Characterization of MGMT and EGFR protein expression in glioblastoma and association with survival

Potential Diagnostic and Clinical Significance of Selected Genetic Alterations in Glioblastoma

Glioblastoma is currently considered the most common and, unfortunately, also the most aggressive primary brain tumor, with the highest morbidity and mortality rates. The average survival of patients diagnosed with glioblastoma is 14 months, and only 2% of patients survive 3 years after surgery. Based on our clinical experience and knowledge from extensive clinical studies, survival is mainly related to the molecular biological properties of glioblastoma, which are of interest to the general medical community. Our study examined a total of 71 retrospective studies published from 2016 through 2022 and available on PubMed that deal with mutations of selected genes in the pathophysiology of GBM. In conclusion, we can find other mutations within a given gene group that have different effects on the prognosis and quality of survival of a patient with glioblastoma. These mutations, together with the associated mutations of other genes, as well as intratumoral heterogeneity itself, offer enormous potential for further clinical research and possible application in therapeutic practice.

New Avenues and Major Achievements in Phytocompounds Research for Glioblastoma Therapy

Phytocompounds have been evaluated for their anti-glioblastoma actions for decades, with promising results from preclinical studies but only limited translation into clinics. Indeed, by targeting multiple signaling pathways deregulated in cancer, they often show high efficacy in the in vitro studies, but their poor bioavailability, low tumor accumulation, and rapid clearance compromise their efficacy in vivo. Here, we present the new avenues in phytocompound research for the improvement of glioblastoma therapy, including the ways to enhance the response to temozolomide using phytochemicals, the current focus on phytocompound-based immunotherapy, or the use of phytocompounds as photosensitizers in photodynamic therapy. Moreover, we present new, intensively evaluated approaches, such as chemical modifications of phytochemicals or encapsulation into numerous types of nanoformulations, to improve their bioavailability and delivery to the brain. Finally, we present the clinical trials evaluating the role of phytocompounds or phytocompound-derived drugs in glioblastoma therapy and the less studied phytocompounds or plant extracts that have only recently been found to possess promising anti-glioblastoma properties. Overall, recent advancements in phytocompound research are encouraging; however, only with more 3D glioblastoma models, in vivo studies, and clinical trials it is possible to upgrade the role of phytocompounds in glioblastoma treatment to a satisfactory level.

Dissecting the Methylomes of EGFR-Amplified Glioblastoma Reveals Altered DNA Replication and Packaging, and Chromatin and Gene Silencing Pathways

Glioblastoma IDH wildtype is the most frequent brain tumor in adults. It shows a highly malignant behavior and devastating outcomes. To date, there is still no targeted therapy available; thus, patients' median survival is limited to 12-15 months. Epithelial growth factor receptor (EGFR) is an interesting targetable candidate in advanced precision medicine for brain tumor patients. In this study, we performed integrated epigenome-wide DNA-methylation profiling of 866,895 methylation specific sites in 50 glioblastoma IDH wildtype samples, comparing EGFR amplified and non-amplified glioblastomas. We found 9849 significantly differentially methylated CpGs (DMCGs) with Δβ ≥ 0.1 and p-value < 0.05 in EGFR amplified, compared to EGFR non-amplified glioblastomas. Of these DMCGs, 2380 were annotated with tiling (2090), promoter (117), gene (69) and CpG islands (104); 7460 are located at other loci. Interestingly, the list of differentially methylated genes allocated eleven functionally relevant RNAs: five miRNAs (miR1180, miR1255B1, miR126, miR128-2, miR3125), two long non-coding RNAs (LINC00474, LINC01091), and four antisense RNAs (EPN2-AS1, MNX1-AS2, NKX2-2-AS1, WWTR1-AS1). Gene ontology (GO) analysis showed enrichment of "DNA replication-dependent nucleosome assembly", "chromatin silencing at rDNA", "regulation of gene silencing by miRNA", "DNA packaging", "posttranscriptional gene silencing", "gene silencing by RNA", "negative regulation of gene expression, epigenetic", "regulation of gene silencing", "protein-DNA complex subunit organization", and "DNA replication-independent nucleosome organization" pathways being hypomethylated in EGFR amplified glioblastomas. In summary, dissecting the methylomes of EGFR amplified and non-amplified glioblastomas revealed altered DNA replication, DNA packaging, chromatin silencing and gene silencing pathways, opening potential novel targets for future precision medicine.

A proteome-level view of brain tumors for a better understanding of novel diagnosis, prognosis, and therapy

INTRODUCTION

Brain tumors are complex and heterogeneous malignancies with significant challenges in diagnosis, prognosis, and therapy. Proteomics, the large-scale study of proteins and their functions, has emerged as a powerful tool to comprehensively investigate the molecular mechanisms underlying brain tumor regulation.

AREAS COVERED

This review explores brain tumors from a proteomic standpoint, highlighting recent progress and insights gained through proteomic methods. It delves into the proteomic techniques employed and underscores potential biomarkers for early detection, prognosis, and treatment planning. Recent PubMed Central proteomic studies (2017-present) are discussed, summarizing findings on altered protein expression, post-translational changes, and protein interactions. This sheds light on brain tumor signaling pathways and their significance in innovative therapeutic approaches.

EXPERT OPINION

Proteomics offers immense potential for revolutionizing brain tumor diagnosis and therapy. To unlock its full benefits, further translational research is crucial. Combining proteomics with other omics data enhances our grasp of brain tumors. Validating and translating proteomic biomarkers are vital for better patient results. Challenges include tumor complexity, lack of curated proteomic databases, and the need for collaboration between researchers and clinicians. Overcoming these challenges requires investment in technology, data sharing, and translational research.

Gene Targets of CAR-T Cell Therapy for Glioblastoma

Glioblastoma (GBM) is an aggressive primary brain tumor with a poor prognosis following conventional therapeutic interventions. Moreover, the blood-brain barrier (BBB) severely impedes the permeation of chemotherapy drugs, thereby reducing their efficacy. Consequently, it is essential to develop novel GBM treatment methods. A novel kind of pericyte immunotherapy known as chimeric antigen receptor T (CAR-T) cell treatment uses CAR-T cells to target and destroy tumor cells without the aid of the antigen with great specificity and in a manner that is not major histocompatibility complex (MHC)-restricted. It has emerged as one of the most promising therapy techniques with positive clinical outcomes in hematological cancers, particularly leukemia. Due to its efficacy in hematologic cancers, CAR-T cell therapy could potentially treat solid tumors, including GBM. On the other hand, CAR-T cell treatment has not been as therapeutically effective in treating GBM as it has in treating other hematologic malignancies. CAR-T cell treatments for GBM have several challenges. This paper reviewed the use of CAR-T cell therapy in hematologic tumors and the selection of targets, difficulties, and challenges in GBM.

The diagnostic value of ADC histogram and direct ADC measurements for coexisting isocitrate dehydrogenase mutation and O6-methylguanine-DNA methyltransferase promoter methylation in glioma

Objectives

To non-invasively predict the coexistence of isocitrate dehydrogenase (IDH) mutation and O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation in adult-type diffuse gliomas using apparent diffusion coefficient (ADC) histogram and direct ADC measurements and compare the diagnostic performances of the two methods.

Materials and methods

A total of 118 patients with adult-type diffuse glioma who underwent preoperative brain magnetic resonance imaging (MRI) and diffusion weighted imaging (DWI) were included in this retrospective study. The patient group included 40 patients with coexisting IDH mutation and MGMT promoter methylation (IDHmut/MGMTmet) and 78 patients with other molecular status, including 32 patients with IDH wildtype and MGMT promoter methylation (IDHwt/MGMTmet), one patient with IDH mutation and unmethylated MGMT promoter (IDHmut/MGMTunmet), and 45 patients with IDH wildtype and unmethylated MGMT promoter (IDHwt/MGMTunmet). ADC histogram parameters of gliomas were extracted by delineating the region of interest (ROI) in solid components of tumors. The minimum and mean ADC of direct ADC measurements were calculated by placing three rounded or elliptic ROIs in solid components of gliomas. Receiver operating characteristic (ROC) curve analysis and the area under the curve (AUC) were used to evaluate the diagnostic performances of the two methods.

Results

The 10th percentile, median, mean, root mean squared, 90th percentile, skewness, kurtosis, and minimum of ADC histogram analysis and minimum and mean ADC of direct measurements were significantly different between IDHmut/MGMTmet and the other glioma group (P < 0.001 to P = 0.003). In terms of single factors, 10th percentile of ADC histogram analysis had the best diagnostic efficiency (AUC = 0.860), followed by mean ADC obtained by direct measurements (AUC = 0.844). The logistic regression model combining ADC histogram parameters and direct measurements had the best diagnostic efficiency (AUC = 0.938), followed by the logistic regression model combining the ADC histogram parameters with statistically significant difference (AUC = 0.916) and the logistic regression model combining minimum ADC and mean ADC (AUC = 0.851).

Conclusion

Both ADC histogram analysis and direct measurements have potential value in predicting the coexistence of IDHmut and MGMTmet in adult-type diffuse glioma. The diagnostic performance of ADC histogram analysis was better than that of direct ADC measurements. The combination of the two methods showed the best diagnostic performance.

Nomogram Model for Predicting the Prognosis of High-Grade Glioma in Adults Receiving Standard Treatment: A Retrospective Cohort Study

OBJECTIVES

To identify the critical factors associated with the progression-free survival (PFS) and overall survival (OS) of high-grade glioma (HGG) in adults who have received standard treatment and establish a novel graphical nomogram and an online dynamic nomogram.

PATIENTS AND METHODS

This is a retrospective study of adult HGG patients receiving standard treatment (surgery, postoperative radiotherapy, and temozolomide (TMZ) chemotherapy) at Huashan Hospital, Fudan University between January 2017 and December 2019. We used uni- and multi-variable COX models to identify the significant prognostic factors for PFS and OS. Based on the significant predictors, graphical and online nomograms were established.

RESULTS

A total of 246 patients were enrolled in the study based on the inclusion criteria. The average PFS and OS were 22.99 ± 11.43 and 30.51 ± 13.73 months, respectively. According to the multi-variable COX model, age, extent of resection (EOR), and IDH mutation were associated with PFS and OS, while edema index (EI) was relevant to PFS. In addition, patients with IDH and TERT promoter co-mutations had longer PFSs and OSs, and no apparent survival benefit was found in the long-cycle TMZ adjuvant chemotherapy compared with the standard Stupp protocol. Based on these critical factors, a graphical nomogram and online nomogram were developed for predicting PFS and OS, respectively. The calibration curve showed favorable consistency between the predicted and actual survival rates. C-index and time-dependent AUC showed good discrimination abilities.

CONCLUSIONS

We identified the significant predictors for the PFS and OS of HGG adults receiving standard treatment and established user-friendly nomogram models to assist neurosurgeons in optimizing clinical management and treatment strategies.

Cost Matrix of Molecular Pathology in Glioma-Towards AI-Driven Rational Molecular Testing and Precision Care for the Future

Gliomas are the most common and aggressive primary brain tumors. Gliomas carry a poor prognosis because of the tumor's resistance to radiation and chemotherapy leading to nearly universal recurrence. Recent advances in large-scale genomic research have allowed for the development of more targeted therapies to treat glioma. While precision medicine can target specific molecular features in glioma, targeted therapies are often not feasible due to the lack of actionable markers and the high cost of molecular testing. This review summarizes the clinically relevant molecular features in glioma and the current cost of care for glioma patients, focusing on the molecular markers and meaningful clinical features that are linked to clinical outcomes and have a realistic possibility of being measured, which is a promising direction for precision medicine using artificial intelligence approaches.

Impact of Rural vs. Urban Residence on Survival Rates of Patients with Glioblastoma: A Tertiary Care Center Experience

Purpose: Although the association between residential location and survival in patients with different cancer types has been established, the conclusions are contentious, and the underlying mechanisms remain unknown. Here, we reviewed the impact of residence on the survival of patients with glioblastoma (GBM). Methods: We conducted a retrospective study to compare the impact of rural and urban residence on the survival rates of patients with GBM diagnosed in Riyadh City and outside Riyadh. All patients in this study were treated in a tertiary care hospital, and their survival rates were analyzed in relation to their residence and other related factors, namely radiotherapy timing. Results: Overall, 125 patients were included: 61 from Riyadh City and 64 from outside. The majority of patients in both groups were aged >50 years (p = 0.814). There was no statistically significant difference between the groups in the Eastern Cooperative Oncology Group Performance Status (p = 0.430), seizure (p = 0.858), or initiation timing of radiotherapy (p = 0.781). Furthermore, the median survival rate in the Riyadh group versus the other group was 14.4 months and 12.2 months, respectively, with no statistical significance (p = 0.187). Conclusions: Our study showed that residential location had no significant effect on GBM prognosis. However, further studies with a larger sample size are required to delineate the other factors of referral within the healthcare system to facilitate the management of these patients within a specific timeframe.

The Next Frontier in Health Disparities—A Closer Look at Exploring Sex Differences in Glioma Data and Omics Analysis, from Bench to Bedside and Back

Sex differences are increasingly being explored and reported in oncology, and glioma is no exception. As potentially meaningful sex differences are uncovered, existing gender-derived disparities mirror data generated in retrospective and prospective trials, real-world large-scale data sets, and bench work involving animals and cell lines. The resulting disparities at the data level are wide-ranging, potentially resulting in both adverse outcomes and failure to identify and exploit therapeutic benefits. We set out to analyze the literature on women’s data disparities in glioma by exploring the origins of data in this area to understand the representation of women in study samples and omics analyses. Given the current emphasis on inclusive study design and research, we wanted to explore if sex bias continues to exist in present-day data sets and how sex differences in data may impact conclusions derived from large-scale data sets, omics, biospecimen analysis, novel interventions, and standard of care management.

EGFR Amplification Is a Phenomenon of IDH Wildtype and TERT Mutated High-Grade Glioma: An Integrated Analysis Using Fluorescence In Situ Hybridization and DNA Methylome Profiling

Gliomas are the most common intrinsic brain tumors in adults, and in accordance with their clinical behavior and patients’ outcome, they are graded by the World Health Organization (WHO) classification of brain tumors. One very interesting candidate for targeted tumor therapy may be epidermal growth factor receptor (EGFR) amplification. Here, we performed an integrated comparative analysis of EGFR amplification in 34 glioma samples using standard fluorescence in situ hybridization (FISH) and Illumina EPIC Infinium Methylation Bead Chip and correlated results with molecular glioma hallmarks. We found that the EPIC analysis showed the same power of detecting EGFR amplification compared with FISH. EGFR amplification was detectable in high-grade gliomas (25%). Moreover, EGFR amplification was found to be present solely in IDH wildtype gliomas (26%) and TERT mutated gliomas (27%), occurring independently of MGMT promoter methylation status and being mutually exclusive with 1p/19q codeletion (LOH). In summary, EPIC Bead Chip analysis is a reliable tool for detecting EGFR amplification and is comparable with the standard method FISH. EGFR amplification is a phenomenon of IDH wildtype TERT mutated high-grade gliomas.

Radiomics Analysis Based on Magnetic Resonance Imaging for Preoperative Overall Survival Prediction in Isocitrate Dehydrogenase Wild-Type Glioblastoma

Purpose

This study aimed to develop a radiomics signature for the preoperative prognosis prediction of isocitrate dehydrogenase (IDH)-wild-type glioblastoma (GBM) patients and to provide personalized assistance in the clinical decision-making for different patients.

Materials and Methods

A total of 142 IDH-wild-type GBM patients classified using the new classification criteria of WHO 2021 from two centers were included in the study and randomly divided into a training set and a test set. Firstly, their clinical characteristics were screened using univariate Cox regression. Then, the radiomics features were extracted from the tumor and peritumoral edema areas on their contrast-enhanced T1-weighted image (CE-T1WI), T2-weighted image (T2WI), and T2-weighted fluid-attenuated inversion recovery (T2-FLAIR) magnetic resonance imaging (MRI) images. Subsequently, inter- and intra-class correlation coefficient (ICC) analysis, Spearman’s correlation analysis, univariate Cox, and the least absolute shrinkage and selection operator (LASSO) Cox regression were used step by step for feature selection and the construction of a radiomics signature. The combined model was established by integrating the selected clinical factors. Kaplan–Meier analysis was performed for the validation of the discrimination ability of the model, and the C-index was used to evaluate consistency in the prediction. Finally, a Radiomics + Clinical nomogram was generated for personalized prognosis analysis and then validated using the calibration curve.

Results

Analysis of the clinical characteristics resulted in the screening of four risk factors. The combination of ICC, Spearman’s correlation, and univariate and LASSO Cox resulted in the selection of eight radiomics features, which made up the radiomics signature. Both the radiomics and combined models can significantly stratify high- and low-risk patients (p &lt; 0.001 and p &lt; 0.05 for the training and test sets, respectively) and obtained good prediction consistency (C-index = 0.74–0.86). The calibration plots exhibited good agreement in both 1- and 2-year survival between the prediction of the model and the actual observation.

Conclusion

Radiomics is an independent preoperative non-invasive prognostic tool for patients who were newly classified as having IDH-wild-type GBM. The constructed nomogram, which combined radiomics features with clinical factors, can predict the overall survival (OS) of IDH-wild-type GBM patients and could be a new supplement to treatment guidelines.

Tyrosine Kinase Inhibitors in Adult Glioblastoma: An (Un)Closed Chapter?

Glioblastoma (GBM) is the most common and lethal form of malignant brain tumor. GBM patients normally undergo surgery plus adjuvant radiotherapy followed by chemotherapy. Numerous studies into the molecular events driving GBM highlight the central role played by the Epidermal Growth Factor Receptor (EGFR), as well as the Platelet-derived Growth Factor Receptors PDGFRA and PDGFRB in tumor initiation and progression. Despite strong preclinical evidence for the therapeutic potential of tyrosine kinase inhibitors (TKIs) that target EGFR, PDGFRs, and other tyrosine kinases, clinical trials performed during the last 20 years have not led to the desired therapeutic breakthrough for GBM patients. While clinical trials are still ongoing, in the medical community there is the perception of TKIs as a lost opportunity in the fight against GBM. In this article, we review the scientific rationale for the use of TKIs targeting glioma drivers. We critically analyze the potential causes for the failure of TKIs in the treatment of GBM, and we propose alternative approaches to the clinical evaluation of TKIs in GBM patients.

Molecular Biomarkers Predict Pathological Complete Response of Neoadjuvant Chemotherapy in Breast Cancer Patients: Review

Simple Summary

Breast cancer is the most common cancer in women worldwide. Although many studies have aimed to understand the genetic basis of breast cancer, leading to increasingly accurate diagnoses, only a few molecular biomarkers are used in clinical practice to predict response to therapy. Current studies aim to develop more personalized therapies to decrease the adverse effects of chemotherapy. Personalized medicine not only requires clinical, but also molecular characterization of tumors, which allows the use of more effective drugs for each patient. The aim of this study was to identify potential molecular biomarkers that can predict the response to therapy after neoadjuvant chemotherapy in patients with breast cancer. In this review, we summarize genomic, transcriptomic, and proteomic biomarkers that can help predict the response to therapy.

Abstract

Neoadjuvant chemotherapy (NAC) is often used to treat locally advanced disease for tumor downstaging, thus improving the chances of breast-conserving surgery. From the NAC response, it is possible to obtain prognostic information as patients may reach a pathological complete response (pCR). Those who do might have significant advantages in terms of survival rates. Breast cancer (BC) is a heterogeneous disease that requires personalized treatment strategies. The development of targeted therapies depends on identifying biomarkers that can be used to assess treatment efficacy as well as the discovery of new and more accurate therapeutic agents. With the development of new “OMICS” technologies, i.e., genomics, transcriptomics, and proteomics, among others, the discovery of new biomarkers is increasingly being used in the context of clinical practice, bringing us closer to personalized management of BC treatment. The aim of this review is to compile the main biomarkers that predict pCR in BC after NAC.

The regulatory pattern of target gene expression by aberrant enhancer methylation in glioblastoma

Background

Glioblastoma multiforme (GBM) is the most common and aggressive primary malignant brain tumor with grim prognosis. Aberrant DNA methylation is an epigenetic mechanism that promotes GBM carcinogenesis, while the function of DNA methylation at enhancer regions in GBM remains poorly described.

Results

We integrated multi-omics data to identify differential methylation enhancer region (DMER)-genes and revealed global enhancer hypomethylation in GBM. In addition, a DMER-mediated target genes regulatory network and functional enrichment analysis of target genes that might be regulated by hypomethylation enhancer regions showed that aberrant enhancer regions could contribute to tumorigenesis and progression in GBM. Further, we identified 22 modules in which lncRNAs and mRNAs synergistically competed with each other. Finally, through the construction of drug-target association networks, our study identified potential small-molecule drugs for GBM treatment.

Conclusions

Our study provides novel insights for understanding the regulation of aberrant enhancer region methylation and developing methylation-based biomarkers for the diagnosis and treatment of GBM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04345-8.

DNA Repair Mechanisms and Therapeutic Targets in Glioma

PURPOSE OF REVIEW

This review discusses current and investigative strategies for targeting DNA repair in the management of glioma.

RECENT FINDINGS

Recent strategies in glioma treatment rely on the production of overwhelming DNA damage and inhibition of repair mechanisms, resulting in lethal cytotoxicity. Many strategies are effective in preclinical glioma models while clinical feasibility remains under investigation. The presence of glioma biomarkers, including IDH mutation and/or MGMT promoter methylation, may confer particular susceptibility to DNA damage and inhibition of repair. These biomarkers have been adopted as eligibility criteria in the design of multiple ongoing clinical trials. Targeting DNA repair mechanisms with novel agents or therapeutic combinations is a promising approach to the treatment of glioma. Further investigations are underway to optimize this approach in the clinical setting.

The Emerging Roles of circFOXO3 in Cancer

Circular RNAs (circRNAs) are a class of endogenous non-coding RNAs which are mainly formed by reverse splicing of precursor mRNAs. They are relatively stable and resistant to RNase R because of their covalently closed structure without 5' caps or 3' poly-adenylated tails. CircRNAs are widely expressed in eukaryotic cells and show tissue, timing, and disease specificity. Recent studies have found that circRNAs play an important role in many diseases. In particular, they affect the proliferation, invasion and prognosis of cancer by regulating gene expression. CircRNA Forkhead box O3 (circFOXO3) is a circRNA confirmed to be abnormally expressed in a variety of cancers, including prostate cancer, hepatocellular carcinoma, glioblastoma, bladder cancer, and breast cancer, etc. At present, the feature of circFOXO3 as a molecular sponge is widely studied to promote or inhibit the development of cancers. However, the diverse functions of circFOXO3 have not been fully understood. Hence, it is important to review the roles of circFOXO3 in cancers. This review has summarized and discussed the roles and molecular mechanism of circFOXO3 and its target genes in these cancers, which can help to enrich our understanding to the functions of circRNAs and carry out subsequent researches on circFOXO3.

Temozolomide: An Updated Overview of Resistance Mechanisms, Nanotechnology Advances and Clinical Applications

Temozolomide (TMZ), an oral alkylating prodrug which delivers a methyl group to purine bases of DNA (O6-guanine; N7-guanine and N3-adenine), is frequently used together with radiotherapy as part of the first-line treatment of high-grade gliomas. The main advantages are its high oral bioavailability (almost 100% although the concentration found in the cerebrospinal fluid was approximately 20% of the plasma concentration of TMZ), its lipophilic properties, and small size that confer the ability to cross the blood-brain barrier. Furthermore, this agent has demonstrated activity not only in brain tumors but also in a variety of solid tumors. However, conventional therapy using surgery, radiation, and TMZ in glioblastoma results in a median patient survival of 14.6 months. Treatment failure has been associated with tumor drug resistance. This phenomenon has been linked to the expression of O6-methylguanine-DNA methyltransferase, but the mismatch repair system and the presence of cancer stem-like cells in tumors have also been related to TMZ resistance. The understanding of these mechanisms is essential for the development of new therapeutic strategies in the clinical use of TMZ, including the use of nanomaterial delivery systems and the association with other chemotherapy agents. The aim of this review is to summarize the resistance mechanisms of TMZ and the current advances to improve its clinical use.

CK2 Activity Mediates the Aggressive Molecular Signature of Glioblastoma Multiforme by Inducing Nerve/Glial Antigen (NG)2 Expression

Nerve/glial antigen (NG)2 expression crucially determines the aggressiveness of glioblastoma multiforme (GBM). Recent evidence suggests that protein kinase CK2 regulates NG2 expression. Therefore, we investigated in the present study whether CK2 inhibition suppresses proliferation and migration of NG2-positive GBM cells. For this purpose, CK2 activity was suppressed in the NG2-positive cell lines A1207 and U87 by the pharmacological inhibitor CX-4945 and CRISPR/Cas9-mediated knockout of CK2α. As shown by quantitative real-time PCR, luciferase-reporter assays, flow cytometry and western blot, this significantly reduced NG2 gene and protein expression when compared to vehicle-treated and wild type controls. In addition, CK2 inhibition markedly reduced NG2-dependent A1207 and U87 cell proliferation and migration. The Cancer Genome Atlas (TCGA)-based data further revealed not only a high expression of both NG2 and CK2 in GBM but also a positive correlation between the mRNA expression of the two proteins. Finally, we verified a decreased NG2 expression after CX-4945 treatment in patient-derived GBM cells. These findings indicate that the inhibition of CK2 represents a promising approach to suppress the aggressive molecular signature of NG2-positive GBM cells. Therefore, CX-4945 may be a suitable drug for the future treatment of NG2-positive GBM.