1. Expression profiling based on graph-clustering approach to determine colon cancer pathway.
- Author
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Zhu XQ, Hu ML, Zhang F, Tao Y, Wu CM, Lin SZ, and He FL
- Subjects
- Algorithms, Computational Biology methods, Data Mining methods, Databases, Genetic, Humans, Cluster Analysis, Colonic Neoplasms genetics, Colonic Neoplasms metabolism, Gene Expression Profiling, Models, Biological, Signal Transduction
- Abstract
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.
- Published
- 2013
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