Journal Article

Prognostic Biomarkers for Esophageal Adenocarcinoma Identified by Analysis of Tumor Transcriptome

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

2010

Overview

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. 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. 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.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Adenocarcinoma / Adenocarcinoma - diagnosis / Adenocarcinoma - genetics / Adult / Aged / Bioindicators / Bioinformatics / Biological markers / Biology / Biomarkers / Biomarkers, Tumor - genetics / Biopsy / Cancer patients / Cell growth / Chemoradiotherapy / Cluster Analysis / Deoxyribonucleic acid / Development and progression / DNA / DNA microarrays / Endoscopes / Epidemiology / Esophageal cancer / Esophageal Neoplasms - diagnosis / Esophageal Neoplasms - genetics / Esophagus / Extracellular matrix / Female / Formaldehyde / Gastroenterology / Gene expression / Gene Expression Profiling / Genes / Genomes / Genomics / Hepatology / Humans / Kaplan-Meier Estimate / Male / Medical prognosis / Medicine / Metastasis / Middle Aged / Multivariate Analysis / Oligonucleotide Array Sequence Analysis - statistics & numerical data / Oncology / Osteonectin - genetics / Osteopontin - genetics / Paraffin / Patients / Polymerase chain reaction / Pretreatment / Prognosis / Proportional Hazards Models / Prostate / Proteins / Regression analysis / Reverse Transcriptase Polymerase Chain Reaction / Statistical analysis / Statistical methods / Subgroups / Surgery / Tissues / Tumors