Construction of a competitive endogenous RNA network and analysis of potential regulatory axis targets in glioblastoma

Ropivacaine represses the proliferation, invasion, and migration of glioblastoma via modulating the microRNA-21-5p/KAT8 regulatory NSL complex subunit 2 axis

Ropivacaine (Rop) is available to suppress the growth of glioblastoma (GBM), while its mechanism has not been completely elaborated. In this study, we explore the latent mechanism of Rop repressing GBM's growth via mediating the microRNA (miR)-21-5p/KAT8 regulatory NSL complex subunit 2 (KANSL2) axis. MiR-21-5p was declined in GBM, while KANSL2 was elevated. Clinical association studies manifested miR-21-5p was distinctly linked to the tumor size and grade of GBM. Rop constrained GBM cell proliferation, invasion, and migration but boosted apoptosis. Elevated miR-21-5p strengthened Rop's action, while augmented KANSL2 weakened Rop's role. Furthermore, the impact of silencing miR-21-5p on GBM was turned around via declining KANSL2 in Rop-treated GBM cells. KANSL2 was the target gene of miR-21-5p. In short, Rop exerted an anti-tumor impact on GBM via mediating the miR-21-5p/KANSL2 axis, which offered novel viewpoints for the later adoption of Rop as GBM drugs.

Integrative analysis of DNA methylation and gene expression profiles to identify biomarkers of glioblastoma

Glioblastoma multiforme (GBM) is the most common, most invasive, and malignant type of primary brain tumor with poor prognosis and poor survival rate. Using GSE22891 the expression and methylation status of same GBM patients was evaluated to identify key epigenetic genes in GBM. Using |log2FC| > 1 and FDR 〈 0.05 as the threshold, DEGs including 4910 downregulated and 2478 upregulated were screened and by |log2FC| 〉 0.2 and p-value < 0.05, 3223 DMCs were detected. By merging the results of DEGs and DMCs, 643 genes were selected for network analysis by WGCNA, and based on expression values three modules and by methylation values, one module was selected. Using STRING and Cytoscape databases, PPI network of genes of all modules were constructed separately. According to the PPI network, core genes were picked out. The expression status of core genes was evaluated using GSE77043, GSE42656, GSE30563, GSE22891, GSE15824, and GSE122498, and 50 genes were validated. The methylation status of 50 genes was explored using GSE50923, GSE22891, and GSE36245, and finally, 12 hub genes including ARHGEF7, RAB11FIP4, PPP1R16B, OLFM1, CLDN10, BCAT1, C1QB, C1QC, IFI16, NUP37, PARP9, and PCLAF were selected. Using GEPIA database, the expression and by cBioportal the survival plot and also scatterplot of methylation versus expression of 12 hub genes were extracted based on TCGA. To determine the diagnostic values of the hub genes, the receiver operating characteristic (ROC) curve and the area under the curve (AUC) were extracted based on GSE22891 and GSE122498. Finally, we evaluated the expression level of the genes in tissue of 83 GBM patients and also non-tumoral adjacent (as control) tissues.

The regulatory pattern of target gene expression by aberrant enhancer methylation in glioblastoma

Background

Glioblastoma multiforme (GBM) is the most common and aggressive primary malignant brain tumor with grim prognosis. Aberrant DNA methylation is an epigenetic mechanism that promotes GBM carcinogenesis, while the function of DNA methylation at enhancer regions in GBM remains poorly described.

Results

We integrated multi-omics data to identify differential methylation enhancer region (DMER)-genes and revealed global enhancer hypomethylation in GBM. In addition, a DMER-mediated target genes regulatory network and functional enrichment analysis of target genes that might be regulated by hypomethylation enhancer regions showed that aberrant enhancer regions could contribute to tumorigenesis and progression in GBM. Further, we identified 22 modules in which lncRNAs and mRNAs synergistically competed with each other. Finally, through the construction of drug-target association networks, our study identified potential small-molecule drugs for GBM treatment.

Conclusions

Our study provides novel insights for understanding the regulation of aberrant enhancer region methylation and developing methylation-based biomarkers for the diagnosis and treatment of GBM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04345-8.

Complement C1s and C4d as Prognostic Biomarkers in Renal Cancer: Emergence of Noncanonical Functions of C1s

The complement system plays a complex role in cancer. In clear cell renal cell carcinoma (ccRCC), local production of complement proteins drives tumor progression, but the mechanisms by which they do this are poorly understood. We found that complement activation, as reflected by high plasma C4d or as C4d deposits at the tumor site, was associated with poor prognosis in two cohorts of patients with ccRCC. High expression of the C4-activating enzyme C1s by tumor cells was associated with poor prognosis in three cohorts. Multivariate Cox analysis revealed that the prognostic value of C1s was independent from complement deposits, suggesting the possibility of complement cascade-unrelated, protumoral functions for C1s. Silencing of C1s in cancer cell lines resulted in decreased proliferation and viability of the cells and in increased activation of T cells in in vitro cocultures. Tumors expressing high levels of C1s showed high infiltration of macrophages and T cells. Modification of the tumor cell phenotype and T-cell activation were independent of extracellular C1s levels, suggesting that C1s was acting in an intracellular, noncanonical manner. In conclusion, our data point to C1s playing a dual role in promoting ccRCC progression by triggering complement activation and by modulating the tumor cell phenotype and tumor microenvironment in a complement cascade-independent, noncanonical manner. Overexpression of C1s by tumor cells could be a new escape mechanism to promote tumor progression.See related Spotlight by Magrini and Garlanda, p. 855. See article by Daugan et al., p. 909 (40).