Predicting hepatocellular carcinoma through cross-talk genes identified by risk pathways
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Lei Liu1,*, Lin Pang1,*, Yunfeng Wang1,*, Ming Hu1,*, Zhuo Shao1, Diwei Huo2, Denan Zhang1, Hongbo Xie1, Jingbo Yang1, Qiuqi Liu1 and Xiujie Chen1
1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang Province, China
2The 2nd Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin, Heilongjiang Province, China
*These authors contributed equally to this work
Xiujie Chen, email: firstname.lastname@example.org
Keywords: cross-talk genes; risk pathways; molecular markers; hepatocellular carcinoma (HCC)
Received: January 19, 2017 Accepted: November 16, 2017 Published: April 20, 2018
Hepatocellular carcinoma (HCC) is the most frequent type of liver cancer with poor survival rate and high mortality. Despite efforts on the mechanism of HCC, new molecular markers are needed for exact diagnosis, evaluation and treatment. Here, we combined transcriptome of HCC with networks and pathways to identify reliable molecular markers. Through integrating 249 differentially expressed genes with syncretic protein interaction networks, we constructed a HCC-specific network, from which we further extracted 480 pivotal genes. Based on the cross-talk between the enriched pathways of the pivotal genes, we finally identified a HCC signature of 45 genes, which could accurately distinguish HCC patients with normal individuals and reveal the prognosis of HCC patients. Among these 45 genes, 15 showed dysregulated expression patterns and a part have been reported to be associated with HCC and/or other cancers. These findings suggested that our identified 45 gene signature could be potential and valuable molecular markers for diagnosis and evaluation of HCC.
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