title: Immunoglobulin superfamily genes are novel prognostic biomarkers for breast cancer.
abstract: Breast cancer progression is associated with dysregulated expression of the immunoglobulin superfamily (IgSF) genes that are involved in cell-cell recognition, binding and adhesion. Despite widespread evidence that many IgSF genes could serve as effective biomarkers, this potential has not been realized because the studies have focused mostly on individual genes and not the entire network. To gain a global perspective of the IgSF-related biomarkers, we constructed an IgSF-directed neighbor network (IDNN) and an IgSF-directed driver network (IDDN) by integrating multiple levels of data, including IgSF genes, breast cancer driver genes, protein-protein interaction (PPI) networks and gene expression profiling data. Our study shows that IgSF genes in the PPI network have important topological features related to cancer. Most IgSF genes are either cancer driver genes themselves or associated with them. We also identified a 21-gene IgSF network module with enriched mutations that are associated with overall survival based on 450 breast cancer patient samples extracted from The Cancer Genome Atlas (TCGA) and multiple independent microarray validation datasets. These results highlight the potential of IgSF genes as novel diagnostic, prognostic and therapeutic targets for breast cancer.
authors.affiliation: Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, 150081, China.
authors.forename: Yue
authors.initials: Y
authors.lastname: Li
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
authors.forename: Maoni
authors.initials: M
authors.lastname: Guo
authors.affiliation: Department of Immunology, Harbin Medical University, Harbin, 150081, China.
authors.forename: Zhenkun
authors.initials: Z
authors.lastname: Fu
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
authors.forename: Peng
authors.initials: P
authors.lastname: Wang
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
authors.forename: Yue
authors.initials: Y
authors.lastname: Gao
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
authors.forename: Ming
authors.initials: M
authors.lastname: Yue
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
authors.forename: Shangwei
authors.initials: S
authors.lastname: Ning
authors.affiliation: Department of Immunology, Harbin Medical University, Harbin, 150081, China.
authors.forename: Dianjun
authors.initials: D
authors.lastname: Li
mesh_terms: D014408:Biomarkers, Tumor / Q000235:genetics*; D001943:Breast Neoplasms / Q000235:genetics*; D018450:Disease Progression; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D005803:Genes, Immunoglobulin; D006801:Humans; D005810:Multigene Family; D009154:Mutation; D011379:Prognosis; D060066:Protein Interaction Maps; D016019:Survival Analysis
chemical_list: D014408:Biomarkers, Tumor
keywords: breast cancer; immunoglobulin superfamily; network module; prognostic biomarker; topology feature