Prognostic Biomarkers for Esophageal Adenocarcinoma Identified by Analysis of Tumor Transcriptome

Soo Mi Kim, Yun-Yong Park, Eun Sung Park, Jae Yong Cho, Julie G Izzo, Di Zhang, Sang-Bae Kim, Jeffrey H Lee, Manoop S Bhutani, Stephen G Swisher, Xifeng Wu, Kevin R Coombes, Dipen Maru, Kenneth K Wang, Navtej S Buttar, Jaffer A Ajani and Ju-Seog Lee

PLOS ONE, 2010, vol. 5, issue 11, 1-8

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. Methodology/Principal Findings: 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

Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0015074

DOI: 10.1371/journal.pone.0015074

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