title: Prognostic biomarkers for esophageal adenocarcinoma identified by analysis of tumor transcriptome.
abstract: BACKGROUND
  Despite many attempts to establish pre-treatment prognostic markers to understand the clinical biology of esophageal adenocarcinoma (EAC), validated clinical biomarkers or parameters remain elusive. We generated and analyzed tumor transcriptome to develop a practical biomarker prognostic signature in EAC.
  
  
  RESULTS
  Untreated esophageal endoscopic biopsy specimens were obtained from 64 patients undergoing surgery and chemoradiation. Using DNA microarray technology, genome-wide gene expression profiling was performed on 75 untreated cancer specimens from 64 EAC patients. By applying various statistical and informatical methods to gene expression data, we discovered distinct subgroups of EAC with differences in overall gene expression patterns and identified potential biomarkers significantly associated with prognosis. The candidate marker genes were further explored in formalin-fixed, paraffin-embedded tissues from an independent cohort (52 patients) using quantitative RT-PCR to measure gene expression. We identified two genes whose expression was associated with overall survival in 52 EAC patients and the combined 2-gene expression signature was independently associated with poor outcome (P<0.024) in the multivariate Cox hazard regression analysis.
  
  
  CONCLUSIONS
  Our findings suggest that the molecular gene expression signatures are associated with prognosis of EAC patients and can be assessed prior to any therapy. This signature could provide important improvement for the management of EAC patients.
authors.affiliation: Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
authors.forename: Soo Mi
authors.initials: SM
authors.lastname: Kim
authors.forename: Yun-Yong
authors.initials: YY
authors.lastname: Park
authors.forename: Eun Sung
authors.initials: ES
authors.lastname: Park
authors.forename: Jae Yong
authors.initials: JY
authors.lastname: Cho
authors.forename: Julie G
authors.initials: JG
authors.lastname: Izzo
authors.forename: Di
authors.initials: D
authors.lastname: Zhang
authors.forename: Sang-Bae
authors.initials: SB
authors.lastname: Kim
authors.forename: Jeffrey H
authors.initials: JH
authors.lastname: Lee
authors.forename: Manoop S
authors.initials: MS
authors.lastname: Bhutani
authors.forename: Stephen G
authors.initials: SG
authors.lastname: Swisher
authors.forename: Xifeng
authors.initials: X
authors.lastname: Wu
authors.forename: Kevin R
authors.initials: KR
authors.lastname: Coombes
authors.forename: Dipen
authors.initials: D
authors.lastname: Maru
authors.forename: Kenneth K
authors.initials: KK
authors.lastname: Wang
authors.forename: Navtej S
authors.initials: NS
authors.lastname: Buttar
authors.forename: Jaffer A
authors.initials: JA
authors.lastname: Ajani
authors.forename: Ju-Seog
authors.initials: JS
authors.lastname: Lee
mesh_terms: D000230:Adenocarcinoma / Q000175:diagnosis / Q000235:genetics*; D000328:Adult; D000368:Aged; D014408:Biomarkers, Tumor / Q000235:genetics*; D016000:Cluster Analysis; D004938:Esophageal Neoplasms / Q000175:diagnosis / Q000235:genetics*; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data; D015676:Osteonectin / Q000235:genetics; D053495:Osteopontin / Q000235:genetics; D011379:Prognosis; D016016:Proportional Hazards Models; D020133:Reverse Transcriptase Polymerase Chain Reaction
chemical_list: D014408:Biomarkers, Tumor; D015676:Osteonectin; C506895:SPP1 protein, human; D053495:Osteopontin