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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Bioinformatics Analysis of Expression and Alterations of BARD1 in Breast Cancer
Yong-Zi Chen1,2, Duo Zuo3,2, Hai-Ling Ren4
1Laboratory of Tumor Cell Biology, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, PR China.
Background:
Breast cancer is one of the most common malignant tumor type in women worldwide. BARD1 could impact function of BRCA1 as its interaction partner. In the current study, we aimed to investigate the prognostic role of BARD1 expression as well as its alterations in breast cancer using different online tools.
Methods:
We performed a bioinformatics analysis for BARD1 in patients with breast cancer using several online databases, including Oncomine, bc-GenExMiner, PrognoScan, Search Tool for the Retrieval of Interacting Genes, Cytoscape, and cBioPortal.
Results:
We found that BARD1 was highly expressed in basal-like, HER2-E, and luminal B compared with normal-like subtype. Forest plot showed that BARD1 overexpression was correlated with worse distant metastasis-free survival (hazard ratio: 2.72, 95% confidence interval: 1.02-2.21; P = .0448), disease-specific survival (hazard ratio: 2.65, 95% confidence interval: 1.37-5.12; P = .0037), and disease-free survival (hazard ratio: 1.98, 95% confidence interval: 1.22-3.24; P = .0062) but positively correlated with overall survival (hazard ratio: 0.66, 95% confidence interval: 0.50-0.85; P = .0017). Multivariate analysis indicated that BARD1 expression was significantly associated with distant metastasis-free survival (hazard ratio: 4.60, 95% confidence interval: 1.22-17.28; P = .0239) whereas marginally significant for disease-free survival (hazard ratio: 1.00, 95% confidence interval: 1.00-1.01, P = .0630) and disease-specific survival (hazard ratio: 1.96, 95% confidence interval: 0.97-3.96; P = .0602). Meanwhile, alterations in BARD1 interaction network were associated with worse overall survival instead of BARD1 alteration alone.
Conclusions:
Bioinformatics analysis revealed that BARD1 may be a predictive biomarker for prognosis of breast cancer. However, future research is required to validate our findings.
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