Prognostic Biomarkers for Esophageal Adenocarcinoma Identified by Analysis of Tumor Transcriptome

被引:116
作者
Kim, Soo Mi [1 ,8 ]
Park, Yun-Yong [1 ]
Park, Eun Sung [1 ]
Cho, Jae Yong [1 ]
Izzo, Julie G. [2 ]
Zhang, Di [3 ]
Kim, Sang-Bae [1 ]
Lee, Jeffrey H. [4 ]
Bhutani, Manoop S. [4 ]
Swisher, Stephen G. [6 ]
Wu, Xifeng [3 ]
Coombes, Kevin R. [5 ]
Maru, Dipen [4 ]
Wang, Kenneth K. [7 ]
Buttar, Navtej S. [7 ]
Ajani, Jaffer A. [4 ]
Lee, Ju-Seog [1 ]
机构
[1] Univ Texas MD Anderson Canc Ctr, Dept Syst Biol, Houston, TX 77030 USA
[2] Univ Texas MD Anderson Canc Ctr, Dept Expt Therapeut, Houston, TX 77030 USA
[3] Univ Texas MD Anderson Canc Ctr, Dept Epidemiol, Houston, TX 77030 USA
[4] Univ Texas MD Anderson Canc Ctr, Dept Gastrointestinal Med Oncol, Houston, TX 77030 USA
[5] Univ Texas MD Anderson Canc Ctr, Dept Bioinformat & Computat Biol, Houston, TX 77030 USA
[6] Univ Texas MD Anderson Canc Ctr, Dept Pathol, Houston, TX 77030 USA
[7] Mayo Clin, Coll Med, Div Gastroenterol & Hepatol, Barrett Esophagus Unit, Rochester, MN USA
[8] Chonbuk Natl Univ Med Sch & Hosp, Dept Physiol, Jeonju, South Korea
来源
PLOS ONE | 2010年 / 5卷 / 11期
基金
美国国家卫生研究院;
关键词
HEPATOCELLULAR-CARCINOMA; MATRICELLULAR PROTEIN; EXPRESSION; SPARC; SURVIVAL; CANCER; OSTEOPONTIN; PROGRESSION; MATRIX; GROWTH;
D O I
10.1371/journal.pone.0015074
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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 < 0.024) in the multivariate Cox hazard regression analysis. Conclusions/Significance: 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.
引用
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页数:8
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