Identification of a novel set of DNA methylation markers in bladder cancer using MBD-methylCap/seq and urine DNA screening in a Chinese population
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE33839 | GEO | 2012/05/01
SECONDARY ACCESSION(S): PRJNA148095
REPOSITORIES: GEO
Similar Datasets
Project description:The aim of the present study was to identify novel DNA methylation markers in bladder cancer (BCa) through genome-wide profiling of bladder cancer cell lines and subsequent MSP screening in urine samples. Experimental Design: MBD methylCap/seq was carried out to screen differentially methylated CpG islands using two BCa cell lines (5637 and T24) and two normal bladder mucosa (BM) samples. The top one hundred most hypermethylated targets were screened using Methylation Specific PCR (MSP) in small and big cohort of urine samples from BCa patients and normal controls. The diagnostic performance of the gene panel was further evaluated in different clinical scenarios. Results: In total, 1,627 gene promoter regions hypermethylated in BCa cell line were identified in genomic level methylation profiling. The followed screening procedure in clinical urine sample generated eight genes (VAX1, KCNV1, ECEL1, TMEM26, TAL1, PROX1, SLC6A20, and LMX1A) capable of differentiating BCa from normal control. Subsequent validation in a large sample size enabled the optimisation of 5 methylation targets (VAX1, KCNV1, TAL1, PPOX1 and CFTR) for BCa diagnosis with sensitivity and specificity of 86.32% and 87.13%, respectively. In addition, VAX1 and LMX1A methylation could predict the tumour recurrence. Conclusions: Tumor specific biomarkers of BCa could be established by first performing genome level methylation profiling with cell lines and then screening the potential targets in urine samples. The panel of methylated genes identified was promising for the early non-invasive detection and surveillance of BCa. MBD methylCap/seq was carried out to screen differentially methylated CpG islands using two BCa cell lines (5637 and T24), and two normal bladder tissue mix as control.
2012-04-30 | E-GEOD-33839 | biostudies-arrayexpress
Project description:Urine is an ideal material to study and examine the bladder cancer (BCa) biomarkers, whereas exploration to the corresponding protein candidates is confronting technique challenges. Herein, we proposed a comprehensive strategy of searching the urine proteins related to BCa. The strategy consists of three core combinations, screening the candidates in the secreted proteins derived from the BCa cell lines and verifying them in the patient urines, defining the differential proteins through two-dimensional electrophoresis (2DE) and isobaric tags for relative and absolute quantitation (iTRAQ), and implementing quantitative analysis in profiling and targeting proteomics. The differential proteins were globally and quantitatively determined between the two typical cell lines of BCa, T24 and 5637, and the immortalized normal uroepithelium cell line, SV-HUC-1, while the BCa related proteins were verified between the relatively normal and patient urines. With proteomic survey combined with 2DE and iTRAQ, a total of 724 secreted proteins were identified as the BCa related proteins. With label-free quantitative proteomics, the 96 candidates were detected in the pooled urine samples. Furthermore, the multiple reaction monitoring (MRM)-based quantification was adapted to verify these urine proteins in individual urines that were collected from 23 BCa patients and 24 relative normal people, and resulted in the 10 urine proteins with significant abundance differences between the two groups. Of the potential indicators for BCa, analysis of receiver operating characteristics (ROC) revealed the combination of complement component 3 (CO3) and lactose dehydrogenase B (LDHB) was more sensitive and efficient to distinguish healthy and disease urine. The discovery of the indicative proteins of BCa through our strategy has thus paved an avenue to further validation of BCa biomarkers in urine.
2016-06-17 | PXD003557 | Pride
Project description:Renal cell carcinoma (RCC), particularly clear cell RCC (ccRCC), is the most common type of kidney tumors characterized by the highest mortality rate of the genitourinary cancers. Lack of symptoms leads to late detection of the disease using conventional imagining procedures. There is an urgent need for new diagnostic biomarkers with the potential for early detection and prediction of high risk of progression. In the present study, based on microarray profiling of DNA methylation in 11 pairs of ccRCC and noncancerous renal tissues (NRT), the methylation at regulatory regions of six putative ccRCC biomarkers was further analyzed in 123 ccRCC and 45 NRT samples by means of methylation specific PCR (MSP). Thereafter, the quantitative MSP was applied for the methylation analysis in the urine samples of 123 ccRCC patients and 93 asymptomatic controls (ASC). The comparison of ccRCC and NRT samples revealed significant methylation differences in 1319 genes, of which 191 were hypermethylated and 1128 were hypomethylated. DNA methylation of selected genes were validated by means of MSP and significantly higher methylation frequencies for all genes was found in ccRCC tissues compared to NRT (33-60% vs. 0-11%). Methylated status of at least one gene was significantly related with various adverse clinical-pathological parameters of the patients, including larger tumor size, higher tumor pathological stage, grade, intravascular and fat invasion as welll as tumor necrosis. The multivariate Cox regression model revealed the methylation in a panel of selected three genes as independent prognostic biomarker of ccRCC. Moreover, five genes were characterised by higher methylation intensity in the urine samples of ccRCC patients, as compared to ASC, and various combination of these biomarkers revealed moderate-to-high sensitivity and specificity values for the diagnosis of ccRCC.
2021-02-15 | GSE166734 | GEO
Project description:Epigenetic modifications, such as aberrant DNA promoter methylation is frequently observed in cervical cancer. Identification of hypermethylated regions maybe useful for discrimination between normal cervical epithelium and high-grade cervical intraepithelial neoplasia (CIN2/3) or worse may improve current cervical cancer population-based screening programs. In this study, the DNA methylome of high-grade CIN lesions were characterised using genome-wide methylation screening to identify potential biomarkers for early diagnosis of cervical neoplasia. Methyl-DNA Immunoprecipitation (MeDIP) combined with DNA microarray was used to compare DNA methylation profiles of epithelial cells derived from high-grade CIN lesions with normal cervical epithelium resulting in the identification of hypermethylated differentially methylated regions (DMRs). Validation of 9 selected DMRs by MSP or BSP in cervical tissue revealed methylation in 63.2-94.7% high-grade CIN and in 59.3-100% cervical carcinomas. QMSP for the two most significant high-grade CIN-specific methylation markers was applied exploring test performance in a large series of cervical scrapings. Frequency and relative level of methylation were significantly different between normal and cancer samples (p<0.001). Clinical validation of both markers in cervical scrapings from patients referred with an abnormal cervical smear, confirmed that frequency and relative level of methylation were related with increasing severity of the underlying CIN lesion (p<0.001) and the ROC analysis was discriminative (p<0.005). These possible methylation markers represent COL25A1 and KATNAL2 promoters and their observed increased methylation upon progression is in agreement with their biological function (cytoskeleton regulation). In conclusion, our newly identified hypermethylated DMRs represent specific DNA methylation patterns in high-grade CIN lesions and could be potential biomarkers for early detection. Epigenetic modifications, such as aberrant DNA promoter methylation is frequently observed in cervical cancer. Identification of hypermethylated regions maybe useful for discrimination between normal cervical epithelium and high-grade cervical intraepithelial neoplasia (CIN2/3) or worse may improve current cervical cancer population-based screening programs. In this study, the DNA methylome of high-grade CIN lesions were characterised using genome-wide methylation screening to identify potential biomarkers for early diagnosis of cervical neoplasia. Methyl-DNA Immunoprecipitation (MeDIP) combined with DNA microarray was used to compare DNA methylation profiles of epithelial cells derived from high-grade CIN lesions with normal cervical epithelium resulting in the identification of hypermethylated differentially methylated regions (DMRs). Validation of 9 selected DMRs by MSP or BSP in cervical tissue revealed methylation in 63.2-94.7% high-grade CIN and in 59.3-100% cervical carcinomas. QMSP for the two most significant high-grade CIN-specific methylation markers was applied exploring test performance in a large series of cervical scrapings. Frequency and relative level of methylation were significantly different between normal and cancer samples (p<0.001). Clinical validation of both markers in cervical scrapings from patients referred with an abnormal cervical smear, confirmed that frequency and relative level of methylation were related with increasing severity of the underlying CIN lesion (p<0.001) and the ROC analysis was discriminative (p<0.005). These possible methylation markers represent COL25A1 and KATNAL2 promoters and their observed increased methylation upon progression is in agreement with their biological function (cytoskeleton regulation). In conclusion, our newly identified hypermethylated DMRs represent specific DNA methylation patterns in high-grade CIN lesions and could be potential biomarkers for early detection. MeDIP with subsequent microarray analysis was performed on DNA isolated from frozen macrodissected epithelial tissue of CIN3 lesions (n=15) and normal cervices (n=10).
2012-11-01 | E-GEOD-36319 | biostudies-arrayexpress
Project description:To analyze the gene expression profiles of progressive and non-progressive T1G3 bladder cancer (BCa) patients in order to develop a gene expression signature to predict tumour progression. Multicenter, retrospective study of formalin-fixed paraffin embedded (FFPE) tissue samples from 96 T1G3 BCa patients who underwent a transurethral resection. Patients with concomitant CIS were excluded. Global gene expression patterns were analyzed in 21 selected samples from progressive and non-progressive T1G3 BCa patients using microarrays. Expression levels of 94 key genes selected from microarrays and from the literature were studied by quantitative PCR in an independent cohort of 75 samples from progressive and non-progressive T1G3 BCa patients. Univariate logistic regression was used to identify individual predictors. Progressive and non-progressive T1G3 BCa patients show different gene expression patterns. Identification of new genes associated with a high probability of tumour progression in combination with a robust, easy-to-use and reliable algorithm may contribute to tailor treatment and surveillance strategies in these patients. Transcriptomic profile from nine non-progressive and twelve progressive T1G3 bladder cancer FFPE samples
2016-07-29 | E-GEOD-57813 | biostudies-arrayexpress
Project description:Urine is an ideal material to study and examine the bladder cancer (BCa) biomarkers, whereas exploration to the corresponding protein candidates is confronting technique challenges. Herein, we proposed a comprehensive strategy of searching the urine proteins related to BCa. The strategy consists of three core combinations, screening the candidates in the secreted proteins derived from the BCa cell lines and verifying them in the patient urines, defining the differential proteins through two-dimensional electrophoresis (2DE) and isobaric tags for relative and absolute quantitation (iTRAQ), and implementing quantitative analysis in profiling and targeting proteomics. The differential proteins were globally and quantitatively determined between the two typical cell lines of BCa, T24 and 5637, and the immortalized normal uroepithelium cell line, SV-HUC-1, while the BCa related proteins were verified between the relatively normal and patient urines. With proteomic survey combined with 2DE and iTRAQ, a total of 724 secreted proteins were identified as the BCa related proteins. With label-free quantitative proteomics, the 96 candidates were detected in the pooled urine samples. Furthermore, the multiple reaction monitoring (MRM)-based quantification was adapted to verify these urine proteins in individual urines that were collected from 23 BCa patients and 24 relative normal people, and resulted in the 10 urine proteins with significant abundance differences between the two groups. Of the potential indicators for BCa, analysis of receiver operating characteristics (ROC) revealed the combination of complement component 3 (CO3) and lactose dehydrogenase B (LDHB) was more sensitive and efficient to distinguish healthy and disease urine. The discovery of the indicative proteins of BCa through our strategy has thus paved an avenue to further validation of BCa biomarkers in urine.
2017-03-28 | MSV000080696 | MassIVE
Project description:Epigenetic modifications, such as aberrant DNA promoter methylation is frequently observed in cervical cancer. Identification of hypermethylated regions maybe useful for discrimination between normal cervical epithelium and high-grade cervical intraepithelial neoplasia (CIN2/3) or worse may improve current cervical cancer population-based screening programs. In this study, the DNA methylome of high-grade CIN lesions were characterised using genome-wide methylation screening to identify potential biomarkers for early diagnosis of cervical neoplasia. Methyl-DNA Immunoprecipitation (MeDIP) combined with DNA microarray was used to compare DNA methylation profiles of epithelial cells derived from high-grade CIN lesions with normal cervical epithelium resulting in the identification of hypermethylated differentially methylated regions (DMRs). Validation of 9 selected DMRs by MSP or BSP in cervical tissue revealed methylation in 63.2-94.7% high-grade CIN and in 59.3-100% cervical carcinomas. QMSP for the two most significant high-grade CIN-specific methylation markers was applied exploring test performance in a large series of cervical scrapings. Frequency and relative level of methylation were significantly different between normal and cancer samples (p<0.001). Clinical validation of both markers in cervical scrapings from patients referred with an abnormal cervical smear, confirmed that frequency and relative level of methylation were related with increasing severity of the underlying CIN lesion (p<0.001) and the ROC analysis was discriminative (p<0.005). These possible methylation markers represent COL25A1 and KATNAL2 promoters and their observed increased methylation upon progression is in agreement with their biological function (cytoskeleton regulation). In conclusion, our newly identified hypermethylated DMRs represent specific DNA methylation patterns in high-grade CIN lesions and could be potential biomarkers for early detection. Epigenetic modifications, such as aberrant DNA promoter methylation is frequently observed in cervical cancer. Identification of hypermethylated regions maybe useful for discrimination between normal cervical epithelium and high-grade cervical intraepithelial neoplasia (CIN2/3) or worse may improve current cervical cancer population-based screening programs. In this study, the DNA methylome of high-grade CIN lesions were characterised using genome-wide methylation screening to identify potential biomarkers for early diagnosis of cervical neoplasia. Methyl-DNA Immunoprecipitation (MeDIP) combined with DNA microarray was used to compare DNA methylation profiles of epithelial cells derived from high-grade CIN lesions with normal cervical epithelium resulting in the identification of hypermethylated differentially methylated regions (DMRs). Validation of 9 selected DMRs by MSP or BSP in cervical tissue revealed methylation in 63.2-94.7% high-grade CIN and in 59.3-100% cervical carcinomas. QMSP for the two most significant high-grade CIN-specific methylation markers was applied exploring test performance in a large series of cervical scrapings. Frequency and relative level of methylation were significantly different between normal and cancer samples (p<0.001). Clinical validation of both markers in cervical scrapings from patients referred with an abnormal cervical smear, confirmed that frequency and relative level of methylation were related with increasing severity of the underlying CIN lesion (p<0.001) and the ROC analysis was discriminative (p<0.005). These possible methylation markers represent COL25A1 and KATNAL2 promoters and their observed increased methylation upon progression is in agreement with their biological function (cytoskeleton regulation). In conclusion, our newly identified hypermethylated DMRs represent specific DNA methylation patterns in high-grade CIN lesions and could be potential biomarkers for early detection.
2012-11-01 | GSE36319 | GEO
Project description:Bladder cancer (BCa) is one of the most common malignancy of the urinary tract. In order to improve the diagnosis, prevention and treatment of BCa, the details of molecular mechanisms underlying the tumorigenesis and development needs to be clarified. Results provide insight into molecular mechanisms underlying the mRNA and miRNA interactions in BCa. 3 human bladder cancer tissues and 3 normal bladder tissues were analyzed using microarray. The alteration of mRNA and miRNA expression between the 2 groups were detected.
2017-02-22 | GSE76211 | GEO
Project description:The aim of this study was to investigate the presence of intact O- and N-glycopeptides in profiles of normal human urine analyzed by capillary electrophoresis coupled to mass spectrometry (CE-MS).CE and liquid chromatography coupled to tandem mass spectrometry (CE- and LC-MS/MS) were both used to identify glycopeptide sequences. Furthermore, we estimated the abundance levels of these glycopeptides in urine from five different cancer types i.e. bladder cancer (BCa), prostate cancer (PCa), pancreatic cancer, cholangiocarcinoma (CC) and renal cell carcinoma (RCC).
2018-11-29 | PXD011214 | Pride
Project description:Bladder cancer is one of the most common cancers. Since prognosis ameliorates with early detection, it is a challenge to develop techniques that could replace or complement the current diagnosis protocols. The study of extracellular vesicles (EVs) that are present in urine samples has become an attractive alternative. The present study describes the mRNA content of vesicles isolated from voided urine samples within bladder cancer context. To discover a genetic signature of cancer, RNA associated to EVs was analyzed by microarray technique. Total RNA isolated from Extracellular Vesicles obtained from urine of bladder cancer patients was compared with RNA isolated from urinary vesicles of non-cancer patients.
2014-01-29 | E-GEOD-51843 | biostudies-arrayexpress