A 16-gene signature distinguishes anaplastic astrocytoma from glioblastoma

Genetic Discrimination of Grade 3 and Grade 4 Gliomas by Artificial Neural Network

Gliomas, including anaplastic gliomas (AG; grade 3) and glioblastomas (GBM; grade 4), are malignant brain tumors associated with poor prognosis and low survival rates. Current classification systems based on histopathology have limitations due to intratumoral heterogeneity. The treatment and prognosis are distinctly different between grade 3 and grade 4 gliomas patients. Therefore, there is a need for molecular markers to differentiate these tumors accurately. In this study, we aimed to identify a gene expression signature using an artificial neural network (ANN) in application to microarray and serial analysis of gene expression (SAGE) data for grade 3 (AG) and grade 4 (GBM) gliomas discrimination. We acquired gene expression data from publicly available datasets on glial tumors of grades 3 and 4-a total of 93 grade 3 gliomas and 224 grade 4 gliomas. To select genes for classification, we implemented an artificial neural network-based method using a combination of self-organized maps (SOM) and perceptron. In general, we implemented a multi-stage procedure that involved multiple runs of a genetic algorithm to identify genes that provided optimal clusterization on the SOM. We performed this procedure multiple times, resulting in different sets of genes each time. Eventually, we selected several genes that appeared most frequently in the reduced sets and performed classification using them. Our analysis identified a set of seven genes (BCAS4, GLUD2, KCNJ10, KCND2, AKR7A2, FOLR1, and KIAA0319). The classification accuracy using this gene set was 87.5%. These findings suggest the potential of this gene set as a molecular marker for distinguishing grade 3 (AG) from grade 4 (GBM) gliomas.

The Transcriptomic Landscape of Pediatric Astrocytoma

Central nervous system tumors are the most common solid neoplasia during childhood and represent one of the leading causes of cancer-related mortality. Tumors arising from astrocytic cells (astrocytomas) are the most frequently diagnosed, and according to their histological and pathological characteristics, they are classified into four categories. However, an additional layer of molecular classification considering the DNA sequence of the tumorigenesis-associated genes IDH1/2 and H3F3A has recently been incorporated into the classification guidelines. Although mutations in H3F3A are found exclusively in a subtype of grade IV pediatric astrocytoma, mutations in IDH1/2 genes are very rare in children under 14 years of age. The transcriptomic profiles of astrocytoma in adults and children have been extensively studied. However, there is scarce information on these profiles in pediatric populations considering the status of tumorigenesis-associated genes. Therefore, here we report the transcriptomic landscape of the four grades of pediatric astrocytoma by RNA sequencing. We found several well-documented biological functions associated with the misregulated genes in the four grades of astrocytoma, as well as additional biological pathways. Among the four grades of astrocytoma, we found shared misregulated genes that could have implications in tumorigenesis. Finally, we identified a transcriptional signature for almost all grades of astrocytoma that could be used as a transcription-based identification method.

The Risk of Heart Disease-Related Death Among Anaplastic Astrocytoma Patients After Chemotherapy: A SEER Population-Based Analysis

Background

Despite improved overall survival outcomes, chemotherapy has brought concerns for heart disease–related death (HDRD) among cancer patients. The effect of chemotherapy on the risk of HDRD in anaplastic astrocytoma (AA) patients remains unclear.

Methods

We obtained 7,129 AA patients from the Surveillance, Epidemiology, and End Results (SEER) database from 1975 to 2016. Kaplan–Meier and Cox regression analysis were conducted to evaluate the effect of chemotherapy on the HDRD risk. Based on the competing risk model, we calculated the cumulative incidences of HDRD and non-HDRD and performed univariate and multivariate regression analyses. Then, a 1:1 propensity score matching (PSM) was used to improve the comparability between AA patients with and without chemotherapy. Landmark analysis at 216 and 314 months was employed to minimize immortal time bias.

Results

AA patients with chemotherapy were at a lower HDRD risk compared to those patients without chemotherapy (adjusted HR=0.782, 95%CI=0.736–0.83, P<0.001). For competing risk regression analysis, the cumulative incidence of HDRD in non-chemotherapy exceeded HDRD in the chemotherapy group (P<0.001) and multivariable analysis showed a lower HDRD risk in AA patients with chemotherapy (adjusted SHR=0.574, 95%CI=0.331–0.991, P=0.046). In the PSM-after cohort, there were no significant association between chemotherapy and the increased HDRD risk (adjusted SHR=0.595, 95%CI=0.316−1.122, P=0.11). Landmark analysis showed that AA patients who received chemotherapy had better heart disease–specific survival than those in the non-chemotherapy group (P=0.007) at the follow-up time points of 216 months. No difference was found when the follow-up time was more than 216 months.

Conclusion

AA patients with chemotherapy are associated with a lower risk of HDRD compared with those without chemotherapy. Our findings may help clinicians make a decision about the management of AA patients and provide new and important evidence for applying chemotherapy in AA patients as the first-line treatment. However, more research is needed to confirm these findings and investigate the correlation of the risk of HDRD with different chemotherapy drugs and doses.

Evidence for age-related contributions of DNA damage and epigenetics in brain tumorigenesis

Glioblastoma (GBM) is a highly malignant primary brain tumour displaying rapid cell proliferation and infiltration. GBM primarily occurs at older age; however, younger populations have also been affected. In GBM and other cancers, genetic and epigenetic alterations promote tumorigenesis causing increased cell proliferation and invasiveness. This investigation explored epigenetic events as contributing factors, especially in gliomas that arise in patients aged 40-60 years. Furthermore, DNA damage in tumours with respect to age was assessed. Archival fixed tissues from 88 cases of glioblastoma and adjacent non-malignant tissues were tested. Global methylation and DNA damage were measured using ELISA detection of 5-methyl cytosine and 8-hydroxy guanine, respectively. IDH mutations and CDKN2 promoter hypermethylation were analysed by pyrosequencing. Tumour tissue was hypomethylated compared with non-malignant tissue (P = .001), and there was a trend towards increased methylation with increasing age. There was a significant increase in DNA damage in patients older than forty years compared with those aged forty years or younger (P = .035). CDKN2 promoter methylation levels followed the age trends of global methylation in this patient group. Patients younger than 60 had more frequently mutated IDH (P = .004). Conclusions: The data support the potential of epigenetic factors in promoting tumorigenesis in younger patients, while increased DNA damage contributes to tumorigenesis in the older patients.

Diosmin Inhibits Glioblastoma Growth through Inhibition of Autophagic Flux

Diosmin, a natural flavone glycoside acquired through dehydrogenation of the analogous flavanone glycoside hesperidin, is plentiful in many citrus fruits. Glioblastoma multiforme (GBM) is the most malignant primary brain tumor; the average survival time of GBM patients is less than 18 months after standard treatment. The present study demonstrated that diosmin, which is able to cross the blood-brain barrier, inhibited GBM cell growth in vitro and in vivo. Diosmin also impeded migration and invasion by GBM8401and LN229 GBM cells by suppressing epithelial-mesenchymal transition, as indicated by increased expression of E-cadherin and decreased expression of Snail and Twist. Diosmin also suppressed autophagic flux, as indicated by increased expression of LC3-II and p62, and induced cell cycle arrest at G1 phase. Importantly, diosmin did not exert serious cytotoxic effects toward control SVG-p12 astrocytes, though it did reduce astrocyte viability at high concentrations. These findings provide potentially helpful support to the development of new therapies for the treatment of GBM.

The Mystery of Multiple Masses: A Case of Anaplastic Astrocytoma

Though most primary brain gliomas present as a single mass lesion in the brain, this potential diagnosis must be considered in the differential diagnosis when faced with a case of multifocal brain mass lesions. Among the most common brain tumors in humans, glioblastomas can be classified into four classes, one of which consists of anaplastic astrocytomas (AA). Due to its significant malignant potential, a prompt stereotactic brain biopsy should be considered to allow for early diagnosis. Karyotypic analysis of the specimen may allow for the discovery of 1p12q and IDH132 gene mutations. This knowledge can be used to best determine prognosis and guide therapy.

DNA methylation signatures for 2016 WHO classification subtypes of diffuse gliomas

Background

Glioma is the most common of all primary brain tumors with poor prognosis and high mortality. The 2016 World Health Organization classification of the tumors of central nervous system uses molecular parameters in addition to histology to redefine many tumor entities. The new classification scheme divides diffuse gliomas into low-grade glioma (LGG) and glioblastoma (GBM) as per histology. LGGs are further divided into isocitrate dehydrogenase (IDH) wild type or mutant, which is further classified into either oligodendroglioma that harbors 1p/19q codeletion or diffuse astrocytoma that has an intact 1p/19q loci but enriched for ATRX loss and TP53 mutation. GBMs are divided into IDH wild type that corresponds to primary or de novo GBMs and IDH mutant that corresponds to secondary or progressive GBMs. To make the 2016 WHO subtypes of diffuse gliomas more robust, we carried out Prediction Analysis of Microarrays (PAM) to develop DNA methylation signatures for these subtypes.

Results

In this study, we applied PAM on a training set of diffuse gliomas derived from The Cancer Genome Atlas (TCGA) and identified DNA methylation signatures to classify LGG IDH wild type from LGG IDH mutant, LGG IDH mutant with 1p/19q codeletion from LGG IDH mutant with intact 1p/19q loci and GBM IDH wild type from GBM IDH mutant with an accuracy of 99–100%. The signatures were validated using the test set of diffuse glioma samples derived from TCGA with an accuracy of 96 to 99%. In addition, we also carried out additional validation of all three signatures using independent LGG and GBM cohorts. Further, the methylation signatures identified a fraction of samples as discordant, which were found to have molecular and clinical features typical of the subtype as identified by methylation signatures.

Conclusions

Thus, we identified methylation signatures that classified different subtypes of diffuse glioma accurately and propose that these signatures could complement 2016 WHO classification scheme of diffuse glioma.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-017-0331-9) contains supplementary material, which is available to authorized users.

Computational analysis of the mesenchymal signature landscape in gliomas

BACKGROUND

Epithelial to mesenchymal transition, and mimicking processes, contribute to cancer invasion and metastasis, and are known to be responsible for resistance to various therapeutic agents in many cancers. While a number of studies have proposed molecular signatures that characterize the spectrum of such transition, more work is needed to understand how the mesenchymal signature (MS) is regulated in non-epithelial cancers like gliomas, to identify markers with the most prognostic significance, and potential for therapeutic targeting.

RESULTS

Computational analysis of 275 glioma samples from "The Cancer Genome Atlas" was used to identify the regulatory changes between low grade gliomas with little expression of MS, and high grade glioblastomas with high expression of MS. TF (transcription factor)-gene regulatory networks were constructed for each of the cohorts, and 5 major pathways and 118 transcription factors were identified as involved in the differential regulation of the networks. The most significant pathway - Extracellular matrix organization - was further analyzed for prognostic relevance. A 20-gene signature was identified as having prognostic significance (HR (hazard ratio) 3.2, 95% CI (confidence interval) = 1.53-8.33), after controlling for known prognostic factors (age, and glioma grade). The signature's significance was validated in an independent data set. The putative stem cell marker CD44 was biologically validated in glioma cell lines and brain tissue samples.

CONCLUSIONS

Our results suggest that the differences between low grade gliomas and high grade glioblastoma are associated with differential expression of the signature genes, raising the possibility that targeting these genes might prolong survival in glioma patients.

A five-miRNA signature with prognostic and predictive value for MGMT promoter-methylated glioblastoma patients

Although O(6)-methylguanine DNA methyltransferase (MGMT) promoter methylation status is an important marker for glioblastoma multiforme (GBM), there is considerable variability in the clinical outcome of patients with similar methylation profiles. The present study aimed to refine the prognostic and predictive value of MGMT promoter status in GBM by identifying a micro (mi)RNA risk signature. Data from The Cancer Genome Atlas was used for this study, with MGMT promoter-methylated samples randomly divided into training and internal validation sets. Data from The Chinese Glioma Genome Atlas was used for independent validation. A five miRNA-based risk signature was established for MGMT promoter-methylated GBM to distinguish cases as high- or low-risk with distinct prognoses, which was confirmed using internal and external validation sets. Importantly, the prognostic value of the signature was significant in different cohorts stratified by clinicopathologic factors and alkylating chemotherapy, and a multivariate Cox analysis found it to be an independent prognostic marker along with age and chemotherapy. Based on these three factors, we developed a quantitative model with greater accuracy for predicting the 1-year survival of patients with MGMT promoter-methylated GBM. These results indicate that the five-miRNA signature is an independent risk predictor for GBM with MGMT promoter methylation and can be used to identify patients at high risk of unfavorable outcome and resistant to alkylating chemotherapy, underscoring its potential for personalized GBM management.

Anaplastic astrocytoma: prognostic factors and survival in 4807 patients with emphasis on receipt and impact of adjuvant therapy

To determine the receipt and impact of adjuvant therapy on overall survival (OS) for anaplastic astrocytoma (AA). Data were extracted from the National Cancer Data Base (NCDB). Chi square test, Kaplan-Meier method, and Cox regression models were employed in SPSS 22.0 (Armonk, NY: IBM Corp.) for data analyses. 4807 patients with AA diagnosed from 2004 to 2013 who underwent surgery were identified. 3243 (67.5 %) received adjuvant chemoRT, 525 (10.9 %) adjuvant radiotherapy (RT) alone, 176 (3.7 %) adjuvant chemotherapy alone and 863 (18.0 %) received no adjuvant therapy. Patients were more likely to receive adjuvant chemoRT if they were diagnosed in 2009-2013 (p = 0.022), were ≤ 50 years (p < 0.001), were male (p = 0.043), were Asian or White race (p < 0.001), had private insurance (p < 0.001), had income ≥$38,000 (p < 0.001), or underwent total resection (p < 0.003). Those who received adjuvant chemoRT had significantly better 5-year OS than the other adjuvant treatment types (41.8 % vs. 31.2 % vs. 29.8 % vs. 27.4 %, p < 0.001). This significant 5-year OS benefit was also observed regardless of age at diagnosis. Of those undergoing adjuvant chemoRT, those receiving ≥59.4 Gy had significantly better 5-year OS than those receiving <59.4 Gy (44.4 % vs. 25.9 %, p < 0.001). There was no significant difference in OS when comparing 59.4 Gy to higher RT doses. On multivariate analysis, receipt of adjuvant chemoRT, age at diagnosis, extent of disease, and insurance status were independent prognostic factors for OS. Adjuvant chemoRT is an independent prognostic factor for improved OS in AA and concomitant chemoRT should be considered for all clinically suitable patients who have undergone surgery for the disease.

Indian data on central nervous tumors: A summary of published work

Tumors of the central nervous system (CNS) constitute approximately 2% of all malignancies. Although relatively rare, the associated morbidity and mortality and the significant proportion of affected young and middle-aged individuals has a major bearing on the death-adjusted life years compared to other malignancies. CNS tumors encompass a very broad spectrum with regards to age, location, histology, and clinical outcomes. Advances in diagnostic imaging, surgical techniques, radiotherapy equipment, and generation of newer chemotherapeutic and targeted agents over the past few years have helped improving treatment outcome. Further insights into the molecular pathways leading to the development of tumors made in the past decade are being incorporated into routine clinical practice. Several focused groups within India have been working on a range of topics related to CNS tumors, and a significant body of work from India, in the recent years, is being increasingly recognized throughout the world. The present article summarizes key published work with particular emphasis on gliomas and medulloblastoma, the two commonly encountered tumors.

KITENIN promotes glioma invasiveness and progression, associated with the induction of EMT and stemness markers

KITENIN (KAI1 COOH-terminal interacting tetraspanin) promotes tumor invasion and metastasis in various cancers. This study assessed the association between KITENIN expression and advanced glioma grade in patients. In vitro assays revealed that KITENIN knockdown inhibited the invasion and migration of glioma cells, whereas KITENIN overexpression promoted their invasion and migration. In orthotopic mouse tumor models, mice transplanted with KITENIN-transfected glioma cells had significantly shorter survival than mice transplanted with mock-transfected cells. Patients with low KITENIN expression showed a significantly longer progression-free survival than patients with high KITENIN expression. KITENIN induced the expression of the epithelial-mesenchymal transition (EMT) markers (N-cadherin, ZEB1, ZEB2, SNAIL and SLUG) as well as the glioma stemness markers (CD133, ALDH1 and EPH-B1). Taken together, these findings showed that high levels of KITENIN increased glioma invasiveness and progression, associated with the up-regulation of EMT and stemness markers.

An Eighteen Serum Cytokine Signature for Discriminating Glioma from Normal Healthy Individuals

Glioblastomas (GBM) are largely incurable as they diffusely infiltrate adjacent brain tissues and are difficult to diagnose at early stages. Biomarkers derived from serum, which can be obtained by minimally invasive procedures, may help in early diagnosis, prognosis and treatment monitoring. To develop a serum cytokine signature, we profiled 48 cytokines in sera derived from normal healthy individuals (n = 26) and different grades of glioma patients (n = 194). We divided the normal and grade IV glioma/GBM serum samples randomly into equal sized training and test sets. In the training set, the Prediction Analysis for Microarrays (PAM) identified a panel of 18 cytokines that could discriminate GBM sera from normal sera with maximum accuracy (95.40%) and minimum error (4.60%). The 18-cytokine signature obtained in the training set discriminated GBM sera from normal sera in the test set as well (accuracy 96.55%; error 3.45%). Interestingly, the 18-cytokine signature also differentiated grade II/Diffuse Astrocytoma (DA) and grade III/Anaplastic Astrocytoma (AA) sera from normal sera very efficiently (DA vs. normal–accuracy 96.00%, error 4.00%; AA vs. normal–accuracy 95.83%, error 4.17%). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using 18 cytokines resulted in the enrichment of two pathways, cytokine-cytokine receptor interaction and JAK-STAT pathways with high significance. Thus our study identified an 18-cytokine signature for distinguishing glioma sera from normal healthy individual sera and also demonstrated the importance of their differential abundance in glioma biology.

Definition of a serum marker panel for glioblastoma discrimination and identification of Interleukin 1β in the microglial secretome as a novel mediator of endothelial cell survival induced by C-reactive protein

Glioblastoma (GBM) is the most common malignant adult primary brain tumor. We profiled 724 cancer-associated proteins in sera of healthy individuals (n=27) and GBM (n=28) using antibody microarray. While 69 proteins exhibited differential abundance in GBM sera, a three-marker panel (LYAM1, BHE40 and CRP) could discriminate GBM sera from that of healthy donors with an accuracy of 89.7% and p<0.0001. The high abundance of C-reactive protein (CRP) in GBM sera was confirmed in 264 independent samples. High levels of CRP protein was seen in GBM but without a change in transcript levels suggesting a non-tumoral origin. Glioma-secreted Interleukin 6 (IL6) was found to induce hepatocytes to secrete CRP, involving JAK-STAT pathway. The culture supernatant from CRP-treated microglial cells induced endothelial cell survival under nutrient-deprivation condition involving CRP-FcγRIII signaling cascade. Transcript profiling of CRP-treated microglial cells identified Interleukin 1β (IL1β) present in the microglial secretome as the key mediator of CRP-induced endothelial cell survival. IL1β neutralization by antibody-binding or siRNA-mediated silencing in microglial cells reduced the ability of the supernatant from CRP-treated microglial cells to induce endothelial cell survival. Thus our study identifies a serum based three-marker panel for GBM diagnosis and provides leads for developing targeted therapies. Biological significance A complex antibody microarray based serum marker profiling identified a three-marker panel - LYAM1, BHE40 and CRP as an accurate discriminator of glioblastoma sera from that of healthy individuals. CRP protein is seen in high levels without a concomitant increase of CRP transcripts in glioblastoma. Glioma-secreted IL6 induced hepatocytes to produce CRP in a JAK-STAT signaling dependent manner. CRP induced microglial cells to release IL1β which in turn promoted endothelial cell survival. This study, besides defining a serum panel for glioblastoma discrimination, identified IL1β as a potential candidate for developing targeted therapy.