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Expression signature of E2F1 and its associated genes predict superficial to invasive progression of bladder tumors

Authors
 Ju-Seog Lee  ;  Sun-Hee Leem  ;  Sang-Yeop Lee  ;  Sang-Cheol Kim  ;  Eun-Sung Park  ;  Sang-Bae Kim  ;  Seon-Kyu Kim  ;  Yong-June Kim  ;  Wun-Jae Kim  ;  In-Sun Chu 
Citation
 JOURNAL OF CLINICAL ONCOLOGY, Vol.28(16) : 2660-2667, 2010 
Journal Title
JOURNAL OF CLINICAL ONCOLOGY
ISSN
 0732-183X 
Issue Date
2010
MeSH
Adult ; Aged ; Aged, 80 and over ; Analysis of Variance ; Biopsy, Needle ; Carcinoma, Transitional Cell/genetics* ; Carcinoma, Transitional Cell/mortality ; Carcinoma, Transitional Cell/pathology ; Carcinoma, Transitional Cell/surgery ; Cohort Studies ; Cystoscopy/methods ; Disease Progression ; E2F2 Transcription Factor/genetics* ; E2F2 Transcription Factor/metabolism ; Female ; Gene ExpressionProfiling* ; Gene ExpressionRegulation, Neoplastic/genetics ; Humans ; Immunohistochemistry ; Male ; Middle Aged ; Multivariate Analysis ; Neoplasm Invasiveness/pathology* ; Neoplasm Staging ; Predictive Value of Tests ; Proportional Hazards Models ; RNA, Neoplasm/genetics ; Retrospective Studies ; Risk Assessment ; Survival Analysis ; Urinary Bladder Neoplasms/genetics* ; Urinary Bladder Neoplasms/mortality ; Urinary Bladder Neoplasms/pathology ; Urinary Bladder Neoplasms/surgery ; Young Adult
Abstract
PURPOSE: In approximately 20% of patients with superficial bladder tumors, the tumors progress to invasive tumors after treatment. Current methods of predicting the clinical behavior of these tumors prospectively are unreliable. We aim to identify a molecular signature that can reliably identify patients with high-risk superficial tumors that are likely to progress to invasive tumors.

PATIENTS AND METHODS: Gene expression data were collected from tumor specimens from 165 patients with bladder cancer. Various statistical methods, including leave-one-out cross-validation methods, were applied to identify a gene expression signature that could predict the likelihood of progression to invasive tumors and to test the robustness of the expression signature in an independent cohort. The robustness of the gene expression signature was validated in an independent (n = 353) cohort.

RESULTS: Supervised analysis of gene expression data revealed a gene expression signature that is strongly associated with invasive bladder tumors. A molecular classifier based on this gene expression signature correctly predicted the likelihood of progression of superficial tumor to invasive tumor.

CONCLUSION: We present a molecular signature that can predict, at diagnosis, the likelihood of bladder cancer progression and, possibly, lead to improvements in patient therapy
Full Text
http://jco.ascopubs.org/content/28/16/2660.long
DOI
10.1200/JCO.2009.25.0977
Appears in Collections:
1. College of Medicine (의과대학) > Research Institute (부설연구소) > 1. Journal Papers
Yonsei Authors
Park, Eun Sung(박은성)
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/103084
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