Molecular Classification Of Gliomas Research Articles

KDELR1 Is an Independent Prognostic Predictor and Correlates With Immunity in Glioma.

BackgroundGliomas are the most malignant central nervous system tumors. With the development of sequencing technology, more potential biomarkers related to the treatment, prognosis, and molecular classification of glioma have been identified. Here, we intend to investigate the potential biological function and clinical value of a new biomarker in glioma.MethodsKDELR1 expression data and the corresponding clinical information were downloaded from public databases and then preprocessed using R language. Correlation, Kaplan–Meier survival, and Cox regression analyses were performed to explore the clinical significance of KDELR1 in glioma patients. Furthermore, the immune infiltration and microenvironment parameters were evaluated via TIMER and CIBERSORT. Immunohistochemistry was conducted to confirm the KDELR1 expression and its correlation with immunity infiltration and prognosis.ResultsKDELR1 was upregulated in glioma samples compared with normal brain tissues, and its expression was significantly correlated with age, the World Health Organization (WHO) grade, recurrence, necrosis, microvascular proliferation, molecular classification, isocitrate dehydrogenase (IDH) mutation, and 1p/19q codeletion status. In addition, survival analysis showed that glioma patients with KDELR1 overexpression had shorter overall survival (OS) and disease-free survival times, and Cox regression analysis revealed that KDELR1 acted as an independent prognostic factor of OS in glioma patients. Gene set enrichment analysis indicated a significant enrichment of metabolism-associated pathways. KDELR1 expression was positively associated with immune infiltration (including infiltration by CD8+ T cells, CD4+ T cells, macrophages, and so on) and microenvironment parameters (including stromal, immune, and ESTIMATE scores) in gliomas. The expression of KDELR1 and its correlation with the tumor grade and prognosis were confirmed by immunohistochemistry in clinical samples (n = 119, P < 0.05).ConclusionsTaken together, these findings suggest that KDELR1 is correlated with the tumor grade, molecular classifications, and immune infiltration; highlighting that KDELR1 is a novel and promising biomarker for molecular classification, treatment, and prognostic assessment may further indicate the treating effect of immune therapy.

The Place and Prognostic Value of TERT Promoter Mutation in Molecular Classification in Grade II-III Glial Tumors and Primary Glioblastomas.

Diffuse gliomas, the most common primary malignant brain tumors, have been classified by the World Health Organization as class II-IV gliomas. After 2016, two mutations in the promoter region of the telomerase reverse transcriptase (TERT) gene were identified in addition to the IDH, 1p / 19q, and ATRX status. We identified 84 patients with grade II-IV glioma with IDH, ATRX, 1p / 19q and TERT status. All tumor samples were subjected to molecular genetic screening (Sanger sequencing for IDH and TERT mutations, fluorescence in situ hybridization for 1p/19q status) after histological diagnosis (immunohistochemistry for IDH1 R132H, ATRX, and p53) for a more precise molecular diagnosis. The confidence intervals were calculated at the 95% confidence level, and differences at p < 0.05 were considered statistically significant. Primary glioblastomas had the highest frequency of TERT promoter mutations (25 of 28, 89.2%, p=0.006) followed by oligodendrogliomas (29 of 35, 82.8%, p < 0.001) while astrocytomas showed the lowest frequency (3 of 15, 20%, p=0.107), and the positivity significantly differed among these three groups (p < 0.001). TERT promoter mutations were more frequent in patients older than 55 years of age at diagnosis (p=0.023). The group with TERT promoter mutations, and without IDH mutations showed the worst overall survival. However, the presence of both TERT promoter and IDH mutations, which resembled oligodendroglial progression, showed best overall survival (p=0.042). The discovery of TERT promoter mutations in numerous gliomas has opened the door for a better molecular classification of gliomas, and TERT status is associated with survival. Further studies will help in elucidating the value of TERT promoter mutations as biomarkers in clinical practice, and eventual therapeutic targets.

NI-10 T2/FLAIR mismatch sign and methionine PET uptake in grade II and III gliomas

Background: Recent study suggests that “T2/FLAIR mismatch” sign is specific MRI finding for isocitrate dehydrogenase mutated (IDH-mut) 1p19q non-codeleted gliomas (Grade II and III astrocytic tumors). T2/FLAIR mismatch sign may be useful for predicting the histological type of glioma before surgery. However, it is not known what this finding reflects. Therefore, we examined the correlation between T2/FLAIR mismatch sign and uptake of methionine with positron emission tomography (MET-PET), and molecular classification of glioma.Methods: 74 glioma patients (grade II: 30 cases, grade III: 44 cases) with preoperative MRI and MET-PET who underwent surgical resection during 2000–2019 were included in this study. MR scans were evaluated by 3 independent reviewers to assess presence/absence of T2/FLAIR mismatch sign. The tumor-to-normal (T/N) ratio of methionine uptake was calculated by dividing the maximum standardized uptake value (SUV) for the tumor by the mean SUV of the normal brain. We examined the relationship between IDH mutation, 1p/19q codeletion, mismatch, and T/N ratio of MET-PET.Results: Out of the 74 cases, astrocytic tumors (A group: IDH-mutant, 1p19q non-codeleted) were 21 (28%), oligodendroglial tumors (O group: IDH-mutant, 1p19q codeleted) were 19 (26%), and IDH wild tumors (W group) were 34 (46%). The T2/FLAIR mismatch sign was present in 16 cases (22%). The T/N ratio of MET-PET in the tumor with T2/FLAIR mismatch sign was 1.56, which was significantly lower than that in the tumor without mismatch sign (2.01, p=0.016). T2/FLAIR mismatch sign was found in 7 (33%) cases in the A group, 0 (0%) case in the O group and 9 (26%) cases in the W group, and the positive rate was significantly higher in the A group (p=0.013).Conclusions: “T2/FLAIR mismatch” sign was a specific finding for astrocytic tumor, and the cases with positive “T2/FLAIR mismatch” sign had significantly lower MET-PET uptake than that with negative cases.

Molecular Classification of Gliomas is Associated with Seizure Control: A Retrospective Analysis.

Classically, histologic grading of gliomas has been used to predict seizure association, with low-grade gliomas associated with an increased incidence of seizures compared to high-grade gliomas. In 2016, WHO reclassified gliomas based on histology and molecular characteristics. We sought to determine whether molecular classification of gliomas is associated with preoperative seizure presentation and/or post-operative seizure control across multiple glioma subtypes. All gliomas operated at our institution from 2007 to 2017 were identified based on ICD 9 and 10 billing codes and were retrospectively assessed for molecular classification of the IDH1 mutation, and 1p/19q codeletion. Logistic regression models were performed to assess associations of seizures at presentation as well as post-operative seizures with IDH status and the new WHO integrated classification. Our study included 376 patients: 82 IDH mutant and 294 IDH wildtype. The presence of IDH mutation was associated with seizures at presentation [OR 3.135 (1.818-5.404), p<0.001]. IDH-mutant glioblastomas presented with seizures less often than other IDH-mutant glioma subtypes grade II and III [OR 0.104 (0.032-0.340), p<0.001]. IDH-mutant tumors were associated with worse post-operative seizure outcomes, demonstrated by Engel Class [OR 2.666 (1.592-4.464), p<0.001]. IDH mutation in gliomas is associated with an increased risk of seizure development and worse post-operative seizure control, in all grades except for GBM.

GNG5 is an unfavourable independent prognostic indicator of gliomas.

Gliomas are the most common primary brain tumours, and glioblastomas (GBMs) are subgrouped into four distinct molecular subtypes. This study aimed to identify the potential gene related to glioma progression. Weighted gene co‐expression network analysis (WGCNA) was used to explore the related gene. Correlation, ROC, survival and Cox regression analyses were performed. Blue module was strongly associated with WHO grade (r = .65, P = 1e‐19). GNG5 in gliomas was overexpressed compared with normal samples and associated with clinicopathologic characteristics. GNG5 was frequent in Mesenchymal subtype and lowly expressed in Proneural subtype of GBMs. Survival and Cox regression analyses showed that glioma patients with GNG5 overexpression had shorter survival time, and GNG5 was an independent prognostic indicator of overall survival. Overall, GNG5 expression is closely associated with clinicopathologic characteristics and is an independent prognostic indicator for glioma patients, as well as a promising subtype‐associated biomarker in molecular classification of gliomas.

Characteristics of the isocitrate dehydrogenase gene and telomerase reverse transcriptase promoter mutations in gliomas in Chinese patients.

ObjectivesTo explore the characteristics of IDH and TERT promoter mutations in gliomas in Chinese patients.MethodsA total of 124 Chinese patients with gliomas were enrolled to study the frequencies of mutations in isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase promoter (TERTp). Among the 124 patients, 59 patients were enrolled to study the classification of gliomas based on mutations in IDH and TERTp.ResultsIsocitrate dehydrogenase mutations are positively correlated with a good prognosis but mutations in TERTp cannot predict prognoses independently. The combined analysis of the mutations of IDH and TERTp can predict the prognosis more accurately. Patients with IDH and TERTp glioma mutations have the best prognosis, followed by only IDH mutation patients and only TERTp mutation patients, which have the worst prognosis. IDH and TERTp mutations occur frequently in males, younger patients or lower‐grade patients. In contrast, only TERTp mutations occur frequently in females, older patients or higher‐grade patients.ConclusionsPatients with IDH and TERTp glioma mutations have the best prognosis, and only IDH mutation patients and only TERTp mutation patients have the worst prognosis. Moreover, the molecular classification of gliomas by mutations of IDH and TERTp is not suitable for pediatric patients.

Abstract 4238: DNA-methylation based epigenetic signatures predict and deconvolute somatic genomic alterations in gliomas

Abstract PURPOSE: Genomic alterations classify cancers into subtypes with distinct clinical management and prognoses. Molecular classification of gliomas, the most common and lethal primary brain tumor, define tumors into distinct biologic and clinical entities. Mutation of isocitrate dehydrogenese (IDH) is associated with hypermethylation of CpG sites in gene promotors. Other alterations, including telomerase (TERTp) mutation, ATRX mutation, chromosome 1p/19q co-deletion (1p19q codel), and gene expression subtype (Classical/CL, Mesenchymal/MES, Proneural/PN), have yet to be associated with an epigenetic signature. We hypothesized that DNA methylation signatures would classify gliomas based on genetic alterations and give insight into the development of each subtype. The resulting platform functions as a unified diagnostic (UniD) with high processivity applicable to clinical diagnosis and generalizable across molecular oncology. METHODS: Machine learning algorithms were applied to whole methylome data to build classifiers for IDH, TERTp, and ATRX mutations; 1p19q codel and gene expression subtype. Models were validated with data from a phase III trial of anaplastic gliomas. RESULTS: Individual models were generated and prediction accuracies for IDH, TERTp, and ATRX mutations, and 1p19q codel were 100%, 98.3%, 90.48%, and 99.21% in test set and 89.9%, 82.8%, 92.47%, and 89.99% in the validation clinical trial data. The prediction model for gene expression subtype, a previously reported classifier enriched for characteristic somatic alterations, achieved 72% accuracy. Analysis of the misclassified cases revealed that the characteristic alterations associated with the expression subtypes were more correctly classified by methylation than by gene expression. Methylation-determined CL subtype showed high EGFR (p-value = 0.04) and amplification (p-value = 0.00019) compared to transcriptional MES samples, and low expression (p-value = 0.08) and amplification (p-value = 0.056) in methylation-determined MES but transcriptional CL samples. CONCLUSION: Distinct DNA methylation signatures were associated with key somatic genomic alterations in gliomas. It improved the existing classifiers based on gene expression and provided a unique clinical diagnostic platform for rapid determination of glioma subtype at the time of patient diagnosis. The extensive and significant relationship between cancer epigenetic signatures indicates that this approach would have broad applicability to other tumor types and lead to similar unified diagnostic platforms. A R package (UniD) is provided for implantation of this diagnostic platform. Citation Format: Jie Yang, Qianghu Wang, Ravesanker Ezhilarasan, Lihong Long, Benedikt Wiestler, Wolfgang Wick, Yinsen Miao, Erik Sulman. DNA-methylation based epigenetic signatures predict and deconvolute somatic genomic alterations in gliomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4238.

Abstract 482: Recurrent glioma with lineage conversion from oligodendroglioma to astrocytoma: Another facet of glioma evolution during recurrence

Abstract Background: Following the introduction of the molecular classification of gliomas by the WHO in 2016, molecularly-proven lineage conversion during glioma recurrence has never been reported. Methods: We analyzed two cases of recurrent glioma that began as oligodendroglioma, both histologically and molecularly, but converted to astrocytoma over episodes of recurrence. Results: The cases were initially diagnosed as oligodendroglioma with 1p/19q-codeletion and mutation of isocitrate dehydrogenase 1 (IDH1)-R132H. The recurrent tumors showed loss of alpha-thalassemia/mental retardation X-linked (ATRX) expression, strong P53 positivity, and 1p/19q-nondeletion. Next generation sequencing (NGS) analysis performed on the first case confirmed the transition of molecular traits from oligodendroglioma to astrocytoma. An IDH mutation of R132H was preserved in the episodes of recurrence, but ATRX and TP53 mutations were newly acquired and TERT promoter mutation C228T was lost at the most recent recurrence. Conclusions: The issue in question for the presented cases is whether the original tumors were pure oligodendrogliomas that then transdifferentiated into astrocytomas, or whether the original tumor was an oligoastrocytoma having oligodendroglioma cells that outnumbered the astrocytoma cells and where the astrocytoma cells becoming more dominant over the episodes of recurrence. With the recognition of the possibility of lineage conversion, our study suggests that molecular examination should be performed to adjust therapeutic strategies in recurrent gliomas. Indeed, our observation of lineage conversion in glioma recurrence calls into question the current distinction drawn between oligodendroglioma, astrocytoma and oligoastrocytoma, rather than simply bidding “farewell to oligoastrocytoma”. Citation Format: Kyung-Hwa Lee, Tae-Young Jung, Shin Jung, Jae-Hyuk Lee, Kyung-Keun Kim, Hangun Kim, Kyung-Sub Moon. Recurrent glioma with lineage conversion from oligodendroglioma to astrocytoma: Another facet of glioma evolution during recurrence [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 482.

Abstract B58: The effect of differential miRNA expression in glioblastoma multiforme molecular subtypes

Abstract Glioblastoma multiforme (GBM) is characterized by a distinct profile of specific miRNAs that regulate pathways of therapeutic importance, such as cell proliferation, apoptosis, cell cycle regulation, migration, invasion, and angiogenesis. Recently, the molecular classification of gliomas was updated, and three methylation clusters with distinct prognostic values for GBM were characterized. The aim of this research is to evaluate the expression, the functional roles, and the target genes of the miRNAs that have potential value for diagnosis, prognosis, and treatment in patients within the newest molecular subgroup classification of GBM. First, we performed an in silico analysis 606 GBM samples from the Genome Data Commons (GDC) cohort. Based on the methylation subgroups of gliomas recently published (Cecarelli et al., 2016), we performed a comparison of the miRNA expression between LGm4, LGm5, and LGm6 subgroups through Nexus Expression 3.0 (Biodiscovery). The comparison between LGm4 x LGm6 indicated that eight miRNAs were upregulated, while 17 were downregulated. The LGm5 x LGm4 comparison showed two downregulated miRNAs, and the LGm5 x LGm6 comparison showed one upregulated miRNA. By comparing the differentially expressed miRNAs found in our analysis with two other in silico studies, we found an overlap of 54% of the differentially expressed miRNAs. We will now evaluate the expression levels of the upregulated miRNAs obtained through the in silico analysis of samples of the Hospital of Clinics - Faculty of Medicine of Ribeirão Preto (HCFMRP/USP) through a customized nCounter NanoString panel of 24 miRNA. We will also evaluate the plasma exosomal miRNAs from the same patients using the same 24 miRNA nCounter NanoString panel. By identifying the most significant miRNAs regulating cell proliferation and invasive behavior in this tumor, we will be able to use expression levels of the most informative miRNA to both guide the molecular diagnosis of GBM and facilitate future targeted therapeutics for this aggressive disease. Citation Format: Livia Ferreira Silva Verzola, Thiago Vidotto, Jeremy Andrew Squire. The effect of differential miRNA expression in glioblastoma multiforme molecular subtypes [abstract]. In: Proceedings of the AACR International Conference held in cooperation with the Latin American Cooperative Oncology Group (LACOG) on Translational Cancer Medicine; May 4-6, 2017; São Paulo, Brazil. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(1_Suppl):Abstract nr B58.

Advance of molecular subtyping and precise treatment for gliomas

With the advance of genomics research, there have been a new breakthrough in the molecular classification of gliomas. Glioblastoma (WHO grade Ⅳ) could be subtyped to proneural, neural, classical, and mesochymal according to the mRNA expression. Lower grade gliomas (WHO grade Ⅱ and Ⅲ) could be divided into 5 types using 1p/19q co-deletion, isocitrate dehydrogenase(IDH) mutation, and TERTp (promotor region) mutation. In 2016, a new classification of tumors of the central nervous system was proposed, and some new markers such as IDH1 mutation were introduced into the diagnosis of gliomas. Genotype and phenotype were integrated to diagnose gliomas. In the meantime, precision treatment for gliomas has also been vigorously developed. This article reviewed recent studies on the molecular diagnosis, precise chemotherapy, targeted therapy, and immunotherapy for gliomas to provide new ideas and strategies for precise diagnosis and treatment of gliomas.

Chapter 6 - Molecular classification of gliomas

The identification of distinct genetic and epigenetic profiles in different types of gliomas has revealed novel diagnostic, prognostic, and predictive molecular biomarkers for refinement of glioma classification and improved prediction of therapy response and outcome. Therefore, the new (2016) World Health Organization (WHO) classification of tumors of the central nervous system breaks with the traditional principle of diagnosis based on histologic criteria only and incorporates molecular markers. This will involve a multilayered approach combining histologic features and molecular information in an "integrated diagnosis". We review the current state of diagnostic molecular markers for gliomas, focusing on isocitrate dehydrogenase 1 or 2 (IDH1/IDH2) gene mutation, α-thalassemia/mental retardation syndrome X-linked (ATRX) gene mutation, 1p/19q co-deletion and telomerase reverse transcriptase (TERT) promoter mutation in adult tumors, as well as v-raf murine sarcoma viral oncogene homolog B1 (BRAF) and H3 histone family 3A (H3F3A) aberrations in pediatric gliomas. We also outline prognostic and predictive molecular markers, including O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation, and discuss the potential clinical relevance of biologic glioblastoma subtypes defined by integration of multiomics data. Commonly used methods for individual marker detection as well as novel large-scale DNA methylation profiling and next-generation sequencing approaches are discussed. Finally, we illustrate how advances in molecular diagnostics affect novel strategies of targeted therapy, thereby raising new challenges and identifying new leads for personalized treatment of glioma patients.

CNS cancer: molecular classification of glioma.

CNS cancer: molecular classification of glioma.

Cluster analysis and significance of novel genes related to molecular classification of glioma

To screen differentially expressed genes in the development of human glioma and establish a primary molecular classification of glioma based on gene expression using cDNA microarrays. Brain specimens were obtained from 18 patients with glioma, 10 males and 8 females, ages 14–62 with an average age of 44.4. The total RNAs of these glioma specimens and two specimens of donated brain of normal adults were extracted. BioStarH140S microarrays (including 8,347 old genes and 5,592 novel genes) were adopted and hybridized with probes which were prepared from the total RNAs. Differentially expressed genes between normal tissues and glioma tissues were assayed after scanning cDNA microarrays with ScanArray4000. Northern hybridization and in situ hybridization (ISH) were used to identify functions of novel genes. Those differentially expressed genes were studied with a Hierarchical method and molecular classification of glioma was preliminary carried out. Among the 13,939 target genes, there were 1,200 (8.61% ) differentially expressed genes, of which 395 (2.83%) were novel genes. A total of 348 genes were up—regulated and 852 genes were down—regulated in the gliomas. The results of bioinformatical analysis, Northern hybridization and ISH revealed that those novel genes were highly associated with gliomas. There were multiple genes, such as the MAP gene cytoskeleton & matrix motility genes, etc, which were of relevance to classification by the Hierarchical method. Molecular classification of glioma using a Hierarchical cluster was in accordance with pathology and suggested a molecular process of tumorigenesis and development. Multiple genes play important roles in development of glioma. cDNA microarray technology is a powerful technique in screening for differentially expressed genes between two different kinds of tissues. Further analysis of gene expression and novel genes would be helpful to understand the molecular mechanism of glioma development.

PAI-1 and EGFR expression in adult glioma tumors: toward a molecular prognostic classification

Purpose : Molecular classification of gliomas is a major challenge in the effort to improve therapeutic decisions. The plasminogen activator system, including plasminogen activator inhibitor type 1 (PAI-1), plays a key role in tumor invasion and neoangiogenesis. Epidermal growth factor receptor (EGFR) is involved in the control of proliferation. The contribution of PAI-1 and EGFR to the survival of gliomas was retrospectively investigated. Methods and Materials : Fifty-nine adult gliomas treated by neurosurgery and conventional irradiation were analyzed, including 9 low-grade (2) and 50 high-grade (3–4) tumors (WHO classification). PAI-1 was measured on cytosols and EGFR on solubilized membranes using ELISA methods. Results : High PAI-1 levels were strongly associated with high histologic grade ( p < 0.001) and histologic necrosis ( p < 0.001). PAI-1 also correlated positively with patient age ( p = 0.05) and negatively with Karnofsky index ( p = 0.01). By univariate analysis of the high-grade population, higher PAI-1 ( p < 0.0001) and EGFR values ( p = 0.02) were associated with shorter overall survival. Only PAI-1 was an independent factor in multivariate analysis. Grade 3 tumors with low PAI-1 (100% 3-year overall survival rate) presented the same clinical outcome as the low-grade tumors. Conclusions : In this prognostic study, PAI-1 and EGFR expression revealed similarities and differences between high-grade gliomas that were not apparent by traditional clinical criteria. These data strongly support that biologic factors should be included in glioma classification and the design of clinical trials to treat more homogeneous populations.

Toward a molecular classification of the gliomas: histopathology, molecular genetics, and gene expression profiling.

As many as 100,000 new cases of brain tumor are diagnosed each year in the United States. About half of these are primary gliomas and the remaining half are metastatic tumors and non-glial primary tumors. Currently, gliomas are classified based on phenotypic characteristics. Recent progress in the elucidation of genetic alterations found in gliomas have raised the exciting possibility of using genetic and molecular analyses to resolve some of the problematic issues currently associated with the histological approach to glioma classification. Recently, immunohistochemical studies using novel proliferation markers have significantly advanced the assessment of tumor growth potential and the grading criteria of some tumor subtypes. Preliminary studies using cDNA array technologies suggest that the profiling of gene expression patterns may provide a novel and meaningful approach to glioma classification and subclassification. Furthermore, cDNA array technologies may also be used to identify candidate genes involved in glioma tumor development, invasion, and progression. This review summarizes current glioma classification schemes that are based on histopathological characteristics and discusses the potential for using cDNA array technology in the molecular classification of gliomas.