Journal of Shandong University (Health Sciences) ›› 2020, Vol. 58 ›› Issue (5): 69-76.doi: 10.6040/j.issn.1671-7554.0.2020.117

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Significance of a three-lncRNAs signature on the prediction of survival for HER2 positive breast cancer patients

YANG Xuemei1, LI Juan1, WANG Yifan1, LI Peilong1, WANG Yunshan1, DU Lutao1, WANG Chuanxin1,2   

  1. 1. Department of Clinical Laboratory, The Second Hospital, Cheeloo College of Medcine, Shandong University, Jinan 250033, Shandong, China;
    2. Tumor Marker Detection Engineering Laboratory of Shandong Province, Jinan 250033, Shandong, China
  • Published:2022-09-27

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Abstract: Objective To construct a long non-coding RNA(lncRNA)-based signature for predicting the survival of human epidermal growth factor receptor-2(HER2)positive breast cancer patients by using The Cancer Genome Atlas(TCGA)database. Methods RNA expression profiles and clinical data were downloaded from TCGA database. Differentially expression lncRNAs(DELs)were identified by the “DESeq2” package in R. Univariate Cox proportional hazards regression(CPHR)analysis and Kaplan-Meier curve were then used to identify prognostic DELs. Stepwise multivariate CPHR model was performed for constructing a lncRNAs-based prognostic signature in the training set. Kaplan-Meier curve was used to assess the predictive performance of the signature in the training set, validation set, total set and other subgroups. Results Based on TCGA database, 1 332 DELs were identified between 161 HER2 positive breast cancer and 113 normal cases by using the “DESeq2” package. Out of these DELs, 25 DELs were found to be associated with overall survival(OS)according to the univariate CPHR analysis and Kaplan-Meier curve. In the training set, a 3-lncRNAs signature was constructed: risk score=0.710 × ExpressionLINC01833+1.869×ExpressionLINC00536+2.992×ExpressionLINC02725. This signature could effectively pick out high-risk group and low-risk group. Kaplan-Meier curve revealed that high-risk group tended to shorten survival. The area under the time-dependent receiver operating characteristic(ROC)curve of the molecular signature was 0.825, which was superior to TNM stage(AUC=0.605). Furthermore, the 3-lncRNAs signature could still distinguish the high-risk patients who had a shorter OS from the low-risk patients even in the TNM Ⅰ-Ⅱ subgroup, ER positive subgroup, PR negative subgroup and PR positive subgroup. Conclusion The proposed 3-lncRNAs signature based on LINC01833, LINC00536, and LINC02725 exhibits satisfactory individual prediction of survival for HER2 positive breast cancer, which may improve clinical management of HER2 positive breast cancer.

Key words: Human epidermal growth factor receptor-2, Breast cancer, Long non-coding RNA, Prognosis, Cox regression model

CLC Number: 

  • R737.9
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