Malignant gliomas: current perspectives in diagnosis, treatment, and early response assessment using advanced quantitative imaging methods

Prognostic significance of oligodendrocyte transcription factor 2 expression in glioma patients: A systematic review and meta-analysis

BACKGROUND

Gliomas are the most common primary central nervous system neoplasm. Despite recent advances in the diagnosis and treatment of gliomas, patient prognosis remains dismal. Therefore, it is imperative to identify novel diagnostic biomarkers and therapeutic targets of glioma to effectively improve treatment outcomes.

AIM

To investigate the association between oligodendrocyte transcription factor 2 (Olig2) expression and the outcomes of glioma patients.

METHODS

The PubMed, Embase, Cochrane Library, and China National Knowledge Infrastructure databases were searched for studies (published up to October 2023) that investigated the relationship between Olig2 expression and prognosis of glioma patients. The quality of the studies was assessed using the Newcastle Ottawa Scale. Data analyses were performed using Stata Version 12.0 software.

RESULTS

A total of 1205 glioma patients from six studies were included in the meta-analysis. High Olig2 expression was associated with better outcomes in glioma patients [hazard ratio (HR): 0.81; 95% (confidence interval) CI: 0.51-1.27; P = 0.000]. Furthermore, the results of subgroup meta-analysis showed that high expression of Olig2 was associated with poor overall survival in European patients (HR: 1.34; 95%CI: 0.79-2.27) and better prognosis in Asian patients (HR: 0.43; 95%CI: 0.22-0.84). The sensitivity analysis showed that no single study had a significant effect on pooled HR, and there was also no indication of publication bias according to the Egger’s and Begger’s P value test or funnel plot test.

CONCLUSION

High Olig2 expression may have a positive impact on the prognosis of glioma patients, and should be investigated further as a prognostic biomarker and therapeutic target for glioma.

From Text to Insight: A Natural Language Processing-Based Analysis of Topics and Trends in Neurosurgery

BACKGROUND AND OBJECTIVES

Neurosurgical research is a rapidly evolving field, with new research topics emerging continually. To provide a clearer understanding of the evolving research landscape, our study aimed to identify and analyze the prevalent research topics and trends in Neurosurgery.

METHODS

We used BERTopic, an advanced natural language processing-based topic modeling approach, to analyze papers published in the journal Neurosurgery . Using this method, topics were identified based on unique sets of keywords that encapsulated the core themes of each article. Linear regression models were then trained on the topic probabilities to identify trends over time, allowing us to identify "hot" (growing in prominence) and "cold" (decreasing in prominence) topics. We also performed a focused analysis of the trends in the current decade.

RESULTS

Our analysis led to the categorization of 12 438 documents into 49 distinct topics. The topics covered a wide range of themes, with the most commonly identified topics being "Spinal Neurosurgery" and "Treatment of Cerebral Ischemia." The hottest topics of the current decade were "Peripheral Nerve Surgery," "Unruptured Aneurysms," and "Endovascular Treatments" while the cold topics were "Chiari Malformations," "Thromboembolism Prophylaxis," and "Infections."

CONCLUSION

Our study underscores the dynamic nature of neurosurgical research and the evolving focus of the field. The insights derived from the analysis can guide future research directions, inform policy decisions, and identify emerging areas of interest. The use of natural language processing in synthesizing and analyzing large volumes of academic literature demonstrates the potential of advanced analytical techniques in understanding the research landscape, paving the way for similar analyses across other medical disciplines.

A Wearable Fluorescence Imaging Device for Intraoperative Identification of Human Brain Tumors

Malignant glioma (MG) is the most common type of primary malignant brain tumors. Surgical resection of MG remains the cornerstone of therapy and the extent of resection correlates with patient survival. A limiting factor for resection, however, is the difficulty in differentiating the tumor from normal tissue during surgery. Fluorescence imaging is an emerging technique for real-time intraoperative visualization of MGs and their boundaries. However, most clinical grade neurosurgical operative microscopes with fluorescence imaging ability are hampered by low adoption rates due to high cost, limited portability, limited operation flexibility, and lack of skilled professionals with technical knowledge. To overcome the limitations, we innovatively integrated miniaturized light sources, flippable filters, and a recording camera to the surgical eye loupes to generate a wearable fluorescence eye loupe (FLoupe) device for intraoperative imaging of fluorescent MGs. Two FLoupe prototypes were constructed for imaging of Fluorescein and 5-aminolevulinic acid (5-ALA), respectively. The wearable FLoupe devices were tested on tumor-simulating phantoms and patients with MGs. Comparable results were observed against the standard neurosurgical operative microscope (PENTERO® 900) with fluorescence kits. The affordable and wearable FLoupe devices enable visualization of both color and fluorescence images with the same quality as the large and expensive stationary operative microscopes. The wearable FLoupe device allows for a greater range of movement, less obstruction, and faster/easier operation. Thus, it reduces surgery time and is more easily adapted to the surgical environment than unwieldy neurosurgical operative microscopes. Clinical and Translational Impact Statement-The affordable and wearable fluorescence imaging device developed in this study enables neurosurgeons to observe brain tumors with the same clarity and greater flexibility compared to bulky and costly operative microscopes.

Auto-Segmentation and Classification of Glioma Tumors with the Goals of Treatment Response Assessment Using Deep Learning Based on Magnetic Resonance Imaging

Glioma is the most common primary intracranial neoplasm in adults. Radiotherapy is a treatment approach in glioma patients, and Magnetic Resonance Imaging (MRI) is a beneficial diagnostic tool in treatment planning. Treatment response assessment in glioma patients is usually based on the Response Assessment in Neuro Oncology (RANO) criteria. The limitation of assessment based on RANO is two-dimensional (2D) manual measurements. Deep learning (DL) has great potential in neuro-oncology to improve the accuracy of response assessment. In the current research, firstly, the BraTS 2018 Challenge dataset included 210 HGG and 75 LGG were applied to train a designed U-Net network for automatic tumor and intra-tumoral segmentation, followed by training of the designed classifier with transfer learning for determining grading HGG and LGG. Then, designed networks were employed for the segmentation and classification of local MRI images of 49 glioma patients pre and post-radiotherapy. The results of tumor segmentation and its intra-tumoral regions were utilized to determine the volume of different regions and treatment response assessment. Treatment response assessment demonstrated that radiotherapy is effective on the whole tumor and enhancing region with p-value ≤ 0.05 with a 95% confidence level, while it did not affect necrosis and peri-tumoral edema regions. This work demonstrated the potential of using deep learning in MRI images to provide a beneficial tool in the automated treatment response assessment so that the patient can obtain the best treatment.

Downfield Proton MRSI at 3 Tesla: A Pilot Study in Human Brain Tumors

PURPOSE

To investigate the use of 3D downfield proton magnetic resonance spectroscopic imaging (DF-MRSI) for evaluation of tumor recurrence in patients with glioblastoma (GBM).

METHODS

Seven patients (4F, age range 44-65 and mean ± standard deviation 59.3 ± 7.5 years) with previously treated GBM were scanned using a recently developed 3D DF-MRSI sequence at 3T. Short TE 3D DF-MRSI and water reference 3D-MRSI scans were collected with a nominal spatial resolution of 0.7 cm3. DF volume data in eight slices covered 12 cm of brain in the cranio-caudal axis. Data were analyzed using the 'LCModel' program and a basis set containing nine peaks ranging in frequency between 6.83 to 8.49 ppm. The DF8.18 (assigned to amides) and DF7.90 peaks were selected for the creation of metabolic images and statistical analysis. Longitudinal MR images and clinical history were used to classify brain lesions as either recurrent tumor or treatment effect, which may include necrosis. DF-MRSI data were compared between lesion groups (recurrent tumor, treatment effect) and normal-appearing brain.

RESULTS

Of the seven brain tumor patients, two were classified as having recurrent tumor and the rest were classified as treatment effect. Amide metabolite levels from recurrent tumor regions were significantly (p < 0.05) higher compared to both normal-appearing brain and treatment effect regions. Amide levels in lesion voxels classified as treatment effect were significantly lower than normal brain.

CONCLUSIONS

3D DF-MRSI in human brain tumors at 3T is feasible and was well tolerated by all patients enrolled in this preliminary study. Amide levels measured by 3D DF-MRSI were significantly different between treatment effect and tumor regrowth.

miR‑137 is a diagnostic tumor‑suppressive miRNA that targets SPHK2 to promote M1‑type tumor‑associated macrophage polarization

The present study investigated the expression level of microRNA (miR)-137 in glioma tissues and cell lines and explored its potential diagnostic significance as well as its function effects on glioma cells. miR-137 expression level was detected in glioma tissues using in situ hybridization, and in glioma cell lines using reverse transcription-quantitative PCR (RT-qPCR). The diagnostic significance of miR-137 in glioma was assessed using receiver operating characteristic curve analyses. Quantibody® Human Inflammation Array 1 was used to evaluate the impact of ectopic miR-137 expression on release of cytokines in glioma cell lines. IL-13, TNF-α and IFN-γ levels were detected using ELISA. To confirm that sphingosine kinase 2 (SPHK2) is a target of miR-137, RT-qPCR, western blot analysis and dual-luciferase assay were adopted. The results demonstrated that miR-137 expression was downregulated in both glioma tissues and cell lines. Downregulation of miR-137 was significantly associated with high grade gliomas. Additionally, it was found that overexpression of miR-137 reduced IL-13, but promoted TNFα and IFN-γ production. SPHK2 knockdown inhibited IL-13 release, promoted TNF-α and IFN-γ production. SPHK2 was a direct target of miR-137. Collectively, the results of the present study indicated that miR-137 expression plays a tumor-suppressive role in glioma. It is downregulated in glioma and may promote M1-type TAMs polarization, and may be a diagnostic biomarker and potential therapeutic strategy for glioma treatment in the future.

A multi-label CNN model for the automatic detection and segmentation of gliomas using [18F]FET PET imaging

PURPOSE

The aim of this study was to develop a convolutional neural network (CNN) for the automatic detection and segmentation of gliomas using [18F]fluoroethyl-L-tyrosine ([18F]FET) PET.

METHODS

Ninety-three patients (84 in-house/7 external) who underwent a 20-40-min static [18F]FET PET scan were retrospectively included. Lesions and background regions were defined by two nuclear medicine physicians using the MIM software, such that delineations by one expert reader served as ground truth for training and testing the CNN model, while delineations by the second expert reader were used to evaluate inter-reader agreement. A multi-label CNN was developed to segment the lesion and background region while a single-label CNN was implemented for a lesion-only segmentation. Lesion detectability was evaluated by classifying [18F]FET PET scans as negative when no tumor was segmented and vice versa, while segmentation performance was assessed using the dice similarity coefficient (DSC) and segmented tumor volume. The quantitative accuracy was evaluated using the maximal and mean tumor to mean background uptake ratio (TBRmax/TBRmean). CNN models were trained and tested by a threefold cross-validation (CV) using the in-house data, while the external data was used for an independent evaluation to assess the generalizability of the two CNN models.

RESULTS

Based on the threefold CV, the multi-label CNN model achieved 88.9% sensitivity and 96.5% precision for discriminating between positive and negative [18F]FET PET scans compared to a 35.3% sensitivity and 83.1% precision obtained with the single-label CNN model. In addition, the multi-label CNN allowed an accurate estimation of the maximal/mean lesion and mean background uptake, resulting in an accurate TBRmax/TBRmean estimation compared to a semi-automatic approach. In terms of lesion segmentation, the multi-label CNN model (DSC = 74.6 ± 23.1%) demonstrated equal performance as the single-label CNN model (DSC = 73.7 ± 23.2%) with tumor volumes estimated by the single-label and multi-label model (22.9 ± 23.6 ml and 23.1 ± 24.3 ml, respectively) closely approximating the tumor volumes estimated by the expert reader (24.1 ± 24.4 ml). DSCs of both CNN models were in line with the DSCs by the second expert reader compared with the lesion segmentations by the first expert reader, while detection and segmentation performance of both CNN models as determined with the in-house data were confirmed by the independent evaluation using external data.

CONCLUSION

The proposed multi-label CNN model detected positive [18F]FET PET scans with high sensitivity and precision. Once detected, an accurate tumor segmentation and estimation of background activity was achieved resulting in an automatic and accurate TBRmax/TBRmean estimation, such that user interaction and potential inter-reader variability can be minimized.

Paeoniflorin Regulates NEDD4L/STAT3 Pathway to Induce Ferroptosis in Human Glioma Cells

Background

Paeoniflorin is an active component of a widely used traditional Chinese medicine with antitumor activity through ferroptosis induction. It has been reported recently that ferroptosis is emerging in certain types of cancer; however, its relevance in glioma is still not well studied.

Methods

CCK8 assay was performed for cell proliferation. Expression of mRNA and protein was tested by qPCR and western blot, respectively. Clinical section samples were detected by IHC. The relationship between NEDD4L and STAT3 was validated by a coimmunoprecipitation assay. Apoptosis was identified by TUNEL assay. A xenograft mouse model was utilized to validate the potential of paeoniflorin toward glioma cancer cells.

Results

The data suggested that paeoniflorin could increase NEDD4L expression in glioma cells. The NEDD4L expression level was lower in glioma cancer tissues compared to adjacent normal tissues, and it correlates with poor prognosis. Meanwhile, NEDD4L mediates the ubiquitination of STAT3. Furthermore, increased NEDD4L significantly inhibited cell viability and induced accumulation of intracellular ROS levels, accompanied by decreased expression of key ferroptosis factors Nrl2 and GPX4, while NEDD4L knockdown had a reverse effect, suggesting that ferroptosis could be involved. NEDD4L-induced ferroptosis could be rescued by forced expression of STAT3. A xenograft nude mouse model showed that paeoniflorin inhibits tumor growth and further sensitizes glioma cells to RSL3, another well-known ferroptosis inducer.

Conclusions

In summary, this study demonstrated that paeoniflorin might function as an effective drug for glioma by inducing ferroptosis via upregulation of NEDD4L and repression of Nrl2, GPX4, and STAT3.

The role of preoperative inflammatory markers in patients with central nervous system tumors, focus on glioma

BACKGROUND

CNS tumors, particularly gliomas, are associated with a high rate of disability and lethality, and are typically diagnosed with histopathology and immunohistochemistry. Our research aims to develop a minimally invasive method for diagnosing, grading and molecular typing glioma.

METHODS

We collected patients who underwent surgery for glioma, Trigeminal neuralgia/Hemifacial spasm, schwannoma, pituitary adenomas and meningioma at our hospital from June 2019 to June 2021. Preoperative WBCs, neutrophils, lymphocytes, monocytes, platelet counts and albumin levels were collected. Preoperative NLR, dNLR, PLR, LMR and PNI were calculated, and the correlation between them and glioma diagnosis as well as grading was analyzed. We also evaluated the diagnostic significance of NLR, dNLR, PLR, LMR, PNI and their combinations for gliomas, particularly GBM, as well as the diagnostic significance of IDH molecular typing of gliomas.

RESULTS

There were 182 healthy samples and 3101 diseased samples in our study. Compared with other groups, glioma patients had significantly higher preoperative NLR, dNLR and PLR values, but lower LMR and PNI values. Further analysis showed that NLR, dNLR, and PLR were positively correlated with glioma grading, while LMR and PNI were negatively correlated with glioma grading. For the diagnosis of glioma, NLR showed a maximum AUC value of 0.8099 (0.7823-0.8374). For GBM, NLR showed a maximum AUC value of 0.9585 (0.9467-0.9703). In the combination, NLR+dNLR showed the highest AUC value of 0.8070(0.7849-0.8291). NLR showed significant statistical significance in all grades of glioma IDH molecular typing, while PLR did not show statistical significance.

CONCLUSIONS

NLR has the greatest value for the diagnosis, differential diagnosis, grading and molecular typing of gliomas. The NLR+dNLR combination also showed high sensitivity and specificity. We believe that inflammatory parameters may serve as economical and specific markers for glioma diagnosis, grading, molecular typing, and progression.

Optimization of Tumor Targeting Gold Nanoparticles for Glioblastoma Applications

Glioblastoma brain tumors represent an aggressive form of gliomas that is hallmarked by being extremely invasive and aggressive due to intra and inter-tumoral heterogeneity. This complex tumor microenvironment makes even the newer advancements in glioblastoma treatment less effective long term. In developing newer treatment technologies against glioblastoma, one should tailor the treatment to the tumor microenvironment, thus allowing for a more robust and sustained anti-glioblastoma effect. Here, we present a novel gold nanoparticle therapy explicitly designed for bioactivity against glioblastoma representing U87MG cell lines. We employ standard conjugation techniques to create oligonucleotide-coated gold nanoparticles exhibiting strong anti-glioblastoma behavior and optimize their design to maximize bioactivity against glioblastoma. Resulting nanotherapies are therapy specific and show upwards of 75% inhibition in metabolic and proliferative activity with stark effects on cellular morphology. Ultimately, these gold nanotherapies are a good base for designing more multi-targeted approaches to fighting against glioblastoma.

Androgen Receptor Expression in the Various Regions of Resected Glioblastoma Multiforme Tumors and in an In Vitro Model

Glioblastoma multiforme (GBM) is a malignant glioma, difficult to detect and with the lowest survival rates among gliomas. Its greater incidence among men and its higher survival rate among premenopausal women suggest that it may be associated with the levels of androgens. As androgens stimulate the androgen receptor (AR), which acts as a transcription factor, the aim of this study was the investigate the role of AR in the progression of GBM. The study was conducted on tissues collected from three regions of GBM tumors (tumor core, enhancing tumor region, and peritumoral area). In addition, an in vitro experiment was conducted on U-87 cells under various culture conditions (necrotic, hypoxic, and nutrient-deficient), mimicking the conditions in a tumor. In both of the models, androgen receptor expression was determined at the gene and protein levels, and the results were confirmed by confocal microscopy and immunohistochemistry. AR mRNA expression was higher under nutrient-deficient conditions and lower under hypoxic conditions in vitro. However, there were no differences in AR protein expression. No differences in AR mRNA expression were observed between the tested tumor structures taken from patients. No differences in AR mRNA expression were observed between the men and women. However, AR protein expression in tumors resected from patients was higher in the enhancing tumor region and in the peritumoral area than in the tumor core. In women, higher AR expression was observed in the peritumoral area than in the tumor core. AR expression in GBM tumors did not differ significantly between men and women, which suggests that the higher incidence of GBM in men is not associated with AR expression. In the group consisting of men and women, AR expression varied between the regions of the tumor: AR expression was higher in the enhancing tumor region and in the peritumoral area than in the tumor core, showing a dependence on tumor conditions (hypoxia and insufficient nutrient supply).

Preparation, applications, and challenges of functional DNA nanomaterials

As a carrier of genetic information, DNA is a versatile module for fabricating nanostructures and nanodevices. Functional molecules could be integrated into DNA by precise base complementary pairing, greatly expanding the functions of DNA nanomaterials. These functions endow DNA nanomaterials with great potential in the application of biomedical field. In recent years, functional DNA nanomaterials have been rapidly investigated and perfected. There have been reviews that classified DNA nanomaterials from the perspective of functions, while this review primarily focuses on the preparation methods of functional DNA nanomaterials. This review comprehensively introduces the preparation methods of DNA nanomaterials with functions such as molecular recognition, nanozyme catalysis, drug delivery, and biomedical material templates. Then, the latest application progress of functional DNA nanomaterials is systematically reviewed. Finally, current challenges and future prospects for functional DNA nanomaterials are discussed.

The Impact of Extent of Resection on the Prognosis of Glioblastoma Multiforme: A Systematic Review and Meta-analysis

Purpose: To investigate the predictor factors of mortality describing the prognosis of primary surgical resection of Glioblastoma Multiforme (GBM). Materials and Methods: A systemic search was conducted from electronic databases (PubMed/Medline, Cochrane Library, and Google Scholar) from inception to 12th September 2021.  All statistical analysis was conducted in Review Manager 5.4.1. Studies meeting inclusion criteria were selected. A random-effect model was used when heterogeneity was seen to pool the studies, and the result were reported in the Hazards Ratio (HR) and corresponding 95% Confidence interval (CI). Result: Twenty-three cohort studies were selected for meta-analysis. There was statistically significant effect of extent of resection on prognosis of surgery in GBM patients (HR= 0.90 [0.86, 0.95]; p< 0.0001; I2= 96%), male gender (HR= 1.19 [1.06, 1.34]; p= 0.002; I2= 0%) and decrease Karnofsky Performance Status (HR= 0.97 [0.95, 0.99]; p= 0.003; I2= 90%). Age and tumor volume was also analyzed in the study. Conclusion: The results of our meta-analysis suggested that age, gender, pre-operative KPS score and extent of resection have significant effects on the post-surgical mortality rate, therefore, these factors can be used significant predictor of mortality in GBM patients.

Potential of Novel Methyl Jasmonate Analogs as Anticancer Agents to Metabolically Target HK-2 Activity in Glioblastoma Cells

Change in the energy metabolism of cancer cells, which display significant differences compared to normal cells, is a rising phenomenon in developing new therapeutic approaches against cancers. One of the metabolic enzymes, hexokinase-II (HK-II) is involved in glycolysis, and inhibiting the HK-II activity may be a potential metabolic target for cancer therapy as most of the drugs in clinical use act on DNA damage. Methyl jasmonate (MJ) is one of the compounds blocking HK-II activity in cancer cells. In a previous study, we showed that the novel MJ analogs inhibit HK-II activity through VDAC detachment from the mitochondria. In this study, to evaluate the potential of targeting HK-2 activity, through patient cohort analysis, we first determined HK-2 expression levels and prognostic significance in highly lethal glioblastoma (GBM) brain tumor. We then examined the in vitro therapeutic effects of the novel analogs in the GBM cells. Here, we report that, among all, compound-10 (C-10) showed significant in vitro therapeutic efficacy as compared to MJ which is in use for preclinical and clinical studies. Afterward, we analyzed cell death triggered by C-10 in two different GBM cell lines. We found that C-10 treatment increased the apoptotic/necrotic cells and autophagy in GBM cells. The newly developed analog, C-10, was found to be lethal against GBM by the activation of cell death authorities, mostly in a necrotic and autophagic fashion at the early stages of the treatment. Considering that possibly decreased intracellular ATP levels by C-10 mediated inhibition of HK-2 activity and disabled VDAC interaction, a more detailed analysis of HK-2 inhibition-mediated cell death can provide a deep understanding of the mechanism of action on the oncosis/necroptosis axis. These findings provide an option to design clinically relevant and effective novel HK-II inhibitors and suggest novel MJ analogs to further study them as potential anticancer agents against GBM.

Intraoperative MR Imaging during Glioma Resection

One of the major issues in the surgical treatment of gliomas is the concern about maximizing the extent of resection while minimizing neurological impairment. Thus, surgical planning by carefully observing the relationship between the glioma infiltration area and eloquent area of the connecting fibers is crucial. Neurosurgeons usually detect an eloquent area by functional MRI and identify a connecting fiber by diffusion tensor imaging. However, during surgery, the accuracy of neuronavigation can be decreased due to brain shift, but the positional information may be updated by intraoperative MRI and the next steps can be planned accordingly. In addition, various intraoperative modalities may be used to guide surgery, including neurophysiological monitoring that provides real-time information (e.g., awake surgery, motor-evoked potentials, and sensory evoked potential); photodynamic diagnosis, which can identify high-grade glioma cells; and other imaging techniques that provide anatomical information during the surgery. In this review, we present the historical and current context of the intraoperative MRI and some related approaches for an audience active in the technical, clinical, and research areas of radiology, as well as mention important aspects regarding safety and types of devices.

Diagnosis of Glioblastoma by Immuno-Positron Emission Tomography

Simple Summary

Neuroimaging has transformed the way brain tumors are diagnosed and treated. Although different non-invasive modalities provide very helpful information, in some situations, they present a limited value. By merging the specificity of antibodies with the resolution, sensitivity, and quantitative capabilities of positron emission tomography (PET), “Immuno-PET” allows us to conduct the non-invasive diagnosis and monitoring of patients over time using antibody-based probes as an in vivo, integrated, quantifiable, 3D, full-body “immunohistochemistry”, like a “virtual biopsy”. This review provides and focuses on immuno-PET applications and future perspectives of this promising imaging approach for glioblastoma.

Abstract

Neuroimaging has transformed neuro-oncology and the way that glioblastoma is diagnosed and treated. Magnetic Resonance Imaging (MRI) is the most widely used non-invasive technique in the primary diagnosis of glioblastoma. Although MRI provides very powerful anatomical information, it has proven to be of limited value for diagnosing glioblastomas in some situations. The final diagnosis requires a brain biopsy that may not depict the high intratumoral heterogeneity present in this tumor type. The revolution in “cancer-omics” is transforming the molecular classification of gliomas. However, many of the clinically relevant alterations revealed by these studies have not yet been integrated into the clinical management of patients, in part due to the lack of non-invasive biomarker-based imaging tools. An innovative option for biomarker identification in vivo is termed “immunotargeted imaging”. By merging the high target specificity of antibodies with the high spatial resolution, sensitivity, and quantitative capabilities of positron emission tomography (PET), “Immuno-PET” allows us to conduct the non-invasive diagnosis and monitoring of patients over time using antibody-based probes as an in vivo, integrated, quantifiable, 3D, full-body “immunohistochemistry” in patients. This review provides the state of the art of immuno-PET applications and future perspectives on this imaging approach for glioblastoma.

Identification of Hub Gene GRIN1 Correlated with Histological Grade and Prognosis of Glioma by Weighted Gene Coexpression Network Analysis

The function of glutamate ionotropic receptor NMDA type subunit 1 (GRIN1) in neurodegenerative diseases has been widely reported; however, its role in the occurrence of glioma remains less explored. We obtained clinical data and transcriptome data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Hub gene's expression differential analysis and survival analysis were conducted by browsing the Gene Expression Profiling Interactive Analysis (GEPIA) database, Human Protein Atlas database, and LOGpc database. We conducted a variation analysis of datasets obtained from GEO and TCGA and performed a weighted gene coexpression network analysis (WGCNA) using the R programming language (3.6.3). Kaplan-Meier (KM) analysis was used to calculate the prognostic value of GRIN1. Finally, we conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Using STRING, we constructed a protein–protein interaction (PPI) network. Cytoscape software, a prerequisite of visualizing core genes, was installed, and CytoHubba detected the 10 most tumor-related core genes. We identified 185 differentially expressed genes (DEGs). GO and KEGG enrichment analyses illustrated that the identified DEGs are imperative in different biological functions and ascertained the potential pathways in which the DEGs may be enriched. The overall survival calculated by KM analysis showed that patients with lower expression of GRIN1 had worse prognoses than patients with higher expression of GRIN1 (p = 0.004). The GEPIA and LOGpc databases were used to verify the expression difference of GRIN1 among GBM, LGG, and normal brain tissues. Ultimately, immunohistochemical assay results showed that GRIN1 was detected in normal tissue and not in the tumor specimens. Our results highlight a potential target for glioma treatment and will further our understanding of the molecular mechanisms underlying the treatment of glioma.

Research Progress of Gliomas in Machine Learning

In the field of gliomas research, the broad availability of genetic and image information originated by computer technologies and the booming of biomedical publications has led to the advent of the big-data era. Machine learning methods were applied as possible approaches to speed up the data mining processes. In this article, we reviewed the present situation and future orientations of machine learning application in gliomas within the context of workflows to integrate analysis for precision cancer care. Publicly available tools or algorithms for key machine learning technologies in the literature mining for glioma clinical research were reviewed and compared. Further, the existing solutions of machine learning methods and their limitations in glioma prediction and diagnostics, such as overfitting and class imbalanced, were critically analyzed.

Overexpressed GNA13 induces temozolomide sensitization via down-regulating MGMT and p-RELA in glioma

Temozolomide (TMZ), one of the few effective drugs used during adjuvant therapy, could effectively prolong the overall survival (OS) of glioma patients. In our previous study, the mRNA level of G Protein Subunit Alpha 13 (GNA13) was found to be inversely correlated with OS and was therefore identified as a potential biomarker for the prognosis of glioma. Henceforth, this study aims to identify the molecular mechanism of GNA13 in enhancing TMZ sensitization through bioinformatic analyses of GSE80729 and GSE43452 and other experiments. In glioma, overexpression of GNA13 downregulated PRKACA, which is a subunit of PKA, hence reducing phosphorylated RELA and MGMT. Since p-RELA and MGMT were proven to be closely associated with TMZ resistance, we therefore investigated whether thetwo signaling pathways, "GNA13/PRKACA/p-RELA", and "GNA13/PRKACA/MGMT", were involved in the molecular mechanism of GNA13 in TMZ sensitization. Our conclusion was that, GNA13 overexpression in glioma cells were more sensitive in TMZ treatment.

Imaging Hallmarks of the Tumor Microenvironment in Glioblastoma Progression

Glioblastoma progression involves multifaceted changes in vascularity, cellularity, and metabolism. Capturing such complexities of the tumor niche, from the tumor core to the periphery, by magnetic resonance imaging (MRI) and spectroscopic imaging (MRSI) methods has translational impact. In human-derived glioblastoma models (U87, U251) we made simultaneous and longitudinal measurements of tumor perfusion (F_p), permeability (K^trans), and volume fractions of extracellular (v_e) and blood (v_p) spaces from dynamic contrast enhanced (DCE) MRI, cellularity from apparent diffusion coefficient (ADC) MRI, and extracellular pH (pH_e) from an MRSI method called Biosensor Imaging of Redundant Deviation in Shifts (BIRDS). Spatiotemporal patterns of these parameters during tumorigenesis were unique for each tumor. While U87 tumors grew faster, F_p, K^trans, and v_p increased with tumor growth in both tumors but these trends were more pronounced for U251 tumors. Perfused regions between tumor periphery and core with U87 tumors exhibited higher F_p, but K^trans of U251 tumors remained lowest at the tumor margin, suggesting primitive vascularization. Tumor growth was uncorrelated with v_e, ADC, and pH_e. U87 tumors showed correlated regions of reduced v_e and lower ADC (higher cellularity), suggesting ongoing proliferation. U251 tumors revealed that the tumor core had higher v_e and elevated ADC (lower cellularity), suggesting necrosis development. The entire tumor was uniformly acidic (pH_e 6.1-6.8) early and throughout progression, but U251 tumors were more acidic, suggesting lower aerobic glycolysis in U87 tumors. Characterizing these cancer hallmarks with DCE-MRI, ADC-MRI, and BIRDS-MRSI will be useful for exploring tumorigenesis as well as timely therapies targeted to specific vascular and metabolic aspects of the tumor microenvironment.

Comparison of In Vivo and Ex Vivo Magnetic Resonance Imaging in a Rat Model for Glioblastoma-Associated Epilepsy

Magnetic resonance imaging (MRI) is frequently used for preclinical treatment monitoring in glioblastoma (GB). Discriminating between tumors and tumor-associated changes is challenging on in vivo MRI. In this study, we compared in vivo MRI scans with ex vivo MRI and histology to estimate more precisely the abnormal mass on in vivo MRI. Epileptic seizures are a common symptom in GB. Therefore, we used a recently developed GB-associated epilepsy model from our group with the aim of further characterizing the model and making it useful for dedicated epilepsy research. Ten days after GB inoculation in rat entorhinal cortices, in vivo MRI (T2w and mean diffusivity (MD)), ex vivo MRI (T2w) and histology were performed, and tumor volumes were determined on the different modalities. The estimated abnormal mass on ex vivo T2w images was significantly smaller compared to in vivo T2w images, but was more comparable to histological tumor volumes, and might be used to estimate end-stage tumor volumes. In vivo MD images displayed tumors as an outer rim of hyperintense signal with a core of hypointense signal, probably reflecting peritumoral edema and tumor mass, respectively, and might be used in the future to distinguish the tumor mass from peritumoral edema—associated with reactive astrocytes and activated microglia, as indicated by an increased expression of immunohistochemical markers—in preclinical models. In conclusion, this study shows that combining imaging techniques using different structural scales can improve our understanding of the pathophysiology in GB.

A perspective on the radiopharmaceutical requirements for imaging and therapy of glioblastoma

Despite numerous clinical trials and pre-clinical developments, the treatment of glioblastoma (GB) remains a challenge. The current survival rate of GB averages one year, even with an optimal standard of care. However, the future promises efficient patient-tailored treatments, including targeted radionuclide therapy (TRT). Advances in radiopharmaceutical development have unlocked the possibility to assess disease at the molecular level allowing individual diagnosis. This leads to the possibility of choosing a tailored, targeted approach for therapeutic modalities. Therapeutic modalities based on radiopharmaceuticals are an exciting development with great potential to promote a personalised approach to medicine. However, an effective targeted radionuclide therapy (TRT) for the treatment of GB entails caveats and requisites. This review provides an overview of existing nuclear imaging and TRT strategies for GB. A critical discussion of the optimal characteristics for new GB targeting therapeutic radiopharmaceuticals and clinical indications are provided. Considerations for target selection are discussed, i.e. specific presence of the target, expression level and pharmacological access to the target, with particular attention to blood-brain barrier crossing. An overview of the most promising radionuclides is given along with a validation of the relevant radiopharmaceuticals and theranostic agents (based on small molecules, peptides and monoclonal antibodies). Moreover, toxicity issues and safety pharmacology aspects will be presented, both in general and for the brain in particular.

Role of Polymeric Local Drug Delivery in Multimodal Treatment of Malignant Glioma: A Review

Malignant gliomas (MGs) are the most common and devastating primary brain tumor. At present, surgical interventions, radiotherapy, and chemotherapy are only marginally effective in prolonging the life expectancy of patients with MGs. Inherent heterogeneity, aggressive invasion and infiltration, intact physical barriers, and the numerous mechanisms underlying chemotherapy and radiotherapy resistance contribute to the poor prognosis for patients with MGs. Various studies have investigated methods to overcome these obstacles in MG treatment. In this review, we address difficulties in MG treatment and focus on promising polymeric local drug delivery systems. In contrast to most local delivery systems, which are directly implanted into the residual cavity after intratumoral injection or the surgical removal of a tumor, some rapidly developing and promising nanotechnological methods—including surface-decorated nanoparticles, magnetic nanoparticles, and focused ultrasound assist transport—are administered through (systemic) intravascular injection. We also discuss further synergistic and multimodal strategies for heightening therapeutic efficacy. Finally, we outline the challenges and therapeutic potential of these polymeric drug delivery systems.

Multi-responsive nanofibers composite gel for local drug delivery to inhibit recurrence of glioma after operation

Background

The postoperative recurrence of malignant gliomas has presented a clinical conundrum currently. Worse, there is no standard treatment for these recurrent tumours. Therefore, novel promising methods of clinical treatment are urgently needed.

Methods

In this study, we synthesized reactive oxygen species (ROS)-triggered poly(propylene sulfide)60 (PPS60) mixed with matrix metalloproteinases (MMPs)-responsive triglycerol monostearate (T) lipids and TMZ. The mixed solution could self-assemble at 50 ℃ to generate hydrogels with MMPs- and ROS-responsiveness. We explored whether the T/PPS + TMZ hydrogel could achieve the MMP- and ROS-responsive delivery of TMZ and exert anti-glioma regrowth effects in vitro and in vivo. These results demonstrated that the T/PPS + TMZ hydrogel significantly improved the curative effect of TMZ to inhibit postsurgical recurrent glioma.

Results

The results confirmed the responsive release of TMZ encapsulated in the T/PPS + TMZ hydrogel, and the hydrogel showed excellent performance against glioma in an incomplete glioma operation model, which indicated that the T/PPS + TMZ hydrogel effectively inhibited the growth of recurrent glioma.

Conclusion

In summary, we successfully developed injectable MMPs- and ROS-responsive hydrogels that could achieve the sustained release of TMZ in the surgical cavity to inhibit local recurrent glioma after surgery.

Graphic abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12951-021-00943-z.

CircRNA NALCN acts as an miR-493-3p sponge to regulate PTEN expression and inhibit glioma progression

Background

An increasing number of studies have shown that circular RNAs (circRNAs) play important roles in the regulation of tumor progression. Therefore, we explored the expression characteristics, function, and related mechanism of the newly identified circNALCN in glioma.

Methods

RNA sequencing was used to analyze the expression profiles of circRNAs in brain tissue from five glioma cases and four normal controls. Quantitative real-time polymerase chain reaction was implemented to examine the levels of circNALCN, miR-493-3p, and phosphatase and tensin homolog (PTEN). Cell counting kit 8 assays were performed to analyze cell proliferation, and cell migration was assessed by the wound healing test and Transwell assay. Dual-luciferase reporter, fluorescence in situ hybridization, and RNA pulldown assays were performed to confirm the role of circNALCN as an miR-493-3p sponge, weakening the inhibitory effect of miR-493-3p on target PTEN expression.

Results

The downregulated expression of circNALCN was observed in both glioma tissues and cell lines. CircNALCN expression was negatively correlated with World Health Organization grade and overall survival in patients with glioma. Functionally, the overexpression of circNALCN significantly inhibited the proliferation and migration of glioma cells, whereas miR-493-3p mimics counteracted these effects. The mechanistic analysis demonstrated that circNALCN acted as a competing endogenous RNA for miR-493-3p to relieve the repressive effects of miR-493-3p on its target, PTEN, suppressing glioma tumorigenesis.

Conclusions

CircNALCN inhibits the progression of glioma through the miR-493-3p/PTEN axis, providing a developable biomarker and therapeutic target for glioma patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02001-y.

Nanogels as a Versatile Drug Delivery System for Brain Cancer

Chemotherapy and radiation remain as mainstays in the treatment of a variety of cancers globally, yet some therapies exhibit limited specificity and result in harsh side effects in patients. Brain tissue differs from other tissue due to restrictions from the blood-brain barrier, thus systemic treatment options are limited. The focus of this review is on nanogels as local and systemic drug delivery systems in the treatment of brain cancer. Nanogels are a unique local or systemic drug delivery system that is tailorable and consists of a three-dimensional polymeric network formed via physical or chemical assembly. For example, thermosensitive nanogels show promise in their ability to incorporate therapeutic agents in nano-structured matrices, be applied in the forms of sprays or sols to the area from which a tumor has been removed, form adhesive gels to fill the cavity and deliver treatment locally. Their usage does come with complications, such as handling, storage, chemical stability, and degradation. Despite these limitations, the current ongoing development of nanogels allows patient-centered treatment that can be considered as a promising tool for the management of brain cancer.

Assessment of the effect of therapy in a rat model of glioblastoma using [18F]FDG and [18F]FCho PET compared to contrast-enhanced MRI

Objective

We investigated the potential of [¹⁸F]fluorodeoxyglucose ([¹⁸F]FDG) and [¹⁸F]Fluoromethylcholine ([¹⁸F]FCho) PET, compared to contrast-enhanced MRI, for the early detection of treatment response in F98 glioblastoma (GB) rats.

Methods

When GB was confirmed on T2- and contrast-enhanced T1-weighted MRI, animals were randomized into a treatment group (n = 5) receiving MRI-guided 3D conformal arc micro-irradiation (20 Gy) with concomitant temozolomide, and a sham group (n = 5). Effect of treatment was evaluated by MRI and [¹⁸F]FDG PET on day 2, 5, 9 and 12 post-treatment and [¹⁸F]FCho PET on day 1, 6, 8 and 13 post-treatment. The metabolic tumor volume (MTV) was calculated using a semi-automatic thresholding method and the average tracer uptake within the MTV was converted to a standard uptake value (SUV).

Results

To detect treatment response, we found that for [¹⁸F]FDG PET (SUV_mean x MTV) is superior to MTV only. Using (SUV_mean x MTV), [¹⁸F]FDG PET detects treatment effect starting as soon as day 5 post-therapy, comparable to contrast-enhanced MRI. Importantly, [¹⁸F]FDG PET at delayed time intervals (240 min p.i.) was able to detect the treatment effect earlier, starting at day 2 post-irradiation. No significant differences were found at any time point for both the MTV and (SUV_mean x MTV) of [¹⁸F]FCho PET.

Conclusions

Both MRI and particularly delayed [¹⁸F]FDG PET were able to detect early treatment responses in GB rats, whereas, in this study this was not possible using [¹⁸F]FCho PET. Further comparative studies should corroborate these results and should also include (different) amino acid PET tracers.

Epidemiology of Anthropometric Factors in Glioblastoma Multiforme-Literature Review

Although glioblastoma multiforme (GBM) is a widely researched cancer of the central nervous system, we still do not know its full pathophysiological mechanism and we still lack effective treatment methods as the current combination of surgery, radiotherapy, and chemotherapy does not bring about satisfactory results. The median survival time for GBM patients is only about 15 months. In this paper, we present the epidemiology of central nervous system (CNS) tumors and review the epidemiological data on GBM regarding gender, age, weight, height, and tumor location. The data indicate the possible influence of some anthropometric factors on the occurrence of GBM, especially in those who are male, elderly, overweight, and/or are taller. However, this review of single and small-size epidemiological studies should not be treated as definitive due to differences in the survey methods used. Detailed epidemiological registers could help identify the main at-risk groups which could then be used as homogenous study groups in research worldwide. Such research, with less distortion from various factors, could help identify the pathomechanisms that lead to the development of GBM.

N6-methyladenine-related genes affect biological behavior and the prognosis of glioma

Background

Although aberrant expression of N6‐methyladenine (m⁶A) methylation‐related genes contribute to tumorigenesis in many solid tumors, the prognostic value of the m⁶A‐related genes and their correlation with clinicopathological features in gliomas need advanced study.

Methods

The clinical and sequencing data of 288 patients with glioma were extracted from Chinese Glioma Genome Atlas database. By univariate and multivariable Cox regression analysis, the m⁶A‐related prognostic genes were identified, and their correlation with clinicopathological features was further analysis. A nomogram was constructed by R software and the performance of it was assessed by calibration and time‐dependent receiver operating characteristic curve.

Results

Nine m⁶A‐related genes were identified as independent prognostic factors, which were mostly enriched in RNA splicing, regulation of immune response and vesicle‐mediated transport. By expression value and regression coefficient of these genes, we constructed risk score of each patient, which was highly associated with clinicopathological features. Kaplan–Meier curve showed that the prognosis of patients with high‐risk scores was significantly worse than that with low‐risk scores (HR = 4.30, 95% CI = 3.16–5.85, p < 0.0001). A nomogram was constructed based on the nine m⁶A‐related genes signature and clinicopathological features with well‐fitted calibration curves (c‐index = 0.82), showing high specificity and sensitivity (area under the curve for 1‐, 3‐, and 5‐years survival probability = 0.874, 0.918, and 0.934).

Conclusions

A nine m⁶A‐related genes signature was identified in gliomas. The m⁶A‐related risk score is a novel prognostic factor for patients with glioma, and is associated with clinicopathological features. Moreover, the nomogram based on the nine m⁶A‐related genes signature and clinicopathological features had good efficacy in predicting the survival probability.

Visualization of Diagnostic and Therapeutic Targets in Glioma With Molecular Imaging

Gliomas, particularly high-grade gliomas including glioblastoma (GBM), represent the most common and malignant types of primary brain cancer in adults, and carry a poor prognosis. GBM has been classified into distinct subgroups over the years based on cellular morphology, clinical characteristics, biomarkers, and neuroimaging findings. Based on these classifications, differences in therapeutic response and patient outcomes have been established. Recently, the identification of complex molecular signatures of GBM has led to the development of diverse targeted therapeutic regimens and translation into multiple clinical trials. Chemical-, peptide-, antibody-, and nanoparticle-based probes have been designed to target specific molecules in gliomas and then be visualized with multimodality molecular imaging (MI) techniques including positron emission tomography (PET), single-photon emission computed tomography (SPECT), near-infrared fluorescence (NIRF), bioluminescence imaging (BLI), and magnetic resonance imaging (MRI). Thus, multiple molecules of interest can now be noninvasively imaged to guide targeted therapies with a potential survival benefit. Here, we review developments in molecular-targeted diagnosis and therapy in glioma, MI of these targets, and MI monitoring of treatment response, with a focus on the biological mechanisms of these advanced molecular probes. MI probes have the potential to noninvasively demonstrate the pathophysiologic features of glioma for diagnostic, treatment, and response assessment considerations for various targeted therapies, including immunotherapy. However, most MI tracers are in preclinical development, with only integrin α_Vβ₃ and isocitrate dehydrogenase (IDH)-mutant MI tracers having been translated to patients. Expanded international collaborations would accelerate translational research in the field of glioma MI.

Local Delivery of Minocycline and Vorinostat Targets the Tumor Microenvironment to Inhibit the Recurrence of Glioma

Background

Postoperative recurrence is the main reason for poor clinical outcomes in glioma patients, so preventing tumor recurrence is crucial in the management of gliomas.

Methods

In this study, the expression of matrix metalloproteinases (MMPs) in normal tissues was detected via RNA-seq analysis. Glioma cases from the public databases (The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA)) were included in this study. The hydrogel contains minocycline (Mino) and vorinostat (Vor) (G/Mino+Vor) was formed under 365 nm when the photoinitiator was added. High-performance liquid chromatography (HPLC) was used to assess the release of drugs in the G/Mino+Vor hydrogel. An MTT assay was used to explore the biosecurity of GelMA. Immunohistochemistry, ELISA, and TUNEL assays were used to demonstrate the antitumor effect of the G/Mino+Vor hydrogel.

Results

We successfully developed a G/Mino+Vor hydrogel. The experiments in vitro and in vivo confirmed the MMPs-responsive delivery of minocycline and vorinostat in hydrogel and the anti-glioma effect on an incomplete tumor operation model, which indicated that the G/Mino+Vor hydrogel effectively inhibited the recurrence of glioma after surgery.

Conclusion

In summary, the G/Mino+Vor hydrogel could continuously release drugs and improve the therapy effects against recurrent glioma.

Employment and Work Ability of Persons With Brain Tumors: A Systematic Review

Brain tumors (BT) are between the eight most common cancers among persons aged 40 years, with an average survival time of 10 years for patients affected by non-malignant brain tumor. Some patients continue to work, reporting difficulties in work-related activities, or even job loss. The purpose of the present study was to review the existing information about the ability people with BT to return to work and to identify factors associated with job loss. We performed a systematic review on SCOPUS and EMBASE for peer-reviewed papers that reported studies assessing work ability in patients with BT that were published in the period from January 2010 to January 2020. Out of 800 identified records, 7 articles were selected for analysis, in which 1,507 participants with BT were enrolled overall. Three main themes emerged: the impact of neuropsychological functioning on work productivity, the change of employment status for long-term survivors and issues related to return to work processes. Based on the results of selected studies, it can be concluded that the impact of BT on workforce participation is determined by depressive symptoms and cognitive deficits, as well as by high short-term mortality but also on environmental barriers. Vocational Rehabilitation programs should be implemented to help patients wishing to return to or maintain their current work, as much as possible.

The Role of Translocator Protein TSPO in Hallmarks of Glioblastoma

Simple Summary

The translocator protein (TSPO) has been under extensive investigation as a specific marker in positron emission tomography (PET) to visualize brain lesions following injury or disease. In recent years, TSPO is increasingly appreciated as a potential novel therapeutic target in cancer. In Glioblastoma (GBM), the most malignant primary brain tumor, TSPO expression levels are strongly elevated and scientific evidence accumulates, hinting at a pivotal role of TSPO in tumorigenesis and glioma progression. The aim of this review is to summarize the current literature on TSPO with respect to its role both in diagnostics and especially with regard to the critical hallmarks of cancer postulated by Hanahan and Weinberg. Overall, our review contributes to a better understanding of the functional significance of TSPO in Glioblastoma and draws attention to TSPO as a potential modulator of treatment response and thus an important factor that may influence the clinical outcome of GBM.

Abstract

Glioblastoma (GBM) is the most fatal primary brain cancer in adults. Despite extensive treatment, tumors inevitably recur, leading to an average survival time shorter than 1.5 years. The 18 kDa translocator protein (TSPO) is abundantly expressed throughout the body including the central nervous system. The expression of TSPO increases in states of inflammation and brain injury due to microglia activation. Not least due to its location in the outer mitochondrial membrane, TSPO has been implicated with a broad spectrum of functions. These include the regulation of proliferation, apoptosis, migration, as well as mitochondrial functions such as mitochondrial respiration and oxidative stress regulation. TSPO is frequently overexpressed in GBM. Its expression level has been positively correlated to WHO grade, glioma cell proliferation, and poor prognosis of patients. Several lines of evidence indicate that TSPO plays a functional part in glioma hallmark features such as resistance to apoptosis, invasiveness, and proliferation. This review provides a critical overview of how TSPO could regulate several aspects of tumorigenesis in GBM, particularly in the context of the hallmarks of cancer proposed by Hanahan and Weinberg in 2011.

Machine Learning-Based Radiomics Predicting Tumor Grades and Expression of Multiple Pathologic Biomarkers in Gliomas

BACKGROUND

The grading and pathologic biomarkers of glioma has important guiding significance for the individual treatment. In clinical, it is often necessary to obtain tumor samples through invasive operation for pathological diagnosis. The present study aimed to use conventional machine learning algorithms to predict the tumor grades and pathologic biomarkers on magnetic resonance imaging (MRI) data.

METHODS

The present study retrospectively collected a dataset of 367 glioma patients, who had pathological reports and underwent MRI scans between October 2013 and March 2019. The radiomic features were extracted from enhanced MRI images, and three frequently-used machine-learning models of LC, Support Vector Machine (SVM), and Random Forests (RF) were built for four predictive tasks: (1) glioma grades, (2) Ki67 expression level, (3) GFAP expression level, and (4) S100 expression level in gliomas. Each sub dataset was split into training and testing sets at a ratio of 4:1. The training sets were used for training and tuning models. The testing sets were used for evaluating models. According to the area under curve (AUC) and accuracy, the best classifier was chosen for each task.

RESULTS

The RF algorithm was found to be stable and consistently performed better than Logistic Regression and SVM for all the tasks. The RF classifier on glioma grades achieved a predictive performance (AUC: 0.79, accuracy: 0.81). The RF classifier also achieved a predictive performance on the Ki67 expression (AUC: 0.85, accuracy: 0.80). The AUC and accuracy score for the GFAP classifier were 0.72 and 0.81. The AUC and accuracy score for S100 expression levels are 0.60 and 0.91.

CONCLUSION

The machine-learning based radiomics approach can provide a non-invasive method for the prediction of glioma grades and expression levels of multiple pathologic biomarkers, preoperatively, with favorable predictive accuracy and stability.

Glioma surveillance imaging: current strategies, shortcomings, challenges and outlook

Inaccurate assessment of surveillance imaging to assess response to glioma therapy may have life-changing consequences. Varied management plans including chemotherapy, radiotherapy or immunotherapy may all contribute to heterogeneous post-treatment appearances and the overlap between the morphological features of pseudoprogression, pseudoresponse and radiation necrosis can make their discrimination very challenging. Therefore, there has been a drive to develop objective strategies for post-treatment assessment of brain gliomas. This review discusses the most important of these approaches such as the RANO "Response Assessment in Neuro-Oncology", iRANO "Immunotherapy Response Assessment in Neuro-Oncology" and RAPNO "Response Assessment in Paediatric Neuro-Oncology" models. In addition to these systematic approaches for glioma surveillance, the relatively limited information provided by conventional imaging modalities alone has motivated the development of novel advanced magnetic resonance (MR) and metabolic imaging methods for further discrimination between viable tumour and treatment induced changes. Multiple clinical trials and meta-analyses have investigated the diagnostic performance of these novel techniques in the follow up of brain gliomas, including both single modality descriptive studies and comparative imaging assessment. In this manuscript, we review the literature and discuss the promises and pitfalls of frequently studied modalities in glioma surveillance imaging, including MR perfusion, MR diffusion and MR spectroscopy. In addition, we evaluate other promising MR techniques such as chemical exchange saturation transfer as well as fludeoxyglucose and non-FDG positron emission tomography techniques.

Checking NEKs: Overcoming a Bottleneck in Human Diseases

In previous years, several kinases, such as phosphoinositide 3-kinase (PI3K), mammalian target of rapamycin (mTOR), and extracellular-signal-regulated kinase (ERK), have been linked to important human diseases, although some kinase families remain neglected in terms of research, hiding their relevance to therapeutic approaches. Here, a review regarding the NEK family is presented, shedding light on important information related to NEKs and human diseases. NEKs are a large group of homologous kinases with related functions and structures that participate in several cellular processes such as the cell cycle, cell division, cilia formation, and the DNA damage response. The review of the literature points to the pivotal participation of NEKs in important human diseases, like different types of cancer, diabetes, ciliopathies and central nervous system related and inflammatory-related diseases. The different known regulatory molecular mechanisms specific to each NEK are also presented, relating to their involvement in different diseases. In addition, important information about NEKs remains to be elucidated and is highlighted in this review, showing the need for other studies and research regarding this kinase family. Therefore, the NEK family represents an important group of kinases with potential applications in the therapy of human diseases.

Discrimination between Glioblastoma and Solitary Brain Metastasis: Comparison of Inflow-Based Vascular-Space-Occupancy and Dynamic Susceptibility Contrast MR Imaging

BACKGROUND AND PURPOSE

Accurate differentiation between glioblastoma and solitary brain metastasis is of vital importance clinically. This study aimed to investigate the potential value of the inflow-based vascular-space-occupancy MR imaging technique, which has no need for an exogenous contrast agent, in differentiating glioblastoma and solitary brain metastasis and to compare it with DSC MR imaging.

MATERIALS AND METHODS

Twenty patients with glioblastoma and 22 patients with solitary brain metastasis underwent inflow-based vascular-space-occupancy and DSC MR imaging with a 3T clinical scanner. Two neuroradiologists independently measured the maximum inflow-based vascular-space-occupancy-derived arteriolar CBV and DSC-derived CBV values in intratumoral regions and peritumoral T2-hyperintense regions, which were normalized to the contralateral white matter (relative arteriolar CBV and relative CBV, inflow-based vascular-space-occupancy relative arteriolar CBV, and DSC-relative CBV). The intraclass correlation coefficient, Student t test, or Mann-Whitney U test and receiver operating characteristic analysis were performed.

RESULTS

All parameters of both regions had good or excellent interobserver reliability (0.74∼0.89). In peritumoral T2-hyperintese regions, DSC-relative CBV (P < .001), inflow-based vascular-space-occupancy arteriolar CBV (P = .001), and relative arteriolar CBV (P = .005) were significantly higher in glioblastoma than in solitary brain metastasis, with areas under the curve of 0.94, 0.83, and 0.72 for discrimination, respectively. In the intratumoral region, both inflow-based vascular-space-occupancy arteriolar CBV and relative arteriolar CBV were significantly higher in glioblastoma than in solitary brain metastasis (both P < .001), with areas under the curve of 0.91 and 0.90, respectively. Intratumoral DSC-relative CBV showed no significant difference (P = .616) between the 2 groups.

CONCLUSIONS

Inflow-based vascular-space-occupancy has the potential to discriminate glioblastoma from solitary brain metastasis, especially in the intratumoral region.

Circular RNA SMO sponges miR-338-3p to promote the growth of glioma by enhancing the expression of SMO

Glioma is one of the most common tumors in the brain and complete cure still a challenge. The present research aimed to investigate the molecular mechanism of circular RNA SMO (circSMO742) in glioma, via targeting miR-338-3p and regulating SMO expression. QRT-PCR was utilized to examine the expression profiles of circSMO742 and microRNA-338-3p (miR-338-3p) in glioma. SMO protein in glioma was tested via western blot. RNA pulldown assay and dual luciferase reporter assays were used to explore the targeting correlation between RNAs. MTT assay, transwell assays and flow cytometry were used to investigate cell proliferation, migration and invasion, and apoptosis, respectively. Tumor xenograft was done to ascertain the effect of circSMO742 knocking down on tumor growth. CircSMO742 and SMO were highly expressed in glioma tissues, while miR-338-3p expression was reduced. CircSMO742 together with SMO could promote cells proliferation, migration and invasion while inhibit cells apoptosis, whereas miR-338-3p showed negative impacts on the cell activity. Knocking down of circSMO742 suppressed glioma growing in vivo. CircSMO742 promoted glioma growth by sponging miR-338-3p to regulate SMO expression. Our research revealed a new molecular mechanism of glioma growth and provide a fresh perspective on circRNAs in glioma progression.

Integrin αvβ3-Specific Hydrocyanine for Cooperative Targeting of Glioblastoma with High Sensitivity and Specificity

Glioblastoma is a highly malignant brain tumor with poor prognosis and survival rate because of a lack of effective diagnostic methods. Hydrocyanines are a type of reactive oxygen species (ROS)-responsive fluorescent probes, allowing for distinguishing tumor cells from normal cells based on their different intracellular levels of ROS. However, their diagnostic applications for glioblastoma have been limited because of the inability to discriminate between tumor cells and other tissues with high ROS production, leading to high false-positive diagnosis. Therefore, tumor-responsive and -specific hydrocyanines with cooperative targeting ability have great potential for improving the diagnosis and treatment of glioblastoma. Integrin αvβ3 plays a critical role in the progression and angiogenesis of glioblastoma and has become a promising target for diagnosing glioblastoma. Herein, we identify a specific peptide ligand for integrin αvβ3, Arg-Trp-(d-Arg)-Asn-Arg (RWrNR), which shows high binding affinity to human glioblastoma U87MG cells. Importantly, hydro-Cy5-RWrNR conjugation allowed for distinguishing U87MG cells from normal cells in response to intracellular ROS. Particularly, hydro-Cy5-RWrNR could not only selectively accumulate in orthotopic U87MG tumor with minimal background fluorescence but also effectively discriminate between glioblastoma and inflammatory tissues for the first time, leading to detection of glioblastoma in vivo with high target-to-background ratios and minimal background fluorescence. Therefore, hydro-Cy5-RWrNR is the first integrin αvβ3-specific hydrocyanine probe and has great potential in precise tumor diagnosis because of its cooperative targeting of integrin αvβ3 and ROS.

Stoichioproteomics reveal oxygen usage bias, key proteins and pathways in glioma

Background

The five-year survival rate and therapeutic effect of malignant glioma is low. Identification of key/associated proteins and pathways in glioma is necessary for developing effective diagnosis and targeted therapy of glioma. In addition, Glioma involves hypoxia-specific microenvironment, whether hypoxia restriction influences the stoichioproteomic characteristics of expressed proteins is unknown.

Methods

In this study, we analyzed the most comprehensive immunohistochemical data from 12 human glioma samples and 4 normal cell types of cerebral cortex, identified differentially expressed proteins (DEPs), and researched the oxygen contents of DEPs, highly and lowly expressed proteins. Further we located key genes on human genome to determine their locations and enriched them for key functional pathways.

Results

Our results showed that although no difference was detected on whole proteome, the average oxygen content of highly expressed proteins is 6.65% higher than that of lowly expressed proteins in glioma. A total of 1480 differentially expressed proteins were identified in glioma, including 226 up regulated proteins and 1254 down regulated proteins. The average oxygen content of up regulated proteins is 2.56% higher than that of down regulated proteins in glioma. The localization of differentially expressed genes on human genome showed that most genes were on chromosome 1 and least on Y. The up regulated proteins were significantly enriched in pathways including cell cycle, pathways in cancer, oocyte meiosis, DNA replication etc. Functional dissection of the up regulated proteins with high oxygen contents showed that 51.28% of the proteins were involved in cell cycle and cyclins.

Conclusions

Element signature of oxygen limitation could not be detected in glioma, just as what happened in plants and microbes. Unsaved use of oxygen by the highly expressed proteins and DEPs were adapted to the fast division of glioma cells. This study can help to reveal the molecular mechanism of glioma, and provide a new approach for studies of cancer-related biomacromolecules. In addition, this study lays a foundation for application of stoichioproteomics in precision medicine.

Electronic supplementary material

The online version of this article (10.1186/s12920-019-0571-y) contains supplementary material, which is available to authorized users.

Biopsy Confirmed Glioma Recurrence Predicted by Multi-Modal Neuroimaging Metrics

Histopathological verification is currently required to differentiate tumor recurrence from treatment effects related to adjuvant therapy in patients with glioma. To bypass the complications associated with collecting neural tissue samples, non-invasive classification methods are needed to alleviate the burden on patients while providing vital information to clinicians. However, uncertainty remains as to which tissue features on magnetic resonance imaging (MRI) are useful. The primary objective of this study was to quantitatively assess the reliability of combining MRI and diffusion tensor imaging metrics to discriminate between tumor recurrence and treatment effects in histopathologically identified biopsy samples. Additionally, this study investigates the noise adjuvant radiation therapy introduces when discriminating between tissue types. In a sample of 41 biopsy specimens, from a total of 10 patients, we derived region-of-interest samples from MRI data in the ipsilateral hemisphere that encompassed biopsies obtained during resective surgery. This study compares normalized intensity values across histopathology classifications and contralesional volumes reflected across the midline. Radiation makes noninvasive differentiation of abnormal-nontumor tissue to tumor recurrence much more difficult. This is because radiation exhibits opposing behavior on key MRI modalities: specifically, on post-contrast T1, FLAIR, and GFA. While radiation makes noninvasive differentiation of tumor recurrence more difficult, using a novel analysis of combined MRI metrics combined with clinical annotation and histopathological correlation, we observed that it is possible to successfully differentiate tumor tissue from other tissue types. Additional work will be required to expand upon these findings.

Novel management of glioma by molecular therapies, a review article

The most frequent type of brain tumors is Glioma which commonly appears initially in the neuroglia in the central nervous system. They grow steadily and generally do not outspread to neighboring tissue of the brain. By applying dominant remedial regimens, the patients would have negligible survival rates. Despite the achieved advances in conventional glioma therapy, it proved that a proper medication for glioma is not easily reachable. The glioma penetration nature and accumulate resistance considerably limit the remedial options. Superior explanation of the glioma complex pathobiology and characterization of biological proteogenomic may finally open new approaches for the outlining of extra artificial and impressive combination regimens. This aim could be achieved by exclusively outfitting advanced techniques of neuroimaging, terminating synthesis of DNA via genes that activated via prodrugs, experimental technique of gene therapy via conciliating genes of gliomagenesis, targeting miRNA-mRNA activity of oncogenic, applying stem cell therapy for combining inhibitors of Hedgehog-Gli, adaptive transmission of chimeric immunoreceptors T cells, incorporate inhibitors of regulators of the immune system with conventional remedial modalities and additionally using tumor cell lysates as sources of antigen for efficient evacuation of particular stem cells of tumor via cytotoxic T lymphocytes. Consequently, in this study the authors trying to survey the latest progressions related to the molecular procedures connected with the formation of glial tumors in addition to the radiation, surgery and chemotherapy limitations. Additionally, the novel strategies of molecular remedies and their procedure for the prosperous treatment of glioma will be discussed.

Artificial Intelligence in the Management of Glioma: Era of Personalized Medicine

Purpose: Artificial intelligence (AI) has accelerated novel discoveries across multiple disciplines including medicine. Clinical medicine suffers from a lack of AI-based applications, potentially due to lack of awareness of AI methodology. Future collaboration between computer scientists and clinicians is critical to maximize the benefits of transformative technology in this field for patients. To illustrate, we describe AI-based advances in the diagnosis and management of gliomas, the most common primary central nervous system (CNS) malignancy.

Methods: Presented is a succinct description of foundational concepts of AI approaches and their relevance to clinical medicine, geared toward clinicians without computer science backgrounds. We also review novel AI approaches in the diagnosis and management of glioma.

Results: Novel AI approaches in gliomas have been developed to predict the grading and genomics from imaging, automate the diagnosis from histopathology, and provide insight into prognosis.

Conclusion: Novel AI approaches offer acceptable performance in gliomas. Further investigation is necessary to improve the methodology and determine the full clinical utility of these novel approaches.

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.

Preclinical Evaluation of Radiolabeled Peptides for PET Imaging of Glioblastoma Multiforme

In this study, we have compared four ⁶⁸Ga-labeled peptides (three Arg-Gly-Asp (RGD) peptides and substance-P) with two ¹⁸F-tracers clinically approved for tumor imaging. We have studied in vitro and in vivo characteristics of selected radiolabeled tracers in a glioblastoma multiforme tumor model. The in vitro part of the study was mainly focused on the evaluation of radiotracers stability under various conditions. We have also determined in vivo stability of studied ⁶⁸Ga-radiotracers by analysis of murine urine collected at various time points after injection. The in vivo behavior of tested ⁶⁸Ga-peptides was evaluated through ex vivo biodistribution studies and PET/CT imaging. The obtained data were compared with clinically used ¹⁸F-tracers. ⁶⁸Ga-RGD peptides showed better imaging properties compared to ¹⁸F-tracers, i.e., higher tumor/background ratios and no accumulation in non-target organs except for excretory organs.

MRI combined with PET-CT of different tracers to improve the accuracy of glioma diagnosis: a systematic review and meta-analysis

Based on studies focusing on positron emission tomography (PET)-computed tomography (CT) combined with magnetic resonance imaging (MRI) in the diagnosis of glioma, we conducted a systematic review and meta-analysis evaluating the pros and cons and the accuracy of different examinations. PubMed and Cochrane Library were searched. The search was conducted until April 2017. Two reviewers independently conducted the literature search according to the criteria set initially. Based on the exclusion criteria, 15 articles are included in this study. Of all studies that used MRI examination, there are five involving 18F-fluorodeoxyglucose-PET, five involving 11C-methionine-PET, five involving 18F-fluoro-ethyl-tyrosine-PET, and three involving 18F-fluorothymidine-PET. Due to the limitations such as lack of data, small sample size, and unrepresentative studies, we use a non-quantitative methodology. MRI examination can provide the anatomy information of glioma more clearly. PET-CT examinations based on tumor metabolism using different tracers have more advantages in determining the degree of glioma malignancy and boundaries. However, information provided by PET-CT of different tracers is not the same. With respect to the novel hybrid MRI/PET examination equipment proposed in recent years, the combination of MRI and PET-CT can definitively improve the diagnostic accuracy of glioma.

The Selective Acetamidine-Based iNOS Inhibitor CM544 Reduces Glioma Cell Proliferation by Enhancing PARP-1 Cleavage In Vitro

Gliomas are the most aggressive adult primary brain tumors. Expression of inducible Nitric Oxide Synthase has been reported as a hallmark of chemoresistance in gliomas and several studies have reported that inhibition of inducible Nitric Oxide Synthase could be related to a decreased proliferation of glioma cells. The present work was to analyze the molecular effects of the acetamidine derivative compound 39 (formally CM544, N-(3-{[(1-iminioethyl)amino]methyl}benzyl) prolinamide dihydrochloride), a newly synthetized iNOS inhibitor, in a C6 rat glioma cell model. There is evidence of CM544 selective binding to the iNOS, an event that triggers the accumulation of ROS/RNS, the expression of Nrf-2 and the phosphorylation of MAPKs after 3 h of treatment. In the long run, CM544 leads to the dephosphorylation of p38 and to a massive cleavage of PARP-1, confirming the block of C6 rat glioma cell proliferation in the G1/S checkpoint and the occurrence of necrotic cell death.

Magnetic resonance imaging-guided radiation therapy using animal models of glioblastoma

Glioblastoma is the most aggressive and most common malignant primary brain tumour in adults and has a high mortality and morbidity. Because local tumour control in glioblastoma patients is still elusive in the majority of patients, there is an urgent need for alternative treatment strategies. However, to implement changes to the existing clinical standard of care, research must be conducted to develop alternative treatment strategies. A novel approach in radiotherapy is the introduction of pre-clinical precision image-guided radiation research platforms. The aim of this review is to give a brief overview of the efforts that have been made in the field of radiation research using animal models of glioblastoma. Because MRI has become the reference imaging technique for treatment planning and assessment of therapeutic responses in glioblastoma patients, we will focus in this review on small animal radiotherapy combined with MRI.