Identification of Implications of Angiogenesis and m6A Modification on Immunosuppression and Therapeutic Sensitivity in Low-Grade Glioma by Network Computational Analysis of Subtypes and Signatures

The role of N6-methyladenosine modification in tumor angiogenesis

Tumor angiogenesis is a characteristics of malignant cancer progression that facilitates cancer cell growth, diffusion and metastasis, and has an indispensable role in cancer development. N6-methyladenosine (m6A) is among the most prevalent internal modifications in eukaryotic RNAs, and has considerable influence on RNA metabolism, including its transcription, splicing, localization, translation, recognition, and degradation. The m6A modification is generated by m6A methyltransferases ("writers"), removed by m6A demethylases ("erasers"), and recognized by m6A-binding proteins ("readers"). There is accumulating evidence that abnormal m6A modification is involved in the pathogenesis of multiple diseases, including cancers, and promotes cancer occurrence, development, and progression through its considerable impact on oncoprotein expression. Furthermore, increasing studies have demonstrated that m6A modification can influence angiogenesis in cancers through multiple pathways to regulate malignant processes. In this review, we elaborate the role of m6A modification in tumor angiogenesis-related molecules and pathways in detail, providing insights into the interactions between m6A and tumor angiogenesis. Moreover, we describe how targeting m6A modification in combination with anti-angiogenesis drugs is expected to be a promising anti-tumor treatment strategy, with potential value for addressing the challenge of drug resistance.

Characterization of growth arrest-specific transcript 5 and growth arrest-specific transcript 5-related m6A gene signature in glioma: An observational study

Glioma remains a significant clinical challenge and poses a dismal patient prognosis. This study focused on the long noncoding ribonucleic acid growth arrest-specific transcript 5 (GAS5) and explored the role of GAS5 and GAS5-related m6A genes in glioma. We explored the mechanisms of GAS5 expression in glioma using bioinformatic analysis based on glioma data from the Cancer Genome Atlas, GSE1142, and Chinese Glioma Genome Atlas databases. Kaplan-Meier curve analysis, nomogram construction, immune cell infiltration, drug sensitivity, mutations, and pathway analyses were performed to determine the GAS5 mechanism in glioma. Spearman correlation and weighted gene co-expression analyses were used to identify the GAS5-related m6A gene. Furthermore, we explored the correlation between GAS5, GAS5-related m6A gene, and clinical traits using analysis of variance. The Kaplan-Meier curve analysis suggested that patients with high expressions of GAS5 had better survival. The nomogram constructed indicated that GAS5 was an independent prognostic factor. Furthermore, GAS5 significantly correlated with plasma cells. GAS5 expression was significantly associated with biological processes, including oxidative phosphorylation, proteasome, and ribosome mitotic spindle. GAS5 expression was associated with sensitivity to erlotinib and gemcitabine. Differentially expressed GAS5 was significant in histology (P = 2.8e-09), grade (P = 3.7e-05), isocitrate dehydrogenase (IDH) mutation (P = 3.4e-17), 1p/19q co-deletion (Codel) status (P = 1.7e-08), and IDH mutation status and 1p/19q Codel status (P = 2.9e-18). Heterogeneous nuclear ribonucleoproteins C1/C2 (HNRNPC) gene was significant in IDH mutation (P = .008) and IDH mutation status and 1p/19q Codel status (P = 2.1e-05). GAS5 and HNRNPC expressions reflected the malignant grade of glioma and are associated with prognosis. The abnormal expression of GAS5 could be an important biomarker for guiding erlotinib and gemcitabine use in glioma treatment. GAS5 and heterogeneous nuclear ribonucleoproteins C1/C2 are potential diagnostic and prognostic markers for glioma.

TGF-β Score based on Silico Analysis can Robustly Predict Prognosis and Immunological Characteristics in Lower-grade Glioma: The Evidence from Multicenter Studies

INTRODUCTION

Nowadays, mounting evidence shows that variations in TGF-β signaling pathway-related components influence tumor development. Current research has patents describing the use of anti-TGF-β antibodies and checkpoint inhibitors for the treatment of proliferative diseases. Importantly, TGF-β signaling pathway is significant for lower-grade glioma (LGG) to evade host immunity. Loss of particular tumor antigens and shutdown of professional antigenpresenting cell activity may render the anti-tumor response ineffective in LGG patients. However, the prognostic significance of TGF-β related genes in LGG is still unknown.

METHODS

We collected RNA-seq data from the GTEx database (normal cortical tissues), the Cancer Genome Atlas database (TCGA-LGG), and the Chinese Glioma Genome Atlas database (CGGA-693 and CGGA-325) for conducting our investigation.

RESULTS

In addition, previous publications were explored for the 223 regulators of the TGF-β signaling pathway, and 30 regulators with abnormal expression in TCGA and GTEx database were identified. In order to identify hub prognostic regulators, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis were used to screen from differentially expressed genes (DEGs). On the basis of 11 genes from LASSO-Cox regression analysis (NEDD8, CHRD, TGFBR1, TP53, BMP2, LRRC32, THBS2, ID1, NOG, TNF, and SERPINE1), TGF-β score was calculated. Multiple statistical approaches verified the predictive value of the TGF-β score for the training cohort and two external validation cohorts. Considering the importance of the TGF-β signaling pathway in immune regulation, we evaluated the prediction of the TGF-β score for immunological characteristics and the possible application of the immunotherapeutic response using six algorithms (TIMER, CIBERSORT, QUANTISEQ, MCP-counter, XCELL and EPIC) and three immunotherapy cohorts (GSE78820, Imvigor-210 and PRJEB23709). Notably, we compared our risk signature with the signature in ten publications in the meta-cohort (TCGA-LGG, CGGA-693 and CGGA-325), and the TGF-β score had the best predictive efficiency (C-index =0.812).

CONCLUSION

In conclusion, our findings suggest that TGF-β signaling pathway-related signatures are prognostic biomarkers in LGG and provide a novel tool for tumor microenvironment (TME) assessment.

The Comprehensive Analysis of m6A-Associated Anoikis Genes in Low-Grade Gliomas

The relationship between N6-methyladenosine (m6A) regulators and anoikis and their effects on low-grade glioma (LGG) is not clear yet. The TCGA-LGG cohort, mRNAseq 325 dataset, and GSE16011 validation set were separately obtained via the Cancer Genome Atlas (TCGA), Chinese Glioma Genome Altas (CGGA), and Gene Expression Omnibus (GEO) databases. In total, 27 m6A-related genes (m6A-RGs) and 508 anoikis-related genes (ANRGs) were extracted from published articles individually. First, differentially expressed genes (DEGs) between LGG and normal samples were sifted out by differential expression analysis. DEGs were respectively intersected with m6A-RGs and ANRGs to acquire differentially expressed m6A-RGs (DE-m6A-RGs) and differentially expressed ANRGs (DE-ANRGs). A correlation analysis of DE-m6A-RGs and DE-ANRGs was performed to obtain DE-m6A-ANRGs. Next, univariate Cox and least absolute shrinkage and selection operator (LASSO) were performed on DE-m6A-ANRGs to sift out risk model genes, and a risk score was gained according to them. Then, gene set enrichment analysis (GSEA) was implemented based on risk model genes. After that, we constructed an independent prognostic model and performed immune infiltration analysis and drug sensitivity analysis. Finally, an mRNA-miRNA-lncRNA regulatory network was constructed. There were 6901 DEGs between LGG and normal samples. Six DE-m6A-RGs and 214 DE-ANRGs were gained through intersecting DEGs with m6A-RGs and ANRGs, respectively. A total of 149 DE-m6A-ANRGs were derived after correlation analysis. Four genes, namely ANXA5, KIF18A, BRCA1, and HOXA10, composed the risk model, and they were involved in apoptosis, fatty acid metabolism, and glycolysis. The age and risk scores were finally sifted out to construct an independent prognostic model. Activated CD4 T cells, gamma delta T cells, and natural killer T cells had the largest positive correlations with risk model genes, while activated B cells were significantly negatively correlated with KIF18A and BRCA1. AT.9283, EXEL.2280, Gilteritinib, and Pracinostat had the largest correlation (absolute value) with a risk score. Four risk model genes (mRNAs), 12 miRNAs, and 21 lncRNAs formed an mRNA-miRNA-lncRNA network, containing HOXA10-hsa-miR-129-5p-LINC00689 and KIF18A-hsa-miR-221-3p-DANCR. Through bioinformatics, we constructed a prognostic model of m6A-associated anoikis genes in LGG, providing new ideas for research related to the prognosis and treatment of LGG.

YTHDF1 Attenuates TBI-Induced Brain-Gut Axis Dysfunction in Mice

The brain-gut axis (BGA) is a significant bidirectional communication pathway between the brain and gut. Traumatic brain injury (TBI) induced neurotoxicity and neuroinflammation can affect gut functions through BGA. N⁶-methyladenosine (m⁶A), as the most popular posttranscriptional modification of eukaryotic mRNA, has recently been identified as playing important roles in both the brain and gut. However, whether m⁶A RNA methylation modification is involved in TBI-induced BGA dysfunction is not clear. Here, we showed that YTHDF1 knockout reduced histopathological lesions and decreased the levels of apoptosis, inflammation, and oedema proteins in brain and gut tissues in mice after TBI. We also found that YTHDF1 knockout improved fungal mycobiome abundance and probiotic (particularly Akkermansia) colonization in mice at 3 days post-CCI. Then, we identified the differentially expressed genes (DEGs) in the cortex between YTHDF1-knockout and WT mice. These genes were primarily enriched in the regulation of neurotransmitter-related neuronal signalling pathways, inflammatory signalling pathways, and apoptotic signalling pathways. This study reveals that the ITGA6-mediated cell adhesion molecule signalling pathway may be the key feature of m⁶A regulation in TBI-induced BGA dysfunction. Our results suggest that YTHDF1 knockout could attenuate TBI-induced BGA dysfunction.

The Potential Role of m6A in the Regulation of TBI-Induced BGA Dysfunction

The brain–gut axis (BGA) is an important bidirectional communication pathway for the development, progress and interaction of many diseases between the brain and gut, but the mechanisms remain unclear, especially the post-transcriptional regulation of BGA after traumatic brain injury (TBI). RNA methylation is one of the most important modifications in post-transcriptional regulation. N6-methyladenosine (m⁶A), as the most abundant post-transcriptional modification of mRNA in eukaryotes, has recently been identified and characterized in both the brain and gut. The purpose of this review is to describe the pathophysiological changes in BGA after TBI, and then investigate the post-transcriptional bidirectional regulation mechanisms of TBI-induced BGA dysfunction. Here, we mainly focus on the characteristics of m⁶A RNA methylation in the post-TBI BGA, highlight the possible regulatory mechanisms of m⁶A modification in TBI-induced BGA dysfunction, and finally discuss the outcome of considering m⁶A as a therapeutic target to improve the recovery of the brain and gut dysfunction caused by TBI.