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Article Open Access

Breast cancer survival prediction using seven prognostic biomarker genes

  • Authors:
    • Liu Liu
    • Zhilin Chen
    • Wenjie Shi
    • Hui Liu
    • Weiyi Pang
  • View Affiliations / Copyright

    Affiliations: Department of Pharmacy, Pharmacy School of Guilin Medical University, Guilin, Guangxi 541000, P.R. China, Department of Breast and Thoracic Oncological Surgery, The First Affiliated Hospital of Hainan Medical College, Haikou, Hainan 570102, P.R. China, School of Public Health, Guilin Medical University, Guilin, Guangxi 541000, P.R. China
    Copyright: © Liu et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 2907-2916
    |
    Published online on: July 18, 2019
       https://doi.org/10.3892/ol.2019.10635
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Abstract

Breast cancer (BC) is one of the most prevalent forms of cancer globally. However, the practical relevance of the RNA expression‑based prediction of BC is not clearly understood and requires further study. Using gene expression data downloaded from The Cancer Genome Atlas (TCGA), a risk score staging classification was created using Cox's multiple regression and was used to predict the clinical outcomes of patients with BC. In total, 7 genes, including AC123595.1, leukocyte immunoglobulin‑like receptor B5, CD209 molecule, AL049749.1, lymphatic vessel endothelial hyaluronan receptor 1, transmembrane protein 190 and tubulin α 3D chain were identified in association with patient survival. The patients with lower risk scores had considerably improved survival rates than those with higher risk scores. Compared with other clinical factors, the risk score more accurately predicted the clinical outcome of patients with BC. In summary, 7 genes were identified using the Cox regression model, and subsequently used to develop a risk staging model for BC, which may be of use for the medical management of patients.
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Copy and paste a formatted citation
Spandidos Publications style
Liu L, Chen Z, Shi W, Liu H and Pang W: Breast cancer survival prediction using seven prognostic biomarker genes. Oncol Lett 18: 2907-2916, 2019.
APA
Liu, L., Chen, Z., Shi, W., Liu, H., & Pang, W. (2019). Breast cancer survival prediction using seven prognostic biomarker genes. Oncology Letters, 18, 2907-2916. https://doi.org/10.3892/ol.2019.10635
MLA
Liu, L., Chen, Z., Shi, W., Liu, H., Pang, W."Breast cancer survival prediction using seven prognostic biomarker genes". Oncology Letters 18.3 (2019): 2907-2916.
Chicago
Liu, L., Chen, Z., Shi, W., Liu, H., Pang, W."Breast cancer survival prediction using seven prognostic biomarker genes". Oncology Letters 18, no. 3 (2019): 2907-2916. https://doi.org/10.3892/ol.2019.10635
Copy and paste a formatted citation
x
Spandidos Publications style
Liu L, Chen Z, Shi W, Liu H and Pang W: Breast cancer survival prediction using seven prognostic biomarker genes. Oncol Lett 18: 2907-2916, 2019.
APA
Liu, L., Chen, Z., Shi, W., Liu, H., & Pang, W. (2019). Breast cancer survival prediction using seven prognostic biomarker genes. Oncology Letters, 18, 2907-2916. https://doi.org/10.3892/ol.2019.10635
MLA
Liu, L., Chen, Z., Shi, W., Liu, H., Pang, W."Breast cancer survival prediction using seven prognostic biomarker genes". Oncology Letters 18.3 (2019): 2907-2916.
Chicago
Liu, L., Chen, Z., Shi, W., Liu, H., Pang, W."Breast cancer survival prediction using seven prognostic biomarker genes". Oncology Letters 18, no. 3 (2019): 2907-2916. https://doi.org/10.3892/ol.2019.10635
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