title: Identification of breast cancer recurrence risk factors based on functional pathways in tumor and normal tissues.
abstract: The recurrence of breast cancer (BC) is a serious therapeutic problem, and the risk factors for recurrence urgently need to be identified. In this study, we examined the functional pathways in tumor and normal tissues to more comprehensively identify biomarkers for the risk of BC recurrence. We collected tumor and normal tissue gene expression profiles of recurrent BC patients and non-recurrent BC patients from the TCGA database.We derived an expression interval (mean ± 1.96SD) based on non-recurrent patients rather than a single value, such as a mean or median. If the expression of a gene was significantly different from its normal expression interval, it was considered a differentially expressed gene. Eight pathways that significantly distinguished recurrent and non-recurrent BC patients were obtained based on 65% accuracy, and these pathways were all associated with the immune response and sensitivity to drugs. The genes in these eight pathways were also used to analyze survival, and the significance level reached 0.003 in an independent dataset (p = 0.02 in tumor and p = 0.03 in normal tissue). Our results reveal that the integration of tumor and normal tissue functional analyses can comprehensively enhance the understanding of BC prognosis.
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, PR China.
authors: Xiujie
authors: X
authors: Chen
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, PR China.
authors: Lei
authors: L
authors: Liu
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, PR China.
authors: YunFeng
authors: Y
authors: Wang
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, PR China.
authors: Bo
authors: B
authors: Liu
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, PR China.
authors: Diheng
authors: D
authors: Zeng
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, PR China.
authors: Qing
authors: Q
authors: Jin
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, PR China.
authors: MengJian
authors: M
authors: Li
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, PR China.
authors: DeNan
authors: D
authors: Zhang
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, PR China.
authors: Qiuqi
authors: Q
authors: Liu
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, PR China.
authors: Hongbo
authors: H
authors: Xie
mesh_terms: D014408:Biomarkers, Tumor / Q000032:analysis / Q000235:genetics*; D001943:Breast Neoplasms / Q000235:genetics* / Q000473:pathology; D016000:Cluster Analysis; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D053263:Gene Regulatory Networks; D006801:Humans; D009364:Neoplasm Recurrence, Local / Q000235:genetics* / Q000473:pathology; D059467:Transcriptome
chemical_list: D014408:Biomarkers, Tumor
keywords: breast cancer; normal tissue; recurrence; risk factors; tumor tissue