Gene Signature Associated With Bromodomain Genes Predicts the Prognosis of Kidney Renal Clear Cell Carcinoma

被引:12
作者
Lu, Junwan [1 ]
Qian, Changrui [2 ]
Ji, Yongan [1 ]
Bao, Qiyu [1 ]
Lu, Bin [1 ]
机构
[1] Wenzhou Med Univ, Key Lab Med Genet Zhejiang Prov, Prot Qual Control & Dis Lab, Key Lab Lab Med,Minist Educ China,Sch Lab Med & L, Wenzhou, Peoples R China
[2] Wenzhou Cent Hosp, Wenzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
KIRC; bromodomain genes; prognosis signatures; overall survival; TCGA; EXPRESSION ANALYSIS; SWI/SNF COMPLEX; YEAST; P300; ACETYLATION; HOMEOSTASIS; REGULATOR; PROTEIN; CANCER; DOMAIN;
D O I
10.3389/fgene.2021.643935
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Bromodomain (BRD) proteins exhibit a variety of activities, such as histone modification, transcription factor recruitment, chromatin remodeling, and mediator or enhancer complex assembly, that affect transcription initiation and elongation. These proteins also participate in epigenetic regulation. Although specific epigenetic regulation plays an important role in the occurrence and development of cancer, the characteristics of the BRD family in renal clear cell carcinoma (KIRC) have not been determined. In this study, we investigated the expression of BRD family genes in KIRC at the transcriptome level and examined the relationship of the expression of these genes with patient overall survival. mRNA levels of tumor tissues and adjacent tissues were extracted from The Cancer Genome Atlas (TCGA) database. Seven BRD genes (KAT2A, KAT2B, SP140, BRD9, BRPF3, SMARCA2, and EP300) were searched by using LASSO Cox regression and the model with prognostic risk integration. The patients were divided into two groups: high risk and low risk. The combined analysis of these seven BRD genes showed a significant association with the high-risk groups and lower overall survival (OS). This analysis demonstrated that total survival could be predicted well in the low-risk group according to the time-dependent receiver operating characteristic (ROC) curve. The prognosis was determined to be consistent with that obtained using an independent dataset from TCGA. The relevant biological functions were identified using Gene Set Enrichment Analysis (GSEA). In summary, this study provides an optimized survival prediction model and promising data resources for further research investigating the role of the expression of BRD genes in KIRC.
引用
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页数:12
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