Codeletion of 1p and 19q determines distinct gene methylation and expression profiles in IDH-mutated oligodendroglial tumors

Systemic and local immunosuppression in glioblastoma and its prognostic significance

The effectiveness of tumor therapy, especially immunotherapy and oncolytic virotherapy, critically depends on the activity of the host immune cells. However, various local and systemic mechanisms of immunosuppression operate in cancer patients. Tumor-associated immunosuppression involves deregulation of many components of immunity, including a decrease in the number of T lymphocytes (lymphopenia), an increase in the levels or ratios of circulating and tumor-infiltrating immunosuppressive subsets [e.g., macrophages, microglia, myeloid-derived suppressor cells (MDSCs), and regulatory T cells (Tregs)], as well as defective functions of subsets of antigen-presenting, helper and effector immune cell due to altered expression of various soluble and membrane proteins (receptors, costimulatory molecules, and cytokines). In this review, we specifically focus on data from patients with glioblastoma/glioma before standard chemoradiotherapy. We discuss glioblastoma-related immunosuppression at baseline and the prognostic significance of different subsets of circulating and tumor-infiltrating immune cells (lymphocytes, CD4+ and CD8+ T cells, Tregs, natural killer (NK) cells, neutrophils, macrophages, MDSCs, and dendritic cells), including neutrophil-to-lymphocyte ratio (NLR), focus on the immune landscape and prognostic significance of isocitrate dehydrogenase (IDH)-mutant gliomas, proneural, classical and mesenchymal molecular subtypes, and highlight the features of immune surveillance in the brain. All attempts to identify a reliable prognostic immune marker in glioblastoma tissue have led to contradictory results, which can be explained, among other things, by the unprecedented level of spatial heterogeneity of the immune infiltrate and the significant phenotypic diversity and (dys)functional states of immune subpopulations. High NLR is one of the most repeatedly confirmed independent prognostic factors for shorter overall survival in patients with glioblastoma and carcinoma, and its combination with other markers of the immune response or systemic inflammation significantly improves the accuracy of prediction; however, more prospective studies are needed to confirm the prognostic/predictive power of NLR. We call for the inclusion of dynamic assessment of NLR and other blood inflammatory markers (e.g., absolute/total lymphocyte count, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, systemic immune-inflammation index, and systemic immune response index) in all neuro-oncology studies for rigorous evaluation and comparison of their individual and combinatorial prognostic/predictive significance and relative superiority.

Considerations for modelling diffuse high-grade gliomas and developing clinically relevant therapies

Diffuse high-grade gliomas contain some of the most dangerous human cancers that lack curative treatment options. The recent molecular stratification of gliomas by the World Health Organisation in 2021 is expected to improve outcomes for patients in neuro-oncology through the development of treatments targeted to specific tumour types. Despite this promise, research is hindered by the lack of preclinical modelling platforms capable of recapitulating the heterogeneity and cellular phenotypes of tumours residing in their native human brain microenvironment. The microenvironment provides cues to subsets of glioma cells that influence proliferation, survival, and gene expression, thus altering susceptibility to therapeutic intervention. As such, conventional in vitro cellular models poorly reflect the varied responses to chemotherapy and radiotherapy seen in these diverse cellular states that differ in transcriptional profile and differentiation status. In an effort to improve the relevance of traditional modelling platforms, recent attention has focused on human pluripotent stem cell-based and tissue engineering techniques, such as three-dimensional (3D) bioprinting and microfluidic devices. The proper application of these exciting new technologies with consideration of tumour heterogeneity and microenvironmental interactions holds potential to develop more applicable models and clinically relevant therapies. In doing so, we will have a better chance of translating preclinical research findings to patient populations, thereby addressing the current derisory oncology clinical trial success rate.

Stromal protein CCN family contributes to the poor prognosis in lower-grade gioma by modulating immunity, matrix, stemness, and metabolism

Background: The CCN family of stromal proteins is involved in the regulation of many important biological functions. However, the role of dysregulated CCN proteins in lower-grade glioma (LGG) remain less understand. Methods: The clinical significance of the CCN proteins was explored based on RNA-seq profiles from multiple cohorts. A CCNScore was constructed using LASSO regression analysis. The PanCanAtlas data and MEXPRESS database were employed to elucidate molecular underpinnings. Results: The expression of CCN4 was associated with poor prognosis in LGG. The CCNScore (CCN1 = 0.06, CCN4 = 0.86) showed implication in prognosis prediction, subtype assessment and therapy selection. The gene mutation pattern of the high-CCNScore group was similar with glioblastoma, including EGFR, PTEN, and NF1 mutation frequently. Besides, the high-CCNScore group was comprised of samples mainly classic-like and mesenchymal-like, had lower methylation levels, higher stemness, higher inflammation, higher levels of extracellular matrix remodel and dysfunction of metabolic pathways. On the other hand, the low-CCNScore group consisted mainly of IDH-mutation LGG, and was characterized by TP53, CIC, and ATRX gene mutations, hyper-methylation status, lower stemness, lower proliferation, immune quietness and low extracellular matrix stiffness. Conclusion: In summary, these results outlined the role of CCN family in LGG and provided a potential and promising therapeutic target.

The sinuous, wave-like intratumoral-wall sign is a sensitive and specific radiological biomarker for oligodendrogliomas

OBJECTIVES

The purpose of this study was to investigate the clinical utility of the sinuous, wave-like intratumoral-wall (SWITW) sign on T2WI in diagnosing isocitrate dehydrogenase (IDH) mutant and 1p/19q codeleted (IDHmut-Codel) oligodendrogliomas, for which a relatively conservative resection strategy might be sufficient due to a better response to chemoradiotherapy and favorable prognosis.

METHODS

Imaging data from consecutive adult patients with diffuse lower-grade gliomas (LGGs, histological grades 2-3) in Beijing Tiantan Hospital (December 1, 2013, to October 31, 2021, BTH set, n = 711) and the Cancer Imaging Archive (TCIA) LGGs set (n = 117) were used to develop and validate our findings. Two independent observers assessed the SWITW sign and some well-reported discriminative radiological features to establish a practical diagnostic strategy.

RESULTS

The SWITW sign showed satisfying sensitivity (0.684 and 0.722 for BTH and TCIA sets) and specificity (0.938 and 0.914 for BTH and TCIA sets) in defining IDHmut-Codels, and the interobserver agreement was substantial (κ 0.718 and 0.756 for BTH and TCIA sets). Compared to calcification, the SWITW sign improved the sensitivity by 0.28 (0.404 to 0.684) in the BTH set, and 81.0% (277/342) of IDHmut-Codel cases demonstrated SWITW and/ or calcification positivity. Combining the SWITW sign, calcification, low ADC values, and other discriminative features, we established a concise and reliable diagnostic protocol for IDHmut-Codels.

CONCLUSIONS

The SWITW sign was a sensitive and specific imaging biomarker for IDHmut-Codels. The integrated protocol provided an explicable, efficient, and reproducible method for precise preoperative diagnosis, which was essential to guide individualized surgical plan-making.

KEY POINTS

• The SWITW sign was a sensitive and specific imaging biomarker for IDHmut-Codel oligodendrogliomas. • The SWITW sign was more sensitive than calcification and an integrated strategy could improve diagnostic sensitivity for IDHmut-Codel oligodendrogliomas. • Combining SWITW, calcification, low ADC values, and other discriminative features could make a precise preoperative diagnosis for IDHmut-Codel oligodendrogliomas.

CIMP-positive glioma is associated with better prognosis: A systematic analysis

BACKGROUND

CpG island methylator phenotype (CIMP) was closely related to the degree of pathological differentiation of tumors, and it's an important determinant of glioma pathogenicity. However, the molecular and pathological features of CIMP-positive glioma have not been fully elucidated. In addition, CIMP have been reported to be a useful prognostic marker in several human cancers, yet its prognostic value in gliomas is still controversial. Therefore, we aimed to evaluate gene mutations and pathological features of CIMP-positive glioma and explore the prognostic value of CIMP in gliomas.

METHODS

We comprehensively searched PubMed, Embase, and MEDLINE for studies describing gene mutations, pathological features and overall survival of gliomas stratified by CIMP status. Odds ratios (OR), hazard ratios (HR), and their 95% confidence intervals (CI) were used to estimate the correlation between CIMP and the outcome parameters.

RESULTS

Twelve studies with 2386 gliomas (1051 CIMP-positive and 1335 CIMP-negative) were included. Our results showed that CIMP was more frequent in isocitrate dehydrogenase 1 (IDH1)-mutated gliomas (OR 229.07; 95% CI 138.72-378.26) and 1p19q loss of heterozygosis (LOH) gliomas (OR 5.65; 95% CI 2.66-12.01). Pathological analysis showed that CIMP was common in low-malignant oligodendroglioma (OR 5.51; 95% CI 3.95-7.70) with molecular features including IDH1 mutations and 1p19q LOH, but rare in glioblastoma (OR 0.14; 95% CI 0.10-0.19). However, CIMP showed no obvious correlation with anaplastic oligoastrocytomas (OR 1.57; 95% CI 1.24-2.00) or oligoastrocytomas (OR 0.79; 95% CI 0.35-1.76). Concerning the prognosis, we found that CIMP-positive gliomas had longer overall survival (HR 0.57; 95% CI 0.97-0.16) than CIMP-negative gliomas.

CONCLUSIONS

CIMP could be used as a potential independent prognostic indicator for glioma.

P-Rex1 Signaling Hub in Lower Grade Glioma Patients, Found by In Silico Data Mining, Correlates With Reduced Survival and Augmented Immune Tumor Microenvironment

Systematic analysis of tumor transcriptomes, combined with deep genome sequencing and detailed clinical assessment of hundreds of patients, constitutes a powerful strategy aimed to identify potential biomarkers and therapeutic targets to guide personalized treatments. Oncogenic signaling cascades are integrated by multidomain effector proteins such as P-Rex1, a guanine nucleotide exchange factor for the Rac GTPase (RacGEF), known to promote metastatic dissemination of cancer cells. We hypothesized that patients with high P-Rex1 expression and reduced survival might be characterized by a particular set of signaling proteins co-expressed with this effector of cell migration as a central component of a putative signaling hub indicative of poor prognosis. High P-Rex1 expression correlated with reduced survival of TCGA Lower Grade Glioma (LGG) patients. Thus, guided by PREX1 expression, we searched for signaling partners of this RacGEF by applying a systematic unbiased in silico data mining strategy. We identified 30 putative signaling partners that also correlated with reduced patient survival. These included GPCRs such as CXCR3, GPR82, FZD6, as well as MAP3K1, MAP2K3, NEK8, DYRK3 and RPS6KA3 kinases, and PTPN2 and PTPN22 phosphatases, among other transcripts of signaling proteins and phospho-substrates. This PREX1 signaling hub signature correlated with increased risk of shorter survival of LGG patients from independent datasets and coincided with immune and endothelial transcriptomic signatures, indicating that myeloid infiltration and tumor angiogenesis might contribute to worsen brain tumor pathology. In conclusion, P-Rex1 and its putative signaling partners in LGG are indicative of a signaling landscape of the tumor microenvironment that correlates with poor prognosis and might guide the characterization of signaling targets leading the eventual development of immunotherapeutic strategies.

Investigating the Potential Use of Chemical Biopsy Devices to Characterize Brain Tumor Lipidomes

The development of a fast and accurate intraoperative method that enables the differentiation and stratification of cancerous lesions is still a challenging problem in laboratory medicine. Therefore, it is important to find and optimize a simple and effective analytical method of enabling the selection of distinctive metabolites. This study aims to assess the usefulness of solid-phase microextraction (SPME) probes as a sampling method for the lipidomic analysis of brain tumors. To this end, SPME was applied to sample brain tumors immediately after excision, followed by lipidomic analysis via liquid chromatography-high resolution mass spectrometry (LC-HRMS). The results showed that long fibers were a good option for extracting analytes from an entire lesion to obtain an average lipidomic profile. Moreover, significant differences between tumors of different histological origin were observed. In-depth investigation of the glioma samples revealed that malignancy grade and isocitrate dehydrogenase (IDH) mutation status impact the lipidomic composition of the tumor, whereas 1p/19q co-deletion did not appear to alter the lipid profile. This first on-site lipidomic analysis of intact tumors proved that chemical biopsy with SPME is a promising tool for the simple and fast extraction of lipid markers in neurooncology.

Diagnostic test accuracy and cost-effectiveness of tests for codeletion of chromosomal arms 1p and 19q in people with glioma

BACKGROUND

Complete deletion of both the short arm of chromosome 1 (1p) and the long arm of chromosome 19 (19q), known as 1p/19q codeletion, is a mutation that can occur in gliomas. It occurs in a type of glioma known as oligodendroglioma and its higher grade counterpart known as anaplastic oligodendroglioma. Detection of 1p/19q codeletion in gliomas is important because, together with another mutation in an enzyme known as isocitrate dehydrogenase, it is needed to make the diagnosis of an oligodendroglioma. Presence of 1p/19q codeletion also informs patient prognosis and prediction of the best drug treatment. The main two tests in use are fluorescent in situ hybridisation (FISH) and polymerase chain reaction (PCR)-based loss of heterozygosity (LOH) assays (also known as PCR-based short tandem repeat or microsatellite analysis). Many other tests are available. None of the tests is perfect, although PCR-based LOH is expected to have very high sensitivity.

OBJECTIVES

To estimate the sensitivity and specificity and cost-effectiveness of different deoxyribonucleic acid (DNA)-based techniques for determining 1p/19q codeletion status in glioma.

SEARCH METHODS

We searched MEDLINE, Embase and BIOSIS up to July 2019. There were no restrictions based on language or date of publication. We sought economic evaluation studies from the results of this search and using the National Health Service Economic Evaluation Database.

SELECTION CRITERIA

We included cross-sectional studies in adults with glioma or any subtype of glioma, presenting raw data or cross-tabulations of two or more DNA-based tests for 1p/19q codeletion. We also sought economic evaluations of these tests.

DATA COLLECTION AND ANALYSIS

We followed procedures outlined in the Cochrane Handbook for Diagnostic Test Accuracy Reviews. Two review authors independently screened titles/abstracts/full texts, performed data extraction, and undertook applicability and risk of bias assessments using QUADAS-2. Meta-analyses used the hierarchical summary ROC model to estimate and compare test accuracy. We used FISH and PCR-based LOH as alternate reference standards to examine how tests compared with those in common use, and conducted a latent class analysis comparing FISH and PCR-based LOH. We constructed an economic model to evaluate cost-effectiveness.

MAIN RESULTS

We included 53 studies examining: PCR-based LOH, FISH, single nucleotide polymorphism (SNP) array, next-generation sequencing (NGS), comparative genomic hybridisation (CGH), array comparative genomic hybridisation (aCGH), multiplex-ligation-dependent probe amplification (MLPA), real-time PCR, chromogenic in situ hybridisation (CISH), mass spectrometry (MS), restriction fragment length polymorphism (RFLP) analysis, G-banding, methylation array and NanoString. Risk of bias was low for only one study; most gave us concerns about how patients were selected or about missing data. We had applicability concerns about many of the studies because only patients with specific subtypes of glioma were included. 1520 participants contributed to analyses using FISH as the reference, 1304 participants to analyses involving PCR-based LOH as the reference and 262 participants to analyses of comparisons between methods from studies not including FISH or PCR-based LOH. Most evidence was available for comparison of FISH with PCR-based LOH (15 studies, 915 participants): PCR-based LOH detected 94% of FISH-determined codeletions (95% credible interval (CrI) 83% to 98%) and FISH detected 91% of codeletions determined by PCR-based LOH (CrI 78% to 97%). Of tumours determined not to have a deletion by FISH, 94% (CrI 87% to 98%) had a deletion detected by PCR-based LOH, and of those determined not to have a deletion by PCR-based LOH, 96% (CrI 90% to 99%) had a deletion detected by FISH. The latent class analysis suggested that PCR-based LOH may be slightly more accurate than FISH. Most other techniques appeared to have high sensitivity (i.e. produced few false-negative results) for detection of 1p/19q codeletion when either FISH or PCR-based LOH was considered as the reference standard, although there was limited evidence. There was some indication of differences in specificity (false-positive rate) with some techniques. Both NGS and SNP array had high specificity when considered against FISH as the reference standard (NGS: 6 studies, 243 participants; SNP: 6 studies, 111 participants), although we rated certainty in the evidence as low or very low. NGS and SNP array also had high specificity when PCR-based LOH was considered the reference standard, although with much more uncertainty as these results were based on fewer studies (just one study with 49 participants for NGS and two studies with 33 participants for SNP array). G-banding had low sensitivity and specificity when PCR-based LOH was the reference standard. Although MS had very high sensitivity and specificity when both FISH and PCR-based LOH were considered the reference standard, these results were based on only one study with a small number of participants. Real-time PCR also showed high specificity with FISH as a reference standard, although there were only two studies including 40 participants. We found no relevant economic evaluations. Our economic model using FISH as the reference standard suggested that the resource-optimising test depends on which measure of diagnostic accuracy is most important. With FISH as the reference standard, MLPA is likely to be cost-effective if society was willing to pay GBP 1000 or less for a true positive detected. However, as the value placed on a true positive increased, CISH was most cost-effective. Findings differed when the outcome measure changed to either true negative detected or correct diagnosis. When PCR-based LOH was used as the reference standard, MLPA was likely to be cost-effective for all measures of diagnostic accuracy at lower threshold values for willingness to pay. However, as the threshold values increased, none of the tests were clearly more likely to be considered cost-effective.

AUTHORS' CONCLUSIONS

In our review, most techniques (except G-banding) appeared to have good sensitivity (few false negatives) for detection of 1p/19q codeletions in glioma against both FISH and PCR-based LOH as a reference standard. However, we judged the certainty of the evidence low or very low for all the tests. There are possible differences in specificity, with both NGS and SNP array having high specificity (fewer false positives) for 1p/19q codeletion when considered against FISH as the reference standard. The economic analysis should be interpreted with caution due to the small number of studies.

PODNL1 Methylation Serves as a Prognostic Biomarker and Associates with Immune Cell Infiltration and Immune Checkpoint Blockade Response in Lower-Grade Glioma

Lower-grade glioma (LGG) is a diffuse infiltrative tumor of the central nervous system, which lacks targeted therapy. We investigated the role of Podocan-like 1 (PODNL1) methylation in LGG clinical outcomes using the TCGA-LGG transcriptomics dataset. We identified four PODNL1 CpG sites, cg07425555, cg26969888, cg18547299, and cg24354933, which were associated with unfavorable overall survival (OS) and disease-free survival (DFS) in univariate and multivariate analysis after adjusting for age, gender, tumor-grade, and IDH1-mutation. In multivariate analysis, the OS and DFS hazard ratios ranged from 0.44 to 0.58 (p < 0.001) and 0.62 to 0.72 (p < 0.001), respectively, for the four PODNL1 CpGs. Enrichment analysis of differential gene and protein expression and analysis of 24 infiltrating immune cell types showed significantly increased infiltration in LGGs and its histological subtypes with low-methylation levels of the PODNL1 CpGs. High PODNL1 expression and low-methylation subgroups of the PODNL1 CpG sites were associated with significantly increased PD-L1, PD-1, and CTLA4 expressions. PODNL1 methylation may thus be a potential indicator of immune checkpoint blockade response, and serve as a biomarker for determining prognosis and immune subtypes in LGG.

Immune cell deconvolution of bulk DNA methylation data reveals an association with methylation class, key somatic alterations, and cell state in glial/glioneuronal tumors

It is recognized that the tumor microenvironment (TME) plays a critical role in the biology of cancer. To better understand the role of immune cell components in CNS tumors, we applied a deconvolution approach to bulk DNA methylation array data in a large set of newly profiled samples (n = 741) as well as samples from external data sources (n = 3311) of methylation-defined glial and glioneuronal tumors. Using the cell-type proportion data as input, we used dimensionality reduction to visualize sample-wise patterns that emerge from the cell type proportion estimations. In IDH-wildtype glioblastomas (n = 2,072), we identified distinct tumor clusters based on immune cell proportion and demonstrated an association with oncogenic alterations such as EGFR amplification and CDKN2A/B homozygous deletion. We also investigated the immune cluster-specific distribution of four malignant cellular states (AC-like, OPC-like, MES-like and NPC-like) in the IDH-wildtype cohort. We identified two major immune-based subgroups of IDH-mutant gliomas, which largely aligned with 1p/19q co-deletion status. Non-codeleted gliomas showed distinct proportions of a key genomic aberration (CDKN2A/B loss) among immune cell-based groups. We also observed significant positive correlations between monocyte proportion and expression of PD-L1 and PD-L2 (R = 0.54 and 0.68, respectively). Overall, the findings highlight specific roles of the TME in biology and classification of CNS tumors, where specific immune cell admixtures correlate with tumor types and genomic alterations.

Epigenetic age acceleration and clinical outcomes in gliomas

Epigenetic age acceleration-the difference between an individual's DNA methylation age and chronological age-is associated with many diseases including cancer. This study aims to evaluate epigenetic age acceleration as a prognostic biomarker for gliomas. DNA methylation data of gliomas patients (516 low-grade and intermediate-grade gliomas and 140 glioblastoma) were obtained from The Cancer Genome Atlas (TCGA) and patient epigenetic ages were computed using Horvath's age prediction model. We used multivariate linear regression to assess the association of epigenetic age acceleration with tumor molecular subtypes, including Codel, Classic-like, G-CIMP-high, G-CIMP-low, Mesenchymal-like and PA-like. Compared with Codel subtype, epigenetic ages in other molecular subtypes show deceleration after controlling age and race. Age deceleration for Classic-like, G-CIMP-high, G-CIMP-low, Mesenchymal-like and PA-like were 15.42 years (CI: 7.98-22.86, p = 5.38E-05), 25.00 years (CI: 20.79-29.22, p = 4.06E-28), 28.56 years (CI: 14.37-42.74, p = 8.75E-05), 45.34 years (CI: 38.80-51.88, p = 2.15E-36), and 53.58 years (CI: 44.90-62.26, p = 4.81E-30), respectively. Then, Cox proportional hazards regression was used to assess the association of epigenetic age acceleration with patient overall survival. Our results show epigenetic age acceleration is positively associated with patient overall survival (per 10-year age acceleration, HR = 0.89; 95%CI: 0.82-0.97; p = 9.04E-03) in multivariate analysis. When stratified by molecular subtypes, epigenetic age acceleration remains positively associated with patient survival after adjusting age and tumor grade. In conclusion, epigenetic age acceleration is significantly associated with molecular subtypes and patient overall survival in gliomas, indication that epigenetic age acceleration has potential as a quantitative prognostic biomarker for gliomas.

Lower Lactate Levels and Lower Intracellular pH in Patients with IDH-Mutant versus Wild-Type Gliomas

BACKGROUND AND PURPOSE

Preclinical evidence points toward a metabolic reprogramming in isocitrate dehydrogenase (IDH) mutated tumor cells with down-regulation of the expression of genes that encode for glycolytic metabolism. We noninvasively investigated lactate and Cr concentrations, as well as intracellular pH using ¹H/phosphorus 31 (³¹P) MR spectroscopy in a cohort of patients with gliomas.

MATERIALS AND METHODS

Thirty prospectively enrolled, mostly untreated patients with gliomas met the spectral quality criteria (World Health Organization II [n = 7], III [n = 16], IV [n = 7]; IDH-mutant [n = 23]; IDH wild-type [n = 7]; 1p/19q codeletion [n = 9]). MR imaging protocol included 3D ³¹P chemical shift imaging and ¹H single-voxel spectroscopy (point-resolved spectroscopy sequence at TE = 30 ms and TE = 97 ms with optimized echo spacing for detection of 2-hydroxyglutarate) from the tumor area. Values for absolute metabolite concentrations were calculated (phantom replacement method). Intracellular pH was determined from ³¹P chemical shift imaging.

RESULTS

At TE = 97 ms, lactate peaks can be fitted with little impact of lipid/macromolecule contamination. We found a significant difference in lactate concentrations, lactate/Cr ratios, and intracellular pH when comparing tumor voxels of patients with IDH-mutant with those of patients with IDH wild-type gliomas, with reduced lactate levels and near-normal intracellular pH in patients with IDH-mutant gliomas. We additionally found evidence for codependent effects of 1p/19q codeletion and IDH mutations with regard to lactate concentrations for World Health Organization tumor grades II and III, with lower lactate levels in patients exhibiting the codeletion. There was no statistical significance when comparing lactate concentrations between IDH-mutant World Health Organization II and III gliomas.

CONCLUSIONS

We found indirect evidence for metabolic reprogramming in IDH-mutant tumors with significantly lower lactate concentrations compared with IDH wild-type tumors and a near-normal intracellular pH.

Computational identification and characterization of glioma candidate biomarkers through multi-omics integrative profiling

BACKGROUND

Glioma is one of the most common malignant brain tumors and exhibits low resection rate and high recurrence risk. Although a large number of glioma studies powered by high-throughput sequencing technologies have led to massive multi-omics datasets, there lacks of comprehensive integration of glioma datasets for uncovering candidate biomarker genes.

RESULTS

In this study, we collected a large-scale assemble of multi-omics multi-cohort datasets from worldwide public resources, involving a total of 16,939 samples across 19 independent studies. Through comprehensive molecular profiling across different datasets, we revealed that PRKCG (Protein Kinase C Gamma), a brain-specific gene detectable in cerebrospinal fluid, is closely associated with glioma. Specifically, it presents lower expression and higher methylation in glioma samples compared with normal samples. PRKCG expression/methylation change from high to low is indicative of glioma progression from low-grade to high-grade and high RNA expression is suggestive of good survival. Importantly, PRKCG in combination with MGMT is effective to predict survival outcomes in a more precise manner.

CONCLUSIONS

PRKCG bears the great potential for glioma diagnosis, prognosis and therapy, and PRKCG-like genes may represent a set of important genes associated with different molecular mechanisms in glioma tumorigenesis. Our study indicates the importance of computational integrative multi-omics data analysis and represents a data-driven scheme toward precision tumor subtyping and accurate personalized healthcare.

Pan-Cancer Analysis of Mitochondria Chaperone-Client Co-Expression Reveals Chaperone Functional Partitioning

Metabolic reprogramming is a hallmark of cancer. Such reprogramming entails the up-regulation of the expression of specific mitochondrial proteins, thus increasing the burden on the mitochondrial protein quality control. However, very little is known about the specificity of interactions between mitochondrial chaperones and their clients, or to what extent the mitochondrial chaperone–client co-expression is coordinated. We hypothesized that a physical interaction between a chaperone and its client in mitochondria ought to be manifested in the co-expression pattern of both transcripts. Using The Cancer Genome Atlas (TCGA) gene expression data from 13 tumor entities, we constructed the mitochondrial chaperone-client co-expression network. We determined that the network is comprised of three distinct modules, each populated with unique chaperone-clients co-expression pairs belonging to distinct functional groups. Surprisingly, chaperonins HSPD1 and HSPE1, which are known to comprise a functional complex, each occupied a different module: HSPD1 co-expressed with tricarboxylic acid cycle cycle enzymes, while HSPE1 co-expressed with proteins involved in oxidative phosphorylation. Importantly, we found that the genes in each module were enriched for discrete transcription factor binding sites, suggesting the mechanism for the coordinated co-expression. We propose that our mitochondrial chaperone–client interactome can facilitate the identification of chaperones supporting specific mitochondrial pathways and bring forth a fundamental principle in metabolic adaptation.

Tumor mutational burden predicts survival in patients with low-grade gliomas expressing mutated IDH1

Background

Gliomas are the most common primary brain tumors. High-Grade Gliomas have a median survival (MS) of 18 months, while Low-Grade Gliomas (LGGs) have an MS of approximately 7.3 years. Seventy-six percent of patients with LGG express mutated isocitrate dehydrogenase (mIDH) enzyme. Survival of these patients ranges from 1 to 15 years, and tumor mutational burden ranges from 0.28 to 3.85 somatic mutations/megabase per tumor. We tested the hypothesis that the tumor mutational burden would predict the survival of patients with tumors bearing mIDH.

Methods

We analyzed the effect of tumor mutational burden on patients' survival using clinical and genomic data of 1199 glioma patients from The Cancer Genome Atlas and validated our results using the Glioma Longitudinal AnalySiS consortium.

Results

High tumor mutational burden negatively correlates with the survival of patients with LGG harboring mIDH (P = .005). This effect was significant for both Oligodendroglioma (LGG-mIDH-O; MS = 2379 vs 4459 days in high vs low, respectively; P = .005) and Astrocytoma (LGG-mIDH-A; MS = 2286 vs 4412 days in high vs low respectively; P = .005). There was no differential representation of frequently mutated genes (eg, TP53, ATRX, CIC, and FUBP) in either group. Gene set enrichment analysis revealed an enrichment in Gene Ontologies related to cell cycle, DNA-damage response in high versus low tumor mutational burden. Finally, we identified 6 gene sets that predict survival for LGG-mIDH-A and LGG-mIDH-O.

Conclusions

we demonstrate that tumor mutational burden is a powerful, robust, and clinically relevant prognostic factor of MS in mIDH patients.

A Distinct DNA Methylation Shift in a Subset of Glioma CpG Island Methylator Phenotypes during Tumor Recurrence

Glioma diagnosis is based on histomorphology and grading; however, such classification does not have predictive clinical outcome after glioblastomas have developed. To date, no bona fide biomarkers that significantly translate into a survival benefit to glioblastoma patients have been identified. We previously reported that the IDH mutant G-CIMP-high subtype would be a predecessor to the G-CIMP-low subtype. Here, we performed a comprehensive DNA methylation longitudinal analysis of diffuse gliomas from 77 patients (200 tumors) to enlighten the epigenome-based malignant transformation of initially lower-grade gliomas. Intra-subtype heterogeneity among G-CIMP-high primary tumors allowed us to identify predictive biomarkers for assessing the risk of malignant recurrence at early stages of disease. G-CIMP-low recurrence appeared in 9.5% of all gliomas, and these resembled IDH-wild-type primary glioblastoma. G-CIMP-low recurrence can be characterized by distinct epigenetic changes at candidate functional tissue enhancers with AP-1/SOX binding elements, mesenchymal stem cell-like epigenomic phenotype, and genomic instability. Molecular abnormalities of longitudinal G-CIMP offer possibilities to defy glioblastoma progression.

Glioma CpG island methylator phenotype (G-CIMP): biological and clinical implications

Gliomas are a heterogeneous group of brain tumors with distinct biological and clinical properties. Despite advances in surgical techniques and clinical regimens, treatment of high-grade glioma remains challenging and carries dismal rates of therapeutic success and overall survival. Challenges include the molecular complexity of gliomas, as well as inconsistencies in histopathological grading, resulting in an inaccurate prediction of disease progression and failure in the use of standard therapy. The updated 2016 World Health Organization (WHO) classification of tumors of the central nervous system reflects a refinement of tumor diagnostics by integrating the genotypic and phenotypic features, thereby narrowing the defined subgroups. The new classification recommends molecular diagnosis of isocitrate dehydrogenase (IDH) mutational status in gliomas. IDH-mutant gliomas manifest the cytosine-phosphate-guanine (CpG) island methylator phenotype (G-CIMP). Notably, the recent identification of clinically relevant subsets of G-CIMP tumors (G-CIMP-high and G-CIMP-low) provides a further refinement in glioma classification that is independent of grade and histology. This scheme may be useful for predicting patient outcome and may be translated into effective therapeutic strategies tailored to each patient. In this review, we highlight the evolution of our understanding of the G-CIMP subsets and how recent advances in characterizing the genome and epigenome of gliomas may influence future basic and translational research.

Array-based profiling of the lymphoma cell DNA methylome does not unequivocally distinguish primary lymphomas of the central nervous system from non-CNS diffuse large B-cell lymphomas

Primary lymphomas of the central nervous system (PCNSL) are diffuse large B-cell lymphomas (DLBCLs) confined to the central nervous system (CNS). We here performed array-based DNA methylation analyses of 26 PCNSL and 78 DLBCL and validated our findings in an independent dataset. We identified 2847 CpGs differentially methylated between PCNSL and non-CNS-DLBCL. Neither a supervised analysis using these CpGs nor application of 3 CpG classifiers selected for class separation unambiguously separated PCNSL from non-CNS-DLBCL. Remarkably, 6/78 non-CNS-DLBCL consistently segregated with PCNSL, which displayed molecular features typical for PCNSL. Our findings suggest that a subset of non-CNS-DLBCL exists which molecularly resembles PCNSL.

Models of epigenetic age capture patterns of DNA methylation in glioma associated with molecular subtype, survival, and recurrence

Background

Models of epigenetic aging (epigenetic clocks) have been implicated as potentially useful markers for cancer risk and prognosis. Using 2 previously published methods for modeling epigenetic age, Horvath's clock and epiTOC, we investigated epigenetic aging patterns related to World Health Organization grade and molecular subtype as well as associations of epigenetic aging with glioma survival and recurrence.

Methods

Epigenetic ages were calculated using Horvath's clock and epiTOC on 516 lower-grade glioma and 141 glioblastoma cases along with 136 nontumor (normal) brain samples. Associations of tumor epigenetic age with patient chronological age at diagnosis were assessed with correlation and linear regression, and associations were validated in an independent cohort of 203 gliomas. Contribution of epigenetic age to survival prediction was assessed using Cox proportional hazards modeling. Sixty-three samples from 18 patients with primary-recurrent glioma pairs were also analyzed and epigenetic age difference and rate of epigenetic aging of primary-recurrent tumors were correlated to time to recurrence.

Results

Epigenetic ages of gliomas were near-universally accelerated using both Horvath's clock and epiTOC compared with normal tissue. The 2 independent models of epigenetic aging were highly associated with each other and exhibited distinct aging patterns reflective of molecular subtype. EpiTOC was found to be a significant independent predictor of survival. Epigenetic aging of gliomas between primary and recurrent tumors was found to be highly variable and not significantly associated with time to recurrence.

Conclusions

We demonstrate that epigenetic aging reflects coherent modifications of the epigenome and can potentially provide additional prognostic power for gliomas.

A PRDX1-p38α heterodimer amplifies MET-driven invasion of IDH-wildtype and IDH-mutant gliomas

The Peroxiredoxin 1 (PRDX1) gene maps to chromosome arm 1p and is hemizygously deleted and epigenetically silenced in isocitrate dehydrogenase 1 or 2 (IDH)-mutant and 1p/19q-codeleted oligodendroglial tumors. In contrast, IDH-wildtype astrocytic gliomas including glioblastomas mostly lack epigenetic silencing and express PRDX1 protein. In our study, we investigated how PRDX1 contributes to the infiltrative growth of IDH-wildtype gliomas. Focusing on p38α-dependent pathways, we analyzed clinical data from 133 patients of the NOA-04 trial cohort to look for differences in the gene expression profiles of gliomas with wildtype or mutant IDH. Biochemical interaction studies as well as in vitro and ex vivo migration studies were used to establish a biological role of PRDX1 in maintaining pathway activity. Whole-brain high-resolution ultramicroscopy and survival analyses of pre-clinical mouse models for IDH-wildtype gliomas were then used for in vivo confirmation. Based on clinical data, we found that the absence of PRDX1 is associated with changes in the expression of MET/HGF signaling components. PRDX1 forms a heterodimer with p38α mitogen-activated protein kinase 14 (MAPK14), stabilizing phospho-p38α in glioma cells. This process amplifies hepatocyte growth factor (HGF)-mediated signaling and stimulates actin cytoskeleton dynamics that promote glioma cell migration. Whole-brain high-resolution ultramicroscopy confirms these findings, indicating that PRDX1 promotes glioma brain invasion in vivo. Finally, reduced expression of PRDX1 increased survival in mouse glioma models. Thus, our preclinical findings suggest that PRDX1 expression levels may serve as a molecular marker for patients who could benefit from targeted inhibition of MET/HGF signaling.

Not all 1p/19q non-codeleted oligodendroglial tumors are astrocytic

Although 1p/19q codeletion is the genetic hallmark defining oligodendrogliomas, approximately 30-40% of oligodendroglial tumors have intact 1p/19q in the literature and they demonstrate a worse prognosis. This group of 1p/19q intact oligodendroglial tumors is frequently suggested to be astrocytic in nature with TP53 and ATRX mutations but actually remains under-investigated. In the present study, we provided evidence that not all 1p/19q intact oligodendroglial tumors are astrocytic through histologic and molecular approaches. We examined 1p/19q status by FISH in a large cohort of 337 oligodendroglial tumors and identified 39.8% lacking 1p/19q codeletion which was independently associated with poor prognosis. Among this 1p/19q intact oligodendroglial tumor cohort, 58 cases demonstrated classic oligodendroglial histology which showed older patient age, better prognosis, association with grade III histology, PDGFRA expression, TERTp mutation, as well as frequent IDH mutation. More than half of the 1p/19q intact oligodendroglial tumors showed lack of astrocytic defining markers, p53 expression and ATRX loss. TP53 mutational analysis was additionally conducted in 45 cases of the 1p/19q intact oligodendroglial tumors. Wild-type TP53 was detected in 71.1% of cases which was associated with classic oligodendroglial histology. Importantly, IDH and TERTp co-occurred in 75% of 1p/19q intact, TP53 wild-type oligodendrogliomas, highlighting the potential of the co-mutations in assisting diagnosis of oligodendrogliomas in tumors with clear cell morphology and non-codeleted 1p/19q status. In summary, our study demonstrated that not all 1p/19q intact oligodendroglial tumors are astrocytic and co-evaluation of IDH and TERTp mutation could potentially serve as an adjunct for diagnosing 1p/19q intact oligodendrogliomas.

A Comprehensive Review of Genomics and Noncoding RNA in Gliomas

Glioblastoma (GBM) is the most malignant primary adult brain tumor. In spite of our greater understanding of the biology of GBMs, clinical outcome of GBM patients remains poor, as their median survival with best available treatment is 12 to 18 months. Recent efforts of The Cancer Genome Atlas (TCGA) have subgrouped patients into 4 molecular/transcriptional subgroups: proneural, neural, classical, and mesenchymal. Continuing efforts are underway to provide a comprehensive map of the heterogeneous makeup of GBM to include noncoding transcripts, genetic mutations, and their associations to clinical outcome. In this review, we introduce key molecular events (genetic and epigenetic) that have been deemed most relevant as per studies such as TCGA, with a specific focus on noncoding RNAs such as microRNAs (miRNA) and long noncoding RNAs (lncRNA). One of our main objectives is to illustrate how miRNAs and lncRNAs play a pivotal role in brain tumor biology to define tumor heterogeneity at molecular and cellular levels. Ultimately, we elaborate how radiogenomics-based predictive models can describe miRNA/lncRNA-driven networks to better define heterogeneity of GBM with clinical relevance.

Relation between Established Glioma Risk Variants and DNA Methylation in the Tumor

Genome-wide association studies and candidate gene studies have identified several genetic variants that increase glioma risk. The majority of these variants are non-coding and the mechanisms behind the increased risk in carriers are not known. In this study, we hypothesize that some of the established glioma risk variants induce aberrant DNA methylation in the developing tumor, either locally (gene-specific) or globally (genome-wide). In a pilot data set including 77 glioma patients, we used Illumina beadchip technology to analyze genetic variants in blood and DNA methylation in matched tumor samples. To validate our findings, we used data from the Cancer Genome Atlas, including 401 glioblastoma patients. Consensus clustering identified the glioma CpG island methylator phenotype (gCIMP) and two additional subgroups with distinct patterns of global DNA methylation. In the pilot dataset, gCIMP was associated with two genetic variants in CDKN2B-AS1, rs1412829 and rs4977756 (9p21.3, p = 8.1 x 10-7 and 4.8 x 10-5, respectively). The association was in the same direction in the TCGA dataset, although statistically significant only when combining individuals with AG and GG genotypes. We also investigated the relation between glioma risk variants and DNA methylation in the promoter region of genes located within 30 kb of each variant. One association in the pilot dataset, between the TERT risk variant rs2736100 and lower methylation of cg23827991 (in TERT; p = 0.001), was confirmed in the TCGA dataset (p = 0.001). In conclusion, we found an association between rs1412829 and rs4977756 (9p21.3, CDKN2B-AS1) and global DNA methylation pattern in glioma, for which a trend was seen also in the TCGA glioblastoma dataset. We also found an association between rs2736100 (in TERT) and levels of methylation at cg23827991 (localized in the same gene, 3.3 kbp downstream of the risk variant), which was validated in the TCGA dataset. Except for this one association, we did not find strong evidence for gene-specific DNA methylation mediated by glioma risk variants.

Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma

Therapy development for adult diffuse glioma is hindered by incomplete knowledge of somatic glioma driving alterations and suboptimal disease classification. We defined the complete set of genes associated with 1,122 diffuse grade II-III-IV gliomas from The Cancer Genome Atlas and used molecular profiles to improve disease classification, identify molecular correlations, and provide insights into the progression from low- to high-grade disease. Whole-genome sequencing data analysis determined that ATRX but not TERT promoter mutations are associated with increased telomere length. Recent advances in glioma classification based on IDH mutation and 1p/19q co-deletion status were recapitulated through analysis of DNA methylation profiles, which identified clinically relevant molecular subsets. A subtype of IDH mutant glioma was associated with DNA demethylation and poor outcome; a group of IDH-wild-type diffuse glioma showed molecular similarity to pilocytic astrocytoma and relatively favorable survival. Understanding of cohesive disease groups may aid improved clinical outcomes.

Epidemiology

More than 250,000 new cases of primary malignant brain tumors are diagnosed annually worldwide, 77% of which are gliomas. A small proportion of gliomas are caused by the inheritance of rare high-penetrance genetic variants or high-dose radiation. Since 2009, inherited genetic variants in 10 regions near eight different genes have been consistently associated with glioma risk via genome-wide association studies. Most of these variants increase glioma risk by 20-40%, but two have higher relative risks. One on chromosome 8 increases risk of IDH-mutated gliomas sixfold and another that affects TP53 function confers a 2.5-fold increased risk of glioma. Functions of some of the other risk variants are known or suspected, but future research will determine functions of other risk loci. Recent progress also has been made in defining subgroups of glioma based on acquired alterations within tumors. Allergy history has been consistently associated with reduced glioma risk, though the mechanisms have not yet been clarified. Future studies will need to be large enough so that environmental and constitutive genetic risk factors can be examined within molecularly defined, etiologically homogeneous subgroups.

Molecular Markers in Low-Grade Glioma-Toward Tumor Reclassification

Low-grade diffuse gliomas are a heterogeneous group of primary glial brain tumors with highly variable survival. Currently, patients with low-grade diffuse gliomas are stratified into risk subgroups by subjective histopathologic criteria with significant interobserver variability. Several key molecular signatures have emerged as diagnostic, prognostic, and predictor biomarkers for tumor classification and patient risk stratification. In this review, we discuss the effect of the most critical molecular alterations described in diffuse (IDH1/2, 1p/19q codeletion, ATRX, TERT, CIC, and FUBP1) and circumscribed (BRAF-KIAA1549, BRAF(V600E), and C11orf95-RELA fusion) gliomas. These molecular features reflect tumor heterogeneity and have specific associations with patient outcome that determine appropriate patient management. This has led to an important, fundamental shift toward developing a molecular classification of World Health Organization grade II-III diffuse glioma.

Diffusely infiltrating astrocytomas: pathology, molecular mechanisms and markers

Diffusely infiltrating astrocytomas include diffuse astrocytomas WHO grade II and anaplastic astrocytomas WHO grade III and are classified under astrocytic tumours according to the current WHO Classification. Although the patients generally have longer survival as compared to those with glioblastoma, the timing of inevitable malignant progression ultimately determines the prognosis. Recent advances in molecular genetics have uncovered that histopathologically diagnosed astrocytomas may consist of two genetically different groups of tumours. The majority of diffusely infiltrating astrocytomas regardless of WHO grade have concurrent mutations of IDH1 or IDH2, TP53 and ATRX. Among these astrocytomas, no other genetic markers that may distinguish grade II and grade III tumours have been identified. Those astrocytomas without IDH mutation tend to have a distinct genotype and a poor prognosis comparable to that of glioblastomas. On the other hand, diffuse astrocytomas that arise in children do not harbour IDH/TP53 mutations, but instead display mutations of BRAF or structural alterations involving MYB/MYBL1 or FGFR1. A molecular classification may thus help delineate diffusely infiltrating astrocytomas into distinct pathogenic and prognostic groups, which could aid in determining individualised therapeutic strategies.

Anaplastic glioma: current treatment and management

Anaplastic glioma (AG) is divided into three morphology-based groups (anaplastic astrocytoma, anaplastic oligodendroglioma, anaplastic oligoastrocytoma) as well as three molecular groups (glioma-CpG island methylation phenotype [G-CIMP] negative, G-CIMP positive non-1p19q codeleted tumors and G-CIMP positive codeleted tumors). The RTOG 9402 and EORTC 26951 trials established radiotherapy plus (procarbazine, lomustine, vincristine) chemotherapy as the standard of care in 1p/19q codeleted AG. Uni- or non-codeleted AG are currently best treated with radiotherapy only or alkylator-based chemotherapy only as determined by the NOA-04 trial. Maturation of NOA-04 and results of the currently accruing studies, CODEL (for codeleted AG) and CATNON (for uni or non-codeleted AG), will likely refine current up-front treatment recommendations for AG.

Molecular classification defines 4 prognostically distinct glioma groups irrespective of diagnosis and grade

According to World Health Organization criteria, diffuse gliomas are divided into several histological subtypes, including astrocytomas, oligodendrogliomas, and oligoastrocytomas, and 4 malignancy grades (I-IV). Molecular alterations, such as the isocitrate dehydrogenase gene (IDH) mutation or 1p/19q loss, are found in these tumors but are not included in the current classification system. Recently, mutation of α thalassemia/mental retardation syndrome X-linked (ATRX) gene and its loss of expression have been reported in infiltrating gliomas. We evaluated ATRX protein expression in 272 gliomas and its association with molecular and clinical features. Loss of ATRX expression was more common in tumors with an astrocytic component (astrocytomas II/III, 46.4%; oligoastrocytomas, 47.5%) but was uncommon in oligodendrogliomas (7.3%) and glioblastomas (0.9%). In astrocytic tumors, loss of ATRX expression was significantly associated with longer overall survival. Remarkably, on the basis of IDH mutation, 1p/19q codeletion, and ATRX expression, our study defined 4 molecularly and prognostically different groups of gliomas, showing the relevance of ATRX expression as a new marker for refining the molecular classification of gliomas and for distinguishing clinically distinct prognostic subgroups of patients.

Impact on prognosis of the regional distribution of MGMT methylation with respect to the CpG island methylator phenotype and age in glioma patients

Clinical and molecular prognostic factors in gliomas include age, IDH mutation, the glioma CpG island methylator phenotype (G-CIMP+) and promoter methylation of the O(6)-methylguanine DNA-methyltransferase (MGMT) gene. Among these markers, a predictive value was reported in glioblastomas (GBM) for MGMT promoter methylation, in particular in elderly GBM patients. In this study, methylation data from 46 glioma samples with the Illumina 450K platform were obtained and extended using external data to include a total of 247 glioma samples. Methylation analysis of the whole MGMT gene with this platform revealed two strongly survival-associated CpG regions within the promoter and the gene body, which were confirmed in a reported dataset of high grade-gliomas. Methylation at the promoter (CpG 25, cg12981137 and the prognostic model MGMT-STP27) and at the gene body CpG 165 (cg07933035), were significantly associated with better overall survival, and strongly correlated with G-CIMP+ status. In this series, the prognostic value of MGMT methylation at the promoter was not observed in G-CIMP- cases, although around 50 % of them were MGMT-methylated. These results were also obtained in an homogeneously-treated series of chemoradiated G-CIMP- GBMs analyzed by MSP and qMSP, and confirmed in a reported pyrosequencing-analyzed series of gliomas. Interestingly, in contrast to the MGMT promoter, gene body methylation was of prognostic value in G-CIMP-patients older than 65 years. Our study highlights the relevance of the prognostic value of the different regions of methylation throughout the MGMT gene that could be affected by specific G-CIMP profiles and age groups.

The future of high-grade glioma: Where we are and where are we going

High-grade glioma (HGG) are optimally treated with maximum safe surgery, followed by radiotherapy (RT) and/or systemic chemotherapy (CT). Recently, the treatment of newly diagnosed anaplastic glioma (AG) has changed, particularly in patients with 1p19q codeleted tumors. Results of trials currenlty ongoing are likely to determine the best standard of care for patients with noncodeleted AG tumors. Trials in AG illustrate the importance of molecular characterization, which are germane to both prognosis and treatment. In contrast, efforts to improve the current standard of care of newly diagnosed glioblastoma (GB) with, for example, the addition of bevacizumab (BEV), have been largely disappointing and furthermore molecular characterization has not changed therapy except in elderly patients. Novel approaches, such as vaccine-based immunotherapy, for newly diagnosed GB are currently being pursued in multiple clinical trials. Recurrent disease, an event inevitable in nearly all patients with HGG, continues to be a challenge. Both recurrent GB and AG are managed in similar manner and when feasible re-resection is often suggested notwithstanding limited data to suggest benefit from repeat surgery. Occassional patients may be candidates for re-irradiation but again there is a paucity of data to commend this therapy and only a minority of selected patients are eligible for this approach. Consequently systemic therapy continues to be the most often utilized treatment in recurrent HGG. Choice of therapy, however, varies and revolves around re-challenge with temozolomide (TMZ), use of a nitrosourea (most often lomustine; CCNU) or BEV, the most frequently used angiogenic inhibitor. Nevertheless, no clear standard recommendation regarding the prefered agent or combination of agents is avaliable. Prognosis after progression of a HGG remains poor, with an unmet need to improve therapy.

Genome-wide methylation analysis in vestibular schwannomas shows putative mechanisms of gene expression modulation and global hypomethylation at the HOX gene cluster

Schwannomas are tumors that develop from Schwann cells in the peripheral nerves and commonly arise from the vestibular nerve. Vestibular schwannomas can present unilaterally and sporadically or bilaterally when the tumor is associated with neurofibromatosis Type 2 (NF2) syndrome. The molecular hallmark of the disease is biallelic inactivation of the NF2 gene. The epigenetic signature of schwannomas remains poorly understood and is mostly limited to DNA methylation of the NF2 gene, whose altered expression due to epigenetic factors in this tumor is controversial. In this study, we tested the genomewide DNA methylation pattern of schwannomas to shed light on this epigenetic alteration in these particular tumors. The methodology used includes Infinium Human Methylation 450K BeadChip microarrays in a series of 36 vestibular schwannomas, 4 nonvestibular schwannomas, and 5 healthy nerves. Our results show a trend toward hypomethylation in schwannomas. Furthermore, homeobox (HOX) genes, located at four clusters in the genome, displayed hypomethylation in several CpG sites in the vestibular schwannomas but not in the nonvestibular schwannomas. Several microRNA (miRNA) and protein-coding genes were also found to be hypomethylated at promoter regions and were confirmed as upregulated by expression analysis; including miRNA-21, Met Proto-Oncogene (MET), and PMEPA1. We also detected methylation patterns that might be involved in alternative transcripts of several genes such as NRXN1 or MBP, which would increase the complexity of the methylation and expression patterns. Overall, our results show specific epigenetic signatures in several coding genes and miRNAs that could potentially be used as therapeutic targets.

Integrated DNA methylation and copy-number profiling identify three clinically and biologically relevant groups of anaplastic glioma

The outcome of patients with anaplastic gliomas varies considerably. Whether a molecular classification of anaplastic gliomas based on large-scale genomic or epigenomic analyses is superior to histopathology for reflecting distinct biological groups, predicting outcomes and guiding therapy decisions has yet to be determined. Epigenome-wide DNA methylation analysis, using a platform which also allows the detection of copy-number aberrations, was performed in a cohort of 228 patients with anaplastic gliomas (astrocytomas, oligoastrocytomas, and oligodendrogliomas), including 115 patients of the NOA-04 trial. We further compared these tumors with a group of 55 glioblastomas. Unsupervised clustering of DNA methylation patterns revealed two main groups correlated with IDH status: CpG island methylator phenotype (CIMP) positive (77.5 %) or negative (22.5 %). CIMP(pos) (IDH mutant) tumors showed a further separation based on copy-number status of chromosome arms 1p and 19q. CIMP(neg) (IDH wild type) tumors showed hallmark copy-number alterations of glioblastomas, and clustered together with CIMP(neg) glioblastomas without forming separate groups based on WHO grade. Notably, there was no molecular evidence for a distinct biological entity representing anaplastic oligoastrocytoma. Tumor classification based on CIMP and 1p/19q status was significantly associated with survival, allowing a better prediction of outcome than the current histopathological classification: patients with CIMP(pos) tumors with 1p/19q codeletion (CIMP-codel) had the best prognosis, followed by patients with CIMP(pos) tumors but intact 1p/19q status (CIMP-non-codel). Patients with CIMP(neg) anaplastic gliomas (GBM-like) had the worst prognosis. Collectively, our data suggest that anaplastic gliomas can be grouped by IDH and 1p/19q status into three molecular groups that show clear links to underlying biology and a significant association with clinical outcome in a prospective trial cohort.

The combination of IDH1 mutations and MGMT methylation status predicts survival in glioblastoma better than either IDH1 or MGMT alone

BACKGROUND

Genetic and epigenetic profiling of glioblastomas has provided a comprehensive list of altered cancer genes of which only O(6)-methylguanine-methyltransferase (MGMT) methylation is used thus far as a predictive marker in a clinical setting. We investigated the prognostic significance of genetic and epigenetic alterations in glioblastoma patients.

METHODS

We screened 98 human glioblastoma samples for genetic and epigenetic alterations in 10 genes and chromosomal loci by PCR and multiplex ligation-dependent probe amplification (MLPA). We tested the association between these genetic and epigenetic alterations and glioblastoma patient survival. Subsequently, we developed a 2-gene survival predictor.

RESULTS

Multivariate analyses revealed that mutations in isocitrate dehydrogenase 1 (IDH1), promoter methylation of MGMT, irradiation dosage, and Karnofsky Performance Status (KFS) were independent prognostic factors. A 2-gene predictor for glioblastoma survival was generated. Based on the genetic and epigenetic status of IDH1 and MGMT, glioblastoma patients were stratified into 3 clinically different genotypes: glioblastoma patients with IDH1mt/MGMTmet had the longest survival, followed by patients with IDH1mt/MGMTunmet or IDH1wt/MGMTmet, and patients with IDH1wt/MGMTunmet had the shortest survival. This 2-gene predictor was an independent prognostic factor and performed significantly better in predicting survival than either IDH1 mutations or MGMT methylation alone. The predictor was validated in 3 external datasets.

DISCUSSION

The combination of IDH1 mutations and MGMT methylation outperforms either IDH1 mutations or MGMT methylation alone in predicting survival of glioblastoma patients. This information will help to increase our understanding of glioblastoma biology, and it may be helpful for baseline comparisons in future clinical trials.

The epidemiology of glioma in adults: a "state of the science" review

Gliomas are the most common primary intracranial tumor, representing 81% of malignant brain tumors. Although relatively rare, they cause significant mortality and morbidity. Glioblastoma, the most common glioma histology (∼45% of all gliomas), has a 5-year relative survival of ∼5%. A small portion of these tumors are caused by Mendelian disorders, including neurofibromatosis, tuberous sclerosis, and Li-Fraumeni syndrome. Genomic analyses of glioma have also produced new evidence about risk and prognosis. Recently discovered biomarkers that indicate improved survival include O⁶-methylguanine-DNA methyltransferase methylation, isocitrate dehydrogenase mutation, and a glioma cytosine-phosphate-guanine island methylator phenotype. Genome-wide association studies have identified heritable risk alleles within 7 genes that are associated with increased risk of glioma. Many risk factors have been examined as potential contributors to glioma risk. Most significantly, these include an increase in risk by exposure to ionizing radiation and a decrease in risk by history of allergies or atopic disease(s). The potential influence of occupational exposures and cellular phones has also been examined, with inconclusive results. We provide a “state of the science” review of current research into causes and risk factors for gliomas in adults.

Oligodendroglial tumors

Oligodendroglial tumors are relatively rare, comprising approximately 5% of all glial neoplasms. Oligodendroglial tumor patients have a better prognosis than those with astrocytic neoplasms, and patients with tumors that contain 1p/19q co-deletions or IDH-1 mutations appear to be particularly sensitive to treatment. In the past decade, scientists have made significant progress in the unraveling the molecular events that relate to the pathogenesis of these neoplasms. There is considerable excitement resulting from the recent reports from two large phase III randomized trials (European Organization for Research and Treatment of Cancer [EORTC] 26951 and Radiation Therapy Oncology Group [RTOG] 9402), which disclosed that patients with newly diagnosed 1p/19q co-deleted anaplastic oligodendroglial tumors have a 7+year increase in median overall survival following chemoradiation, as compared to radiation alone. This has stimulated a renewed interest in the development of new therapeutic strategies for treatment and potential cure of oligodendroglial tumors, based on an improved scientific understanding of the molecular events involved in the pathogenesis of these neoplasms. The goal of this document is to summarize the key translational developments and recent clinical therapeutic trial data, with a correlative perspective on current and future directions.

Homozygous deletion of TNFRSF4, TP73, PPAP2B and DPYD at 1p and PDCD5 at 19q identified by multiplex ligation-dependent probe amplification (MLPA) analysis in pediatric anaplastic glioma with questionable oligodendroglial component

Background

Pediatric oligodendrogliomas are rare and appear to show a different molecular profile from adult tumors. Some gliomas display allelic losses at 1p/19q in pediatric patients, although less frequently than in adult patients, but this is rare in tumors with an oligodendroglial component. The molecular basis of this genomic abnormality is unknown in pediatric gliomas, but it represents a relatively common finding in pediatric oligodendroglioma-like neoplasms with leptomeningeal dissemination.

Results

Multiplex ligation-dependent probe amplification (MLPA) analysis using SALSA P088-B1 for the analysis of the 1p/19q allelic constitution in a pediatric anaplastic (oligodendro)-glioma showed homozygous co-deletion for markers: TNFRSF4 (located at 1p36.33), TP73 (1p36.32), PPAP2B (1pter-p22.1), DPYD (1p21.3), and PDCD5 (19q13.12), and hemizygous deletion of BAX (19q13.3-q13.4). No sequence changes for R132 and R172 of the IDH1/2 genes were identified.

Conclusions

The molecular findings in this pediatric anaplastic glioma do not allow for a clearly definitive pathological diagnosis. However, the findings provide data on a number of 1p/19q genomic regions that, because of homozygotic deletion, might be the location of genes that are important for the development and clinical evolution of some malignant gliomas in children.

Using the molecular classification of glioblastoma to inform personalized treatment

Glioblastoma is the most common and most aggressive diffuse glioma, associated with short survival and uniformly fatal outcome, irrespective of treatment. It is characterized by morphological, genetic and gene-expression heterogeneity. The current standard of treatment is maximal surgical resection, followed by radiation, with concurrent and adjuvant chemotherapy. Due to the heterogeneity, most tumours develop resistance to treatment and shortly recur. Following recurrence, glioblastoma is quickly fatal in the majority of cases. Recent genetic molecular advances have contributed to a better understanding of glioblastoma pathophysiology and disease stratification. In this paper we review basic glioblastoma pathophysiology, with emphasis on clinically relevant genetic molecular alterations and potential targets for further drug development.