Bladder cancer (BC) is known as one of the most common malignancies in the world and it ranks just after prostate cancer in genitourinary malignancies [1]. It is reported that 75% of the primary tumors present as a non-muscle-invasive stage Ta or T1 tumor while other tumors show bladder muscle invasion in stages T2-4. Clinically, stage Ta BC is characterized by frequent recurrence after resection, up to 60% of patients [2]. Typically, within 8 to 10 years, one or more tumors will appear each year with no progression, but, as many as 25% of tumors will eventually develop an aggressive invasive phenotype [3].
In current, cystoscopy/biopsy is the gold standard for the BC detection of suspicious lesions. Unfortunately, 10–40% of malignancies were failed to be detected by this procedure. In addition, cystoscopy/biopsy it is not only invasive, painful and costly but also misses up to 15% of the papillary and up to 30% of the flat recurrences. On the other hand, although urine cytology possesses a high specificity, it lacks of sensitivity, particularly in low-risk tumors [4].
Recently, many researchers are committed to discovering better markers for disease diagnosis and prognosis by employing non-invasive methods to collect samples, such as urine sediments. Although the sensitivity of cytology has been improved by the addition of nuclear matrix protein 22 (NMP-22), bladder tumor antigen, or UroVysion FISH, the proposed markers have been rarely adopted in clinical practice due to their limited specificity or sensitivity[1, 5, 6].
DNA methylation plays an important role in transcription regulation [7, 8]. It has been found that the changes in DNA methylation are chemically stable and can be accurate quantified, making them competitive candidates as tumor markers [9, 10]. Inactivation of tumor suppressor genes by gain of DNA methylation (hypermethylation) or global loss of DNA methylation (hypomethylation), activating genes that were normally not expressed, had been both observed in bladder tumors [11–13]. Further studies also demonstrated methylation changes found in urine sediments reflected those found in tumor tissues [14–16]. Reduced representation bisulfite sequencing (RRBS) has become increasingly for analysis of genome-wide methylation profiles with single nucleotide precision. One of the main goals for RRBS study is to discover differentially methylated regions (DMRs) between different biological conditions.
In last decades, more and more DNA methylation markers had been found for BC detection and these proposed markers were evaluated with different methods such as MS-MLPA, quantitative methylation-specific PCR (qMSP) and pyrosequencing. However, in most cases, the performance of marker panels were not satisfying with sensitivity in the range of 44%-90% and specificity varying from 31–94% (Table 1). Thus, it is still urgently to seek a reliable DNA methylation marker set operating on a low-cost platform with high sensitivity and specificity for BC detection.
Table 1
Reviewed panels for bladder cancer detection
ID
|
Gene Panel
|
Method
|
AUC
|
AC
|
SP
|
SN
|
ref
|
1
|
TIMP3,APC,CDKN2A,MLH1,ATM,RARB, CDKN2B,HIC1,CHFR,BRCA1,CASP8,CDKN1B, PTEN,BRCA2,CD44,RASSF1,DAPK1,FHIT,VHL, ESR1,TP73,IGSF4,GSTP1,CDH13
|
MS-MLPA
|
-
|
-
|
-
|
-
|
[17]
|
2
|
HIC1,RASSF1,GSTP1
|
MS-MLPA
|
0.696
|
0.72
|
0.66
|
0.78
|
[17]
|
3
|
HOXA9,ISL1
|
qMSP
|
-
|
-
|
0.91
|
0.44
|
[18]
|
4
|
PCDH17,POU4F2
|
qMSP
|
-
|
-
|
0.94
|
0.90
|
[19]
|
5
|
E2F3,CCND1,UTP6,CDADC1,SLC35E3,METRNL,TPCN2, NACC2,VGLL4,PTEN
|
metadata
|
-
|
-
|
-
|
-
|
[20]
|
6
|
CDH13,CFTR,NID2,SALL3,TMEFF2,TWIST1,VIM2
|
pyrosequencing
|
-
|
-
|
-
|
-
|
[21]
|
7
|
CFTR,SALL3,TWIST1
|
pyrosequencing
|
0.741
|
-
|
0.31
|
0.90
|
[21]
|
*AUC: area under ROC curve, AC: accuracy, SP: specificity, SN: sensitivity |
In this study, we aimed to develop a reliable DNA methylation panel for early BC detection in clinical practise. We composed an improved urine DNA methylation panel based on other published methylation panels. This newly proposed panel was compared with published panels using RRBS and the panel performance was further applied to clinical diagnosis with qMSP and systematically evaluated.