Gene clusters based on OLIG2 and CD276 could distinguish molecular profiling in glioblastoma

mRNA markers for survival prediction in glioblastoma multiforme patients: a systematic review with bioinformatic analyses

BACKGROUND

Glioblastoma multiforme (GBM) is a type of fast-growing brain glioma associated with a very poor prognosis. This study aims to identify key genes whose expression is associated with the overall survival (OS) in patients with GBM.

METHODS

A systematic review was performed using PubMed, Scopus, Cochrane, and Web of Science up to Journey 2024. Two researchers independently extracted the data and assessed the study quality according to the New Castle Ottawa scale (NOS). The genes whose expression was found to be associated with survival were identified and considered in a subsequent bioinformatic study. The products of these genes were also analyzed considering protein-protein interaction (PPI) relationship analysis using STRING. Additionally, the most important genes associated with GBM patients' survival were also identified using the Cytoscape 3.9.0 software. For final validation, GEPIA and CGGA (mRNAseq_325 and mRNAseq_693) databases were used to conduct OS analyses. Gene set enrichment analysis was performed with GO Biological Process 2023.

RESULTS

From an initial search of 4104 articles, 255 studies were included from 24 countries. Studies described 613 unique genes whose mRNAs were significantly associated with OS in GBM patients, of which 107 were described in 2 or more studies. Based on the NOS, 131 studies were of high quality, while 124 were considered as low-quality studies. According to the PPI network, 31 key target genes were identified. Pathway analysis revealed five hub genes (IL6, NOTCH1, TGFB1, EGFR, and KDR). However, in the validation study, only, the FN1 gene was significant in three cohorts.

CONCLUSION

We successfully identified the most important 31 genes whose products may be considered as potential prognosis biomarkers as well as candidate target genes for innovative therapy of GBM tumors.

MiRNAs from the Dlk1-Dio3 locus and miR-224/452 cluster contribute to glioblastoma tumor heterogeneity

Glioblastoma is one of the most common and aggressive brain tumors and has seen few improvements in patient outcomes. Inter-tumor heterogeneity between tumors of different patients as well as intra-tumor heterogeneity of cells within the same tumor challenge the development of effective drugs. MiRNAs play an essential role throughout the developing brain and regulate many key genes involved in oncogenesis, yet their role in driving many of the processes underlying tumor heterogeneity remains unclear. In this study, we highlight miRNAs from the Dlk1-Dio3 and miR-224/452 clusters which may be expressed cell autonomously and have expression that is associated with cell state genes in glioblastoma, most prominently in neural progenitor-like and mesenchymal-like states respectively. These findings implicate these miRNA clusters as potential regulators of glioblastoma intra-tumoral heterogeneity and may serve as valuable biomarkers for cell state identification.

Cell Cycle-Related FAM64A Could be Activated by TGF-β Signaling to Promote Glioma Progression

Gliomas are aggressive brain tumors characterized by uncontrolled cell proliferation. FAM64A, a cell cycle-related gene, has been found to promote cell proliferation in various tumors, including gliomas. However, the regulatory mechanism and clinical significance of FAM64A in gliomas remain unclear. In this study, we investigated FAM64A expression in gliomas with different grades and constructed FAM64A silenced cell lines to study its functions. Our results demonstrated that FAM64A was highly expressed in glioblastoma (P < 0.001) and associated with a poor prognosis (P < 0.001). Expression profiles at the single-cell resolution indicated FAM64A could play a role in a cell-cycle-dependent way to promote glioma cell proliferation. We further observed that FAM64A silencing in glioma cells resulted in disrupted proliferation and migration ability, and increased cell accumulation in the G2/M phase (P = 0.034). Additionally, TGF-β signaling upregulates FAM64A expression, and SMAD4 and FAM64A co-localize in high-grade glioma tissues. We found FAM64A knockdown inhibited TGF-β-induced epithelial-mesenchymal transition in glioma. Our findings suggest that FAM64A could serve as a diagnostic and therapeutic target in gliomas.