Project description:At diagnosis approximately 75% of bladder urothelial carcinomas are non muscle invasive bladder cancers (Ta, T1 and Tis), 20% are muscle invasive bladder cancer (T2-T4) and 5% are already metastatic. Non muscle invasive bladder cancers are characterized by tumor recurrence in 60% to 85% of cases and, therefore, long-term followup is needed. The current standard methods to detect and monitor bladder cancer are cystoscopy and cytology. Cystoscopy is an invasive method and cytology is hampered by low sensitivity, especially for low grade tumors. So there is need to develop reliable and noninvasive methods to detect and predict bladder cancer biological behavior. So we have performed high density oligonucleotide microarray for discovery of new molecular markers to diagnose and predict the outcome of bladder cancer. Under an ethical guideline of Chhatrapati Shahuji Maharaj Medical University, India histologically confirmed seven bladder cancer patients were recruited from Department of Urology, Chhatrapati Shahuji Maharaj Medical University, Lucknow, India. Total RNA was extracted from tumor biopsies and hybridized on affymetrix Human Gene ST 1.1 array to determine differentially expressed genes in urinary bladder cancer with muscle invasion in comparison of normal human urinary bladder.
Project description:This study aimed to identify the genetic signatures associated with disease prognosis in bladder cancer. We used 165 primary bladder cancer samples, 23 recurrent non-muscle invasive tumor tissues, 58 normal looking bladder mucosae surrounding cancer and 10 normal bladder mucosae for microarray analysis. Hierarchical clustering was used to stratify the prognosis-related gene classifiers. For validation, real-time reverse-transcriptase polymerase chain reaction (RT-PCR) of top-ranked 14 genes was performed. On unsupervised hierarchical clustering using prognosis related gene-classifier, tumors were divided into 2 groups. The high risk gene signatures had significantly poor prognosis compared to low risk gene signatures (P<0.001 by the log-rank test, respectively). The prognosis-related gene classifiers correlated significantly with recurrence of non-muscle invasive bladder cancer (hazard ratio, 4.09; 95% confidence interval [CI], 1.94 to 8.64; P<0.001), and progression (hazard ratio, 23.68; 95% confidence interval [CI], 4.91 to 114.30; P<0.001), cancer-specific survival (hazard ratio, 29.25; 95% confidence interval [CI], 3.47 to 246.98; P=0.002) and overall survival (hazard ratio, 23.33; 95% confidence interval [CI], 4.97 to 109.50; P<0.001) of muscle invasive bladder cancer (p < 0.001, respectively). No patient with non-muscle invasive bladder cancer experienced cancer progression in low risk gene signature group. Prognosis-related gene classifiers validated by RT- PCR showed identical results. Prognosis related gene-classifiers provided strong predictive value for disease outcome. These gene classifiers could assist in selecting patients who might benefit from more aggressive therapeutic intervention or surveillance. Keywords: Gene expression, Bladder cancer, Prognosis 165 primary bladder cancer samples and 23 recurrent non-muscle invasive tumor tissues from 14 patients were taken in the Chungbuk National University Hospital. Only histologically verified transitional cell carcinoma samples were selected. Simultaneously 58 normal looking bladder mucosae surrounding cancer were obtained during the operation, which were histologically confirmed normal. Also, 10 normal bladder mucosae were obtained from patients with benign disease. The normal controls were determined to be free of cancer after revealing no malignant cells on urine cytology and no observable bladder cancer on cystoscopic examination during operation for their diseases, and were histologically reconfirmed normal.
Project description:miRNAs are involved in cancer development and progression,acting as tumor suppressors or oncogenes. Half of the human miRNAs are located in cancer-associated genomic regions and can function as tumor suppressor genes or oncogenes depending on their targets miRNA profiling was performed on paired bladder cancer tissues and differentially expressed miRNAs were identified in BC and adjacent noncancerous tissues of any disease stage/grade. Ten paired bladder cancer tissues (5 low-grade non-muscle-invasive bladder cancer[NMIBC] and 5 high-grade muscle-invasive bladder cancer[MIBC]) were sent to CapitalBio Corp. (Beijing) for noncoding RNA microarray analysis. The microarray analysis was done as described on the Web site of CapitalBio. NMIBC samples include 07A, 19A, 23A, 24A and T63 while coresponding pairs include 07B, 19B, 23B, 24B and 63. MIBC samples include 10A, 20A, 21A, 34A and 49A while coresponding pairs include 10B, 20B, 21B, 34B and 49B.
Project description:Bladder cancer tissue from 11 patients diagnosed as superficial and muscle invasive and 7 normal bladder mucoa were analyzed by protein antibody array kit with 656 antibodies
Project description:This Series contains data from 845 participants (188 men and 657 women) in the EPIC-Italy cohort that was produced at the Human Genetics Foundation (HuGeF) in Turin, Italy. At the last follow-up (2010), 424 participants remained cancer-free, 235 had developed primary breast cancer, 166 had developed primary colorectal cancer, and 20 had developed other primary cancers. Anthropometric measurements, and dietary and lifestyle information obtained by questionnaire are also available. A total of 845 samples from the EPIC-Italy cohort were analyzed.
Project description:At diagnosis approximately 75% of bladder urothelial carcinomas are non muscle invasive bladder cancers (Ta, T1 and Tis), 20% are muscle invasive bladder cancer (T2-T4) and 5% are already metastatic. Non muscle invasive bladder cancers are characterized by tumor recurrence in 60% to 85% of cases and, therefore, long-term followup is needed. The current standard methods to detect and monitor bladder cancer are cystoscopy and cytology. Cystoscopy is an invasive method and cytology is hampered by low sensitivity, especially for low grade tumors. So there is need to develop reliable and noninvasive methods to detect and predict bladder cancer biological behavior. So we have performed high density oligonucleotide microarray for discovery of new molecular markers to diagnose and predict the outcome of bladder cancer.
Project description:This RNA-sequencing cohort includes 52 Non-muscle Invasive Bladder cancer (NMIBC) samples and 6 Muscle Invasive Bladder cancer (MIBC) samples.
Project description:DNA methylation is the most studied epigenetic modification due to its role in regulating gene expression and aberrations in methylation involved in the pathogenesis of cancer and several diseases. The method of choice to evaluate genome-wide methylation has been the Illumina HumanMethylation450 BeadChip (450K), but it was recently replaced with the MethylationEPIC BeadChip (EPIC). We therefore sought to validate the EPIC array in comparison to the 450K array for both fresh-frozen (FF) and formalin-fixed paraffin-embedded (FFPE) pediatric brain tumors. We also performed analysis on the EPIC array with paired FF and FFPE samples, to adapt to a clinical setting where FFPE is routinely used. Further, we compared two restoration methods, REPLI-g and Infinium, for FFPE-derived DNA on the EPIC array.
Project description:Background: Epigenome-wide association studies (EWAS) have been widely applied to identify methylation CpG sites associated with human disease. To date, the Infinium Methylation EPIC array (EPIC) is commonly used for high-throughput DNA methylation profiling. However, the EPIC array covers only 30% of the human methylome. Methylation Capture bisulfite sequencing (MC-seq) captures target regions of methylome and has advantages of extensive coverage in the methylome at an affordable price. Methods: Epigenome-wide DNA methylation in four peripheral blood mononuclear cell samples was profiled by using SureSelectXT Methyl-Seq for MC-seq and EPIC platforms separately. CpG site-based reproducibility of MC-seq was assessed with DNA sample inputs ranging in quantity of high (> 1000ng), medium (300-1000ng), and low (150ng-300ng). To compare the performance of MC-seq and the EPIC arrays, we conducted a Pearson correlation and methylation value difference at each CpG site that was detected by both MC-seq and EPIC. We compared the percentage and counts in each CpG island and gene annotation between MC-seq and the EPIC array. Results: After quality control, an average of 3,708,550 CpG sites per sample was detected by MC-seq with DNA quantity >1000ng. Reproducibility of MC-seq detected CpG sites was high with strong correlation estimates for CpG methylation among samples with high, medium, and low DNA inputs (r > 0.96). The EPIC array captured an average of 846,464 CpG sites per sample. Compared with the EPIC array, MC-seq detected more CpGs in coding regions and CpG islands. Among the 472,540 CpG sites captured by both platforms, methylation of a majority of CpG sites was highly correlated in the same sample (r: 0.98~0.99). However, methylation for a small proportion of CpGs (N=235) differed significantly between the two platforms, with differences in beta values of greater than 0.5. Conclusions: Our results show that MC-seq is an efficient and reliable platform for methylome profiling with a broader coverage of the methylome than the array-based platform. Although methylation measurements in majority of CpGs are highly correlated, a number of CpG sites show large discrepancy between the two platforms, which warrants further investigation and needs cautious interpretation.