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Prognostic Biomarkers for Esophageal Adenocarcinoma Identified by Analysis of Tumor Transcriptome

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...

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Autores principales: Kim, Soo Mi, Park, Yun-Yong, Park, Eun Sung, Cho, Jae Yong, Izzo, Julie G., Zhang, Di, Kim, Sang-Bae, Lee, Jeffrey H., Bhutani, Manoop S., Swisher, Stephen G., Wu, Xifeng, Coombes, Kevin R., Maru, Dipen, Wang, Kenneth K., Buttar, Navtej S., Ajani, Jaffer A., Lee, Ju-Seog
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2994829/
https://www.ncbi.nlm.nih.gov/pubmed/21152079
http://dx.doi.org/10.1371/journal.pone.0015074
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author Kim, Soo Mi
Park, Yun-Yong
Park, Eun Sung
Cho, Jae Yong
Izzo, Julie G.
Zhang, Di
Kim, Sang-Bae
Lee, Jeffrey H.
Bhutani, Manoop S.
Swisher, Stephen G.
Wu, Xifeng
Coombes, Kevin R.
Maru, Dipen
Wang, Kenneth K.
Buttar, Navtej S.
Ajani, Jaffer A.
Lee, Ju-Seog
author_facet Kim, Soo Mi
Park, Yun-Yong
Park, Eun Sung
Cho, Jae Yong
Izzo, Julie G.
Zhang, Di
Kim, Sang-Bae
Lee, Jeffrey H.
Bhutani, Manoop S.
Swisher, Stephen G.
Wu, Xifeng
Coombes, Kevin R.
Maru, Dipen
Wang, Kenneth K.
Buttar, Navtej S.
Ajani, Jaffer A.
Lee, Ju-Seog
author_sort Kim, Soo Mi
collection PubMed
description 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.
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spelling pubmed-29948292010-12-10 Prognostic Biomarkers for Esophageal Adenocarcinoma Identified by Analysis of Tumor Transcriptome Kim, Soo Mi Park, Yun-Yong Park, Eun Sung Cho, Jae Yong Izzo, Julie G. Zhang, Di Kim, Sang-Bae Lee, Jeffrey H. Bhutani, Manoop S. Swisher, Stephen G. Wu, Xifeng Coombes, Kevin R. Maru, Dipen Wang, Kenneth K. Buttar, Navtej S. Ajani, Jaffer A. Lee, Ju-Seog PLoS One Research Article 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. Public Library of Science 2010-11-30 /pmc/articles/PMC2994829/ /pubmed/21152079 http://dx.doi.org/10.1371/journal.pone.0015074 Text en Kim et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Kim, Soo Mi
Park, Yun-Yong
Park, Eun Sung
Cho, Jae Yong
Izzo, Julie G.
Zhang, Di
Kim, Sang-Bae
Lee, Jeffrey H.
Bhutani, Manoop S.
Swisher, Stephen G.
Wu, Xifeng
Coombes, Kevin R.
Maru, Dipen
Wang, Kenneth K.
Buttar, Navtej S.
Ajani, Jaffer A.
Lee, Ju-Seog
Prognostic Biomarkers for Esophageal Adenocarcinoma Identified by Analysis of Tumor Transcriptome
title Prognostic Biomarkers for Esophageal Adenocarcinoma Identified by Analysis of Tumor Transcriptome
title_full Prognostic Biomarkers for Esophageal Adenocarcinoma Identified by Analysis of Tumor Transcriptome
title_fullStr Prognostic Biomarkers for Esophageal Adenocarcinoma Identified by Analysis of Tumor Transcriptome
title_full_unstemmed Prognostic Biomarkers for Esophageal Adenocarcinoma Identified by Analysis of Tumor Transcriptome
title_short Prognostic Biomarkers for Esophageal Adenocarcinoma Identified by Analysis of Tumor Transcriptome
title_sort prognostic biomarkers for esophageal adenocarcinoma identified by analysis of tumor transcriptome
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2994829/
https://www.ncbi.nlm.nih.gov/pubmed/21152079
http://dx.doi.org/10.1371/journal.pone.0015074
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