A five-CpG signature of microRNA methylation in non-G-CIMP glioblastoma

DNA methylation heterogeneity attributable to a complex tumor immune microenvironment prompts prognostic risk in glioma

Gliomas are malignant tumours of the human nervous system with different World Health Organization (WHO) classifications, glioblastoma (GBM) with higher grade and are more malignant than lower-grade glioma (LGG). To dissect how the DNA methylation heterogeneity in gliomas is influenced by the complex cellular composition of the tumour immune microenvironment, we first compared the DNA methylation profiles of purified human immune cells and bulk glioma tissue, stratifying three tumour immune microenvironmental subtypes for GBM and LGG samples from The Cancer Genome Atlas (TCGA). We found that more intermediate methylation sites were enriched in glioma tumour tissues, and used the Proportion of sites with Intermediate Methylation (PIM) to compare intertumoral DNA methylation heterogeneity. A larger PIM score reflected stronger DNA methylation heterogeneity. Enhanced DNA methylation heterogeneity was associated with stronger immune cell infiltration, better survival rates, and slower tumour progression in glioma patients. We then created a Cell-type-associated DNA Methylation Heterogeneity Contribution (CMHC) score to explore the impact of different immune cell types on heterogeneous CpG site (CpGct) in glioma tissues. We identified eight prognosis-related CpGct to construct a risk score: the Cell-type-associated DNA Methylation Heterogeneity Risk (CMHR) score. CMHR was positively correlated with cytotoxic T-lymphocyte infiltration (CTL), and showed better predictive performance for IDH status (AUC = 0.96) and glioma histological phenotype (AUC = 0.81). Furthermore, DNA methylation alterations of eight CpGct might be related to drug treatments of gliomas. In conclusion, we indicated that DNA methylation heterogeneity is associated with a complex tumour immune microenvironment, glioma phenotype, and patient's prognosis.

Multi-cohort comprehensive analysis unveiling the clinical value and therapeutic effect of GNAL in glioma

Clinical data indicates that glioma patients have poor treatment outcomes and clinical prognosis. The role of olfactory signaling pathway-related genes (OSPRGs) in glioma has not been fully elucidated. In this study, we aimed to investigate the role and relationship between OSPRGs and glioma. Univariate and multivariate Cox regression analyses were performed to assess the relationship between OSPRGs and the overall survival of glioma based on public cohorts, and the target gene (G Protein Subunit Alpha L, GNAL) was screened. The association of GNAL expression with clinicopathological characteristics, gene mutation landscape, tumor immune microenvironment (TIME), deoxyribonucleic acid (DNA) methylation, and naris-occlusion controlled genes (NOCGs) was performed. Immunohistochemistry was used to evaluate GNAL level in glioma. Further analysis was conducted to evaluate the drug sensitivity, immunotherapy response, and functional enrichment of GNAL. GNAL was an independent prognostic factor, and patients with low GNAL expression have a poor prognosis. Expression of GNAL was closely associated with clinicopathological characteristics, DNA methylation, and several immune-related pathways. Immune infiltration analysis indicated that GNAL levels were negatively correlated with immune scores. GNAL low-expression group showed efficacy with anti-PD-1 therapy. Ten compounds with significantly different half-maximal inhibitory concentration (IC50) values between the GNAL high and low-expression groups were identified. Furthermore, its expression was associated with several immune cells, immune-related genes, and NOCGs. The expression of GNAL is closely associated with clinicopathological characteristics, TIME, and the response to therapeutic interventions, highlighting its potential as a prognostic biomarker for glioma.

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.

LRRFIP1, an epigenetically regulated gene, is a prognostic biomarker and predicts malignant phenotypes of glioma

Aims

Glioblastoma (GBM) is the most common malignant brain tumor with an adverse prognosis in the central nervous system. Traditional histopathological diagnosis accompanied by subjective deviations cannot accurately reflect tumor characteristics for clinical guidance. DNA methylation plays a critical role in GBM genesis. The focus of this project was to identify an effective methylation point for the classification of gliomas, the interactions between DNA methylation and potential epigenetic targeted therapies for clinical treatments.

Methods

Three online (TCGA, CGGA, and REMBRANDT) databases were employed in this study. T‐test, Venn analysis, univariate cox analysis, and Pearson's correlation analysis were adopted to screen significant prognostic methylation genes. Clinical samples were collected to determine the distributions of LRRFIP1 (Leucine Rich Repeat of Flightless‐1 Interacting Protein) protein by immunohistochemistry assay. Kaplan–Meier survival and Cox analysis were adopted to evaluate the prognostic value of LRRFIP1. Nomogram model was used to construct a prediction model. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway were performed to explore functions and related mechanisms of LRRFIP1 in gliomas.

Results

Our results showed that 16 genes were negatively connected with their methylation level and correlated with clinical prognosis of GBM patients. Among them, LRRFIP1 expression showed the highest correlation with its methylation level. LRRFIP1 was highly expressed in WHO IV, mesenchymal, and IDH wild‐type subtype. LRRFIP1 expression was an independent risk factor for OS (overall survival) in gliomas.

Conclusion

LRRFIP1 is an epigenetically regulated gene and a potential prognostic biomarker for glioma. Our research may be beneficial to evaluate clinical efficacy, assess the prognosis, and provide individualized treatment for gliomas.

Evaluation of a tumor electric field treatment system in a rat model of glioma

Objective

Glioma is a devastating disease lacking effective treatment. Tumor electric field therapy is emerging as a novel non‐invasive therapy. The current study evaluates the efficacy and safety of a self‐designed tumor electric field therapy system (TEFTS ASCLU‐300) in a rat orthotopic transplantation model of glioma.

Methods

A model of intracranial orthotopic transplantation was established in rats using glioma C6 cells. For electric field therapy, glioma‐bearing rats were exposed to alternating electric fields generated by a self‐developed TEFTS starting on either 1st (Group 2) or 3rd (Group 3) day after transplantation, while other conditions were maintained the same as non‐treated rats (Group 1). Glioma size, body weight, and overall survival (OS) were compared between groups. Immunohistochemical staining was applied to access tumor cell death and microvessel density within the tumor. In addition, the systemic effects of TEFTS on blood cells, vital organs, and hepatorenal functions were evaluated.

Results

TEFTS treatment significantly elongated the OS of tumor‐bearing rats compared with non‐treated rats (non‐treated vs treated: 24.77 ± 7.08 days vs 40.31 ± 19.11 days, P = .0031). Continuous TEFTS treatment starting on 1st or 3rd day significantly reduced glioma size at 2 and 3 weeks after tumor cell inoculation (Week 2: Group 1:289.95 ± 101.69 mm³; Group 2:70.45 ± 17.79 mm³; Group 3:73.88 ± 33.21 mm³, P < .0001. Week 3: Group 1:544.096 ± 78.53 mm³; Group 2:187.58 ± 78.44 mm³; Group 3:167.14 ± 109.96 mm³, P = .0005). Continuous treatment for more than 4 weeks inhibited tumor growth. The TEFTS treatment promoted tumor cell death, as demonstrated by increased number of Caspase 3⁺ cells within the tumor (non‐treated vs treated: 38.06 ± 10.04 vs 68.57 ± 8.09 cells/field, P = .0007), but had minimal effect on microvessel density, as shown by CD31 expression (non‐treated vs treated: 1.63 ± 0.09 vs 1.57 ± 0.13% of positively stained areas, P > .05). No remarkable differences were observed in hepatorenal function, blood cell counts, or other vital organs between non‐treated and treated groups.

Conclusion

The TEFTS developed by our research team was proved to be effective and safe to inhibit tumor growth and improve general outcomes in a rat model of brain glioma.

Identification of a Tumor Microenvironment-Related Eight-Gene Signature for Predicting Prognosis in Lower-Grade Gliomas

Lower-grade gliomas (LrGG), characterized by invasiveness and heterogeneity, remain incurable with current therapies. Clinicopathological features provide insufficient information to guide optimal individual treatment and cannot predict prognosis completely. Recently, an increasing amount of studies indicate that the tumor microenvironment plays a pivotal role in tumor malignancy and treatment responses. However, studies focusing on the tumor microenvironment (TME) of LrGG are still limited. In this study, taking advantage of the currently popular computational methods for estimating the infiltration of tumor-associated normal cells in tumor samples and using weighted gene co-expression network analysis, we screened the co-expressed gene modules associated with the TME and further identified the prognostic hub genes in these modules. Furthermore, eight prognostic hub genes (ARHGDIB, CLIC1, OAS3, PDIA4, PARP9, STAT1, TAP2, and TAGLN2) were selected to construct a prognostic risk score model using the least absolute shrinkage and selection operator method. Univariate and multivariate Cox regression analysis demonstrated that the risk score was an independent prognostic factor for LrGG. Moreover, time-dependent ROC curves indicated that our model had favorable efficiency in predicting both short- and long-term prognosis in LrGG patients, and the stratified survival analysis demonstrated that our model had prognostic value for different subgroups of LrGG patients. Additionally, our model had potential value for predicting the sensitivity of LrGG patients to radio- and chemotherapy. Besides, differential expression analysis showed that the eight genes were aberrantly expressed in LrGG compared to normal brain tissue. Correlation analysis revealed that the expression of the eight genes was significantly associated with the infiltration levels of six types of immune cells in LrGG. In summary, the TME-related eight-gene signature was significantly associated with the prognosis of LrGG patients. They might act as potential prognostic biomarkers for LrGG patients, offer better stratification for future clinical trials, and be candidate targets for immunotherapy, thus deserving further investigation.

A five-CpG signature of microRNA methylation in non-G-CIMP glioblastoma

AIMS

DNA methylation has been found to regulate microRNAs (miRNAs) expression, but the prognostic value of miRNA-related DNA methylation aberration remained largely elusive in cancers including glioblastomas (GBMs). This study aimed to investigate the clinical and biological feature of miRNA methylation in GBMs of non-glioma-CpG island methylator phenotype (non-G-CIMP).

METHODS

Prognostic miRNA methylation loci were analyzed, with TCGA and Rennes cohort as training sets, and independent datasets of GBMs and low-grade gliomas (LGGs) were obtained as validation sets. Different statistical and bioinformatic analysis and experimental validations were performed to clinically and biologically characterize the signature.

RESULTS

We identified and validated a risk score based on methylation status of five miRNA-associated CpGs which could predict survival of GBM patients in a series of training and validation sets. This signature was independent of age and O-6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. The risk subgroup was associated with angiogenesis and accordingly differential responses to bevacizumab-contained therapy. MiRNA target analysis and in vitro experiments further confirmed the accuracy of this signature.

CONCLUSION

The five-CpG signature of miRNA methylation was biologically relevant and was of potential prognostic and predictive value for GBMs. It might be of help for improving individualized treatment.