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Generation Of A Concise Gene Panel For Outcome Prediction In Urinary Bladder Cancer.
A. P. Mitra, V. Pagliarulo, D. Yang, F. Waldman, R. Datar, D. Skinner, S. Groshen, R. Cote
Published 2009 · Biology, Medicine
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PURPOSE This study sought to determine if alterations in molecular pathways could supplement TNM staging to more accurately predict clinical outcome in patients with urothelial carcinoma (UC). PATIENTS AND METHODS Expressions of 69 genes involved in known cancer pathways were quantified on bladder specimens from 58 patients with UC (stages Ta-T4) and five normal urothelium controls. All tumor transcript values beyond two standard deviations from the normal mean expression were designated as over- or underexpressed. Univariate and multivariable analyses were conducted to obtain a predictive expression signature. A published external data set was used to confirm the potential of the prognostic gene panels. RESULTS In univariate analysis, six genes were significantly associated with time to recurrence, and 10 with overall survival. Recursive partitioning identified three genes as significant determinants for recurrence, and three for overall survival. Of all genes identified by either univariate or partitioning analysis, four were found to significantly predict both recurrence and survival (JUN, MAP2K6, STAT3, and ICAM1); overexpression was associated with worse outcome. Comparing the favorable (low or normal) expression of > or = three of four versus < or = two of four of these oncogenes showed 5-year recurrence probability of 41% versus 88%, respectively (P < .001), and 5-year overall survival probability of 61% versus 5%, respectively (P < .001). The prognostic potential of this four-gene panel was confirmed in a large independent external cohort (disease-specific survival, P = .039). CONCLUSION We have documented the generation of a concise, biologically relevant four-gene panel that significantly predicts recurrence and survival and may also identify potential therapeutic targets for UC.
This paper references
Analysis of matched mRNA measurements from two different microarray technologies
W. Kuo (2002)
Molecular staging of bladder cancer
A. P. Mitra (2005)
Early detection of lung cancer: role of biomarkers
C. Brambilla (2003)
p53, p21, pRB, and p16 expression predict clinical outcome in cystectomy with bladder cancer.
S. Shariat (2004)
BCL2 expression predicts survival in patients receiving synchronous chemoradiotherapy in advanced transitional cell carcinoma of the bladder.
S. Hussain (2003)
Bladder Cancer Outcome and Subtype Classification by Gene Expression
E. Blaveri (2005)
The use of genetic programming in the analysis of quantitative gene expression profiles for identification of nodal status in bladder cancer
A. P. Mitra (2006)
Expression measurement of many genes simultaneously by quantitative RT-PCR using standardized mixtures of competitive templates.
J. Willey (1998)
Novel targets for the 18p11.3 amplification frequently observed in esophageal squamous cell carcinomas.
K. Nakakuki (2002)
Requirement of STAT3 activation for maximal collagenase-1 (MMP-1) induction by epidermal growth factor and malignant characteristics in T24 bladder cancer cells
M. Itoh (2006)
R. G. Miller (1981)
Gene expression profiles identify a role for cyclooxygenase 2-dependent prostanoid generation in BMP6-induced angiogenic responses.
R. Ren (2007)
A genetic explanation of Slaughter's concept of field cancerization: evidence and clinical implications.
B. J. Braakhuis (2003)
Do cytogenetic abnormalities precede morphologic abnormalities in a developing malignant condition?
J. Northup (2007)
TUTORIAL IN BIOSTATISTICS MULTIVARIABLE PROGNOSTIC MODELS: ISSUES IN DEVELOPING MODELS, EVALUATING ASSUMPTIONS AND ADEQUACY, AND MEASURING AND REDUCING ERRORS
K. Lee (1996)
Sensitivity and reproducibility of standardized-competitive RT-PCR for transcript quantification and its comparison with real time RT-PCR
V. Pagliarulo (2003)
c-jun oncogene expression in transitional cell carcinoma of the urinary bladder.
D. Tiniakos (1994)
A note on two problems in connexion with graphs
E. Dijkstra (1959)
Bootstrap investigation of the stability of a Cox regression model.
D. Altman (1989)
Differential expression of bcl-2 family proteins in bladder carcinomas. Relationship with apoptotic rate and survival.
P. Korkolopoulou (2002)
Superoxide dismutase, catalase, and glutathione peroxidase in red blood cells from patients with malignant diseases.
R. Gonzales (1984)
Differential susceptibility to TRAIL of normal versus malignant human urothelial cells
L. Steele (2006)
A new look at the statistical model identification
H. Akaike (1974)
Microarray analyses in bladder cancer cells: Inhibition of hTERT expression down‐regulates EGFR
K. Kraemer (2006)
Classification and Regression Trees
L. Breiman (1983)
Susceptibility genes: GSTM1 and GSTM3 as genetic risk factors in bladder cancer
E. Schnakenberg (2000)
Combined effects of p53, p21, and pRb expression in the progression of bladder transitional cell carcinoma.
S. Chatterjee (2004)
Plasma levels of insulin-like growth factor-1 and binding protein-3, and their association with bladder cancer risk.
H. Zhao (2003)
Molecular pathways in invasive bladder cancer: new insights into mechanisms, progression, and target identification.
A. P. Mitra (2006)
The bootstrap and identification of prognostic factors via Cox's proportional hazards regression model.
C. H. Chen (1985)
A comparison of two simple hazard ratio estimators based on the logrank test.
T. Sato (1992)
Defining molecular profiles of poor outcome in patients with invasive bladder cancer using oligonucleotide microarrays.
M. Sánchez-Carbayo (2006)
Prediction of recurrence in Ta urothelial cell carcinoma by real‐time quantitative PCR analysis: A microarray validation study
I. Schultz (2006)
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P. L. Ho (2012)
Genetic variation in the GSTM3 promoter confer risk and prognosis of renal cell carcinoma by reducing gene expression
X. Tan (2013)
S100A9 and EGFR gene signatures predict disease progression in muscle invasive bladder cancer patients after chemotherapy.
W. Kim (2014)
Prediction of Stage, Grade, and Survival in Bladder Cancer Using Genome-wide Expression Data: A Validation Study
Martin Lauss (2010)
Molecular diagnostics in urologic malignancies: a work in progress.
G. Netto (2011)
GSTM3 and GSTP1: novel players driving tumor progression in cervical cancer
Alberto Checa-Rojas (2018)
Glutathione S-Transferase Mu-3 Predicts a Better Prognosis and Inhibits Malignant Behavior and Glycolysis in Pancreatic Cancer
Shunda Wang (2020)
Stat3 activation in urothelial stem cells leads to direct progression to invasive bladder cancer.
P. L. Ho (2012)
Imaging , Diagnosis , Prognosis Combination of a Novel Gene Expression Signature with a Clinical Nomogram Improves the Prediction of Survival in High-Risk Bladder Cancer
M. Riester (2012)
The prognostic value of FGFR3 mutational status for disease recurrence and progression depends on allelic losses at 9p22.
G. Ploussard (2011)
Sphingosine-1-phosphate receptor 1 (S1PR1) expression in non-muscle invasive urothelial carcinoma: Association with poor clinical outcome and potential therapeutic target.
H. Go (2015)
Prognostic value of cell-cycle regulation biomarkers in bladder cancer.
A. P. Mitra (2012)
PRACTICAL & CONTROVERSIAL ISSUES IN DIAGNOSIS , GRADING AND STAGING OF UROTHELIAL CARCINOMA : AN APPROACH
M. Amin (2011)
Neoadjuvant Chemotherapy for Invasive Bladder Cancer
G. Sonpavde (2012)
Molecular signatures that predict nodal metastasis in bladder cancer: does the primary tumor tell tales?
A. P. Mitra (2011)
Grade progression in urothelial carcinoma can occur with high or low mutational homology: a first-step toward tumor-specific care in initial low-grade bladder cancer
R. Kittler (2018)
Radiomics Signature: A Potential Biomarker for the Prediction of Disease-Free Survival in Early-Stage (I or II) Non-Small Cell Lung Cancer.
Yanqi Huang (2016)
The Relationship between the Intercellular Adhesion Molecule-1 Expression and the Response to BCG Immunotherapy in Non Muscle Invasive Bladder Cancer
Faouzia Ajili (2014)
Emerging personalized approaches for the management of advanced urothelial carcinoma
C. Tsao (2012)
Roles of Signal Transducer Pathways in Investigation of Biopsies from Patients with Bladder Tumors
A. Bayrak (2017)
Molecular genetics and genomics progress in urothelial bladder cancer.
G. Netto (2013)
Tyrosine Kinase ETK/BMX Is Up-Regulated in Bladder Cancer and Predicts Poor Prognosis in Patients with Cystectomy
S. Guo (2011)
Expression profiling for bladder cancer: strategies to uncover prognostic factors
G. Bartsch (2010)
Development and External Validation of a Novel 12-Gene Signature for Prediction of Overall Survival in Muscle-Invasive Bladder Cancer
M. Abudurexiti (2019)
Three differentiation states risk-stratify bladder cancer into distinct subtypes
Jens-Peter Volkmer (2012)
Second-line systemic therapy and emerging drugs for metastatic transitional-cell carcinoma of the urothelium.
G. Sonpavde (2010)
Molecular Pathology of Bladder Cancer
L. Cheng (2012)
Prediction of recurrence of non muscle‐invasive bladder cancer by means of a protein signature identified by antibody microarray analyses
H. Srinivasan (2014)
Role of STAT3 and FOXO1 in the Divergent Therapeutic Responses of Non-metastatic and Metastatic Bladder Cancer Cells to miR-145
Guosong Jiang (2017)
EZH2 in Bladder Cancer, a Promising Therapeutic Target
M. Martinez-Fernandez (2015)
Development of prognostic signatures for intermediate-risk papillary thyroid cancer
K. Brennan (2016)
Potential Role for Targeted Therapy in Muscle-Invasive Bladder Cancer from the Cancer Genome
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