![]() Worse prognosis of recurrent LGGs is predominantly a resultant of their malignant transformation. In these recurrent cases, some have LGGs, while 17%–32% progress to high-grade gliomas (HGGs) ( 7– 10). About 52%–62% of patients have a recurrence within 5 years ( 4– 6). Reportedly, LGG patients have a 5-year survival rate of 70%–97% and a 10-year survival rate of 49%–76% ( 2, 3). Surgical resection remains the mainstay of treatment for LGGs, and adjuvant treatment with chemoradiotherapy is administered if needed. ![]() Occurring at all ages, LGGs have an incidence rate of 2.31/100,000 in the 0–14 years age group, 1.43/10,000 for 15–39 years of age, and 1.57/100,000 in the age group of 40 years and older. Low-grade gliomas (LGGs) make up about 7.6% of all brain tumors and 31.8% of gliomas. In conclusion, the prediction model based on these five key genes can better identify the high- and low-risk groups of LGG and lay a solid foundation for evaluating the risk of LGG recurrence and malignant progression. Finally, the value of potential therapeutic targets for the five key genes was analyzed, and findings demonstrated that KIF18A was the gene most likely to be a potential therapeutic target. The tumor mutational burden and tumor methylation burden in the high- and low-risk groups were also analyzed, which indicated higher gene mutation burden and lower DNA methylation level in the high-risk group, suggesting that with the accumulation of genomic mutations and epigenetic changes, tumor cells continued to evolve and led to the progression of LGG to HGG. Furthermore, the infiltration of immune cells in the high- and low-risk groups was analyzed, which indicated a stronger infiltration of immune cells in the high-risk group than that in the low-risk group, suggesting that an immune microenvironment more conducive to tumor growth emerged due to the interaction between tumor and immune cells. Gene Set Enrichment Analysis (GSEA) revealed that signaling pathway differences in the high- and low-risk groups were mainly seen in tumor immune regulation and DNA damage-related cell cycle checkpoints. LGG was divided into high- and low-risk groups using this prediction model. Univariate Cox regression analysis of data from The Cancer Genome Atlas (TCGA) yielded 86 prognostically relevant DEGs a prognostic prediction model based on five key genes (HOXA1, KIF18A, FAM133A, HGF, and MN1) was established using the least absolute shrinkage and selection operator (LASSO) regression dimensionality reduction and multivariate Cox regression analysis. In this study, 296 downregulated and 396 upregulated differentially expressed genes (DEGs) with high consensus were screened out. In this study, the transcriptome characteristics of four groups, namely, normal brain tissue and recurrent LGG (rLGG), normal brain tissue and secondary glioblastoma (sGBM), primary LGG (pLGG) and rLGG, and pLGG and sGBM, were compared using Chinese Glioma Genome Atlas (CGGA) and Genotype-Tissue Expression Project (GTEx) databases. It is of great importance to learn about the risk factors and underlying mechanisms of LGG recurrence and progression. 3Department of Neurosurgery, The First Affiliated Hospital, University of South China, Hengyang, Chinaĭespite a generally better prognosis than high-grade glioma (HGG), recurrence and malignant progression are the main causes for the poor prognosis and difficulties in the treatment of low-grade glioma (LGG). ![]()
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