期刊
GENOMICS
卷 104, 期 4, 页码 242-248出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ygeno.2013.11.002
关键词
Colon cancer; Module
资金
- Science & Technology Research Project of the Heilongjiang Ministry of Education [12511271]
- National Natural Science Foundation of China [61272388]
- Student Innovation Funds of Heilongjiang Province [2012-011HLJ, 2012-071HMU]
Identifying differences between normal and tumor samples from a modular perspective may help to improve our understanding of the mechanisms responsible for colon cancer. Many cancer studies have shown that signaling transduction and biological pathways are disturbed in disease states, and expression profiles can distinguish variations in diseases. In this study, we integrated a weighted human signaling network and gene expression profiles to select risk modules associated with tumor conditions. Risk modules as classification features by our method had a better classification performance than other methods, and one risk module for colon cancer had a good classification performance for distinguishing between normal/tumor samples and between tumor stages. All genes in the module were annotated to the biological process of positive regulation of cell proliferation, and were highly associated with colon cancer. These results suggested that these genes might be the potential risk genes for colon cancer. (C) 2013 Published by Elsevier Inc.
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