title: Expression profiling based on graph-clustering approach to determine colon cancer pathway.
abstract: BACKGROUND
  Colorectal cancer is the second leading cause of cancer deaths worldwide. DNA microarray-based technologies allow simultaneous analysis of expression of thousands of genes.
  
  
  OBJECTIVE
  To search for important molecular markers and pathways that hold great promise for further treatment of patients with colorectal cancer.
  
  
  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.
authors.affiliation: Department of Traditional Chinese Medicine, Hangzhou First People's Hospital, 261 Huansha Road, Hangzhou, Zhejiang 310006, China.
authors.forename: Xiao-qu
authors.initials: XQ
authors.lastname: Zhu
authors.forename: Mei-lan
authors.initials: ML
authors.lastname: Hu
authors.forename: Feng
authors.initials: F
authors.lastname: Zhang
authors.forename: Yu
authors.initials: Y
authors.lastname: Tao
authors.forename: Chun-ming
authors.initials: CM
authors.lastname: Wu
authors.forename: Shang-zhu
authors.initials: SZ
authors.lastname: Lin
authors.forename: Fu-le
authors.initials: FL
authors.lastname: He
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D003110:Colonic Neoplasms / Q000235:genetics* / Q000378:metabolism*; D019295:Computational Biology / Q000379:methods; D057225:Data Mining / Q000379:methods; D030541:Databases, Genetic; D020869:Gene Expression Profiling; D006801:Humans; D008954:Models, Biological; D015398:Signal Transduction