Glioma was characterized by its severe cellular heterogeneity during cell differentiation. Based on scRNA-seq and high throughput sequencing data, this research revealed the potential connections between cell differentiation trajectory and immune landscape in glioma. Glioma differentiation-related genes (GDRGs) were extracted from cell differentiation trajectories to establish a three-subtype molecular classification. Enrichment analysis indicated that GDRGs were involved in cell differentiation, intercellular adhesion, cytotoxicity, and cell cycle. ESTIMATE and CIBERSORT analysis showed that GDRGs and macrophages-related immune checkpoints (CD163, CD206, LILRB4, LILRB2, LILRB1, CD47, and SIRPα) promoted M2-dominated immune landscape in glioma. Finally, a novel prognostic risk score (RS) signature and nomogram based on 8 GDRGs (SOX4, MEX3A, EGFR, NES, ENC1, NEFL, NNAT, and TMSB15A) were established to predict the patient's 3-years and 5-years OS In conclusion, the molecular subtypes defined by cell differentiation trajectories predicted the M2-dominated immune landscape. GDRGs named SOX4, MEX3A, EGFR, NES, ENC1, NEFL, NNAT, and TMSB15A could be regarded as novel prognostic signatures and potential targets for immunotherapy.

The regulatory role of autophagy-related genes (ARGs) on the differentiation trajectory and immune landscape of glioblastoma remained obscure. This research identified 11 ARGs differentially expressed in glioblastomas; LASSO and Binomial regression analysis identified five core ARGs (EGFR, HSPB8, CTSB, DNAJB1, and MYC) that affect the prognosis of gliomas. Enrichment analysis suggested that ARGs can activate malignant tumor-related signal pathways, including gliomas, while biological processes regulate autophagy and apoptosis. Subsequently, based on scRNA-seq data from CGGA, this study identified that macrophage M2 dominated the immune landscapes in the glioblastoma differentiation trajectory. After consistent clustering established the ARGs-based molecular subtypes, ESTIMATE and CIBERSORT results suggested that ARGs were associated with macrophage M2 polarization and affected the prognosis of glioma. Finally, ARGs-based nomograms were established to predict the incidence and prognosis of glioma. AUC and DCA prove the validity of nomograms. In conclusion, EGFR, HSPB8, CTSB, DNAJB1, and MYC as ARGs were associated with the M2-dominated immune landscape in glioblastomas and were influential in predicting the incidence and prognosis of glioma.

Purpose MRC2 aberrantly expressed in malignant tumors had been reported in multiple researches, but not in glioma. This study mainly to explore the effect of DNA methylation on the MRC2 expression, and the mechanism of MRC2 regulating the biological function of glioma cells. Methods In this study, the differentially expressed gene MRC2 was found after large-scale screening of glioma whole genome sequencing data. Logistic regression analysis was used to scale the correlation between MRC2 expression and clinical characteristics; immunohistochemistry and Western blot verified the expression of MRC2 in normal brain and glioma. The correlation between DNA methylation and MRC2 expression was examined by Pearson correlation coefficient (r). ROC, Cox and Kaplan-Meier approach for quantifying MRC2 expression on disease free survival (DFS) and overall survival (OS). Gene enrichment analysis (GSEA) predicted glioma related signal pathways that may be activated by high expressed MRC2. Expression and methylation data were obtained from TCGA, CGGA and GTEx, Results MRC2 was highly expressed in glioma, and the expression was not related to gender, age, radiotherapy, but related to recurrence, tumor grade, chemotherapy, IDH_mutation, and 1p19q_codeletion. The up-regulation of MRC2 expression was related to the hypomethylation of 9 CpG sites located in MRC2 promoter and intron 1 region, both together led to a poor prognosis. GSEA predicted six pathways could activated by highly expressed MRC2, these pathways mainly regulated the proliferation and invasion in glioma. Co-expressed genes of MRC2 could be found in each pathway, and they were functionally consistent with MRC2 in influencing prognosis. Conclusion It was not only DNA hypomethylation that affects the expression of MRC2, hypomethylation of CpG site in promoter and first intron region had the similar regulatory function. Up-regulated MRC2 could activated six signal pathways mainly regulated the proliferation and invasion, and led to poor prognosis in glioma. Thereby, MRC2 could be seen as a novel molecular target for glioma.

Purpose This study mainly to explore the effect of DNA methylation on the MRC2 expression, and the mechanism of MRC2 regulating the biological function of glioma cells. Methods MRC2 was found to be differentially expressed in glioma after large-scale screening of expression data. Logistic regression and Pearson correlation coefficient (r) scaled the correlation between MRC2 expression and clinical characteristics; immunohistochemistry and Western blot verified the expression of MRC2. ROC, Cox and Kaplan-Meier approach for quantifying MRC2 expression on survival. GSEA predicted signal pathways that may be activated by high expressed MRC2. Results High expression of MRC2 accompanied by promoter and intronic hypomethylation in glioma was related to survival rate, recurrence, tumor grade, chemotherapy, IDH_mutation, 1p19q_codeletion. Six pathways activated by highly expressed MRC2 were mainly regulated the proliferation and invasion in glioma. Co-expressed genes of MRC2 could be found in each pathway, and they were functionally consistent with MRC2. Conclusion The up-regulated MRC2 expression was related to promoter and intronic hypomethylation in glioma. Signal pathways activated by MRC2 mainly regulated the proliferation and invasion in glioma, and led to poor prognosis. MRC2 could be seen as a novel molecular target for glioma.