Construction and Validation of Prognostic Regulation Network Based on RNA-Binding Protein Genes in Lung Squamous Cell Carcinoma

生物 癌变 肺癌 基因 核糖核酸 生存分析 RNA结合蛋白 计算生物学 肿瘤科 癌症研究 生物信息学 遗传学 内科学 医学
作者
Shilong Zhao,Qiuhong Liu,Junlu Li,Chunling Hu,Fengan Cao,Wentao Ma,Jing Gao
出处
期刊:DNA and Cell Biology [Mary Ann Liebert, Inc.]
卷期号:40 (12): 1563-1583 被引量:9
标识
DOI:10.1089/dna.2021.0145
摘要

Lung squamous cell carcinoma (LUSC) is a common histologic subtype of non-small cell lung cancer with a poor prognosis. RNA-binding proteins (RBPs) are key modulators in the posttranscriptional regulation and RBP alterations are commonly found in various cancer types. However, its roles in predicting the tumorigenesis and prognosis have not been identified in LUSC. To identify the roles of RBPs in the tumorigenesis and prognosis of LUSC, the RNA sequencing data of patients with LUSC were retrieved from The Cancer Genome Atlas (TCGA) databases. The differential expressed genes (DEGs) were evaluated and identified. The intersection of manually curated RBPs and tumorigenesis-related DEGs was filtered to the univariate Cox regression analysis. The intersection genes with prognostic value were defined as prognostic RNA-binding protein genes (PRBPGs). Based on them, the predicted model was constructed. Its accuracy was tested by the area under the curve (AUC) of the receiver operator characteristic curve and the risk score. In addition, to explore the key regulatory network, the relationship among PRBPGs, target RNA, and absolute quantification of 50 hallmarks of cancer was also identified by Pearson correlation analysis. A total of 311 genes were filtered as the intersection of 1542 manually curated RBPs and tumorigenesis-related DEGs and the results revealed 17 PRBPGs. Based on them, we constructed the predict model with a relatively high accuracy (AUC: 0.739). The Kaplan-Meier survival curve showed the significant prognostic value of risk score (p < 0.001). Moreover, we uncovered the regulatory networks of PHF5A-TOMM22-oxidative phosphorylation, TLR3-CTSO inflammation-related pathway, SECISBP2L-targeted RNA (ADGRF5, TGFBR2, CD302, AC096921.2, AHCYL2, RPS6KA2, SLC34A2, and SFTPB) angiogenesis, and SECISBP2L-AKAP13 signaling (DNA repair, MTORC1 signaling, and MYC targets). The regulation mechanisms and cellular location of key PRBPGs were validated by assay for targeting accessible chromatin with high-throughput sequencing and single-cell RNA sequencing. Our study identifies PRBPGs as reliable indexes in predicting the tumorigenesis and prognosis of patients with LUSC and provides a well-applied model for predicting the overall survival for patients with LUSC. Besides, we also identified the regulatory network among PRBPGs, target RNA, and cancer gene sets in mediating the LUSC tumorigenesis.
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