Detection of glioblastoma in biofluids

GBM immunotherapy: Exploring molecular and clinical frontiers

GBM is the most common, aggressive, and intracranial primary brain tumor; it originates from the glial progenitor cells, has poor overall survival (OS), and has limited treatment options. In this decade, GBM immunotherapy is in trend and preferred over several conventional therapies, due to their better patient survival outcome. This review explores the clinical trials of several immunotherapeutic approaches (immune checkpoint blockers (ICBs), CAR T-cell therapy, cancer vaccines, and adoptive cell therapy) with their efficacy and safety. Despite significant progress, several challenges (viz., immunosuppressive microenvironment, heterogeneity, and blood-brain barrier (BBB)) were experienced that hamper their immunotherapeutic potential. Furthermore, these challenges were clinically studied to be resolved by multiple combinatorial approaches, discussed in the later part of the review. Thus, this review suggests the clinical use and potential of immunotherapy in GBM and provides the holistic recent knowledge and future perspectives.

Extracellular vesicles in glioblastoma: Biomarkers and therapeutic tools

Glioblastoma (GBM) is the most aggressive tumor among the gliomas and intracranial tumors and to date prognosis for GBM patients remains poor, with a median survival typically measured in months to a few years depending on various factors. Although standardized therapies are routinely employed, it is clear that these strategies are unable to cope with heterogeneity and invasiveness of GBM. Furthermore, diagnosis and monitoring of responses to therapies are directly dependent on tissue biopsies or magnetic resonance imaging (MRI) techniques. From this point of view, liquid biopsies are arising as key sources of a variety of biomarkers with the advantage of being easily accessible and monitorable. In this context, extracellular vesicles (EVs), physiologically shed into body fluids by virtually all cells, are gaining increasing interest both as natural carriers of biomarkers and as specific signatures even for GBM. What makes these vesicles particularly attractive is they are also emerging as therapeutical vehicles to treat GBM given their native ability to cross the blood-brain barrier (BBB). Here, we reviewed recent advances on the use of EVs as biomarker for liquid biopsy and nanocarriers for targeted delivery of anticancer drugs in glioblastoma.

Targeting inflammation in glioblastoma: An updated review from pathophysiology to novel therapeutic approaches

Glioblastoma (GBM) is a highly aggressive primary malignant brain tumor with a dismal prognosis despite current treatment strategies. Inflammation plays an essential role in GBM pathophysiology, contributing to tumor growth, invasion, immunosuppression, and angiogenesis. As a result, pharmacological intervention with anti-inflammatory drugs has been used as a potential approach for the management of GBM. To provide an overview of the current understanding of GBM pathophysiology, potential therapeutic applications of anti-inflammatory drugs in GBM, conventional treatments of glioblastoma and emerging therapeutic approaches currently under investigation. A narrative review was carried out, scanning publications from 2000 to 2023 on PubMed and Google Scholar. The search was not guided by a set research question or a specific search method but rather focused on the area of interest. Conventional treatments such as surgery, radiotherapy, and chemotherapy have shown some benefits, but their effectiveness is limited by various factors such as tumor heterogeneity and resistance.

Exploring ncRNA-mediated regulation of EGFR signalling in glioblastoma: From mechanisms to therapeutics

Glioblastoma (GBM) is the most prevalent and deadly primary brain tumor type, with a discouragingly low survival rate and few effective treatments. An important function of the EGFR signalling pathway in the development of GBM is to affect tumor proliferation, persistence, and treatment resistance. Advances in molecular biology in the last several years have shown how important ncRNAs are for controlling a wide range of biological activities, including cancer progression and development. NcRNAs have become important post-transcriptional regulators of gene expression, and they may affect the EGFR pathway by either directly targeting EGFR or by modifying important transcription factors and downstream signalling molecules. The EGFR pathway is aberrantly activated in response to the dysregulation of certain ncRNAs, which has been linked to GBM carcinogenesis, treatment resistance, and unfavourable patient outcomes. We review the literature on miRNAs, circRNAs and lncRNAs that are implicated in the regulation of EGFR signalling in GBM, discussing their mechanisms of action, interactions with the signalling pathway, and implications for GBM therapy. Furthermore, we explore the potential of ncRNA-based strategies to overcome resistance to EGFR-targeted therapies, including the use of ncRNA mimics or inhibitors to modulate the activity of key regulators within the pathway.

Biosensor-Enhanced Organ-on-a-Chip Models for Investigating Glioblastoma Tumor Microenvironment Dynamics

Glioblastoma, an aggressive primary brain tumor, poses a significant challenge owing to its dynamic and intricate tumor microenvironment. This review investigates the innovative integration of biosensor-enhanced organ-on-a-chip (OOC) models as a novel strategy for an in-depth exploration of glioblastoma tumor microenvironment dynamics. In recent years, the transformative approach of incorporating biosensors into OOC platforms has enabled real-time monitoring and analysis of cellular behaviors within a controlled microenvironment. Conventional in vitro and in vivo models exhibit inherent limitations in accurately replicating the complex nature of glioblastoma progression. This review addresses the existing research gap by pioneering the integration of biosensor-enhanced OOC models, providing a comprehensive platform for investigating glioblastoma tumor microenvironment dynamics. The applications of this combined approach in studying glioblastoma dynamics are critically scrutinized, emphasizing its potential to bridge the gap between simplistic models and the intricate in vivo conditions. Furthermore, the article discusses the implications of biosensor-enhanced OOC models in elucidating the dynamic features of the tumor microenvironment, encompassing cell migration, proliferation, and interactions. By furnishing real-time insights, these models significantly contribute to unraveling the complex biology of glioblastoma, thereby influencing the development of more accurate diagnostic and therapeutic strategies.

Liquid Biopsy for Glioma Using Cell-Free DNA in Cerebrospinal Fluid

Glioma is one of the most common primary central nervous system (CNS) tumors, and its molecular diagnosis is crucial. However, surgical resection or biopsy is risky when the tumor is located deep in the brain or brainstem. In such cases, a minimally invasive approach to liquid biopsy is beneficial. Cell-free DNA (cfDNA), which directly reflects tumor-specific genetic changes, has attracted attention as a target for liquid biopsy, and blood-based cfDNA monitoring has been demonstrated for other extra-cranial cancers. However, it is still challenging to fully detect CNS tumors derived from cfDNA in the blood, including gliomas, because of the unique structure of the blood-brain barrier. Alternatively, cerebrospinal fluid (CSF) is an ideal source of cfDNA and is expected to contribute significantly to the liquid biopsy of gliomas. Several successful studies have been conducted to detect tumor-specific genetic alterations in cfDNA from CSF using digital PCR and/or next-generation sequencing. This review summarizes the current status of CSF-based cfDNA-targeted liquid biopsy for gliomas. It highlights how the approaches differ from liquid biopsies of other extra-cranial cancers and discusses the current issues and prospects.

Study of low-frequency spectroscopic characteristics of γ-aminobutyric acid with THz and low-wavenumber Raman spectroscopy

γ-aminobutyric (GABA) is the most important inhibitory neurotransmitier in vertebrate central nervous systems. The content level of GABA is related to the different degree of malignancy gliomas. Thus, it can be considered a promising glioma biomarker. In this paper, the spectroscopic properties of GABA have been characterized by combining the THz spectroscopy with low-wavenumber Raman spectroscopy. The experimental results showed that, GABA exhibited three absorption peaks and three refractive index peaks in the range of 0.6-2.1 THz. The limit of detection can reach up to 0.428 % based on the absorption coefficient at the peak of 2.04 THz. Moreover, the low-wavenumber Raman spectrum of GABA showed seven characteristic peaks at 41.0, 50.8, 58.8, 77.2, 98.8, 115.6, 141.2 cm-1 in 0-150 cm-1 region. Moreover, the THz and low-wavenumber theoretical spectra of GABA were simulated with solid-state density function theory, respectively. The calculated results were in good agreement with the experimental observations. On the basis of calculated result, the vibrational motions of each THz and Raman characteristic modes were quantitatively decomposed by analytical mode-decoupling method, where the contribution percentages of external translation, external librations and intramolecular vibration of each vibration modes were analyzed Furthermore, the low-frequency characteristics of GABA was analyzed by combining the THz and low-wavenumber Raman spectroscopy. It is beneficial for the structural information analysis and quantitative identification of biomarker GABA in early stage diagnosis of glioma.

Recent advancements and theranostics strategies in glioblastoma therapy

Glioblastoma (GBM) is the most aggressive and lethal malignant brain tumor, and it is challenging to cure with surgery and treatment. The prevention of permanent brain damage and tumor invasion, which is the ultimate cause of recurrence, are major obstacles in GBM treatment. Besides, emerging treatment modalities and newer genetic findings are helping to understand and manage GBM in patients. Accordingly, researchers are focusing on advanced nanomaterials-based strategies for tackling the various problems associated with GBM. In this context, researchers explored novel strategies with various alternative treatment approaches such as early detection techniques and theranostics approaches. In this review, we have emphasized the recent advancement of GBM cellular models and their roles in designing GBM therapeutics. We have added a special emphasis on the novel genetic and drug target findings as well as strategies for early detection. Besides, we have discussed various theranostic approaches such as hyperthermia therapy, phototherapy and image-guided therapy. Approaches utilized for targeted drug delivery to the GBM were also discussed. This article also describes the recentin vivo, in vitroandex vivoadvances using innovative theranostic approaches.

Seq-ing the SINEs of central nervous system tumors in cerebrospinal fluid

It is often challenging to distinguish cancerous from non-cancerous lesions in the brain using conventional diagnostic approaches. We introduce an analytic technique called Real-CSF (repetitive element aneuploidy sequencing in CSF) to detect cancers of the central nervous system from evaluation of DNA in the cerebrospinal fluid (CSF). Short interspersed nuclear elements (SINEs) are PCR amplified with a single primer pair, and the PCR products are evaluated by next-generation sequencing. Real-CSF assesses genome-wide copy-number alterations as well as focal amplifications of selected oncogenes. Real-CSF was applied to 280 CSF samples and correctly identified 67% of 184 cancerous and 96% of 96 non-cancerous brain lesions. CSF analysis was considerably more sensitive than standard-of-care cytology and plasma cell-free DNA analysis in the same patients. Real-CSF therefore has the capacity to be used in combination with other clinical, radiologic, and laboratory-based data to inform the diagnosis and management of patients with suspected cancers of the brain.

Emerging extracellular vesicle-based carriers for glioblastoma diagnosis and therapy

Glioblastoma (GBM) treatment is still a big clinical challenge because of its highly malignant, invasive, and lethal characteristics. After treatment with the conventional therapeutic paradigm of surgery combined with radio- and chemotherapy, patients bearing GBMs generally exhibit a poor prognosis, with high mortality and a high disability rate. The main reason is the existence of the formidable blood-brain barrier (BBB), aggressive growth, and the infiltration nature of GBMs. Especially, the BBB suppresses the delivery of imaging and therapeutic agents to lesion sites, and thus this leads to difficulties in achieving a timely diagnosis and treatment. Recent studies have demonstrated that extracellular vesicles (EVs) exhibit favorable merits including good biocompatibility, a strong drug loading capacity, long circulation time, good BBB crossing efficiency, specific targeting to lesion sites, and high efficiency in the delivery of a variety of cargos for GBM therapy. Importantly, EVs inherit physiological and pathological molecules from the source cells, which are ideal biomarkers for molecularly tracking the malignant progression of GBMs. Herein, we start by introducing the pathophysiology and physiology of GBMs, followed by presenting the biological functions of EVs in GBMs with a special focus on their role as biomarkers for GBM diagnosis and as messengers in the modulation of the GBM microenvironment. Furthermore, we provide an update on the recent progress of using EVs in biology, functionality, and isolation applications. More importantly, we systematically summarize the most recent advances of EV-based carriers for GBM therapy by delivering different drugs including gene/RNA-based drugs, chemotherapy drugs, imaging agents, and combinatory drugs. Lastly, we point out the challenges and prospects of future research on EVs for diagnosing and treating GBMs. We hope this review will stimulate interest from researchers with different backgrounds and expedite the progress of GBM treatment paradigms.

Recent advances in the detection of glioblastoma, from imaging-based methods to proteomics and biosensors: A narrative review

Glioblastoma (GBM) is an aggressive type of cancer that originates in the cells called astrocytes, which support the functioning of nerve cells. It can develop in either the brain or the spinal cord and is also known as glioblastoma multiform. GBM is a highly aggressive cancer that can occur in either the brain or spinal cord. The detection of GBM in biofluids offers potential advantages over current methods for diagnosing and treatment monitoring of glial tumors. Biofluid-based detection of GBM focuses on identifying tumor-specific biomarkers in blood and cerebrospinal fluid. To date, different methods have been used to detect biomarkers of GBM, ranging from various imaging techniques to molecular approaches. Each method has its own strengths and weaknesses. The present review aims to scrutinize multiple diagnostic methods for GBM, with a focus on proteomics methods and biosensors. In other words, this study aims to provide an overview of the most significant research findings based on proteomics and biosensors for the diagnosis of GBM.

Ultra High-plex Spatial Proteogenomic Investigation of Giant Cell Glioblastoma Multiforme Immune Infiltrates Reveals Distinct Protein and RNA Expression Profiles

A deeper understanding of complex biological processes, including tumor development and immune response, requires ultra high-plex, spatial interrogation of multiple "omes". Here we present the development and implementation of a novel spatial proteogenomic (SPG) assay on the GeoMx Digital Spatial Profiler platform with next-generation sequencing readout that enables ultra high-plex digital quantitation of proteins (>100-plex) and RNA (whole transcriptome, >18,000-plex) from a single formalin-fixed paraffin-embedded (FFPE) sample. This study highlighted the high concordance, R > 0.85 and <15% change in sensitivity between the SPG assay and the single-analyte assays on various cell lines and tissues from human and mouse. Furthermore, we demonstrate that the SPG assay was reproducible across multiple users. When used in conjunction with advanced cellular neighborhood segmentation, distinct immune or tumor RNA and protein targets were spatially resolved within individual cell subpopulations in human colorectal cancer and non-small cell lung cancer. We used the SPG assay to interrogate 23 different glioblastoma multiforme (GBM) samples across four pathologies. The study revealed distinct clustering of both RNA and protein based on pathology and anatomic location. The in-depth investigation of giant cell glioblastoma multiforme (gcGBM) revealed distinct protein and RNA expression profiles compared with that of the more common GBM. More importantly, the use of spatial proteogenomics allowed simultaneous interrogation of critical protein posttranslational modifications alongside whole transcriptomic profiles within the same distinct cellular neighborhoods.

Significance

We describe ultra high-plex spatial proteogenomics; profiling whole transcriptome and high-plex proteomics on a single FFPE tissue section with spatial resolution. Investigation of gcGBM versus GBM revealed distinct protein and RNA expression profiles.

Engineered EVs designed to target diseases of the CNS

Diseases of the central nervous system (CNS) are challenging to treat, mainly due to the blood-brain barrier (BBB), which restricts drugs in circulation from entering target regions in the brain. To address this issue extracellular vesicles (EVs) have gained increasing scientific interest as carriers able to cross the BBB with multiplex cargos. EVs are secreted by virtually every cell, and their escorted biomolecules are part of an intercellular information gateway between cells within the brain and with other organs. Scientists have undertaken efforts to safeguard the inherent features of EVs as therapeutic delivery vehicles, such as protecting and transferring functional cargo, as well as loading them with therapeutic small molecules, proteins, and oligonucleotides and targeting them to specific cell types for the treatment of CNS diseases. Here, we review current emerging approaches that engineer the EV surface and cargo to improve targeting and functional responses in the brain. We summarize existing applications of engineered EVs as a therapeutic delivery platform for brain diseases, some of which have been evaluated clinically.

Coculture with Neural Stem Cells May Shift the Transcription Profile of Glioblastoma Multiforme towards Cancer-Specific Stemness

Glioblastoma multiforme (GBM) possesses a small but significant population of cancer stem cells (CSCs) thought to play a role in its invasiveness, recurrence, and metastasis. The CSCs display transcriptional profiles for multipotency, self-renewal, tumorigenesis, and therapy resistance. There are two possible theories regarding the origin of CSCs in the context of neural stem cells (NSCs); i.e., NSCs modify cancer cells by conferring them with cancer-specific stemness, or NSCs themselves are transformed into CSCs due to the tumor environment created by cancer cells. To test the theories and to investigate the transcriptional regulation of the genes involved in CSC formation, we cocultured NSC and GBM cell lines together. Where genes related to cancer stemness, drug efflux, and DNA modification were upregulated in GBM, they were downregulated in NSCs upon coculture. These results indicate that cancer cells shift the transcriptional profile towards stemness and drug resistance in the presence of NSCs. Concurrently, GBM triggers NSCs differentiation. Because the cell lines were separated by a membrane (0.4 µm pore size) to prevent direct contact between GBM and NSCs, cell-secreted signaling molecules and extracellular vesicles (EVs) are likely involved in reciprocal communication between NSCs and GBM, causing transcription modification. Understanding the mechanism of CSC creation will aid in the identification of precise molecular targets within the CSCs to exterminate them, which, in turn, will increase the efficacy of chemo-radiation treatment.

Discovering Glioma Tissue through Its Biomarkers' Detection in Blood by Raman Spectroscopy and Machine Learning

The most commonly occurring malignant brain tumors are gliomas, and among them is glioblastoma multiforme. The main idea of the paper is to estimate dependency between glioma tissue and blood serum biomarkers using Raman spectroscopy. We used the most common model of human glioma when continuous cell lines, such as U87, derived from primary human tumor cells, are transplanted intracranially into the mouse brain. We studied the separability of the experimental and control groups by machine learning methods and discovered the most informative Raman spectral bands. During the glioblastoma development, an increase in the contribution of lactate, tryptophan, fatty acids, and lipids in dried blood serum Raman spectra were observed. This overlaps with analogous results of glioma tissues from direct Raman spectroscopy studies. A non-linear relationship between specific Raman spectral lines and tumor size was discovered. Therefore, the analysis of blood serum can track the change in the state of brain tissues during the glioma development.

Glioblastoma-derived extracellular vesicle subpopulations following 5-aminolevulinic acid treatment bear diagnostic implications

Liquid biopsy is a minimally invasive alternative to surgical biopsy, encompassing different analytes including extracellular vesicles (EVs), circulating tumour cells (CTCs), circulating tumour DNA (ctDNA), proteins, and metabolites. EVs are released by virtually all cells, but at a higher rate by faster cycling, malignant cells. They encapsulate cargo native to the originating cell and can thus provide a window into the tumour landscape. EVs are often analysed in bulk which hinders the analysis of rare, tumour-specific EV subpopulations from the large host EV background. Here, we fractionated EV subpopulations in vitro and in vivo and characterized their phenotype and generic cargo. We used 5-aminolevulinic acid (5-ALA) to induce release of endogenously fluorescent tumour-specific EVs (EVPpIX ). Analysis of five different subpopulations (EVPpIX , EVCD63 , EVCD9 , EVEGFR , EVCFDA ) from glioblastoma (GBM) cell lines revealed unique transcriptome profiles, with the EVPpIX transcriptome demonstrating closer alignment to tumorigenic processes over the other subpopulations. Similarly, isolation of tumour-specific EVs from GBM patient plasma showed enrichment in GBM-associated genes, when compared to bulk EVs from plasma. We propose that fractionation of EV populations facilitates detection and isolation of tumour-specific EVs for disease monitoring.

5-Hydroxymethylcytosines in circulating cell-free DNA reveal a diagnostic biomarker for glioma

Gliomas typically have unfavorable prognosis, due to late detection and interventions. However, effective biomarkers for early glioma diagnosis based on 5-hydroxymethylcytosines (5 hm C) in circulating cell-free DNA (cfDNA) are not currently available. 5 hm C profiles in GSE132118 set were subjected for establishment of diagnostic model using the LASSO (least absolute shrinkage and selection operator) algorithm. The 5 hm C-based models demonstrated great potency in differentiating healthy subjects from gliomas, with area under the curves (AUCs) > 0.91 in the training and validation sets. Moreover, the indicator performed well in combination with clinicopathological characteristics to differentiate glioblastomas (GBMs) from lower grade glioma (LGGs). Enrichment analysis on 5 hm C profiles displayed great correlation with glioma pathophysiology. The 5 hm C-derived biomarker might act as an effective and non-invasive measure in glioma screening.

Advances in nano-based materials for glioblastoma multiforme diagnosis: A mini-review

The development of nano-based materials for diagnosis enables a more precise prognosis and results. Inorganic, organic, or hybrid nanoparticles using nanomaterials, such as quantum dots, extracellular vesicle systems, and others, with different molecular compositions, have been extensively explored as a better strategy to overcome the blood-brain barrier and target brain tissue and tumors. Glioblastoma multiforme (GBM) is the most common and aggressive primary tumor of the central nervous system, with a short, established prognosis. The delay in early detection is considered a key challenge in designing a precise and efficient treatment with the most encouraging prognosis. Therefore, the present mini-review focuses on discussing distinct strategies presented recently in the literature regarding nanostructures’ use, design, and application for GBM diagnosis.

The road-map for establishment of a prognostic molecular marker panel in glioma using liquid biopsy: current status and future directions

Gliomas are primary intracranial tumors with defined molecular markers available for precise diagnosis. The prognosis of glioma is bleak as there is an overlook of the dynamic crosstalk between tumor cells and components of the microenvironment. Herein, different phases of gliomagenesis are presented with reference to the role and involvement of secreted proteomic markers at various stages of tumor initiation and development. The secreted markers of inflammatory response, namely interleukin-6, tumor necrosis factor-α, interferon-ϒ, and kynurenine, proliferation markers human telomerase reverse transcriptase and microtubule-associated-protein-Tau, and stemness marker human-mobility-group-AThook-1 are involved in glial tumor initiation and growth. Further, hypoxia and angiogenic factors, heat-shock-protein-70, endothelial-growth-factor-receptor-1 and vascular endothelial growth factor play a major role in promoting vascularization and tumor volume expansion. Eventually, molecules such as matrix-metalloprotease-7 and intercellular adhesion molecule-1 contribute to the degradation and remodeling of the extracellular matrix, ultimately leading to glioma progression. Our study delineates the roadmap to develop and evaluate a non-invasive panel of secreted biomarkers using liquid biopsy for precisely evaluating disease progression, to accomplish a clinical translation.

Extracellular Vesicle-Based Multianalyte Liquid Biopsy as a Diagnostic for Cancer

Liquid biopsy is the analysis of materials shed by tumors into circulation, such as circulating tumor cells, nucleic acids, and extracellular vesicles (EVs), for the diagnosis and management of cancer. These assays have rapidly evolved with recent FDA approvals of single biomarkers in patients with advanced metastatic disease. However, they have lacked sensitivity or specificity as a diagnostic in early-stage cancer, primarily due to low concentrations in circulating plasma. EVs, membrane-enclosed nanoscale vesicles shed by tumor and other cells into circulation, are a promising liquid biopsy analyte owing to their protein and nucleic acid cargoes carried from their mother cells, their surface proteins specific to their cells of origin, and their higher concentrations over other noninvasive biomarkers across disease stages. Recently, the combination of EVs with non-EV biomarkers has driven improvements in sensitivity and accuracy; this has been fueled by the use of machine learning (ML) to algorithmically identify and combine multiple biomarkers into a composite biomarker for clinical prediction. This review presents an analysis of EV isolation methods, surveys approaches for and issues with using ML in multianalyte EV datasets, and describes best practices for bringing multianalyte liquid biopsy to clinical implementation. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Telomerase-positive circulating tumor cells are associated with poor prognosis via a neutrophil-mediated inflammatory immune environment in glioma

BACKGROUND

Gliomas are the most common aggressive cancer in the central nervous system. Considering the difficulty in monitoring glioma response and progression, an approach is needed to evaluate the progression or survival of patients with glioma. We propose an application to facilitate clinical detection and treatment monitoring in glioma patients by using telomerase-positive circulating tumor cells (CTCs) and to further evaluate the relationship between the immune microenvironment and CTCs in glioma patients.

METHODS

From October 2014 to June 2017, 106 patients newly diagnosed with glioma were enrolled. We used the telomerase reverse transcriptase CTC detection method to detect and analyze the CTC statuses of glioma patients before and after surgery. FlowSight and FISH confirmed the CTCs detected by the telomerase-based method. To verify the correlation between CTCs and the immune response, peripheral white blood cell RNA sequencing was performed.

RESULTS

CTCs were common in the peripheral blood of glioma patients and were not correlated with the pathological classification or grade of patients. The results showed that the presence of postoperative CTCs but not preoperative CTCs in glioma patients was a poor prognostic factor. The level of postoperative CTCs, which predicts a poor prognosis after surgery, may be associated with neutrophils. RNA sequencing suggested that postoperative CTCs were positively correlated with innate immune responses, especially the activation of neutrophils and the generation of neutrophil extracellular traps, but negatively correlated with the cytotoxic response.

CONCLUSIONS

Our results showed that telomerase-positive CTCs can predict a poor prognosis of patients with glioma. Our results also showed a correlation between CTCs and the immune macroenvironment, which provides a new perspective for the treatment of glioma.

EV Translational Horizons as Viewed Across the Complex Landscape of Liquid Biopsies

Extracellular Vesicle (EV)-based diagnostic and therapeutic tools are an area of intensive study and substantial promise, but EVs as liquid biopsies have advanced years ahead of EVs as therapeutic tools. EVs are emerging as a promising approach for detecting tumors, evaluating the molecular profiles of known disease, and monitoring treatment responses. Although correlative assays based on liquid biopsies are already having an impact on translational studies and clinical practice, much remains to be learned before these assays will be optimized for clinical correlations, functional biological studies, and therapeutic use. What follows is an overview of current evidence supporting the investigation and use of liquid biopsies, organized by specific liquid biopsy components available for analysis, along with a summary of what challenges must be overcome before these assays will provide functional biological insights into the pathogenesis and treatment of disease. The same challenges must also be overcome before it will be feasible to measure and monitor the dosing, distribution, pharmacokinetics, and delivery of EV therapeutics and their cargo in complex biofluids where EVs and circulate with and are co-isolated with a number of other nanoscale materials, including lipoproteins (LPPs), ribonucleoprotein complexes (RNPs), and cell free nucleic acids (cfNA).

Extracellular vesicles: the key for precision medicine in glioblastoma

Glioblastoma (GBM) represents the most aggressive and lethal disease of the central nervous system. Diagnosis is delayed following the occurrence of symptoms, and treatment is based on standardized approaches that are unable to cope with its heterogeneity, mutability, and invasiveness. The follow-up of patients relies on burdensome schedules for magnetic resonance imaging (MRI). However, to personalize treatment, biomarkers and liquid biopsy still represent unmet clinical needs. Extracellular vesicles (EVs) may be the key to revolutionize the entire process of care for patients with GBM. EVs can be collected noninvasively (eg, blood) and impressively possess multilayered information, which is constituted by their concentration and molecular cargo. EV-based liquid biopsy may facilitate GBM diagnosis and enable the implementation of personalized treatment, resulting in customized care for each patient and for each analyzed time point of the disease, thereby tackling the distinctive heterogeneity and mutability of GBM that confounds effective treatment. Herein, we discuss the limitations of current GBM treatment options and the rationale behind the need for personalized care. We also review the evidence supporting GBM-associated EVs as a promising tool capable of fulfilling the still unmet clinical need for effective and timely personalized care of patients with GBM.

Raman Spectral Signatures of Serum-Derived Extracellular Vesicle-Enriched Isolates May Support the Diagnosis of CNS Tumors

Investigating the molecular composition of small extracellular vesicles (sEVs) for tumor diagnostic purposes is becoming increasingly popular, especially for diseases for which diagnosis is challenging, such as central nervous system (CNS) malignancies. Thorough examination of the molecular content of sEVs by Raman spectroscopy is a promising but hitherto barely explored approach for these tumor types. We attempt to reveal the potential role of serum-derived sEVs in diagnosing CNS tumors through Raman spectroscopic analyses using a relevant number of clinical samples. A total of 138 serum samples were obtained from four patient groups (glioblastoma multiforme, non-small-cell lung cancer brain metastasis, meningioma and lumbar disc herniation as control). After isolation, characterization and Raman spectroscopic assessment of sEVs, the Principal Component Analysis-Support Vector Machine (PCA-SVM) algorithm was performed on the Raman spectra for pairwise classifications. Classification accuracy (CA), sensitivity, specificity and the Area Under the Curve (AUC) value derived from Receiver Operating Characteristic (ROC) analyses were used to evaluate the performance of classification. The groups compared were distinguishable with 82.9-92.5% CA, 80-95% sensitivity and 80-90% specificity. AUC scores in the range of 0.82-0.9 suggest excellent and outstanding classification performance. Our results support that Raman spectroscopic analysis of sEV-enriched isolates from serum is a promising method that could be further developed in order to be applicable in the diagnosis of CNS tumors.

Pseudoprogression versus true progression in glioblastoma patients: A multiapproach literature review. Part 2 - Radiological features and metric markers

After chemoradiotherapy for glioblastoma, pseudoprogression can occur and must be distinguished from true progression to correctly manage glioblastoma treatment and follow-up. Conventional treatment response assessment is evaluated via conventional MRI (contrast-enhanced T1-weighted and T2/FLAIR), which is unreliable. The emergence of advanced MRI techniques, MR spectroscopy, and PET tracers has improved pseudoprogression diagnostic accuracy. This review presents a literature review of the different imaging techniques and potential imaging biomarkers to differentiate pseudoprogression from true progression.

Diagnosis of Glioma Molecular Markers by Terahertz Technologies

This review considers glioma molecular markers in brain tissues and body fluids, shows the pathways of their formation, and describes traditional methods of analysis. The most important optical properties of glioma markers in the terahertz (THz) frequency range are also presented. New metamaterial-based technologies for molecular marker detection at THz frequencies are discussed. A variety of machine learning methods, which allow the marker detection sensitivity and differentiation of healthy and tumor tissues to be improved with the aid of THz tools, are considered. The actual results on the application of THz techniques in the intraoperative diagnosis of brain gliomas are shown. THz technologies’ potential in molecular marker detection and defining the boundaries of the glioma’s tissue is discussed.

Small Extracellular Vesicles Isolated from Serum May Serve as Signal-Enhancers for the Monitoring of CNS Tumors

Liquid biopsy-based methods to test biomarkers (e.g., serum proteins and extracellular vesicles) may help to monitor brain tumors. In this proteomics-based study, we aimed to identify a characteristic protein fingerprint associated with central nervous system (CNS) tumors. Overall, 96 human serum samples were obtained from four patient groups, namely glioblastoma multiforme (GBM), non-small-cell lung cancer brain metastasis (BM), meningioma (M) and lumbar disc hernia patients (CTRL). After the isolation and characterization of small extracellular vesicles (sEVs) by nanoparticle tracking analysis (NTA) and atomic force microscopy (AFM), liquid chromatography -mass spectrometry (LC-MS) was performed on two different sample types (whole serum and serum sEVs). Statistical analyses (ratio, Cohen's d, receiver operating characteristic; ROC) were carried out to compare patient groups. To recognize differences between the two sample types, pairwise comparisons (Welch's test) and ingenuity pathway analysis (IPA) were performed. According to our knowledge, this is the first study that compares the proteome of whole serum and serum-derived sEVs. From the 311 proteins identified, 10 whole serum proteins and 17 sEV proteins showed the highest intergroup differences. Sixty-five proteins were significantly enriched in sEV samples, while 129 proteins were significantly depleted compared to whole serum. Based on principal component analysis (PCA) analyses, sEVs are more suitable to discriminate between the patient groups. Our results support that sEVs have greater potential to monitor CNS tumors, than whole serum.

Current and Future Trends on Diagnosis and Prognosis of Glioblastoma: From Molecular Biology to Proteomics

Glioblastoma multiforme is the most aggressive malignant tumor of the central nervous system. Due to the absence of effective pharmacological and surgical treatments, the identification of early diagnostic and prognostic biomarkers is of key importance to improve the survival rate of patients and to develop new personalized treatments. On these bases, the aim of this review article is to summarize the current knowledge regarding the application of molecular biology and proteomics techniques for the identification of novel biomarkers through the analysis of different biological samples obtained from glioblastoma patients, including DNA, microRNAs, proteins, small molecules, circulating tumor cells, extracellular vesicles, etc. Both benefits and pitfalls of molecular biology and proteomics analyses are discussed, including the different mass spectrometry-based analytical techniques, highlighting how these investigation strategies are powerful tools to study the biology of glioblastoma, as well as to develop advanced methods for the management of this pathology.

Pyrosequencing versus methylation-specific PCR for assessment of MGMT methylation in tumor and blood samples of glioblastoma patients

Circulating biomarkers in blood may provide an interesting alternative to risky tissue biopsies in the diagnosis and follow-up of glioblastoma patients. We have assessed MGMT methylation status in blood and tissue samples from unresected glioblastoma patients who had been included in the randomized GENOM-009 trial. Paired blood and tissue samples were assessed by methylation-specific PCR (MSP) and pyrosequencing (PYR). After establishing the minimum PYR cut-off that could yield a significant difference in overall survival, we assessed the sensitivity, specificity, positive predictive value and negative predictive value (NPV) of the analyses. Methylation could be detected in cfDNA by both MSP and PYR but with low concordance with results in tissue. Sensitivity was low for both methods (31% and 38%, respectively), while specificity was higher for MSP in blood than for PYR in plasma (96% vs 76%) and NPV was similar (56 vs 57%). Concordance of results in tissue by MSP and PYR was 84.3% (P < 0.001) and correlated with outcome. We conclude that detection of cfDNA in the blood of glioblastoma patients can be an alternative when tumor tissue is not available but methods for the detection of cfDNA in blood must improve before it can replace analysis in tumor tissue.

The French glioblastoma biobank (FGB): a national clinicobiological database

BACKGROUND

Glioblastomas (GB) are the most common and lethal primary brain tumors. Significant progress has been made toward identifying potential risk factors for GB and diagnostic and prognostic biomarkers. However, the current standard of care for newly diagnosed GB, the Stupp protocol, has remained unchanged for over a decade. Large-scale translational programs based on a large clinicobiological database are required to improve our understanding of GB biology, potentially facilitating the development of personalized and specifically targeted therapies. With this goal in mind, a well-annotated clinicobiological database housing data and samples from GB patients has been set up in France: the French GB biobank (FGB).

METHODS

The biobank contains data and samples from adult GB patients from 24 centers in France providing written informed consent. Clinical and biomaterial data are stored in anonymized certified electronic case report forms. Biological samples (including frozen and formalin-fixed paraffin-embedded tumor tissues, blood samples, and hair) are conserved in certified biological resource centers or tumor tissue banks at each participating center.

RESULTS

Clinical data and biological materials have been collected for 1087 GB patients. A complete set of samples (tumor, blood and hair) is available for 66%, and at least one frozen tumor sample is available for 88% of the GB patients.

CONCLUSIONS

This large biobank is unique in Europe and can support the large-scale translational projects required to improve GB care. Additional biological materials, such as peritumoral brain zone and fecal samples, will be collected in the future, to respond to research needs.

Extracellular Vesicles as Conduits of Non-Coding RNA Emission and Intercellular Transfer in Brain Tumors

Non-coding RNA (ncRNA) species have emerged in as molecular fingerprints and regulators of brain tumor pathogenesis and progression. While changes in ncRNA levels have been traditionally regarded as cell intrinsic there is mounting evidence for their extracellular and paracrine function. One of the key mechanisms that enables ncRNA to exit from cells is their selective packaging into extracellular vesicles (EVs), and trafficking in the extracellular space and biofluids. Vesicular export processes reduce intracellular levels of specific ncRNA in EV donor cells while creating a pool of EV-associated ncRNA in the extracellular space and biofluids that enables their uptake by other recipient cells; both aspects have functional consequences. Cancer cells produce several EV subtypes (exosomes, ectosomes), which differ in their ncRNA composition, properties and function. Several RNA biotypes have been identified in the cargo of brain tumor EVs, of which microRNAs are the most studied, but other species (snRNA, YRNA, tRNA, and lncRNA) are often more abundant. Of particular interest is the link between transforming oncogenes and the biogenesis, cargo, uptake and function of tumor-derived EV, including EV content of oncogenic RNA. The ncRNA repertoire of EVs isolated from cerebrospinal fluid and serum is being developed as a liquid biopsy platform in brain tumors.

Glioblastoma Chemoresistance: The Double Play by Microenvironment and Blood-Brain Barrier

For glioblastoma, the tumor microenvironment (TME) is pivotal to support tumor progression and therapeutic resistance. TME consists of several types of stromal, endothelial and immune cells, which are recruited by cancer stem cells (CSCs) to influence CSC phenotype and behavior. TME also promotes the establishment of specific conditions such as hypoxia and acidosis, which play a critical role in glioblastoma chemoresistance, interfering with angiogenesis, apoptosis, DNA repair, oxidative stress, immune escape, expression and activity of multi-drug resistance (MDR)-related genes. Finally, the blood brain barrier (BBB), which insulates the brain microenvironment from the blood, is strongly linked to the drug-resistant phenotype of glioblastoma, being a major physical and physiological hurdle for the delivery of chemotherapy agents into the brain. Here, we review the features of the glioblastoma microenvironment, focusing on their involvement in the phenomenon of chemoresistance; we also summarize recent advances in generating systems to modulate or bypass the BBB for drug delivery into the brain. Genetic aspects associated with glioblastoma chemoresistance and current immune-based strategies, such as checkpoint inhibitor therapy, are described too.

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.