A Systems Approach to Brain Tumor Treatment

An atlas of causal and mechanistic drivers of interpatient heterogeneity in glioma

Grade IV glioma, formerly known as glioblastoma multiforme (GBM) is the most aggressive and lethal type of brain tumor, and its treatment remains challenging in part due to extensive interpatient heterogeneity in disease driving mechanisms and lack of prognostic and predictive biomarkers. Using mechanistic inference of node-edge relationship (MINER), we have analyzed multiomics profiles from 516 patients and constructed an atlas of causal and mechanistic drivers of interpatient heterogeneity in GBM (gbmMINER). The atlas has delineated how 30 driver mutations act in a combinatorial scheme to causally influence a network of regulators (306 transcription factors and 73 miRNAs) of 179 transcriptional "programs", influencing disease progression in patients across 23 disease states. Through extensive testing on independent patient cohorts, we share evidence that a machine learning model trained on activity profiles of programs within gbmMINER significantly augments risk stratification, identifying patients who are super-responders to standard of care and those that would benefit from 2 nd line treatments. In addition to providing mechanistic hypotheses regarding disease prognosis, the activity of programs containing targets of 2 nd line treatments accurately predicted efficacy of 28 drugs in killing glioma stem-like cells from 43 patients. Our findings demonstrate that interpatient heterogeneity manifests from differential activities of transcriptional programs, providing actionable strategies for mechanistically characterizing GBM from a systems perspective and developing better prognostic and predictive biomarkers for personalized medicine.

Breaking Barriers: A Future Perspective on Glioblastoma Therapy with mRNA-Based Immunotherapies and Oncolytic Viruses

The use of mRNA-based immunotherapies that leverage the genomes of oncolytic viruses holds significant promise in addressing glioblastoma (GBM), an exceptionally aggressive neurological tumor. We explore the significance of mRNA-based platforms in the area of immunotherapy, introducing an innovative approach to mitigate the risks associated with the use of live viruses in cancer treatment. The ability to customize oncolytic virus genome sequences enables researchers to precisely target specific cancer cells, either through viral genome segments containing structural proteins or through a combination of regions with oncolytic potential. This strategy may enhance treatment effectiveness while minimizing unintended impacts on non-cancerous cells. A notable case highlighted here pertains to advanced findings regarding the application of the Zika virus (ZIKV) in GBM treatment. ZIKV, a member of the family Flaviviridae, shows oncolytic properties against GBM, opening novel therapeutic avenues. We explore intensive investigations of glioblastoma stem cells, recognized as key drivers in GBM initiation, progression, and resistance to therapy. However, a comprehensive elucidation of ZIKV's underlying mechanisms is imperative to pave the way for ZIKV-based clinical trials targeting GBM patients. This investigation into harnessing the potential of oncolytic-virus genomes for mRNA-based immunotherapies underscores its noteworthy implications, potentially paving the way for a paradigm shift in cancer treatment strategies.

Advances in Glioblastoma Therapy: An Update on Current Approaches

Glioblastoma multiforme (GBM) is a primary malignant brain tumor characterized by a high grade of malignancy and an extremely unfavorable prognosis. The current efficacy of established treatments for GBM is insufficient, necessitating the prompt development of novel therapeutic approaches. The progress made in the fundamental scientific understanding of GBM is swiftly translated into more advanced stages of therapeutic studies. Despite extensive efforts to identify new therapeutic approaches, GBM exhibits a high mortality rate. The current efficacy of treatments for GBM patients is insufficient due to factors such as tumor heterogeneity, the blood-brain barrier, glioma stem cells, drug efflux pumps, and DNA damage repair mechanisms. Considering this, pharmacological cocktail therapy has demonstrated a growing efficacy in addressing these challenges. Towards this, various forms of immunotherapy, including the immune checkpoint blockade, chimeric antigen receptor T (CAR T) cell therapy, oncolytic virotherapy, and vaccine therapy have emerged as potential strategies for enhancing the prognosis of GBM. Current investigations are focused on exploring combination therapies to mitigate undesirable side effects and enhance immune responses against tumors. Furthermore, clinical trials are underway to evaluate the efficacy of several strategies to circumvent the blood-brain barrier (BBB) to achieve targeted delivery in patients suffering from recurrent GBM. In this review, we have described the biological and molecular targets for GBM therapy, pharmacologic therapy status, prominent resistance mechanisms, and new treatment approaches. We also discuss these promising therapeutic approaches to assess prospective innovative therapeutic agents and evaluated the present state of preclinical and clinical studies in GBM treatment. Overall, this review attempts to provide comprehensive information on the current status of GBM therapy.

Systems Medicine for Precise Targeting of Glioblastoma

Glioblastoma (GBM) is a malignant cancer that is fatal even after standard therapy and the effects of current available therapeutics are not promising due its complex and evolving epigenetic and genetic profile. The mysteries that lead to GBM intratumoral heterogeneity and subtype transitions are not entirely clear. Systems medicine is an approach to view the patient in a whole picture integrating systems biology and synthetic biology along with computational techniques. Since the GBM oncogenesis involves genetic mutations, various therapies including gene therapeutics based on CRISPR-Cas technique, MicroRNAs, and implanted synthetic cells endowed with synthetic circuits against GBM with neural stem cells and mesenchymal stem cells acting as potential vehicles carrying therapeutics via the intranasal route, avoiding the risks of invasive methods in order to reach the GBM cells in the brain are discussed and proposed in this review. Systems medicine approach is a rather novel strategy, and since the GBM of a patient is complex and unique, thus to devise an individualized treatment strategy to tailor personalized multimodal treatments for the individual patient taking into account the phenotype of the GBM, the unique body health profile of the patient and individual responses according to the systems medicine concept might show potential to achieve optimum effects.

Precision medicine in neurosurgery: The evolving role of theranostics

Theranostics in neurosurgery is a rapidly advancing field of precision medicine that combines diagnostic and therapeutic modalities to optimize patient outcomes. This approach has the potential to provide real-time feedback during therapy and diagnose a condition while simultaneously providing treatment. One such form of theranostics is focused ultrasound, which has been found to be effective in inducing neuroablation and neuromodulation and improving the efficacy of chemotherapy drugs by disrupting the blood-brain barrier. Targeted radionuclide therapy, which pairs positron emission tomography tracers with therapeutic effects and imaging modalities, is another promising form of theranostics for neurosurgery. Automated pathology analysis is yet another form of theranostics that can provide real-time feedback during the surgical resection of tumors. Electrical stimulation has also shown promise in optimizing therapies for patients with cerebral palsy. Overall, theranostics is a cost-effective way to optimize medical care for patients in neurosurgery. It is a relatively new field, but the advancements made so far show great promise for improving patient outcomes.

Liposomes for the Treatment of Brain Cancer-A Review

Due to their biocompatibility, non-toxicity, and surface-conjugation capabilities, liposomes are effective nanocarriers that can encapsulate chemotherapeutic drugs and facilitate targeted delivery across the blood-brain barrier (BBB). Additionally, strategies have been explored to synthesize liposomes that respond to internal and/or external stimuli to release their payload controllably. Although research into liposomes for brain cancer treatment is still in its infancy, these systems have great potential to fundamentally change the drug delivery landscape. This review paper attempts to consolidate relevant literature regarding the delivery to the brain using nanocarriers, particularly liposomes. The paper first briefly explains conventional treatment modalities for cancer, followed by describing the blood-brain barrier and ways, challenges, and techniques involved in transporting drugs across the BBB. Various nanocarrier systems are introduced, with attention to liposomes, due to their ability to circumvent the challenges imposed by the BBB. Relevant studies involving liposomal systems researched to treat brain tumors are reviewed in vitro, in vivo, and clinical studies. Finally, the challenges associated with the use of liposomes to treat brain tumors and how they can be addressed are presented.

ETISTP: An Enhanced Model for Brain Tumor Identification and Survival Time Prediction

Technology-assisted diagnosis is increasingly important in healthcare systems. Brain tumors are a leading cause of death worldwide, and treatment plans rely heavily on accurate survival predictions. Gliomas, a type of brain tumor, have particularly high mortality rates and can be further classified as low- or high-grade, making survival prediction challenging. Existing literature provides several survival prediction models that use different parameters, such as patient age, gross total resection status, tumor size, or tumor grade. However, accuracy is often lacking in these models. The use of tumor volume instead of size may improve the accuracy of survival prediction. In response to this need, we propose a novel model, the enhanced brain tumor identification and survival time prediction (ETISTP), which computes tumor volume, classifies it into low- or high-grade glioma, and predicts survival time with greater accuracy. The ETISTP model integrates four parameters: patient age, survival days, gross total resection (GTR) status, and tumor volume. Notably, ETISTP is the first model to employ tumor volume for prediction. Furthermore, our model minimizes the computation time by allowing for parallel execution of tumor volume computation and classification. The simulation results demonstrate that ETISTP outperforms prominent survival prediction models.

Applications and current challenges of chimeric antigen receptor T cells in treating high-grade gliomas in adult and pediatric populations

High-grade gliomas (HGGs) continue to be some of the most devastating diseases in the USA. Despite extensive efforts, the survival of HGG patients has remained relatively stagnant. Chimeric antigen receptor (CAR) T-cell immunotherapy has recently been studied in the context of improving these tumors' clinical outcomes. HGG murine models treated with CAR T cells targeting tumor antigens have shown reduced tumor burden and longer overall survival than models without treatment. Subsequent clinical trials investigating the efficacy of CAR T cells have further shown that this therapy could be safe and might reduce tumor burden. However, there are still many challenges that need to be addressed to optimize the safety and efficacy of CAR T-cell therapy in treating HGG patients.

Nano-inspired smart medicines targeting brain cancer: diagnosis and treatment

Cancer, despite being the bull's eye for the research community, accounts for a large number of morbidity and mortality. Cancer of the brain is considered the most intractable, with the least diagnosis rates, hence treatment and survival. Despite the extensive development of therapeutic molecules, their targeting to the diseased site is a challenge. Specially tailored nanoparticles can efficiently deliver drugs and genes to the brain to treat tumours and diseases. These nanotechnology-based strategies target the blood-brain barrier, the local space, or a specific cell type. These nanoparticles are preferred over other forms of targeted drug delivery due to the chances for controlled delivery of therapeutic cargo to the intended receptor. Targeted cancer therapy involves using specific receptor-blocking compounds that block the spreading or growth of cancerous cells. This review presents an account of the recent applications of nano-based cancer theragnostic, which deal in conjunct functionalities of nanoparticles for effective diagnosis and treatment of cancer. It commences with an introduction to tumours of the brain and their grades, followed by hurdles in its conventional diagnosis and treatment. The characteristic mechanism of nanoparticles for efficiently tracing brain tumour grade and delivery of therapeutic genes or drugs has been summarised. Nanocarriers like liposomes have been widely used and commercialized for human brain cancer treatment. However, nano-inspired structures await their translational recognition. The green synthesis of nanomaterials and their advantages have been discussed. The article highlights the challenges in the nano-modulation of brain cancer and its future outlook.

Fibrinogen-like protein 2: Its biological function across cell types and the potential to serve as an immunotherapy target for brain tumors

Brain tumors are among the 10 leading causes of cancer-related death and present unique treatment challenges due to their critical location, genetic heterogeneity, and the blood-brain barrier. Recent advances in targeted immunotherapy and immune checkpoint blocking therapy provide alternative therapeutic strategies for brain tumors. Fibrinogen-like protein 2 (FGL2), which induces transformation from low-grade glioma to high-grade glioblastoma, is a type II membrane protein that is highly expressed in both host immune cells and tumor cells. Studies have uncovered multiple forms of FGL2 proteins with a broad range of roles in inducing immune tolerance and avoiding immune surveillance in tumor cells. Of note, presence of FGL2 transforms low grade to high grade brain tumors via promoting Treg, macrophages, and perhaps stemness. Absence (knockout) of FGL2 in tumor cells (not in host cells) induces CD103 DC cells, which triggers tumor specific CD8 +T cell activity to reject brain tumor progression. Immunotherapies targeting FGL2 have shown great promise in improving survival time in murine models. In this article, we will summarize the biological function of FGL2 in immune and tumor cells.

Mesenchymal stem cell-derived exosomes as a new therapeutic strategy in the brain tumors

Brain tumors are one of the most mortal cancers, leading to many deaths among kids and adults. Surgery, chemotherapy, and radiotherapy are available options for brain tumor treatment. However, these methods are not able to eradicate cancer cells. The blood-brain barrier (BBB) is one of the most important barriers to treat brain tumors that prevents adequate drug delivery to brain tissue. The connection between different brain parts is heterogeneous and causes many challenges in treatment. Mesenchymal stem cells (MSCs) migrate to brain tumor cells and have anti-tumor effects by delivering cytotoxic compounds. They contain very high regenerative properties, as well as support the immune system. MSCs-based therapy involves cell replacement and releases various vesicles, including exosomes. Exosomes receive more attention due to their excellent stability, less immunogenicity and toxicity compare to cells. Exosomes derived from MSCs can develop a powerful therapeutic strategy for different diseases and be a hopeful candidate for cell-based and cell-free regenerative medicine. These nanoparticles contain nucleic acid, proteins, lipids, microRNAs, and other biologically active substances. Many studies show that each microRNA can prevent angiogenesis, migration, and metastasis in glioblastoma. These exosomes can-act as a suitable nanoparticle carrier for therapeutic applications of brain tumors by passing through the BBB. In this review, we discuss potential applications of MSC and their produced exosomes in the treatment of brain tumors.

Particle Swarm Optimization and Two-Way Fixed-Effects Analysis of Variance for Efficient Brain Tumor Segmentation

Simple Summary

Segmentation of brain tumor images from magnetic resonance imaging (MRI) is a challenging topic in medical image analysis. The brain tumor can take many shapes, and MRI images vary considerably in intensity, making lesion detection difficult for radiologists. This paper proposes a three-step approach to solving this problem: (1) pre-processing, based on morphological operations, is applied to remove the skull bone from the image; (2) the particle swarm optimization (PSO) algorithm, with a two-way fixed-effects analysis of variance (ANOVA)-based fitness function, is used to find the optimal block containing the brain lesion; (3) the K-means clustering algorithm is adopted, to classify the detected block as tumor or non-tumor. An extensive experimental analysis, including visual and statistical evaluations, was conducted, using two MRI databases: a private database provided by the Kouba imaging center—Algiers (KICA)—and the multimodal brain tumor segmentation challenge (BraTS) 2015 database. The results show that the proposed methodology achieved impressive performance, compared to several competing approaches.

Abstract

Segmentation of brain tumor images, to refine the detection and understanding of abnormal masses in the brain, is an important research topic in medical imaging. This paper proposes a new segmentation method, consisting of three main steps, to detect brain lesions using magnetic resonance imaging (MRI). In the first step, the parts of the image delineating the skull bone are removed, to exclude insignificant data. In the second step, which is the main contribution of this study, the particle swarm optimization (PSO) technique is applied, to detect the block that contains the brain lesions. The fitness function, used to determine the best block among all candidate blocks, is based on a two-way fixed-effects analysis of variance (ANOVA). In the last step of the algorithm, the K-means segmentation method is used in the lesion block, to classify it as a tumor or not. A thorough evaluation of the proposed algorithm was performed, using: (1) a private MRI database provided by the Kouba imaging center—Algiers (KICA); (2) the multimodal brain tumor segmentation challenge (BraTS) 2015 database. Estimates of the selected fitness function were first compared to those based on the sum-of-absolute-differences (SAD) dissimilarity criterion, to demonstrate the efficiency and robustness of the ANOVA. The performance of the optimized brain tumor segmentation algorithm was then compared to the results of several state-of-the-art techniques. The results obtained, by using the Dice coefficient, Jaccard distance, correlation coefficient, and root mean square error (RMSE) measurements, demonstrated the superiority of the proposed optimized segmentation algorithm over equivalent techniques.

Spatial organization of heterogeneous immunotherapy target antigen expression in high-grade glioma

High-grade (WHO grades III-IV) glioma remains one of the most lethal human cancers. Adoptive transfer of tumor-targeting chimeric antigen receptor (CAR)-redirected T cells for high-grade glioma has revealed promising indications of anti-tumor activity, but objective clinical responses remain elusive for most patients. A significant challenge to effective immunotherapy is the highly heterogeneous structure of these tumors, including large variations in the magnitudes and distributions of target antigen expression, observed both within individual tumors and between patients. To obtain a more detailed understanding of immunotherapy target antigens within patient tumors, we immunochemically mapped at single cell resolution three clinically-relevant targets, IL13Rα2, HER2 and EGFR, on tumor samples drawn from a 43-patient cohort. We observed that within individual tumor samples, expression of these antigens was neither random nor uniform, but rather that they mapped into local neighborhoods - phenotypically similar cells within regions of cellular tumor - reflecting not well understood properties of tumor cells and their milieu. Notably, tumor cell neighborhoods of high antigen expression were not arranged independently within regions. For example, in cellular tumor regions, neighborhoods of high IL13Rα2 and HER2 expression appeared to be reciprocal to those of EGFR, while in areas of pseudopalisading necrosis, expression of IL13Rα2 and HER2, but not EGFR, appeared to reflect the radial organization of tumor cells around hypoxic cores. Other structural features affecting expression of immunotherapy target antigens remain to be elucidated. This structured but heterogeneous organization of antigen expression in high grade glioma is highly permissive for antigen escape, and combinatorial antigen targeting is a commonly suggested potential mitigating strategy. Deeper understanding of antigen expression within and between patient tumors will enhance optimization of combination immunotherapies, the most immediate clinical application of the observations presented here being the importance of including (wild-type) EGFR as a target antigen.

Prognostic/predictive markers in systemic therapy resistance and metastasis in breast cancer

Breast cancer is a highly heterogeneous group of diseases posing a significant challenge in biomarker-driven research and the development of effective targeted therapies. Especially the treatment of metastatic breast cancer poses even more challenges, as we still lose more than 42,000 women and men each year in the United States alone. New biological insight helps to improve breast cancer treatment through early detection, adaptation to chemotherapy resistance, and tailoring to find the right size of care. This review focuses on existing and new areas of predictive biomarkers under development to tailor the management of breast cancer and the application of integrative approaches that have resulted in the promising candidate biomarker discovery. Furthermore, we review new methods to detect metastatic progression using imaging, and blood-based assays. We hope to increase the attention and awareness of a new generation of therapeutic development strategies in metastatic breast cancer.

Suicide gene therapy in cancer and HIV-1 infection: An alternative to conventional treatments

Suicide Gene Therapy (SGT) aims to introduce a gene encoding either a toxin or an enzyme making the targeted cell more sensitive to chemotherapy. SGT represents an alternative approach to combat pathologies where conventional treatments fail such as pancreatic cancer or the high-grade glioblastoma which are still desperately lethal. We review the possibility to use SGT to treat these cancers which have shown promising results in vitro and in preclinical trials. However, SGT has so far failed in phase III clinical trials thus further improvements are awaited. We can now take advantages of the many advances made in SGT for treating cancer to combat other pathologies such as HIV-1 infection. In the review we also discuss the feasibility to add SGT to the therapeutic arsenal used to cure HIV-1-infected patients. Indeed, preliminary results suggest that both productive and latently infected cells are targeted by the SGT. In the last section, we address the limitations of this approach and how we might improve it.

Profiling Glioblastoma Cases with an Expression of DCX, OLIG2 and NES

Glioblastoma (GBM) remains the leading cause of cancer-related deaths with the lowest five-year survival rates among all of the human cancers. Multiple factors contribute to its poor outcome, including intratumor heterogeneity, along with migratory and invasive capacities of tumour cells. Over the last several years Doublecortin (DCX) has been one of the debatable factors influencing GBM cells’ migration. To resolve DCX’s ambiguous role in GBM cells’ migration, we set to analyse the expression patterns of DCX along with Nestin (NES) and Oligodendrocyte lineage transcription factor 2 (OLIG2) in 17 cases of GBM, using immunohistochemistry, followed by an analysis of single-cell RNA-seq data. Our results showed that only a small subset of DCX positive (DCX⁺) cells was present in the tumour. Moreover, no particular pattern emerged when analysing DCX⁺ cells relative position to the tumour margin. By looking into single-cell RNA-seq data, the majority of DCX⁺ cells were classified as non-cancerous, with a small subset of cells that could be regarded as glioma stem cells. In conclusion, our findings support the notion that glioma cells express DCX; however, there is no clear evidence to prove that DCX participates in GBM cell migration.

Genomic and Transcriptomic Profiling of Brain Metastases

Simple Summary

Brain metastases (BM) are the most common brain tumors in adults and are the main cause of cancer-associated death. Omics analysis of BM will allow for a better understanding of metastatic progression, prognosis and therapeutic targeting. In this study, BM samples underwent comprehensive molecular profiling with genomics and transcriptomics. Mutational signatures suggested that most mutations were gained prior to metastasis. A novel copy number event centered around the MCL1 gene was found in 75% of all samples. Transcriptomics revealed that melanoma BM formed a distinct cluster in comparison to other subtypes. Poor survival correlated to self-identified black race and absence of radiation treatment but not molecular profiles. These data identify potential new drivers of brain metastatic progression, implicate that melanoma BM are distinctive and likely responsive to unique therapies, and further investigation of sociodemographic and clinical features are needed in BM cohorts.

Abstract

Brain metastases (BM) are the most common brain tumors in adults occurring in up to 40% of all cancer patients. Multi-omics approaches allow for understanding molecular mechanisms and identification of markers with prognostic significance. In this study, we profile 130 BM using genomics and transcriptomics and correlate molecular characteristics to clinical parameters. The most common tumor origins for BM were lung (40%) followed by melanoma (21%) and breast (15%). Melanoma and lung BMs contained more deleterious mutations than other subtypes (p < 0.001). Mutational signatures suggested that the bulk of the mutations were gained before metastasis. A novel copy number event centered around the MCL1 gene was found in 75% of all samples, suggesting a broader role in promoting metastasis. Unsupervised hierarchical cluster analysis of transcriptional signatures available in 65 samples based on the hallmarks of cancer revealed four distinct clusters. Melanoma samples formed a distinctive cluster in comparison to other BM subtypes. Characteristics of molecular profiles did not correlate with survival. However, patients with self-identified black race or those who did not receive radiation correlated with poor survival. These data identify potential new drivers of brain metastatic progression. Our data also suggest further investigation of sociodemographic and clinical features is needed in BM cohorts.

Sulforaphane Causes Cell Cycle Arrest and Apoptosis in Human Glioblastoma U87MG and U373MG Cell Lines under Hypoxic Conditions

Glioblastoma multiforme (GBM) is the most prevalent and aggressive primary brain tumor. The median survival rate from diagnosis ranges from 15 to 17 months because the tumor is resistant to most therapeutic strategies. GBM exhibits microvascular hyperplasia and pronounced necrosis triggered by hypoxia. Sulforaphane (SFN), an isothiocyanate derived from cruciferous vegetables, has already demonstrated the ability to inhibit cell proliferation, by provoking cell cycle arrest, and leading to apoptosis in many cell lines. In this study, we investigated the antineoplastic effects of SFN [20-80 μM for 48 h] in GBM cells under normoxic and hypoxic conditions. Cell viability assays, flow cytometry, and Western blot results revealed that SFN could induce apoptosis of GBM cells in a dose-dependent manner, under both conditions. In particular, SFN significantly induced caspase 3/7 activation and DNA fragmentation. Moreover, our results demonstrated that SFN suppressed GBM cells proliferation by arresting the cell cycle at the S-phase, also under hypoxic condition, and that these effects may be due in part to its ability to induce oxidative stress by reducing glutathione levels and to increase the phosphorylation of extracellular signal-regulated kinases (ERKs). Overall, we hypothesized that SFN treatment might serve as a potential therapeutic strategy, alone or in combination, against GBM.

Chromatin insulation dynamics in glioblastoma: challenges and future perspectives of precision oncology

Glioblastoma (GBM) is the most aggressive primary brain tumor, having a poor prognosis and a median overall survival of less than two years. Over the last decade, numerous findings regarding the distinct molecular and genetic profiles of GBM have led to the emergence of several therapeutic approaches. Unfortunately, none of them has proven to be effective against GBM progression and recurrence. Epigenetic mechanisms underlying GBM tumor biology, including histone modifications, DNA methylation, and chromatin architecture, have become an attractive target for novel drug discovery strategies. Alterations on chromatin insulator elements (IEs) might lead to aberrant chromatin remodeling via DNA loop formation, causing oncogene reactivation in several types of cancer, including GBM. Importantly, it is shown that mutations affecting the isocitrate dehydrogenase (IDH) 1 and 2 genes, one of the most frequent genetic alterations in gliomas, lead to genome-wide DNA hypermethylation and the consequent IE dysfunction. The relevance of IEs has also been observed in a small population of cancer stem cells known as glioma stem cells (GSCs), which are thought to participate in GBM tumor initiation and drug resistance. Recent studies revealed that epigenomic alterations, specifically chromatin insulation and DNA loop formation, play a crucial role in establishing and maintaining the GSC transcriptional program. This review focuses on the relevance of IEs in GBM biology and their implementation as a potential theranostic target to stratify GBM patients and develop novel therapeutic approaches. We will also discuss the state-of-the-art emerging technologies using big data analysis and how they will settle the bases on future diagnosis and treatment strategies in GBM patients.