title: Alterations of tumor-related genes do not exactly match the histopathological grade in gastric adenocarcinomas.
abstract: OBJECTIVE
  To investigate the diverse characteristics of different pathological gradings of gastric adenocarcinoma (GA) using tumor-related genes.
  
  
  METHODS
  GA tissues in different pathological gradings and normal tissues were subjected to tissue arrays. Expressions of 15 major tumor-related genes were detected by RNA in situ hybridization along with 3' terminal digoxin-labeled anti-sense single stranded oligonucleotide and locked nucleic acid modifying probe within the tissue array. The data obtained were processed by support vector machines by four different feature selection methods to discover the respective critical gene/gene subsets contributing to the GA activities of different pathological gradings.
  
  
  RESULTS
  In comparison of poorly differentiated GA with normal tissues, tumor-related gene TP53 plays a key role, although other six tumor-related genes could also achieve the Area Under Curve (AUC) of the receiver operating characteristic independently by more than 80%. Comparing the well differentiated GA with normal tissues, we found that 11 tumor-related genes could independently obtain the AUC by more than 80%, but only the gene subsets, TP53, RB and PTEN, play a key role. Only the gene subsets, Bcl10, UVRAG, APC, Beclin1, NM23, PTEN and RB could distinguish between the poorly differentiated and well differentiated GA. None of a single gene could obtain a valid distinction.
  
  
  CONCLUSIONS
  Different from the traditional point of view, the well differentiated cancer tissues have more alterations of important tumor-related genes than the poorly differentiated cancer tissues.
authors.affiliation: Department of General Surgery, The Affiliated Zhongshan Hospital of Xiamen University, The Digestive Disease Research Institute of Xiamen University, Xiamen 361004, Fujian Province, China.
authors.forename: Guo-Yan
authors.initials: GY
authors.lastname: Liu
authors.forename: Kun-Hong
authors.initials: KH
authors.lastname: Liu
authors.forename: Yong
authors.initials: Y
authors.lastname: Zhang
authors.forename: Yu-Zhi
authors.initials: YZ
authors.lastname: Wang
authors.forename: Xiao-Hong
authors.initials: XH
authors.lastname: Wu
authors.forename: Yi-Zhuo
authors.initials: YZ
authors.lastname: Lu
authors.forename: Chao
authors.initials: C
authors.lastname: Pan
authors.forename: Ping
authors.initials: P
authors.lastname: Yin
authors.forename: Hong-Feng
authors.initials: HF
authors.lastname: Liao
authors.forename: Ji-Qin
authors.initials: JQ
authors.lastname: Su
authors.forename: Qing
authors.initials: Q
authors.lastname: Ge
authors.forename: Qi
authors.initials: Q
authors.lastname: Luo
authors.forename: Bin
authors.initials: B
authors.lastname: Xiong
mesh_terms: D000230:Adenocarcinoma / Q000235:genetics* / Q000473:pathology*; D000328:Adult; D000368:Aged; D014408:Biomarkers, Tumor / Q000235:genetics*; D002454:Cell Differentiation / Q000235:genetics*; D005260:Female; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D017403:In Situ Hybridization; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D011237:Predictive Value of Tests; D012333:RNA, Messenger / Q000032:analysis; D012372:ROC Curve; D013274:Stomach Neoplasms / Q000235:genetics* / Q000473:pathology*; D046888:Tissue Array Analysis
chemical_list: D014408:Biomarkers, Tumor; D012333:RNA, Messenger