title: Topologically inferring pathway activity for precise survival outcome prediction: breast cancer as a case.
abstract: Accurately predicting the survival outcome of patients is of great importance in clinical cancer research. In the past decade, building survival prediction models based on gene expression data has received increasing interest. However, the existing methods are mainly based on individual gene signatures, which are known to have limited prediction accuracy on independent datasets and unclear biological relevance. Here, we propose a novel pathway-based survival prediction method called DRWPSurv in order to accurately predict survival outcome. DRWPSurv integrates gene expression profiles and prior gene interaction information to topologically infer survival associated pathway activities, and uses the pathway activities as features to construct Lasso-Cox model. It uses topological importance of genes evaluated by directed random walk to enhance the robustness of pathway activities and thereby improve the predictive performance. We applied DRWPSurv on three independent breast cancer datasets and compared the predictive performance with a traditional gene-based method and four pathway-based methods. Results showed that pathway-based methods obtained comparable or better predictive performance than the gene-based method, whereas DRWPSurv could predict survival outcome with better accuracy and robustness among the pathway-based methods. In addition, the risk pathways identified by DRWPSurv provide biologically informative models for breast cancer prognosis and treatment.
authors.affiliation: The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou, 515041, China. lyxu@stu.edu.cn nmli@stu.edu.cn and Department of Mathematics, Heilongjiang Institute of Technology, Harbin, 150050, China.
authors.forename: Wei
authors.identifier: http://orcid.org/0000-0002-5496-3641
authors.initials: W
authors.lastname: Liu
authors.affiliation: Department of Mathematics, Heilongjiang Institute of Technology, Harbin, 150050, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Wang
authors.affiliation: Department of Mathematics, Heilongjiang Institute of Technology, Harbin, 150050, China.
authors.forename: Guohua
authors.initials: G
authors.lastname: Tian
authors.affiliation: Network Information Center, Shantou University Medical College, Shantou, 515041, China.
authors.forename: Wenming
authors.initials: W
authors.lastname: Xie
authors.affiliation: Network Information Center, Shantou University Medical College, Shantou, 515041, China.
authors.forename: Li
authors.initials: L
authors.lastname: Lei
authors.affiliation: Network Information Center, Shantou University Medical College, Shantou, 515041, China.
authors.forename: Jiujin
authors.initials: J
authors.lastname: Liu
authors.affiliation: Network Information Center, Shantou University Medical College, Shantou, 515041, China.
authors.forename: Wanxun
authors.initials: W
authors.lastname: Huang
authors.affiliation: The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou, 515041, China. lyxu@stu.edu.cn nmli@stu.edu.cn and Institute of Oncologic Pathology, Shantou University Medical College, Shantou, 515041, China.
authors.forename: Liyan
authors.initials: L
authors.lastname: Xu
authors.affiliation: The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou, 515041, China. lyxu@stu.edu.cn nmli@stu.edu.cn and Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou 515041, China.
authors.forename: Enmin
authors.initials: E
authors.lastname: Li
mesh_terms: D000465:Algorithms; D014408:Biomarkers, Tumor; D001943:Breast Neoplasms / Q000235:genetics / Q000378:metabolism* / Q000401:mortality*; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D030541:Databases, Genetic; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D006801:Humans; D053208:Kaplan-Meier Estimate; D008954:Models, Biological; D011379:Prognosis; D025941:Protein Interaction Mapping / Q000379:methods; D015203:Reproducibility of Results; D015398:Signal Transduction
chemical_list: D014408:Biomarkers, Tumor