title: Gene expression signature-based prognostic risk score in gastric cancer.
abstract: OBJECTIVE
  Despite continual efforts to develop a prognostic model of gastric cancer by using clinical and pathologic parameters, a clinical test that can discriminate patients with good outcomes from those with poor outcomes after gastric cancer surgery has not been established. We aim to develop practical biomarker-based risk score that can predict relapse of gastric cancer after surgical treatment.
  
  
  METHODS
  Microarray technologies were used to generate and analyze gene expression profiling data from 65 gastric cancer patients to identify biomarker genes associated with relapse. The association of expression patterns of identified genes with relapse and overall survival was validated in independent gastric cancer patients.
  
  
  RESULTS
  We uncovered two subgroups of gastric cancer that were strongly associated with the prognosis. For the easy translation of our findings into practice, we developed a scoring system based on the expression of six genes that predicted the likelihood of relapse after curative resection. In multivariate analysis, the risk score was an independent predictor of relapse in a cohort of 96 patients. We were able to validate the robustness of the six-gene signature in an additional independent cohort.
  
  
  CONCLUSIONS
  The risk score derived from the six-gene set successfully prognosticated the relapse of gastric cancer patients after gastrectomy.
authors: Department of Systems Biology, Division of Cancer Medicine, The University of Texas M. D. Anderson Cancer Center, Houston, Texas 77054, USA.
authors: Jae Yong
authors: JY
authors: Cho
authors: Jae Yun
authors: JY
authors: Lim
authors: Jae Ho
authors: JH
authors: Cheong
authors: Yun-Yong
authors: YY
authors: Park
authors: Se-Lyun
authors: SL
authors: Yoon
authors: Soo Mi
authors: SM
authors: Kim
authors: Sang-Bae
authors: SB
authors: Kim
authors: Hoguen
authors: H
authors: Kim
authors: Soon Won
authors: SW
authors: Hong
authors: Young Nyun
authors: YN
authors: Park
authors: Sung Hoon
authors: SH
authors: Noh
authors: Eun Sung
authors: ES
authors: Park
authors: In-Sun
authors: IS
authors: Chu
authors: Waun Ki
authors: WK
authors: Hong
authors: Jaffer A
authors: JA
authors: Ajani
authors: Ju-Seog
authors: JS
authors: Lee
mesh_terms: D000230:Adenocarcinoma / Q000175:diagnosis* / Q000235:genetics / Q000378:metabolism; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000378:metabolism*; D018572:Disease-Free Survival; D005260:Female; D046152:Gastrointestinal Stromal Tumors / Q000175:diagnosis / Q000235:genetics / Q000378:metabolism; D020869:Gene Expression Profiling; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009364:Neoplasm Recurrence, Local; D016017:Odds Ratio; D020411:Oligonucleotide Array Sequence Analysis; D011379:Prognosis; D016016:Proportional Hazards Models; D012372:ROC Curve; D013274:Stomach Neoplasms / Q000175:diagnosis* / Q000235:genetics / Q000378:metabolism
chemical_list: D014408:Biomarkers, Tumor