Improved prognostication of glioblastoma beyond molecular subtyping by transcriptional profiling of the tumor microenvironment

Knockdown of CENPF induces cell cycle arrest and inhibits epithelial‑mesenchymal transition progression in glioma

Gliomas are among the most common malignant tumors of the central nervous system. Despite surgical resection followed by postoperative radiotherapy and chemotherapy, their prognosis remains unfavorable. The present study aimed to assess new mechanisms and explore promising prognostic biomarkers for patients with glioma using comprehensive bioinformatics analysis and in vitro and in vivo assays. Overlapping differentially expressed genes were screened from The Cancer Genome Atlas, GSE111260 and GSE16011 samples for protein-protein interaction networks, a risk score model, gene mutation analysis and a nomogram to identify the prognostic hub genes. Subsequently, an immunoassay was performed to determine key genes. Functional and animal assays were then performed to assess the tumorigenesis of the key genes in glioma. Using bioinformatics analysis, centromere protein F (CENPF), kinesin superfamily member 20A, kinesin superfamily protein 4A and marker of proliferation Ki-67 were identified as potential prognostic biomarkers for patients with glioma. Furthermore, CENPF knockdown was demonstrated to suppress the proliferation and metastasis of glioma cells, and induce G2 arrest in the cell cycle. Moreover, CENPF knockdown was revealed to decrease Vimentin and increase E-cadherin levels in glioma cells, and significantly reduce the size and mass of tumors in vivo. Overall, the present study identified new clinical biomarkers and revealed that CENPF may promote glioma progression by regulating the epithelial-mesenchymal transition pathway. By elucidating the complexities of glioma and identifying prognostic biomarkers, the present research enables further improvement of patient outcomes and the advancement of precision medicine for this disease.

Understanding the Immune System and Biospecimen-Based Response in Glioblastoma: A Practical Guide to Utilizing Signal Redundancy for Biomarker and Immune Signature Discovery

Glioblastoma (GBM) is a primary central nervous system malignancy with a median survival of 15-20 months. The presence of both intra- and intertumoral heterogeneity limits understanding of biological mechanisms leading to tumor resistance, including immune escape. An attractive field of research to examine treatment resistance are immune signatures composed of cluster of differentiation (CD) markers and cytokines. CD markers are surface markers expressed on various cells throughout the body, often associated with immune cells. Cytokines are the effector molecules of the immune system. Together, CD markers and cytokines can serve as useful biomarkers to reflect immune status in patients with GBM. However, there are gaps in the understanding of the intricate interactions between GBM and the peripheral immune system and how these interactions change with standard and immune-modulating treatments. The key to understanding the true nature of these interactions is through multi-omic analysis of tumor progression and treatment response. This review aims to identify potential non-invasive blood-based biomarkers that can contribute to an immune signature through multi-omic approaches, leading to a better understanding of immune involvement in GBM.

DNA methylation-based analysis reveals accelerated epigenetic aging in giant cell-enriched adult-type glioblastoma

BACKGROUND

Giant cell (gc)-enriched glioblastoma (gcGB) represents a distinct histological variant of isocitrate dehydrogenase wild-type adult-type glioblastoma with notable enlarged mono- or multinuclear tumor cells. While some studies suggest a survival advantage for gcGB patients, the underlying causes remain elusive. GcGBs are associated with TP53 mutations, and gcs were shown to accumulate DNA double-strand breaks and show deficient mitosis, potentially triggering cellular senescence programs. Epigenetic clocks have emerged as valuable tools for assessing tumor-induced age acceleration (DNAMethAgeAcc), which has lately proved itself as prognostic biomarker in glioblastoma. Our study aimed to comprehensively analyze the methylome and key metabolic proteins of gcGBs, hypothesizing that they undergo cellular aging programs compared to non-gcGBs.

RESULTS

A total of 310 epigenetically classified GBs, including 26 gcGBs, and nine adults with malignant gliomas allocating to pediatric high-grade glioma molecular subclasses (summarized as "pediatric GB") were included. DNAMethAgeAcc was computed by subtraction of chronological patient ages from DNA methylome-derived age estimations and its increase was associated with better survival within gcGB and non-gcGB. GcGBs were significantly more often allocated to the subgroup with increased DNAMethAgeAcc and demonstrated the highest DNAMethAgeAcc. Hypothetical senescence/aging-induced changes of the tumor microenvironment were addressed by tumor deconvolution, which was able to identify a cluster enriched for tumors with increased DNAMethAgeAcc. Key metabolic protein expression did not differ between gcGB and non-gcGB and tumor with versus without increased DNAMethAgeAcc but for elevated levels of one single mitochondrial marker, anti-mitochondrial protein MT-C02, in gcGBs.

CONCLUSIONS

With its sped-up epigenetic aging, gcGB presented as the epigenetic oldest GB variant in our cohort. Whereas the correlation between accelerated tumor-intrinsic epigenetic aging and cellular senescence in gcGB stays elusive, fostering epigenetic aging programs in GB might be of interest for future exploration of alternative treatment options in GB patients.

Development and verification of a novel risk model related to ubiquitination linked with prognosis and therapeutic response in clear cell renal cell carcinoma

Increasing evidence highlights the important role of ubiquitination in cancer. The objective of our study is to establish a reliable marker for predicting clinical outcomes and treatment responses in patients with clear cell renal cell carcinoma (ccRCC) using genes related to ubiquitination (URGs). The URGs subtypes were identified using consensus clustering based on TCGA-KIRC, and a signature containing the prognostic differentially expressed genes of the subtypes was determined using LASSO and Cox regression analysis. To demonstrate the strength of the signature, verification analyses were performed on both E-MTAB-1980 and TCGA-KIRC test datasets. We developed a nomogram to enhance the effectiveness of our predictive tool. Risk genes expression was determined through RT-qPCR. Six genes were combined to create the URGs signature, which had a highly correlated with patient prognosis in patients with ccRCC. A nomogram was developed based on the URGs signature and clinicopathological characteristics. We found that the predictive power was substantially greater than the other individual predictors. Moreover, the study on the immune microenvironment revealed significant variations in the levels of immune cells and the expression of immune checkpoint genes among the groups categorized as high-risk and low-risk. Furthermore, it was found that immunotherapy yielded better outcomes in cohorts with low risk. The URGs signature might serve as a novel and powerful prognosis biomarker and offer a momentous reference for individualized treatment for patients in ccRCC.

Comprehensive understanding of glioblastoma molecular phenotypes: classification, characteristics, and transition

Among central nervous system-associated malignancies, glioblastoma (GBM) is the most common and has the highest mortality rate. The high heterogeneity of GBM cell types and the complex tumor microenvironment frequently lead to tumor recurrence and sudden relapse in patients treated with temozolomide. In precision medicine, research on GBM treatment is increasingly focusing on molecular subtyping to precisely characterize the cellular and molecular heterogeneity, as well as the refractory nature of GBM toward therapy. Deep understanding of the different molecular expression patterns of GBM subtypes is critical. Researchers have recently proposed tetra fractional or tripartite methods for detecting GBM molecular subtypes. The various molecular subtypes of GBM show significant differences in gene expression patterns and biological behaviors. These subtypes also exhibit high plasticity in their regulatory pathways, oncogene expression, tumor microenvironment alterations, and differential responses to standard therapy. Herein, we summarize the current molecular typing scheme of GBM and the major molecular/genetic characteristics of each subtype. Furthermore, we review the mesenchymal transition mechanisms of GBM under various regulators.

Biological implications and clinical potential of invasion and migration related miRNAs in glioma

Gliomas are the most common primary malignant brain tumors and are highly aggressive. Invasion and migration are the main causes of poor prognosis and treatment resistance in gliomas. As migration and invasion occur, patient survival and prognosis decline dramatically. MicroRNAs (miRNAs) are small, non-coding 21-23 nucleotides involved in regulating the malignant phenotype of gliomas, including migration and invasion. Numerous studies have demonstrated the mechanism and function of some miRNAs in glioma migration and invasion. However, the biological and clinical significance (including diagnosis, prognosis, and targeted therapy) of glioma migration and invasion-related miRNAs have not been systematically discussed. This paper reviews the progress of miRNAs-mediated migration and invasion studies in glioma and discusses the clinical value of migration and invasion-related miRNAs as potential biomarkers or targeted therapies for glioma. In addition, these findings are expected to translate into future directions and challenges for clinical applications. Although many biomarkers and their biological roles in glioma invasion and migration have been identified, none have been specific so far, and further exploration of clinical treatment is still in progress; therefore, we aimed to further identify specific markers that may guide clinical treatment and improve the quality of patient survival.

Necrotic reshaping of the glioma microenvironment drives disease progression

Glioblastoma is the most common primary brain tumor and has a dismal prognosis. The development of central necrosis represents a tipping point in the evolution of these tumors that foreshadows aggressive expansion, swiftly leading to mortality. The onset of necrosis, severe hypoxia and associated radial glioma expansion correlates with dramatic tumor microenvironment (TME) alterations that accelerate tumor growth. In the past, most have concluded that hypoxia and necrosis must arise due to "cancer outgrowing its blood supply" when rapid tumor growth outpaces metabolic supply, leading to diffusion-limited hypoxia. However, growing evidence suggests that microscopic intravascular thrombosis driven by the neoplastic overexpression of pro-coagulants attenuates glioma blood supply (perfusion-limited hypoxia), leading to TME restructuring that includes breakdown of the blood-brain barrier, immunosuppressive immune cell accumulation, microvascular hyperproliferation, glioma stem cell enrichment and tumor cell migration outward. Cumulatively, these adaptations result in rapid tumor expansion, resistance to therapeutic interventions and clinical progression. To inform future translational investigations, the complex interplay among environmental cues and myriad cell types that contribute to this aggressive phenotype requires better understanding. This review focuses on contributions from intratumoral thrombosis, the effects of hypoxia and necrosis, the adaptive and innate immune responses, and the current state of targeted therapeutic interventions.

PIK3CA Mutations in Diffuse Gliomas: An Update on Molecular Stratification, Prognosis, Recurrence, and Aggressiveness

Introduction:

PIK3CA is one of the most mutated oncogenes in solid tumors. In breast cancer (ER-positive, HER2-negative), these events represent a predictive biomarker of response to alpelisib. In glioblastomas (GBM), PIK3CA mutations were described as early constitutive events. Here, we investigated PIK3CA mutational profile across glioma molecular subgroups and its relevance during glioma recurrence. Furthermore, PIK3CA mutations’ effect in PI3K pathway, prognosis, and response to therapy was also explored.

Material and Methods:

Exons 10 and 21 of PIK3CA mutations were evaluated in 394 gliomas and 19 glioma recurrences from Instituto Português de Oncologia Lisboa Francisco Gentil (IPOLFG) and compared with The Cancer Genome Atlas (TCGA) data. TIMER2.0 and NetMHCpan4.1 were used to assess the immune-microenvironment contribution.

Results:

PIK3CA mutations were identified among all glioma subgroups, although with no impact on their stratification or prognosis. In both cohorts (IPOLFG and TCGA), PIK3CA mutation frequencies in IDH-mutant and IDH-wild-type GBM were similar (IPOLFG: 9% and 3%; TCGA: 8% and 2%). These mutations were not mutually exclusive with PTEN deletion and EGFR amplification. Despite their reduced frequency, we discovered PIK3CA mutations were maintained during glioma recurrence regardless of administered therapies. The immune microenvironment might not contribute to this phenotype as PIK3CA mutations did not influence immune cell infiltration.

Conclusions:

Despite the absence of a predominant effect in glioma stratification, PIK3CA mutations were maintained during glioma recurrence, possibly contributing to glioma cell survival, representing promising therapeutic targets in recurrent glioma. Nevertheless, understanding the potential synergistic effects between PIK3CA mutations, PTEN deletion, and EGFR amplification is pivotal to targeted therapies’ efficiency.

TMEM2 Combined with IDH and 1p19q in Refining Molecular Subtypes for Predicting Survival of Patients with Glioma

Gliomas are common intracranial tumors with high morbidity and mortality in adults. Transmembrane protein 2 (TMEM2) is involved in the malignant behavior of solid tumors. TMEM2 regulates cell adhesion and metastasis as well as intercellular communication by degrading nonprotein components of the extracellular matrix. This study aimed to evaluate the relationship between TMEM2 expression levels and glioma subtypes or patient prognosis. Our findings revealed that TMEM2 expression was abnormally upregulated in high-grade glioma. Moreover, combining TMEM2, the status of isocitrate dehydrogenase (IDH) and 1p19q, we subdivided molecular subtypes with significant differences in survival. Patients in the MT-codel-low subgroup had better prognosis than those in the WT-no-codel-high subgroup, who fared the worst. Additionally, correlation analysis of TMEM2 and immune cell infiltration indicated an altered tumor microenvironment (TME) and cell redistribution in the TMEM2 high-expression subtype. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that focal adhesion and PI3K-Akt signaling pathways were enriched in the TMEM2-expressing group. In conclusion, aberrant TMEM2 expression can be used as an independent prognostic marker for refining glioma molecular subtyping and accurate prognosis. These findings will improve rational decision making to provide individualized therapy for patients with glioma.

Development and Validation of an Mesenchymal-Related Long Non-Coding RNA Prognostic Model in Glioma

Glioma is well known as the most aggressive and prevalent primary malignant tumor in the central nervous system. Molecular subtypes and prognosis biomarkers remain a promising research area of gliomas. Notably, the aberrant expression of mesenchymal (MES) subtype related long non-coding RNAs (lncRNAs) is significantly associated with the prognosis of glioma patients. In this study, MES-related genes were obtained from The Cancer Genome Atlas (TCGA) and the Ivy Glioblastoma Atlas Project (Ivy GAP) data sets of glioma, and MES-related lncRNAs were acquired by performing co-expression analysis of these genes. Next, Cox regression analysis was used to establish a prognostic model, that integrated ten MES-related lncRNAs. Glioma patients in TCGA were divided into high-risk and low-risk groups based on the median risk score; compared with the low-risk groups, patients in the high-risk group had shorter survival times. Additionally, we measured the specificity and sensitivity of our model with the ROC curve. Univariate and multivariate Cox analyses showed that the prognostic model was an independent prognostic factor for glioma. To verify the predictive power of these candidate lncRNAs, the corresponding RNA-seq data were downloaded from the Chinese Glioma Genome Atlas (CGGA), and similar results were obtained. Next, we performed the immune cell infiltration profile of patients between two risk groups, and gene set enrichment analysis (GSEA) was performed to detect functional annotation. Finally, the protective factors DGCR10 and HAR1B, and risk factor SNHG18 were selected for functional verification. Knockdown of DGCR10 and HAR1B promoted, whereas knockdown of SNHG18 inhibited the migration and invasion of gliomas. Collectively, we successfully constructed a prognostic model based on a ten MES-related lncRNAs signature, which provides a novel target for predicting the prognosis for glioma patients.

Electrotherapies for Glioblastoma

Non-thermal, intermediate frequency (100-500 kHz) electrotherapies present a unique therapeutic strategy to treat malignant neoplasms. Here, pulsed electric fields (PEFs) which induce reversible or irreversible electroporation (IRE) and tumour-treating fields (TTFs) are reviewed highlighting the foundations, advances, and considerations of each method when applied to glioblastoma (GBM). Several biological aspects of GBM that contribute to treatment complexity (heterogeneity, recurrence, resistance, and blood-brain barrier(BBB)) and electrophysiological traits which are suggested to promote glioma progression are described. Particularly, the biological responses at the cellular and molecular level to specific parameters of the electrical stimuli are discussed offering ways to compare these parameters despite the lack of a universally adopted physical description. Reviewing the literature, a disconnect is found between electrotherapy techniques and how they target the biological complexities of GBM that make treatment difficult in the first place. An attempt is made to bridge the interdisciplinary gap by mapping biological characteristics to different methods of electrotherapy, suggesting important future research topics and directions in both understanding and treating GBM. To the authors' knowledge, this is the first paper that attempts an in-tandem assessment of the biological effects of different aspects of intermediate frequency electrotherapy methods, thus offering possible strategies toward GBM treatment.

iGlioSub: an integrative transcriptomic and epigenomic classifier for glioblastoma molecular subtypes

BACKGROUND

Glioblastoma (GBM) is the most aggressive and prevalent primary brain tumor, with a median survival of 15 months. Advancements in multi-omics profiling combined with computational algorithms have unraveled the existence of three GBM molecular subtypes (Classical, Mesenchymal, and Proneural) with clinical relevance. However, due to the costs of high-throughput profiling techniques, GBM molecular subtyping is not currently employed in clinical settings.

METHODS

Using Random Forest and Nearest Shrunken Centroid algorithms, we constructed transcriptomic, epigenomic, and integrative GBM subtype-specific classifiers. We included gene expression and DNA methylation (DNAm) profiles from 304 GBM patients profiled in the Cancer Genome Atlas (TCGA), the Human Glioblastoma Cell Culture resource (HGCC), and other publicly available databases.

RESULTS

The integrative Glioblastoma Subtype (iGlioSub) classifier shows better performance (mean AUC = 95.9%) stratifying patients than gene expression (mean AUC = 91.9%) and DNAm-based classifiers (AUC = 93.6%). Also, to expand the understanding of the molecular differences between the GBM subtypes, this study shows that each subtype presents unique DNAm patterns and gene pathway activation.

CONCLUSIONS

The iGlioSub classifier provides the basis to design cost-effective strategies to stratify GBM patients in routine pathology laboratories for clinical trials, which will significantly accelerate the discovery of more efficient GBM subtype-specific treatment approaches.

Identification of a mesenchymal-related signature associated with clinical prognosis in glioma

Malignant glioma with a mesenchymal (MES) signature is characterized by shorter survival time due to aggressive dissemination and resistance to chemoradiotherapy. Here, this study used the TCGA database as the training set and the CGGA database as the testing set. Consensus clustering was performed on the two data sets, and it was found that two groups had distinguished prognostic and molecular features. Cox analysis and Lasso regression analysis were used to construct MES signature-based risk score model of glioma. Our results show that MES signature-based risk score model can be used to assess the prognosis of glioma. Three methods (ROC curve analyses, univariate Cox regression analysis, multivariate Cox regression analysis) were used to investigate the prognostic role of texture parameters. The result showed that the MES-related gene signature was proved to be an independent prognostic factor for glioma. Furthermore, functional analysis of the gene related to the risk signature showed that the genes sets were closely related to the malignant process of tumors. Finally, FCGR2A and EHD2 were selected for functional verification. Silencing these two genes inhibited the proliferation, migration and invasion of gliomas and reduced the expression of mesenchymal marker genes. Collectively, MES-related risk signature seems to provide a novel target for predicting the prognosis and treatment of glioma.

Multifaceted microglia - key players in primary brain tumour heterogeneity

Microglia are the resident innate immune cells of the immune-privileged CNS and, as such, represent the first line of defence against tissue injury and infection. Given their location, microglia are undoubtedly the first immune cells to encounter a developing primary brain tumour. Our knowledge of these cells is therefore important to consider in the context of such neoplasms. As the heterogeneous nature of the most aggressive primary brain tumours is thought to underlie their poor prognosis, this Review places a special emphasis on the heterogeneity of the tumour-associated microglia and macrophage populations present in primary brain tumours. Where available, specific information on microglial heterogeneity in various types and subtypes of brain tumour is included. Emerging evidence that highlights the importance of considering the heterogeneity of both the tumour and of microglial populations in providing improved treatment outcomes for patients is also discussed.

Immune Profiling of Gliomas Reveals a Connection with IDH1/2 Mutations, Tau Function and the Vascular Phenotype

Simple Summary

In the present work we have confirmed that gliomas with isocitrate dehydrogenase 1/2 mutations are “cold” tumors, whereas the immune content of their wild-type counterparts is more heterogeneous. A large subgroup of wild-type glioblastomas is characterized by an important immune component, particularly enriched in myeloid cells, and an elevated expression of the ligand of programmed death ligand 1 (PD-L1) in the immune compartment. The rest contain few lymphocytes and myeloid cells. Notably, we have observed a direct correlation between the immune content and the presence of vascular alterations, as well as with the reduced expression of Tau, a microtubule-binding protein that we described as a negative regulator of angiogenesis. Using syngeneic mouse models, we show that overexpression of Tau reduces the immune content, delaying tumor growth.

Abstract

Background: Gliomas remain refractory to all attempted treatments, including those using immune checkpoint inhibitors. The characterization of the tumor (immune) microenvironment has been recognized as an important challenge to explain this lack of response and to improve the therapy of glial tumors. Methods: We designed a prospective analysis of the immune cells of gliomas by flow cytometry. Tumors with or without isocitrate dehydrogenase 1/2 (IDH1/2) mutations were included in the study. The genetic profile and the presence of different molecular and cellular features of the gliomas were analyzed in parallel. The findings were validated in syngeneic mouse models. Results: We observed that few immune cells infiltrate mutant IDH1/2 gliomas whereas the immune content of IDH1/2 wild-type tumors was more heterogeneous. Some of them contained an important immune infiltrate, particularly enriched in myeloid cells with immunosuppressive features, but others were more similar to mutant IDH1/2 gliomas, with few immune cells and a less immunosuppressive profile. Notably, we observed a direct correlation between the percentage of leukocytes and the presence of vascular alterations, which were associated with a reduced expression of Tau, a microtubule-binding protein that controls the formation of tumor vessels in gliomas. Furthermore, overexpression of Tau was able to reduce the immune content in orthotopic allografts of GL261 cells, delaying tumor growth. Conclusions: We have confirmed the reduced infiltration of immune cells in IDH1/2 mutant gliomas. By contrast, in IDH1/2 wild-type gliomas, we have found a direct correlation between the presence of vascular alterations and the entrance of leukocytes into the tumors. Interestingly, high levels of Tau inversely correlated with the vascular and the immune content of gliomas. Altogether, our results could be exploited for the design of more successful clinical trials with immunomodulatory molecules.

Role of Ubiquitination in PTEN Cellular Homeostasis and Its Implications in GB Drug Resistance

Glioblastoma (GB) is the most common and aggressive brain malignancy, characterized by heterogeneity and drug resistance. PTEN, a crucial tumor suppressor, exhibits phosphatase-dependent (PI3K-AKT-mTOR pathway)/independent (nucleus stability) activities to maintain the homeostatic regulation of numerous physiological processes. Premature and absolute loss of PTEN activity usually tends to cellular senescence. However, monoallelic loss of PTEN is frequently observed at tumor inception, and absolute loss of PTEN activity also occurs at the late stage of gliomagenesis. Consequently, aberrant PTEN homeostasis, mainly regulated at the post-translational level, renders cells susceptible to tumorigenesis and drug resistance. Ubiquitination-mediated degradation or deregulated intracellular localization of PTEN hijacks cell growth rheostat control for neoplastic remodeling. Functional inactivation of PTEN mediated by the overexpression of ubiquitin ligases (E3s) renders GB cells adaptive to PTEN loss, which confers resistance to EGFR tyrosine kinase inhibitors and immunotherapies. In this review, we discuss how glioma cells develop oncogenic addiction to the E3s-PTEN axis, promoting their growth and proliferation. Antitumor strategies involving PTEN-targeting E3 ligase inhibitors can restore the tumor-suppressive environment. E3 inhibitors collectively reactivate PTEN and may represent next-generation treatment against deadly malignancies such as GB.

Molecular and Cellular Complexity of Glioma. Focus on Tumour Microenvironment and the Use of Molecular and Imaging Biomarkers to Overcome Treatment Resistance

This review highlights the importance and the complexity of tumour biology and microenvironment in the progression and therapy resistance of glioma. Specific gene mutations, the possible functions of several non-coding microRNAs and the intra-tumour and inter-tumour heterogeneity of cell types contribute to limit the efficacy of the actual therapeutic options. In this scenario, identification of molecular biomarkers of response and the use of multimodal in vivo imaging and in particular the Positron Emission Tomography (PET) based molecular approach, can help identifying glioma features and the modifications occurring during therapy at a regional level. Indeed, a better understanding of tumor heterogeneity and the development of diagnostic procedures can favor the identification of a cluster of patients for personalized medicine in order to improve the survival and their quality of life.