title: p42.3 gene expression in gastric cancer cell and its protein regulatory network analysis.
abstract: BACKGROUND
  To analyze the p42.3 gene expression in gastric cancer (GC) cell, find the relationship between protein structure and function, establish the regulatory network of p42.3 protein molecule and then to obtain the optimal regulatory pathway.
  
  
  METHODS
  The expression of p42.3 gene was analyzed by RT-PCR, Western Blot and other biotechnologies. The relationship between the spatial conformation of p42.3 protein molecule and its function was analyzed using bioinformatics, MATLAB and related knowledge about protein structure and function. Furthermore, based on similarity algorithm of spatial layered spherical coordinate, we compared p42.3 molecule with several similar structured proteins which are known for the function, screened the characteristic nodes related to tumorigenesis and development, and established the multi variable relational model between p42.3 protein expression, cell cycle regulation and biological characteristics in the level of molecular regulatory networks. Finally, the optimal regulatory network was found by using Bayesian network.
  
  
  RESULTS
  (1) The expression amount of p42.3 in G1 and M phase was higher than that in S and G2 phase; (2) The space coordinate systems of different structural domains of p42.3 protein were established in Matlab7.0 software; (3) The optimal pathway of p42.3 gene in protein regulatory network in gastric cancer is Ras protein, Raf-1 protein, MEK, MAPK kinase, MAPK, tubulin, spindle protein, centromere protein and tumor.
  
  
  CONCLUSIONS
  It is of vital significance for mechanism research to find out the action pathway of p42.3 in protein regulatory network, since p42.3 protein plays an important role in the generation and development of GC.
authors.affiliation: Department of Biomedical Engineering, School of Electrical Engineering, Zhengzhou University, Zhengzhou, Henan Province 450001, China.
authors.forename: Jianhua
authors.initials: J
authors.lastname: Zhang
authors.forename: Chunlei
authors.initials: C
authors.lastname: Lu
authors.forename: Zhigang
authors.initials: Z
authors.lastname: Shang
authors.forename: Rui
authors.initials: R
authors.lastname: Xing
authors.forename: Li
authors.initials: L
authors.lastname: Shi
authors.forename: Youyong
authors.initials: Y
authors.lastname: Lv
mesh_terms: D001499:Bayes Theorem; D002453:Cell Cycle / Q000235:genetics; D018797:Cell Cycle Proteins / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks / Q000235:genetics*; D006801:Humans; D009363:Neoplasm Proteins / Q000235:genetics* / Q000378:metabolism; D009687:Nuclear Proteins; D017434:Protein Structure, Tertiary; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism; D013274:Stomach Neoplasms / Q000235:genetics* / Q000473:pathology*
chemical_list: D018797:Cell Cycle Proteins; D009363:Neoplasm Proteins; D009687:Nuclear Proteins; D012333:RNA, Messenger; C000607889:SAPCD2 protein, human