Multiomics Data Analysis and Identification of Immune-Related Prognostic Signatures With Potential Implications in Prognosis and Immune Checkpoint Blockade Therapy of Glioblastoma.

Background: In recent years, glioblastoma multiforme (GBM) has been a concern of many researchers, as it is one of the main drivers of cancer-related deaths worldwide. GBM in general usually does not responding well to immunotherapy due to its unique microenvironment. Methods: To uncover any further informative immune-related prognostic signatures, we explored the immune-related distinction in the genetic or epigenetic features of the three types (expression profile, somatic mutation, and DNA methylation). Twenty eight immune-related hub genes were identified by Weighted Gene Co-Expression Network Analysis (WGCNA). The findings showed that three genes (IL1R1, TNFSF12, and VDR) were identified to construct an immune-related prognostic model (IRPM) by lasso regression. Then, we used three hub genes to construct an IRPM for GBM and clarify the immunity, mutation, and methylation characteristics. Results: Survival analysis of patients undergoing anti-program cell death protein 1 (anti-PD-1) therapy showed that overall survival was superior in the low-risk group than in the high-risk group. The high-risk group had an association with epithelial-mesenchymal transition (EMT), high immune cell infiltration, immune activation, a low mutation number, and high methylation, while the low-risk group was adverse status. Conclusions: In conclusion, IRPM is a promising tool to distinguish the prognosis of patients and molecular and immune characteristics in GBM, and the IRPM risk score can be used to predict patient sensitivity to checkpoint inhibitor blockade therapy. Thus, three immune-related signatures will guide us in improving treatment strategies and developing objective diagnostic tools.

5-Methylcytosine Related LncRNAs Reveal Immune Characteristics, Predict Prognosis and Oncology Treatment Outcome in Lower-Grade Gliomas.

5-Methylcytosine (m5C) methylation is an important RNA modification pattern that can participate in oncogenesis and progression of cancers by affecting RNA stability, expression of oncogenes, and the activity of cancer signaling pathways. Alterations in the expression pattern of long non-coding RNAs (lncRNAs) are potentially correlated with abnormalities in the m5C regulation features of cancers. Our aim was to reveal the mechanisms by which lncRNAs regulated the m5C process, to explore the impact of aberrant regulation of m5C on the biological properties of lower-grade gliomas (LGG), and to optimize current therapeutic. By searching 1017 LGG samples from the Cancer Genome Atlas and Chinese Glioma Genome Atlas, we first clarified the potential impact of m5C regulators on LGG prognosis in this study and used univariate Cox analysis and least absolute shrinkage and selection operator regression to explore clinically meaningful lncRNAs. Consequently, we identified four lncRNAs, including LINC00265, CIRBP-AS1, GDNF-AS1, and ZBTB20-AS4, and established a novel m5C-related lncRNAs signature (m5CrLS) that was effective in predicting prognosis. Notably, mutation rate, WHO class II, IDH mutation, 1p/19q co-deletion and MGMT promoter methylation were increased in the low m5CrLS score group. Patients with increased m5CrLS scores mostly showed activation of tumor malignancy-related pathways, increased immune infiltrating cells, and decreased anti-tumor immune function. Besides, the relatively high expression of immune checkpoints also revealed the immunosuppressed state of patients with high m5CrLS scores. In particular, m5CrLS stratification was sensitive to assess the efficacy of LGG to temozolomide and the responsiveness of immune checkpoint blockade. In conclusion, our results revealed the molecular basis of LGG, provided valuable clues for our understanding of m5C-related lncRNAs, and filled a gap between epigenetics and tumor microenvironment.

Integrated analysis of genome-wide DNA methylation and cancer-associated fibroblasts identified prognostic biomarkers and immune checkpoint blockade in lower grade gliomas.

Background: Cancer-associated fibroblasts (CAFs) are vital components of prominent cellular components in lower-grade gliomas (LGGs) that contribute to LGGs' progression, treatment resistance, and immunosuppression. Epigenetic modification and immunity have significant implications for tumorigenesis and development. Methods: We combined aberrant methylation and CAFs abundances to build a prognostic model and the impact on the biological properties of LGGs. Grouping based on the median CAFs abundances score of samples in the TCGA-LGGs dataset, differentially expressed genes and aberrantly methylated genes were combined for subsequent analysis. Results: We identified five differentially methylated and expressed genes (LAT32, SWAP70, GSAP, EMP3, and SLC2A10) and established a prognostic gene signature validated in the CGGA-LGGs dataset. Immunohistochemistry (IHC) and in vitro tests were performed to verify these expressions. The high-risk group increased in tumor-promoting immune cells and tumor mutational burden. Notably, risk stratification had different ICB sensitivities in LGGs, and there were also significant sensitivity differences for temozolomide and the other three novel chemotherapeutic agents. Conclusion: Our study reveals characteristics of CAFs in LGGs, refines the direct link between epigenetics and tumor stroma, and might provide clinical implications for guiding tailored anti-CAFs therapy in combination with immunotherapy for LGGs patients.

Recognition of Tumor-Associated Antigens and Immune Subtypes in Glioma for mRNA Vaccine Development.

Background: Although mRNA vaccines have been efficient for combating a variety of tumors, their effectiveness against glioma remains unclear. There is growing evidence that immunophenotyping can reflect the comprehensive immune status and microenvironment of the tumor, which correlates closely with treatment response and vaccination potency. The purpose of this research was to screen for effective antigens in glioma that could be used for developing mRNA vaccines and to further differentiate the immune subtypes of glioma to create an selection criteria for suitable patients for vaccination. Methods: Gene expression profiles and clinical data of 698 glioma samples were extracted from The Cancer Genome Atlas, and RNA_seq data of 1018 glioma samples was gathered from Chinese Glioma Genome Atlas. Gene Expression Profiling Interactive Analysis was used to determine differential expression genes and prognostic markers, cBioPortal software was used to verify gene alterations, and Tumor Immune Estimation Resource was used to investigate the relationships among genes and immune infiltrating cells. Consistency clustering was applied for consistent matrix construction and data aggregation, Gene oncology enrichment was performed for functional annotation, and a graph learning-based dimensionality reduction method was applied to describe the subtypes of immunity. Results: Four overexpressed and mutated tumor antigens associated with poor prognosis and infiltration of antigen presenting cells were identified in glioma, including TP53, IDH1, C3, and TCF12. Besides, four immune subtypes of glioma (IS1-IS4) and 10 immune gene modules were identified consistently in the TCGA data. The immune subtypes had diverse molecular, cellular, and clinical features. IS1 and IS4 displayed an immune-activating phenotype and were associated with worse survival than the other two subtypes, while IS2 and IS3 had lower levels of tumor immune infiltration. Immunogenic cell death regulators and immune checkpoints were also diversely expressed in the four immune subtypes. Conclusion: TP53, IDH1, C3, and TCF12 are effective antigens for the development of anti-glioma mRNA vaccines. We found four stable and repeatable immune subtypes of human glioma, the classification of the immune subtypes of glioma may play a crucial role in the predicting mRNA vaccine outcome.

Dihydroartemisinin prompts amplification of photodynamic therapy-induced reactive oxygen species to exhaust Na/H exchanger 1-mediated glioma cells invasion and migration.

Photodynamic therapy (PDT) is a promising glioma therapy; however, its efficacy is compromised due to the PDT-induced reactive oxygen species (ROS) production being limited by the local hypoxic tumor microenvironment. Furthermore, Hypoxia activates sodium/hydrogen exchanger 1 (NHE1), an essential component for tumor progression and metastasis, enables glioma cells (GC) to escape PDT-mediated phototoxicity via increased H+ extrusion. However, interactions between NHE1 expression with ROS level involving response of GC remain unclear. Dihydroartemisinin (DHA), a ROS generator, has extensive anti-tumor effects. This study aimed to explore whether PDT along with DHA could amplify the total ROS levels and diminish GC invasion and migration by inhibiting NHE1 expression. Proliferation and invasion of U251 and LN229 cells were evaluated under different treatments using cell counting Kit-8 (CCK-8), transwell, and wound healing assays. ROS levels were measured using fluorescence probes and flow cytometry. NHE1 levels were detected by immunofluorescence and western blotting. Co-treatment effects and molecular events were further confirmed in a bilateral tumor-bearing nude mouse model. PDT with synergistic DHA significantly increased the total abundance of ROS to further suppress the invasion and migration of GC by reducing NHE1 levels in vitro. Using a bilateral glioma xenograft mouse model with primary and recurrent gliomas, we found that PDT markedly suppressed primary tumor growth, while PDT in synergy with DHA also suppressed recurrent tumors, and improved overall survival by regulating the ROS-NHE1 axis. No evident side effects were observed. Our results suggest that PDT with DHA can amplify the total ROS levels to weaken GC invasion and migration by suppressing NHE1 expression in vitro and in vivo, thus abolishing the resistance of GC to PDT. The synergistic therapy of PDT and DHA therefore represents a more efficient and safe strategy for comprehensive glioma treatment.

Construction of Interferon-Gamma-Related Gene Signature to Characterize the Immune-Inflamed Phenotype of Glioblastoma and Predict Prognosis, Efficacy of Immunotherapy and Radiotherapy.

Interferon-gamma (IFNG) has profound impacts on tumor-immune interaction and is of great clinical significance for multiple cancers. Exploring the role of IFNG in glioblastoma (GBM) may optimize the current treatment paradigm of this disease. Here, multi-dimensional data of 429 GBM samples were collected. Various bioinformatics algorithms were employed to establish a gene signature that characterizes immunological features, genomic alterations, and clinical characteristics associated with the IFNG response. In this way, a novel IFNG-related gene signature (IFNGrGS, including TGFBI, IL4I1, ACP5, and LUM) has been constructed and validated. Samples with increased IFNGrGS scores were characterized by increased neutrophil and macrophage infiltration and exuberant innate immune responses, while the activated adaptive immune response may be frustrated by multiple immunosuppressive mechanisms. Notably, the IFNG pathway as well as its antagonistic pathways including IL4, IL10, TGF-beta, and VEGF converged on the expression of immune checkpoints. Besides, gene mutations involved in the microenvironment were associated with the IFNGrGS-based stratification, where the heterogeneous prognostic significance of EGFR mutation may be related to the different degrees of IFNG response. Moreover, the IFNGrGS score had solid prognostic value and the potential to screen ICB and radiotherapy sensitive populations. Collectively, our study provided insights into the role of IFNG on the GBM immune microenvironment and offered feasible information for optimizing the treatment of GBM.

FtMt promotes glioma tumorigenesis and angiogenesis via lncRNA SNHG1/miR-9-5p axis.

OBJECTIVE: This study is to investigate the effects and the mechanisms of mitochondrial ferritin (FtMt) on the glioma tumorigenesis and angiogenesis. METHODS: FtMt expression was detected in glioma tissues and cells as well as in nude mouse tissues. Cell proliferation and apoptosis rate were observed following transfection of LV-FtMt or sh-FtMt in glioma cell line. Moreover, glioma cells with FtMt over-expression/knockdown were co-cultured with human umbilical vein endothelial cells (HUVECs) to observe its function on HUVEC proliferation, angiogenic ability and the vascular endothelial growth factor (VEGF) content. Gain and loss of function of small nucleolar RNA host gene 1 (SNHG1) and miR-9-5p were performed in glioma cells and GBM nude mice to observe its effect on glioma cell proliferation and HUVEC angiogenic ability. Luciferase reporter gene and RIP assay were employed to inspect the interactions among SNHG1, FtMt and miR-9-5p. Additionally, a xenograft mouse model was applied to determine the role of FtMt in glioma. RESULTS: In this work, FtMt was strongly expressed in glioma tissues and cells as well as in nude mouse tumor tissues. The employment of the loss-of and gain-of functions assays illustrated that FtMt enhanced glioma tumorigenesis and angiogenesis. Mechanistically, our findings showed that FtMt positively related to SNHG1 while negatively correlated with miR-9-5p, and both SNHG1 and FtMt can competitively bind with miR-9-5p. Besides, the inhibition effects of sh-FtMt on glioma were surveyed in vivo experiments. CONCLUSION: Evidence in this study suggested that FtMt promotes glioma tumorigenesis and angiogenesis via SNHG1 mediated miR-9-5p expression, which may provide a theoretical basis for glioma treatment.

Malignant Evaluation and Clinical Prognostic Values of m6A RNA Methylation Regulators in Glioblastoma.

N6-methyladenosine (m6A) RNA methylation, the most common form of mRNA modification and regulated by the m6A RNA methylation regulators ("writers," "erasers," and "readers"), has been reported to be associated with the progression of the malignant tumor. However, its role in glioblastoma (GBM) has been poorly known. This study aimed to identify the expression, potential functions, and prognostic values of m6A RNA methylation regulators in GBM. Here, we revealed that the 13 central m6A RNA methylation regulators were firmly related to the clinical and molecular phenotype of GBM. Taking advantage of consensus cluster analysis, we obtained two categories of GBM samples and found malignancy-related processes of m6A methylation regulators and compounds that specifically targeted the malignant processes. Besides, we also obtained a list of genes with poor prognosis in GBM. Finally, we derived a risk-gene signature with three selected m6A RNA methylation regulators, which allowed us to extend the in-depth study and dichotomized the OS of patients with GBM into high- and low-risk subgroups. Notably, this risk-gene signature could be used as independent prognostic markers and accurate clinicopathological parameter predictors. In conclusion, m6A RNA methylation regulators are a type of vital participant in the malignant progression of GBM, with a critical potential in the prognostic stratification and treatment strategies of GBM.

Identification of Prognostic Model and Biomarkers for Cancer Stem Cell Characteristics in Glioblastoma by Network Analysis of Multi-Omics Data and Stemness Indices.

The progression of most human cancers mainly involves the gradual accumulation of the loss of differentiated phenotypes and the sequential acquisition of progenitor and stem cell-like features. Glioblastoma multiforme (GBM) stem cells (GSCs), characterized by self-renewal and therapeutic resistance, play vital roles in GBM. However, a comprehensive understanding of GBM stemness remains elusive. Two stemness indices, mRNAsi and EREG-mRNAsi, were employed to comprehensively analyze GBM stemness. We observed that mRNAsi was significantly related to multi-omics parameters (such as mutant status, sample type, transcriptomics, and molecular subtype). Moreover, potential mechanisms and candidate compounds targeting the GBM stemness signature were illuminated. By combining weighted gene co-expression network analysis with differential analysis, we obtained 18 stemness-related genes, 10 of which were significantly related to survival. Moreover, we obtained a prediction model from both two independent cancer databases that was not only an independent clinical outcome predictor but could also accurately predict the clinical parameters of GBM. Survival analysis and experimental data confirmed that the five hub genes (CHI3L2, FSTL3, RPA3, RRM2, and YTHDF2) could be used as markers for poor prognosis of GBM. Mechanistically, the effect of inhibiting the proliferation of GSCs was attributed to the reduction of the ratio of CD133 and the suppression of the invasiveness of GSCs. The results based on an in vivo xenograft model are consistent with the finding that knockdown of the hub gene inhibits the growth of GSCs in vitro. Our approach could be applied to facilitate the development of objective diagnostic and targeted treatment tools to quantify cancer stemness in clinical tumors, and perhaps lead considerable benefits that could predict tumor prognosis, identify new stemness-related targets and targeted therapies, or improve targeted therapy sensitivity. The five genes identified in this study are expected to be the targets of GBM stem cell therapy.