Expression-based intrinsic glioma subtypes are prognostic in low-grade gliomas of the EORTC22033-26033 clinical trial

Stemness subtypes in lower-grade glioma with prognostic biomarkers, tumor microenvironment, and treatment response

Our research endeavors are directed towards unraveling the stem cell characteristics of lower-grade glioma patients, with the ultimate goal of formulating personalized treatment strategies. We computed enrichment stemness scores and performed consensus clustering to categorize phenotypes. Subsequently, we constructed a prognostic risk model using weighted gene correlation network analysis (WGCNA), random survival forest regression analysis as well as full subset regression analysis. To validate the expression differences of key genes, we employed experimental methods such as quantitative Polymerase Chain Reaction (qPCR) and assessed cell line proliferation, migration, and invasion. Three subtypes were assigned to patients diagnosed with LGG. Notably, Cluster 2 (C2), exhibiting the poorest survival outcomes, manifested characteristics indicative of the subtype characterized by immunosuppression. This was marked by elevated levels of M1 macrophages, activated mast cells, along with higher immune and stromal scores. Four hub genes-CDCA8, ORC1, DLGAP5, and SMC4-were identified and validated through cell experiments and qPCR. Subsequently, these validated genes were utilized to construct a stemness risk signature. Which revealed that Lower-Grade Glioma (LGG) patients with lower scores were more inclined to demonstrate favorable responses to immune therapy. Our study illuminates the stemness characteristics of gliomas, which lays the foundation for developing therapeutic approaches targeting CSCs and enhancing the efficacy of current immunotherapies. By identifying the stemness subtype and its correlation with prognosis and TME patterns in glioma patients, we aim to advance the development of personalized treatments, enhancing the ability to predict and improve overall patient prognosis.

Nanomedicine facilitated cell signaling blockade: difficulties and strategies to overcome glioblastoma

Glioblastoma (GBM) is a highly aggressive and lethal type of brain tumor with complex and diverse molecular signaling pathways involved that are in its development and progression. Despite numerous attempts to develop effective treatments, the survival rate remains low. Therefore, understanding the molecular mechanisms of these pathways can aid in the development of targeted therapies for the treatment of glioblastoma. Nanomedicines have shown potential in targeting and blocking signaling pathways involved in glioblastoma. Nanomedicines can be engineered to specifically target tumor sites, bypass the blood-brain barrier (BBB), and release drugs over an extended period. However, current nanomedicine strategies also face limitations, including poor stability, toxicity, and low therapeutic efficacy. Therefore, novel and advanced nanomedicine-based strategies must be developed for enhanced drug delivery. In this review, we highlight risk factors and chemotherapeutics for the treatment of glioblastoma. Further, we discuss different nanoformulations fabricated using synthetic and natural materials for treatment and diagnosis to selectively target signaling pathways involved in GBM. Furthermore, we discuss current clinical strategies and the role of artificial intelligence in the field of nanomedicine for targeting GBM.

Pan-cancer landscape of epigenetic factor expression predicts tumor outcome

Oncogenic pathways that drive cancer progression reflect both genetic changes and epigenetic regulation. Here we stratified primary tumors from each of 24 TCGA adult cancer types based on the gene expression patterns of epigenetic factors (epifactors). The tumors for five cancer types (ACC, KIRC, LGG, LIHC, and LUAD) separated into two robust clusters that were better than grade or epithelial-to-mesenchymal transition in predicting clinical outcomes. The majority of epifactors that drove the clustering were also individually prognostic. A pan-cancer machine learning model deploying epifactor expression data for these five cancer types successfully separated the patients into poor and better outcome groups. Single-cell analysis of adult and pediatric tumors revealed that expression patterns associated with poor or worse outcomes were present in individual cells within tumors. Our study provides an epigenetic map of cancer types and lays a foundation for discovering pan-cancer targetable epifactors.

RARRES2 is Downregulated in Isocitrate Dehydrogenase 1 Mutant Glioma Patients and Served as an Unfavorable Prognostic Factor of Glioma

BACKGROUND

Mutations in isocitrate dehydrogenase 1 (IDH1) induce extensive transcriptional alterations to promote glioma development. However, IDH1 mutation contributes the better clinical outcomes of glioma. Further understanding the transcriptional and DNA methylation changes mediated by IDH1 mutation will provide new therapeutic targets for glioma.

METHODS

Public glioma cohorts were collected and processed using R software. The transcriptional changes mediated by IDH1 mutation were determined and presented using heatmap. The differentially expressed genes in IDH1 mutant glioma were overlapped using TBtools. The prognostic effects of IDH1 regulated genes were determined by Kaplan-Meier survival analysis.

RESULTS

Retinoic acid receptor responder 2 (RARRES2) was upregulated in IDH1 wild type lower-grade glioma (LGG) patients, and higher expression levels of RARRES2 were associated with worse clinical outcomes of LGG. Moreover, IDH1 wild type LGG patients with higher expression levels of RARRES2 had even worse overall survival. Compared with LGG, RARRES2 was upregulated in grade IV glioma (glioblastoma multiforme, GBM). Also, RARRES2 represented an unfavorable prognostic factor of glioma. In GBM, RARRES2 was also associated with IDH1 mutation. In both LGG and GBM, IDH1 mutation induced extensive DNA hypermethylation, and more than half genes that were downregulated in IDH1 mutant glioma were contributed by DNA hypermethylation. RARRES2 was also hypermethylated in IDH1 mutant LGG or GBM patients. Furthermore, RARRES2 hypomethylation was an unfavorable prognostic factor in patients with LGG.

CONCLUSIONS

RARRES2 was downregulated by IDH1 mutation and served as an unfavorable prognostic factor in glioma.

RYK Gene Expression Associated with Drug Response Variation of Temozolomide and Clinical Outcomes in Glioma Patients

Temozolomide (TMZ) chemotherapy is an important tool in the treatment of glioma brain tumors. However, variable patient response and chemo-resistance remain exceptionally challenging. Our previous genome-wide association study (GWAS) identified a suggestively significant association of SNP rs4470517 in the RYK (receptor-like kinase) gene with TMZ drug response. Functional validation of RYK using lymphocytes and glioma cell lines resulted in gene expression analysis indicating differences in expression status between genotypes of the cell lines and TMZ dose response. We conducted univariate and multivariate Cox regression analyses using publicly available TCGA and GEO datasets to investigate the impact of RYK gene expression status on glioma patient overall (OS) and progression-free survival (PFS). Our results indicated that in IDH mutant gliomas, RYK expression and tumor grade were significant predictors of survival. In IDH wildtype glioblastomas (GBM), MGMT status was the only significant predictor. Despite this result, we revealed a potential benefit of RYK expression in IDH wildtype GBM patients. We found that a combination of RYK expression and MGMT status could serve as an additional biomarker for improved survival. Overall, our findings suggest that RYK expression may serve as an important prognostic or predictor of TMZ response and survival for glioma patients.

Co-amplified with PDGFRA, IGFBP7 is a prognostic biomarker correlated with the immune infiltrations of glioma

BACKGROUND

A subgroup of glioma carry genetic 4q12 amplification including platelet derived growth factor receptor α (PDGFRA) and insulin like growth factor binding protein 7 (IGFBP7). However, the prognosis of PDGFRA and IGFBP7 in glioma is unclear.

METHODS

The prognosis of PDGFRA and IGFBP7 was determined using cox regression and Kaplan-Meier survival analysis. Pathways associated with IGFBP7 were analyzed through gene set enrichment analysis (GSEA). Immune profiling of glioma was determined using "ESTIMATE" and "TIMER" database.

RESULTS

PDGFRA amplification or expression was not correlated with the outcomes of glioblastoma (GBM). IGFBP7 but not PDGFRA was over-expressed in GBM. IGFBP7 over-expression was correlated with the unfavorable outcomes of GBM. In lower grade glioma (LGG), PDGFRA over-expression was not correlated with the unfavorable prognosis of LGG, while, IGFBP7 was a prognostic biomarker of LGG. LGG patients with IGFBP7 lower expressions had prolonged clinical overall survival. Combination of IDH mutation, LGG grade and IGFBP7 achieved even better prognostic effects in LGG. Moreover, IGFBP7 was over-expressed in glioma patients with wild type IDH or with high grades. IGFBP7 over-expression was correlated with the unfavorable outcomes of glioma. Furthermore, IGFBP7 was hypo-methylated in GBM or LGG patients without IDH mutations. IGFBP7 hyper-methylation was correlated with the lower overall survival of GBM or LGG. LGG patients with wild type IDH and with IGFBP7 hypo-methylation demonstrated even worse prognosis. IGFBP7 was associated with multiple immune-related signaling pathways in GBM or LGG. The stromal score, immune score and the infiltrations of immune cells were also correlated with IGFBP7 and the prognosis of LGG.

CONCLUSIONS

IGFBP7 but not PDGFRA served an ideal prognostic marker and therapeutic target of glioma.

In silico validation of RNA-Seq results can identify gene fusions with oncogenic potential in glioblastoma

RNA-Sequencing (RNA-Seq) can identify gene fusions in tumors, but not all these fusions have functional consequences. Using multiple data bases, we have performed an in silico analysis of fusions detected by RNA-Seq in tumor samples from 139 newly diagnosed glioblastoma patients to identify in-frame fusions with predictable oncogenic potential. Among 61 samples with fusions, there were 103 different fusions, involving 167 different genes, including 20 known oncogenes or tumor suppressor genes (TSGs), 16 associated with cancer but not oncogenes or TSGs, and 32 not associated with cancer but previously shown to be involved in fusions in gliomas. After selecting in-frame fusions able to produce a protein product and running Oncofuse, we identified 30 fusions with predictable oncogenic potential and classified them into four non-overlapping categories: six previously described in cancer; six involving an oncogene or TSG; four predicted by Oncofuse to have oncogenic potential; and 14 other in-frame fusions. Only 24 patients harbored one or more of these 30 fusions, and only two fusions were present in more than one patient: FGFR3::TACC3 and EGFR::SEPTIN14. This in silico study provides a good starting point for the identification of gene fusions with functional consequences in the pathogenesis or treatment of glioblastoma.

Molecular Features of Glioma Determined and Validated Using Combined TCGA and GTEx Data Analyses

Gliomas are among the most common intracranial tumors which originated from neuroepithelial cells. Increasing evidence has revealed that long noncoding RNA (lncRNA)-microRNA (miRNA)-mRNA module regulation and tumor-infiltrating immune cells play important regulatory roles in the occurrence and progression of gliomas. However, the precise underlying molecular mechanisms remain largely unknown. Data on gliomas in The Cancer Genome Atlas lack normal control samples; to overcome this limitation, we combined 665 The Cancer Genome Atlas glioma RNA sequence datasets with 188 Genotype-Tissue Expression normal brain RNA sequences to construct an expression matrix profile after normalization. We systematically analyzed the expression of mRNAs, lncRNAs, and miRNAs between gliomas and normal brain tissues. Kaplan–Meier survival analyses were conducted to screen differentially expressed mRNAs, lncRNAs, and miRNAs. A prognostic miRNA-related competitive endogenous RNA network was constructed, and the core subnetworks were filtered using 6 miRNAs, 3 lncRNAs, and 11 mRNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to investigate the biological functions of significantly dysregulated mRNAs. Co-expression network analysis was performed to analyze and screen the core genes. Furthermore, single-sample Gene Set Enrichment Analysis and immune checkpoint gene expression analysis were performed, as co-expression analysis indicated immune gene dysregulation in glioma. Finally, the expression of representative dysregulated genes was validated in U87 cells at the transcriptional level, establishing a foundation for further research. We identified 7017 mRNAs, 437 lncRNAs, and 9 miRNAs that were differentially expressed in gliomas. Kaplan–Meier survival analysis revealed 5684 mRNAs, 61 lncRNAs, and 7 miRNAs with potential as prognostic signatures in patients with glioma. The hub subnetwork of the competing endogenous RNA network between PART1-hsa-mir-25-SLC12A5/TACC2/BSN/TLN2/ZDHHC8 was screened out. Gene co-expression network, single-sample Gene Set Enrichment Analysis, and immune checkpoint expression analysis demonstrated that tumor-infiltrating immune cells are closely related to gliomas. We identified novel potential biomarkers to predict survival and therapeutic targets for patients with gliomas based on a large-scale sample. Importantly, we filtered pivotal genes that provide valuable information for further exploration of the molecular mechanisms underlying glioma tumorigenesis and progression.

Predicting prognosis and IDH mutation status for patients with lower-grade gliomas using whole slide images

We developed end-to-end deep learning models using whole slide images of adults diagnosed with diffusely infiltrating, World Health Organization (WHO) grade 2 gliomas to predict prognosis and the mutation status of a somatic biomarker, isocitrate dehydrogenase (IDH) 1/2. The models, which utilize ResNet-18 as a backbone, were developed and validated on 296 patients from The Cancer Genome Atlas (TCGA) database. To account for the small sample size, repeated random train/test splits were performed for hyperparameter tuning, and the out-of-sample predictions were pooled for evaluation. Our models achieved a concordance- (C-) index of 0.715 (95% CI: 0.569, 0.830) for predicting prognosis and an area under the curve (AUC) of 0.667 (0.532, 0.784) for predicting IDH mutations. When combined with additional clinical information, the performance metrics increased to 0.784 (95% CI: 0.655, 0.880) and 0.739 (95% CI: 0.613, 0.856), respectively. When evaluated on the WHO grade 3 gliomas from the TCGA dataset, which were not used for training, our models predicted survival with a C-index of 0.654 (95% CI: 0.537, 0.768) and IDH mutations with an AUC of 0.814 (95% CI: 0.721, 0.897). If validated in a prospective study, our method could potentially assist clinicians in managing and treating patients with diffusely infiltrating gliomas.

Association of Circadian Clock Gene Expression with Glioma Tumor Microenvironment and Patient Survival

Simple Summary

Gliomas are the most common type of malignant primary brain tumors and are classified according to the cell of origin and genetic features, which can help predict the prognosis and treatment sensitivity. Improving the prognosis remains a challenge; however, chronobiology is a promising field for future works, as circadian clock genes are linked to the tumor biology and outcomes in multiple cancers, including glioma. Here, we examined the relationship of circadian clock genes, IDH mutational status, and prognosis in glioma patients by using unsupervised clustering of the expression of 13 clock genes. We further explored the expression of the clock genes across the tumor regions and cell subpopulations, highlighting the importance of the tumor microenvironment in researching circadian rhythms in cancer. Our research is important for understanding how best to target circadian rhythms to improve patient outcomes in neuro-oncology.

Abstract

Circadian clock genes have been linked to clinical outcomes in cancer, including gliomas. However, these studies have not accounted for established markers that predict the prognosis, including mutations in Isocitrate Dehydrogenase (IDH), which characterize the majority of lower-grade gliomas and secondary high-grade gliomas. To demonstrate the connection between circadian clock genes and glioma outcomes while accounting for the IDH mutational status, we analyzed multiple publicly available gene expression datasets. The unsupervised clustering of 13 clock gene transcriptomic signatures from The Cancer Genome Atlas showed distinct molecular subtypes representing different disease states and showed the differential prognosis of these groups by a Kaplan–Meier analysis. Further analyses of these groups showed that a low period (PER) gene expression was associated with the negative prognosis and enrichment of the immune signaling pathways. These findings prompted the exploration of the relationship between the microenvironment and clock genes in additional datasets. Circadian clock gene expression was found to be differentially expressed across the anatomical tumor location and cell type. Thus, the circadian clock expression is a potential predictive biomarker in glioma, and further mechanistic studies to elucidate the connections between the circadian clock and microenvironment are warranted.

The presence of TIM-3 positive cells in WHO grade III and IV astrocytic gliomas correlates with isocitrate dehydrogenase mutation status

Diffuse gliomas are aggressive brain tumors that respond poorly to immunotherapy including immune checkpoint inhibition. This resistance may arise from an immunocompromised microenvironment and deficient immune recognition of tumor cells because of low mutational burden. The most prominent genetic alterations in diffuse glioma are mutations in the isocitrate dehydrogenase (IDH) genes that generate the immunosuppressive oncometabolite d-2-hydroxyglutarate. Our objective was to explore the association between IDH mutation and presence of cells expressing the immune checkpoint proteins galectin-9 and/or T cell immunoglobulin and mucin-domain containing-3 (TIM-3). Astrocytic gliomas of World Health Organization (WHO) grades III or IV (36 IDH-mutant and 36 IDH-wild-type) from 72 patients were included in this study. A novel multiplex chromogenic immunohistochemistry panel was applied using antibodies against galectin-9, TIM-3, and the oligodendrocyte transcription factor 2 (OLIG2). Validation studies were performed using data from The Cancer Genome Atlas (TCGA) project. IDH mutation was associated with decreased levels of TIM-3⁺ cells (p < 0.05). No significant association was found between galectin-9 and IDH status (p = 0.10). Most TIM-3⁺ and galectin-9⁺ cells resembled microglia/macrophages, and very few TIM-3⁺ and/or galectin-9⁺ cells co-expressed OLIG2. The percentage of TIM-3⁺ T cells was generally low, however, IDH-mutant tumors contained significantly fewer TIM-3⁺ T cells (p < 0.01) and had a lower interaction rate between TIM-3⁺ T cells and galectin-9⁺ microglia/macrophages (p < 0.05). TCGA data confirmed lower TIM-3 mRNA expression in IDH-mutant compared to IDH-wild-type astrocytic gliomas (p = 0.013). Our results show that IDH mutation is associated with diminished levels of TIM-3⁺ cells and fewer interactions between TIM-3⁺ T cells and galectin-9⁺ microglia/macrophages, suggesting reduced activity of the galectin-9/TIM-3 immune checkpoint pathway in IDH-mutant astrocytic gliomas.

Role of Temozolomide Regimen on Survival Outcomes in Molecularly Stratified WHO Grade II Gliomas: A Systematic Review

OBJECTIVE/INTRODUCTION

Although a critical chemotherapeutic, temozolomide's optimal regimen for 2016 World Health Organization (WHO) Grade II gliomas remains elusive, hence there is utility in not only cataloging survival outcomes of Grade II glioma subtypes against the background of temozolomide regimens, but also quantifying differences in progression-free survival (PFS) and overall survival (OS).

MATERIALS AND METHODS

A systematic review of MEDLINE, Embase, and Cochrane Central Register of Controlled Trails was conducted by using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis and the Cochrane Handbook of Systemic Reviews of Interventions.

RESULTS

Each molecular subtype of WHO Grade II glioma had a different temozolomide regimen identified as optimal in prolonging PFS and OS. For PFS, with temozolomide, the 25th, 50th, and 75th percentiles, were as follows (in months), respectively-A-wt II: 6.90, 12.95, and 19.95; A-mt II: 34.45, 36.01, and 39.60; OD II: 37.90, 46.00, and 55.03 (P = 0.016). For OS, the first quartile (25%), median (50%), third quartile (75%), were respectively identified (in months-A-wt II: 21.6 (median; n = 1); A-mt II: 60.6, 85.2, and 109.8; OD II: 86.1, 96.2, and 106.3 (P = 0.37).

CONCLUSION

For each tumor molecular subtype, a different temozolomide regimen was identified as optimal for prolonging PFS and OS. Furthermore, regardless of temozolomide regimen, A-wt II had a significantly shorter PFS than A-mt II and OD-II. Overall, the data can provide useful prognostic insight to patients when making critical treatment decisions. Moreover, by cataloging and assessing survival outcomes per temozolomide regimen, such may facilitate future clinical trial design.

RNA sequencing and Immunohistochemistry Reveal ZFN7 as a Stronger Marker of Survival than Molecular Subtypes in G-CIMP-negative Glioblastoma

PURPOSE

Glioblastoma is the most aggressive brain tumor in adults and has few therapeutic options. The study of molecular subtype classifications may lead to improved prognostic classification and identification of new therapeutic targets. The Cancer Genome Atlas (TCGA) subtype classification has mainly been applied in U.S. clinical trials, while the intrinsic glioma subtype (IGS) has mainly been applied in European trials.

EXPERIMENTAL DESIGN

From paraffin-embedded tumor samples of 432 patients with uniformly treated, newly diagnosed glioblastoma, we built tissue microarrays for IHC analysis and applied RNA sequencing to the best samples to classify them according to TCGA and IGS subtypes.

RESULTS

We obtained transcriptomic results from 124 patients. There was a lack of agreement among the three TCGA classificatory algorithms employed, which was not solely attributable to intratumoral heterogeneity. There was overlapping of TCGA mesenchymal subtype with IGS cluster 23 and of TCGA classical subtype with IGS cluster 18. Molecular subtypes were not associated with prognosis, but levels of expression of 13 novel genes were identified as independent prognostic markers in glioma-CpG island methylator phenotype-negative patients, independently of clinical factors and MGMT methylation. These findings were validated in at least one external database. Three of the 13 genes were selected for IHC validation. In particular, high ZNF7 RNA expression and low ZNF7 protein expression were strongly associated with longer survival, independently of molecular subtypes.

CONCLUSIONS

TCGA and IGS molecular classifications of glioblastoma have no higher prognostic value than individual genes and should be refined before being applied to clinical trials.

Transcriptional Characteristics of IDH-Wild Type Glioma Subgroups Highlight the Biological Processes Underlying Heterogeneity of IDH-Wild Type WHO Grade IV Gliomas

Isocitric dehydrogenase (IDH)-wild type diffuse gliomas, which have a poorer prognosis than their IDH-mutant counterparts, are also accompanied with high heterogeneity. Here, we aimed to identify the key biological processes associated with the three groups of IDH-wild type diffuse gliomas in 323 patients. By The Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT-NOW) update 3 recommendation, the three groups are Group A, diffuse astrocytic glioma, World Health Organization (WHO) grade II/III; Group B, diffuse astrocytic glioma, with one (or more) of the three genetic alterations: TERT promoter mutation, EGFR gene amplification, gain of chromosome 7 combined with loss of chromosome 10, WHO grade IV; and Group C, glioblastoma, WHO grade IV. Consistent with their histologic and genetic molecular features, we successfully identified that biological activities associated with “cell cycle” and “cell mitosis” are significantly elevated in Group B compared with Group A; microenvironment-related hallmarks “angiogenesis” and “hypoxia,” and biological processes of “extracellular matrix,” “immune response,” and “positive regulation of transcriptional activities” were more enriched in Group C than Group B. We also constructed a nine-gene signature from differentially expressed genes among the three groups to further stratify the WHO grade IV gliomas (Groups B and C) whose survival cannot be clearly stratified by current classification systems. This signature was an independent prognosis factor for WHO grade IV gliomas and had better prognostic value than other known factors in both training and validation dataset. In addition, the signature risk score was positively correlated with the amount of infiltrated immune cells, expression of immune checkpoints, and the genes enriched in biological processes of “immune response,” “cell cycle,” and “extracellular matrix.” The bioinformatic analysis results were also validated by immunohistochemistry and patient-derived cell proliferation assay. Overall, our findings revealed the key biological processes underlying the new classifications of IDH-wild type diffuse glioma. Meanwhile, we constructed a signature, which could properly stratify the prognosis, cell proliferation activates, extracellular matrix-mediated biological activities, and immune-microenvironment of IDH-wild type WHO grade IV gliomas.

Identification of a three-long non-coding RNA signature for predicting survival of temozolomide-treated isocitrate dehydrogenase mutant low-grade gliomas

Temozolomide (TMZ) is the major chemotherapy agent in glioma, and isocitrate dehydrogenase (IDH) is a well-known prognostic marker in glioma. O6-methylguanine-DNA methyltransferase promoter methylation (MGMTmethyl) is a predictive biomarker in overall gliomas rather than in IDH mutant gliomas. To discover effective biomarkers that could predict TMZ efficacy in IDH mutant low-grade gliomas (LGGs), we retrieved data of IDH mutant LGGs from TMZ arm of the EORTC22033-26033 trial as the training-set (n = 83), analyzed correlations between long non-coding RNAs (lncRNAs) and progression-free survival (PFS) using Lasso-Cox regression, and created a risk score (RS) to stratify patients. We identified a three-lncRNA signature in TMZ-treated IDH mutant LGGs. All of the three lncRNAs, as well as the RS derived, were significantly correlated with PFS. Patients were classified into high-risk and low-risk groups according to RS. PFS of the high-risk group was significantly worse than that of the low-risk group (P < 0.001). AUCs of the three-, four-, and five-year survival probability predicted by RS were 0.73, 0.79, and 0.76, respectively. The predictive role of the three-lncRNA signature was further validated in an independent testing-set, the TCGA-LGGs, which resulted in a significantly worse PFS (P < 0.001) in the high-risk group. Three-, four-, and five-year survival probabilities predicted by RS were 0.65, 0.69, and 0.84, respectively. Functions of these three lncRNAs involve cell proliferation and differentiation, predicted by their targeting cancer genes. Conclusively, we created a scoring model based on the expression of three lncRNAs, which can effectively predict the survival of IDH mutant LGGs treated with TMZ.

Glioblastoma TCGA Mesenchymal and IGS 23 Tumors are Identifiable by IHC and have an Immune-phenotype Indicating a Potential Benefit from Immunotherapy

PURPOSE

Molecular subtype classifications in glioblastoma may detect therapy sensitivities. IHC would potentially allow the identification of molecular subtypes in routine clinical practice.

EXPERIMENTAL DESIGN

Formalin-fixed, paraffin-embedded tumor samples of 124 uniformly treated, newly diagnosed patients with glioblastoma were submitted to RNA sequencing, IHC, and immune-phenotyping to identify differences in molecular subtypes associated with treatment sensitivities.

RESULTS

We detected high molecular and IHC overlapping of the The Cancer Genome Atlas (TCGA) mesenchymal subtype with instrinsic glioma subtypes (IGS) cluster 23 and of the TCGA classical subtype with IGS cluster 18. IHC patterns, gene fusion profiles, and immune-phenotypes varied across subtypes. IHC revealed that the TCGA classical subtype was identified by high expression of EGFR and low expression of PTEN, while the mesenchymal subtype was identified by low expression of SOX2 and high expression of two antibodies, SHC1 and TCIRG1, selected on the basis of RNA differential transcriptomic expression. The proneural subtype was identified by frequent positive IDH1 expression and high Olig2 and Ki67 expression. Immune-phenotyping showed that mesenchymal and IGS 23 tumors exhibited a higher positive effector cell score, a higher negative suppressor cell score, and lower levels of immune checkpoint molecules. The cell-type deconvolution analysis revealed that these tumors are highly enriched in M2 macrophages, resting memory CD4⁺ T cells, and activated dendritic cells, indicating that they may be ideal candidates for immunotherapy, especially with anti-M2 and/or dendritic cell vaccination.

CONCLUSIONS

There is a subset of tumors, frequently classified as mesenchymal or IGS cluster 23, that may be identified with IHC and could well be optimal candidates for immunotherapy.

An algorithm to quantify intratumor heterogeneity based on alterations of gene expression profiles

Intratumor heterogeneity (ITH) is a biomarker of tumor progression, metastasis, and immune evasion. Previous studies evaluated ITH mostly based on DNA alterations. Here, we developed a new algorithm (DEPTH) for quantifying ITH based on mRNA alterations in the tumor. DEPTH scores displayed significant correlations with ITH-associated features (genomic instability, tumor advancement, unfavorable prognosis, immunosuppression, and drug response). Compared to DNA-based ITH scores (EXPANDS, PhyloWGS, MATH, and ABSOLUTE), DEPTH scores had stronger correlations with antitumor immune signatures, cell proliferation, stemness, tumor advancement, survival prognosis, and drug response. Compared to two other mRNA-based ITH scores (tITH and sITH), DEPTH scores showed stronger and more consistent associations with genomic instability, unfavorable tumor phenotypes and clinical features, and drug response. We further validated the reliability and robustness of DEPTH in 50 other datasets. In conclusion, DEPTH may provide new insights into tumor biology and potential clinical implications for cancer prognosis and treatment.

Histopathological grading affects survival in patients with IDH-mutant grade II and grade III diffuse gliomas

BACKGROUND

Diffuse grade II and grade III gliomas are actually classified in accordance with the presence of isocitrate dehydrogenase mutation (IDH-mut) and the deletion of both 1p and 19q chromosome arms (1p/19q codel). The role of tumour grading as independent prognostic factor in these group of tumours remains matter of debate. The aim of this study was to determine if grade is an independent prognostic factor and not somehow associated to IDH mutation and 1p/19q status of the tumour.

METHODS

We analysed 399 consecutive patients with newly diagnosed, histologically proven World Health Organisation (WHO) 2016 grade II or grade III IDH-mut gliomas, assessed by polymerase chain reaction, immunohistochemistry or next-generation sequencing (NGS).

RESULTS

The analysis included 399 patients with grade II (n = 250, 62.7%) or grade III (n = 149, 37.3%) diffuse gliomas. Median follow-up time was 105.3 months. Median survival was 148.1 months. In multivariate analysis, grade II (hazard ratio [HR] = 0.342, 95% confidence interval [CI]: 0.221-0.531; P < 0.001) and 1p/19q codeletion (HR = 0.440, 95% CI: 0.290-0.668; P < 0.001) were independently associated with a lower risk for death. The difference in survival remained significant (p = 0.006 in astrocytomas, p = 0.014 in oligodendrogliomas) when adjusted for histological subtype. Residual disease after surgery (or biopsy) negatively affected survival (HR: 2.151, 95% CI: 1.375-3.367, P = 0.001). Post-surgical treatment with radiotherapy + adjuvant chemotherapy improved survival compared with follow-up and other treatments (HR: 0.316, 95% CI: 0.156-0.641, P = 0.001).

CONCLUSIONS

In our study, histopathological grade still affects survival in IDH-mutant WHO grade II and III diffuse gliomas. This effect appears to be independent from molecular features, extension of surgical resection and post-surgical treatments. Therefore, physicians should continue to take into account tumour grade, along their molecular characteristics, for a better clinical and therapeutic management of the patients.

Systematically characterize the clinical and biological significances of 1p19q genes in 1p/19q non-codeletion glioma

1p/19q codeletion, which leads to the abnormal expression of 1p19q genes in oligodendroglioma, is associated with chemosensitivity and favorable prognosis. Here, we aimed to explore the clinical implications of 1p19q gene expression in 1p/19q non-codel gliomas. We analyzed expression of 1p19q genes in 668 1p/19q non-codel gliomas obtained from The Cancer Genome Atlas (n = 447) and the Chinese Glioma Genome Atlas (n = 221) for training and validation, respectively. The expression of 1p19q genes was significantly correlated with the clinicopathological features and overall survival of 1p/19q non-codel gliomas. Then, we derived a risk signature of 25 selected 1p19q genes that not only had prognosis value in total 1p/19q non-codel gliomas but also had prognosis value in stratified gliomas. The prognosis value of the risk signature was superior than known clinicopathological features in 1p/19q non-codel gliomas and was also highly associated with the following features: loss of CDKN2A/B copy number in mutant-IDH-astrocytoma; telomerase reverse transcriptase (TERT) promoter mutation, combined chromosome 7 gain/chromosome 10 loss and epidermal growth factor receptor amplification in wild-type-IDH-astrocytoma; classical and mesenchymal subtypes in glioblastoma. Furthermore, genes enriched in the biological processes of cell division, extracellular matrix, angiogenesis significantly correlated to the signature risk score, and this is also supported by the immunohistochemistry and cell biology experiments. In conclusion, the expression profile of 1p19q genes is highly associated with the malignancy and prognosis of 1p/19q non-codel gliomas. A 25-1p19q-gene signature has powerfully predictive value for both malignant molecular pathological features and prognosis across distinct subgroups of 1p/19q non-codel gliomas.

Biomarkers for immunotherapy for treatment of glioblastoma

Immunotherapy is a promising new therapeutic field that has demonstrated significant benefits in many solid-tumor malignancies, such as metastatic melanoma and non-small cell lung cancer. However, only a subset of these patients responds to treatment. Glioblastoma (GBM) is the most common malignant primary brain tumor with a poor prognosis of 14.6 months and few treatment advancements over the last 10 years. There are many clinical trials testing immune therapies in GBM, but patient responses in these studies have been highly variable and a definitive benefit has yet to be identified. Biomarkers are used to quantify normal physiology and physiological response to therapies. When extensively characterized and vigorously validated, they have the potential to delineate responders from non-responders for patients treated with immunotherapy in malignancies outside of the central nervous system (CNS) as well as GBM. Due to the challenges of current modalities of radiographic diagnosis and disease monitoring, identification of new predictive and prognostic biomarkers to gauge response to immune therapy for patients with GBM will be critical in the precise treatment of this highly heterogenous disease. This review will explore the current and future strategies for the identification of potential biomarkers in the field of immunotherapy for GBM, as well as highlight major challenges of adapting immune therapy for CNS malignancies.

Comprehensive Analysis Reveals a 4-Gene Signature in Predicting Response to Temozolomide in Low-Grade Glioma Patients

Low-grade gliomas (LGGs) are a highly heterogeneous group of slow-growing, lethal, diffusive brain tumors. Temozolomide (TMZ) is a frequently used primary chemotherapeutic agent for LGGs. Currently there is no consensus as to the optimal biomarkers to predict the efficacy of TMZ, which calls for decision-making for each patient while considering molecular profiles. Low-grade glioma data sets were retrieved from The Cancer Genome Atlas. Cox regression and survival analyses were applied to identify clinical features significantly associated with survival. Subsequently, Ordinal logistic regression, co-expression, and Cox regression analyses were applied to identify genes that correlate significantly with response rate, disease-free survival, and overall survival of patients receiving TMZ as primary therapy. Finally, gene expression and methylation analyses were exploited to explain the mechanism between these gene expression and TMZ efficacy in LGG patients. Overall survival was significantly correlated with age, Karnofsky Performance Status score, and histological grade, but not with IDH1 mutation status. Using 3 distinct efficacy end points, regression and co-expression analyses further identified a novel 4-gene signature of ASPM, CCNB1, EXO1, and KIF23 which negatively correlated with response to TMZ therapy. In addition, expression of the 4-gene signature was associated with those of genes involved in homologous recombination. Finally, expression and methylation profiling identified a largely unknown olfactory receptor OR51F2 as potential mediator of the roles of the 4-gene signature in reducing TMZ efficacy. Taken together, these findings propose the 4-gene signature as a novel panel of efficacy predictors of TMZ therapy, as well as potential downstream mechanisms, including homologous recombination, OR51F2, and DNA methylation independent of MGMT.

Systematically profiling the expression of eIF3 subunits in glioma reveals the expression of eIF3i has prognostic value in IDH-mutant lower grade glioma

Background

Abnormal expression of the eukaryotic initiation factor 3 (eIF3) subunits plays critical roles in tumorigenesis and progression, and also has potential prognostic value in cancers. However, the expression and clinical implications of eIF3 subunits in glioma remain unknown.

Methods

Expression data of eIF3 for patients with gliomas were obtained from the Chinese Glioma Genome Atlas (CGGA) (n = 272) and The Cancer Genome Atlas (TCGA) (n = 595). Cox regression, the receiver operating characteristic (ROC) curves and Kaplan–Meier analysis were used to study the prognostic value. Gene oncology (GO) and gene set enrichment analysis (GSEA) were utilized for functional prediction.

Results

In both the CGGA and TCGA datasets, the expression levels of eIF3d, eIF3e, eIF3f, eIF3h and eIF3l highly were associated with the IDH mutant status of gliomas. The expression of eIF3b, eIF3i, eIF3k and eIF3m was increased with the tumor grade, and was associated with poorer overall survival [All Hazard ratio (HR) > 1 and P < 0.05]. By contrast, the expression of eIF3a and eIF3l was decreased in higher grade gliomas and was associated with better overall survival (Both HR < 1 and P < 0.05). Importantly, the expression of eIF3i (located on chromosome 1p) and eIF3k (Located on chromosome 19q) were the two highest risk factors in both the CGGA [eIF3i HR = 2.068 (1.425–3.000); eIF3k HR = 1.737 (1.166–2.588)] and TCGA [eIF3i HR = 1.841 (1.642–2.064); eIF3k HR = 1.521 (1.340–1.726)] databases. Among eIF3i, eIF3k alone or in combination, the expression of eIF3i was the more robust in stratifying the survival of glioma in various pathological subgroups. The expression of eIF3i was an independent prognostic factor in IDH-mutant lower grade glioma (LGG) and could also predict the 1p/19q codeletion status of IDH-mutant LGG. Finally, GO and GSEA analysis showed that the elevated expression of eIF3i was significantly correlated with the biological processes of cell proliferation, mRNA processing, translation, T cell receptor signaling, NF-κB signaling and others.

Conclusions

Our study reveals the expression alterations during glioma progression, and highlights the prognostic value of eIF3i in IDH-mutant LGG.

Electronic supplementary material

The online version of this article (10.1186/s12935-019-0867-1) contains supplementary material, which is available to authorized users.

Management for Different Glioma Subtypes: Are All Low-Grade Gliomas Created Equal?

Following the identification of key molecular alterations that provided superior prognostication and led to the updated 2016 World Health Organization (WHO) Central Nervous System (CNS) Tumor Classification, the understanding of glioma behavior has rapidly evolved. Mutations in isocitrate dehydrogenase (IDH) 1 and 2 are present in the majority of adult grade 2 and 3 gliomas, and when used in conjunction with 1p/19q codeletion for classification, the prognostic distinction between grade 2 versus grade 3 is diminished. As such, the previously often used term of "low-grade glioma," which referred to grade 2 gliomas, has now been replaced by the phrase "lower-grade glioma" to encompass both grade 2 and 3 tumors. Additional molecular characterization is ongoing to even further classify this heterogeneous group of tumors. With such a colossal shift in the understanding of lower-grade gliomas, management of disease is being redefined in the setting of emerging molecular-genetic biomarkers. In this article, we review recent progress and future directions regarding the surgical, radiotherapeutic, chemotherapeutic, and long-term management of adult lower-grade gliomas.