Glioblastoma multiforme: a multi-omics analysis of driver genes and tumour heterogeneity

Machine learning unravels the mysteries of glioma typing and treatment

Gliomas, which are complex primary malignant brain tumors known for their heterogeneous and invasive nature, present substantial challenges for both treatment and prognosis. Recent advancements in whole-genome studies have opened new avenues for investigating glioma mechanisms and therapies. Through single-cell analysis, we identified a specific cluster of cancer cell-related genes within gliomas. By leveraging diverse datasets and employing non-negative matrix factorization (NMF), we developed a glioma subtyping method grounded in this identified gene set. Our exploration delved into the clinical implications and underlying regulatory frameworks of the newly defined subtype classification, revealing its intimate ties to glioma malignancy and prognostic outcomes. Comparative assessments between the identified subtypes revealed differences in clinical features, immune modulation, and the tumor microenvironment (TME). Using tools such as the limma R package, weighted gene co-expression network analysis (WGCNA), machine learning methodologies, survival analyses, and protein-protein interaction (PPI) networks, we identified key driver genes influencing subtype differentiation while quantifying associated outcomes. This study not only sheds light on the biological mechanisms within gliomas but also paves the way for precise molecular targeted therapies within this intricate disease landscape.

In Silico and In Vitro Study of mRNA Biomarkers for Glioblastoma Multiforme Resistance to Temozolomide (TMZ): The Association with Stemness

BACKGROUND

Glioblastoma multiforme (GBM) is an aggressive brain tumor that primarily affects adults. The Stupp Protocol, which includes surgical resection, chemoradiation, and monotherapy with temozolomide (TMZ), is the standard treatment regimen for GBM. However, repeated use of TMZ leads to resistance in GBM cells, resulting in a poor prognosis for patients. This resistance is driven by several intrinsic factors. This study aims to identify potential biomarkers of resistance associated with stemness.

METHODS

We utilized datasets from GEO, performed Venn diagram intersection analysis, conducted GO enrichment analysis using DAVID and ENRICHR, carried out pathway enrichment analysis with KEGG and REACTOME, and executed survival analysis with GEPIA. Additionally, we compared mRNA expression using the Human Protein Atlas and validated our findings with qRT-PCR.

RESULTS

We identified that PAQR6 and ITPKB mRNA expression was consistently higher in TMZ-resistant T98G cells, but TGFBI mRNA expression was found to be significantly higher in TMZ-resistant T98G cells compared to U87MG cells. In addition, a significantly higher CD133 mRNA expression as a stemness marker was found in T98G cells compared to U87MG cells. It is hoped that the acquired disease-related resistance biomarker candidates will be able to be used at the clinical level in terms of non-invasive early detection in GBM patients. However, additional research is required to validate the findings of this preliminary biomarker discovery study.

Predictive and Prognostic Significance of Molecular Biomarkers in Glioblastoma

Glioblastoma multiforme (GBM), a WHO grade 4 glioma, is the most common and aggressive primary brain tumor, characterized by rapid progression and poor prognosis. The heterogeneity of GBM complicates diagnosis and treatment, driving research into molecular biomarkers that can offer insights into tumor behavior and guide personalized therapies. This review explores recent advances in molecular biomarkers, highlighting their potential to improve diagnosis and treatment outcomes in GBM patients. Key biomarkers such as MGMT promoter methylation, IDH1/2 mutations, EGFR amplification, and TERT promoter mutations, etc., are examined for their roles in prognosis, therapeutic response, and tumor classification. While molecular biomarkers offer valuable insights for tailoring GBM treatments, their clinical application is hindered by tumor heterogeneity, dynamic genetic evolution, and the lack of standardized testing methods. Future research should aim to confirm new biomarkers and incorporate them into regular clinical practice to improve prognosis and treatment choices. Advances in genomic and proteomic technologies, along with consistent biomarker detection, could transform GBM care and enhance patient outcomes.

Evolution of Molecular Biomarkers and Precision Molecular Therapeutic Strategies in Glioblastoma

Glioblastoma is the most commonly occurring malignant brain tumor, with a high mortality rate despite current treatments. Its classification has evolved over the years to include not only histopathological features but also molecular findings. Given the heterogeneity of glioblastoma, molecular biomarkers for diagnosis have become essential for initiating treatment with current therapies, while new technologies for detecting specific variations using computational tools are being rapidly developed. Advances in molecular genetics have made possible the creation of tailored therapies based on specific molecular targets, with various degrees of success. This review provides an overview of the latest advances in the fields of histopathology and radiogenomics and the use of molecular markers for management of glioblastoma, as well as the development of new therapies targeting the most common molecular markers. Furthermore, we offer a summary of the results of recent preclinical and clinical trials to recognize the current trends of investigation and understand the possible future directions of molecular targeted therapies in glioblastoma.

Identification of an Immune signature assisted prognosis, and immunotherapy prediction for IDH wildtype glioblastoma

IDH-wildtype glioblastoma (GBM) is the most common and malignant primary brain tumor. The purpose of this study is to establish a prognostic gene signature for IDH-wildtype GBM. RNA sequencing data of normal brain tissue and GBM patients were obtained from TCGA, CGGA, GEO and the GTEx databases. Identification of prognostic differentially expressed genes (DEGs) with | log2 fold change | > 0.5 and adjust p < 0.05 in TCGA and CGGA databases by "limma" method. By LASSO regression analysis and multivariate Cox analysis, a 3-gene prognostic signature composed of FMOD, MXRA5 and RAB36 was established. The 3-gene prognostic risk model is validated by TCGA and GSE43378 datasets. The expression of FMOD, MXRA5 and RAB36 in GBM patients was significantly higher than that in normal brain tissues in CCGA, TCGA and GSE29796 data sets. In order to further verify this result, total RNA was extracted from tumors and paracancerous tissues of 9 GBM patients. RT-PCR results showed that the expression of FMOD, MXRA5 and RAB36 in tumor tissues of most patients was higher than that in paracancerous tissues. The results of GSEA showed that the pathway enrichment of the 3-gene signature was mainly related to tumor immunity. Immune cell infiltration analyzed by ssGSEA showed that there were significant differences in macrophages between high- and low-risk groups. Immune checkpoint genes correlation analysis showed that PD-L1 gene expression is closely related to risk score. Our study identifies a prognostic-associated risk model and provides a potential effective immunotherapy target for IDH-wildtype GBM patients.

Nrf2/Keap1/ARE regulation by plant secondary metabolites: a new horizon in brain tumor management

Brain cancer is regarded as one of the most life-threatening forms of cancer worldwide. Oxidative stress acts to derange normal brain homeostasis, thus is involved in carcinogenesis in brain. The Nrf2/Keap1/ARE pathway is an important signaling cascade responsible for the maintenance of redox homeostasis, and regulation of anti-inflammatory and anticancer activities by multiple downstream pathways. Interestingly, Nrf2 plays a somewhat, contradictory role in cancers, including brain cancer. Nrf2 has traditionally been regarded as a tumor suppressor since its cytoprotective functions are considered to be the principle cellular defense mechanism against exogenous and endogenous insults, such as xenobiotics and oxidative stress. However, hyperactivation of the Nrf2 pathway supports the survival of normal as well as malignant cells, protecting them against oxidative stress, and therapeutic agents. Plants possess a pool of secondary metabolites with potential chemotherapeutic/chemopreventive actions. Modulation of Nrf2/ARE and downstream activities in a Keap1-dependant manner, with the aid of plant-derived secondary metabolites exhibits promise in the management of brain tumors. Current article highlights the effects of Nrf2/Keap1/ARE cascade on brain tumors, and the potential role of secondary metabolites regarding the management of the same.

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.

Understanding Glioblastoma Signaling, Heterogeneity, Invasiveness, and Drug Delivery Barriers

The most prevalent and aggressive type of brain cancer, namely, glioblastoma (GBM), is characterized by intra- and inter-tumor heterogeneity and strong spreading capacity, which makes treatment ineffective. A true therapeutic answer is still in its infancy despite various studies that have made significant progress toward understanding the mechanisms behind GBM recurrence and its resistance. The primary causes of GBM recurrence are attributed to the heterogeneity and diffusive nature; therefore, monitoring the tumor's heterogeneity and spreading may offer a set of therapeutic targets that could improve the clinical management of GBM and prevent tumor relapse. Additionally, the blood-brain barrier (BBB)-related poor drug delivery that prevents effective drug concentrations within the tumor is discussed. With a primary emphasis on signaling heterogeneity, tumor infiltration, and computational modeling of GBM, this review covers typical therapeutic difficulties and factors contributing to drug resistance development and discusses potential therapeutic approaches.

Targeting GBM with an Oncolytic Picornavirus SVV-001 alone and in combination with fractionated Radiation in a Novel Panel of Orthotopic PDX models

BACKGROUND

Animal models representing different molecular subtypes of glioblastoma multiforme (GBM) is desired for developing new therapies. SVV-001 is an oncolytic virus selectively targeting cancer cells. It's capacity of passing through the blood brain barrier makes is an attractive novel approach for GBM.

MATERIALS AND METHODS

23 patient tumor samples were implanted into the brains of NOD/SCID mice (1 × 105 cells/mouse). Tumor histology, gene expression (RNAseq), and growth rate of the developed patient-derived orthotopic xenograft (PDOX) models were compared with the originating patient tumors during serial subtransplantations. Anti-tumor activities of SVV-001 were examined in vivo; and therapeutic efficacy validated in vivo via single i.v. injection (1 × 1011 viral particle) with or without fractionated (2 Gy/day x 5 days) radiation followed by analysis of animal survival times, viral infection, and DNA damage.

RESULTS

PDOX formation was confirmed in 17/23 (73.9%) GBMs while maintaining key histopathological features and diffuse invasion of the patient tumors. Using differentially expressed genes, we subclassified PDOX models into proneural, classic and mesenchymal groups. Animal survival times were inversely correlated with the implanted tumor cells. SVV-001 was active in vitro by killing primary monolayer culture (4/13 models), 3D neurospheres (7/13 models) and glioma stem cells. In 2/2 models, SVV-001 infected PDOX cells in vivo without harming normal brain cells and significantly prolonged survival times in 2/2 models. When combined with radiation, SVV-001 enhanced DNA damages and further prolonged animal survival times.

CONCLUSION

A panel of 17 clinically relevant and molecularly annotated PDOX modes of GBM is developed, and SVV-001 exhibited strong anti-tumor activities in vitro and in vivo.

Glioblastoma modeling with 3D organoids: progress and challenges

Glioblastoma (GBM) is the most aggressive adult primary brain tumor with nearly universal treatment resistance and recurrence. The mainstay of therapy remains maximal safe surgical resection followed by concurrent radiation therapy and temozolomide chemotherapy. Despite intensive investigation, alternative treatment options, such as immunotherapy or targeted molecular therapy, have yielded limited success to achieve long-term remission. This difficulty is partly due to the lack of pre-clinical models that fully recapitulate the intratumoral and intertumoral heterogeneity of GBM and the complex tumor microenvironment. Recently, GBM 3D organoids originating from resected patient tumors, genetic manipulation of induced pluripotent stem cell (iPSC)-derived brain organoids and bio-printing or fusion with non-malignant tissues have emerged as novel culture systems to portray the biology of GBM. Here, we highlight several methodologies for generating GBM organoids and discuss insights gained using such organoid models compared to classic modeling approaches using cell lines and xenografts. We also outline limitations of current GBM 3D organoids, most notably the difficulty retaining the tumor microenvironment, and discuss current efforts for improvements. Finally, we propose potential applications of organoid models for a deeper mechanistic understanding of GBM and therapeutic development.

The complexities underlying epilepsy in people with glioblastoma

Seizures are among the most common clinical signs in people with glioblastoma. Advances over the past 5 years, including new clinical trial data, have increased the understanding of why some individuals with glioblastoma are susceptible to seizures, how seizures manifest clinically, and what implications seizures have for patient management. The pathophysiology of epilepsy in people with glioblastoma relates to a combination of intrinsic epileptogenicity of tumour tissue, alterations in the tumour and peritumoural microenvironment, and the physical and functional disturbance of adjacent brain structures. Successful management of epilepsy in people with glioblastoma remains challenging; factors such as drug-drug interactions between cancer therapies and antiseizure medications, and medication side-effects, can affect seizure outcomes and quality of life. Advances in novel therapies provide some promise for people with glioblastoma; however, the effects of these therapies on seizures are yet to be fully determined. Looking forward, insights into electrical activity as a driver of tumour cell growth and the intrinsic hyperexcitability of tumour tissue might represent useful targets for treatment and disease modification. There is a pressing need for large randomised clinical trials in this field.

The anterior gradient homologue 2 (AGR2) co-localises with the glucose-regulated protein 78 (GRP78) in cancer stem cells, and is critical for the survival and drug resistance of recurrent glioblastoma: in situ and in vitro analyses

BACKGROUND

Glioblastomas (GBs) are characterised as one of the most aggressive primary central nervous system tumours (CNSTs). Single-cell sequencing analysis identified the presence of a highly heterogeneous population of cancer stem cells (CSCs). The proteins anterior gradient homologue 2 (AGR2) and glucose-regulated protein 78 (GRP78) are known to play critical roles in regulating unfolded protein response (UPR) machinery. The UPR machinery influences cell survival, migration, invasion and drug resistance. Hence, we investigated the role of AGR2 in drug-resistant recurrent glioblastoma cells.

METHODS

Immunofluorescence, biological assessments and whole exome sequencing analyses were completed under in situ and in vitro conditions. Cells were treated with CNSTs clinical/preclinical drugs taxol, cisplatin, irinotecan, MCK8866, etoposide, and temozolomide, then resistant cells were analysed for the expression of AGR2. AGR2 was repressed using single and double siRNA transfections and combined with either temozolomide or irinotecan.

RESULTS

Genomic and biological characterisations of the AGR2-expressed Jed66_GB and Jed41_GB recurrent glioblastoma tissues and cell lines showed features consistent with glioblastoma. Immunofluorescence data indicated that AGR2 co-localised with the UPR marker GRP78 in both the tissue and their corresponding primary cell lines. AGR2 and GRP78 were highly expressed in glioblastoma CSCs. Following treatment with the aforementioned drugs, all drug-surviving cells showed high expression of AGR2. Prolonged siRNA repression of a particular region in AGR2 exon 2 reduced AGR2 protein expression and led to lower cell densities in both cell lines. Co-treatments using AGR2 exon 2B siRNA in conjunction with temozolomide or irinotecan had partially synergistic effects. The slight reduction of AGR2 expression increased nuclear Caspase-3 activation in both cell lines and caused multinucleation in the Jed66_GB cell line.

CONCLUSIONS

AGR2 is highly expressed in UPR-active CSCs and drug-resistant GB cells, and its repression leads to apoptosis, via multiple pathways.

An update on the molecular biology of glioblastoma, with clinical implications and progress in its treatment

Glioblastoma multiforme (GBM) is the most aggressive and common malignant primary brain tumor. Patients with GBM often have poor prognoses, with a median survival of ∼15 months. Enhanced understanding of the molecular biology of central nervous system tumors has led to modifications in their classifications, the most recent of which classified these tumors into new categories and made some changes in their nomenclature and grading system. This review aims to give a panoramic view of the last 3 years' findings in glioblastoma characterization, its heterogeneity, and current advances in its treatment. Several molecular parameters have been used to achieve an accurate and personalized characterization of glioblastoma in patients, including epigenetic, genetic, transcriptomic and metabolic features, as well as age- and sex-related patterns and the involvement of several noncoding RNAs in glioblastoma progression. Astrocyte-like neural stem cells and outer radial glial-like cells from the subventricular zone have been proposed as agents involved in GBM of IDH-wildtype origin, but this remains controversial. Glioblastoma metabolism is characterized by upregulation of the PI3K/Akt/mTOR signaling pathway, promotion of the glycolytic flux, maintenance of lipid storage, and other features. This metabolism also contributes to glioblastoma's resistance to conventional therapies. Tumor heterogeneity, a hallmark of GBM, has been shown to affect the genetic expression, modulation of metabolic pathways, and immune system evasion. GBM's aggressive invasion potential is modulated by cell-to-cell crosstalk within the tumor microenvironment and altered expressions of specific genes, such as ANXA2, GBP2, FN1, PHIP, and GLUT3. Nevertheless, the rising number of active clinical trials illustrates the efforts to identify new targets and drugs to treat this malignancy. Immunotherapy is still relevant for research purposes, given the amount of ongoing clinical trials based on this strategy to treat GBM, and neoantigen and nucleic acid-based vaccines are gaining importance due to their antitumoral activity by inducing the immune response. Furthermore, there are clinical trials focused on the PI3K/Akt/mTOR axis, angiogenesis, and tumor heterogeneity for developing molecular-targeted therapies against GBM. Other strategies, such as nanodelivery and computational models, may improve the drug pharmacokinetics and the prognosis of patients with GBM.

A novel necroptosis-related gene signature for predict prognosis of glioma based on single-cell and bulk RNA sequencing

Background: Glioma is the most fatal neoplasm among the primary intracranial cancers. Necroptosis, a form of programmed cell death, is correlated with tumor progression and immune response. But, the role of necroptosis-related genes (NRGs) in glioma has not been well-uncovered.

Methods: Single-cell and bulk RNA sequencing data, obtained from publicly accessed databases, were used to establish a necroptosis-related gene signature for predicting the prognosis of glioma patients. Multiple bioinformatics algorithms were conducted to evaluate the efficacy of the signature. The relative mRNA level of each signature gene was validated by quantitative real-time reverse transcription PCR (qRT-PCR) in glioma cell lines compared to human astrocytes.

Results: In this predicted prognosis model, patients with a high risk score showed a shorter overall survival, which was verified in the testing cohorts. The signature risk score was positively related with immune cell infiltration and some immune check points, such as CD276 (B7-H3), CD152 (CTLA-4), CD223 (LAG-3), and CD274 (PD-L1). Single-cell RNA sequencing analysis confirmed that the glioma microenvironment consists of various immune cells with different markers. The eight NRGs of the signature were detected to be expressed in several immune cells. QRT-PCR results verified that all the eight signature genes were differentially expressed between human astrocytes and glioma cells.

Conclusion: The eight NRGs correlate with the immune microenvironment of glioma according to our bioinformatics analysis. This necroptosis-related gene signature may evaluate the precise methodology of predicting prognosis of glioma and provide a novel thought in glioma investigation.

Characterization of Different Subtypes of Immune Cell Infiltration in Glioblastoma to Aid Immunotherapy

Glioblastoma multiforme (GBM) has been identified as a frequently occurring adult primary brain cancer that is highly aggressive. Currently, the prognostic outcome for GBM patients is dismal, even with intensive treatment, and the median overall survival (OS) is 14.6 months. Immunotherapy, which is specific at the cellular level and can generate persistent immunosurveillance, is now becoming a promising tool to treat diverse cancers. However, the complicated nature of the tumor microenvironment (TME) makes it challenging to develop anti-GBM immunotherapy because several cell types, cytokines, and signaling pathways are involved in generating the immunosuppressive environment. Novel immunotherapies can illustrate novel tumor-induced immunosuppressive mechanisms. Here, we used unsupervised clustering analysis to identify different subtypes of immune cell infiltration that actuated different prognoses, biological actions, and immunotherapy responses. Gene cluster A, with a hot immune cell infiltration phenotype, had high levels of immune-related genes (IRGs), which were associated with immune pathways including the interferon-gamma response and interferon-alpha response, and had low IDH1 and ATRX mutation frequencies. Gene cluster B, a cold immune cell infiltration subtype, exhibited a high expression of the KCNIP2, SCRT1, CPLX2, JPH3, UNC13A, GABRB3, ARPP21, DLGAP1, NRXN1, DLL3, CA10, MAP2, SEZ6L, GRIA2, and GRIA4 genes and a low expression of immune-related genes, i.e., low levels of immune reactivity. Our study highlighted the complex interplay between immune cell infiltration and genetic mutation in the establishment of the tumor immune phenotype. Gene cluster A was identified as an important subtype with a better prognosis and improved immunotherapy response.

Gene Expression Profiling of Glioblastoma to Recognize Potential Biomarker Candidates

Glioblastoma is an aggressive malignant tumor of the brain and spinal cord. Due to the blood-brain barrier, the accessibility of its treatments still remains significantly challenging. Unfortunately, the recurrence rates of glioblastoma upon surgery are very high too. Hence, understanding the molecular drivers of disease progression is valuable. In this study, we aimed to investigate the molecular drivers responsible for glioblastoma progression and identify valid biomarkers. Three microarray expression profiles GSE90604, GSE50601, and GSE134470 containing healthy and glioblastoma-affected samples revealed overlapping differentially expressed genes (DEGs). The interrelational pathway enrichment analysis elucidated the halt of cell cycle checkpoints and activation of signaling pathways and led to the identification of 6 predominant hub genes. Validation of hub genes in comparison with The Cancer Genome Atlas datasets identified the potential biomarkers of glioblastoma. The study evaluated two significantly upregulated genes, SPARC (secreted protein acidic and rich in cysteine) and VIM (vimentin) for glioblastoma. The genes CACNA1E (calcium voltage-gated channel subunit alpha1 e), SH3GL2 (SH3 domain-containing GRB2-like 2, endophilin A1), and DDN (dendrin) were identified as under-expressed genes as compared to the normal and pan-cancer tissues along with prominent putative prognostic biomarker potentials. The genes DDN and SH3GL2 were found to be upregulated in the proneural subtype, while CACNA1E in the mesenchymal subtype of glioblastoma exhibits good prognostic potential. The mutational analysis also revealed the benign, possibly, and probably damaging substitution mutations. The correlation between the DEG and survival in glioblastoma was evaluated using the Kaplan-Meier plots, and VIM had a greater life expectancy of 60.25 months. Overall, this study identified key candidate genes that might serve as predictive biomarkers for glioblastoma.

Bioinformatics in Latin America: ISCB-LA SOIBIO RMB Symposium 2020

This special issue ‘Bioinformatics in Latin America: ISCB-LA SOIBIO RMB Symposium 2020’ features the papers presented at the ISCB-LA SoIBio BioNetMX 2020 Virtual Symposium held on 28–29 October 2020. This is the first international joint event organized by the Mexican Network for Bioinformatics (RMB), the International Society of Computational Biology (ISCB) and the Iberoamerican Society for Bioinformatics (SOIBIO). The aim of this event is to foster interdisciplinary and multidisciplinary collaborations in research across Exact and Life Sciences.