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ORIGINAL ARTICLE
Year : 2014  |  Volume : 10  |  Issue : 7  |  Page : 186-194

Analysis of hepatocellular carcinoma and metastatic hepatic carcinoma via functional modules in a protein-protein interaction network


1 Department of General Surgery, Second Affiliated Hospital of Soochow University, Suzhou 215004, China
2 Department of Colorectal Surgery, Renji Hospital, School of Medical, Shanghai Jiaotong University, Shanghai 200127, Jiangsu, China

Correspondence Address:
Yihui Sun
Department of General Surgery, Second Affiliated Hospital to Soochow University, 1055, Sanxiang Road, Suzhou, Jiangsu province 215004
China
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0973-1482.145866

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Introduction: This study aims to identify protein clusters with potential functional relevance in the pathogenesis of hepatocellular carcinoma (HCC) and metastatic hepatic carcinoma using network analysis. Materials and Methods: We used human protein interaction data to build a protein-protein interaction network with Cytoscape and then derived functional clusters using MCODE. Combining the gene expression profiles, we calculated the functional scores for the clusters and selected statistically significant clusters. Meanwhile, Gene Ontology was used to assess the functionality of these clusters. Finally, a support vector machine was trained on the gold standard data sets. Results: The differentially expressed genes of HCC were mainly involved in metabolic and signaling processes. We acquired 13 significant modules from the gene expression profiles. The area under the curve value based on the differentially expressed modules were 98.31%, which outweighed the classification with DEGs. Conclusions: Differentially expressed modules are valuable to screen biomarkers combined with functional modules.


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