Proteogenomic characterization and integrative analysis of glioblastoma multiforme

Integrated pipeline for ultrasensitive protein detection in cancer nanomedicine

Although nanotechnologies have attractive attributes in cancer therapy, their full potential has yet to be realized due to challenges in their translation to clinical settings. The evaluation of cancer nanomedicine efficacy in preclinical in vivo studies is limited to tumor size and animal survival metrics, which do not provide adequate understanding of the nanomedicine's mechanism of action. To address this, we have developed an integrated pipeline called nanoSimoa that combines an ultrasensitive protein detection technique (Simoa) with cancer nanomedicine. As a proof-of concept, we assessed the therapeutic efficacy of an ultrasound-responsive mesoporous silica nanoparticle (MSN) drug delivery system on OVCAR-3 ovarian cancer cells using CCK-8 assays to evaluate cell viability and Simoa assays to measure IL-6 protein levels. The results demonstrated significant reductions in both IL-6 levels and cell viability following nanomedicine treatment. In addition, a Ras Simoa assay (limit of detection: 0.12 pM) was developed to detect and quantify Ras protein levels in OVCAR-3 cells, which are undetectable by commercial enzyme-linked immunosorbent assays (ELISA). These results suggest that nanoSimoa has the potential to guide the development of cancer nanomedicines and predict their behavior in vivo, making it a valuable tool for preclinical testing and accelerating the development of precision medicine if its generalizability is confirmed.

Glioblastoma stem cells express non-canonical proteins and exclusive mesenchymal-like or non-mesenchymal-like protein signatures

Glioblastoma (GBM) cancer stem cells (GSCs) contribute to GBM's origin, recurrence, and resistance to treatment. However, the understanding of how mRNA expression patterns of GBM subtypes are reflected at global proteome level in GSCs is limited. To characterize protein expression in GSCs, we performed in-depth proteogenomic analysis of patient-derived GSCs by RNA-sequencing and mass-spectrometry. We quantified > 10 000 proteins in two independent GSC panels and propose a GSC-associated proteomic signature characterizing two distinct phenotypic conditions; one defined by proteins upregulated in proneural and classical GSCs (GPC-like), and another by proteins upregulated in mesenchymal GSCs (GM-like). The GM-like protein set in GBM tissue was associated with necrosis, recurrence, and worse overall survival. Through proteogenomics, we discovered 252 non-canonical peptides in the GSCs, i.e., protein sequences that are variant or derive from genome regions previously considered non-protein-coding, including variants of the heterogeneous ribonucleoproteins implicated in RNA splicing. In summary, GSCs express two protein sets that have an inverse association with clinical outcomes in GBM. The discovery of non-canonical protein sequences questions existing gene models and pinpoints new protein targets for research in GBM.

MEOX2 Regulates the Growth and Survival of Glioblastoma Stem Cells by Modulating Genes of the Glycolytic Pathway and Response to Hypoxia

Simple Summary

Glioblastoma is the most common incurable primary brain tumor in adults, typically leading to death within 15 months of diagnosis. Although there is an ongoing debate in the scientific community about the precise cellular origin of this tumor, glioblastoma stem cells (GSCs), which are able to self-renew, yield a full tumor mass, and determine chemo- and radio-resistance, are recognized to have a pivotal role. Our research aims to understand the role of the mesenchyme homeobox 2 (MEOX2) transcription factor in GSCs where it is strongly and specifically expressed. We have found that MEOX2 is indeed important for the survival of these cells. In fact, when we reduce its expression in two different GSC lines, they undergo a massive death accompanied by the inhibition of key genes of the glycolytic metabolism, the main source of energy for these cells. Our results reveal a novel function for MEOX2 in glioblastoma and suggest a mechanism through which GSCs may survive even in unfavorable conditions.

Abstract

The most widely accepted hypothesis for the development of glioblastoma suggests that glioblastoma stem-like cells (GSCs) are crucially involved in tumor initiation and recurrence as well as in the occurrence of chemo- and radio-resistance. Mesenchyme homeobox 2 (MEOX2) is a transcription factor overexpressed in glioblastoma, whose expression is negatively correlated with patient survival. Starting from our observation that MEOX2 expression is strongly enhanced in six GSC lines, we performed shRNA-mediated knock-down experiments in two different GSC lines and found that MEOX2 depletion resulted in the inhibition of cell growth and sphere-forming ability and an increase in apoptotic cell death. By a deep transcriptome analysis, we identified a core group of genes modulated in response to MEOX2 knock-down. Among these genes, the repressed ones are largely enriched in genes involved in the hypoxic response and glycolytic pathway, two strictly related pathways that contribute to the resistance of high-grade gliomas to therapies. An in silico study of the regulatory regions of genes differentially expressed by MEOX2 knock-down revealed that they mainly consisted of GC-rich regions enriched for Sp1 and Klf4 binding motifs, two main regulators of metabolism in glioblastoma. Our results show, for the first time, the involvement of MEOX2 in the regulation of genes of GSC metabolism, which is essential for the survival and growth of these cells.

Integration of RNA-Seq and proteomics data identifies glioblastoma multiforme surfaceome signature

Background

Glioblastoma multiforme (GBM) is a highly lethal, stage IV brain tumour with a prevalence of approximately 2 per 10,000 people globally. The cell surface proteins or surfaceome serve as information gateway in many oncogenic signalling pathways and are important in modulating cancer phenotypes. Dysregulation in surfaceome expression and activity have been shown to promote tumorigenesis. The expression of GBM surfaceome is a case in point; OMICS screening in a cell-based system identified that this sub-proteome is largely perturbed in GBM. Additionally, since these cell surface proteins have ‘direct’ access to drugs, they are appealing targets for cancer therapy. However, a comprehensive GBM surfaceome landscape has not been fully defined yet. Thus, this study aimed to define GBM-associated surfaceome genes and identify key cell-surface genes that could potentially be developed as novel GBM biomarkers for therapeutic purposes.

Methods

We integrated the RNA-Seq data from TCGA GBM (n = 166) and GTEx normal brain cortex (n = 408) databases to identify the significantly dysregulated surfaceome in GBM. This was followed by an integrative analysis that combines transcriptomics, proteomics and protein-protein interaction network data to prioritize the high-confidence GBM surfaceome signature.

Results

Of the 2381 significantly dysregulated genes in GBM, 395 genes were classified as surfaceome. Via the integrative analysis, we identified 6 high-confidence GBM molecular signature, HLA-DRA, CD44, SLC1A5, EGFR, ITGB2, PTPRJ, which were significantly upregulated in GBM. The expression of these genes was validated in an independent transcriptomics database, which confirmed their upregulated expression in GBM. Importantly, high expression of CD44, PTPRJ and HLA-DRA is significantly associated with poor disease-free survival. Last, using the Drugbank database, we identified several clinically-approved drugs targeting the GBM molecular signature suggesting potential drug repurposing.

Conclusions

In summary, we identified and highlighted the key GBM surface-enriched repertoires that could be biologically relevant in supporting GBM pathogenesis. These genes could be further interrogated experimentally in future studies that could lead to efficient diagnostic/prognostic markers or potential treatment options for GBM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08591-0.

Progesterone Receptor Together with PKCα Expression as Prognostic Factors for Astrocytomas Malignancy

Introduction

Astrocytomas are the most common and aggressive primary brain tumors, and they are classified according to the degree of malignancy on a scale of I to IV, in which grade I is the least malignant and grade IV the highest. Many factors are related to astrocytomas progression as progesterone receptor (PR), whose transcriptional activity could be regulated by phosphorylation by protein kinase C alpha (PKCα) at the residue Ser400. Our aim was to investigate if PR phosphorylation together with PKCα expression could be used as a prognostic factor for astrocytomas malignancy.

Methods

By immunofluorescence, we detected the content of PKCα, PR and its phosphorylation at Ser400 in 46 biopsies from Mexican patients with different astrocytoma malignancy grades; by bioinformatic tools using TCGA data, we evaluated the expression of PR and PKCα mRNA according to astrocytoma malignancy grades. For all statistical analyses, significance was p<0.05.

Results

We detected a positive correlation between the tumor grade and the content of PKCα, PR and its phosphorylation at Ser400, as well as the intracellular colocalization of these proteins. Interestingly, using an in silico assay, we found that the PR and PKCα expression at mRNA level has an inverse ratio with astrocytomas tumor grade.

Discussion

These results indicate that PR and its phosphorylation at Ser400 site, as well as PKCα and their colocalization, could be considered as possible malignancy biomarkers for astrocytomas grades I–IV.

LPA1 Receptor Promotes Progesterone Receptor Phosphorylation through PKCα in Human Glioblastoma Cells

Lysophosphatidic acid (LPA) induces a wide range of cellular processes and its signaling is increased in several cancers including glioblastoma (GBM), a high-grade astrocytoma, which is the most common malignant brain tumor. LPA1 receptor is expressed in GBM cells and its signaling pathways activate protein kinases C (PKCs). A downstream target of PKC, involved in GBM progression, is the intracellular progesterone receptor (PR), which can be phosphorylated by this enzyme, increasing its transcriptional activity. Interestingly, in GBM cells, PKCα isotype translocates to the nucleus after LPA stimulation, resulting in an increase in PR phosphorylation. In this study, we determined that LPA1 receptor activation induces protein-protein interaction between PKCα and PR in human GBM cells; this interaction increased PR phosphorylation in serine400. Moreover, LPA treatment augmented VEGF transcription, a known PR target. This effect was blocked by the PR selective modulator RU486; also, the activation of LPA1/PR signaling promoted migration of GBM cells. Interestingly, using TCGA data base, we found that mRNA expression of LPAR1 increases according to tumor malignancy and correlates with a lower survival in grade III astrocytomas. These results suggest that LPA1/PR pathway regulates GBM progression.

Glioblastoma CUSA Fluid Protein Profiling: A Comparative Investigation of the Core and Peripheral Tumor Zones

Simple Summary

The biological processes responsible for the high infiltration and recurrence rate of glioblastoma multiforme, the most frequent and aggressive primary brain tumor (GBM), are still under investigation. By the original analysis of cavitating ultrasound aspirator fluid as the biological specimen, the present study aimed to preliminarily explore and compare the protein profiles of the tumor core and tumor periphery, as defined by 5-aminolevulinic acid fluorescence, in newly diagnosed and recurrent glioblastoma sampled pools. The results showed distinguished protein elements in the different tumor and peritumoral zones, as well as in the two tumor states (newly diagnosed vs recurrent), and suggested the presence of pathological aspects in the fluorescent negative periphery, possibly contributing to the comprehension of the molecular mechanisms underlying this tumor’s onset and development, opening to potential clinical applications.

Abstract

The present investigation aimed to characterize the protein profile of cavitating ultrasound aspirator fluid of newly diagnosed and recurrent glioblastoma comparing diverse zones of collection, i.e., tumor core and tumor periphery, with the aid of 5-aminolevulinic acid fluorescence. The samples were pooled and analyzed in triplicate by LC-MS following the shotgun proteomic approach. The identified proteins were then grouped to disclose elements exclusive and common to the tumor state or tumor zones and submitted to gene ontology classification and pathway overrepresentation analysis. The proteins common to the distinct zones were further investigated by relative quantitation, following a label free approach, to disclose possible differences of expression. Nine proteins, i.e., tubulin 2B chain, CD59, far upstream element-binding, CD44, histone H1.4, caldesmon, osteopontin, tropomyosin chain and metallothionein-2, marked the core of newly diagnosed glioblastoma with respect to tumor periphery. Considering the tumor zone, including the core and the fluorescence positive periphery, the serine glycine biosynthesis, pentose phosphate, 5-hydroxytryptamine degredation, de novo purine biosynthesis and huntington disease pathways resulted statistically significantly overrepresented with respect to the human genome of reference. The fluorescence negative zone shared several protein elements with the tumor zone, possibly indicating the presence of pathological aspects of glioblastoma rather than of normal brain parenchyma. On the other hand, its exclusive protein elements were considered to represent the healthy zone and, accordingly, exhibiting no pathways overrepresentation. On the contrary to newly diagnosed glioblastoma, pathway overrepresentation was recognized only in the healthy zone of recurrent glioblastoma. The TGFβ signaling pathway, exclusively classified in the fluorescence negative periphery in newly diagnosed glioblastoma, was instead the exclusive pathway classified in the tumor core of recurrent glioblastoma. These results, preliminary obtained on sample pools, demonstrated the potential of cavitron ultrasonic surgical aspirate fluid for proteomic profiling of glioblastoma able to distinguish molecular features specific of the diverse tumor zones and tumor states, possibly contributing to the understanding of the highly infiltrative capability and recurrent rate of this aggressive brain tumor and opening to potential clinical applications to be further investigated.

Bidirectional Relation Between Parkinson's Disease and Glioblastoma Multiforme

Cancer and Parkinson's disease (PD) define two disease entities that include opposite concepts. Indeed, the involved mechanisms are at different ends of a spectrum related to cell survival - one due to enhanced cellular proliferation and the other due to premature cell death. There is increasing evidence indicating that patients with neurodegenerative diseases like PD have a reduced incidence for most cancers. In support, epidemiological studies demonstrate an inverse association between PD and cancer. Both conditions apparently can involve the same set of genes, however, in affected tissues the expression was inversely regulated: genes that are down-regulated in PD were found to be up-regulated in cancer and vice versa, for example p53 or PARK7. When comparing glioblastoma multiforme (GBM), a malignant brain tumor with poor overall survival, with PD, astrocytes are dysregulated in both diseases in opposite ways. In addition, common genes, that are involved in both diseases and share common key pathways of cell proliferation and metabolism, were shown to be oppositely deregulated in PD and GBM. Here, we provide an overview of the involvement of PD- and GBM-associated genes in common pathways that are dysregulated in both conditions. Moreover, we illustrate why the simultaneous study of PD and GBM regarding the role of common pathways may lead to a deeper understanding of these still incurable conditions. Eventually, considering the inverse regulation of certain genes in PD and GBM will help to understand their mechanistic basis, and thus to define novel target-based strategies for causative treatments.

Integrated pharmaco-proteogenomics defines two subgroups in isocitrate dehydrogenase wild-type glioblastoma with prognostic and therapeutic opportunities

The prognostic and therapeutic relevance of molecular subtypes for the most aggressive isocitrate dehydrogenase 1/2 (IDH) wild-type glioblastoma (GBM) is currently limited due to high molecular heterogeneity of the tumors that impedes patient stratification. Here, we describe a distinct binary classification of IDH wild-type GBM tumors derived from a quantitative proteomic analysis of 39 IDH wild-type GBMs as well as IDH mutant and low-grade glioma controls. Specifically, GBM proteomic cluster 1 (GPC1) tumors exhibit Warburg-like features, neural stem-cell markers, immune checkpoint ligands, and a poor prognostic biomarker, FKBP prolyl isomerase 9 (FKBP9). Meanwhile, GPC2 tumors show elevated oxidative phosphorylation-related proteins, differentiated oligodendrocyte and astrocyte markers, and a favorable prognostic biomarker, phosphoglycerate dehydrogenase (PHGDH). Integrating these proteomic features with the pharmacological profiles of matched patient-derived cells (PDCs) reveals that the mTORC1/2 dual inhibitor AZD2014 is cytotoxic to the poor prognostic PDCs. Our analyses will guide GBM prognosis and precision treatment strategies.

The heterogeneity of IDH1/2 wild-type glioblastoma limits its prognosis and therapy. Here, the authors show a binary stratification, based on quantitative proteomic analysis of samples from patients with glioblastoma, with different prognosis and therapeutic vulnerabilities.

Identification of potential crucial genes and molecular mechanisms in glioblastoma multiforme by bioinformatics analysis

Glioblastoma multiforme (GBM) is the most common and malignant brain tumor of the adult central nervous system and is associated with poor prognosis. The present study aimed to identify the hub genes in GBM in order to improve the current understanding of the underlying mechanism of GBM. The RNA-seq data were downloaded from The Cancer Genome Atlas database. The edgeR package in R software was used to identify differentially expressed genes (DEGs) between two groups: Glioblastoma samples and normal brain samples. Gene Ontology (GO) functional enrichment analysis and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed using Database for Annotation, Visualization and Integrated Discovery software. Additionally, Cytoscape and Search Tool for the Retrieval of Interacting Genes/Proteins tools were used for the protein-protein interaction network, while the highly connected modules were extracted from this network using the Minimal Common Oncology Data Elements plugin. Next, the prognostic significance of the candidate hub genes was analyzed using UALCAN. In addition, the identified hub genes were verified by reverse transcription-quantitative (RT-q) PCR. In total, 1,483 DEGs were identified between GBM and control samples, including 954 upregulated genes and 529 downregulated genes (P<0.01; fold-change >16) and these genes were involved in different GO terms and signaling pathways. Furthermore, CDK1, BUB1, BUB1B, CENPA and GNG3 were identified as key genes in the GBM samples. The UALCAN tool verified that higher expression level of CENPA was relevant to poorer overall survival rates. In conclusion, CDK1, BUB1, BUB1B, CENPA and GNG3 were found to be potential biomarkers for GBM. Additionally, ‘cell cycle’ and ‘γ-aminobutyric acid signaling’ pathways may serve a significant role in the pathogenesis of GBM.

Rapid Proteomic Profiling by MALDI-TOF Mass Spectrometry for Better Brain Tumor Classification

PURPOSE

Glioblastoma is one of the most aggressive primary brain cancers. The precise grading of tumors is important to adopt the best follow-up treatment but complementary methods to histopathological diagnosis still lack in achieving an unbiased and reliable classification.

EXPERIMENTAL DESIGN

To progress in the field, a rapid Matrix Assisted Laser Desorption Ionization - Time of Flight Mass spectrometry (MALDI-TOF MS) protocole, devised for the identification and taxonomic classification of microorganisms and based on the analysis of whole cell extracts, was applied to glioma cell lines.

RESULTS

The analysis of different human glioblastoma cell lines permitted to identify distinct proteomic profiles thus demonstrating the ability of MALDI-TOF to distinguish different malignant cell types.

CONCLUSIONS AND CLINICAL RELEVANCE

In the study, the authors showed the ability of MALDI-TOF profiling to discriminate glioblastoma cell lines, demonstrating that this technique could be used in complement to histological tumor classification. The proposed procedure is rapid and inexpensive and could be used to improve brain tumors classification and help propose a personalized and more efficient treatment.

Tenascin-C expression contributes to pediatric brainstem glioma tumor phenotype and represents a novel biomarker of disease

Diffuse intrinsic pontine glioma (DIPG), an infiltrative, high grade glioma (HGG) affecting young children, has the highest mortality rate of all pediatric cancers. Despite treatment, average survival is less than twelve months, and five-year survival under 5%. We previously detected increased expression of Tenascin-C (TNC) protein in DIPG cerebrospinal fluid and tumor tissue relative to normal specimens. TNC is an extracellular matrix (ECM) glycoprotein that mediates cell-matrix interactions, guides migrating neurons during normal brain development and is thought to maintain the periventricular stem cell niche in the developing brain. Tumor TNC expression is reported in adult glioma and other cancers. However, the pattern and effects of TNC expression in DIPG has not been previously explored. Here, we characterize TNC expression in patient derived pediatric supratentorial HGG (n = 3) and DIPG (n = 6) cell lines, as well as pediatric glioma tumor (n = 50) and normal brain tissue specimens (n = 3). We found tumor specific TNC gene and protein overexpression that directly correlated with higher tumor grade (WHO III and IV, p = 0.05), H3K27 M mutation (p = 0.012), shorter progression free survival (p = 0.034), and poorer overall survival (0.041) in association with these factors. TNC knockdown via lentiviral shRNA transfection of HGG (n = 1) and DIPG (n = 3) cell lines resulted in decreased cell proliferation, migration, and invasion in vitro (p < 0.01), while TNC cDNA transfection resulted in increased cell migration, invasion and proliferation (p < 0.01) as well as altered cell morphology in H3K27 M mutant DIPG lines. Whole transcriptome sequencing analysis (RNA-Seq) on DIPG (n = 3) and HGG (n = 2) cell lines after TNC cDNA, shRNA, and empty vector control transfection revealed the effects of TNC expression level on global gene expression profiles. Together, our findings reveal TNC expression in DIPG in association with H3K27 M mutation and VEGF signaling, and suggest that TNC may contribute to DIPG tumor phenotype, and serve as a clinically detectable biomarker for DIPG.

Current Options and Future Directions in Immune Therapy for Glioblastoma

Glioblastoma is in need of innovative treatment approaches. Immune therapy for cancer refers to the use of the body's immune system to target malignant cells in the body. Such immune therapeutics have recently been very successful in treating a diverse group of cancerous lesions. As a result, many new immune therapies have gained Food and Drug Administration approval for the treatment of cancer, and there has been an explosion in the study of immune therapeutics for cancer treatment over the past few years. However, the immune suppression of glioblastoma and the unique immune microenvironment of the brain make immune therapeutics more challenging to apply to the brain than to other systemic cancers. Here, we discuss the existing barriers to successful immune therapy for glioblastoma and the ongoing development of immune therapeutics. We will discuss the discovery and classification of immune suppressive factors in the glioblastoma microenvironment; the development of vaccine-based therapies; the use of convection-enhanced delivery to introduce tumoricidal viruses into the tumor microenvironment, leading to secondary immune responses; the emerging use of adoptive cell therapy in the treatment of glioblastoma; and future frontiers, such as the use of cerebral microdialysis for immune monitoring and the use of sequencing to develop patient-specific therapeutics. Armed with a better understanding of the challenges inherent in immune therapy for glioblastoma, we may soon see more successes in immune-based clinical trials for this deadly disease.

Integration of transcriptome and proteome profiles in glioblastoma: looking for the missing link

Background

Glioblastoma (GB) is the most common and aggressive tumor of the brain. Genotype-based approaches and independent analyses of the transcriptome or the proteome have led to progress in understanding the underlying biology of GB. Joint transcriptome and proteome profiling may reveal new biological insights, and identify pathogenic mechanisms or therapeutic targets for GB therapy. We present a comparison of transcriptome and proteome data from five GB biopsies (TZ) vs their corresponding peritumoral brain zone (PBZ). Omic analyses were performed using RNA microarray chips and the isotope-coded protein label method (ICPL).

Results

As described in other cancers, we found a poor correlation between transcriptome and proteome data in GB. We observed only two commonly deregulated mRNAs/proteins (neurofilament light polypeptide and synapsin 1) and 12 altered biological processes; they are related to cell communication, synaptic transmission and nervous system processes. This poor correlation may be a consequence of the techniques used to produce the omic profiles, the intrinsic properties of mRNA and proteins and/or of cancer- or GB-specific phenomena. Of interest, the analysis of the transcription factor binding sites present upstream from the open reading frames of all altered proteins identified by ICPL method shows a common binding site for the topoisomerase I and p53-binding protein TOPORS. Its expression was observed in 7/11 TZ samples and not in PBZ. Some findings suggest that TOPORS may function as a tumor suppressor; its implication in gliomagenesis should be examined in future studies.

Conclusions

In this study, we showed a low correlation between transcriptome and proteome data for GB samples as described in other cancer tissues. We observed that NEFL, SYN1 and 12 biological processes were deregulated in both the transcriptome and proteome data. It will be important to analyze more specifically these processes and these two proteins to allow the identification of new theranostic markers or potential therapeutic targets for GB.

Electronic supplementary material

The online version of this article (10.1186/s12867-018-0115-6) contains supplementary material, which is available to authorized users.

Imaging and Histopathologic Nuances of Epithelioid Glioblastoma

A 27-year-old male without significant past medical history presented following collapse resulting from a syncopal episode at work. There was an episode of vomiting, and one of tonic-clonic seizure activity, which was spontaneously resolved after approximately one minute. His neurologic exam was nonfocal, with full strength in the bilateral upper and lower extremities, and no sensory deficits were elicited. MRI studies demonstrated a 4.7 cm rim-enhancing cystic mass in the right temporal-parietal region, with resultant mass effect and edema. At surgery, intraoperative pathologic consultation favoured a primary glial neoplasm. Subsequent complete histologic examination on permanent sections confirmed the presence of glioblastoma, with a morphologic pattern and immunohistochemical profile most consistent with epithelioid glioblastoma (WHO grade IV). Epithelioid glioblastoma is a rare, especially aggressive variant of IDH-wildtype glioblastoma, recognized in the 2016 World Health Organization classification. Approximately 50% of such tumors harbour the BRAF V600E mutation, which has also been observed in some melanomas where selective inhibitors have demonstrated a therapeutic role. The especially aggressive behaviour and poor clinical outcome typically observed for this variant of glioblastoma demonstrate the importance of emerging areas relevant to neurooncology, specifically those of proteomic characterization and therapeutic nanomedicine.

Sequencing the next generation of glioblastomas

The most aggressive brain malignancy, glioblastoma, accounts for 60-70% of all gliomas and is uniformly fatal. According to the molecular signature, glioblastoma is divided into four subtypes (proneural, neural, classical, and mesenchymal), each with its own genetic background. The Cancer Genome Atlas project provides information about the most common genetic changes in glioblastoma. They involve mutations in TP53, TERT, and PTEN, and amplifications in EFGR, PDGFRA, CDK4, CDK6, MDM2, and MDM4. Recently, epigenetics was used to demonstrate the oncogenic roles of miR-124, miR-137, and miR-128. The most important findings so far are mutations in IDH1/2 and MGMT promoter methylation, which are routinely used as predictive biomarkers in patient care. Current clinical treatment leaves patients with only a 10% chance for 5-year survival. Attempts to define the mutational profile of glioblastoma to identify clinically relevant changes have not yet yielded significant results. This can be attributed to inter- and intra-tumor heterogeneity that is present in most glioblastomas, as well as hypermutation that appears as a consequence of chemotherapy. The evolving field of radiogenomics aims to classify glioblastoma using a combination of magnetic resonance imaging and genomic information. In the era of genomic medicine, next-generation sequencing is extensively used in glioblastoma research because it can detect multiple changes in a single biological sample; its potential in detecting circulating cell-free DNA has been tested in cerebrospinal fluid and plasma, and it shows promise in the examination of the cellular content of extracellular vesicles as a potential source of biomarkers. Next-generation sequencing is making its way into glioblastoma diagnostics. Gene panels like GlioSeq, which includes the most commonly mutated genes, are currently being tested on snap frozen and formalin fixed paraffin embedded tissues. This new methodology is helping to define the "next generation of glioblastomas" - clinically defined and better understood, with greater potential to improve patient care. However, limitations of the necessary infrastructure, space for data storage, technical expertise, and data ownership need to be considered carefully.