TY - JOUR
T1 - Detection of bladder cancer using novel DNA methylation biomarkers in urine sediments
AU - Chung, Woonbok
AU - Bondaruk, Jolanta
AU - Jelinek, Jaroslav
AU - Lotan, Yair
AU - Liang, Shoudan
AU - Czerniak, Bogdan
AU - Issa, Jean Pierre J
PY - 2011/7
Y1 - 2011/7
N2 - Background: Bladder cancer (BCa) remains a lethal malignancy that can be cured if detected early. DNA hypermethylation is a common epigenetic abnormality in cancer that may serve as a marker of disease activity. Methods: We selected 10 novel candidate genes from the most frequently hypermethylated genes detected by DNA microarray and bisulfite pyrosequencing of bladder cancers and applied them to detect bladder cancer in urine sediments. We analyzed DNA methylation in the candidate genes by quantitative methylation-specific real-time PCR (qMSP) to detect bladder cancer in urine sediments from 128 bladder cancer patients and 110 age-matched control subjects. Results: Based on a multigene predictive model, we discovered 6 methylation markers (MYO3A, CA10, SOX11, NKX6-2, PENK, and DBC1) as most promising for detecting bladder cancer. A panel of 4 genes (MYO3A, CA10, NKX6-2, and DBC1 or SOX11) had 81% sensitivity and 97% specificity, whereas a panel of 5 genes (MYO3A, CA10, NKX6-2, DBC1, and SOX11 or PENK) had 85% sensitivity and 95% specificity for detection of bladder cancer (area under curve = 0.939). By analyzing the data by cancer invasiveness, detection rate was 47 of 58 (81%) in non-muscle invasive tumors (pTa, Tis, and pT1) and 62 of 70 (90%) in muscle invasive tumors (T2, T3, and T4). Conclusions: This biomarker panel analyzed by qMSP may help the early detection of bladder tumors in urine sediments with high accuracy. Impact: The panel of biomarker deserves validation in a large well-controlled prospectively collected sample set.
AB - Background: Bladder cancer (BCa) remains a lethal malignancy that can be cured if detected early. DNA hypermethylation is a common epigenetic abnormality in cancer that may serve as a marker of disease activity. Methods: We selected 10 novel candidate genes from the most frequently hypermethylated genes detected by DNA microarray and bisulfite pyrosequencing of bladder cancers and applied them to detect bladder cancer in urine sediments. We analyzed DNA methylation in the candidate genes by quantitative methylation-specific real-time PCR (qMSP) to detect bladder cancer in urine sediments from 128 bladder cancer patients and 110 age-matched control subjects. Results: Based on a multigene predictive model, we discovered 6 methylation markers (MYO3A, CA10, SOX11, NKX6-2, PENK, and DBC1) as most promising for detecting bladder cancer. A panel of 4 genes (MYO3A, CA10, NKX6-2, and DBC1 or SOX11) had 81% sensitivity and 97% specificity, whereas a panel of 5 genes (MYO3A, CA10, NKX6-2, DBC1, and SOX11 or PENK) had 85% sensitivity and 95% specificity for detection of bladder cancer (area under curve = 0.939). By analyzing the data by cancer invasiveness, detection rate was 47 of 58 (81%) in non-muscle invasive tumors (pTa, Tis, and pT1) and 62 of 70 (90%) in muscle invasive tumors (T2, T3, and T4). Conclusions: This biomarker panel analyzed by qMSP may help the early detection of bladder tumors in urine sediments with high accuracy. Impact: The panel of biomarker deserves validation in a large well-controlled prospectively collected sample set.
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U2 - 10.1158/1055-9965.EPI-11-0067
DO - 10.1158/1055-9965.EPI-11-0067
M3 - Article
C2 - 21586619
AN - SCOPUS:79960101746
SN - 1055-9965
VL - 20
SP - 1483
EP - 1491
JO - Cancer Epidemiology Biomarkers and Prevention
JF - Cancer Epidemiology Biomarkers and Prevention
IS - 7
ER -