Molecular Markers in Low-Grade Glioma-Toward Tumor Reclassification

Cerebrospinal Fluid Liquid Biopsies in the Evaluation of Adult Gliomas

PURPOSE OF REVIEW

This review aims to discuss recent research regarding the biomolecules explored in liquid biopsies and their potential clinical uses for adult-type diffuse gliomas.

RECENT FINDINGS

Evaluation of tumor biomolecules via cerebrospinal fluid (CSF) is an emerging technology in neuro-oncology. Studies to date have already identified various circulating tumor DNA, extracellular vesicle, micro-messenger RNA and protein biomarkers of interest. These biomarkers show potential to assist in multiple avenues of central nervous system (CNS) tumor evaluation, including tumor differentiation and diagnosis, treatment selection, response assessment, detection of tumor progression, and prognosis. In addition, CSF liquid biopsies have the potential to better characterize tumor heterogeneity compared to conventional tissue collection and CNS imaging. Current imaging modalities are not sufficient to establish a definitive glioma diagnosis and repeated tissue sampling via conventional biopsy is risky, therefore, there is a great need to improve non-invasive and minimally invasive sampling methods. CSF liquid biopsies represent a promising, minimally invasive adjunct to current approaches which can provide diagnostic and prognostic information as well as aid in response assessment.

Personalized treatment selection via product partition models with covariates

Precision medicine is an approach for disease treatment that defines treatment strategies based on the individual characteristics of the patients. Motivated by an open problem in cancer genomics, we develop a novel model that flexibly clusters patients with similar predictive characteristics and similar treatment responses; this approach identifies, via predictive inference, which one among a set of treatments is better suited for a new patient. The proposed method is fully model based, avoiding uncertainty underestimation attained when treatment assignment is performed by adopting heuristic clustering procedures, and belongs to the class of product partition models with covariates, here extended to include the cohesion induced by the normalized generalized gamma process. The method performs particularly well in scenarios characterized by considerable heterogeneity of the predictive covariates in simulation studies. A cancer genomics case study illustrates the potential benefits in terms of treatment response yielded by the proposed approach. Finally, being model based, the approach allows estimating clusters' specific response probabilities and then identifying patients more likely to benefit from personalized treatment.

Self-Functionalized Superlattice Nanosensor Enables Glioblastoma Diagnosis Using Liquid Biopsy

Glioblastoma (GBM), the most aggressive and lethal brain cancer, is detected only in the advanced stage, resulting in a median survival rate of 15 months. Therefore, there is an urgent need to establish GBM diagnosis tools to identify the tumor accurately. The clinical relevance of the current liquid biopsy techniques for GBM diagnosis remains mostly undetermined, owing to the challenges posed by the blood-brain barrier (BBB) that restricts biomarkers entering the circulation, resulting in the unavailability of clinically validated circulating GBM markers. GBM-specific liquid biopsy for diagnosis and prognosis of GBM has not yet been developed. Here, we introduce extracellular vesicles of GBM cancer stem cells (GBM CSC-EVs) as a previously unattempted, stand-alone GBM diagnosis modality. As GBM CSCs are fundamental building blocks of tumor initiation and recurrence, it is desirable to investigate these reliable signals of malignancy in circulation for accurate GBM diagnosis. So far, there are no clinically validated circulating biomarkers available for GBM. Therefore, a marker-free approach was essential since conventional liquid biopsy relying on isolation methodology was not viable. Additionally, a mechanism capable of trace-level detection was crucial to detecting the rare GBM CSC-EVs from the complex environment in circulation. To break these barriers, we applied an ultrasensitive superlattice sensor, self-functionalized for surface-enhanced Raman scattering (SERS), to obtain holistic molecular profiling of GBM CSC-EVs with a marker-free approach. The superlattice sensor exhibited substantial SERS enhancement and ultralow limit of detection (LOD of attomolar 10-18 M concentration) essential for trace-level detection of invisible GBM CSC-EVs directly from patient serum (without isolation). We detected as low as 5 EVs in 5 μL of solution, achieving the lowest LOD compared to existing SERS-based studies. We have experimentally demonstrated the crucial role of the signals of GBM CSC-EVs in the precise detection of glioblastoma. This was evident from the unique molecular profiles of GBM CSC-EVs demonstrating significant variation compared to noncancer EVs and EVs of GBM cancer cells, thus adding more clarity to the current understanding of GBM CSC-EVs. Preliminary validation of our approach was undertaken with a small amount of peripheral blood (5 μL) derived from GBM patients with 100% sensitivity and 97% specificity. Identification of the signals of GBM CSC-EV in clinical sera specimens demonstrated that our technology could be used for accurate GBM detection. Our technology has the potential to improve GBM liquid biopsy, including real-time surveillance of GBM evolution in patients upon clinical validation. This demonstration of liquid biopsy with GBM CSC-EV provides an opportunity to introduce a paradigm potentially impacting the current landscape of GBM diagnosis.

A survival nomogram model constructed with common clinical characteristics to assist clinical decisions for diffuse low-grade gliomas: A population analysis based on SEER database

Background

The prognosis of diffuse low-grade gliomas (DLGGs, WHO grade 2) is highly variable, making it difficult to evaluate individual patient outcomes. In this study, we used common clinical characteristics to construct a predictive model with multiple indicators.

Methods

We identified 2459 patients diagnosed with astrocytoma and oligodendroglioma from 2000 to 2018 in the SEER database. After removing invalid information, we randomly divided the cleaned patient data into training and validation groups. We performed univariate and multivariate Cox regression analyses and constructed a nomogram. Receiver operating characteristic (ROC) curve, c-index, calibration curve, and subgroup analyses were used to assess the accuracy of the nomogram by internal and external validation.

Results

After univariate and multivariate Cox regression analyses, we identified seven independent prognostic factors, namely, age (P<0.001), sex (P<0.05), histological type (P<0.001), surgery (P<0.01), radiotherapy (P<0.001), chemotherapy (P<0.05) and tumor size (P<0.001). The ROC curve, c-index, calibration curve, and subgroup analyses of the training group and the validation group showed that the model had good predictive value. The nomogram for DLGGs predicted patients' 3-, 5- and 10-year survival rates based on these seven variables.

Conclusions

The nomogram constructed with common clinical characteristics has good prognostic value for patients with DLGGs and can help physicians make clinical decisions.

ATRX status in patients with gliomas: Radiomics analysis

MATERIAL AND METHODS

A cohort of 123 patients diagnosed with gliomas (World Health Organization grades II-IV) who underwent surgery and was treated at our center between January 2016 and July 2020, was enrolled in this retrospective study. Radiomics features were extracted from MR T1WI, T2WI, T2FLAIR, CE-T1WI, and ADC images. Patients were randomly split into training and validation sets at a ratio of 4:1. A radiomics signature was constructed using the least absolute shrinkage and selection operator (LASSO) to train the SVM model using the training set. The prediction accuracy and area under curve and other evaluation indexes were used to explore the performance of the model established in this study for predicting the ATRX mutation state.

RESULTS

Fifteen radiomic features were selected to generate an ATRX-associated radiomic signature using the LASSO logistic regression model. The area under curve for ATRX mutation (ATRX(-)) on training set was 0.93 (95% confidence interval [CI]: 0.87-1.0), with the sensitivity, specificity and accuracy being 0.91, 0.82 and 0.88, while on the validation set were 0.84 (95% CI: 0.63-0.91), with the sensitivity, specificity and accuracy of 0.73, 0.86, and 0.79, respectively.

CONCLUSIONS

These results indicate that radiomic features derived from preoperative MRI facilitat efficient prediction of ATRX status in gliomas, thus providing a novel evaluation method for noninvasive imaging biomarkers.

A Qualitative Signature to Identify TERT Promoter Mutant High-Risk Tumors in Low-Grade Gliomas

Background: Telomerase reverse transcriptase promoter (TERT-p) mutation has been frequently found, but associated with contrary prognosis, in both low-grade gliomas and glioblastomas. For the low-grade gliomas (Grades II-III), TERT-p mutant patients have a better prognosis than the wildtype patients, whereas for the GBMs (Grade IV), TERT-p mutation is related to a poor prognosis. We hypothesize that there exist high-risk patients in LGGs who share GBM-like molecular features, including TERT-p mutation, and need more intensive treatment than other LGGs. A molecular signature is needed to identify these high-risk patients for an accurate and timely treatment.

Methods: Using the within-sample relative expression orderings of gene pairs, we identified the gene pairs with significantly stable REOs, respectively, in both the TERT-p mutant LGGs and GBMs but with opposite directions in the two groups. These reversely stable gene pairs were used as the molecular signature to stratify the LGGs into high-risk and low-risk groups.

Results: A signature consisting of 21 gene pairs was developed, which can classify LGGs into two groups with significantly different overall survival. The high-risk group has a similar genetic mutation profile and a similar survival profile as GBMs, and these high-risk tumors may progress to a more malignant state.

Conclusion: The 21 gene-pair signature based on REOs is capable of identifying high-risk patients in LGGs and guiding the clinical choice for appropriate and timely intervention.

WHO Grade Loses Its Prognostic Value in Molecularly Defined Diffuse Lower-Grade Gliomas

BACKGROUND

While molecular insights to diffuse lower-grade glioma (dLGG) have improved the basis for prognostication, most established clinical prognostic factors come from the pre-molecular era. For instance, WHO grade as a predictor for survival in dLGG with isocitrate dehydrogenase (IDH) mutation has recently been questioned. We studied the prognostic role of WHO grade in molecularly defined subgroups and evaluated earlier used prognostic factors in the current molecular setting.

MATERIAL AND METHODS

A total of 253 adults with morphological dLGG, consecutively included between 2007 and 2018, were assessed. IDH mutations, codeletion of chromosomal arms 1p/19q, and cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) deletions were analyzed.

RESULTS

There was no survival benefit for patients with WHO grade 2 over grade 3 IDH-mut dLGG after exclusion of tumors with known CDKN2A/B homozygous deletion (n=157) (log-rank p=0.97). This was true also after stratification for oncological postoperative treatment and when astrocytomas and oligodendrogliomas were analyzed separately. In IDH-mut astrocytomas, residual tumor volume after surgery was an independent prognostic factor for survival (HR 1.02; 95% CI 1.01-1.03; p=0.003), but not in oligodendrogliomas (HR 1.02; 95% CI 1.00-1.03; p=0.15). Preoperative tumor size was an independent predictor in both astrocytomas (HR 1.03; 95% CI 1.00-1.05; p=0.02) and oligodendrogliomas (HR 1.05; 95% CI 1.01-1.09; p=0.01). Age was not a significant prognostic factor in multivariable analyses (astrocytomas p=0.64, oligodendrogliomas p=0.08).

CONCLUSION

Our findings suggest that WHO grade is not a robust prognostic factor in molecularly well-defined dLGG. Preoperative tumor size remained a prognostic factor in both IDH-mut astrocytomas and oligodendrogliomas in our cohort, whereas residual tumor volume predicted prognosis in IDH-mut astrocytomas only. The age cutoffs for determining high risk in patients with IDH-mut dLGG from the pre-molecular era are not supported by our results.

Comprehensive analysis of the LncRNAs, MiRNAs, and MRNAs acting within the competing endogenous RNA network of LGG

Messenger RNA (mRNA) and long noncoding RNA (lncRNA) targets interact via competitive microRNA (miRNA) binding. However, the roles of cancer-specific lncRNAs in the competing endogenous RNA (ceRNA) networks of low-grade glioma (LGG) remain unclear. This study obtained RNA sequencing data for normal solid tissue and LGG primary tumour tissue from The Cancer Genome Atlas database. We used a computational method to analyse the relationships among the mRNAs, lncRNAs, and miRNAs in these samples. Gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was used to predict the biological processes (BPs) and pathways associated with these genes. Kaplan-Meier survival analysis was used to evaluate the association between the expression levels of specific mRNAs, lncRNAs, and miRNAs and overall survival. Finally, we created a ceRNA network describing the relationships among these mRNAs, lncRNAs, and miRNAs using Cytoscape 3.5.1. A total of 2555 differentially expressed (DE) mRNAs, 218 DElncRNAs, and 192 DEmiRNAs were identified using R. In addition, GO and KEGG pathway analysis of the mRNAs and lncRNAs in the ceRNA network identified 10 BPs, 10 cell components, 10 molecular functions, and 48 KEGG pathways as selectively enriched. A total of 55 lncRNAs, 50 miRNAs, and 10 mRNAs from this network were shown to be closely associated with overall survival in LGG. Finally, 59 miRNAs, 235 mRNAs, and 17 lncRNAs were used to develop a ceRNA network comprising 313 nodes and 1046 edges. This study helps expand our understanding of ceRNA networks and serves to clarify the underlying pathogenesis mechanism of LGG.

Seizures in patients with IDH-mutated lower grade gliomas

PURPOSE

Most patients with Lower Grade Gliomas (LGG) present with epileptic seizures. Since the advent of molecular diagnostics, more homogenous sub-entities have emerged, including the isocitrate dehydrogenase-mutated (IDH-mutated) astrocytomas and 1p19q-codeleted oligodendrogliomas. We aimed to describe the occurrence of seizures in patients with molecularly defined LGG pre- and postoperatively and to analyze factors affecting seizure status postoperatively.

METHODS

A population-based cohort of 130 adult patients with IDH-mutated WHO grade 2 or 3 astrocytomas and oligodendrogliomas was assessed pertaining to seizure burden before and after surgery.

RESULTS

Fifty-four (79.4%) patients with astrocytoma and 45 (72.6%) patients with oligodendroglioma had a history of seizures before surgery. At 12 months postoperatively, 51/67 (76.1%) patients with astrocytoma and 47/62 (75.8%) patients with oligodendrogliomas were seizure free. In a multivariable logistic regression analysis, lower extent of resection (EOR) (OR 0.98; 95% CI 0.97-1.00, p = 0.01) and insular tumor location (OR 5.02; 95% CI 1.01-24.87, p = 0.048) were associated with presence of seizures within 1 year postoperatively in the entire LGG cohort. In sub-entities, EOR was in a similar manner associated with seizures postoperatively in astrocytomas (OR 0.98; 95% CI 0.96-0.99, p < 0.01) but not in oligodendrogliomas (p = 0.34).

CONCLUSION

Our results are well in line with data published for non-molecularly defined LGG with a large proportion of patients being seizure free at 1 year postoperative. Better seizure outcome was observed with increased EOR in astrocytomas, but this association was absent in oligodendrogliomas.

Deep Neural Network Analysis of Pathology Images With Integrated Molecular Data for Enhanced Glioma Classification and Grading

Gliomas are primary brain tumors that originate from glial cells. Classification and grading of these tumors is critical to prognosis and treatment planning. The current criteria for glioma classification in central nervous system (CNS) was introduced by World Health Organization (WHO) in 2016. This criteria for glioma classification requires the integration of histology with genomics. In 2017, the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT-NOW) was established to provide up-to-date recommendations for CNS tumor classification, which in turn the WHO is expected to adopt in its upcoming edition. In this work, we propose a novel glioma analytical method that, for the first time in the literature, integrates a cellularity feature derived from the digital analysis of brain histopathology images integrated with molecular features following the latest WHO criteria. We first propose a novel over-segmentation strategy for region-of-interest (ROI) selection in large histopathology whole slide images (WSIs). A Deep Neural Network (DNN)-based classification method then fuses molecular features with cellularity features to improve tumor classification performance. We evaluate the proposed method with 549 patient cases from The Cancer Genome Atlas (TCGA) dataset for evaluation. The cross validated classification accuracies are 93.81% for lower-grade glioma (LGG) and high-grade glioma (HGG) using a regular DNN, and 73.95% for LGG II and LGG III using a residual neural network (ResNet) DNN, respectively. Our experiments suggest that the type of deep learning has a significant impact on tumor subtype discrimination between LGG II vs. LGG III. These results outperform state-of-the-art methods in classifying LGG II vs. LGG III and offer competitive performance in distinguishing LGG vs. HGG in the literature. In addition, we also investigate molecular subtype classification using pathology images and cellularity information. Finally, for the first time in literature this work shows promise for cellularity quantification to predict brain tumor grading for LGGs with IDH mutations.

The Impact of an Ultra-Early Postoperative MRI on Treatment of Lower Grade Glioma

The timing of MRI imaging after surgical resection may have an important role in assessing the extent of resection (EoR) and in determining further treatment. The aim of our study was to evaluate the time dependency of T2 and FLAIR changes after surgery for LGG. The Log-Glio database of patients treated at our hospital from 2016 to 2021 was searched for patients >18a and non-enhancing intra-axial lesion with complete MR-imaging protocol. A total of 16 patients matched the inclusion criteria and were thus selected for volumetric analysis. All patients received an intraoperative scan (iMRI) after complete tumor removal, an ultra-early postoperative scan after skin closure, an early MRI within 48 h and a late follow up MRI after 3-4 mo. Detailed volumetric analysis of FLAIR and T2 abnormalities was conducted. Demographic data and basic characteristics were also analyzed. An ultra-early postoperative MRI was performed within a median time of 30 min after skin closure and showed significantly lower FLAIR (p = 0.003) and T2 (p = 0.003) abnormalities when compared to early postoperative MRI (median 23.5 h), though no significant difference was found between ultra-early and late postoperative FLAIR (p = 0.422) and T2 (p = 0.575) images. A significant difference was calculated between early and late postoperative FLAIR (p = 0.005) and T2 (p = 0.019) MRI scans. Additionally, we found no significant difference between intraoperative and ultra-early FLAIR/T2 (p = 0.919 and 0.499), but we found a significant difference between iMRI and early MRI FLAIR/T2 (p = 0.027 and p = 0.035). Therefore, a postoperative MRI performed 24 h or 48 h might lead to false positive findings. An MRI scan in the first hour after surgery (ultra-early) correlated best with residual tumor at 3 months follow up. An iMRI with open skull, at the end of resection, was similar to an ultra-early MRI with regard to residual tumor.

Gene Regulatory Network of ETS Domain Transcription Factors in Different Stages of Glioma

The ETS domain family of transcription factors is involved in a number of biological processes, and is commonly misregulated in various forms of cancer. Using microarray datasets from patients with different grades of glioma, we have analyzed the expression profiles of various ETS genes, and have identified ETV1, ELK3, ETV4, ELF4, and ETV6 as novel biomarkers for the identification of different glioma grades. We have further analyzed the gene regulatory networks of ETS transcription factors and compared them to previous microarray studies, where Elk-1-VP16 or PEA3-VP16 were overexpressed in neuroblastoma cell lines, and we identify unique and common regulatory networks for these ETS proteins.

FoundationOne CDx testing accurately determines whole arm 1p19q codeletion status in gliomas

BACKGROUND

Molecular profiling of gliomas is vital to ensure diagnostic accuracy, inform prognosis, and identify clinical trial options for primary and recurrent tumors. This study aimed to determine the accuracy of reporting the whole arm 1p19q codeletion status from the FoundationOne platform.

METHODS

Testing was performed on glioma samples as part of clinical care and analyzed up to 395 cancer-associated genes (including IDH1/2). The whole arm 1p19q codeletion status was predicted from the same assay using a custom research-use only algorithm, which was validated using 463 glioma samples with available fluorescence in-situ hybridization (FISH) data. For 519 patients with available outcomes data, progression-free and overall survival were assessed based on whole arm 1p19q codeletion status derived from sequencing data.

RESULTS

Concordance between 1p19q status based on FISH and our algorithm was 96.7% (449/463) with a positive predictive value (PPV) of 100% and a positive percent agreement (PPA) of 91.0%. All discordant samples were positive for codeletion by FISH and harbored genomic alterations inconsistent with oligodendrogliomas. Median overall survival was 168 months for the IDH1/2 mutant, codeleted group, and 122 months for IDH1/2 mutant-only (hazard ratio (HR): 0.42; P < .05).

CONCLUSIONS

1p19q codeletion status derived from FoundationOne testing is highly concordant with FISH results. Genomic profiling may be a reliable substitute for traditional FISH testing while also providing IDH1/2 status.

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.

Increased Expression of Sema3C Indicates a Poor Prognosis and Is Regulated by miR-142-5p in Glioma

Sema3C has been reported to promote glioma stem cells self-renewal and glioblastoma growth. However, the prognostic value and the regulatory mechanism for its abnormal expression in glioma remain poorly understood. In the current study, the immunohistochemistry results demonstrated that Sema3C was overexpressed in 169 of 216 (78.2%) interpretable glioma patients compared with 3 of 15 (20.0%) interpretable non-neoplastic brain cases (p = 0.0001). Sema3C overexpression was significantly associated with histologic type (p = 0.008), high Ki67 labeling index (p = 0.02), tumor grade (p = 0.002) and wild type IDH1 (p = 0.0001). Importantly, its overexpression predicts the shorter overall survival of glioma patients (p = 0.0017), especially the ones with high grade (p = 0.0124). Functionally, Sema3C silencing significantly reduced the proliferation and invasion of glioma cells, indicating an oncogenic role of Sema3C in glioma in vitro. To elucidate the reason accounting for its overexpression, it is identified miR-142-5p as a tumor suppressor that directly targets Sema3C in glioma cells. miR-142-5p and Sema3C were co-regulators of epithelial-mesenchymal transition. Clinically, miR-142-5p expression was conversely related with Sema3C expression in glioma samples. Together, we identified that Sema3C could promote the progression of glioma and its expression was negatively regulated by miR-142-5p in vitro. Thus, the miR-142-5p-Sema3C axis plays importantly in glioma and holds potential to be therapeutic targets as well.

OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma

Glioma is the most frequent primary brain tumor that causes high mortality and morbidity with poor prognosis. There are four grades of gliomas, I to IV, among which grade II and III are low-grade glioma (LGG). Although less aggressive, LGG almost universally progresses to high-grade glioma and eventual causes death if lacking of intervention. Current LGG treatment mainly depends on surgical resection followed by radiotherapy and chemotherapy, but the survival rates of LGG patients are low. Therefore, it is necessary to use prognostic biomarkers to classify patients into subgroups with different risks and guide clinical managements. Using gene expression profiling and long-term follow-up data, we established an Online consensus Survival analysis tool for LGG named OSlgg. OSlgg is comprised of 720 LGG cases from two independent cohorts. To evaluate the prognostic potency of genes, OSlgg employs the Kaplan-Meier plot with hazard ratio and p value to assess the prognostic significance of genes of interest. The reliability of OSlgg was verified by analyzing 86 previously published prognostic biomarkers of LGG. Using OSlgg, we discovered two novel potential prognostic biomarkers (CD302 and FABP5) of LGG, and patients with the elevated expression of either CD302 or FABP5 present the unfavorable survival outcome. These two genes may be novel risk predictors for LGG patients after further validation. OSlgg is public and free to the users at http://bioinfo.henu.edu.cn/LGG/LGGList.jsp.

Integrating Genomic Data with Transcriptomic Data for Improved Survival Prediction for Adult Diffuse Glioma

Background: Glioma is the most common type of primary central nervous system tumors. However, the relationship between gene mutations and transcriptome is unclear in diffuse glioma, and there are no systemic analyses with regard to the genotype-phenotype association currently.

Methods: We performed the multi-omics analysis in large glioblastoma multiforme (GBM, n=126) and low-grade glioma (LGG, n=481) cohorts obtained from The Cancer Genome Atlas (TCGA) database. We used multivariate linear models to evaluate associations between driver gene mutations and global gene expression. We developed generalized linear models to evaluate associations between genetic/expression factors with clinicopathologic features. Multivariate Cox proportional hazards models were used to predict the overall survival.

Results: The potential relationship between genotype and genetics, clinical as well as pathologic features, on diffused glioma was observed. At least one driver mutation correlated with expression changes of about 10% of genes in GBMs while about 80% of genes in LGGs. The strongest association between mutations and expression changes was observed for DRG2 and LRCC41 gene in GBMs and LGGs, respectively. Additionally, the association between genomics features and clinicopathologic features suggested the different underlying molecular mechanisms in molecular subtypes or histology subtypes. For predicting survival, among genetics, transcriptome and clinical variables, transcriptome features made the largest contribution. By combining all the available data, the accuracy in predicting the prognosis of diffuse glioma in patients was also improved.

Conclusion: Our study results revealed the influences of driver gene mutations on global gene expression in diffuse glioma patients. A more accurate model in predicting the prognosis of patients was achieved when combining with all the available data than just transcriptomic data.

Survival analysis of immune-related lncRNA in low-grade glioma

BACKGROUND

Low-grade glioma is grade I-II glioma. Immunotherapy is a promising way of tumor killing. Research on immune molecular mechanisms in low-grade gliomas and discovery of new immune checkpoints for low-grade gliomas are of great importance.

METHODS

Gene sequencing data and clinical data of low-grade glioma were downloaded from TCGA database. Prognosis related lncRNAs were identified by Cox regression and their possible functions were found by gene enrichment set analysis.

RESULTS

A total of 529 low-grade glioma samples and 5 non-tumor brain tissue samples are obtained from the TCGA database. Two hundred forty-seven immune-associated lncRNAs are screened. Cox regression showed that 16 immune-related lncRNAs are associated with low-grade glioma prognosis, and 7 lncRNAs are independent risk factors. Gene set enrichment analysis suggests that these molecules are enriched in extracellular region, sequence-specific DNA binding, neuropeptide signaling pathway, transcriptional misregulation in cancer, cytokine-cytokine receptor interaction, protein digestion and absorption, chemokine signaling pathway, etc. CONCLUSION: The identification of immune-related lncRNA may provide new targets for the research of the molecular mechanisms and treatment of low-grade glioma.

A Novel Assay for Profiling GBM Cancer Model Heterogeneity and Drug Screening

Accurate patient-derived models of cancer are needed for profiling the disease and for testing therapeutics. These models must not only be accurate, but also suitable for high-throughput screening and analysis. Here we compare two derivative cancer models, microtumors and spheroids, to the gold standard model of patient-derived orthotopic xenografts (PDX) in glioblastoma multiforme (GBM). To compare these models, we constructed a custom NanoString panel of 350 genes relevant to GBM biology. This custom assay includes 16 GBM-specific gene signatures including a novel GBM subtyping signature. We profiled 11 GBM-PDX with matched orthotopic cells, derived microtumors, and derived spheroids using the custom NanoString assay. In parallel, these derivative models underwent drug sensitivity screening. We found that expression of certain genes were dependent on the cancer model while others were model-independent. These model-independent genes can be used in profiling tumor-specific biology and in gauging therapeutic response. It remains to be seen whether or not cancer model-specific genes may be directly or indirectly, through changes to tumor microenvironment, manipulated to improve the concordance of in vitro derivative models with in vivo models yielding better prediction of therapeutic response.

A Multi-Cohort and Multi-Omics Meta-Analysis Framework to Identify Network-Based Gene Signatures

Although massive amounts of condition-specific molecular profiles are being accumulated in public repositories every day, meaningful interpretation of these data remains a major challenge. In an effort to identify the biomarkers that describe the key biological phenomena for a given condition, several approaches have been developed over the past few years. However, the majority of these approaches either (i) do not consider the known intermolecular interactions, or (ii) do not integrate molecular data of multiple types (e.g., genomics, transcriptomics, proteomics, epigenomics, etc.), and thus potentially fail to capture the true biological changes responsible for complex diseases (e.g., cancer). In addition, these approaches often ignore the heterogeneity and study bias present in independent molecular cohorts. In this manuscript, we propose a novel multi-cohort and multi-omics meta-analysis framework that overcomes all three limitations mentioned above in order to identify robust molecular subnetworks that capture the key dynamic nature of a given biological condition. Our framework integrates multiple independent gene expression studies, unmatched DNA methylation studies, and protein-protein interactions to identify methylation-driven subnetworks. We demonstrate the proposed framework by constructing subnetworks related to two complex diseases: glioblastoma and low-grade gliomas. We validate the identified subnetworks by showing their ability to predict patients' clinical outcome on multiple independent validation cohorts.

Withdrawal of antiepileptic drugs in patients with low grade and anaplastic glioma after long-term seizure freedom: a prospective observational study

Background

When glioma patients experience long-term seizure freedom the question arises whether antiepileptic drugs (AEDs) should be continued. As no prospective studies exist on seizure recurrence in glioma patients after AED withdrawal, we evaluated the decision-making process to withdraw AEDs in glioma patients, and seizure outcome after withdrawal.

Methods

Patients with a histologically confirmed low grade or anaplastic glioma were included. Eligible patients were seizure free ≥ 1 year from the date of last antitumor treatment, or ≥ 2 years since the last seizure when seizures occurred after the end of the last antitumor treatment. Patients and neuro-oncologists made a shared decision on the preferred AED treatment (i.e. AED withdrawal or continuation). Primary outcomes were: (1) outcome of the shared decision-making process and (2) rate of seizure recurrence.

Results

Eighty-three patients fulfilled all eligibility criteria. However, in 12/83 (14%) patients, the neuro-oncologist had serious objections to AED withdrawal. Therefore, 71/83 (86%) patients were analyzed; In 46/71 (65%) patients it was decided to withdraw AED treatment. In the withdrawal group, 26% (12/46) had seizure recurrence during follow-up. Seven of these 12 patients (58%) had tumor progression, of which three within 3 months after seizure recurrence. In the AED continuation group, 8% (2/25) of patients had seizure recurrence of which one had tumor progression.

Conclusion

In 65% of patients a shared decision was made to withdraw AEDs, of which 26% had seizure recurrence. AED withdrawal should only be considered in carefully selected patients with a presumed low risk of tumor progression.

Noninvasive Prediction of IDH1 Mutation and ATRX Expression Loss in Low-Grade Gliomas Using Multiparametric MR Radiomic Features

BACKGROUND

Noninvasive detection of isocitrate dehydrogenase 1 mutation (IDH1(+)) and loss of nuclear alpha thalassemia/mental retardation syndrome X-linked expression ((ATRX(-)) are clinically meaningful for molecular stratification of low-grade gliomas (LGGs).

PURPOSE

To study a radiomic approach based on multiparametric MR for noninvasively determining molecular status of IDH1(+) and ATRX(-) in patients with LGG.

STUDY TYPE

Retrospective, radiomics.

POPULATION

Fifty-seven LGG patients with IDH1(+) (n = 36 with 19 ATRX(-) and 17 ATRX(+) patients) and IDH1(-) (n = 21).

FIELD STRENGTH/SEQUENCE

3.0T MRI / 3D arterial spin labeling (3D-ASL), T₂ /fluid-attenuated inversion recovery (T₂ FLAIR), and diffusion-weighted imaging (DWI).

ASSESSMENT

In all, 265 high-throughput radiomic features were extracted on each tumor volume of interest from T₂ FLAIR and the other three parametric maps of ASL-derived cerebral blood flow (CBF), DWI-derived apparent diffusion coefficient (ADC), and exponential ADC (eADC). Optimal feature subsets were selected as using the support vector machine with a recursive feature elimination algorithm (SVM-RFE). Receiver operating characteristic curve (ROC) analysis was employed to assess the efficiency for identifying the IDH1(+) and ATRX(-) status.

STATISTICAL TESTS

Student's t-test, chi-square test, and Fisher's exact test were applied to confirm whether intergroup significant differences exist between molecular subtypes decided by IDH1 and ATRX.

RESULTS

Optimal SVM predictive models of IDH1(+) and ATRX(-) were established using 28 features from T₂ Flair, ADC, eADC, and CBF and six features from T₂ Flair, ADC, and CBF. The accuracies/AUCs/sensitivity/specifity/PPV/NPV of predicting IDH1(+) in LGG were 94.74%/0.931/100%/85.71%/92.31%/100%, and those of predicting ATRX(-) in LGG with IDH1(+) were 91.67%/0.926/94.74%/88.24%/90.00%/93.75%, respectively.

DATA CONCLUSION

Using the optimal texture features extracted from multiple MR sequences or parametric maps, a promising stratifying strategy was acquired for predicting molecular subtypes of IDH1 and ATRX in LGGs.

LEVEL OF EVIDENCE

3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;49:808-817.

NLRP3 in human glioma is correlated with increased WHO grade, and regulates cellular proliferation, apoptosis and metastasis via epithelial-mesenchymal transition and the PTEN/AKT signaling pathway

Glioma is the most prevalent and fatal primary tumor of the central nervous system in adults, while the development of effective therapeutic strategies in clinical practice remain a challenge. Nucleotide-binding domain leucine-rich family pyrin-containing 3 (NLRP3) has been reported to be associated with tumorigenesis and progression; however, its expression and function in human glioma remain unclear. The present study was designed to explore the biological role and potential mechanism of NLRP3 in human glioma. The results demonstrated that overexpression of NLRP3, apoptosis-associated speck-like protein containing a caspase-recruitment domain (ASC), caspase-1 and interleukin (IL)-1β protein in human glioma tissues were significantly correlated with higher World Health Organization grades. The in vitro biological experiments demonstrated that NLRP3 downregulation significantly inhibited the proliferation, migration and invasion, and promoted the apoptosis of SHG44 and A172 glioma cell lines. Furthermore, western blot assays revealed that the downregulation of NLRP3 significantly reduced the expression of ASC, caspase-1 and IL-1β protein. Furthermore, NLRP3 knockdown caused the inhibition of epithelial-mesenchymal transition (EMT), and inhibited the phosphorylation of AKT serine/threonine kinase (AKT) and phosphorylation of phosphatase and tensin homolog (PTEN). Consistently, the upregulation of NLRP3 significantly increased the expression of ASC, caspase-1, IL-1β and phosphorylated-PTEN, promoted proliferation, migration, invasion and EMT, inhibited apoptosis, and activated the AKT signaling pathway. The data of the present study indicate that NLRP3 affects human glioma progression and metastasis through multiple pathways, including EMT and PTEN/AKT signaling pathway regulation, enhanced inflammasome activation, and undefined inflammasome-independent mechanisms. Understanding the biological effects of NLRP3 in human glioma and the underlying mechanisms may offer novel insights for the development of glioma clinical therapeutic strategies.

Mutant ATRX: uncovering a new therapeutic target for glioma

INTRODUCTION

ATRX is a chromatin remodeling protein whose main function is the deposition of the histone variant H3.3. ATRX mutations are widely distributed in glioma, and correlate with alternative lengthening of telomeres (ALT) development, but they also affect other cellular functions related to epigenetic regulation. Areas covered: We discuss the main molecular characteristics of ATRX, from its various functions in normal development to the effects of its loss in ATRX syndrome patients and animal models. We focus on the salient consequences of ATRX mutations in cancer, from a clinical to a molecular point of view, focusing on both adult and pediatric glioma. Finally, we will discuss the therapeutic opportunities future research perspectives. Expert opinion: ATRX is a major component of various essential cellular pathways, exceeding its functions as a histone chaperone (e.g. DNA replication and repair, chromatin higher-order structure regulation, gene transcriptional regulation, etc.). However, it is unclear how the loss of these functions in ATRX-null cancer cells affects cancer development and progression. We anticipate new treatments and clinical approaches will emerge for glioma and other cancer types as mechanistic and molecular studies on ATRX are only just beginning to reveal the many critical functions of this protein in cancer.

Ki-67 proliferation index but not mitotic thresholds integrates the molecular prognostic stratification of lower grade gliomas

Despite several molecular signatures for “lower grade diffuse gliomas” (LGG) have been identified, WHO grade still remains a cornerstone of treatment guidelines. Mitotic count bears a crucial role in its definition, although limited by the poor reproducibility of standard Hematoxylin & Eosin (H&E) evaluation. Phospho-histone-H3 (PHH3) and Ki-67 have been proposed as alternative assays of cellular proliferation. Therefore in the present series of 141 LGG, the molecular characterization (namely IDH status, 1p/19q co-deletion and MGMT promoter methylation) was integrated with the tumor “proliferative trait” (conventional H&E or PHH3-guided mitotic count and Ki-67 index) in term of prognosis definition. Exclusively high PHH3 and Ki-67 values were predictor of poor prognosis (log rank test, P = 0.0281 for PHH3 and P = 0.032 for Ki-67), unlike standard mitotic count. Based on Cox proportional hazard regression analyses, among all clinical (age), pathological (PHH3 and Ki-67) and molecular variables (IDH, 1p/19q codeletion and MGMT methylation) with a prognostic relevance at univariate survival analysis, only IDH expression (P = 0.001) and Ki-67 proliferation index (P = 0.027) proved to be independent prognostic factors. In addition, stratifying by IDH expression status, high Ki-67 retained its prognostic relevance uniquely in the IDH negative patient (P = 0.029) doubling their risk of death (hazard ratio = 2.27). Overall, PHH3 immunostaining is the sole reliable method with a prognostic value to highlight mitotic figures in LGG. Ki-67 proliferation index exceeds PHH3 mitotic count as a predictor of patient's prognosis, and should be integrated with molecular markers in a comprehensive grading system for LGG.

Salvage stereotactic radiosurgery for recurrent gliomas with prior radiation therapy

This study aims to assess the viability of salvage stereotactic radiosurgery (SRS) for recurrent malignant gliomas through assessing overall survival, local control and toxicity. We performed a retrospective review of 65 patients with 76 lesions (55 high-grade, 21 low-grade) treated with salvage SRS between 2002 and   2012. Median follow-up from salvage SRS was 14.9 months (IQR: 0.9-28.1), 8.3 months (IQR: 4.0-13.3) and 8.5 months (IQR: 3.9-15.8) for low-grade, high-grade, and combined, respectively. A 12-month overall survival from salvage SRS was 68.4, 38.7 and 47.3% for low-grade, high-grade and combined respectively. A total of 6-month local control was 86.2, 53.8 and 65.3% for low-grade, high-grade and combined, respectively. Our results indicate salvage SRS can provide acceptable survival and local control with minimal toxicity.

Personalized anticancer therapy selection using molecular landscape topology and thermodynamics

Personalized anticancer therapy requires continuous consolidation of emerging bioinformatics data into meaningful and accurate information streams. The use of novel mathematical and physical approaches, namely topology and thermodynamics can enable merging differing data types for improved accuracy in selecting therapeutic targets. We describe a method that uses chemical thermodynamics and two topology measures to link RNA-seq data from individual patients with academically curated protein-protein interaction networks to select clinically relevant targets for treatment of low-grade glioma (LGG). We show that while these three histologically distinct tumor types (astrocytoma, oligoastrocytoma, and oligodendroglioma) may share potential therapeutic targets, the majority of patients would benefit from more individualized therapies. The method involves computing Gibbs free energy of the protein-protein interaction network and applying a topological filtration on the energy landscape to produce a subnetwork known as persistent homology. We then determine the most likely best target for therapeutic intervention using a topological measure of the network known as Betti number. We describe the algorithm and discuss its application to several patients.

Primary Glial and Neuronal Tumors of the Ovary or Peritoneum: A Clinicopathologic Study of 11 Cases

Primary glial and neuronal tumors of the ovary or peritoneum are rare neuroectodermal-type tumors similar to their counterparts in the central nervous system. We retrospectively reviewed 11 cases. These cases included 4 ependymomas, 6 astrocytic tumors, and 1 neurocytoma. Patients' age ranged from 9 to 50 years (mean, 26 y; median, 24 y). All ependymal tumors with detailed clinical history (n=3) were not associated with any other ovarian neoplasm. In contrast, all astrocytic tumors were associated with immature teratoma (n=4), mature cystic teratoma (n=1), or mixed germ cell tumor (n=1). The neurocytoma arose in association with mature teratomatous components in a patient with a history of treated mixed germ cell tumor. Immunohistochemical staining showed that 7 of 7 ependymal and astrocytic tumors (100%) were positive for glial fibrillary acidic protein, and 2 of 2 ependymomas (100%) were positive for both estrogen and progesterone receptors. The neurocytoma was positive for synaptophysin and negative for S100 protein, glial fibrillary acidic protein, and SALL4. No IDH1-R132H mutation was detected in 2 of 2 (0%) astrocytomas by immunohistochemistry. Next-generation sequencing was performed on additional 2 ependymomas and 2 astrocytomas but detected no mutations in a panel of 50 genes that included IDH1, IDH2, TP53, PIK3CA, EGFR, BRAF, and PTEN. Follow-up information was available for 8 patients, with the follow-up period ranging from 4 to 59 months (mean, 15 mo; median, 8.5 mo), of which 3 had no evidence of disease and 5 were alive with disease. In conclusion, primary glial and neuronal tumors of the ovary can arise independently or in association with other ovarian germ cell tumor components. Pathologists should be aware of these rare tumors and differentiate them from other ovarian neoplasms. Even though an IDH1 or IDH2 mutation is found in the majority of WHO grade II and III astrocytomas, and in secondary glioblastomas arising from them, such mutations were not identified in our series, suggesting that these tumors are molecularly different from their central nervous system counterparts despite their morphologic and immunophenotypic similarities.

Clinical and Radiologic Outcomes in Adults and Children Treated with Pencil-Beam Scanning Proton Therapy for Low-Grade Glioma

PURPOSE

We assessed clinical and radiologic outcomes in adults and children with low-grade glioma (LGG) of the brain treated with pencil-beam scanning (PBS) proton therapy (PT).

MATERIALS AND METHODS

Between 1997 and 2014, 28 patients were treated with PBS PT, 20 (71%) of whom were younger than 18 years. Median age at start of PT was 12.3 years (range, 2.2-53.0 years). Nine patients (32%) underwent at least a subtotal resection; 12 (43%) underwent biopsy; and 7 (25%) were diagnosed radiographically. Twelve patients (43%) had grade II and 9 (32%) had grade I gliomas. Eleven patients (39%) received chemotherapy before PT. A median dose of 54 Gy (relative biologic effectiveness) was administered. Radiologic response to PT was determined using the Response Evaluation Criteria in Solid Tumors (RECIST). Eight domains of quality of life (QoL) for 16 pediatric patients were assessed prospectively by patients' parents using the pediatric QoL proxy questionnaire. Progression-free survival and overall survival (OS) were estimated by the Kaplan-Meier method. Median follow-up was 42.1 months for living patients.

RESULTS

Ten patients (36%) developed local, clinical failure. Three patients (11%) died, all of tumor progression. Radiographic tumor response by RECIST was evaluable in 11 patients: 9 (82%) with stable disease, 1 (9%) with partial response, and 1 (9%) with complete response to PT. Three-year OS and progression-free survival were 83.4% and 56.0%, respectively. No ≥ grade III acute toxicities were observed. Grade III, late radiation necrosis developed in 1 patient (4%). No appreciable change in pediatric QoL proxy scores in children was noted in any of the 8 domains at any time point.

CONCLUSION

Treatment with PBS PT is effective for LGG, with minimal acute toxicity and, in children, no appreciable decline in QoL. More patients and longer follow-up are needed to determine the long-term efficacy and toxicity of PT for LGG.

Adult infiltrating gliomas with WHO 2016 integrated diagnosis: additional prognostic roles of ATRX and TERT

The "integrated diagnosis" for infiltrating gliomas in the 2016 revised World Health Organization (WHO) classification of tumors of the central nervous system requires assessment of the tumor for IDH mutations and 1p/19q codeletion. Since TERT promoter mutations and ATRX alterations have been shown to be associated with prognosis, we analyzed whether these tumor markers provide additional prognostic information within each of the five WHO 2016 categories. We used data for 1206 patients from the UCSF Adult Glioma Study, the Mayo Clinic and The Cancer Genome Atlas (TCGA) with infiltrative glioma, grades II-IV for whom tumor status for IDH, 1p/19q codeletion, ATRX, and TERT had been determined. All cases were assigned to one of 5 groups following the WHO 2016 diagnostic criteria based on their morphologic features, and IDH and 1p/19q codeletion status. These groups are: (1) Oligodendroglioma, IDH-mutant and 1p/19q-codeleted; (2) Astrocytoma, IDH-mutant; (3) Glioblastoma, IDH-mutant; (4) Glioblastoma, IDH-wildtype; and (5) Astrocytoma, IDH-wildtype. Within each group, we used univariate and multivariate Cox proportional hazards models to assess associations of overall survival with patient age at diagnosis, grade, and ATRX alteration status and/or TERT promoter mutation status. Among Group 1 IDH-mutant 1p/19q-codeleted oligodendrogliomas, the TERT-WT group had significantly worse overall survival than the TERT-MUT group (HR: 2.72, 95% CI 1.05-7.04, p = 0.04). In both Group 2, IDH-mutant astrocytomas and Group 3, IDH-mutant glioblastomas, neither TERT mutations nor ATRX alterations were significantly associated with survival. Among Group 4, IDH-wildtype glioblastomas, ATRX alterations were associated with favorable outcomes (HR: 0.36, 95% CI 0.17-0.81, p = 0.01). Among Group 5, IDH-wildtype astrocytomas, the TERT-WT group had significantly better overall survival than the TERT-MUT group (HR: 0.48, 95% CI 0.27-0.87), p = 0.02). Thus, we present evidence that in certain WHO 2016 diagnostic groups, testing for TERT promoter mutations or ATRX alterations may provide additional useful prognostic information.

Molecular Testing of Brain Tumor

The World Health Organization (WHO) classification of central nervous system (CNS) tumors was revised in 2016 with a basis on the integrated diagnosis of molecular genetics. We herein provide the guidelines for using molecular genetic tests in routine pathological practice for an accurate diagnosis and appropriate management. While astrocytomas and IDH-mutant (secondary) glioblastomas are characterized by the mutational status of IDH, TP53, and ATRX, oligodendrogliomas have a 1p/19q codeletion and mutations in IDH, CIC, FUBP1, and the promoter region of telomerase reverse transcriptase (TERTp). IDH-wildtype (primary) glioblastomas typically lack mutations in IDH, but are characterized by copy number variations of EGFR, PTEN, CDKN2A/B, PDGFRA, and NF1 as well as mutations of TERTp. High-grade pediatric gliomas differ from those of adult gliomas, consisting of mutations in H3F3A, ATRX, and DAXX, but not in IDH genes. In contrast, well-circumscribed low-grade neuroepithelial tumors in children, such as pilocytic astrocytoma, pleomorphic xanthoastrocytoma, and ganglioglioma, often have mutations or activating rearrangements in the BRAF, FGFR1, and MYB genes. Other CNS tumors, such as ependymomas, neuronal and glioneuronal tumors, embryonal tumors, meningothelial, and other mesenchymal tumors have important genetic alterations, many of which are diagnostic, prognostic, and predictive markers and therapeutic targets. Therefore, the neuropathological evaluation of brain tumors is increasingly dependent on molecular genetic tests for proper classification, prediction of biological behavior and patient management. Identifying these gene abnormalities requires cost-effective and high-throughput testing, such as next-generation sequencing. Overall, this paper reviews the global guidelines and diagnostic algorithms for molecular genetic testing of brain tumors.

IDH mutant and 1p/19q co-deleted oligodendrogliomas: tumor grade stratification using diffusion-, susceptibility-, and perfusion-weighted MRI

Purpose

Currently, isocitrate dehydrogenase (IDH) mutation and 1p/19q co-deletion are proven diagnostic biomarkers for both grade II and III oligodendrogliomas (ODs). Non-invasive diffusion-weighted imaging (DWI), susceptibility-weighted imaging (SWI), and dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) are widely used to provide physiological information (cellularity, hemorrhage, calcifications, and angiogenesis) of neoplastic histology and tumor grade. However, it is unclear whether DWI, SWI, and DSC-PWI are able to stratify grades of IDH-mutant and 1p/19q co-deleted ODs.

Methods

We retrospectively reviewed the conventional MRI (cMRI), DWI, SWI, and DSC-PWI obtained on 33 patients with IDH-mutated and 1p/19q co-deleted ODs. Features of cMRI, normalized ADC (nADC), intratumoral susceptibility signals (ITSSs), normalized maxim CBV (nCBV), and normalized maximum CBF (nCBF) were compared between low-grade ODs (LGOs) and high-grade ODs (HGOs). Receiver operating characteristic curve and logistic regression were applied to determine diagnostic performances.

Results

HGOs tended to present with prominent edema and enhancement. nADC, ITSSs, nCBV, and nCBF were significantly different between groups (all P < 0.05). The combination of SWI and DSC-PWI for grading resulted in sensitivity and specificity of 100.00 and 93.33%, respectively.

Conclusions

IDH-mutant and 1p/19q co-deleted ODs can be stratified by grades using cMRI and advanced magnetic resonance imaging techniques including DWI, SWI, and DSC-PWI. Combined ITSSs with nCBV appear to be a promising option for grading molecularly defined ODs in clinical practice.

ATRX and DAXX: Mechanisms and Mutations

Recent genome sequencing efforts in a variety of cancers have revealed mutations and/or structural alterations in ATRX and DAXX, which together encode a complex that deposits histone variant H3.3 into repetitive heterochromatin. These regions include retrotransposons, pericentric heterochromatin, and telomeres, the latter of which show deregulation in ATRX/DAXX-mutant tumors. Interestingly, ATRX and DAXX mutations are often found in pediatric tumors, suggesting a particular developmental context in which these mutations drive disease. Here we review the functions of ATRX and DAXX in chromatin regulation as well as their potential contributions to tumorigenesis. We place emphasis on the chromatin remodeler ATRX, which is mutated in the developmental disorder for which it is named, α-thalassemia, mental retardation, X-linked syndrome, and at high frequency in a number of adult and pediatric tumors.

'Low grade glioma': an update for radiologists

With the recent publication of a new World Health Organization brain tumour classification that reflects increased understanding of glioma tumour genetics, there is a need for radiologists to understand the changes and their implications for patient management. There has also been an increasing trend for adopting earlier, more aggressive surgical approaches to low-grade glioma (LGG) treatment. We will summarize these changes, give some context to the increased role of tumour genetics and discuss the associated implications of their adoption for radiologists. We will discuss the earlier and more radical surgical resection of LGG and what it means for patients undergoing imaging.

DNA methylation in adult diffuse gliomas

Adult diffuse gliomas account for the majority of primary malignant brain tumours, and are in most cases lethal. Current therapies are often only marginally effective, and improved options will almost certainly benefit from further insight into the various processes contributing to gliomagenesis and pathology. While molecular characterization of these tumours classifies them on the basis of genetic alterations and chromosomal abnormalities, DNA methylation patterns are increasingly understood to play a role in glioma pathogenesis. Indeed, a subset of gliomas associated with improved survival is characterized by the glioma CpG island methylator phenotype (G-CIMP), which can be induced by the expression of mutant isocitrate dehydrogenase (IDH1/2). Aberrant methylation of particular genes or regulatory elements, within the context of G-CIMP-positive and/or negative tumours, has also been shown to be associated with differential survival. In this review, we provide an overview of the current knowledge regarding the role of DNA methylation in adult diffuse gliomas. In particular, we discuss IDH mutations and G-CIMP, MGMT promoter methylation, DNA methylation-mediated microRNA regulation and aberrant methylation of specific genes or groups of genes.

Current Management of Adult Diffuse Infiltrative Low Grade Gliomas

Diffuse infiltrative low grade gliomas (LGG) account for approximately 15 % of all gliomas. The prognosis of LGG differs between high-risk and low-risk patients notwithstanding varying definitions of what constitutes a high-risk patient. Maximal safe resection optimally is the initial treatment. Surgery that achieves a large volume resection improves both progression-free and overall survival. Based on results of three randomized clinical trials (RCT), radiotherapy (RT) may be deferred in patients with low-risk LGG (defined as age <40 years and having undergone a complete resection), although combined chemoradiotherapy has never been prospectively evaluated in the low-risk population. The recent RTOG 9802 RCT established a new standard of care in high-risk patients (defined as age >40 years or incomplete resection) by demonstrating a nearly twofold improvement in overall survival with the addition of PCV (procarbazine, CCNU, vincristine) chemotherapy following RT as compared to RT alone. Chemotherapy alone as a treatment of LGG may result in less toxicity than RT; however, this has only been prospectively studied once (EORTC 22033) in high-risk patients. A challenge remains to define when an aggressive treatment improves survival without impacting quality of life (QoL) or neurocognitive function and when an effective treatment can be delayed in order to preserve QoL without impacting survival. Current WHO histopathological classification is poorly predictive of outcome in patients with LGG. The integration of molecular biomarkers with histology will lead to an improved classification that more accurately reflects underlying tumor biology, prognosis, and hopefully best therapy.

Genetic Classification of Gliomas: Refining Histopathology

Newly published studies validate prior reports that specific combinations of genetic alternations in IDH1/2, ATRX, TERT, TP53, and co-deletion of 1p/19q have the ability to reclassify gliomas into rational subsets, defining a glioma's biological and clinical behavior more accurately than stratifications based solely on histopathology.