Identification of a three-gene signature in the triple-negative breast cancer

作     者：LIPING WANG ZHOU LUO MINMIN SUN QIUYUE YUAN YINGGANG ZOU DEYUAN FU 

作者机构：Clinical Medical CollegeYangzhou UniversityYangzhou225009China Institute of Epigenetics and EpigenomicsCollege of Animal Science and TechnologyYangzhou UniversityYangzhou225009China Key Laboratory of Animal Genetics and BreedingMolecular Design of Jiangsu ProvinceYangzhou UniversityYangzhou225009China China Medical UniversityShenyang110122China Department of Obstetrics and GynecologyThe Second Hospital of Jilin UniversityChangchun130021China 

出 版 物：《BIOCELL》 (生物细胞（英文）)

年 卷 期：2022年第46卷第3期

页      面：595-606页

核心收录：

学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学] 

基　　金：This study was funded by The National Natural Science Foundation of China(Nos.82072909,825001512) The Maternal and Child Health Research Foundation of Jiangsu Province(No.F201945) The Science and Technology Development Plan Project of Jilin Province(Nos.20200404169YY,20180101140JC) the Postgraduate Training Innovation Foundation of Jiangsu Province(No.KYCX19_2113) 

主　　题：Triple-negative breast cancer Prognosis Biomarker 

摘      要：This work aimed to improve current prognostic signatures based on clinical stages in identifying high-risk patients of triple-negative breast cancer(TNBC),to allow patients with a high-risk score for specific treatment *** this study,396 TNBC samples from TCGA and GEO databases were included in genome-wide transcriptome *** relationship between normalized gene expression values and survival data of patients was determined by Cox proportional hazards models in each *** overlapped genes among all datasets were considered as a potential prognostic *** risk score was constructed based on individual genes and validated with three separate data sets and the combined ***,the Kaplan–Meier analysis including the log-rank test was performed to determine significantly statistical differences in overall *** association analysis between DNA methylation levels and gene expression levels of three genes was measured in the TCGA data *** Cox proportional hazards model analysis,the result showed that potential protective genes included 564 genes in GSE25066 dataset,1132 genes in GSE103091 dataset and 564 genes in TCGA dataset,potentially risky genes contained 1132 genes in GSE25066 dataset,475 genes in GSE25066 dataset and 1115 genes in TCGA *** all datasets,patients in high-risk groups showed worse prognosis than low-risk *** Cox regression analysis displayed that the 3-gene signature(DCAF4,UQCRFS1 and SS18)was an independent prognostic factor in *** AUC values of the 3-gene signature were 0.71,0.73 and 0.77 in GSE25066,GSE103091 and TCGA dataset,*** model,which combined the 3-gene signature(DCAF4,UQCRFS1 and SS18)with the tumor stage(pathological stage or pathological T stage),showed a stronger prognostic power for survival *** 3-genes prognostic signature may be a useful biomarker for survival prediction in TNBC patients and may contribute to patient classification in t