood neutrophils before radiotherapy (HR = 2.073, 95% CI: 1.077-3.990) were independently associated with poor prognosis. Sensitivity analysis determined that the E-value of high TANs infiltration was 2.140 and 2.465 in the TCGA and CGGA cohorts.

CONCLUSIONS

TANs and peripheral blood neutrophil levels before radiotherapy are prognostic of poor outcomes in GBM (CNS5).

Proton radiotherapy in the treatment of IDH-mutant diffuse gliomas: an early experience from shanghai proton and heavy ion center

PURPOSE

According to the presence or absence of isocitrate dehydrogenase (IDH) mutation, the 2021 WHO classification system bisected diffuse gliomas into IDH-mutant tumors and IDH-wildtype tumors. This study was aimed to evaluate the outcomes of proton radiotherapy treating IDH-mutant diffuse gliomas.

PATIENTS AND METHODS

Between May 2015 and May 2022, a total of 52 consecutive patients with IDH-mutant diffuse gliomas were treated at Shanghai Proton and Heavy Ion Center. Tumor histologies were 33 cases of astrocytoma and 19 cases of oligodendroglioma. Tumor classified by WHO grade 2, 3 and 4 were 22, 25, and 5 cases, respectively. All 22 patients with WHO grade 2 tumors and one patient with brain stem WHO grade 4 tumor were irradiated with 54GyE. The other 29 patients with WHO grade 3 and 4 tumors were irradiated with 60GyE. Temozolomide was recommended to all patients, and was eventually conducted in 50 patients.

RESULTS

The median follow-up time was 21.7 months. The 12/24-month progression-free survival (PFS) and overall survival (OS) rates for the entire cohort were 97.6%/78.4% and 100%/91.0% group. Examined by both univariate and multivariate analysis, WHO grade of tumor were of the most significant impact for both PFS and OS. No severe acute toxicity (grade 3 or above) was found. In terms of late toxicity, grade 3 radio-necrosis was developed in one case of oligodendroglioma, WHO grade 3.

CONCLUSION

Proton radiotherapy produced a favorable outcome with acceptable adverse-effects in patients with IDH-mutant diffuse gliomas.

Hierarchical Voting-Based Feature Selection and Ensemble Learning Model Scheme for Glioma Grading with Clinical and Molecular Characteristics

Determining the aggressiveness of gliomas, termed grading, is a critical step toward treatment optimization to increase the survival rate and decrease treatment toxicity for patients. Streamlined grading using molecular information has the potential to facilitate decision making in the clinic and aid in treatment planning. In recent years, molecular markers have increasingly gained importance in the classification of tumors. In this study, we propose a novel hierarchical voting-based methodology for improving the performance results of the feature selection stage and machine learning models for glioma grading with clinical and molecular predictors. To identify the best scheme for the given soft-voting-based ensemble learning model selections, we utilized publicly available TCGA and CGGA datasets and employed four dimensionality reduction methods to carry out a voting-based ensemble feature selection and five supervised models, with a total of sixteen combination sets. We also compared our proposed feature selection method with the LASSO feature selection method in isolation. The computational results indicate that the proposed method achieves 87.606% and 79.668% accuracy rates on TCGA and CGGA datasets, respectively, outperforming the LASSO feature selection method.

Chromosomal instability in adult-type diffuse gliomas

Chromosomal instability (CIN) is a fundamental property of cancer and a key underlying mechanism of tumorigenesis and malignant progression, and has been documented in a wide variety of cancers, including colorectal carcinoma with mutations in genes such as APC. Recent reports have demonstrated that CIN, driven in part by mutations in genes maintaining overall genomic stability, is found in subsets of adult-type diffusely infiltrating gliomas of all histologic and molecular grades, with resulting elevated overall copy number burden, chromothripsis, and poor clinical outcome. Still, relatively few studies have examined the effect of this process, due in part to the difficulty of routinely measuring CIN clinically. Herein, we review the underlying mechanisms of CIN, the relationship between chromosomal instability and malignancy, the prognostic significance and treatment potential in various cancers, systemic disease, and more specifically, in diffusely infiltrating glioma subtypes. While still in the early stages of discovery compared to other solid tumor types in which CIN is a known driver of malignancy, the presence of CIN as an early factor in gliomas may in part explain the ability of these tumors to develop resistance to standard therapy, while also providing a potential molecular target for future therapies.

Identification of a novel cuproptosis-related gene signature and integrative analyses in patients with lower-grade gliomas

Background

Cuproptosis is a newly discovered unique non-apoptotic programmed cell death distinguished from known death mechanisms like ferroptosis, pyroptosis, and necroptosis. However, the prognostic value of cuproptosis and the correlation between cuproptosis and the tumor microenvironment (TME) in lower-grade gliomas (LGGs) remain unknown.

Methods

In this study, we systematically investigated the genetic and transcriptional variation, prognostic value, and expression patterns of cuproptosis-related genes (CRGs). The CRG score was applied to quantify the cuproptosis subtypes. We then evaluated their values in the TME, prognostic prediction, and therapeutic responses in LGG. Lastly, we collected five paired LGG and matched normal adjacent tissue samples from Sun Yat-sen University Cancer Center (SYSUCC) to verify the expression of signature genes by quantitative real-time PCR (qRT-PCR) and Western blotting (WB).

Results

Two distinct cuproptosis-related clusters were identified using consensus unsupervised clustering analysis. The correlation between multilayer CRG alterations with clinical characteristics, prognosis, and TME cell infiltration were observed. Then, a well-performed cuproptosis-related risk model (CRG score) was developed to predict LGG patients' prognosis, which was evaluated and validated in two external cohorts. We classified patients into high- and low-risk groups according to the CRG score and found that patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group (P<0.001). A high CRG score implies higher TME scores, more significant TME cell infiltration, and increased mutation burden. Meanwhile, the CRG score was significantly correlated with the cancer stem cell index, chemoradiotherapy sensitivity-related genes and immune checkpoint genes, and chemotherapeutic sensitivity, indicating the association with CRGs and treatment responses. Univariate and multivariate Cox regression analyses revealed that the CRG score was an independent prognostic predictor for LGG patients. Subsequently, a highly accurate predictive model was established for facilitating the clinical application of the CRG score, showing good predictive ability and calibration. Additionally, crucial CRGs were further validated by qRT-PCR and WB.

Conclusion

Collectively, we demonstrated a comprehensive overview of CRG profiles in LGG and established a novel risk model for LGG patients' therapy status and prognosis. Our findings highlight the potential clinical implications of CRGs, suggesting that cuproptosis may be the potential therapeutic target for patients with LGG.

Nomograms for prognostic risk assessment in glioblastoma multiforme: Applications and limitations

Glioblastoma multiforme (GBM) is the most common and aggressive form of brain cancer. Prognosis evaluation is of great significance in guiding individualized treatment and monitoring of GBM. By integrating different prognostic variables, nomograms simplify the statistical risk prediction model into numerical estimates for death or recurrence, and are hence widely applied in prognosis prediction. In the past two decades, the application of high-throughput profiling technology and the establishment of TCGA database and other public data deposits have provided opportunities to identify cancer-related molecules and prognostic biomarkers. As a result, both molecular features and clinical characteristics of cancer have been reported to be the key factors in nomogram model construction. This article comprehensively reviewed 35 studies of GBM nomograms, analyzed the present situation of GBM nomograms, and discussed the role and significance of nomograms in personalized risk assessment and clinical treatment decision-making. To facilitate the application of nomograms in the prognostic prediction of GBM patients, a website has been established for the online access of nomograms based on the studies of this review, which is called Consensus Nomogram Spectrum for Glioblastoma (CNSgbm) and is accessible through https://bioinfo.henu.edu.cn/nom/NomList.jsp.

Global DNA methylation profiling reveals chromosomal instability in IDH-mutant astrocytomas

Diffusely infiltrating gliomas are among the most common central nervous system tumors in adults. Over the past decade, the subcategorization of these tumors has changed to include both traditional histologic features and more recently identified molecular factors. However, one molecular feature that has yet to be integrated is the presence/absence of chromosomal instability (CIN). Herein, we use global methylation profiling to evaluate a reference cohort of IDH-mutant astrocytomas with and without prior evidence of CIN (n = 42), and apply the resulting methylation-based characteristics to a larger test cohort of publicly-available IDH-mutant astrocytomas (n = 245). We demonstrate that IDH-mutant astrocytomas with evidence of CIN cluster separately from their chromosomally-stable counterparts. CIN cases were associated with higher initial histologic grade, altered expression patterns of genes related to CIN in other cancers, elevated initial total copy number burden, and significantly worse progression-free and overall survival. In addition, in a grade-for-grade analysis, patients with CIN-positive WHO grade 2 and 3 tumors had significantly worse survival. These results suggest that global methylation profiling can be used to discriminate between chromosomally stable and unstable IDH-mutant astrocytomas, and may therefore provide a reliable and cost-effective method for identifying gliomas with chromosomal instability and resultant poor clinical outcome.

Radiogenomic Predictors of Recurrence in Glioblastoma—A Systematic Review

Glioblastoma, as the most aggressive brain tumor, is associated with a poor prognosis and outcome. To optimize prognosis and clinical therapy decisions, there is an urgent need to stratify patients with increased risk for recurrent tumors and low therapeutic success to optimize individual treatment. Radiogenomics establishes a link between radiological and pathological information. This review provides a state-of-the-art picture illustrating the latest developments in the use of radiogenomic markers regarding prognosis and their potential for monitoring recurrence. Databases PubMed, Google Scholar, and Cochrane Library were searched. Inclusion criteria were defined as diagnosis of glioblastoma with histopathological and radiological follow-up. Out of 321 reviewed articles, 43 articles met these inclusion criteria. Included studies were analyzed for the frequency of radiological and molecular tumor markers whereby radiogenomic associations were analyzed. Six main associations were described: radiogenomic prognosis, MGMT status, IDH, EGFR status, molecular subgroups, and tumor location. Prospective studies analyzing prognostic features of glioblastoma together with radiological features are lacking. By reviewing the progress in the development of radiogenomic markers, we provide insights into the potential efficacy of such an approach for clinical routine use eventually enabling early identification of glioblastoma recurrence and therefore supporting a further personalized monitoring and treatment strategy.

WHO Grade Loses Its Prognostic Value in Molecularly Defined Diffuse Lower-Grade Gliomas

BACKGROUND

While molecular insights to diffuse lower-grade glioma (dLGG) have improved the basis for prognostication, most established clinical prognostic factors come from the pre-molecular era. For instance, WHO grade as a predictor for survival in dLGG with isocitrate dehydrogenase (IDH) mutation has recently been questioned. We studied the prognostic role of WHO grade in molecularly defined subgroups and evaluated earlier used prognostic factors in the current molecular setting.

MATERIAL AND METHODS

A total of 253 adults with morphological dLGG, consecutively included between 2007 and 2018, were assessed. IDH mutations, codeletion of chromosomal arms 1p/19q, and cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) deletions were analyzed.

RESULTS

There was no survival benefit for patients with WHO grade 2 over grade 3 IDH-mut dLGG after exclusion of tumors with known CDKN2A/B homozygous deletion (n=157) (log-rank p=0.97). This was true also after stratification for oncological postoperative treatment and when astrocytomas and oligodendrogliomas were analyzed separately. In IDH-mut astrocytomas, residual tumor volume after surgery was an independent prognostic factor for survival (HR 1.02; 95% CI 1.01-1.03; p=0.003), but not in oligodendrogliomas (HR 1.02; 95% CI 1.00-1.03; p=0.15). Preoperative tumor size was an independent predictor in both astrocytomas (HR 1.03; 95% CI 1.00-1.05; p=0.02) and oligodendrogliomas (HR 1.05; 95% CI 1.01-1.09; p=0.01). Age was not a significant prognostic factor in multivariable analyses (astrocytomas p=0.64, oligodendrogliomas p=0.08).

CONCLUSION

Our findings suggest that WHO grade is not a robust prognostic factor in molecularly well-defined dLGG. Preoperative tumor size remained a prognostic factor in both IDH-mut astrocytomas and oligodendrogliomas in our cohort, whereas residual tumor volume predicted prognosis in IDH-mut astrocytomas only. The age cutoffs for determining high risk in patients with IDH-mut dLGG from the pre-molecular era are not supported by our results.

Integrative Analyses and Verification of the Expression and Prognostic Significance for RCN1 in Glioblastoma Multiforme

Glioblastoma multiform is a lethal primary brain tumor derived from astrocytic, with a poor prognosis in adults. Reticulocalbin-1 (RCN1) is a calcium-binding protein, dysregulation of which contributes to tumorigenesis and progression in various cancers. The present study aimed to identify the impact of RCN1 on the outcomes of patients with Glioblastoma multiforme (GBM). The study applied two public databases to require RNA sequencing data of Glioblastoma multiform samples with clinical data for the construction of a training set and a validation set, respectively. We used bioinformatic analyses to determine that RCN1 could be an independent factor for the overall survival of Glioblastoma multiform patients. In the training set, the study constructed a predictive prognostic model based on the combination of RCN1 with various clinical parameters for overall survival at 0.5-, 1.0-, and 1.5-years, as well as developed a nomogram, which was further validated by validation set. Pathways analyses indicated that RCN1 was involved in KEAS and MYC pathways and apoptosis. In vitro experiments indicated that RCN1 promoted cell invasion of Glioblastoma multiform cells. These results illustrated the prognostic role of RCN1 for overall survival in Glioblastoma multiform patients, indicated the promotion of RCN1 in cell invasion, and suggested the probability of RCN1 as a potential targeted molecule for treatment in Glioblastoma multiform.

Downregulation of STOX1 is a novel prognostic biomarker for glioma patients

Storkhead box 1 (STOX1) is a winged helix transcription factor structurally and functionally related to the forkhead family of transcription factors. Recent studies have highlighted its role in the central nervous system and revealed hints in the development of glioma. However, the expression profiles of STOX1, its association with clinicopathological characteristics, and potential functions in glioma remain unknown. In this study, we analyzed three publicly available datasets including CGGA, TCGA, and Rembrandt and revealed a grade-dependent reduction in STOX1 expression in glioma (P < 0.001). Chi-square test demonstrated that low STOX1 expression was significantly associated with older age at initial diagnosis (P < 0.001), less IDH1 mutation (P < 0.001), and advanced WHO grade (P < 0.001). Moreover, multivariate Cox regression analysis showed that STOX1 expression may serve as a novel independent prognostic biomarker in glioma patients. Bioinformatic functional analysis (GSEA) predicted that STOX1 was related to many key cancer pathways including P53 signaling pathway (P < 0.01), DNA replication (P < 0.05), homologous recombination (P < 0.05), and Wnt signaling pathway (P < 0.05). Taken together, these findings suggested that STOX1 may be used as a novel predictive molecular biomarker for glioma grading and overall patient survival. Further investigations on the functional roles and therapeutic value of STOX1 in glioma are warranted.

Targeted Therapies in Rare Brain Tumours

Rare central nervous system (CNS) tumours represent a unique challenge. Given the difficulty of conducting dedicated clinical trials, there is a lack of therapies for these tumours supported by high quality evidence, and knowledge regarding the impact of standard treatments (i.e., surgery, radiotherapy or chemotherapy) is commonly based on retrospective studies. Recently, new molecular techniques have led to the discovery of actionable molecular alterations. The aim of this article is to review recent progress in the molecular understanding of and therapeutic options for rare brain tumours, both in children and adults. We will discuss options such as targeting the mechanistic target of rapamycin (mTOR) pathway in subependymal giant cells astrocytomas (SEGAs) of tuberous sclerosis and BRAF V600E mutation in rare glial (pleomorphic xanthoastrocytomas) or glioneuronal (gangliogliomas) tumours, which are a model of how specific molecular treatments can also favourably impact neurological symptoms (such as seizures) and quality of life. Moreover, we will discuss initial experiences in targeting new molecular alterations in gliomas, such as isocitrate dehydrogenase (IDH) mutations and neurotrophic tyrosine receptor kinase (NTRK) fusions, and in medulloblastomas such as the sonic hedgehog (SHH) pathway.

Expression of TCF7L2 in Glioma and Its Relationship With Clinicopathological Characteristics and Patient Overall Survival

Background: The TCF7L2 gene is known as transcription factor 7-like 2 which has been identified as a novel transcription factor epithelial-mesenchymal transition (EMT) in tumor cells at 10q25.3. TCF7L2 may affect cancer progression and plays a central role in cancer proliferation, migration, and invasion. However, its clinical and prognostic value have not been researched in glioma. The purpose of our study was to research TCF7L2 expression and evaluate the clinical value of prognosis. Method: We collected glioma specimens including low-grade glioma (n = 46) and glioblastoma (n = 51) from September 2015 to September 2017. Expression of TCF7L2 in 97 specimens was detected by quantitative real-time PCR (qRT-PCR). The chi-square test was applied to analyze the relationship between TCF7L2 expression and clinicopathological characteristics. The overall survival (OS) was estimated by log-rank tests among strata, and the survival curves were drawn by Kaplan-Meier. Univariate and multivariate analysis were utilized to analyze the relationship between prognosis and clinicopathological characteristics including TCF7L2 expression. Results: Compared with the low-grade glioma group, the expression of TCF7L2 was significantly increased in the glioblastoma group (p = 0.001). TCF7L2 overexpression was associated with higher WHO grade (p = 0.001), isocitrate dehydrogenase (IDH) wild-type (p = 0.001), and lack of O(6)-methylguanine-DNA methyltransferase (MGMT) methylation (p = 0.001). Moreover, Kaplan-Meier analysis proved that overexpressed TCF7L2 was associated with poor OS (p = 0.010). The multivariate analysis suggested that TCF7L2 expression was an independent prognostic factor (p = 0.020). Conclusions: Our research proved that TCF7L2 was overexpressed in glioblastoma, and related with tumor long-term prognosis, which, therefore, could be an independent prognostic factor for glioma patients.

Spatial progression and molecular heterogeneity of IDH-mutant glioblastoma determined by DNA methylation-based mapping

Glioblastoma (GBM) is the most common malignant primary central nervous system (CNS) neoplasm in adults, and has an almost universally poor prognosis. Recently, an emphasis on genetic and epigenetic profiling has revealed a number of molecular features useful in the diagnostic and prognostic classification of GBM, advancing our understanding of the underlying features that make these tumors so aggressive and providing the rationale for the creation of better targeted therapeutics. One such method, DNA methylation profiling, has recently emerged as an important technique for the classification of CNS tumors, with diagnostic accuracy in some cases surpassing traditional methods. However, how DNA methylation profiles change with the course of the disease remains less understood. Here, we present a case of a 30-year-old male with primary IDH-mutant GBM with widespread recurrence and death two years later. Using unsupervised hierarchical clustering of methylation probes, we created a phylogenetic map to trace the tumor path as it spread from the initial biopsy site throughout the right hemisphere, across the corpus callosum to the contralateral hemisphere, and into the brainstem. We identified molecular divergence between the right and left hemisphere GBM samples marked by distinct copy number profile alterations, alterations in specific methylation sites, and regional loss of MGMT promoter methylation, providing a potential mechanism for treatment resistance in this case. In summary, this case both highlights the molecular diversity in GBM, and illustrates a novel use for methylation profiling in establishing a phylogenetic profile to allow for spatial mapping of tumor progression.

Mesenchymal stem cells in glioblastoma therapy and progression: How one cell does it all

Mesenchymal stem cells (MSCs) are among the most investigated and applied somatic stem cells in experimental therapies for the regeneration of damaged tissues. Moreover, as it was recently postulated, MSCs may demonstrate anti-tumor properties. Glioblastoma (GBM) is a grade IV central nervous system tumor with no available effective therapy and an inevitably fatal prognosis. Experimental studies utilizing MSCs in GBM treatment resulted in numerous controversies. Native MSCs were shown to exert anti-GBM activity by controlling angiogenesis, regulating cell cycle, and inducing apoptosis. They also were used as sensitizing factors and vehicles delivering various anti-cancer compounds. On the other hand, some experiments revealed significant risks related to MSC-based therapies for GBM, such as enhancement of tumor cell proliferation, invasion, and aggressiveness. The following review elaborates on all mentioned contradictory data and provides a realistic, current clinical perspective on MSCs' potential in GBM treatment.

Predictive Role of the Apparent Diffusion Coefficient and MRI Morphologic Features on IDH Status in Patients With Diffuse Glioma: A Retrospective Cross-Sectional Study

Purpose

To evaluate isocitrate dehydrogenase (IDH) status in clinically diagnosed grade II~IV glioma patients using the 2016 World Health Organization (WHO) classification based on MRI parameters.

Materials and Methods

One hundred and seventy-six patients with confirmed WHO grade II~IV glioma were retrospectively investigated as the study set, including lower-grade glioma (WHO grade II, n = 64; WHO grade III, n = 38) and glioblastoma (WHO grade IV, n = 74). The minimum apparent diffusion coefficient (ADCmin) in the tumor and the contralateral normal-appearing white matter (ADCn) and the rADC (ADCmin to ADCn ratio) were defined and calculated. Intraclass correlation coefficient (ICC) analysis was carried out to evaluate interobserver and intraobserver agreement for the ADC measurements. Interobserver agreement for the morphologic categories was evaluated by Cohen’s kappa analysis. The nonparametric Kruskal-Wallis test was used to determine whether the ADC measurements and glioma subtypes were related. By univariable analysis, if the differences in a variable were significant (P<0.05) or an image feature had high consistency (ICC >0.8; κ >0.6), then it was chosen as a predictor variable. The performance of the area under the receiver operating characteristic curve (AUC) was evaluated using several machine learning models, including logistic regression, support vector machine, Naive Bayes and Ensemble. Five evaluation indicators were adopted to compare the models. The optimal model was developed as the final model to predict IDH status in 40 patients with glioma as the subsequent test set. DeLong analysis was used to compare significant differences in the AUCs.

Results

In the study set, six measured variables (rADC, age, enhancement, calcification, hemorrhage, and cystic change) were selected for the machine learning model. Logistic regression had better performance than other models. Two predictive models, model 1 (including all predictor variables) and model 2 (excluding calcification), correctly classified IDH status with an AUC of 0.897 and 0.890, respectively. The test set performed equally well in prediction, indicating the effectiveness of the trained classifier. The subgroup analysis revealed that the model predicted IDH status of LGG and GBM with accuracy of 84.3% (AUC = 0.873) and 85.1% (AUC = 0.862) in the study set, and with the accuracy of 70.0% (AUC = 0.762) and 70.0% (AUC = 0.833) in the test set, respectively.

Conclusion

Through the use of machine-learning algorithms, the accurate prediction of IDH-mutant versus IDH-wildtype was achieved for adult diffuse gliomas via noninvasive MR imaging characteristics, including ADC values and tumor morphologic features, which are considered widely available in most clinical workstations.

Diagnostic Utility of the Immunohistochemical Expression of Serine and Arginine Rich Splicing Factor 1 (SRSF1) in the Differential Diagnosis of Adult Gliomas

Simple Summary

Gliomas represent a wide group of central nervous system neoplasms, arising from the glial component of the central nervous system. They are generally sub-classified into astrocytomas, oligodendrogliomas, ependymomas and other rarer subtypes. Apart from morphological and molecular features, there are currently no specific markers for this heterogeneous group of tumors: thus, there is a need to identify more specific and useful markers to distinguish each histological subtype from the others. SRSF1 has been recently characterized as being functionally involved in gliomagenesis and it has been found that SRSF1 is increased in glioma tissues and its increased immunohistochemical expression among adult diffuse astrocytomas is positively correlated with histological grade. The aim of this study is to evaluate the immunohistochemical expression of the SRSF1 protein in a series of astrocytic and non-astrocytic adult gliomas, emphasizing its potential use in the differential diagnosis of these neuropathological entities.

Abstract

Background: The aim of this study was to investigate the immunohistochemical expression and distribution of serine and arginine rich splicing factor 1 (SRSF1) in a series of 102 cases of both diffuse and circumscribed adult gliomas to establish the potential diagnostic role of this protein in the differential diagnosis of brain tumors. Methods: This retrospective immunohistochemical study included 42 glioblastoma cases, 21 oligodendrogliomas, 15 ependymomas, 15 pilocytic astrocytomas, 5 sub-ependymal giant cell astrocytoma and 4 pleomorphic xanthoastrocytomas. Results: Most glioblastoma (81%), oligodendroglioma (71%), sub-ependymal giant cell astrocytoma (80%) and pleomorphic xanthoastrocytoma (75%) cases showed strong SRSF1 immunoexpression, while no detectable staining was found in the majority of ependymomas (87% of cases) and pilocytic astrocytomas (67% of cases). Conclusions: The immunohistochemical expression of SRSF1 may be a promising diagnostic marker of astrocytomas and oligodendrogliomas and its increased expression might allow for excluding entities that often enter into differential diagnosis, such as ependymomas and pilocytic astrocytomas.

An integrative analysis of the age-associated multi-omic landscape across cancers

Age is the most important risk factor for cancer, as cancer incidence and mortality increase with age. However, how molecular alterations in tumours differ among patients of different age remains largely unexplored. Here, using data from The Cancer Genome Atlas, we comprehensively characterise genomic, transcriptomic and epigenetic alterations in relation to patients' age across cancer types. We show that tumours from older patients present an overall increase in genomic instability, somatic copy-number alterations (SCNAs) and somatic mutations. Age-associated SCNAs and mutations are identified in several cancer-driver genes across different cancer types. The largest age-related genomic differences are found in gliomas and endometrial cancer. We identify age-related global transcriptomic changes and demonstrate that these genes are in part regulated by age-associated DNA methylation changes. This study provides a comprehensive, multi-omics view of age-associated alterations in cancer and underscores age as an important factor to consider in cancer research and clinical practice.

Molecular Characterization of "True" Low-Grade IDH-Wildtype Astrocytomas

Numerous recent studies have demonstrated that the vast majority of IDH-wildtype astrocytomas with WHO grade II/III histology have clinical outcomes equivalent to IDH-wildtype glioblastomas. This has called into question the existence of an IDH-wildtype lower-grade astrocytoma (LGA) category, and the cIMPACT-NOW study group has suggested 3 molecular features which, if present, warrant upgrading IDH-wildtype LGA to glioblastoma: EGFR amplification, 7+/10-, and TERT promoter mutation. Herein, we evaluate the clinical, histologic, and molecular features of IDH-wildtype low-grade astrocytomas, defined here as infiltrative adult astrocytoma lacking histologic features of glioblastoma (microvascular proliferation and/or necrosis), IDH1/2 mutation, and all 3 of the cIMPACT-NOW update 3 factors. Compared with their counterparts with cIMPACT-NOW features of glioblastoma (LGA-C+; n = 108), IDH-wildtype LGAs lacking these features (LGA-C0; n = 36) occur in significantly younger patients, are more frequently WHO grade II, have less total copy number variation distributed across the entire genome, less frequent homozygous deletion of CDKN2A, less frequent PTEN and PIK3CA alterations, and more frequent NF1 alterations. These results suggest that although rare, a "true" IDH-wildtype LGA category does exist, and has distinct clinical and molecular features consistent with relatively beneficial clinical outcomes in these patients.

Molecular Signatures of Chromosomal Instability Correlate With Copy Number Variation Patterns and Patient Outcome in IDH-Mutant and IDH-Wildtype Astrocytomas

Chromosomal instability due to mutations in genes guarding the stability of the genome is a well-known mechanism underlying tumorigenesis and malignant progression in numerous cancers. The effect of this process in gliomas is mostly unknown with relatively little research examining the effects of chromosomal instability on patient outcome and therapeutic efficacy, although studies have shown that overall/total copy number variation (CNV) is elevated in higher histologic grades and in cases with more rapid progression and shorter patient survival. Herein, we examine a 70-gene mRNA expression signature (CIN70), which has been previously shown to correlate tightly with chromosomal instability, in 2 independent cohorts of IDH-mutant astrocytomas (total n = 241), IDH-wildtype astrocytomas (n = 228), and oligodendrogliomas (n = 128). Our results show that CIN70 expression levels correlate with total CNV, as well as higher grade, progression-free survival, and overall survival in both IDH-mutant and IDH-wildtype astrocytomas. In oligodendrogliomas, these mRNA signatures correlate with total CNV but not consistently with clinical outcome. These data suggest that chromosomal instability is an underlying factor in aggressive behavior and progression of a subset of diffuse astrocytomas. In addition, chromosomal instability may in part explain the poor response of diffuse gliomas to treatment and may serve as a future therapeutic target.

The Influence of Gene Aberrations on Survival in Resected IDH Wildtype Glioblastoma Patients: A Single-Institution Study

This prospective population-based study on a group of 132 resected IDH-wildtype (IDH-wt) glioblastoma (GBM) patients assesses the prognostic and predictive value of selected genetic biomarkers and clinical factors for GBM as well as the dependence of these values on the applied therapeutic modalities. The patients were treated in our hospital between June 2006 and June 2015. Clinical data and tumor samples were analyzed to determine the frequencies of TP53, MDM2, EGFR, RB1, BCR, and CCND1 gene aberrations and the duplication/deletion statuses of the 9p21.3, 1p36.3, 19q13.32, and 10p11.1 chromosome regions. Cut-off values distinguishing low (LCN) and high (HCN) copy number status for each marker were defined. Additionally, MGMT promoter methylation and IDH1/2 mutation status were investigated retrospectively. Young age, female gender, Karnofsky scores (KS) above 80, chemoradiotherapy, TP53 HCN, and CCND1 HCN were identified as positive prognostic factors, and smoking was identified as a negative prognostic factor. Cox proportional regression models of the chemoradiotherapy patient group revealed TP53 HCN and CCND1 HCN to be positive prognostic factors for both progression-free survival and overall survival. These results confirmed the influence of key clinical factors (age, KS, adjuvant oncotherapy, and smoking) on survival in GBM IDH-wt patients and demonstrated the prognostic and/or predictive importance of CCND1, MDM2, and 22q12.2 aberrations.

NPC2 as a Prognostic Biomarker for Glioblastoma Based on Integrated Bioinformatics Analysis and Cytological Experiments

Glioblastoma (GBM) is one of the most common and fatal malignancies worldwide, while its prognostic biomarkers are still being explored. This study aims to identify potential genes with clinical and prognostic significance by integrating bioinformatics analysis and investigating their function in HNSCC. Based on the Single-cell RNA sequencing (scRNA-seq) results of H3K27M-glioma cells, computational bioinformatics methods were employed for selecting prognostic biomarker for GBM. The protein NPC2 (NPC Intracellular Cholesterol Transporter 2), which has been shown to be related to lipoprotein metabolism and innate immune system, was identified to be upregulated in GBM. NPC2 showed a relatively higher expression in GBM samples, and a negative correlation with tumor purity and tumor infiltrating immune cells. Additionally, NPC2 was knocked down in U87-MG and U251 cells line, and cell proliferation and migration capability were evaluated with CCK-8, scratch and transwell assay, respectively. Cytological experiments has shown that NPC2 overexpression inhibited GBM cells proliferation and migration, indicating its important role in GBM progression. This is the first investigation into the prognostic value of NPC2 interact with GBM. The potential molecular factor NPC2 have been identified as a prognostic biomarker for GBM.

Overcoming the Odds: Toward a Molecular Profile of Long-Term Survival in Glioblastoma

For over a century, gliomas were characterized solely by histologic features. With the publication of the WHO Classification of Tumours of the Central Nervous System, Revised 4th Edition in 2016, integrated histologic and molecular diagnosis became the norm, providing improved tumor grading and prognosis with IDH1/2 (isocitrate dehydrogenase 1 and 2) mutation being the most significant prognostic feature in all grades of adult diffuse glioma. Since then, much work has been done to identify additional molecular prognostic features, but the bulk of the progress has been made in defining aggressive features in lower grade astrocytoma. Although there have been several large case series of glioblastomas with long-term survival (LTS; overall survival ≥36 months), less is known about the clinical and molecular features of these cases. Herein, we review 19 studies examining LTS glioblastoma patients from 2009 to 2020 that include variable molecular analysis, including 465 cases with survival of 36 months or more (total n = 2328). These studies suggest that while there is no definitive molecular signature of long survival, younger age, IDH mutation, and MGMT (methyl guanine methyl transferase) promoter hypermethylation are associated with longer overall survival, and in IDH-wildtype tumors, chromosome 19/20 co-gain and lack of EGFR amplification, chromosome 7 gain/10 loss, and TERT promoter mutation are associated with LTS.

Advanced imaging techniques for neuro-oncologic tumor diagnosis, with an emphasis on PET-MRI imaging of malignant brain tumors

PURPOSE OF REVIEW

This review will explore the latest in advanced imaging techniques, with a focus on the complementary nature of multiparametric, multimodality imaging using magnetic resonance imaging (MRI) and positron emission tomography (PET).

RECENT FINDINGS

Advanced MRI techniques including perfusion-weighted imaging (PWI), MR spectroscopy (MRS), diffusion-weighted imaging (DWI), and MR chemical exchange saturation transfer (CEST) offer significant advantages over conventional MR imaging when evaluating tumor extent, predicting grade, and assessing treatment response. PET performed in addition to advanced MRI provides complementary information regarding tumor metabolic properties, particularly when performed simultaneously. 18F-fluoroethyltyrosine (FET) PET improves the specificity of tumor diagnosis and evaluation of post-treatment changes. Incorporation of radiogenomics and machine learning methods further improve advanced imaging. The complementary nature of combining advanced imaging techniques across modalities for brain tumor imaging and incorporating technologies such as radiogenomics has the potential to reshape the landscape in neuro-oncology.

Cassane diterpenoid derivative induces apoptosis in IDH1 mutant glioma cells through the inhibition of glutaminase in vitro and in vivo

BACKGROUND

Glioblastoma multiforme (GBM) is the most frequent, lethal and aggressive tumour of the central nervous system in adults. The discovery of novel anti-GBM agents based on the isocitrate dehydrogenase (IDH) mutant phenotypes and classifications have attracted comprehensive attention.

PURPOSE

Diterpenoids are a class of naturally occurring 20-carbon isoprenoid compounds, and have previously been shown to possess high cytotoxicity for a variety of human tumours in many scientific reports. In the present study, 31 cassane diterpenoids of four types, namely, butanolide lactone cassane diterpenoids (I) (1-10), tricyclic cassane diterpenoids (II) (11-15), polyoxybutanolide lactone cassane diterpenoids (III) (16-23), and fused furan ring cassane diterpenoids (IV) (24-31), were tested for their anti-glioblastoma activity and mechanism underlying based on IDH1 mutant phenotypes of primary GBM cell cultures and human oligodendroglioma (HOG) cell lines.

RESULTS

We confirmed that tricyclic-type (II) and compound 13 (Caesalpin A, CSA) showed the best anti-neoplastic potencies in IDH1 mutant glioma cells compared with the other types and compounds. Furthermore, the structure-relationship analysis indicated that the carbonyl group at C-12 and an α, β-unsaturated ketone unit fundamentally contributed to enhancing the anti-glioma activity. Studies investigating the mechanism demonstrated that CSA induced oxidative stress via causing glutathione reduction and NOS activation by negatively regulating glutaminase (GLS), which proved to be highly dependent on IDH mutant type glioblastoma. Finally, GLS overexpression reversed the CSA-induced anti-glioma effects in vitro and in vivo, which indicated that the reduction of GLS contributed to the CSA-induced proliferation inhibition and apoptosis in HOG-IDH1-mu cells.

CONCLUSION

Therefore, the present results demonstrated that compared with other diterpenoids, tricyclic-type diterpenoids could be a targeted drug candidate for the treatment of secondary IDH1 mutant type glioblastoma through negatively regulating GLS.

Analyses of metastasis-associated genes in IDH wild-type glioma

Background

Glioma is the most common malignant tumor of the brain. The existence of metastatic tumor cells is an important cause of recurrence even after radical glioma resection.

Methods

Single-cell sequencing data and high-throughput data were downloaded from GEO database and TCGA/CGGA database. By means of PCA and tSNE clustering methods, metastasis-associated genes in glioma were identified. GSEA explored possible biological functions that these metastasis-associated genes may participate in. Univariate and multivariate Cox regression were used to construct a prognostic model.

Results

Glioma metastatic cells and metastasis-associated genes were identified. The prognostic model based on metastasis-associated genes had good sensitivity and specificity for the prognosis of glioma. These genes may be involved in signal pathways such as cellular protein catabolic process, p53 signaling pathway, transcriptional misregulation in cancer and JAK-STAT signaling pathway.

Conclusion

This study explored glioma metastasis-associated genes through single-cell sequencing data mining, and aimed to identify prognostic metastasis-associated signatures for glioma and may provide potential targets for further cancer research.