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

作者全名："Wang, Jian; Jiang, Li; Shang, Zhenhua; Ye, Zhaohua; Yuan, Dan; Cui, Xin"

作者地址："[Wang, Jian] Sun Yat Sen Univ, Peoples Hosp Foshan 1, Affiliated Hosp, Dept Urol Surg, Foshan, Peoples R China; [Jiang, Li] Chongqing Med Univ, Affiliated Hosp 1, Dept Urol, Chongqing, Peoples R China; [Shang, Zhenhua; Cui, Xin] Capital Med Univ, Xuan Wu Hosp, Dept Urol, 45 Changchun St, Beijing 100053, Peoples R China; [Ye, Zhaohua] Peoples Hosp Dongguan, Dept Urol Surg, Dongguan, Peoples R China; [Yuan, Dan] Jiangmen Cent Hosp, Dept Urol, Jiangmen 529000, Guangdong, Peoples R China"

通信作者："Cui, X (通讯作者)，Capital Med Univ, Xuan Wu Hosp, Dept Urol, 45 Changchun St, Beijing 100053, Peoples R China.; Yuan, D (通讯作者)，Jiangmen Cent Hosp, Dept Urol, Jiangmen 529000, Guangdong, Peoples R China."

来源：CANCER BIOTHERAPY AND RADIOPHARMACEUTICALS

ESI学科分类：PHARMACOLOGY & TOXICOLOGY

WOS号：WOS:001140186400001

JCR分区：Q2

影响因子：2.4

年份：2023

卷号：　

期号：　

开始页：　

结束页：　

文献类型：Article; Early Access

关键词：prostate cancer; DNA damage response mutation; immune; prognostic model; biomarker

摘要："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."

基金机构：　

基金资助正文：