Prognostic analysis of patients with breast cancer based on tumor mutational burden and DNA damage repair genes

被引:3
|
作者
Teng, Xu [1 ]
Yang, Tianshu [1 ]
Yuan, Baowen [2 ]
Yang, Yunkai [2 ]
Liu, Jiaxiang [3 ]
Wang, Xin [3 ]
Wang, Yong [4 ]
Ma, Tianyu [2 ]
Yin, Xin [1 ]
Yu, Hefen [1 ]
Wang, Shuang [5 ]
Huang, Wei [1 ]
机构
[1] Capital Med Univ, Sch Basic Med Sci, Dept Biochem & Mol Biol, Beijing Key Lab Canc Invas & Metastasis Res, Beijing, Peoples R China
[2] Chinese Acad Med Sci & Peking Union Med Coll, Canc Hosp, Natl Clin Res Ctr Canc, Natl Canc Ctr,State Key Lab Mol Oncol,Key Lab Ca, Beijing, Peoples R China
[3] Chinese Acad Med Sci & Peking Union Med Coll, Canc Hosp, Natl Clin Res Ctr Canc, Dept Breast Surg Oncol,Natl Canc Ctr, Beijing, Peoples R China
[4] Chinese Acad Med Sci & Peking Union Med Coll, Canc Hosp, Natl Clin Res Ctr Canc, Dept Ultrasound,Natl Canc Ctr, Beijing, Peoples R China
[5] Shandong Second Prov Gen Hosp, Dept Cardio Surg Ctr, Jinan, Peoples R China
来源
FRONTIERS IN ONCOLOGY | 2023年 / 13卷
基金
中国国家自然科学基金;
关键词
breast cancer; TMB; cox regression analysis; Cox-LASSO regression analysis; prognostic model; tumor-infiltrating immune cells; IMMUNOTHERAPY; DETERMINANTS; CHALLENGES; BIOMARKERS; LANDSCAPE; PACKAGE;
D O I
10.3389/fonc.2023.1177133
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
BackgroundBreast cancer has a high tumor-specific death rate and poor prognosis. In this study, we aimed to provide a basis for the prognostic risk in patients with breast cancer using significant gene sets selected by analyzing tumor mutational burden (TMB) and DNA damage repair (DDR). MethodsBreast cancer genomic and transcriptomic data were obtained from The Cancer Genome Atlas (TCGA). Breast cancer samples were dichotomized into high- and low-TMB groups according to TMB values. Differentially expressed DDR genes between high- and low-TMB groups were incorporated into univariate and multivariate cox regression model to build prognosis model. Performance of the prognosis model was validated in an independently new GEO dataset and evaluated by time-dependent ROC curves. ResultsBetween high- and low-TMB groups, there were 6,424 differentially expressed genes, including 67 DDR genes. Ten genes associated with prognosis were selected by univariate cox regression analysis, among which seven genes constituted a panel to predict breast cancer prognosis. The seven-gene prognostic model, as well as the gene copy numbers are closely associated with tumor-infiltrating immune cells. ConclusionWe established a seven-gene prognostic model comprising MDC1, PARP3, PSMB1, PSMB9, PSMD2, PSMD7, and PSMD14 genes, which provides a basis for further exploration of a population-based prediction of prognosis and immunotherapy response in patients with breast cancer.
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页数:16
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