DNA Methylation-Driven Genes for Developing Survival Nomogram for Low-Grade Glioma

A multi-omics analysis-based model to predict the prognosis of low-grade gliomas

Lower-grade gliomas (LGGs) exhibit highly variable clinical behaviors, while classic histology characteristics cannot accurately reflect the authentic biological behaviors, clinical outcomes, and prognosis of LGGs. In this study, we carried out analyses of whole exome sequencing, RNA sequencing and DNA methylation in primary vs. recurrent LGG samples, and also combined the multi-omics data to construct a prognostic prediction model. TCGA-LGG dataset was searched for LGG samples. 523 samples were used for whole exome sequencing analysis, 532 for transcriptional analysis, and 529 for DNA methylation analysis. LASSO regression was used to screen genes with significant association with LGG survival from the frequently mutated genes, differentially expressed genes, and differentially methylated genes, whereby a prediction model for prognosis of LGG was further constructed and validated. The most frequently mutated diver genes in LGGs were IDH1 (77%), TP53 (48%), ATRX (37%), etc. Top significantly up-regulated genes were C6orf15, DAO, MEOX2, etc., and top significantly down-regulated genes were DMBX1, GPR50, HMX2, etc. 2077 genes were more and 299 were less methylated in recurrent vs. primary LGG samples. Thirty-nine genes from the above analysis were included to establish a prediction model of survival, which showed that the high-score group had a very significantly shorter survival than the low-score group in both training and testing sets. ROC analysis showed that AUC was 0.817 for the training set and 0.819 for the testing set. This study will be beneficial to accurately predict the survival of LGGs to identify patients with poor prognosis to take specific treatment as early, which will help improve the treatment outcomes and prognosis of LGG.

Cuproptosis-related gene-located DNA methylation in lower-grade glioma: Prognosis and tumor microenvironment

Cuproptosis a novel copper-dependent cell death modality, plays a crucial part in the oncogenesis, progression and prognosis of tumors. However, the relationships among DNA-methylation located in cuproptosis-related genes (CRGs), overall survival (OS) and the tumor microenvironment remain undefined. In this study, we systematically assessed the prognostic value of CRG-located DNA-methylation for lower-grade glioma (LGG). Clinical and molecular data were sourced from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We employed Cox hazard regression to examine the associations between CRG-located DNA-methylation and OS, leading to the development of a prognostic signature. Kaplan-Meier survival and time-dependent receiver operating characteristic (ROC) analyses were utilized to gauge the accuracy of the signature. Gene Set Enrichment Analysis (GSEA) was applied to uncover potential biological functions of differentially expressed genes between high- and low-risk groups. A three CRG-located DNA-methylation prognostic signature was established based on TCGA database and validated in GEO dataset. The 1-year, 3-year, and 5-year area under the curve (AUC) of ROC curves in the TCGA dataset were 0.884, 0.888, and 0.859 while those in the GEO dataset were 0.943, 0.761 and 0.725, respectively. Cox-regression-analyses revealed the risk signature as an independent risk factor for LGG patients. Immunogenomic profiling suggested that the signature was associated with immune infiltration level and immune checkpoints. Functional enrichment analysis indicated differential enrichment in cell differentiation in the hindbrain, ECM receptor interactions, glycolysis and reactive oxygen species pathway across different groups. We developed and verified a novel CRG-located DNA-methylation signature to predict the prognosis in LGG patients. Our findings emphasize the potential clinical implications of CRG-located DNA-methylation indicating that it may serve as a promising therapeutic target for LGG patients.

Cardiomyopathy associated 5 (CMYA5) implicated as a genetic risk factor for radial hemimelia in Siamese cats

OBJECTIVES

The present study aimed to determine the inheritance pattern and genetic cause of congenital radial hemimelia (RH) in cats.

METHODS

Clinical and genetic analyses were conducted on a Siamese cat family (n = 18), including two siblings with RH. Radiographs were obtained for the affected kittens and echocardiograms of an affected kitten and sire. Whole genome sequencing was completed on the two cases and the parents. Genomic data were compared with the 99 Lives Cat Genome data set of 420 additional domestic cats with whole genome and whole exome sequencing data. Variants were considered as homozygous in the two cases of the siblings with RH and heterozygous in the parents. Candidate variants were genotyped by Sanger sequencing in the extended pedigree.

RESULTS

Radiographs of the female kitten revealed bilateral absence of the radii and bowing of the humeri, while the male kitten showed a dysplastic right radius. Echocardiography suggested the female kitten had restrictive cardiomyopathy with a positive left atrial-to-aortic root ratio (LA:Ao = 1.83 cm), whereas hypertrophic cardiomyopathy was more likely in the sire, showing diastolic dysfunction using tissue Doppler imaging (59.06 cm/s). Twenty-two DNA variants were unique and homozygous in the affected kittens and heterozygous in the parents. Seven variants clustered in one chromosomal region, including two frameshift variants in cardiomyopathy associated 5 (CMYA5) and five variants in junction mediating and regulatory protein, P53 cofactor (JMY ), including a missense and an in-frame deletion.

CONCLUSIONS AND RELEVANCE

The present study suggested an autosomal recessive mode of inheritance with variable expression for RH in the Siamese cat family. Candidate variants for the phenotype were identified, implicating their roles in bone development. These genes should be considered as potentially causal for other cats with RH. Siamese cat breeders should consider genetically testing their cats for these variants to prevent further dissemination of the suspected variants within the breed.

High ECM2 Expression Predicts Poor Clinical Outcome and Promotes the Proliferation, Migration, and Invasiveness of Glioma

OBJECTIVE

Glioma is the most prevalent and fatal intracranial malignant tumor. Extracellular matrix protein 2 (ECM2) has rarely been studied in gliomas. Therefore, we explored the role of ECM2 in lower-grade gliomas (LGGs).

METHODS

The RNA-seq and clinicopathology data were obtained from the TCGA database. The immunohistochemical (IHC) staining was used to verify the expression of ECM2. Functional enrichment analyses, immune-related analyses, drug sensitivity, and mutation profile analyses were further conducted. Cox regression and Kaplan-Meier curves were utilized for survival analyses, while four external datasets were used to validate the prognostic role of ECM2. Furthermore, qRT-PCR, CCK-8, wound healing, and transwell assays were performed to confirm the function of ECM2 in gliomas.

RESULTS

The study found a significant upregulation of ECM2 expression with increasing glioma grades and a significant association between ECM2 expression and tumor immune infiltration. Cox regression verified the prognostic role of ECM2 in LGG patients (HR = 1.656, 95%CI = 1.055-2.600, p = 0.028). High ECM2 expression was significantly associated with poor outcome (p < 0.001). Four external datasets validated its prognostic value. After the knockdown of ECM2, the functional experiments showed a significant decrease in proliferation, migration, and invasion in glioma cell lines.

CONCLUSION

The study suggested the potential of ECM2 as a novel immune-associated prognostic biomarker and therapeutic target for glioma patients.

High expression of six-transmembrane epithelial antigen of prostate 3 promotes the migration and invasion and predicts unfavorable prognosis in glioma

Recent studies have suggested that ferroptosis, a form of iron-dependent regulated cell death, might play essential roles in tumor initiation and progression. Six-transmembrane epithelial antigen of prostate 3 (STEAP3) is a ferrireductase involved in the regulation of intracellular iron homeostasis. However, the clinical significance and biological function of STEAP3 in human cancers remain poorly understood. Through a comprehensive bioinformatics analysis, we found that STEAP3 mRNA and protein expression were up-regulated in GBM, LUAD, and UCEC, and down-regulated in LIHC. Survival analysis indicated that STEAP3 had prognostic significance only in glioma. Multivariate Cox regression analysis revealed that high STEPA3 expression was correlated with poor prognosis. STEAP3 expression was significantly negatively correlated with promoter methylation level, and patients with lower STEAP3 methylation level had worse prognosis than those with higher STEAP3 methylation level. Single-cell functional state atlas showed that STEAP3 regulated epithelial-to-mesenchymal transition (EMT) in GBM. Furthermore, the results of wound healing and transwell invasion assays demonstrated that knocking down STEAP3 inhibited the migration and invasion of T98G and U251 cells. Functional enrichment analysis suggested that genes co-expressed with STEAP3 mainly participated in inflammation and immune-related pathways. Immunological analysis revealed that STEAP3 expression was significantly correlated with immune infiltration cells, including macrophages and neutrophils, especially the M2 macrophages. Individuals with low STEAP3 expression were more likely to respond to immunotherapy than those with high STEAP3 expression. These results suggest that STEAP3 promotes glioma progression and highlight its pivotal role in regulating immune microenvironment.

DNA Methylation and Histone Modification in Low-Grade Gliomas: Current Understanding and Potential Clinical Targets

Gliomas, the most common type of malignant primary brain tumor, were conventionally classified through WHO Grades I-IV (now 1-4), with low-grade gliomas being entities belonging to Grades 1 or 2. While the focus of the WHO Classification for Central Nervous System (CNS) tumors had historically been on histopathological attributes, the recently released fifth edition of the classification (WHO CNS5) characterizes brain tumors, including gliomas, using an integration of histological and molecular features, including their epigenetic changes such as histone methylation, DNA methylation, and histone acetylation, which are increasingly being used for the classification of low-grade gliomas. This review describes the current understanding of the role of DNA methylation, demethylation, and histone modification in pathogenesis, clinical behavior, and outcomes of brain tumors, in particular of low-grade gliomas. The review also highlights potential diagnostic and/or therapeutic targets in associated cellular biomolecules, structures, and processes. Targeting of MGMT promoter methylation, TET-hTDG-BER pathway, association of G-CIMP with key gene mutations, PARP inhibition, IDH and 2-HG-associated processes, TERT mutation and ARL9-associated pathways, DNA Methyltransferase (DNMT) inhibition, Histone Deacetylase (HDAC) inhibition, BET inhibition, CpG site DNA methylation signatures, along with others, present exciting avenues for translational research. This review also summarizes the current clinical trial landscape associated with the therapeutic utility of epigenetics in low-grade gliomas. Much of the evidence currently remains restricted to preclinical studies, warranting further investigation to demonstrate true clinical utility.

Interfering with CALCRL expression inhibits glioma proliferation, promotes apoptosis, and predicts prognosis in low-grade gliomas

Background

CALCRL is involved in a variety of key biological processes, including cell proliferation, apoptosis, angiogenesis, and inflammation. However, the role of CALCRL in glioma remains unknown. The purpose of this study was to investigate the effect of differential CALCRL expression on the malignant progression of glioma and its value in glioma prognosis.

Methods

Sequencing data from glioma and normal tissues were downloaded from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, and the downloaded data were statistically analyzed using bioinformatics tools and the corresponding R package. The expression of CALCRL in normal brain tissue and different grades of glioma tissue was detected by pathological and immunohistochemical staining of clinical glioma specimens. The expression of CALCRL in different glioma cell lines was detected by quantitative real-time polymerase chain reaction (qRT-PCR), and the U87 cell line with high expression was selected to construct the CALCRL knockdown model by transfection with short hairpin (shRNA). The cell proliferation ability was detected by Celigo assay and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, the ability of cell clone formation was detected by clone formation assay, and the level of apoptosis was detected by flow cytometry.

Results

The expression of CALCRL in glioma was significantly upregulated compared with that of normal tissue, especially in low-grade glioma (LGG) compared to glioblastoma, and the differential expression of CALCRL correlated significantly with the prognosis of LGG. Clinical pathology and immunohistochemistry showed that the expression of CALCRL was related to the pathological grade of glioma, and the highest expression was found in World Health Organization (WHO) grade Ⅲ glioma. The results of qRT-PCR showed that CALCRL expression was highest in the U87 cell line. After knockdown of CALCRL expression, the proliferation and clonogenic ability of U87 cells were significantly decreased, and the apoptosis rate was significantly increased.

Conclusions

CALCRL is highly expressed in LGG. Interfering with CALCRL expression inhibits glioma cell proliferation and promotes apoptosis, and thus has potential as a biomarker and therapeutic target for the prognosis of those with LGGs.

Establishment and validation of a novel prognostic model for lower-grade glioma based on senescence-related genes

Objective

Increasing studies have indicated that senescence was associated with tumorigenesis and progression. Lower-grade glioma (LGG) presented a less invasive nature, however, its treatment efficacy and prognosis prediction remained challenging due to the intrinsic heterogeneity. Therefore, we established a senescence-related signature and investigated its prognostic role in LGGs.

Methods

The gene expression data and clinicopathologic features were from The Cancer Genome Atlas (TCGA) database. The experimentally validated senescence genes (SnGs) from the CellAge database were obtained. Then LASSO regression has been performed to build a prognostic model. Cox regression and Kaplan-Meier survival curves were performed to investigate the prognostic value of the SnG-risk score. A nomogram model has been constructed for outcome prediction. Immunological analyses were further performed. Data from the Chinese Glioma Genome Atlas (CGGA), Repository of Molecular Brain Neoplasia Data (REMBRANDT), and GSE16011 were used for validation.

Results

The 6-SnG signature has been established. The results showed SnG-risk score could be considered as an independent predictor for LGG patients (HR=2.763, 95%CI=1.660-4.599, P<0.001). The high SnG-risk score indicated a worse outcome in LGG (P<0.001). Immune analysis showed a positive correlation between the SnG-risk score and immune infiltration level, and the expression of immune checkpoints. The CGGA datasets confirmed the prognostic role of the SnG-risk score. And Kaplan-Meier analyses in the additional datasets (CGGA, REMBRANDT, and GSE16011) validated the prognostic role of the SnG-signature (P<0.001 for all).

Conclusion

The SnG-related prognostic model could predict the survival of LGG accurately. This study proposed a novel indicator for predicting the prognosis of LGG and provided potential therapeutic targets.

Prognostic biomarker SGSM1 and its correlation with immune infiltration in gliomas

Objective

Glioma was the most common type of intracranial malignant tumor. Even after standard treatment, the recurrence and malignant progression of lower-grade gliomas (LGGs) were almost inevitable. The overall survival (OS) of patients with LGG varied widely, making it critical for prognostic prediction. Small G Protein Signaling Modulator 1 (SGSM1) has hardly been studied in gliomas. Therefore, we aimed to investigate the prognostic role of SGSM1 and its relationship with immune infiltration in LGGs.

Methods

We obtained RNA sequencing data from The Cancer Genome Atlas (TCGA) to analyze SGSM1 expression. Functional enrichment analyses, immune infiltration analyses, immune checkpoint analyses, and clinicopathology analyses were performed. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors. And nomogram model has been developed. Kaplan–Meier survival analysis and log-rank test were used to estimate the relationship between OS and SGSM1 expression. The survival analyses and Cox regression were validated in datasets from the Chinese Glioma Genome Atlas (CGGA).

Results

SGSM1 was significantly down-regulated in LGGs. Functional enrichment analyses revealed SGSM1 was correlated with immune response. Most immune cells and immune checkpoints were negatively correlated with SGSM1 expression. The Kaplan–Meier analyses showed that low SGSM1 expression was associated with a poor outcome in LGG and its subtypes. The Cox regression showed SGSM1 was an independent prognostic factor in patients with LGG (HR = 0.494, 95%CI = 0.311–0.784, P = 0.003).

Conclusion

SGSM1 was considered to be a new prognostic biomarker for patients with LGG. And our study provided a potential therapeutic target for LGG treatment.