The role of neuropathology in the management of patients with diffuse low grade glioma: A systematic review and evidence-based clinical practice guideline

American Association of Neurological Surgeons/Congress of the Neurological Surgeons Section on Tumors Guidelines: Assessing Their Impact on Brain Tumor Clinical Practice

Clinical guidelines direct healthcare professionals toward evidence-based practices. Evaluating guideline impact can elucidate information penetration, relevance, effectiveness, and alignment with evolving medical knowledge and technological advancements. As the American Association of Neurological Surgeons/Congress of Neurological Surgeons Section on Tumors marks its 40th anniversary in 2024, this article reflects on the tumor guidelines established by the Section over the past decade and explores their impact on other publications, patents, and information dissemination. Six tumor guideline categories were reviewed: low-grade glioma, newly diagnosed glioblastoma, progressive glioblastoma, metastatic brain tumors, vestibular schwannoma, and pituitary adenomas. Citation data were collected from Google Scholar and PubMed. Further online statistics, such as social media reach, and features in policy, news, and patents were sourced from Altmetric. Online engagement was assessed through website and CNS+ mobile application visits. Data were normalized to time since publication. Metastatic Tumor guidelines (2019) had the highest PubMed citation rate at 26.1 per year and webpage visits (29 100 page views 1/1/2019-9/30/2023). Notably, this guideline had two endorsement publications by partner societies, the Society of Neuro-Oncology and American Society of Clinical Oncology, concerning antiepileptic prophylaxis and steroid use, and the greatest reach on X (19.7 mentions/y). Citation rates on Google Scholar were led by Vestibular Schwannoma (2018). Non-Functioning Pituitary Adenoma led Mendeley reads. News, patent, or policy publications were led by low-grade glioma at 1.5/year. Our study shows that the American Association of Neurological Surgeons/Congress of Neurological Surgeons Section on Tumors guidelines go beyond citations in peer-reviewed publications to include patents, online engagement, and information dissemination to the public.

Machine-Learning and Radiomics-Based Preoperative Prediction of Ki-67 Expression in Glioma Using MRI Data

BACKGROUND

Gliomas are the most common primary brain tumours and constitute approximately half of all malignant glioblastomas. Unfortunately, patients diagnosed with malignant glioblastomas typically survive for less than a year. In light of this circumstance, genotyping is an effective means of categorising gliomas. The Ki67 proliferation index, a widely used marker of cellular proliferation in clinical contexts, has demonstrated potential for predicting tumour classification and prognosis. In particular, magnetic resonance imaging (MRI) plays a vital role in the diagnosis of brain tumours. Using MRI to extract glioma-related features and construct a machine learning model offers a viable avenue to classify and predict the level of Ki67 expression.

METHODS

This study retrospectively collected MRI data and postoperative immunohistochemical results from 613 glioma patients from the First Affliated Hospital of Nanjing Medical University. Subsequently, we performed registration and skull stripping on the four MRI modalities: T1-weighted (T1), T2-weighted (T2), T1-weighted with contrast enhancement (T1CE), and Fluid Attenuated Inversion Recovery (FLAIR). Each modality's segmentation yielded three distinct tumour regions. Following segmentation, a comprehensive set of features encompassing texture, first-order, and shape attributes were extracted from these delineated regions. Feature selection was conducted using the least absolute shrinkage and selection operator (LASSO) algorithm with subsequent sorting to identify the most important features. These selected features were further analysed using correlation analysis to finalise the selection for machine learning model development. Eight models: logistic regression (LR), naive bayes, decision tree, gradient boosting tree, and support vector classification (SVM), random forest (RF), XGBoost, and LightGBM were used to objectively classify Ki67 expression.

RESULTS

In total, 613 patients were enroled in the study, and 24,455 radiomic features were extracted from each patient's MRI. These features were eventually reduced to 36 after LASSO screening, RF importance ranking, and correlation analysis. Among all the tested machine learning models, LR and linear SVM exhibited superior performance. LR achieved the highest area under the curve score of 0.912 ± 0.036, while linear SVM obtained the top accuracy with a score of 0.884 ± 0.031.

CONCLUSION

This study introduced a novel approach for classifying Ki67 expression levels using MRI, which has been proven to be highly effective. With the LR model at its core, our method demonstrated its potential in signalling a promising avenue for future research. This innovative approach of predicting Ki67 expression based on MRI features not only enhances our understanding of cell activity but also represents a significant leap forward in brain glioma research. This underscores the potential of integrating machine learning with medical imaging to aid in the diagnosis and prognosis of complex diseases.

Unravelling benzazepines and aminopyrimidine as multi-target therapeutic repurposing drugs for EGFR V774M mutation in neuroglioma patients

Introduction

Neuroglioma, a classification encompassing tumors arising from glial cells, exhibits variable aggressiveness and depends on tumor grade and stage. Unraveling the EGFR gene alterations, including amplifications (unaltered), deletions, and missense mutations (altered), is emerging in glioma. However, the precise understanding of emerging EGFR mutations and their role in neuroglioma remains limited. This study aims to identify specific EGFR mutations prevalent in neuroglioma patients and investigate their potential as therapeutic targets using FDA-approved drugs for repurposing approach.

Methods

Neuroglioma patient's data were analyzed to identify the various mutations and survival rates. High throughput virtual screening (HTVS) of FDA-approved (1615) drugs using molecular docking and simulation was executed to determine the potential hits.

Results

Neuroglioma patient samples (n=4251) analysis reveals 19% EGFR alterations with most missense mutations at V774M in exon 19. The Kaplan-Meier plots show that the overall survival rate was higher in the unaltered group than in the altered group. Docking studies resulted the best hits based on each target's higher docking score, minimum free energy (MMGBSA), minimum kd, ki, and IC50 values. MD simulations and their trajectories show that compounds ZINC000011679756 target unaltered EGFR and ZINC000003978005 targets altered EGFR, whereas ZINC000012503187 (Conivaptan, Benzazepine) and ZINC000068153186 (Dabrafenib, aminopyrimidine) target both the EGFRs. The shortlisted compounds demonstrate favorable residual interactions with their respective targets, forming highly stable complexes. Moreover, these shortlisted compounds have drug- like properties as assessed by ADMET profiling.

Conclusion

Therefore, compounds (ZINC000012503187 and ZINC000068153186) can effectively target both the unaltered/altered EGFRs as multi-target therapeutic repurposing drugs towards neuroglioma.

Dysregulation of inflammasome activation in glioma

Gliomas are the most common brain tumors characterized by complicated heterogeneity. The genetic, molecular, and histological pathology of gliomas is characterized by high neuro-inflammation. The inflammatory microenvironment in the central nervous system (CNS) has been closely linked with inflammasomes that control the inflammatory response and coordinate innate host defenses. Dysregulation of the inflammasome causes an abnormal inflammatory response, leading to carcinogenesis in glioma. Because of the clinical importance of the various physiological properties of the inflammasome in glioma, the inflammasome has been suggested as a promising treatment target for glioma management. Here, we summarize the current knowledge on the contribution of the inflammasomes in glioma and therapeutic insights. Video Abstract.

An initial study on the predictive value using multiple MRI characteristics for Ki-67 labeling index in glioma

BACKGROUND AND PURPOSE

Ki-67 labeling index (LI) is an important indicator of tumor cell proliferation in glioma, which can only be obtained by postoperative biopsy at present. This study aimed to explore the correlation between Ki-67 LI and apparent diffusion coefficient (ADC) parameters and to predict the level of Ki-67 LI noninvasively before surgery by multiple MRI characteristics.

METHODS

Preoperative MRI data of 166 patients with pathologically confirmed glioma in our hospital from 2016 to 2020 were retrospectively analyzed. The cut-off point of Ki-67 LI for glioma grading was defined. The differences in MRI characteristics were compared between the low and high Ki-67 LI groups. The receiver operating characteristic (ROC) curve was used to estimate the accuracy of each ADC parameter in predicting the Ki-67 level, and finally a multivariate logistic regression model was constructed based on the results of ROC analysis.

RESULTS

ADC_min, ADC_mean, rADC_min, rADC_mean and Ki-67 LI showed a negative correlation (r = - 0.478, r = - 0.369, r = - 0.488, r = - 0.388, all P < 0.001). The Ki-67 LI of low-grade gliomas (LGGs) was different from that of high-grade gliomas (HGGs), and the cut-off point of Ki-67 LI for distinguishing LGGs from HGGs was 9.5%, with an area under the ROC curve (AUROC) of 0.962 (95%CI 0.933-0.990). The ADC parameters in the high Ki-67 group were significantly lower than those in the low Ki-67 group (all P < 0.05). The peritumoral edema (PTE) of gliomas in the high Ki-67 LI group was higher than that in the low Ki-67 LI group (P < 0.05). The AUROC of Ki-67 LI level assessed by the multivariate logistic regression model was 0.800 (95%CI 0.721-0.879).

CONCLUSIONS

There was a negative correlation between ADC parameters and Ki-67 LI, and the multivariate logistic regression model combined with peritumoral edema and ADC parameters could improve the prediction ability of Ki-67 LI.

Identification and Verification of an Alternative Polyadenylation-Related lncRNA Prognostic Signature for Glioma

Due to the high mortality and modality of glioma, it was urgently needed to develop a glioma prognostic assessment system. Previous studies demonstrated that alternative polyadenylation- (APA-) related genes are important in immune response and oncogenesis. mRNA and lncRNA expression information of glioma samples were acquired from CGGA and TCGA databases, and lncRNAs associated with APA were selected through correlation analysis. The prognosis model of APA-related lncRNAs was built by the univariate Cox, random forest, and univariate Cox regression analyses. Glioma samples were assigned into high- and low-risk groups. Independence and effectiveness of the prognostic model were evaluated by Kaplan-Meier analysis, ROC curve, and Cox regression analyses. GO, KEGG enrichment, and GSEA analyses showed that the mainly involved signaling pathways were enriched in cellular immunity and immune signal transduction. We further analyzed expression differences of negative immune regulatory genes and immune cell infiltration degree between two groups. Immune checkpoints CTLA4 and LAG3 and immune suppressors TGFB, IL10, NOS3, and IDO1 and immune cell infiltration were notably upregulated in the high-risk group. The PD1/PDL1 expression was significantly correlated with risk score, showing that the prognostic model of APA-related lncRNA could effectively assess the tumor immune suppression. In conclusion, we established a risk assessment model of APA-related lncRNA in glioma, which could effectively evaluate prognosis of patients with glioma and tumor immune suppression and could provide guidance for clinical treatment.

Immune Characteristics and Prognosis Analysis of the Proteasome 20S Subunit Beta 9 in Lower-Grade Gliomas

Glioma is a common intracranial malignancy in adults and has a high mortality due to its poor prognosis and high recurrence rate. Dysregulation of protein degradation is one of the main promoting factors in glioma development. As an indispensable unit of the proteasome, Proteasome 20S Subunit Beta 9 (PSMB9) is one of the major enzymes in ubiquitin-dependent protein degradation in cells. In addition, proteasomes also participate in a series of cellular processing, like immune regulation, nerve signal transduction, material transport through channels, cell adhesion, and various signaling pathways. However, the relationship between the PSMB9 expression and the occurrence of lower-grade glioma (LGG) is still unknown. First, we collected the RNA-seq and clinical information about LGG clinical samples from The Cancer Genome Atlas (TCGA) cohort, Chinese Glioma Genome Atlas (CGGA; including CGGAseq1 and CGGAseq2) cohort, and Gene Expression Omnibus (GEO; GSE16011, GSE61374, and Rembrandt) cohort. Then, these data were used for differential analysis, survival analysis, enrichment analysis, clinical model construction, etc. In addition, we combine immune-related data for immune-related analysis, including immune infiltration and immunotherapy. Through the above research, we have provided a new biomarker for LGG prognosis prediction and more comprehensively explained the role of PSMB9 in the development of LGG. This study determined that PSMB9 can be used as an immunotherapy target through the analysis of immune data, providing new ideas for the clinical treatment of LGG.

Preoperative and Noninvasive Prediction of Gliomas Histopathological Grades and IDH Molecular Types Using Multiple MRI Characteristics

Background and Purpose

Gliomas are one of the most common tumors in the central nervous system. This study aimed to explore the correlation between MRI morphological characteristics, apparent diffusion coefficient (ADC) parameters and pathological grades, as well as IDH gene phenotypes of gliomas.

Methods

Preoperative MRI data from 166 glioma patients with pathological confirmation were retrospectively analyzed to compare the differences of MRI characteristics and ADC parameters between the low-grade and high-grade gliomas (LGGs vs. HGGs), IDH mutant and wild-type gliomas (IDH^mut vs. IDH^wt). Multivariate models were constructed to predict the pathological grades and IDH gene phenotypes of gliomas and the performance was assessed by the receiver operating characteristic (ROC) analysis.

Results

Two multivariable logistic regression models were developed by incorporating age, ADC parameters, and MRI morphological characteristics to predict pathological grades, and IDH gene phenotypes of gliomas, respectively. The Noninvasive Grading Model classified tumor grades with areas under the ROC curve (AUROC) of 0.934 (95% CI=0.895-0.973), sensitivity of 91.2%, and specificity of 78.6%. The Noninvasive IDH Genotyping Model differentiated IDH types with an AUROC of 0.857 (95% CI=0.787-0.926), sensitivity of 88.2%, and specificity of 63.8%.

Conclusion

MRI features were correlated with glioma grades and IDH mutation status. Multivariable logistic regression models combined with MRI morphological characteristics and ADC parameters may provide a noninvasive and preoperative approach to predict glioma grades and IDH mutation status.

ZNF655 Promotes the Progression of Glioma Through Transcriptional Regulation of AURKA

Objectives

Glioma has a high degree of malignancy, strong invasiveness, and poor prognosis, which is always a serious threat to human health. Previous studies have reported that C2H2 zinc finger (ZNF) protein is involved in the progression of various cancers. In this study, the clinical significance, biological behavior, and molecule mechanism of ZNF655 in glioma were explored.

Methods

The expression of ZNF655 in glioma and its correlation with prognosis were analyzed through public datasets and immunohistochemical (IHC) staining. The shRNA-mediated ZNF655 knockdown was used to explore the effects of ZNF655 alteration on the phenotypes and tumorigenesis of human glioma cell lines. Chromatin immunoprecipitation (ChIP)-qPCR and luciferase reporter assays were performed to determine the potential mechanism of ZNF655 regulating Aurora kinase A (AURKA).

Results

ZNF655 was abundantly expressed in glioma tissue and cell lines SHG-44 and U251. Knockdown of suppressed the progression of glioma cells, which was characterized by reduced proliferation, enhanced apoptosis, cycle repression in G2, inhibition of migration, and weakened tumorigenesis. Mechanistically, transcription factor ZNF655 activated the expression of AURKA by directly binding to the promoter of AURKA. In addition, downregulation of AURKA partially reversed the promoting effects of overexpression of ZNF655 on glioma cells.

Conclusions

ZNF655 promoted the progression of glioma by binding to the promoter of AURKA, which may be a promising target for molecular therapy.

G-protein-coupled receptor GPR17 inhibits glioma development by increasing polycomb repressive complex 1-mediated ROS production

Glioma is the most common primary tumor in the central nervous system. However, the development of glioma and effective therapeutic strategies remain elusive. Here, we identify GPR17 as a potential target to treat glioma. Data mining with human LGG and GBM samples reveals that GPR17 is negatively correlated with glioma development. Overexpressing GPR17 inhibits glioma cell proliferation and induces apoptosis by raising ROS levels. GPR17-overexpressing glioma cells are less tumorigenic in the brain than in control cells. Mechanistically, GPR17 inhibits the transcription of RNF2, a key component in the PRC1 complex, through cAMP/PKA/NF-κB signaling, leading to reduced histone H2A monoubiquitination. ChIP-Seq and RNA-Seq analyses reveal KLF9 as a direct target of RNF2. KLF9 mediates the functions of GPR17 and RNF2 in glioma cells. Furthermore, activation of GPR17 by its agonist inhibits glioma formation. Our findings have thus identified GPR17 as a key regulator of glioma development and a potential therapeutic target for gliomas.

Radiomic prediction models for the level of Ki-67 and p53 in glioma

OBJECTIVE

To identify glioma radiomic features associated with proliferation-related Ki-67 antigen and cellular tumour antigen p53 levels, common immunohistochemical markers for differentiating benign from malignant tumours, and to generate radiomic prediction models.

METHODS

Patients with glioma, who were scanned before therapy using standard brain magnetic resonance imaging (MRI) protocols on T1 and T2 weighted imaging, were included. For each patient, regions-of-interest (ROI) were drawn based on tumour and peritumoral areas (5/10/15/20 mm), and features were identified using feature calculations, and used to create and assess logistic regression models for Ki-67 and p53 levels.

RESULTS

A total of 92 patients were included. The best area under the curve (AUC) for the Ki-67 model was 0.773 for T2 weighted imaging in solid glioma (sensitivity, 0.818; specificity, 0.833), followed by a less reliable AUC of 0.773 (sensitivity, 0.727; specificity 0.667) in 20-mm peritumoral areas. The highest AUC for the p53 model was 0.709 (sensitivity, 1; specificity, 0.4) for T2 weighted imaging in 10-mm peritumoral areas.

CONCLUSION

Using T2-weighted imaging, the prediction model for Ki-67 level in solid glioma tissue was better than the p53 model. The 20-mm and 10-mm peritumoral areas in the Ki-67 and p53 model, respectively, showed predictive effects, suggesting value in further research into areas without conventional MRI features.

Guidelines in the management of CNS tumors

INTRODUCTION

Evidence-based, clinical practice guidelines in the management of central nervous system tumors (CNS) continue to be developed and updated through the work of the Joint Section on Tumors of the Congress of Neurological Surgeons (CNS) and the American Association of Neurological Surgeons (AANS).

METHODS

The guidelines are created using the most current and clinically relevant evidence using systematic methodologies, which classify available data and provide recommendations for clinical practice.

CONCLUSION

This update summarizes the Tumor Section Guidelines developed over the last five years for non-functioning pituitary adenomas, low grade gliomas, vestibular schwannomas, and metastatic brain tumors.

PD-L1 Expression Correlated with p53 Expression in Pediatric Glioblastoma Multiforme

High-grade gliomas are infrequent in the pediatric population compared to adults, nevertheless, mortality and morbidity caused by malignant gliomas in this group of patients remain significant. PD-L1 and PD-1 Immune checkpoints (IC) molecules maintain immunological balance between activation and suppression. Eighteen patients with a histopathological diagnosis of pediatric glioblastoma multiforme (GBM, WHO IV) were studied. In total, PD-L1 expression was detected in 8 patients (44%). The molecular aspect of IC and immunotherapy targeted on PD-1/PD-L1 axis in pediatric population may be a promising adjuvant therapy in pediatric glioblastoma multiform treatment, however, this subject requires further investigation.

A Simple Panel of IDH1 and P53 in Differential Diagnosis Between Low-Grade Astrocytoma and Reactive Gliosis

Background

Reactive gliosis is a response of glial tissue to different types of injury such as brain abscess, trauma, hemorrhage, or even neoplastic process. In some circumstances, especially when the tissue biopsy is small, there may be difficulty to discriminate this reactive condition with low-grade diffuse astrocytoma (World Health Organization [WHO] grade II) by conventional hematoxylin and eosin (H&E) slides, so some immunohistochemical and molecular markers have been introduced for this differential diagnosis. One of the important aspects of updated WHO classification in 2016 has been dividing some of the glial tumor according to IDH1 (isocitrate dehydrogenase 1) mutation.

Objectives

In this study, we tried to evaluate IDH1 and P53 mutation by immunohistochemistry as a simple and highly specific and sensitive method to differentiate low-grade astrocytoma and reactive gliosis.

Material and methods

For 5 years (2013-2018), 50 cases of clinically documented reactive gliosis and 50 cases of low-grade astrocytoma were evaluated for the presence or absence of IDH1 and P53 mutation by immunohistochemistry.

Results

Isocitrate dehydrogenase 1 was positive in 92% and 4% of the astrocytoma and reactive gliosis cases and P53 was positive in 90% and 4% of the cases with the final diagnosis of astrocytoma and reactive gliosis, respectively.

Discussion and conclusion

Combination of P53 and IDH1 as an immunohistochemical panel showed specificity of 96% and sensitivity of 91% for differential diagnosis of reactive gliosis and low-grade astrocytoma. These 2 markers can be extremely helpful for this differential diagnosis.

Long-term outcome of stereotactic brachytherapy with temporary Iodine-125 seeds in patients with WHO grade II gliomas

BACKGROUND

This long-term retrospective analysis aimed to investigate the outcome and toxicity profile of stereotactic brachytherapy (SBT) in selected low-grade gliomas WHO grade II (LGGII) in a large patient series.

METHODS

This analysis comprised 106 consecutive patients who received SBT with temporary Iodine-125 seeds for histologically verified LGGII at the University of Munich between March 1997 and July 2011. Investigation included clinical characteristics, technical aspects of SBT, the application of other treatments, outcome analyses including malignization rates, and prognostic factors with special focus on molecular biomarkers.

RESULTS

For the entire study population, the 5- and 10-years overall survival (OS) rates were 79% and 62%, respectively, with a median follow-up of 115.9 months. No prognostic factors could be identified. Interstitial radiotherapy was applied in 51 cases as first-line treatment with a median number of two seeds (range 1-5), and a median total implanted activity of 21.8 mCi (range 4.2-43.4). The reference dose average was 54.0 Gy. Five- and ten-years OS and progression-free survival rates after SBT were 72% and 43%, and 40% and 23%, respectively, with a median follow-up of 86.7 months. The procedure-related mortality rate was zero, although an overall complication rate of 16% was registered. Patients with complications had a significantly larger tumor volume (p = 0.029).

CONCLUSION

SBT is a minimally invasive treatment modality with a favorable outcome and toxicity profile. It is both an alternative primary treatment method as well as an adjunct to open tumor resection in selected low-grade gliomas.

Interrogation of IDH1 Status in Gliomas by Fourier Transform Infrared Spectroscopy

Mutations in the isocitrate dehydrogenase 1 (IDH1) gene are found in a high proportion of diffuse gliomas. The presence of the IDH1 mutation is a valuable diagnostic, prognostic and predictive biomarker for the management of patients with glial tumours. Techniques involving vibrational spectroscopy, e.g., Fourier transform infrared (FTIR) spectroscopy, have previously demonstrated analytical capabilities for cancer detection, and have the potential to contribute to diagnostics. The implementation of FTIR microspectroscopy during surgical biopsy could present a fast, label-free method for molecular genetic classification. For example, the rapid determination of IDH1 status in a patient with a glioma diagnosis could inform intra-operative decision-making between alternative surgical strategies. In this study, we utilized synchrotron-based FTIR microanalysis to probe tissue microarray sections from 79 glioma patients, and distinguished the positive class (IDH1-mutated) from the IDH1-wildtype glioma, with a sensitivity and specificity of 82.4% and 83.4%, respectively. We also examined the ability of attenuated total reflection (ATR)-FTIR spectroscopy in detecting the biomolecular events and global epigenetic and metabolic changes associated with mutations in the IDH1 enzyme, in blood serum samples collected from an additional 72 brain tumour patients. Centrifugal filtration enhanced the diagnostic ability of the classification models, with balanced accuracies up to ~69%. Identification of the molecular status from blood serum prior to biopsy could further direct some patients to alternative treatment strategies.

Raman spectroscopy to differentiate between fresh tissue samples of glioma and normal brain: a comparison with 5-ALA-induced fluorescence-guided surgery

OBJECTIVE

Raman spectroscopy is a biophotonic tool that can be used to differentiate between different tissue types. It is nondestructive and no sample preparation is required. The aim of this study was to evaluate the ability of Raman spectroscopy to differentiate between glioma and normal brain when using fresh biopsy samples and, in the case of glioblastomas, to compare the performance of Raman spectroscopy to predict the presence or absence of tumor with that of 5-aminolevulinic acid (5-ALA)-induced fluorescence.

METHODS

A principal component analysis (PCA)-fed linear discriminant analysis (LDA) machine learning predictive model was built using Raman spectra, acquired ex vivo, from fresh tissue samples of 62 patients with glioma and 11 glioma-free brain samples from individuals undergoing temporal lobectomy for epilepsy. This model was then used to classify Raman spectra from fresh biopsies from resection cavities after functional guided, supramaximal glioma resection. In cases of glioblastoma, 5-ALA-induced fluorescence at the resection cavity biopsy site was recorded, and this was compared with the Raman spectral model prediction for the presence of tumor.

RESULTS

The PCA-LDA predictive model demonstrated 0.96 sensitivity, 0.99 specificity, and 0.99 accuracy for differentiating tumor from normal brain. Twenty-three resection cavity biopsies were taken from 8 patients after supramaximal resection (6 glioblastomas, 2 oligodendrogliomas). Raman spectroscopy showed 1.00 sensitivity, 1.00 specificity, and 1.00 accuracy for predicting tumor versus normal brain in these samples. In the glioblastoma cases, where 5-ALA-induced fluorescence was used, the performance of Raman spectroscopy was significantly better than the predictive value of 5-ALA-induced fluorescence, which showed 0.07 sensitivity, 1.00 specificity, and 0.24 accuracy (p = 0.0009).

CONCLUSIONS

Raman spectroscopy can accurately classify fresh tissue samples into tumor versus normal brain and is superior to 5-ALA-induced fluorescence. Raman spectroscopy could become an important intraoperative tool used in conjunction with 5-ALA-induced fluorescence to guide extent of resection in glioma surgery.

Interventions to reduce the time to diagnosis of brain tumours

BACKGROUND

Brain tumours are recognised as one of the most difficult cancers to diagnose because presenting symptoms, such as headache, cognitive symptoms, and seizures, may be more commonly attributable to other, more benign conditions. Interventions to reduce the time to diagnosis of brain tumours include national awareness initiatives, expedited pathways, and protocols to diagnose brain tumours, based on a person's presenting symptoms and signs; and interventions to reduce waiting times for brain imaging pathways. If such interventions reduce the time to diagnosis, it may make it less likely that people experience clinical deterioration, and different treatment options may be available.

OBJECTIVES

To systematically evaluate evidence on the effectiveness of interventions that may influence: symptomatic participants to present early (shortening the patient interval), thresholds for primary care referral (shortening the primary care interval), and time to imaging diagnosis (shortening the secondary care interval and diagnostic interval). To produce a brief economic commentary, summarising the economic evaluations relevant to these interventions.

SEARCH METHODS

For evidence on effectiveness, we searched CENTRAL, MEDLINE, and Embase from January 2000 to January 2020; Clinicaltrials.gov to May 2020, and conference proceedings from 2014 to 2018. For economic evidence, we searched the UK National Health Services Economic Evaluation Database from 2000 to December 2014.

SELECTION CRITERIA

We planned to include studies evaluating any active intervention that may influence the diagnostic pathway, e.g. clinical guidelines, direct access imaging, public health campaigns, educational initiatives, and other interventions that might lead to early identification of primary brain tumours. We planned to include randomised and non-randomised comparative studies. Included studies would include people of any age, with a presentation that might suggest a brain tumour.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed titles identified by the search strategy, and the full texts of potentially eligible studies. We resolved discrepancies through discussion or, if required, by consulting another review author.

MAIN RESULTS

We did not identify any studies for inclusion in this review. We excluded 115 studies. The main reason for exclusion of potentially eligible intervention studies was their study design, due to a lack of control groups. We found no economic evidence to inform a brief economic commentary on this topic.

AUTHORS' CONCLUSIONS

In this version of the review, we did not identify any studies that met the review inclusion criteria for either effectiveness or cost-effectiveness. Therefore, there is no evidence from good quality studies on the best strategies to reduce the time to diagnosis of brain tumours, despite the prioritisation of research on early diagnosis by the James Lind Alliance in 2015. This review highlights the need for research in this area.

Frameless Stereotactic Biopsy with DTI-Based Tractography Integration: How to Adjust the Trajectory-A Case Series

BACKGROUND

Frameless stereotactic biopsy represents a minimally invasive procedure used for the histopathological diagnosis of brain tumors or to safely approach deep-seated lesions near eloquent areas not amenable for classical neurosurgical procedures. Traditionally, biopsy is performed relying on anatomical landmarks, but it can lead itself to intra- and postoperative complications, such as hemorrhage and fiber disruption. Diffusion tensor imaging (DTI) tractography represents a useful tool that can analyze the individual fiber tract conformation in cases of brain tumor and consequently identify the best biopsy trajectory, preserving white matter pathways. In our study, we present a novel technique that is based on the use of preoperative DTI for biopsy.

METHODS

Between January 2018 and January 2020, data about patients who underwent frameless biopsy using DTI tractography were retrospectively reviewed. The inclusion criterion was adult patients eligible for elective surgery for a single or multiple deep-seated lesions with contraindications to complete surgical resection.

RESULTS

We included 12 patients (mean age of 67.9 [±9.6] years). A single cranial lesion was detected in 7 cases, and multiple lesions in 5 cases. The use of DTI enabled the identification of white matter pathways in all cases and adjustment of the biopsy trajectory based on anatomical landmarks in 7 cases. Postoperative hematoma was reported in 1 case, and histological diagnosis was obtained in 11 cases.

CONCLUSION

According to our results, tractography is a useful tool that can enhance the safety of cerebral lesions biopsy sparing any fiber tract damages.

MicroRNA-144 represses gliomas progression and elevates susceptibility to Temozolomide by targeting CAV2 and FGF7

Malignant gliomas are the most common tumor in central nervous system with poor prognosis. Due to the limitation of histological classification in earlier diagnosis and individualized medicine, it is necessary to combine the molecular signatures and the pathological characteristics of gliomas. Lots of microRNAs presented abnormal expression in gliomas and modulated gliomas development. Exploration the miRNAs profile is helpful for the diagnosis, therapy and prognosis of gliomas. It has been demonstrated that miR-144 plays important roles in solid tumors. However, the detail mechanisms remained unrevealed. In this study, we have demonstrated the level of miR-144 decreased in glioma tissues from patients, especially in gliomas with higher grades. MiR-144 was also validated have lower expression in glioma cell lines compared with cortical neuron cell by using qRT-PCR. The in vitro functional experiment indicated miR-144 improved gliomas progression through repressing proliferation, sensitizing to chemotherapeutics and inhibiting metastasis. We further identified fibroblast growth factor 7 (FGF7) and Caveolin 2 (CAV2) were target genes of miR-144 by luciferase reporter assay and western blotting. The mechanisms study suggested forced FGF7 expression elevated Akt activation and decreased reactive oxygen species (ROS) generation. The MTT and cell cycle assay indicated miR-144 suppressed glioma cells proliferation through modulating FGF mediated Akt signaling pathway. Meanwhile, miR-144 promoted Temozolomide (TMZ) induced apoptosis in glioma cells via increasing ROS production by using FACS. On the other hand, CAV2, as another target of miR-144, accelerated glioma cells migration and invasion via promoting glioma cells EMT progress. Retrieved expression of FGF7 or CAV2 rescued the proliferation and migration function mediated by miR-144. Furthermore, the in vivo experiments in PDX models displayed the anti-tumor function of miR-144, which could be retrieved by overexpression of FGF7 and CAV2. Taken together, these findings indicated miR-144 acted as a potential target against gliomas progression and uncovered a novel regulatory mechanism, which may provide a new therapeutic strategy and prognostic indicator for gliomas.

Surgical management of lower-grade glioma in the spotlight of the 2016 WHO classification system

PURPOSE

According to the 2016 WHO classification lower-grade gliomas consist of three groups: IDH-mutated and 1p/19q co-deleted, IDH-mutated and IDH-wildtype tumors. The aim of this study was to evaluate the impact of surgical therapy for lower-grade gliomas with a particular focus on the molecular subgroups.

METHODS

This is a bi-centric retrospective analysis including 299 patients, who underwent treatment for lower-grade glioma between 1990 and 2016. All tumors were re-classified according to the 2016 WHO classification. Data concerning baseline and tumor characteristics, overall survival, different treatment modalities and functional outcome were analyzed.

RESULTS

A total of 112 (37.5%) patients with IDH-mutation and 1p/19q co-deletetion, 86 (28.8%) patients with IDH-mutation and 101 (33.8%) patients with IDH-wildtype tumors were identified. The median overall survival (mOS) differed significantly between the groups (p < 0.001). Surgical resection was performed in 226 patients and showed significantly improved mOS compared to the biopsy group (p = 0.001). Gross total resection (GTR) was associated with better survival (p = 0.007) in the whole cohort as well as in the IDH-mutated and IDH-wildtype groups compared to partial resection or biopsy. IDH-wildtype patients presented a significant survival benefit after combined radio-chemotherapy compared to radio- or chemotherapy alone (p = 0.02). Good clinical status (NANO) was associated with longer OS (p = 0.001).

CONCLUSION

The impact of surgical treatment on the outcome of lower-grade gliomas depends to a great extent on the molecular subtype of the tumors. Patients with more aggressive tumors (IDH-wildtype) seem to profit from more intensive treatment like GTR, multiple resections and combined radio-/chemotherapy.

The diagnostic accuracy of detecting malignant transformation of low-grade glioma using O-(2-[18F]fluoroethyl)-l-tyrosine positron emission tomography: a retrospective study

OBJECTIVE

The diagnostic accuracy of O-(2-[18F]fluoroethyl)-l-tyrosine (FET) PET scanning in detecting the malignant transformation of low-grade gliomas (LGGs) is controversial. In this study, the authors retrospectively assessed the diagnostic potential of FET PET in patients with MRI-suspected malignant progression of LGGs that had previously been treated and the relationship between FET uptake and MRI and molecular biomarkers.

METHODS

Forty-two patients who had previously undergone surgical or multimodal treatment for a histologically verified LGG were referred for FET PET assessment because of clinical signs and/or MRI findings suggestive of tumor progression. Maximal and mean tumor-to-brain ratios (TBRmax and TBRmean, respectively) on FET PET as well as kinetic FET PET parameters (time to peak [TTP] and time-activity curve [TAC]) were determined. Final diagnoses were confirmed histologically. The diagnostic accuracy of FET parameters, separately and combined, for the detection of malignant progression was evaluated using receiver operating characteristic (ROC) curve analysis. Possible predictors that might influence the diagnostic accuracy of FET PET were assessed using multiple linear regression analysis. Spearman’s rank correlation r method was applied to determine the correlation between TBRmax and TAC, and molecular biomarkers from tumor tissues.

RESULTS

A total of 47 FET PET scans were obtained and showed no significant association between FET parameters and contrast enhancement on MRI. ROC curve analyses overall were unable to demonstrate any significant differentiation between nontransformed LGGs and LGGs that had transformed to high-grade gliomas when evaluating FET parameters separately or combined. After excluding the oligodendroglial subgroup, a significant difference was observed between nontransformed and transformed LGGs when combining FET parameters (i.e., TBRmax > 1.6, TAC describing a plateau or decreasing pattern, and TTP < 25 minutes), with the best result yielded by a combined analysis of TBRmax > 1.6 and TAC with a plateau or decreasing pattern (sensitivity 75% and specificity 83%, p = 0.003). The difference was even greater when patients who had previously undergone oncological treatment were also excluded (sensitivity 93% and specificity 100%, p = 0.001). Multiple linear regression analysis revealed that the presence of an oligodendroglial component (p = 0.029), previous oncological treatment (p = 0.039), and the combined FET parameters (p = 0.027) were significant confounding factors in the detection of malignant progression. TBRmax was positively correlated with increasing cell density (p = 0.040) and inversely correlated with IDH1 mutation (p = 0.006).

CONCLUSIONS

A single FET PET scan obtained at the time of radiological and/or clinical progression seems to be of limited value in distinguishing transformed from nontransformed LGGs, especially if knowledge of the primary tumor histopathology is not known. Therefore, FET PET imaging alone is not adequate to replace histological confirmation, but it may provide valuable information on the location and delineation of active tumor tissue, as well as an assessment of tumor biology in a subgroup of LGGs.

IDH1, ATRX, and BRAFV600E mutation in astrocytic tumors and their significance in patient outcome in north Indian population

Background:

According to the current World Health Organization (WHO) classification of central nervous system (CNS) tumors (2016), histological diagnosis of gliomas should be supplemented by molecular information. This study was carried out to determine the frequency of isocitrate dehydrogenase 1 (IDH1), ATRX, and BRAF V600E mutations in different grade astrocytomas and their prognostic value.

Methods:

Eighty cases of astrocytoma (15 pilocytic astrocytoma, 25 diffuse astrocytoma, 15 anaplastic astrocytoma, and 25 glioblastoma) with follow-up information were analyzed using immunohistochemistry for IDH1 mutant protein, ATRX, p53, and BRAF. Sanger sequencing was carried out for IDH1 exon 4 and BRAF exon 15.

Results:

All pilocytic astrocytoma and primary glioblastoma cases were negative for IDH1 mutation. IDH1 mutation was detected in 80% (20/25) DA and 87% (13/15) AA cases. IDH1 R132H was the commonest IDH1 mutation (94.1%) and immunohistochemistry showed 100% sensitivity and specificity to detect this mutation. Loss of nuclear ATRX expression was found in 87% (20/23) and 100% (14/14) DA and AA cases, respectively. IDH1 mutant DA patients had longer overall survival than IDH1 wild cases, although this difference was not significant (79.5 months vs. 42.5 months, P value 0.417). BRAF V600E mutation was not detected in any astrocytic tumor.

Conclusions:

IDH1 and ATRX mutations are very common in diffuse astrocytoma and anaplastic astrocytoma, while they are rare in pilocytic astrocytoma and glioblastoma. Immunohistochemistry for IDH1 and ATRX can successfully characterize the diffuse gliomas into molecularly defined groups in majority of the cases. BRAF V600E mutation is rare in astrocytic tumors in Indian population.

Optical Analysis of Glioma: Fourier-Transform Infrared Spectroscopy Reveals the IDH1 Mutation Status

Purpose: Somatic mutations in the human cytosolic isocitrate dehydrogenase 1 (IDH1) gene cause profound changes in cell metabolism and are a common feature of gliomas with unprecedented predictive and prognostic impact. Fourier-transform infrared (FT-IR) spectroscopy addresses the molecular composition of cells and tissue and was investigated to deduct the IDH1 mutation status.Experimental Design: We tested the technique on human cell lines that were transduced with wild-type IDH1 or mutated IDH1 and on 34 human glioma samples. IR spectra were acquired at 256 positions from cell pellets or tissue cryosections. Moreover, IR spectra were obtained from fresh, unprocessed biopsies of 64 patients with glioma.Results:IDH1 mutation was linked to changes in spectral bands assigned to molecular groups of lipids and proteins in cell lines and human glioma. The spectra of cryosections of brain tumor samples showed high interpatient variability, for example, bands related to calcifications at 1113 cm^-1 However, supervised classification recognized relevant spectral regions at 1103, 1362, 1441, 1485, and 1553 cm^-1 and assigned 88% of the tumor samples to the correct group. Similar spectral positions allowed the classification of spectra of fresh biopsies with an accuracy of 86%.Conclusions: Here, we show that vibrational spectroscopy reveals the IDH1 genotype of glioma. Because it can provide information in seconds, an implementation into the intraoperative workflow might allow simple and rapid online diagnosis of the IDH1 genotype. The intraoperative confirmation of IDH1 mutation status might guide the decision to pursue definitive neurosurgical resection and guide future in situ therapies of infiltrative gliomas. Clin Cancer Res; 24(11); 2530-8. ©2017 AACRSee related commentary by Hollon and Orringer, p. 2467.

Sodium Fluorescein Facilitates Guided Sampling of Diagnostic Tumor Tissue in Nonenhancing Gliomas

BACKGROUND

Accurate tissue sampling in nonenhancing (NE) gliomas is a unique surgical challenge due to their intratumoral histological heterogeneity and absence of contrast enhancement as a guide for intraoperative stereotactic guidance. Instead, T2/fluid-attenuated inversion-recovery (FLAIR) hyperintensity on MRI is commonly used as an imaging surrogate for pathological tissue, but sampling from this region can yield nondiagnostic or underdiagnostic brain tissue. Sodium fluorescein is an intraoperative fluorescent dye that has a high predictive value for tumor identification in areas of contrast enhancement and NE in glioblastomas. However, the underlying histopathological alterations in fluorescent regions of NE gliomas remain undefined.

OBJECTIVE

To evaluate whether fluorescein can identify diagnostic tissue and differentiate regions with higher malignant potential during surgery for NE gliomas, thus improving sampling accuracy.

METHODS

Thirteen patients who presented with NE, T2/FLAIR hyperintense lesions suspicious for glioma received fluorescein (10%, 3 mg/kg intravenously) during surgical resection.

RESULTS

Patchy fluorescence was identified within the T2/FLAIR hyperintense area in 10 of 13 (77%) patients. Samples taken from fluorescent regions were more likely to demonstrate diagnostic glioma tissue and cytologic atypia (P &lt; .05). Fluorescein demonstrated a 95% positive predictive value for the presence of diagnostic tissue. Samples from areas of fluorescence also demonstrated greater total cell density and higher Ki-67 labeling than nonfluorescent biopsies (P &lt; .05).

CONCLUSION

Fluorescence in NE gliomas is highly predictive of diagnostic tumor tissue and regions of higher cell density and proliferative activity.

Incidence and survival trends in oligodendrogliomas and anaplastic oligodendrogliomas in the United States from 2000 to 2013: a CBTRUS Report

Measuring tumor-specific trends in incidence is necessary to elucidate tumor-type contribution to overall cancer burden in the US population. Recently, there have been conflicting reports concerning the incidence of oligodendrogliomas (OD) and anaplastic oligodendrogliomas (AOD). Therefore, our goal was to examine trends in OD and AOD incidence and survival by age, gender and race. Data was analyzed from the Central Brain Tumor Registry of the United States (CBTRUS) from 2000 to 2013. Age-adjusted incidence rates per 100,000 person-years with 95% confidence intervals (CI) and annual percent changes (APCs) with 95% CI were calculated for OD and AOD by age, sex and race. Survival rates were calculated for age, sex and race using a subset of the CBTRUS data. OD and AOD incidence peaked at 36-40 and 56-60 years, respectively. AOD:OD ratio increased up to age 75. Overall, OD and AOD incidence decreased [OD: APC -3.2 (2000-2013), AOD: -6.5 (2000-2007)]. OD incidence was highest in Whites but decreased significantly (2000-2013: APC -3.1) while incidence in Black populations did not significantly decrease (2000-2013: APC -1.6). Survival rates decreased with advancing age for OD, while persons aged 0-24 had the lowest survival for AOD. The current study reports a decrease in overall OD and AOD incidence from 2000 to 2013. Furthermore, AOD makes up an increasing proportion of oligodendroglial tumors up to age 75. Lower AOD survival in 0-24 years old may indicate molecular differences in pediatric cases. Thus, surveillance of tumor-specific trends by age, race and sex can reveal clinically relevant variations.

Glioma Subclassifications and Their Clinical Significance

The impact of targeted therapies in glioma has been modest. All the therapies that have demonstrated a significant survival benefit for gliomas in Phase III trials, including radiation, chemotherapy (temozolomide and PCV [procarbazine, lomustine, vincristine]), and tumor-treating fields, are based on nonspecific targeting of proliferating cells. Recent advances in the molecular understanding of gliomas suggest some potential reasons for the failure of more targeted therapies in gliomas. Specifically, the histologic-based glioma classification is composed of multiple different molecular subtypes with distinct biology, natural history, and prognosis. As a result of these insights, the diagnosis and classification of gliomas have recently been updated by the World Health Organization. However, these changes and other novel observations regarding glioma biomarkers and subtypes highlight several clinical challenges. First, the field is faced with the difficulty of reinterpreting the results of prior studies and retrospective data using the new classifications to clarify prognostic assessments and treatment recommendations for patients. Second, the new classifications and insights require rethinking the design and stratification of future clinical trials. Last, these observations provide the essential framework for the development and testing of new specific targeted therapies for particular glioma subtypes. This review aims to summarize the current literature regarding glioma subclassifications and their clinical relevance in this evolving field.

An integrative molecular and genomic analysis of pediatric hemispheric low-grade gliomas: an update

Hemispheric low-grade gliomas account for the second most common location in pediatric low-grade gliomas (PLGGs) after the cerebellum. The pathological spectrum includes gangliogliomas, dysembryoplastic neuroepithelial tumors (DNETs), diffuse astrocytomas, pilocytic astrocytomas, and pleomorphic xanthoastrocytomas (PXAs), among others. Clinically, hemispheric PLGGs represent a well-recognized cause of intractable epilepsy in children and adolescents. With an excellent long-term outcome, surgery remains the cornerstone and patients with gross total resection typically do not need any further therapies. The recent literature about hemispheric PLGGs was reviewed to provide an up-to-date overview of the molecular and cell biology of these tumors. Hemispheric PLGGs can harbor multiple alterations involving BRAFV600E, FGFR, NTRK, MYB/MYBL1, IDH, and BRAF-KIAA1549 fusions. However, the clinical significance of most of these alterations is still to be defined. The role of RAS/MAPK mutations and other alterations in hemispheric PLGGs is of interest from diagnostic, prognostic, and therapeutic perspectives. Molecular testing for these tumors should be encouraged, since the findings can have an important impact not only in prognosis but also in therapeutic strategies.

Clinical ramifications of "genomic staging" of low-grade gliomas

"Low-grade gliomas" (LGGs), classification of which is derived from histopathological observations, exhibit significant heterogeneity in clinical behavior. Recently, increasing attention has been paid to genomic analyses of these tumors, to aid in treatment and prognostic decision-making. We discuss herein the recent genomic analysis of gliomas from two major recent publications, and also the results of seminal LGG trials in the context of molecular and genomic stratification, with respect to both prognosis and response to therapy. We also analyze implications of these "molecular classifications". We propose separating out the worst prognostic subsets, whose outcomes resemble those of glioblastoma patients. Lastly, a brief discussion is provided regarding translating this collective knowledge into the clinic and in treatment decisions; also addressed are some of the many questions that still need to be examined in light of these strong and emerging data.

Further understanding of the pathology of glioma: implications for the clinic

INTRODUCTION

Glioma classification and grading has been historically based in morphologic appearance of tumor cells: astrocytomas, oligodendrogliomas, oligoastrocytomas and ependymomas. Recent molecular advances have transformed the field of neuro-oncology, as some molecular markers harbor diagnostic, prognostic and therapeutic implications.

AREAS COVERED

In this paper we will review the major molecular changes associated with gliomas and their implications in diagnosis, prognosis, and opportunities in therapeutics. Expert commentary: Based on current understanding, adult diffuse infiltrating gliomas can be molecularly divided into three to five major subgroups with different clinical outcomes. Pediatric gliomas harbor mutations for H3F3A, ATRX and DAXX but not IDH. Circumscribed low-grade gliomas tend to have BRAF alterations. Clinical behavior of ependymomas correlates more with location than WHO grading. Posterior fossa ependymomas tend to behave worse than their cerebral or spinal cord counterparts. However, with the posterior fossa ependymomas, two distinct subtypes have emerged molecularly.

Malignant Transformation in Glioma Steered by an Angiogenic Switch: Defining a Role for Bone Marrow-Derived Cells

Low-grade gliomas, such as pilocytic astrocytoma and subependymoma, are often characterized as benign tumors due to their relative circumscription radiologically and typically non-aggressive biologic behavior. In contrast, low-grades that are by their nature diffusely infiltrative, such as diffuse astrocytomas and oligodendrogliomas, have the potential to transform into malignant high-grade counterparts and, given sufficient time, invariably do so. These high-grade gliomas carry very poor prognoses and are largely incurable, warranting a closer look at what causes this adverse transition. A key characteristic that distinguishes low- and high-grade gliomas is neovascularization: it is absent in low-grade gliomas, but prolific in high-grade gliomas, providing the tumor with ample blood supply for exponential growth. It has been well described in the literature that bone marrow-derived cells (BMDCs) may contribute to the angiogenic switch that is responsible for malignant transformation of low-grade gliomas. In this review, we will summarize the current literature on BMDCs and their known contribution to angiogenesis-associated tumor growth in gliomas.