Differential Gene Expression and Co-expression Network Analysis Reveals CKAP۲L and NCAPH as Key Regulators in Low-Grade Gliomas

Low-grade gliomas (LGG) are a type of primary brain tumor that is typically considered as grade I and II based on WHO ۲۰۲۱. They are mostly derived from astrocytes or oligodendrocytes. The main characteristic of these tumors is a mutation in the isocitrate dehydrogenase (IDH) enzyme. These tumors grow slowly and have a better prognosis than high-grade gliomas. However, clinical management is complicated by its infiltrative nature and possible malignant transformation. WHO grade I tumors are benign and commonly occur in children, while WHO grade II gliomas are often incurable and mainly transform into high-grade gliomas. Recent advances in high-throughput RNA sequencing (RNA-seq) and bioinformatics have opened up new ways for prognosis biomarkers and therapeutic targets for low-grade glioma. Material and methods: To investigate the potential biomarkers of Low-grade gliomas, RNA-seq data from ۵۳۴ LGG samples were downloaded from The Cancer Genome Atlas (TCGA) portal, and RNA-seq data from ۴۶۴ normal brain samples were obtained from the Genotype-Tissue [removed]GTEx) portal. The DESeq۲ package was used to find genes expressed differently between LGG and normal brain tissue using thresholds of |log۲FC| > ۰.۵۸ and p-value < ۰.۰۵. Then, Weighted Gene Co-expression Network Analysis (WGCNA) was utilized for co-expression network analysis where network type was "signed," and soft thresholding power (β) was ۹, based on the scale-free topology of the network. Preservation analysis was carried out to identify modules without preservation in LGG. The CytoHubba plugin in Cytoscape was utilized to identify hub genes within the network. Result: Compared to normal brain tissue, ۳,۵۴۱ genes were upregulated and ۴,۲۰۰ downregulated in LGG based on differential expression analysis. Co-expression network analysis revealed that the "tan" module was non-preserved in samples of LGG, indicating significant rewiring of gene interactions in these tumors. Two major hub genes, including CKAP۲L and NCAPH, were identified from the co-expression network for LGG, suggesting their possible roles in the development and progression of this type of cancer. Conclusion: This study highlights an extensive molecular difference between LGG and normal brain tissue, identifying over ۷,۷۰۰ differentially expressed genes that may be responsible for tumor development and progression. The non-preserved module in LGGs denotes particular network changes that may play a critical role in the transition from normal tissue to tumor. In addition, discovering the hub genes of this module can serve as potential biomarkers or therapeutic targets. These findings form a foundation for future research to develop targeted therapies and improve prognostic models for patients with LGG. Moreover, the incorporation of expression profiling with network analysis promotes a deeper understanding of low-grade glioma, which will lead to more personalized therapies that are more robust and effective.

کلیدواژه ها:

Low-grade glioma (LGG) ، Differential gene [removed]DEG) ، Co-expression network analysis ، Weighted Gene Co-expression Network Analysis (WGCNA)