title: A network-based, integrative approach to identify genes with aberrant co-methylation in colorectal cancer.
abstract: Epigenetic changes, including aberrations in DNA methylation, are a common hallmark of many cancers. The identification and interpretation of epigenetic changes associated with cancers may benefit from integration with protein interactomes. Based on the assumption that genes implicated in a specific tumor phenotype will show high aberrant co-methylation patterns with their interacting partners, we propose an integrated approach to uncover cancer-associated genes by integrating a DNA methylome with an interactome. Aberrant co-methylated interactions were first identified in the specific cancer, and genes were then prioritized based on their enrichment in aberrant co-methylation. By applying this to a large-scale colorectal cancer (CRC) dataset, the proposed method increases the power to capture known genes. More importantly, genes possessing high aberrant co-methylation patterns, located at the topological center of the original protein-protein interaction network (PPIN), affect several cancer-associated pathways and form hotspots that are frequently hijacked in cancer. Additionally, the top-ranked candidate genes may also be useful as an indicator of CRC diagnosis and prognosis. Five fold cross-validation of the top-ranked genes in diagnosis reveals that it can achieve an area under the receiver operating characteristic (ROC) curve ranging from 82.2% to 98.4% in three independent datasets. Five of these genes form a core repressive module. CCNA1 and ESR1 in particular are evidently silenced by promoter hypermethylation in CRC cell lines and tissues, whose re-expression markedly suppresses tumor cell survival and clonogenicity. These results show that the network-centric method could identify novel disease biomarkers and model how oncogenic lesions mediate epigenetic changes, providing important insights into tumorigenesis.
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China. lixia@hrbmu.edu.cn.
authors: Yongsheng
authors: Y
authors: Li
authors: Juan
authors: J
authors: Xu
authors: Huanyu
authors: H
authors: Ju
authors: Yun
authors: Y
authors: Xiao
authors: Hong
authors: H
authors: Chen
authors: Junying
authors: J
authors: Lv
authors: Tingting
authors: T
authors: Shao
authors: Jing
authors: J
authors: Bai
authors: Yunpeng
authors: Y
authors: Zhang
authors: Li
authors: L
authors: Wang
authors: Xishan
authors: X
authors: Wang
authors: Huan
authors: H
authors: Ren
authors: Xia
authors: X
authors: Li
mesh_terms: D045744:Cell Line, Tumor; D002470:Cell Survival; D015179:Colorectal Neoplasms / Q000175:diagnosis* / Q000235:genetics* / Q000473:pathology; D056750:Cyclin A1 / Q000235:genetics* / Q000378:metabolism; D019175:DNA Methylation; D044127:Epigenesis, Genetic; D047628:Estrogen Receptor alpha / Q000235:genetics* / Q000378:metabolism; D020868:Gene Silencing; D015894:Genome, Human; D023281:Genomics / Q000379:methods*; D045325:HCT116 Cells; D019073:HT29 Cells; D006801:Humans; D011401:Promoter Regions, Genetic; D015203:Reproducibility of Results
chemical_list: C503745:CCNA1 protein, human; D056750:Cyclin A1; C506487:ESR1 protein, human; D047628:Estrogen Receptor alpha