Journal of Shandong University (Health Sciences) ›› 2021, Vol. 59 ›› Issue (7): 74-84.doi: 10.6040/j.issn.1671-7554.0.2021.0002

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Construct of a risk assessment model of breast cancer immune-related lncRNAs based on the database information

LI Wanwan1, ZHOU Wenkai1, DONG Shuqing1, HE Shiqing1, LIU Zhao2, ZHANG Jiaxin2, LIU Bin3   

  1. 1.Xuzhou Medical University, Xuzhou 221000, Jiangsu, China;
    2. Department of Thyroid and Breast Surgery, The Affiliated Hospital of Xuzhou Medical University, Xuzhou 221000, Jiangsu, China;
    3. Department of Hepatobiliary and Pancreatic Hernia, The Affiliated Hospital of Xuzhou Medical University, Xuzhou 221000, Jiangsu, China
  • Published:2021-07-16

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Abstract: Objective To screen the immune-related long non-coding RNA(lncRNA)in breast cancer, construct a breast cancer prognostic risk assessment model, and explore the prognostic factors. Methods The sequencing data, clinical information and immune gene set of breast cancer patients from the official websites of UCSC Xena(https://xena.ucsc.edu/), TCGA, and immport(https://www.immport.org/home)were downloaded. The data were sorted and cleaned, and finally breast cancer immune-related lncRNA expression matrix and clinical information were got. Univariate Cox regression analysis and Multivariate Cox regression analysis were used to screen out lncRNAs related to prognosis, so as to construct a prognostic risk score. According to the median risk score, the patients were divided into high-risk and low-risk groups. Kaplan-Meier(K-M)survival analysis, receiver operating characteristic(ROC)curve analysis and independent prognostic factor evaluation were used to evaluate the model. Combined with other clinical factors and risk scores of breast cancer, a nomogram was drawn to predict the individual survival rate of breast cancer patients. Results Ten immune-related lncRNAs were determined to construct a risk scoring model. The high-risk group had a poorer prognosis compared with the low-risk group. Risk score could be used as an independent prognostic factor for breast cancer. The C-index(CI)of the nomogram was 0.751. The calibration chart showed that the predicted value was in good agreement with the actual observation value. Conclusion A risk scoring model composed of 10 immune-related lncRNAs can be used to assess the prognosis of the breast cancer patients, and the corresponding nomogram can further predict the survival rate.

Key words: Breast cancer, Long non-coding RNA, Immunity, Prognosis, Predictive model

CLC Number: 

  • R736.3
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