Molecular subtypes of glioblastoma are relevant to lower grade glioma

PPAR-γ agonists reactivate the ALDOC-NR2F1 axis to enhance sensitivity to temozolomide and suppress glioblastoma progression

Glioblastoma (GBM) is a type of brain cancer categorized as a high-grade glioma. GBM is characterized by limited treatment options, low patient survival rates, and abnormal serotonin metabolism. Previous studies have investigated the tumor suppressor function of aldolase C (ALDOC), a glycolytic enzyme in GBM. However, it is unclear how ALDOC regulates production of serotonin and its associated receptors, HTRs. In this study, we analyzed ALDOC mRNA levels and methylation status using sequencing data and in silico datasets. Furthermore, we investigated pathways, phenotypes, and drug effects using cell and mouse models. Our results suggest that loss of ALDOC function in GBM promotes tumor cell invasion and migration. We observed that hypermethylation, which results in loss of ALDOC expression, is associated with serotonin hypersecretion and the inhibition of PPAR-γ signaling. Using several omics datasets, we present evidence that ALDOC regulates serotonin levels and safeguards PPAR-γ against serotonin metabolism mediated by 5-HT, which leads to a reduction in PPAR-γ expression. PPAR-γ activation inhibits serotonin release by HTR and diminishes GBM tumor growth in our cellular and animal models. Importantly, research has demonstrated that PPAR-γ agonists prolong animal survival rates and increase the efficacy of temozolomide in an orthotopic brain model of GBM. The relationship and function of the ALDOC-PPAR-γ axis could serve as a potential prognostic indicator. Furthermore, PPAR-γ agonists offer a new treatment alternative for glioblastoma multiforme (GBM).

Global analysis of iron metabolism-related genes identifies potential mechanisms of gliomagenesis and reveals novel targets

AIMS

This study aimed to investigate key regulators of aberrant iron metabolism in gliomas, and evaluate their effect on biological functions and clinical translational relevance.

METHODS

We used transcriptomic data from multiple cross-platform glioma cohorts to identify key iron metabolism-related genes (IMRGs) based on a series of bioinformatic and machine learning methods. The associations between IMRGs and prognosis, mesenchymal phenotype, and genomic alterations were analyzed in silico. The performance of the IMRGs-based signature in predicting temozolomide (TMZ) treatment sensitivity was evaluated. In vitro and in vivo experiments were used to explore the biological functions of these key IMRGs.

RESULTS

HMOX1, LTF, and STEAP3 were identified as the most essential IMRGs in gliomas. The expression levels of these genes were strongly related to clinicopathological and molecular features. The robust IMRG-based gene signature could be used for prognosis prediction. These genes facilitate mesenchymal transformation, driver gene mutations, and oncogenic alterations in gliomas. The gene signature was also associated with TMZ resistance. HMOX1, LTF, and STEAP3 knockdown in glioma cells significantly reduced cell proliferation, colony formation, migration, and malignant invasion.

CONCLUSION

The study presented a comprehensive view of key regulators underpinning iron metabolism in gliomas and provided new insights into novel therapeutic approaches.

Diagnostic Utility of Immunohistochemical Detection of MEOX2, SOX11, INSM1 and EGFR in Gliomas

Histological identification of dispersed glioma cells in small biopsies can be challenging, especially in tumours lacking the IDH1 R132H mutation or alterations in TP53. We postulated that immunohistochemical detection of proteins expressed preferentially in gliomas (EGFR, MEOX2, CD34) or during embryonal development (SOX11, INSM1) can be used to distinguish reactive gliosis from glioma. Tissue microarrays of 46 reactive glioses, 81 glioblastomas, 34 IDH1-mutant diffuse gliomas, and 23 gliomas of other types were analysed. Glial neoplasms were significantly more often (p < 0.001, χ2) positive for EGFR (34.1% vs. 0%), MEOX2 (49.3% vs. 2.3%), SOX11 (70.5% vs. 20.4%), and INSM1 (65.4% vs. 2.3%). In 94.3% (66/70) of the glioblastomas, the expression of at least two markers was observed, while no reactive gliosis showed coexpression of any of the proteins. Compared to IDH1-mutant tumours, glioblastomas showed significantly higher expression of EGFR, MEOX2, and CD34 and significantly lower positivity for SOX11. Non-diffuse gliomas were only rarely positive for any of the five markers tested. Our results indicate that immunohistochemical detection of EGFR, MEOX2, SOX11, and INSM1 can be useful for detection of glioblastoma cells in limited histological samples, especially when used in combination.

The clinical value of proneural, classical and mesenchymal protein signatures in WHO 2021 adult-type diffuse lower-grade gliomas

OBJECTIVES

Accumulating evidence shows that mesenchymal transition of glioblastomas is associated with a more aggressive course of disease and therapy resistance. In WHO2021-defined adult-type diffuse gliomas of lower grade (dLGG), the transition of the tumor phenotype over time, has not been studied. Most efforts to correlate proneural, classical or mesenchymal phenotype with outcome in dLGG were made prior to the WHO 2021 classification. Here, we set out to investigate if phenotype predicted survival and tumor recurrence in a clinical cohort of dLGGs, re-classified according to the 2021 WHO criteria.

METHODS

Using a TMA-based approach with five immunohistochemical markers (EGFR, p53, MERTK, CD44 and OLIG2), we investigated 183 primary and 49 recurrent tumors derived from patients with previously diagnosed dLGG. Of the 49 relapses, nine tumors recurred a second time, and one a third time.

RESULTS

In total, 71.0% of all tumors could be subtyped. Proneural was most dominant in IDH-mut tumors (78.5%), mesenchymal more common among IDH-wt tumors (63.6%). There was a significant difference in survival between classical, proneural and mesenchymal phenotypes in the total cohort (p<0.001), but not after molecular stratification (IDH-mut: p = 0.220, IDH-wt: p = 0.623). Upon recurrence, proneural was retained in 66.7% of the proneural IDH-mut dLGGs (n = 21), whereas IDH-wt tumors (n = 10) mainly retained or gained mesenchymal phenotype. No significant difference in survival was found between IDH-mut gliomas remaining proneural and those shifting to mesenchymal phenotype (p = 0.347).

CONCLUSION

Subtyping into classical, proneural and mesenchymal phenotypes by five immunohistochemical markers, was possible for the majority of tumors, but protein signatures did not correlate with patient survival in our WHO2021-stratified cohort. At recurrence, IDH-mut tumors mainly retained proneural, while IDH-wt tumors mostly retained or gained mesenchymal signatures. This phenotypic shift, associated with increased aggressiveness in glioblastoma, did not affect survival. Group sizes were, however, too small to draw any firm conclusions.

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.

High APLN Expression Predicts Poor Prognosis for Glioma Patients

Apelin (APLN) is an endogenous ligand of the G protein-coupled receptor APJ (APLNR). APLN/APLNR system was involved in a variety of pathological and physiological functions, such as tumorigenesis and development. However, its prognostic roles in patients with central nervous system (CNS) cancers remain unknown. The present study was designed to explore the expression profile, prognostic significance, and interaction network of APLN/APLNR by integrating data from Oncomine, GEPIA, LOGpc, STRING, GeneMANIA, and immunohistochemical staining. The results demonstrated that APLN and APLNR mRNA expression were significantly increased in CNS cancers, including both low-grade glioma (LGG) and glioblastoma (GBM), when compared with normal CNS tissues. The high APLN, but not APLNR, expression was significantly correlated with overall survival (OS), recurrence free survival (RFS), and progression free survival (PFS) of LGG patients. However, neither APLN nor APLNR expression was significantly related to prognostic value in terms of OS, disease free interval (DFI), disease specific survival (DSS), or progression free interval (PFI) for GBM patients. Additionally, immunohistochemistry staining confirmed the increased APLN expression in tissues of LGG patients with grade II than grade I. These results showed that an elevated APLN level could predict poor OS, RFS, and PFS for LGG patients, and it could be a promising prognostic biomarker for LGG.

Development and validation of an immune-related gene signature for predicting the radiosensitivity of lower-grade gliomas

Radiotherapy is an important treatment modality for lower-grade gliomas (LGGs) patients. This analysis was conducted to develop an immune-related radiosensitivity gene signature to predict the survival of LGGs patients who received radiotherapy. The clinical and RNA sequencing data of LGGs were obtained from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). Lasso regression analyses were used to construct a 21-gene signature to identify the LGGs patients who could benefit from radiotherapy. Based on this radiosensitivity signature, patients were classified into a radiosensitive (RS) group and a radioresistant (RR) group. According to the Kaplan–Meier analysis results of the TCGA dataset and the two CGGA validation datasets, the RS group had a higher overall survival rate than that of the RR group. This gene signature was RT-specific and an independent prognostic indicator. The nomogram model performed well in predicting 3-, and 5-year survival of LGGs patients after radiotherapy by this gene signature and other clinical factors (age, sex, grade, IDH mutations, 1p/19q codeletion). In summary, this signature is a powerful supplement to the prognostic factors of LGGs patients with radiotherapy and may provide an opportunity to incorporate individual tumor biology into clinical decision making in radiation oncology.

ME2 Promotes Proneural-Mesenchymal Transition and Lipogenesis in Glioblastoma

Malic enzyme 2 (ME2) catalyzes the formation of pyruvate from malic acid and is abnormally expressed in some tumors. However, the exact effects of ME2 on proneural–mesenchymal transition (PMT) and lipogenesis in glioblastoma multiforme (GBM) remain unexplored. Here, we found that ME2 expression was significantly higher in GBM than in normal brain tissues and negatively correlated with overall survival of patients with GBM. Furthermore, we demonstrated that ME2 was positively correlated with mesenchymal features in GBM and promoted proliferation, migration, and invasion of glioma cells. Moreover, ME2 upregulated the expression of mesenchymal markers (N-cadherin, vimentin, YKL40, and MET), whereas it inhibited the expression of proneural maker OLIG2, indicating that ME2 might promote PMT in GBM. We also found that ME2 inhibited the production of mitochondrial reactive oxygen species and AMPK phosphorylation, resulting in SREBP-1 maturation and nuclear localization and enhancing the ACSS2 lipogenesis pathway. Taken together, these results suggest that ME2 promotes PMT and is linked with reprogramming of lipogenesis via AMPK–SREBP-1–ACSS2 signaling in GBM. Therefore, ME2 has potential as a new classification marker in GBM and could provide a new approach to glioma treatment.

An Immune-Related Gene Pairs Signature Predicts Prognosis and Immune Heterogeneity in Glioblastoma

Purpose

Glioblastoma is one of the most aggressive nervous system neoplasms. Immunotherapy represents a hot spot and has not been included in standard treatments of glioblastoma. So in this study, we aim to filtrate an immune-related gene pairs (IRGPs) signature for predicting survival and immune heterogeneity.

Methods

We used gene expression profiles and clinical information of glioblastoma patients in the TCGA and CGGA datasets, dividing into discovery and validation cohorts. IRGPs significantly correlative with prognosis were selected to conduct an IRGPs signature. Low and high risk groups were separated by this IRGPs signature. Univariate and multivariate cox analysis were adopted to check whether risk can be a independent prognostic factor. Immune heterogeneity between different risk groups was analyzed via immune infiltration and gene set enrichment analysis (GSEA). Some different expressed genes between groups were selected to determine their relationship with immune cells and immune checkpoints.

Results

We found an IRGPs signature consisting of 5 IRGPs. Different risk based on IRGPs signature is a independent prognostic factor both in the discovery and validation cohorts. High risk group has some immune positive cells and more immune repressive cells than low risk group by means of immune infiltration. We discovered some pathways are more active in the high risk group, leading to immune suppression, drug resistance and tumor evasion. In two specific signaling, some genes are over expressed in high risk group and positive related to immune repressive cells and immune checkpoints, which indicate aggression and immunotherapy resistance.

Conclusion

We identified a robust IRGPs signature to predict prognosis and immune heterogeneity in glioblastoma patients. Some potential targets and pathways need to be further researched to make different patients benefit from personalized immunotherapy.

CAMTA1, a novel antitumor gene, regulates proliferation and the cell cycle in glioma by inhibiting AKT phosphorylation

Identifying biomarkers for the early diagnosis of glioma and elucidating the molecular mechanisms underlying the development of this cancer are of considerable clinical importance. Recently, studies performing microarray profiling of genes to identify distinct gene signatures reported specific subtypes with predictive and prognostic relevance. Thus, we performed deep sequencing on a total of 26 glioma tissue samples to identify the frequently mutated of oncogenes and tumor suppressors in gliomas. A total of 2306 single-nucleotide polymorphisms (SNPs) and 2010 insertion and deletion sites (indels) were found by aligning sequencing information from 26 glioma samples with sequences from the normal human gene database (GRCh37/hg19). GSEA results suggest that an underexpressed gene, calmodulin binding transcription activator 1 (CAMTA1), participates in the cell proliferation and cell cycle regulation of glioma cells. Moreover, overexpression of CAMTA1 in glioma cells notably inhibited cell growth, migration, invasion and cell cycle and enhanced temozolomide (TMZ)-induced cell apoptosis in glioma cells, while CAMTA1 overexpression decreased the ITGA5, ITGB1, p-AKT, p-FAK, and Myc protein levels, suggesting that the signaling pathways of these proteins might be involved in the cellular functions of CAMTA1 in glioma. Moreover, overexpression of CAMTA1 attenuated the growth and tumorigenesis of glioma in vivo. In summary, we identified high-frequency mutant genes in glioma and provided an experimental basis for a novel mechanism by which CAMTA1 may serve as a tumor suppressor in glioma.

The role of neuropathology in the management of newly diagnosed glioblastoma: a systematic review and evidence-based clinical practice guideline

TARGET POPULATION

These recommendations apply to adult patients with newly diagnosed or suspected glioblastoma (GBM) QUESTION : For adult patients with newly diagnosed GBM does testing for Isocitrate Dehydrogenase 1 or 2 (IDH 1/2) mutations afford benefit beyond standard histopathology in providing accurate classification and outcome prognostication? Level III IDH 1/2 mutational status by immunohistochemistry (IHC) and/or sequencing is suggested for classification and prognostic information. Level III Non-canonical IDH 1/2 mutations are very rare in patients aged 55 or older and universal testing of variant mutations by sequence analysis is not suggested for this age range.

QUESTION

For adult patients with lower grade infiltrating astrocytomas (WHO grades II and III) can the IDH-wildtype status designation supersede histopathology to predict prognosis and biologic relevance to eventual behavior as a GBM? Level III The designation of infiltrating astrocytomas (WHO grades II and III) as IDH-wildtype is not suggested as sufficient for a higher grade designation alone. Level III It is suggested that IDH-wildtype WHO grades II and III astrocytomas be tested for molecular-genetic alterations typical of IDH-wildtype GBM such as EGFR amplification, gain of chromosome 7/loss of chromosome 10 and TERT-p mutation to substantiate prediction of behavior similar to IDH-wildtype glioblastoma. Level III It is suggested that a diagnosis of diffuse astrocytic glioma, IDH-wildtype, with molecular features of GBM, WHO grade IV be rendered for infiltrating astrocytomas that lack histologic criteria of GBM but harbors molecular-genetic alterations of IDH-wildtype glioblastoma.

QUESTION

For adult patients with newly diagnosed infiltrating glioma arising in the midline does testing for H3-K27M mutations provide information beyond that gained by histopathology for accurate classification and outcome prognostication? Level III It is suggested that infiltrating gliomas arising in midline anatomic locations be tested for the H3-K27M mutation as they tend to exhibit WHO grade IV behavior even if they lack histologic criteria for glioblastoma.

Long noncoding RNA LIFR-AS1 suppresses proliferation, migration and invasion and promotes apoptosis through modulating miR-4262/NF-κB pathway in glioma

AIM

This study aimed to explore the role of lncRNA leukemia inhibitory factor receptor antisense RNA 1 (LIFR-AS1) on glioma and its underlying molecular mechanism.

METHODS

The expression of LIFR-AS1 and miR-4262 was detected by quantitative real-time polymerase chain reaction (qRT-RCR) in both glioma tissues and cell lines. Colony formation assay, 5-ethynyl-20-deoxyuridine (EdU) assay, flow cytometry and transwell assay were respectively conducted to detect cell clones, proliferation, apoptosis, migration and invasion. The effect of LIFR-AS1 on the chemoresistance to temozolomide (TMZ) of glioma cells was also analyzed. In addition, dual-luciferase reporter gene assay was performed to evaluate the luciferase activity. The expressions of nuclear factor-κB (NF-κB) p65, p-NF-κB p65 and inhibitor of κBα (IκBα) in glioma cells were measured by western blot.

RESULTS

LIFR-AS1 was lowly expressed and miR-4262 was highly expressed in glioma tissues and cell lines. LIFR-AS1 overexpression inhibited the proliferation, migration and invasion and promoted apoptosis of glioma cells. LIFR-AS1 overexpression also reduced the chemoresistance to TMZ of glioma cells. Moreover, LIFR-AS1 overexpression suppressed the activation of NF-κB signaling pathway in glioma cells. miR-4262 was the target gene of LIFR-AS1. We also found that miR-4262 abrogated the functions of LIFR-AS1 on cell proliferation, apoptosis, migration and invasion of glioma cells in the NF-κB pathway.

CONCLUSION

LIFR-AS1 could suppress the proliferation, migration and invasion and promote the apoptosis through modulating miR-4262/NF-κB pathway in glioma.

Profiling pro-neural to mesenchymal transition identifies a lncRNA signature in glioma

Background

Molecular classification has laid the framework for exploring glioma biology and treatment strategies. Pro-neural to mesenchymal transition (PMT) of glioma is known to be associated with aggressive phenotypes, unfavorable prognosis, and treatment resistance. Recent studies have highlighted that long non-coding RNAs (lncRNAs) are key mediators in cancer mesenchymal transition. However, the relationship between lncRNAs and PMT in glioma has not been systematically investigated.

Methods

Gene expression profiles from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), GSE16011, and Rembrandt with available clinical and genomic information were used for analyses. Bioinformatics methods such as weighted gene co-expression network analysis (WGCNA), gene set enrichment analysis (GSEA), Cox analysis, and least absolute shrinkage and selection operator (LASSO) analysis were performed.

Results

According to PMT scores, we confirmed that PMT status was positively associated with risky behaviors and poor prognosis in glioma. The 149 PMT-related lncRNAs were identified by WGCNA analysis, among which 10 (LINC01057, TP73-AS1, AP000695.4, LINC01503, CRNDE, OSMR-AS1, SNHG18, AC145343.2, RP11-25K21.6, RP11-38L15.2) with significant prognostic value were further screened to construct a PMT-related lncRNA risk signature, which could divide cases into two groups with distinct prognoses. Multivariate Cox regression analyses indicated that the signature was an independent prognostic factor for high-grade glioma. High-risk cases were more likely to be classified as the mesenchymal subtype, which confers enhanced immunosuppressive status by recruiting macrophages, neutrophils, and regulatory T cells. Moreover, six lncRNAs of the signature could act as competing endogenous RNAs to promote PMT in glioblastoma.

Conclusions

We profiled PMT status in glioma and established a PMT-related 10-lncRNA signature for glioma that could independently predict glioma survival and trigger PMT, which enhanced immunosuppression.

The CNS and the Brain Tumor Microenvironment: Implications for Glioblastoma Immunotherapy

Glioblastoma (GBM) is the most common and aggressive malignant primary brain tumor in adults. Its aggressive nature is attributed partly to its deeply invasive margins, its molecular and cellular heterogeneity, and uniquely tolerant site of origin—the brain. The immunosuppressive central nervous system (CNS) and GBM microenvironments are significant obstacles to generating an effective and long-lasting anti-tumoral response, as evidenced by this tumor’s reduced rate of treatment response and high probability of recurrence. Immunotherapy has revolutionized patients’ outcomes across many cancers and may open new avenues for patients with GBM. There is now a range of immunotherapeutic strategies being tested in patients with GBM that target both the innate and adaptive immune compartment. These strategies include antibodies that re-educate tumor macrophages, vaccines that introduce tumor-specific dendritic cells, checkpoint molecule inhibition, engineered T cells, and proteins that help T cells engage directly with tumor cells. Despite this, there is still much ground to be gained in improving the response rates of the various immunotherapies currently being trialed. Through historical and contemporary studies, we examine the fundamentals of CNS immunity that shape how to approach immune modulation in GBM, including the now revamped concept of CNS privilege. We also discuss the preclinical models used to study GBM progression and immunity. Lastly, we discuss the immunotherapeutic strategies currently being studied to help overcome the hurdles of the blood–brain barrier and the immunosuppressive tumor microenvironment.

Low Expression of APOB mRNA or Its Hypermethylation Predicts Favorable Overall Survival in Patients with Low-Grade Glioma

Background

This study was performed to explore the clinical and prognostic significance of APOB mRNA expression, DNA methylation and APOB mutation in patients with low-grade glioma (LGG).

Methods

Bioinformatic analysis was conducted using genomic, clinical and survival data from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Serum APOB protein levels were measured via immunoturbidimetry in 150 patients with LGG and 100 healthy controls from Hubei General Hospital.

Results

There was a negative association between the levels of APOB mRNA and DNA methylation (r=−0.355, P<0.0001) in patients with LGG from the TCGA database. Additionally, LGG patients with low levels of APOB mRNA exhibited better overall survival (OS) than those with high levels of APOB mRNA (HR=0.637, P=0.0085). The survival time of LGG patients with APOB hypermethylation was markedly longer than that of patients with APOB hypomethylation (HR=0.423, P=0.0185). The prognostic significance of APOB mRNA and DNA methylation was also validated with the CGGA cohort, and a similar conclusion was reached. APOB gene mutations were observed in 3% of patients with LGG from the TCGA database, and no association was detected between APOB mutations and OS (P=0.164). Furthermore, the levels of APOB protein were much lower in patients with LGG than in normal individuals (P=0.0022), and the expression of APOB protein was markedly different among groups when stratified by histological type (P<0.0001) and histological-molecular classification (P<0.0001).

Conclusion

APOB mRNA expression is negatively regulated by DNA methylation in patients with LGG. Low expression or hypermethylation of APOB might predict relatively favorable survival in patients with LGG.

Molecular Classification of Diffuse Gliomas

Technological advances in the field of molecular genetics have improved the ability to classify brain tumors into subgroups with distinct clinical features and important therapeutic implications. The World Health Organization’s newest update on classification of gliomas (2016) incorporated isocitrate dehydrogenase 1 and 2 mutations, ATRX loss, 1p/19q codeletion status, and TP53 mutations to allow for improved classification of glioblastomas, low-grade and anaplastic gliomas. This paper reviews current advances in the understanding of diffuse glioma classification and the impact of molecular markers and DNA methylation studies on survival of patients with these tumors. We also discuss whether the classification and grading of diffuse gliomas should be based on histological findings, molecular markers, or DNA methylation subgroups in future iterations of the classification system.

Cellular Plasticity and Tumor Microenvironment in Gliomas: The Struggle to Hit a Moving Target

Brain tumors encompass a diverse group of neoplasias arising from different cell lineages. Tumors of glial origin have been the subject of intense research because of their rapid and fatal progression. From a clinical point of view, complete surgical resection of gliomas is highly difficult. Moreover, the remaining tumor cells are resistant to traditional therapies such as radio- or chemotherapy and tumors always recur. Here we have revised the new genetic and epigenetic classification of gliomas and the description of the different transcriptional subtypes. In order to understand the progression of the different gliomas we have focused on the interaction of the plastic tumor cells with their vasculature-rich microenvironment and with their distinct immune system. We believe that a comprehensive characterization of the glioma microenvironment will shed some light into why these tumors behave differently from other cancers. Furthermore, a novel classification of gliomas that could integrate the genetic background and the cellular ecosystems could have profound implications in the efficiency of current therapies as well as in the development of new treatments.

IDH mutation-specific radiomic signature in lower-grade gliomas

Unravelling the heterogeneity is the central challenge for glioma precession oncology. In this study, we extracted quantitative image features from T2-weighted MR images and revealed that the isocitrate dehydrogenase (IDH) wild type and mutant lower grade gliomas (LGGs) differed in their expression of 146 radiomic descriptors. The logistic regression model algorithm further reduced these to 86 features. The classification model could discriminate the two types in both the training and validation sets with area under the curve values of 1.0000 and 0.9932, respectively. The transcriptome-radiomic analysis revealed that these features were associated with the immune response, biological adhesion, and several malignant behaviors, all of which are consistent with biological processes that are differentially expressed in IDH wild type and IDH mutant LGGs. Finally, a prognostic signature showed an ability to stratify IDH mutant LGGs into high and low risk groups with distinctive outcomes. By extracting a large number of radiomic features, we identified an IDH mutation-specific radiomic signature with prognostic implications. This radiomic signature may provide a way to non-invasively discriminate lower-grade gliomas as with or without the IDH mutation.

Long noncoding RNA TPT1-AS1 downregulates the microRNA-770-5p expression to inhibit glioma cell autophagy and promote proliferation through STMN1 upregulation

Through the microarray analysis, long noncoding RNA TPT1-AS1 (TPT1-AS1) was identified in the development of glioma. However, the specific effect of TPT1-AS1 on glioma autophagy in the recent years has not fully been investigated. Therefore, the purpose of our present study is to investigate the function of TPT1-AS1 on affecting autophagy of glioma cells through regulation of microRNA-770-5p (miR-770-5p)-mediated stathmin 1 (STMN1). Initially, the expression of TPT1-AS1, miR-770-5p, and STMN1 were determined in glioma cell lines, followed by the prediction and validation of their interaction. After that, the effects of TPT1-AS1, miR-770-5p, and STMN1 on the in vitro glioma cell proliferation and autophagy were assessed using EdU assay and macrophage-derived chemokine (MDC) and on the in vivo tumor development and autophagy were evaluated using a nude mouse xenograft tumor assay and immunofluorescence assay. In comparison with the normal cells, the glioma cells displayed upregulated expression of TPT1-AS1 and STMN1, but a downregulated miR-770-5p expression. miR-770-5p, which directly targeted STMN1, could be downregulated by TPT1-AS1. Subsequently, in glioma cells, TPT1-AS1 can function to competitively bind to miR-770-5p, thus regulatEing STMN1 expression. Moreover, glioma cell proliferation and autophagy could be mediated through the TPT1-AS1/miR-770-5p/STMN1 axis. From our data we conclude an inhibitory function of TPT1-AS1 in glioma cell autophagy by downregulating miR-770-5p and upregulating STMN1, which may be instrumental for the therapeutic targeting and clinical management of glioma.

The landscape of the mesenchymal signature in brain tumours

The complexity of glioblastoma multiforme, the most common and lethal variant of gliomas, is reflected by cellular and molecular heterogeneity at both the inter- and intra-tumoural levels. Molecular subtyping has arisen in the past two decades as a promising strategy to give better predictions of glioblastoma multiforme evolution, common disease pathways, and rational treatment options. The Cancer Genome Atlas network initially identified four molecular subtypes of glioblastoma multiforme: proneural, neural, mesenchymal and classical. However, further studies, also investigated glioma stem cells, have only identified two to three subtypes: proneural, mesenchymal and classical. The proneural-mesenchymal transition upon tumour recurrence has been suggested as a mechanism of tumour resistance to radiation and chemotherapy treatment. Glioblastoma multiforme patients with the mesenchymal subtype tend to survive shorter than other subtypes when analysis is restricted to samples with low transcriptional heterogeneity. Although the mesenchymal signature in malignant glioma may seem at odds with the common idea of the ectodermal origin of neural-glial lineages, the presence of the mesenchymal signature in glioma is supported by several studies suggesting that it can result from: (i) intrinsic expression of tumour cells affected with accumulated genetic mutations and cell of origin; (ii) tumour micro-environments with recruited macrophages or microglia, mesenchymal stem cells or pericytes, and other progenitors; (iii) resistance to tumour treatment, including radiotherapy, antiangiogenic therapy and possibly chemotherapy. Genetic abnormalities, mainly NF1 mutations, together with NF-κB transcriptional programs, are the main driver of acquiring mesenchymal-signature. This signature is far from being simply tissue artefacts, as it has been identified in single cell glioma, circulating tumour cells, and glioma stem cells that are released from the tumour micro-environment. All these together suggest that the mesenchymal signature in glioblastoma multiforme is induced and sustained via cell intrinsic mechanisms and tumour micro-environment factors. Although patients with the mesenchymal subtype tend to have poorer prognosis, they may have favourable response to immunotherapy and intensive radio- and chemotherapy.

Identification of Periostin as a Potential Biomarker in Gliomas by Database Mining

BACKGROUND

Bioinformatics analysis integrating microenvironmental factors and single cell analysis segregated the glioblastoma (GBM) subtype into 3 subtypes: proneural, classic, and mesenchymal. Mesenchymal GBM tends to have the worst survival but benefits from aggressive treatment protocols. Therefore, it is clinically meaningful to identify relevant biomarkers to distinguish the mesenchymal subtype. Moreover, in developing nations with limited resources, rigorous examinations are costly and inefficient for patient care.

METHODS

In this study, we analyzed The Cancer Genome Atlas (TCGA)-Glioblastoma and TCGA-Low-Grade Glioma RNA sequencing (RNAseq) cohorts and confirmed that the mesenchymal subtype was associated with the worst prognosis.

RESULTS

We identified periostin (POSTN) as a mesenchymal subtype biomarker with prognostic value across histologic grades and confirmed the reliability of POSTN by gene expression meta-analysis combining TCGA, Chinese Glioma Genome Atlas (CGGA) and REMBRANDT (Repository for Molecular Brain Neoplasia Data) GBM cohorts (hazard ratio, 1.71 [range, 1.47-2.07], n = 693) and LGG cohorts (hazard ratio, 2.55 [range, 1.61-4.05], n = 1226).

CONCLUSIONS

By using available online glioma databases, our study provided an insight into the expression of POSTN as an independent predictor for patients with glioma (GBM and LGG) and could be useful for diagnostic simplification to identify high-risk groups.

Transcriptomic Profiling Identifies a DNA Repair-Related Signature as a Novel Prognostic Marker in Lower Grade Gliomas

BACKGROUND

Gliomas are the most common and malignant intracranial tumors. The standard therapy is surgical resection combined with radiotherapy and chemotherapy. However, the emergence of radioresistance and chemoresistance, which is largely due to DNA damage repair, limits the therapeutic efficacy. Therefore, we identified a high-efficiency DNA damage repair-related risk signature as a predictor for prognosis in lower grade glioma.

METHODS

The signature was developed and validated in two independent datasets of the Chinese Glioma Genome Atlas (172 samples) and The Cancer Genome Atlas (451 samples). The time-dependent ROC curve, Cox regression, Nomogram, and Kaplan-Meier analyses were performed to evaluate the prognostic performance of the risk signature. The Metascape and IHC staining were performed to reveal the potential biological mechanism. GraphPad prism, SPSS, and R language were used for statistical analysis and graphical work.

RESULTS

This signature could distinguish the prognosis of patients, and patients with high-risk scores exhibited short survival time. The time-dependent ROC curve, Cox regression, and Nomogram model indicated the independent prognostic performance and high prognostic accuracy of the signature for survival. Combined with the IDH mutation status, this risk signature could further subdivide patients with distinct survival. Functional analysis of associated genes revealed signature-related biological process of cell cycle and DNA repair. These mechanisms were confirmed in patient samples.

CONCLUSIONS

The DNA damage repair-related signature was an independent and powerful prognostic biomarker in lower grade glioma.

IMPACT

The signature may potentially improve risk stratification of patients and provide a more accurate assessment of personalized treatment in clinic.

Proneural-Mesenchymal Transition: Phenotypic Plasticity to Acquire Multitherapy Resistance in Glioblastoma

Glioblastoma (GBM) is an extremely aggressive tumor of the central nervous system, with a prognosis of 12–15 months and just 3–5% of survival over 5 years. This is mainly because most patients suffer recurrence after treatment that currently consists in maximal resection followed by radio- and chemotherapy with temozolomide. The recurrent tumor shows a more aggressive behavior due to a phenotypic shift toward the mesenchymal subtype. Proneural-mesenchymal transition (PMT) may represent for GBM the equivalent of epithelial–mesenchymal transition associated with other aggressive cancers. In this review we frame this process in the high degree of phenotypic inter- and intra-tumor heterogeneity of GBM, which exists in different subtypes, each one characterized by further phenotypic variability in its stem-cell compartment. Under the selective pressure of different treatment agents PMT is induced. The mechanisms involved, as well as the significance of such event in the acquisition of a multitherapy resistance phenotype, are taken in consideration for future perspectives in new anti-GBM therapeutic options.

Radiomics in Glioblastoma: Current Status and Challenges Facing Clinical Implementation

Radiomics analysis has had remarkable progress along with advances in medical imaging, most notability in central nervous system malignancies. Radiomics refers to the extraction of a large number of quantitative features that describe the intensity, texture and geometrical characteristics attributed to the tumor radiographic data. These features have been used to build predictive models for diagnosis, prognosis, and therapeutic response. Such models are being combined with clinical, biological, genetics and proteomic features to enhance reproducibility. Broadly, the four steps necessary for radiomic analysis are: (1) image acquisition, (2) segmentation or labeling, (3) feature extraction, and (4) statistical analysis. Major methodological challenges remain prior to clinical implementation. Essential steps include: adoption of an optimized standard imaging process, establishing a common criterion for performing segmentation, fully automated extraction of radiomic features without redundancy, and robust statistical modeling validated in the prospective setting. This review walks through these steps in detail, as it pertains to high grade gliomas. The impact on precision medicine will be discussed, as well as the challenges facing clinical implementation of radiomic in the current management of glioblastoma.

DNA methylation, transcriptome and genetic copy number signatures of diffuse cerebral WHO grade II/III gliomas resolve cancer heterogeneity and development

Background

Diffuse lower WHO grade II and III gliomas (LGG) are slowly progressing brain tumors, many of which eventually transform into a more aggressive type. LGG is characterized by widespread genetic and transcriptional heterogeneity, yet little is known about the heterogeneity of the DNA methylome, its function in tumor biology, coupling with the transcriptome and tumor microenvironment and its possible impact for tumor development.

Methods

We here present novel DNA methylation data of an LGG-cohort collected in the German Glioma Network containing about 85% isocitrate dehydrogenase (IDH) mutated tumors and performed a combined bioinformatics analysis using patient-matched genome and transcriptome data.

Results

Stratification of LGG based on gene expression and DNA-methylation provided four consensus subtypes. We characterized them in terms of genetic alterations, functional context, cellular composition, tumor microenvironment and their possible impact for treatment resistance and prognosis. Glioma with astrocytoma-resembling phenotypes constitute the largest fraction of nearly 60%. They revealed largest diversity and were divided into four expression and three methylation groups which only partly match each other thus reflecting largely decoupled expression and methylation patterns. We identified a novel G-protein coupled receptor and a cancer-related ‘keratinization’ methylation signature in in addition to the glioma-CpG island methylator phenotype (G-CIMP) signature. These different signatures overlap and combine in various ways giving rise to diverse methylation and expression patterns that shape the glioma phenotypes. The decrease of global methylation in astrocytoma-like LGG associates with higher WHO grade, age at diagnosis and inferior prognosis. We found analogies between astrocytoma-like LGG with grade IV IDH-wild type tumors regarding possible worsening of treatment resistance along a proneural-to-mesenchymal axis. Using gene signature-based inference we elucidated the impact of cellular composition of the tumors including immune cell bystanders such as macrophages.

Conclusions

Genomic, epigenomic and transcriptomic factors act in concert but partly also in a decoupled fashion what underpins the need for integrative, multidimensional stratification of LGG by combining these data on gene and cellular levels to delineate mechanisms of gene (de-)regulation and to enable better patient stratification and individualization of treatment.

Electronic supplementary material

The online version of this article (10.1186/s40478-019-0704-8) contains supplementary material, which is available to authorized users.

Huge heterogeneity in survival in a subset of adult patients with resected, wild-type isocitrate dehydrogenase status, WHO grade II astrocytomas

OBJECTIVE

World Health Organization grade II gliomas are infiltrating tumors that inexorably progress to a higher grade of malignancy. However, the time to malignant transformation is quite unpredictable at the individual patient level. A wild-type isocitrate dehydrogenase (IDH-wt) molecular profile has been reported as a poor prognostic factor, with more rapid progression and a shorter survival compared with IDH-mutant tumors. Here, the oncological outcomes of a series of adult patients with IDH-wt, diffuse, WHO grade II astrocytomas (AII) who underwent resection without early adjuvant therapy were investigated.

METHODS

A retrospective review of patients extracted from a prospective database who underwent resection between 2007 and 2013 for histopathologically confirmed, IDH-wt, non-1p19q codeleted AII was performed. All patients had a minimum follow-up period of 2 years. Information regarding clinical, radiographic, and surgical results and survival were collected and analyzed.

RESULTS

Thirty-one consecutive patients (18 men and 13 women, median age 39.6 years) were included in this study. The preoperative median tumor volume was 54 cm3 (range 3.5-180 cm3). The median growth rate, measured as the velocity of diametric expansion, was 2.45 mm/year. The median residual volume after surgery was 4.2 cm3 (range 0-30 cm3) with a median volumetric extent of resection of 93.97% (8 patients had a total or supratotal resection). No patient experienced permanent neurological deficits after surgery, and all patients resumed a normal life. No immediate postoperative chemotherapy or radiation therapy was given. The median clinical follow-up duration from diagnosis was 74 months (range 27-157 months). In this follow-up period, 18 patients received delayed chemotherapy and/or radiotherapy for tumor progression. Five patients (16%) died at a median time from radiological diagnosis of 3.5 years (range 2.6-4.5 years). Survival from diagnosis was 77.27% at 5 years. None of the 21 patients with a long-term follow-up greater than 5 years have died. There were no significant differences between the clinical, radiological, or molecular characteristics of the survivors relative to the patients who died.

CONCLUSIONS

Huge heterogeneity in the survival data for a subset of 31 patients with resected IDH-wt AII tumors was observed. These findings suggest that IDH mutation status alone is not sufficient to predict risk of malignant transformation and survival at the individual level. Therefore, the therapeutic management of AII tumors, in particular the decision to administer early adjuvant chemotherapy and/or radiation therapy following surgery, should not solely rely on routine molecular markers.

MGSEA - a multivariate Gene set enrichment analysis

BACKGROUND

Gene Set Enrichment Analysis (GSEA) is a powerful tool to identify enriched functional categories of informative biomarkers. Canonical GSEA takes one-dimensional feature scores derived from the data of one platform as inputs. Numerous extensions of GSEA handling multimodal OMIC data are proposed, yet none of them explicitly captures combinatorial relations of feature scores from multiple platforms.

RESULTS

We propose multivariate GSEA (MGSEA) to capture combinatorial relations of gene set enrichment among multiple platform features. MGSEA successfully captures designed feature relations from simulated data. By applying it to the scores of delineating breast cancer and glioblastoma multiforme (GBM) subtypes from The Cancer Genome Atlas (TCGA) datasets of CNV, DNA methylation and mRNA expressions, we find that breast cancer and GBM data yield both similar and distinct outcomes. Among the enriched functional categories, subtype-specific biomarkers are dominated by mRNA expression in many functional categories in both cancer types and also by CNV in many functional categories in breast cancer. The enriched functional categories belonging to distinct combinatorial patterns are involved different oncogenic processes: cell proliferation (such as cell cycle control, estrogen responses, MYC and E2F targets) for mRNA expression in breast cancer, invasion and metastasis (such as cell adhesion and epithelial-mesenchymal transition (EMT)) for CNV in breast cancer, and diverse processes (such as immune and inflammatory responses, cell adhesion, angiogenesis, and EMT) for mRNA expression in GBM. These observations persist in two external datasets (Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) for breast cancer and Repository for Molecular Brain Neoplasia Data (REMBRANDT) for GBM) and are consistent with knowledge of cancer subtypes. We further compare the characteristics of MGSEA with several extensions of GSEA and point out the pros and cons of each method.

CONCLUSIONS

We demonstrated the utility of MGSEA by inferring the combinatorial relations of multiple platforms for cancer subtype delineation in three multi-OMIC datasets: TCGA, METABRIC and REMBRANDT. The inferred combinatorial patterns are consistent with the current knowledge and also reveal novel insights about cancer subtypes. MGSEA can be further applied to any genotype-phenotype association problems with multimodal OMIC data.

Increased LGALS3 expression independently predicts shorter overall survival in patients with the proneural subtype of glioblastoma

In the current study, we tried to study the expression of LGALS3 and LGALS3BP, their potential as prognostic markers and the possible genetic/epigenetic mechanisms underlying their dysregulation in different subtypes of glioblastoma (GBM). An in silico retrospective study was performed using large online databases. Results showed that LGALS3 and LGALS3BP were upregulated at both RNA and protein levels in GBM tissue and were generally associated with shorter overall survival (OS) in GBM patients. However, in subgroup analysis, we only found the association in proneural subtype. The copy number alterations did not necessarily lead to LGALS3/LGALS3BP dysregulation. In the proneural subtype of GBM patients, hypermethylation of the two CpG sites (cg19099850 and cg17403875) was associated with significantly lower expression of LGALS3. In univariate and multivariate analysis, LGALS3 expression independently predicted shorter OS in the proneural subtype of GBM (HR: 1.487, 95% CI: 1.229‐1.798, P < 0.001), after adjustment of age, gender, IDH1 mutations, temozolomide chemotherapy, radiotherapy and LGALS3BP expression. In comparison, LGALS3BP lost the prognostic value in multivariate analysis. Based on these findings, we infer that LGALS3 expression serves as an independent biomarker of shorter OS in the proneural subtype of GBM, the expression of which might be regulated in an epigenetic manner.

Discovery of 5-Signature Predicting Survival of Patients with Lower-Grade Glioma

OBJECTIVE

In the study, we aimed to identify key microRNAs (miRNAs) and clinical factors associated with survival time of lower-grade glioma (LGG) and develop an expression-based miRNA signature to provide survival risk prediction for patients with LGG.

METHODS

We obtained miRNA expression profiles and clinical information of patients with LGG from The Cancer Genome Atlas dataset. All 591 miRNAs were modeled using random Forest Survival, Regression, and Classification to construct a random forest model for survival analysis, and feature selection was performed. We used univariate and multivariate Cox regression analysis to screen differentially expressed miRNAs and clinical factors related to overall survival of patients with LGG.

RESULTS

A total of 591 differentially expressed miRNAs were obtained between LGG and normal tissues. After univariate and multivariate Cox regression analysis, 2 predictive miRNAs (hsa-miR-10b-5p and hsa-miR-15b-5p) and 3 clinical factors (grade, age, and cancer status) were finally screened out to construct a 5-signature, based on which patients in the training dataset were divided into high-risk and low-risk groups. The competitive performance of the 5-signature was revealed by receiver operating characteristic curve analysis. The prognostic value of the 5-signature was successfully validated in the testing and validation dataset.

CONCLUSIONS

Our study demonstrated the promising potential of the novel 5-signature as an independent biomarker for survival prediction of patients with LGG.

Integrated molecular characterization of IDH-mutant glioblastomas

AIMS

Mutations of isocitrate dehydrogenase (IDH)1/2 affect almost all astrocytomas of WHO grade II and III. A subset of IDH-mutant astrocytic tumours progresses to IDH-mutant glioblastoma or presents with the histology of a glioblastoma at first presentation. We set out here to assess the molecular spectrum of IDH-mutant glioblastomas.

METHODS

We performed an integrated molecular analysis of a mono-centric cohort (n = 97); assessed through genome-wide DNA methylation analysis, copy-number profiling and targeted next generation sequencing using a neurooncology-tailored gene panel.

RESULTS

Of these 97 IDH-mutant glioblastomas, 68 had a glioblastoma at first presentation ('de novo' IDH-mutant glioblastoma) and 29 emerged from a prior low-grade lesion ('evolved' IDH-mutant glioblastoma). Unsupervised hierarchical clustering of DNA methylation data disclosed that IDH-mutant glioblastoma ('de novo' and 'evolved') formed a distinct group separate from other diffuse glioma subtypes. Homozygous deletions of CDKN2A/B were found to be associated with shorter survival.

CONCLUSIONS

This study demonstrates DNA methylation patterns in IDH-mutant glioblastoma to be distinct from lower-grade astrocytic counterparts but homogeneous within de novo and evolved IDH-mutant glioblastomas, and identifies CDKN2A as a marker for possible genetic sub-stratification.

Methylation dependent down-regulation of G0S2 leads to suppression of invasion and improved prognosis of IDH1-mutant glioma

Isocitrate dehydrogenase (IDH) mutations are a prognostic factor in diffuse glioma. However, the mechanism by which these mutations improve prognosis are not clear. In a subset of IDH-mutant glioma, remodeling of the methylome results in the glioma-CpG island methylator phenotype (G-CIMP) and transcriptional reorganization. In this study, we focus on G0/G1 switch 2 (G0S2), which is highly downregulated in G-CIMP glioma. We found that G0S2 expression tended to increase as the WHO grade increased, and G0S2 knockdown inhibited glioma invasion. Additionally, we revealed that the overexpression of the DNA demethylase Ten-eleven translocation 2 (TET2) in IDH1-plasmid transfected glioblastoma multiforme (GBM) cells restored G0S2 expression. These results indicate that G0S2 is epigenetically silenced in IDH1-mutant glioma. In addition, the stereotactic delivery of glioma cells with decreased G0S2 expression in the mouse brain resulted in prolonged survival. The Cancer Genome Atlas (TCGA) analysis also indicated that survival is longer in the lower G0S2 expression group than in the higher G0S2 expression group. Moreover, G0S2 expression was higher in recurrent tumor specimens than at the initial diagnosis in the same patient. These results provide one explanation for the improved survival in IDH1-mutant glioma as well as a new epigenetic target for glioma treatment.

Clair WH, Lightner DD, Villano JL. Comprehensive evaluation of treatment and outcomes of low-grade diffuse gliomas

Background

Low-grade gliomas affect younger adults and carry a favorable prognosis. They include a variety of biological features affecting clinical behavior and treatment. Having no guidelines on treatment established, we aim to describe clinical and treatment patterns of low-grade gliomas across the largest cancer database in the United States.

Methods

We analyzed the National Cancer Database from 2004 to 2015, for adult patients with a diagnosis of World Health Organization grade II diffuse glioma.

Results

We analyzed 13,621 cases with median age of 41 years. Over 56% were male, 88.4% were white, 6.1% were black, and 7.6% Hispanic. The most common primary site location was the cerebrum (79.9%). Overall, 72.2% received surgery, 36.0% radiation, and 27.3% chemotherapy. Treatment combinations included surgery only (41.5%), chemotherapy + surgery (6.6%), chemotherapy only (3.1%), radiation + chemotherapy + surgery (10.7%), radiation + surgery (11.5%), radiation only (6.1%), and radiotherapy + chemotherapy (6.7%). Radiation was more common in treatment of elderly patients, 1p/19q co-deletion (37.3% versus 24.3%, p<0.01), and tumors with midline location. Median survival was 11 years with younger age, 1p/19q co-deletion, and cerebrum location offered survival advantage.

Conclusions

Tumor location, 1p/19q co-deletion, and age were the main determinants of treatment received and survival, likely reflecting tumor biology differences. Any form of treatment was preferred over watchful waiting in the majority of the patients (86.1% versus 8.1%). Survival of low-grade gliomas is higher than previously reported in the majority of clinical trials and population-based analyses. Our analysis provides a real world estimation of treatment decisions, use of molecular data, and outcomes.

Paradoxes of evidence-based medicine in lower-grade glioma: To treat the tumor or the patient?

Brain lower-grade gliomas (LGG) usually occur in young adults who enjoy an active life. This tumor has a high risk of malignant transformation resulting in neurologic deterioration and finally death. Early and multistage therapeutic management can increase survival over 10 years. Preservation of functional neural networks and quality of life is crucial. In the era of evidence-based medicine, the issues discussed are those associated with the design, analysis, and clinical application of randomized controlled trials (RCTs) for LGG. RCTs should take account of the following: considerable variability in the natural course of LGG; limited prognostic value of molecular biology at the individual level; large variability of brain organization across patients; technical and conceptual progress of therapies over years; combination or repetition of iterative treatments, taken as a whole and not only in isolation; and long-term consequences on oncologic and functional outcomes. As it is difficult to translate the results of an RCT into benefits for a unique patient with LGG, personalized decisions must be made by considering the tumor behavior, individual pattern of neuroplasticity, and patient needs, and not by administrating a standardized protocol exclusively based on an RCT.

Histologically defined intratumoral sequencing uncovers evolutionary cues into conserved molecular events driving gliomagenesis

Background

Glioblastoma represents an archetypal example of a heterogeneous malignancy. To understand the diverse molecular consequences of this complex tumor ecology, we analyzed RNA-seq data generated from commonly identified intratumoral structures in glioblastoma enriched using laser capture microdissection.

Methods

Raw gene-level values of fragments per kilobase of transcript per million reads mapped and the associated clinical data were acquired from the publicly available Ivy Glioblastoma Atlas Project database and analyzed using MetaboAnalyst (v3.0). The database includes gene expression data generated from multiple structural features commonly identified in glioblastoma enriched by laser capture microdissection.

Results

We uncovered a relationship between subtype heterogeneity in glioblastoma and its unique tumor microenvironment, with infiltrating cells harboring a proneural signature while the mesenchymal subtype was enriched in perinecrotic regions. When evaluating the tumors' transcriptional profiles in the context of their derived structural regions, there was a relatively small amount of intertumoral heterogeneity in glioblastoma, with individual regions from different tumors clustering tightly together. Analyzing the transcriptional profiles in the context of evolutionary progression identified unique cellular programs associated with specific phases of gliomagenesis. Mediators of cell signaling and cell cycle progression appear to be critical events driving proliferation in the tumor core, while in addition to a multiplex strategy for promoting angiogenesis and/or an immune-tolerant environment, transformation to perinecrotic zones involved global metabolic alterations.

Conclusion

These findings suggest that intratumoral heterogeneity in glioblastoma is a conserved, predictable consequence to its complex microenvironment, and combinatorial approaches designed to target these unequivocally present tumor biomes may lead to therapeutic gains.

Incorporating Advances in Molecular Pathology Into Brain Tumor Diagnostics

Recent advances in molecular pathology have reshaped the practice of brain tumor diagnostics. The classification of gliomas has been restructured with the discovery of isocitrate dehydrogenase (IDH) 1/2 mutations in the vast majority of lower grade infiltrating gliomas and secondary glioblastomas (GBM), with IDH-mutant astrocytomas further characterized by TP53 and ATRX mutations. Whole-arm 1p/19q codeletion in conjunction with IDH mutations now define oligodendrogliomas, which are also enriched for CIC, FUBP1, PI3K, NOTCH1, and TERT-p mutations. IDH-wild-type (wt) infiltrating astrocytomas are mostly primary GBMs and are characterized by EGFR, PTEN, TP53, NF1, RB1, PDGFRA, and CDKN2A/B alterations, TERT-p mutations, and characteristic copy number alterations including gains of chromosome 7 and losses of 10. Other clinically and genetically distinct infiltrating astrocytomas include the aggressive H3K27M-mutant midline gliomas, and smaller subsets that occur in the setting of NF1 or have BRAF V600E mutations. Low-grade pediatric gliomas are both genetically and biologically distinct from their adult counterparts and often harbor a single driver event often involving BRAF, FGFR1, or MYB/MYBL1 genes. Large scale genomic and epigenomic analyses have identified distinct subgroups of ependymomas tightly linked to tumor location and clinical behavior. The diagnosis of embryonal neoplasms also integrates molecular testing: (I) 4 molecularly defined, biologically distinct subtypes of medulloblastomas are now recognized; (II) 3 histologic entities have now been reclassified under a diagnosis of "embryonal tumor with multilayered rosettes (ETMR), C19MC-altered"; and (III) atypical teratoid/rhabdoid tumors (AT/RT) now require SMARCB1 (INI1) or SMARCA4 (BRG1) alterations for their diagnosis. We discuss the practical use of contemporary biomarkers for an integrative diagnosis of central nervous system neoplasia.

Migration/Invasion of Malignant Gliomas and Implications for Therapeutic Treatment

Malignant tumors of the central nervous system (CNS) are among cancers with the poorest prognosis, indicated by their association with tumors of high-level morbidity and mortality. Gliomas, the most common primary CNS tumors that arise from neuroglial stem or progenitor cells, have estimated annual incidence of 6.6 per 100,000 individuals in the USA, and 3.5 per 100,000 individuals in Taiwan. Tumor invasion and metastasis are the major contributors to the deaths in cancer patients. Therapeutic goals including cancer stem cells (CSC), phenotypic shifts, EZH2/AXL/TGF-β axis activation, miRNAs and exosomes are relevant to GBM metastasis to develop novel targeted therapeutics for GBM and other brain cancers. Herein, we highlight tumor metastasis in our understanding of gliomas, and illustrate novel exosome therapeutic approaches in glioma, thereby paving the way towards innovative therapies in neuro-oncology.

Multigene signature for predicting prognosis of patients with 1p19q co-deletion diffuse glioma

Background

Co-deletion of 1p and 19q marks a diffuse glioma subtype associated with relatively favorable overall survival; however, heterogeneous clinical outcomes are observed within this category.

Methods

We assembled gene expression profiles and sample annotation of 374 glioma patients carrying the 1p/19q co-deletion. We predicted 1p/19q status using gene expression when annotation was missing. A first cohort was randomly split into training (n = 170) and a validation dataset (n = 163). A second validation set consisted of 41 expression profiles. An elastic-net penalized Cox proportional hazards model was applied to build a classifier model through cross-validation within the training dataset.

Results

The selected 35-gene signature was used to identify high-risk and low-risk groups in the validation set, which showed significantly different overall survival (P = .00058, log-rank test). For time-to-death events, the high-risk group predicted by the gene signature yielded a hazard ratio of 1.78 (95% confidence interval, 1.02-3.11). The signature was also significantly associated with clinical outcome in the The Cancer Genome Atlas (CGA) IDH-mutant 1p/19q wild-type and IDH-wild-type glioma cohorts. Pathway analysis suggested that high risk was associated with increased acetylation activity and inflammatory response. Tumor purity was found to be significantly decreased in high-risk IDH-mutant with 1p/19q co-deletion gliomas and IDH-wild-type glioblastomas but not in IDH-wild-type lower grade or IDH-mutant, non-co-deleted gliomas.

Conclusion

We identified a 35-gene signature that identifies high-risk and low-risk categories of 1p/19q positive glioma patients. We have demonstrated heterogeneity amongst a relatively new glioma subtype and provided a stepping stone towards risk stratification.

c-Jun-N-terminal phosphorylation regulates DNMT1 expression and genome wide methylation in gliomas

High-grade gliomas (HGG) are the most common brain tumors, with an average survival time of 14 months. A glioma-CpG island methylator phenotype (G-CIMP), associated with better clinical outcome, has been described in low and high-grade gliomas. Mutation of IDH1 is known to drive the G-CIMP status. In some cases, however, the hypermethylation phenotype is independent of IDH1 mutation, suggesting the involvement of other mechanisms. Here, we demonstrate that DNMT1 expression is higher in low-grade gliomas compared to glioblastomas and correlates with phosphorylated c-Jun. We show that phospho-c-Jun binds to the DNMT1 promoter and causes DNA hypermethylation. Phospho-c-Jun activation by Anisomycin treatment in primary glioblastoma-derived cells attenuates the aggressive features of mesenchymal glioblastomas and leads to promoter methylation and downregulation of key mesenchymal genes (CD44, MMP9 and CHI3L1). Our findings suggest that phospho-c-Jun activates an important regulatory mechanism to control DNMT1 expression and regulate global DNA methylation in Glioblastoma.

Phase 1 trial of vocimagene amiretrorepvec and 5-fluorocytosine for recurrent high-grade glioma

Toca 511 (vocimagene amiretrorepvec) is an investigational nonlytic, retroviral replicating vector (RRV) that delivers a yeast cytosine deaminase, which converts subsequently administered courses of the investigational prodrug Toca FC (extended-release 5-fluorocytosine) into the antimetabolite 5-fluorouracil. Forty-five subjects with recurrent or progressive high-grade glioma were treated. The end points of this phase 1, open-label, ascending dose, multicenter trial included safety, efficacy, and molecular profiling; survival was compared to a matching subgroup from an external control. Overall survival for recurrent high-grade glioma was 13.6 months (95% confidence interval, 10.8 to 20.0) and was statistically improved relative to an external control (hazard ratio, 0.45; P = 0.003). Tumor samples from subjects surviving more than 52 weeks after Toca 511 delivery disproportionately displayed a survival-related mRNA expression signature, identifying a potential molecular signature that may correlate with treatment-related survival rather than being prognostic. Toca 511 and Toca FC show excellent tolerability, with RRV persisting in the tumor and RRV control systemically. The favorable assessment of Toca 511 and Toca FC supports confirmation in a randomized phase 2/3 trial (NCT02414165).

Zebrafish in Translational Cancer Research: Insight into Leukemia, Melanoma, Glioma and Endocrine Tumor Biology

Over the past 15 years, zebrafish have emerged as a powerful tool for studying human cancers. Transgenic techniques have been employed to model different types of tumors, including leukemia, melanoma, glioblastoma and endocrine tumors. These models present histopathological and molecular conservation with their human cancer counterparts and have been fundamental for understanding mechanisms of tumor initiation and progression. Moreover, xenotransplantation of human cancer cells in embryos or adult zebrafish offers the advantage of studying the behavior of human cancer cells in a live organism. Chemical-genetic screens using zebrafish embryos have uncovered novel druggable pathways and new therapeutic strategies, some of which are now tested in clinical trials. In this review, we will report on recent advances in using zebrafish as a model in cancer studies—with specific focus on four cancer types—where zebrafish has contributed to novel discoveries or approaches to novel therapies.

Screening critical genes associated with malignant glioma using bioinformatics analysis

Malignant gliomas are high‑grade gliomas, which are derived from glial cells in the spine or brain. To examine the mechanisms underlying malignant gliomas in the present study, the expression profile of GSE54004, which included 12 grade II astrocytomas, 33 grade III astrocytomas and 98 grade IV astrocytomas, was downloaded from the Gene Expression Omnibus. Using the Limma package in R, the differentially expressed genes (DEGs) in grade III, vs. grade II astrocytoma, grade IV, vs. grade II astrocytoma, and grade IV, vs. grade III astrocytoma were analyzed. Venn diagram analysis and enrichment analyses were performed separately for the DEGs using VennPlex software and the Database for Annotation, Visualization and Integrated Discovery. Protein‑protein interaction (PPI) networks were visualized using Cytoscape software, and subsequent module analysis of the PPI networks was performed using the ClusterONE tool. Finally, glioma‑associated genes and glioma marker genes among the DEGs were identified using the CTD database. A total of 27, 1,446 and 776 DEGs were screened for the grade III, vs. grade II, grade IV, vs. grade II, and grade IV, vs. grade III astrocytoma comparison groups, respectively. Functional enrichment analyses showed that matrix metalloproteinase 9 (MMP9) and chitinase 3‑like 1 (CHI3L1) were enriched in the extracellular matrix and extracellular matrix structural constituent, respectively. In the PPI networks, annexin A1 (ANXA1) had a higher degree and MMP9 had interactions with vascular endothelial growth factor A (VEGFA). There were 10 common glioma marker genes between the grade IV, vs. grade II and the grade IV, vs. grade III comparison groups, including MMP9, CHI3L1, VEGFA and S100 calcium binding protein A4 (S100A4). This suggested that MMP9, CHI3L1, VEGFA, S100A4 and ANXA1 may be involved in the progression of malignant gliomas.

Hypomethylation of CNTFRα is associated with proliferation and poor prognosis in lower grade gliomas

Ciliary neurotrophic factor receptor α subunit (CNTFRα) and CNTF play important roles in neuron survival, glial differentiation and brain tumor growth. However, the molecular mechanisms of CNTFRα regulation and its clinical significance in glioma remain largely unknown. Here, we found CNTFRα was overexpressed in lower grade gliomas (LGG) compared with glioblastoma (GBM) and normal brain specimens in TCGA datasets and in an independent cohort. Bioinformatics analysis revealed a CpG shore of the CNTFRα gene regulated its mRNA expression in TCGA datasets. This observation was further validated with clinical specimens and functionally verified using demethylating agents. Additionally, we observed that independent of IDH mutation status, methylation of CNTFRα was significantly correlated with down-regulated CNTFRα gene expression and longer LGG patient survival. Interestingly, combination of CNTFRα methylation and IDH mutation significantly (p < 0.05) improved the prognostic prediction in LGG patients. Furthermore, the role of CNTFRα in glioma proliferation and apoptosis through the PI3K/AKT pathways was demonstrated by supplementation with exogenous CNTF  in vitro and siRNA knockdown in vivo. Our study demonstrated that hypomethylation leading to CNTFRα up-regulation, together with autocrine expression of CNTF, was involved in glioma growth regulation. Importantly, DNA methylation of CNTFRα might serve as a potential epigenetic theranostic target for LGG patients.

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.

Detection of statistically significant network changes in complex biological networks

Background

Biological networks contribute effectively to unveil the complex structure of molecular interactions and to discover driver genes especially in cancer context. It can happen that due to gene mutations, as for example when cancer progresses, the gene expression network undergoes some amount of localized re-wiring. The ability to detect statistical relevant changes in the interaction patterns induced by the progression of the disease can lead to the discovery of novel relevant signatures. Several procedures have been recently proposed to detect sub-network differences in pairwise labeled weighted networks.

Methods

In this paper, we propose an improvement over the state-of-the-art based on the Generalized Hamming Distance adopted for evaluating the topological difference between two networks and estimating its statistical significance. The proposed procedure exploits a more effective model selection criteria to generate p-values for statistical significance and is more efficient in terms of computational time and prediction accuracy than literature methods. Moreover, the structure of the proposed algorithm allows for a faster parallelized implementation.

Results

In the case of dense random geometric networks the proposed approach is 10-15x faster and achieves 5-10% higher AUC, Precision/Recall, and Kappa value than the state-of-the-art. We also report the application of the method to dissect the difference between the regulatory networks of IDH-mutant versus IDH-wild-type glioma cancer. In such a case our method is able to identify some recently reported master regulators as well as novel important candidates.

Conclusions

We show that our network differencing procedure can effectively and efficiently detect statistical significant network re-wirings in different conditions. When applied to detect the main differences between the networks of IDH-mutant and IDH-wild-type glioma tumors, it correctly selects sub-networks centered on important key regulators of these two different subtypes. In addition, its application highlights several novel candidates that cannot be detected by standard single network-based approaches.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-017-0412-6) contains supplementary material, which is available to authorized users.

Evolving Molecular Genetics of Glioblastoma

Objective:

To summary the recent advances in molecular research of glioblastoma (GBM) and current trends in personalized therapy of this disease.

Data Sources:

Data cited in this review were obtained mainly from PubMed in English up to 2015, with keywords “molecular”, “genetics”, “GBM”, “isocitrate dehydrogenase”, “telomerase reverse transcriptase”, “epidermal growth factor receptor”, “PTPRZ1-MET”, and “clinical treatment”.

Study Selection:

Articles regarding the morphological pathology of GBM, the epidemiology of GBM, genetic alteration of GBM, and the development of treatment for GBM patients were identified, retrieved, and reviewed.

Results:

There is a large amount of data supporting the view that these recurrent genetic aberrations occur in a specific context of cellular origin, co-oncogenic hits and are present in distinct patient populations. Primary and secondary GBMs are distinct disease entities that affect different age groups of patients and develop through distinct genetic aberrations. These differences are important, especially because they may affect sensitivity to radio- and chemo-therapy and should thus be considered in the identification of targets for novel therapeutic approaches.

Conclusion:

This review highlights the molecular and genetic alterations of GBM, indicating that they are of potential value in the diagnosis and treatment for patients with GBM.

Glioma: experimental models and reality

In theory, in vitro and in vivo models for human gliomas have great potential to not only enhance our understanding of glioma biology, but also to facilitate the development of novel treatment strategies for these tumors. For reliable prediction and validation of the effects of different therapeutic modalities, however, glioma models need to comply with specific and more strict demands than other models of cancer, and these demands are directly related to the combination of genetic aberrations and the specific brain micro-environment gliomas grow in. This review starts with a brief introduction on the pathological and molecular characteristics of gliomas, followed by an overview of the models that have been used in the last decades in glioma research. Next, we will discuss how these models may play a role in better understanding glioma development and especially in how they can aid in the design and optimization of novel therapies. The strengths and weaknesses of the different models will be discussed in light of genotypic, phenotypic and metabolic characteristics of human gliomas. The last part of this review provides some examples of how therapy experiments using glioma models can lead to deceptive results when such characteristics are not properly taken into account.

KCTD2, an adaptor of Cullin3 E3 ubiquitin ligase, suppresses gliomagenesis by destabilizing c-Myc

Cullin3 E3 ubiquitin ligase ubiquitinates a wide range of substrates through substrate-specific adaptors Bric-a-brac, Tramtrack, and Broad complex (BTB) domain proteins. These E3 ubiquitin ligase complexes are involved in diverse cellular functions. Our recent study demonstrated that decreased Cullin3 expression induces glioma initiation and correlates with poor prognosis of patients with malignant glioma. However, the substrate recognition mechanism associated with tumorigenesis is not completely understood. Through yeast two-hybrid screening, we identified potassium channel tetramerization domain-containing 2 (KCTD2) as a BTB domain protein that binds to Cullin3. The interaction of Cullin3 and KCTD2 was verified using immunoprecipitation and immunofluorescence. Of interest, KCTD2 expression was markedly decreased in patient-derived glioma stem cells (GSCs) compared with non-stem glioma cells. Depletion of KCTD2 using a KCTD2-specific short-hairpin RNA in U87MG glioma cells and primary Ink4a/Arf-deficient murine astrocytes markedly increased self-renewal activity in addition with an increased expression of stem cell markers, and mouse in vivo intracranial tumor growth. As an underlying mechanism for these KCTD2-mediated phenotypic changes, we demonstrated that KCTD2 interacts with c-Myc, which is a key stem cell factor, and causes c-Myc protein degradation by ubiquitination. As a result, KCTD2 depletion acquires GSC features and affects aerobic glycolysis via expression changes in glycolysis-associated genes through c-Myc protein regulation. Of clinical significance was our finding that patients having a profile of KCTD2 mRNA-low and c-Myc gene signature-high, but not KCTD2 mRNA-low and c-Myc mRNA-high, are strongly associated with poor prognosis. This study describes a novel regulatory mode of c-Myc protein in malignant gliomas and provides a potential framework for glioma therapy by targeting c-Myc function.

A novel brain tumour model in zebrafish reveals the role of YAP activation in MAPK- and PI3K-induced malignant growth

Somatic mutations activating MAPK and PI3K signalling play a pivotal role in both tumours and brain developmental disorders. We developed a zebrafish model of brain tumours based on somatic expression of oncogenes that activate MAPK and PI3K signalling in neural progenitor cells and found that HRASV12 was the most effective in inducing both heterotopia and invasive tumours. Tumours, but not heterotopias, require persistent activation of phospho (p)-ERK and express a gene signature similar to the mesenchymal glioblastoma subtype, with a strong YAP component. Application of an eight-gene signature to human brain tumours establishes that YAP activation distinguishes between mesenchymal glioblastoma and low grade glioma in a wide The Cancer Genome Atlas (TCGA) sample set including gliomas and glioblastomas (GBMs). This suggests that the activation of YAP might be an important event in brain tumour development, promoting malignant versus benign brain lesions. Indeed, co-expression of dominant-active YAP (YAPS5A) and HRASV12 abolishes the development of heterotopias and leads to the sole development of aggressive tumours. Thus, we have developed a model proving that neurodevelopmental disorders and brain tumours might originate from the same activation of oncogenes through somatic mutations, and established that YAP activation is a hallmark of malignant brain tumours.

Co-expression of mitosis-regulating genes contributes to malignant progression and prognosis in oligodendrogliomas

The clinical prognosis of patients with glioma is determined by tumor grades, but tumors of different subtypes with equal malignancy grade usually have different prognosis that is largely determined by genetic abnormalities. Oligodendrogliomas (ODs) are the second most common type of gliomas. In this study, integrative analyses found that distribution of TCGA transcriptomic subtypes was associated with grade progression in ODs. To identify critical gene(s) associated with tumor grades and TCGA subtypes, we analyzed 34 normal brain tissue (NBT), 146 WHO grade II and 130 grade III ODs by microarray and RNA sequencing, and identified a co-expression network of six genes (AURKA, NDC80, CENPK, KIAA0101, TIMELESS and MELK) that was associated with tumor grades and TCGA subtypes as well as Ki-67 expression. Validation of the six genes was performed by qPCR in additional 28 ODs. Importantly, these genes also were validated in four high-grade recurrent gliomas and the initial lower-grade gliomas resected from the same patients. Finally, the RNA data on two genes with the highest discrimination potential (AURKA and NDC80) and Ki-67 were validated on an independent cohort (5 NBTs and 86 ODs) by immunohistochemistry. Knockdown of AURKA and NDC80 by siRNAs suppressed Ki-67 expression and proliferation of gliomas cells. Survival analysis showed that high expression of the six genes corporately indicated a poor survival outcome. Correlation and protein interaction analysis provided further evidence for this co-expression network. These data suggest that the co-expression of the six mitosis-regulating genes was associated with malignant progression and prognosis in ODs.