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Predictive value of progression-related gene classifier in primary non-muscle invasive bladder cancer.

Kim WJ, Kim EJ, Kim SK, Kim YJ, Ha YS, Jeong P, Kim MJ, Yun SJ, Lee KM, Moon SK, Lee SC, Cha EJ, Bae SC - Mol. Cancer (2010)

Bottom Line: Furthermore, no patient with NMIBC in the good-prognosis signature group experienced cancer progression.We identified progression-related gene classifier that has strong predictive value for determining disease outcome in NMIBC.This gene classifier could assist in selecting NMIBC patients who might benefit from more aggressive therapeutic intervention or surveillance.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Urology, College of Medicine, Chungbuk National University, Chungbuk, South Korea. wjkim@chungbuk.ac.kr

ABSTRACT

Background: While several molecular markers of bladder cancer prognosis have been identified, the limited value of current prognostic markers has created the need for new molecular indicators of bladder cancer outcomes. The aim of this study was to identify genetic signatures associated with disease prognosis in bladder cancer.

Results: We used 272 primary bladder cancer specimens for microarray analysis and real-time reverse transcriptase polymerase chain reaction (RT-PCR) analysis. Microarray gene expression analysis of randomly selected 165 primary bladder cancer specimens as an original cohort was carried out. Risk scores were applied to stratify prognosis-related gene classifiers. Prognosis-related gene classifiers were individually analyzed with tumor invasiveness (non-muscle invasive bladder cancer [NMIBC] and muscle invasive bladder cancer [MIBC]) and prognosis. We validated selected gene classifiers using RT-PCR in the original (165) and independent (107) cohorts. Ninety-seven genes related to disease progression among NMIBC patients were identified by microarray data analysis. Eight genes, a progression-related gene classifier in NMIBC, were selected for RT-PCR. The progression-related gene classifier in patients with NMIBC was closely correlated with progression in both original and independent cohorts. Furthermore, no patient with NMIBC in the good-prognosis signature group experienced cancer progression.

Conclusions: We identified progression-related gene classifier that has strong predictive value for determining disease outcome in NMIBC. This gene classifier could assist in selecting NMIBC patients who might benefit from more aggressive therapeutic intervention or surveillance.

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Kaplan-Meier estimations in primary bladder cancer with gene signatures based on microarray analysis of the original training cohort. Kaplan-Meier curves of (A) recurrence (B) and progression in NMIBC. Kaplan-Meier curves of (C) progression, (D) cancer-specific survival and (E) overall survival in MIBC.
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Figure 3: Kaplan-Meier estimations in primary bladder cancer with gene signatures based on microarray analysis of the original training cohort. Kaplan-Meier curves of (A) recurrence (B) and progression in NMIBC. Kaplan-Meier curves of (C) progression, (D) cancer-specific survival and (E) overall survival in MIBC.

Mentions: Patients with NMIBC in the poor-prognosis signature group had a significantly shorter recurrence time than those in the good-prognosis signature group (P = 0.009; Fig. 3A). When we examined progression in NMIBC, the time to progression was shorter for patients with poor-prognosis signature than good-prognosis signature. Furthermore, none of the patients with good-prognosis signature were associated with progression (P < 0.001; Fig. 3B). Tumor progression, cancer-specific survival and overall survival in MIBC were significantly different between the two groups having good-, and poor-prognosis signatures, respectively (each P < 0.001; Fig. 3C-E).


Predictive value of progression-related gene classifier in primary non-muscle invasive bladder cancer.

Kim WJ, Kim EJ, Kim SK, Kim YJ, Ha YS, Jeong P, Kim MJ, Yun SJ, Lee KM, Moon SK, Lee SC, Cha EJ, Bae SC - Mol. Cancer (2010)

Kaplan-Meier estimations in primary bladder cancer with gene signatures based on microarray analysis of the original training cohort. Kaplan-Meier curves of (A) recurrence (B) and progression in NMIBC. Kaplan-Meier curves of (C) progression, (D) cancer-specific survival and (E) overall survival in MIBC.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2821358&req=5

Figure 3: Kaplan-Meier estimations in primary bladder cancer with gene signatures based on microarray analysis of the original training cohort. Kaplan-Meier curves of (A) recurrence (B) and progression in NMIBC. Kaplan-Meier curves of (C) progression, (D) cancer-specific survival and (E) overall survival in MIBC.
Mentions: Patients with NMIBC in the poor-prognosis signature group had a significantly shorter recurrence time than those in the good-prognosis signature group (P = 0.009; Fig. 3A). When we examined progression in NMIBC, the time to progression was shorter for patients with poor-prognosis signature than good-prognosis signature. Furthermore, none of the patients with good-prognosis signature were associated with progression (P < 0.001; Fig. 3B). Tumor progression, cancer-specific survival and overall survival in MIBC were significantly different between the two groups having good-, and poor-prognosis signatures, respectively (each P < 0.001; Fig. 3C-E).

Bottom Line: Furthermore, no patient with NMIBC in the good-prognosis signature group experienced cancer progression.We identified progression-related gene classifier that has strong predictive value for determining disease outcome in NMIBC.This gene classifier could assist in selecting NMIBC patients who might benefit from more aggressive therapeutic intervention or surveillance.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Urology, College of Medicine, Chungbuk National University, Chungbuk, South Korea. wjkim@chungbuk.ac.kr

ABSTRACT

Background: While several molecular markers of bladder cancer prognosis have been identified, the limited value of current prognostic markers has created the need for new molecular indicators of bladder cancer outcomes. The aim of this study was to identify genetic signatures associated with disease prognosis in bladder cancer.

Results: We used 272 primary bladder cancer specimens for microarray analysis and real-time reverse transcriptase polymerase chain reaction (RT-PCR) analysis. Microarray gene expression analysis of randomly selected 165 primary bladder cancer specimens as an original cohort was carried out. Risk scores were applied to stratify prognosis-related gene classifiers. Prognosis-related gene classifiers were individually analyzed with tumor invasiveness (non-muscle invasive bladder cancer [NMIBC] and muscle invasive bladder cancer [MIBC]) and prognosis. We validated selected gene classifiers using RT-PCR in the original (165) and independent (107) cohorts. Ninety-seven genes related to disease progression among NMIBC patients were identified by microarray data analysis. Eight genes, a progression-related gene classifier in NMIBC, were selected for RT-PCR. The progression-related gene classifier in patients with NMIBC was closely correlated with progression in both original and independent cohorts. Furthermore, no patient with NMIBC in the good-prognosis signature group experienced cancer progression.

Conclusions: We identified progression-related gene classifier that has strong predictive value for determining disease outcome in NMIBC. This gene classifier could assist in selecting NMIBC patients who might benefit from more aggressive therapeutic intervention or surveillance.

Show MeSH
Related in: MedlinePlus