TGF-β signaling-related signature for predicting prognosis and therapeutic response in lower-grade glioma

TGF-β信号通路相关特征可用于预测低级别胶质瘤的预后和治疗反应

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Abstract

BACKGROUND: Low-grade glioma (LGG) is a tumor that includes World Health Organization (WHO) grade II and III glioma, the treatment of which consistently results in relapse and drug resistance. Transforming growth factor-beta (TGF-β) is a multifunctional cytokine that regulates various cellular processes, which is found to be abnormal in tumors and promotes glioma development and progression. In this study, we aimed to systematically evaluate the importance of the genes associated with TGF-β in LGG and discover the role of these genes in the prognosis and treatment response of LGG. METHODS: We used the "Bioconductor Limma" and "consensusClusterplus" R packages to screen differential and prognostic TGF-β-related genes. The R package "GSVA" was used to estimate the infiltration of immune cells and metabolism signature. The drug sensitivity for each TGF-β subtype was assessed by the R package "pRRophetic". The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was used to assess the copy number variation (CNV). The onco-print tool of the "complexheatmap package" was employed to visualize the somatic mutation and copy number alteration (CNA) among TGF clusters. RESULTS: We reported three subtypes (A, B, and C) of LGG according to the classification of TGF-β-related genes, where subtype A showed the best prognosis. Subtype B was highly enriched in immune cells. Somatic variations were observed to be diverse in all of the three TGF-β subtypes. Furthermore, another three genes (SHA, AC062021.1, and SNCG) related to TGF-β were identified, which can be a superior predictor of prognosis with a risk score. CONCLUSIONS: LGG can be divided into three subtypes based on TGF-β signaling-related genes with distinct immune infiltration, metabolism, somatic variations, and prognosis.

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