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Establishment of State-of-the-Art Methods/Techniques and Identification of Novel Biomarkers in Brain Tumor Diagnosis

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A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Cell Biology and Pathology".

Deadline for manuscript submissions: 31 July 2024 | Viewed by 12595

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Special Issue Editor

Prof. Dr. Dimitrios Kanakis

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Guest Editor

Department of Pathology, University of Nicosia Medical School, Nicosia, Cyprus
Interests: neurooncology; neurodegenerative diseases; traumatic brain injury/chronic traumatic encephalopathy; demyelinating diseases; neurodevelopmental disorders; neuromuscular disorders
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Immense progress has been achieved in the diagnostic approaches used for brain tumors.

The current WHO classification for CNS tumors introduces the term “integrated diagnosis”, which encompasses both the characteristic histopathological criteria and the particular molecular “signatures” for some of the most common brain tumors. In this context, there is a constant interest to identify new diagnostic markers that would be able to recognize either the brain tumors already assigned an “integrated diagnosis” or the various newly introduced tumor entities. Alongside these investigations, the development of innovative techniques and methodologies are expected to contribute a lot in the simplicity and accuracy of the brain tumor diagnosis.

This Special Issue aims to present some of the latest advancements and breakthroughs in the field of brain tumor diagnosis. Its scope includes articles that focus on the identification of novel biomarkers, the development of new diagnostic techniques, and the implementation of state-of-the-art methods for the detection and diagnosis of brain tumors. Hence, original research articles or comprehensive review papers that cover a broad range of topics related to brain tumor diagnosis, including but not limited to neuroimaging, molecular biology, pathology, and clinical diagnosis, are welcomed. Submissions that highlight the latest research in personalized medicine, precision diagnostics, and emerging technologies that have the potential to revolutionize the diagnosis and, subsequently, the treatment of brain tumors are also encouraged.

Prof. Dr. Dimitrios Kanakis
Guest Editor

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Keywords

state-of-the-art methods
emerging technologies
brain tumors
diagnostic markers
integrated diagnosis
molecular profile
histopathological features

Published Papers (10 papers)

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Research

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16 pages, 7242 KiB

Open AccessArticle

The Roles of AGTRAP, ALKBH3, DIVERSIN, NEDD8 and RRM1 in Glioblastoma Pathophysiology and Prognosis

by Claudia Alexandra Dumitru, Nikolas Walter, Carl Ludwig Raven Siebert, Frederik Till Alexander Schäfer, Ali Rashidi, Belal Neyazi, Klaus-Peter Stein, Christian Mawrin and Ibrahim Erol Sandalcioglu

Biomedicines 2024, 12(4), 926; https://doi.org/10.3390/biomedicines12040926 - 22 Apr 2024

Viewed by 380

Abstract

This study determined the expression of five novel biomarker candidates in IDH wild-type glioblastoma (GBM) tissues compared to non-malign brain parenchyma, as well as their prognostic relevance for the GBM patients’ outcomes. The markers were analysed by immunohistochemistry in tumour tissues (n = 186) and healthy brain tissues (n = 54). The association with the patients’ overall survival (OS) and progression-free survival (PFS) was assessed by Kaplan–Meier and log-rank test. The prognostic value of the markers was determined using multivariate Cox proportional hazard models. AGTRAP, DIVERSIN, cytoplasmic NEDD8 (NEDD8c) and RRM1 were significantly overexpressed in tumour tissues compared to the healthy brain, while the opposite was observed for ALKBH3. AGTRAP, ALKBH3, NEDD8c and RRM1 were significantly associated with OS in univariate analysis. AGTRAP and RRM1 were also independent prognostic factors for OS in multivariate analysis. For PFS, only AGTRAP and NEDD8c reached significance in univariate analysis. Additionally, AGTRAP was an independent prognostic factor for PFS in multivariate models. Finally, combined analysis of the markers enhanced their prognostic accuracy. The combination AGTRAP/ALKBH3 had the strongest prognostic value for the OS of GBM patients. These findings contribute to a better understanding of the GBM pathophysiology and may help identify novel therapeutic targets in this type of cancer. Full article

(This article belongs to the Special Issue Establishment of State-of-the-Art Methods/Techniques and Identification of Novel Biomarkers in Brain Tumor Diagnosis)

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17 pages, 16280 KiB

Open AccessArticle

Validating Brain Tumor Reporting and Data System (BT-RADS) as a Diagnostic Tool for Glioma Follow-Up after Surgery

by Yassir Edrees Almalki, Mohammad Abd Alkhalik Basha, Maha Ibrahim Metwally, Nesma Adel Zeed, Mohamad Gamal Nada, Sharifa Khalid Alduraibi, Ahmed A. Morsy, Rawda Balata, Ahmed Z. Al Attar, Mona M. Amer, Mohamed Abd El-Aziz Mohamed Farag, Sameh Abdelaziz Aly, Ahmed M. Abdelkhalik Basha and Enas Mahmoud Hamed

Biomedicines 2024, 12(4), 887; https://doi.org/10.3390/biomedicines12040887 - 17 Apr 2024

Viewed by 424

Abstract

Gliomas are a type of brain tumor that requires accurate monitoring for progression following surgery. The Brain Tumor Reporting and Data System (BT-RADS) has emerged as a potential tool for improving diagnostic accuracy and reducing the need for repeated operations. This prospective multicenter study aimed to evaluate the diagnostic accuracy and reliability of BT-RADS in predicting tumor progression (TP) in postoperative glioma patients and evaluate its acceptance in clinical practice. The study enrolled patients with a history of partial or complete resection of high-grade glioma. All patients underwent two consecutive follow-up brain MRI examinations. Five neuroradiologists independently evaluated the MRI examinations using the BT-RADS. The diagnostic accuracy of the BT-RADS for predicting TP was calculated using histopathology after reoperation and clinical and imaging follow-up as reference standards. Reliability based on inter-reader agreement (IRA) was assessed using kappa statistics. Reader acceptance was evaluated using a short survey. The final analysis included 73 patients (male, 67.1%; female, 32.9%; mean age, 43.2 ± 12.9 years; age range, 31–67 years); 47.9% showed TP, and 52.1% showed no TP. According to readers, TP was observed in 25–41.7% of BT-3a, 61.5–88.9% of BT-3b, 75–90.9% of BT-3c, and 91.7–100% of BT-RADS-4. Considering >BT-RADS-3a as a cutoff value for TP, the sensitivity, specificity, and accuracy of the BT-RADS were 68.6–85.7%, 84.2–92.1%, and 78.1–86.3%, respectively, according to the reader. The overall IRA was good (κ = 0.75) for the final BT-RADS classification and very good for detecting new lesions (κ = 0.89). The readers completely agreed with the statement “the application of the BT-RADS should be encouraged” (score = 25). The BT-RADS has good diagnostic accuracy and reliability for predicting TP in postoperative glioma patients. However, BT-RADS 3 needs further improvements to increase its diagnostic accuracy. Full article

(This article belongs to the Special Issue Establishment of State-of-the-Art Methods/Techniques and Identification of Novel Biomarkers in Brain Tumor Diagnosis)

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14 pages, 1226 KiB

Open AccessArticle

Comparison of MRI Sequences to Predict IDH Mutation Status in Gliomas Using Radiomics-Based Machine Learning

by Dilek N. G. Kasap, Nabila Gala Nacul Mora, David A. Blömer, Burak Han Akkurt, Walter Leonhard Heindel, Manoj Mannil and Manfred Musigmann

Biomedicines 2024, 12(4), 725; https://doi.org/10.3390/biomedicines12040725 - 25 Mar 2024

Viewed by 672

Abstract

Objectives: Regarding the 2021 World Health Organization (WHO) classification of central nervous system (CNS) tumors, the isocitrate dehydrogenase (IDH) mutation status is one of the most important factors for CNS tumor classification. The aim of our study is to analyze which of the commonly used magnetic resonance imaging (MRI) sequences is best suited to obtain this information non-invasively using radiomics-based machine learning models. We developed machine learning models based on different MRI sequences and determined which of the MRI sequences analyzed yields the highest discriminatory power in predicting the IDH mutation status. Material and Methods: In our retrospective IRB-approved study, we used the MRI images of 106 patients with histologically confirmed gliomas. The MRI images were acquired using the T1 sequence with and without administration of a contrast agent, the T2 sequence, and the Fluid-Attenuated Inversion Recovery (FLAIR) sequence. To objectively compare performance in predicting the IDH mutation status as a function of the MRI sequence used, we included only patients in our study cohort for whom MRI images of all four sequences were available. Seventy-one of the patients had an IDH mutation, and the remaining 35 patients did not have an IDH mutation (IDH wild-type). For each of the four MRI sequences used, 107 radiomic features were extracted from the corresponding MRI images by hand-delineated regions of interest. Data partitioning into training data and independent test data was repeated 100 times to avoid random effects associated with the data partitioning. Feature preselection and subsequent model development were performed using Random Forest, Lasso regression, LDA, and Naïve Bayes. The performance of all models was determined with independent test data. Results: Among the different approaches we examined, the T1-weighted contrast-enhanced sequence was found to be the most suitable for predicting IDH mutations status using radiomics-based machine learning models. Using contrast-enhanced T1-weighted MRI images, our seven-feature model developed with Lasso regression achieved a mean area under the curve (AUC) of 0.846, a mean accuracy of 0.792, a mean sensitivity of 0.847, and a mean specificity of 0.681. The administration of contrast agents resulted in a significant increase in the achieved discriminatory power. Conclusions: Our analyses show that for the prediction of the IDH mutation status using radiomics-based machine learning models, among the MRI images acquired with the commonly used MRI sequences, the contrast-enhanced T1-weighted images are the most suitable. Full article

(This article belongs to the Special Issue Establishment of State-of-the-Art Methods/Techniques and Identification of Novel Biomarkers in Brain Tumor Diagnosis)

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13 pages, 3748 KiB

Open AccessArticle

Clinicopathological and Molecular Characteristics of IDH-Wildtype Glioblastoma with FGFR3::TACC3 Fusion

by Hyunsik Bae, Boram Lee, Soohyun Hwang, Jiyeon Lee, Hyun-Soo Kim and Yeon-Lim Suh

Biomedicines 2024, 12(1), 150; https://doi.org/10.3390/biomedicines12010150 - 10 Jan 2024

Viewed by 999

Abstract

The World Health Organization Classification of Tumors of the Central Nervous System recently incorporated histological features, immunophenotypes, and molecular characteristics to improve the accuracy of glioblastoma (GBM) diagnosis. FGFR3::TACC3 (F3T3) fusion has been identified as an oncogenic driver in IDH-wildtype GBMs. Recent studies have demonstrated the potential of using FGFR inhibitors in clinical trials and TACC3-targeting agents in preclinical models for GBM treatment. However, there is limited information on the clinicopathological and genetic features of IDH-wildtype GBMs with F3T3 fusion. The aim of this study was to comprehensively investigate the clinical manifestations, histological features, and mutational profiles of F3T3-positive GBMs. Between September 2017 and February 2023, 25 consecutive cases (5.0%) of F3T3-positive GBM were extracted from 504 cases of IDH-wildtype GBM. Clinicopathological information and targeted sequencing results obtained from 25 primary and 4 recurrent F3T3-positive GBMs were evaluated and compared with those from F3T3-negative GBMs. The provisional grades determined by histology only were distributed as follows: 4 (26/29; 89.7%), 3 (2/29; 6.9%), and 2 (1/29; 3.4%). Grade 2–3 tumors were ultimately diagnosed as grade 4 GBMs based on the identification of the TERT promoter mutation and the combined gain of chromosome 7 and loss of chromosome 10 (7+/10−). F3T3-positive GBMs predominantly affected women (2.6 females per male). The mean age of patients with an F3T3-positive GBM at initial diagnosis was 62 years. F3T3-positive GBMs occurred more frequently in the cortical locations compared to F3T3-negative GBMs. Imaging studies revealed that more than one-third (12/29; 41.4%) of F3T3-positive GBMs displayed a circumscribed tumor border. Seven of the seventeen patients (41.2%) whose follow-up periods exceeded 20 months died of the disease. Histologically, F3T3-positive GBMs more frequently showed curvilinear capillary proliferation, palisading nuclei, and calcification compared to F3T3-negative GBMs. Molecularly, the most common alterations observed in F3T3-positive GBMs were TERT promoter mutations and 7+/10−, whereas amplifications of EGFR, PDGFRA, and KIT were not detected at all. Other genetic alterations included CDKN2A/B deletion, PTEN mutation, TP53 mutation, CDK4 amplification, and MDM2 amplification. Our observations suggest that F3T3-positive GBM is a distinct molecular subgroup of the IDH-wildtype GBM. Both clinicians and pathologists should consider this rare entity in the differential diagnosis of diffuse astrocytic glioma to make an accurate diagnosis and to ensure appropriate therapeutic management. Full article

(This article belongs to the Special Issue Establishment of State-of-the-Art Methods/Techniques and Identification of Novel Biomarkers in Brain Tumor Diagnosis)

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25 pages, 9336 KiB

Open AccessArticle

Identification of MDK as a Hypoxia- and Epithelial–Mesenchymal Transition-Related Gene Biomarker of Glioblastoma Based on a Novel Risk Model and In Vitro Experiments

by Minqi Xia, Shiao Tong and Ling Gao

Biomedicines 2024, 12(1), 92; https://doi.org/10.3390/biomedicines12010092 - 01 Jan 2024

Viewed by 1072

Abstract

Background: Tumor cells are commonly exposed to a hypoxic environment, which can easily induce the epithelial–mesenchymal transition (EMT) of tumor cells, further affecting tumor proliferation, invasion, metastasis, and drug resistance. However, the predictive role of hypoxia and EMT-related genes in glioblastoma (GBM) has not been investigated. Methods: Intersection genes were identified by weighted correlation network analysis (WGCNA) and differential expression analyses, and a risk model was further constructed by LASSO and Cox analyses. Clinical, immune infiltration, tumor mutation, drug treatment, and enrichment profiles were analyzed based on the risk model. The expression level of the MDK gene was tested using RT-PCR, immunohistochemistry, and immunofluorescence. CCK8 and EdU were employed to determine the GBM cells’ capacity for proliferation while the migration and invasion ability were detected by a wound healing assay and transwell assay, respectively. Results: Based on the GBM data of the TCGA and GTEx databases, 58 intersection genes were identified, and a risk model was constructed. The model was verified in the CGGA cohort, and its accuracy was confirmed by the ROC curve (AUC = 0.807). After combining clinical subgroups, univariate and multivariate Cox regression analyses showed that risk score and age were independent risk factors for GBM patients. Furthermore, our subsequent analysis of immune infiltration, tumor mutation, and drug treatment showed that risk score and high- and low-risk groups were associated with multiple immune cells, mutated genes, and drugs. Enrichment analysis indicated that the differences between high- and low-risk groups were manifested in tumor-related pathways, including the PI3K-AKT and JAK-STAT pathways. Finally, in vivo experiments proved that the hypoxia environment promoted the expression of MDK, and MDK knockdown reduced the proliferation, migration, and EMT of GBM cells induced by hypoxia. Conclusions: Our novel prognostic correlation model provided more potential treatment strategies for GBM patients. Full article

(This article belongs to the Special Issue Establishment of State-of-the-Art Methods/Techniques and Identification of Novel Biomarkers in Brain Tumor Diagnosis)

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20 pages, 3176 KiB

Open AccessArticle

Biomarkers in Adult-Type Diffuse Gliomas: Elevated Levels of Circulating Vesicular Heat Shock Protein 70 Serve as a Biomarker in Grade 4 Glioblastoma and Increase NK Cell Frequencies in Grade 3 Glioma

by Philipp Lennartz, Dennis Thölke, Ali Bashiri Dezfouli, Mathias Pilz, Dominik Lobinger, Verena Messner, Hannah Zanth, Karen Ainslie, Morteza Hasanzadeh Kafshgari, Gerhard Rammes, Markus Ballmann, Martin Schlegel, Gemma Ann Foulds, Alan Graham Pockley, Friederike Schmidt-Graf and Gabriele Multhoff

Biomedicines 2023, 11(12), 3235; https://doi.org/10.3390/biomedicines11123235 - 07 Dec 2023

Cited by 1 | Viewed by 1198

Abstract

The presence of circulating Hsp70 levels and their influence on the immunophenotype of circulating lymphocyte subsets were examined as diagnostic/prognostic biomarkers for the overall survival (OS) in patients with IDH-mutant WHO grade 3 oligodendroglioma, astrocytoma, and IDH-wildtype grade 4 glioblastoma (GBM). Vesicular and free Hsp70 in the plasma/serum was measured using the Hsp70-exo and R&D Systems DuoSet^® Hsp70 ELISAs. The immunophenotype and membrane Hsp70 status was determined by multiparameter flow cytometry on peripheral blood lymphocytes and single-cell suspensions of tumor specimens and cultured cells. Compared to healthy controls, circulating vesicular Hsp70 levels were significantly increased in patients with GBM, concomitant with a significant decrease in the proportion of CD3+/CD4+ helper T cells, whereas the frequency of NK cells was most prominently increased in patients with grade 3 gliomas. Elevated circulating Hsp70 levels and a higher prevalence of activated CD3−/CD56+/CD94+/CD69+ NK cells were associated with an improved OS in grade 3 gliomas, whereas high Hsp70 levels and low CD3+/CD4+ frequencies were associated with an adverse OS in GBM. It is assumed that a reduced membrane Hsp70 density on grade 4 versus grade 3 primary glioma cells and reduced CD3+/CD4+ T cell counts in GBM might drive an immunosuppressive tumor microenvironment. Full article

(This article belongs to the Special Issue Establishment of State-of-the-Art Methods/Techniques and Identification of Novel Biomarkers in Brain Tumor Diagnosis)

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19 pages, 2416 KiB

Open AccessArticle

Identification of CD44 as a Reliable Biomarker for Glioblastoma Invasion: Based on Magnetic Resonance Imaging and Spectroscopic Analysis of 5-Aminolevulinic Acid Fluorescence

by Akihiro Inoue, Takanori Ohnishi, Masahiro Nishikawa, Hideaki Watanabe, Kosuke Kusakabe, Mashio Taniwaki, Hajime Yano, Yoshihiro Ohtsuka, Shirabe Matsumoto, Satoshi Suehiro, Daisuke Yamashita, Seiji Shigekawa, Hisaaki Takahashi, Riko Kitazawa, Junya Tanaka and Takeharu Kunieda

Biomedicines 2023, 11(9), 2369; https://doi.org/10.3390/biomedicines11092369 - 24 Aug 2023

Cited by 2 | Viewed by 1066

Abstract

Recurrent glioblastoma multiforme (GBM) is largely attributed to peritumoral infiltration of tumor cells. As higher CD44 expression in the tumor periphery correlates with higher risk of GBM invasion, the present study analyzed the relationship between CD44 expression and magnetic resonance imaging (MRI)-based invasiveness of GBM on a large scale. We also quantitatively evaluated GBM invasion using 5-aminolevulinic acid (5-ALA) spectroscopy to investigate the relationship between CD44 expression and tumor invasiveness as evaluated by intraoperative 5-ALA intensity. Based on MRI, GBM was classified as high-invasive type in 28 patients and low-invasive type in 22 patients. High-invasive type expressed CD44 at a significantly higher level than low-invasive type and was associated with worse survival. To quantitatively analyze GBM invasiveness, the relationship between tumor density in the peritumoral area and the spectroscopic intensity of 5-ALA was investigated. Spectroscopy showed that the 5-ALA intensity of infiltrating tumor cells correlated with tumor density as represented by the Ki-67 staining index. No significant correlation between CD44 and degree of 5-ALA-based invasiveness of GBM was found, but invasiveness of GBM as evaluated by 5-ALA matched the classification from MRI in all except one case, indicating that CD44 expression at the GBM periphery could provide a reliable biomarker for invasiveness in GBM. Full article

(This article belongs to the Special Issue Establishment of State-of-the-Art Methods/Techniques and Identification of Novel Biomarkers in Brain Tumor Diagnosis)

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22 pages, 6894 KiB

Open AccessArticle

Adult IDH Wild-Type Glioblastoma Ultrastructural Investigation Suggests a Possible Correlation between Morphological Biomarkers and Ki-67 Index

by Pietro Familiari, Michela Relucenti, Pierfrancesco Lapolla, Mauro Palmieri, Manila Antonelli, Loredana Cristiano, Claudio Barbaranelli, Myriam Catalano, Luca D’Angelo, Giuseppe Familiari, Antonio Santoro, Alessandro Frati and Placido Bruzzaniti

Biomedicines 2023, 11(7), 1968; https://doi.org/10.3390/biomedicines11071968 - 12 Jul 2023

Cited by 2 | Viewed by 1941

Abstract

Glioblastoma is an aggressive brain tumor with an average life expectancy between 14 and 16 months after diagnosis. The Ki-67 labeling index (LI), a measure of cellular proliferation, is emerging as a prognostic marker in GBM. In this study, we investigated the ultrastructure of glioblastoma tissue from 9 patients with the same molecular profile (adult IDH wild-type glioblastoma, wild-type ATRX, and positive for TP53 expression, GFAP expression, and EGFR overexpression) to find possible ultrastructural features to be used as biomarkers and correlated with the only parameter that differs among our samples, the Ki-67 LI. Our main results were the visualization of the anatomical basis of astrocyte-endothelial cells crosstalk; the ultrastructural in situ imaging of clusters of hyperactivated microglia cells (MsEVs); the ultrastructural in situ imaging of microglia cells storing lipid vesicles (MsLVs); the ultrastructural in situ imaging of neoplastic cells mitophagy (NCsM). The statistical analysis of our data indicated that MsEVs and MsLVs correlate with the Ki-67 LI value. We can thus assume they are good candidates to be considered morphological biomarkers correlating to Ki-67 LI. The role of NCsM instead must be further evaluated. Our study findings demonstrate that by combining ultrastructural characteristics with molecular information, we can discover biomarkers that have the potential to enhance diagnostic precision, aid in treatment decision-making, identify targets for therapy, and enable personalized treatment plans tailored to each patient. However, further research with larger sample sizes is needed to validate these findings and fully utilize the potential of ultrastructural analysis in managing glioblastoma. Full article

(This article belongs to the Special Issue Establishment of State-of-the-Art Methods/Techniques and Identification of Novel Biomarkers in Brain Tumor Diagnosis)

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Review

Jump to: Research

17 pages, 299 KiB

Open AccessReview

Advancements in Glioma Care: Focus on Emerging Neurosurgical Techniques

by Matteo De Simone, Valeria Conti, Giuseppina Palermo, Lucio De Maria and Giorgio Iaconetta

Biomedicines 2024, 12(1), 8; https://doi.org/10.3390/biomedicines12010008 - 20 Dec 2023

Cited by 2 | Viewed by 1184

Abstract

Background: Despite significant advances in understanding the molecular pathways of glioma, translating this knowledge into effective long-term solutions remains a challenge. Indeed, gliomas pose a significant challenge to neurosurgical oncology because of their diverse histopathological features, genetic heterogeneity, and clinical manifestations. Relevant sections: This study focuses on glioma complexity by reviewing recent advances in their management, also considering new classification systems and emerging neurosurgical techniques. To bridge the gap between new neurosurgical approaches and standards of care, the importance of molecular diagnosis and the use of techniques such as laser interstitial thermal therapy (LITT) and focused ultrasound (FUS) are emphasized, exploring how the integration of molecular knowledge with emerging neurosurgical approaches can personalize and improve the treatment of gliomas. Conclusions: The choice between LITT and FUS should be tailored to each case, considering factors such as tumor characteristics and patient health. LITT is favored for larger, complex tumors, while FUS is standard for smaller, deep-seated ones. Both techniques are equally effective for small and superficial tumors. Our study provides clear guidance for treating pediatric low-grade gliomas and highlights the crucial roles of LITT and FUS in managing high-grade gliomas in adults. This research sets the stage for improved patient care and future developments in the field of neurosurgery. Full article

(This article belongs to the Special Issue Establishment of State-of-the-Art Methods/Techniques and Identification of Novel Biomarkers in Brain Tumor Diagnosis)

19 pages, 950 KiB

Open AccessReview

Advances on Liquid Biopsy Analysis for Glioma Diagnosis

by Panagiotis Skouras, Mariam Markouli, Theodosis Kalamatianos, George Stranjalis, Penelope Korkolopoulou and Christina Piperi

Biomedicines 2023, 11(9), 2371; https://doi.org/10.3390/biomedicines11092371 - 24 Aug 2023

Cited by 3 | Viewed by 1804

Abstract

Gliomas comprise the most frequent primary central nervous system (CNS) tumors, characterized by remarkable genetic and epigenetic heterogeneity, difficulty in monitoring, and increased relapse and mortality rates. Tissue biopsy is an established method of tumor cell collection and analysis that enables diagnosis, classification of different tumor types, and prediction of prognosis upon confirmation of tumor’s location for surgical removal. However, it is an invasive and often challenging procedure that cannot be used for frequent patient screening, detection of mutations, disease monitoring, or resistance to therapy. To this end, the minimally invasive procedure of liquid biopsy has emerged, allowing effortless tumor sampling and enabling continuous monitoring. It is considered a novel preferable way to obtain faster data on potential tumor risk, personalized diagnosis, prognosis, and recurrence evaluation. The purpose of this review is to describe the advances on liquid biopsy for glioma diagnosis and management, indicating several biomarkers that can be utilized to analyze tumor characteristics, such as cell-free DNA (cfDNA), cell-free RNA (cfRNA), circulating proteins, circulating tumor cells (CTCs), and exosomes. It further addresses the benefit of combining liquid biopsy with radiogenomics to facilitate early and accurate diagnoses, enable precise prognostic assessments, and facilitate real-time disease monitoring, aiming towards more optimal treatment decisions. Full article

(This article belongs to the Special Issue Establishment of State-of-the-Art Methods/Techniques and Identification of Novel Biomarkers in Brain Tumor Diagnosis)

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