title: Weighted gene co-expression network analysis of colorectal cancer liver metastasis genome sequencing data and screening of anti-metastasis drugs.
abstract: Approximately 9% of cancer-related deaths are caused by colorectal cancer (CRC). CRC patients are prone to liver metastasis, which is the most important cause for the high CRC mortality rate. Understanding the molecular mechanism of CRC liver metastasis could help us to find novel targets for the effective treatment of this deadly disease. Using weighted gene co-expression network analysis on the sequencing data of CRC with and with metastasis, we identified 5 colorectal cancer liver metastasis related modules which were labeled as brown, blue, grey, yellow and turquoise. In the brown module, which represents the metastatic tumor in the liver, gene ontology (GO) analysis revealed functions including the G-protein coupled receptor protein signaling pathway, epithelial cell differentiation and cell surface receptor linked signal transduction. In the blue module, which represents the primary CRC that has metastasized, GO analysis showed that the genes were mainly enriched in GO terms including G-protein coupled receptor protein signaling pathway, cell surface receptor linked signal transduction, and negative regulation of cell differentiation. In the yellow and turquoise modules, which represent the primary non-metastatic CRC, 13 downregulated CRC liver metastasis-related candidate miRNAs were identified (e.g. hsa-miR-204, hsa-miR-455, etc.). Furthermore, analyzing the DrugBank database and mining the literature identified 25 and 12 candidate drugs that could potentially block the metastatic processes of the primary tumor and inhibit the progression of metastatic tumors in the liver, respectively. Data generated from this study not only furthers our understanding of the genetic alterations that drive the metastatic process, but also guides the development of molecular-targeted therapy of colorectal cancer liver metastasis.
authors: Department of General Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150001, P.R. China.
authors: Bo
authors: B
authors: Gao
authors: Department of Pathology, The Research Institute of McGill University Health Center, Montreal, Québec H4A 3J1, Canada.
authors: Qin
authors: Q
authors: Shao
authors: McGill University and Genome Quebec Innovation Centre, Montreal, Québec H3B 1S6, Canada.
authors: Hani
authors: H
authors: Choudhry
authors: Department of Pathology, The Research Institute of McGill University Health Center, Montreal, Québec H4A 3J1, Canada.
authors: Victoria
authors: V
authors: Marcus
authors: Department of Pathology, Beijing Youan Hospital, Capital Medical University, Beijing 100069, P.R. China.
authors: Kung
authors: K
authors: Dong
authors: McGill University and Genome Quebec Innovation Centre, Montreal, Québec H3B 1S6, Canada.
authors: Jiannis
authors: J
authors: Ragoussis
authors: Department of Pathology, The Research Institute of McGill University Health Center, Montreal, Québec H4A 3J1, Canada.
authors: Zu-Hua
authors: ZH
authors: Gao
mesh_terms: D002465:Cell Movement / Q000187:drug effects; D015179:Colorectal Neoplasms / Q000188:drug therapy / Q000235:genetics*; D003198:Computer Simulation; D057225:Data Mining; D062313:Databases, Pharmaceutical; D004354:Drug Screening Assays, Antitumor; D020869:Gene Expression Profiling / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks / Q000187:drug effects; D006801:Humans; D008113:Liver Neoplasms / Q000188:drug therapy / Q000235:genetics* / Q000556:secondary; D058990:Molecular Targeted Therapy; D017422:Sequence Analysis, DNA / Q000379:methods*