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ORIGINAL ARTICLE
Year : 2013  |  Volume : 9  |  Issue : 3  |  Page : 467-470

Expression profiling based on graph-clustering approach to determine colon cancer pathway


1 Department of Gastroenterology and Hepatology, Wenzhou Hospital of Traditional Chinese Medicine, 27 Dashimen Xinhe Road, Wenzhou, Zhejiang 325000, China
2 Department of Traditional Chinese Medicine, Hangzhou First People's Hospital, 261 Huansha Road, Hangzhou, Zhejiang 310006, China
3 Postgraduate student of 2011 grade, The First Clinical Medical College of Zhejiang Chinese Medical University, 548 Binwen Road, Hangzhou, Zhejiang 310053, China
4 Department of Oncology, Wenzhou Hospital of Traditional Chinese Medicine, 27 Dashimen Xinhe Road, Wenzhou, Zhejiang 325000, China

Correspondence Address:
Fu-le He
Department of Traditional Chinese Medicine, Hangzhou First People's Hospital, 261 Huansha Road, Hangzhou, Zhejiang 310006
China
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0973-1482.119351

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Context: Colorectal cancer is the second leading cause of cancer deaths worldwide. DNA microarray-based technologies allow simultaneous analysis of expression of thousands of genes. Aim: To search for important molecular markers and pathways that hold great promise for further treatment of patients with colorectal cancer. Materials and Methods: Here, we performed a comprehensive gene-level assessment of colorectal cancer using 35 colorectal cancer and 24 normal samples. Results: It was shown that AURKA, MT1G, and AKAP12 had a high degree of response in colorectal cancer. Besides, we further explored the underlying molecular mechanism within these different genes. Conclusions: The results indicated calcium signaling pathway and vascular smooth muscle contraction pathway were the two significant pathways, giving hope to provide insights into the development of novel therapeutic targets and pathways.


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