A Prognostic Model for Prostate Cancer Patients Based on Two DNA Damage Response Mutation-Related Immune Genes.

IF 2.4 4区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL
Cancer Biotherapy and Radiopharmaceuticals Pub Date : 2024-05-01 Epub Date: 2023-08-22 DOI:10.1089/cbr.2023.0033
Jian Wang, Li Jiang, Zhenhua Shang, Zhaohua Ye, Dan Yuan, Xin Cui
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引用次数: 0

Abstract

Background: DNA damage response (DDR) mutation-related genes and composition of immune cells are core factors affecting the effectiveness of immune checkpoint inhibitor therapy. The aim of this study is to combine DDR with immune-related genes to screen the prognostic signature for prostate cancer (PCa). Methods: Gene expression profile and somatic mutation were downloaded from The Cancer Genome Atlas (TCGA). DDR-related genes were obtained from published study. After identification of prognostic-related DDR genes, samples were divided into mutation and nonmutation groups. Differentially expressed genes between these two groups were screened, followed by selection of immune-related DDR genes. Univariate and multivariate Cox analyses were performed to screen genes for constructing prognostic model. Nomogram model was also developed. The expression level of signature was detected by quantitative real-time PCR (qPCR). Results: Two genes (MYBBP1A and PCDHA9) were screened to construct the prognostic model, and it showed good risk prediction of PCa prognosis. Survival analysis showed that patients in high-risk group had worse overall survival than those in low-risk group. Cox analyses indicated that risk score could be used as an independent prognostic factor for PCa. qPCR results indicated that MYBBP1A was upregulated, whereas PCDHA9 was downregulated in PCa cell lines. Conclusions: A prognostic model based on DDR mutation-related genes for PCa was established, which serves as an effective tool for prognostic differentiation in patients with PCa.

基于两个 DNA 损伤反应突变相关免疫基因的前列腺癌患者预后模型
背景:DNA损伤应答(DDR)突变相关基因和免疫细胞的组成是影响免疫检查点抑制剂治疗效果的核心因素。本研究旨在结合 DDR 与免疫相关基因筛选前列腺癌(PCa)的预后特征。研究方法基因表达谱和体细胞突变从癌症基因组图谱(TCGA)中下载。DDR相关基因来自已发表的研究。确定预后相关的 DDR 基因后,将样本分为突变组和非突变组。筛选出两组之间的差异表达基因,然后再筛选出与免疫相关的 DDR 基因。对筛选出的基因进行单变量和多变量 Cox 分析,以构建预后模型。同时还建立了提名图模型。通过实时定量 PCR(qPCR)检测特征基因的表达水平。结果显示筛选出两个基因(MYBBP1A和PCDHA9)用于构建预后模型,结果显示这两个基因对PCa预后有很好的风险预测作用。生存分析表明,高风险组患者的总生存率低于低风险组。qPCR 结果表明,在 PCa 细胞系中,MYBBP1A 上调,而 PCDHA9 下调。结论基于DDR突变相关基因的PCa预后模型已经建立,该模型可作为PCa患者预后分化的有效工具。
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来源期刊
CiteScore
7.80
自引率
2.90%
发文量
87
审稿时长
3 months
期刊介绍: Cancer Biotherapy and Radiopharmaceuticals is the established peer-reviewed journal, with over 25 years of cutting-edge content on innovative therapeutic investigations to ultimately improve cancer management. It is the only journal with the specific focus of cancer biotherapy and is inclusive of monoclonal antibodies, cytokine therapy, cancer gene therapy, cell-based therapies, and other forms of immunotherapies. The Journal includes extensive reporting on advancements in radioimmunotherapy, and the use of radiopharmaceuticals and radiolabeled peptides for the development of new cancer treatments.
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