Association of SNPs in the PAI1 Gene with Disease Recurrence and Clinical Outcome in Bladder Cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE224309 | GEO | 2024/01/29
REPOSITORIES: GEO
Similar Datasets
Project description:Bladder cancer is the fifth most prevalent cancer in the U.S., yet is understudied and relatively lacking in suitable models. Here we describe a biobank of patient-derived organoid lines that recapitulates the spectrum of human bladder cancer at the histopathological and molecular levels. Organoid lines can be established efficiently from patient biopsies, including from patients before and after disease recurrence, and are interconvertible with orthotopic xenografts. Notably, these organoid lines often retain tumor heterogeneity and exhibit changes in their mutational profiles that are consistent with tumor evolution in culture. Analyses of drug response using bladder tumor organoids show partial correlations with mutational profiles as well as changes associated with treatment resistance, and specific responses can be validated using xenografts in vivo. Overall, our studies indicate that patient-derived bladder tumor organoids represent a model system for studying tumor evolution and treatment response in the context of precision cancer medicine.
2018-04-09 | GSE103990 | GEO
Project description:Full title: Predictive Gene Signatures as Strong Prognostic Indicators of the Effectiveness of Bacillus Calmette–Guérin (BCG) Immunotherapy in Primary pT1 Bladder Cancers Intravesical BCG immunotherapy is effective in prevention of recurrence and progression in many cases of non-muscle invasive bladder cancer, but many patients fail to respond. This study identified predictive gene signatures in primary pT1 bladder cancer with BCG immunotherapy. Fourty-Eight patients with primary pT1 bladder cancer treated with BCG immunotherapy were used. Microarray gene expression analysis of the 48 primary bladder cancers was carried out. Predictive gene signatures were individually selected based on the recurrence and progression status. Among 43,148 unique genes, 424 and 287 candidate predictive genes that could predict recurrence and progression, respectively, were selected. Time to recurrence or progression was shorter for patients with poor-predictive gene signatures than good-predictive gene signatures (log-rank test, p <0.001, respectively). Validation of predictive gene signatures with RT-PCR was nearly identical to those of microarray (log-rank test, p <0.05, respectively). In multivariate regression analysis, predictive gene signatures were the only independent predictors of recurrence (HR 3.38, p = 0.048) or progression (HR 10.49, p = 0.048) in validation cohorts. Predictive gene signatures have strong diagnostic value for determining the response to intravesical BCG immunotherapy in primary pT1 bladder cancer. Keywords: Gene expression, Bladder cancer, BCG
2010-03-26 | GSE19423 | GEO
Project description:We adapted the DiR barcode-based parallel reporter assay systems strategy to systematically identify the SNPs that affect gene expression by modulating activities of regulatory elements. Among 293 SNPs linked with GWAS-identified prostate cancer-risk SNPs, we found 32, 9, and 11 regulatory SNPs in 22Rv1, PC-3, and LNCaP cells. Further mechanism study indicates that one SNP regulates gene expression in prostate cancer malignancy. The DiR system has great potential to advance the functional study of risk SNPs that have associations with polygenic diseases. Our findings hold great promise in benefiting prostate cancer patients with prognostic prediction.
2021-01-30 | GSE165765 | GEO
Project description:Full title: Predictive Gene Signatures as Strong Prognostic Indicators of the Effectiveness of Bacillus Calmetteâ??Guérin (BCG) Immunotherapy in Primary pT1 Bladder Cancers Intravesical BCG immunotherapy is effective in prevention of recurrence and progression in many cases of non-muscle invasive bladder cancer, but many patients fail to respond. This study identified predictive gene signatures in primary pT1 bladder cancer with BCG immunotherapy. Fourty-Eight patients with primary pT1 bladder cancer treated with BCG immunotherapy were used. Microarray gene expression analysis of the 48 primary bladder cancers was carried out. Predictive gene signatures were individually selected based on the recurrence and progression status. Among 43,148 unique genes, 424 and 287 candidate predictive genes that could predict recurrence and progression, respectively, were selected. Time to recurrence or progression was shorter for patients with poor-predictive gene signatures than good-predictive gene signatures (log-rank test, p <0.001, respectively). Validation of predictive gene signatures with RT-PCR was nearly identical to those of microarray (log-rank test, p <0.05, respectively). In multivariate regression analysis, predictive gene signatures were the only independent predictors of recurrence (HR 3.38, p = 0.048) or progression (HR 10.49, p = 0.048) in validation cohorts. Predictive gene signatures have strong diagnostic value for determining the response to intravesical BCG immunotherapy in primary pT1 bladder cancer. Keywords: Gene expression, Bladder cancer, BCG Total RNA, extracted from the fresh frozen tissues of 48 pT1 bladder cancers, was isolated by TRIzol reagent (Life Technologies, NY, USA), according to the manufacturer's protocol. The quality and integrity of the RNA were confirmed by agarose gel electrophoresis and ethidium bromide staining, followed by visual examination under ultraviolet light. Five-hundred nanograms of total RNA were used for labeling hybridization according to the manufacturerâ??s protocol (Illumina HumanWG-6 BeadChip, version 2, Illumina, Inc., San Diego, CA, USA). Arrays were scanned with an Illumina Bead Array Reader confocal scanner (BeadStation 500GXDW; Illumina, Inc.) according to the manufacturer's instructions. Initial microarray gene expression data were obtained using Bead Studio software with gene expression analysis module (version 3.1.3, Illumina, Inc.).
2010-04-07 | E-GEOD-19423 | biostudies-arrayexpress
Project description:Aneuploidy is among the most common hallmarks of cancer, yet the underlying genetic mechanisms are still poorly defined. We have recently identified STAG2 as a gene that is mutated in human cancer and whose inactivation leads directly to chromosomal instability and aneuploidy. However, no single tumor type has yet been identified in which inactivation of a cohesin subunit represents a predominant mutational event. Here we used immunohistochemistry to screen a panel of 2,214 tumors from each of the major human tumor types to identify additional tumor types harboring somatic loss of STAG2. Strikingly, STAG2 expression was completely absent in 18% of urothelial carcinomas, the most common type of bladder cancer and the fifth most common cancer in the United States. DNA sequencing revealed that somatic mutations of STAG2 were present in 21% of urothelial carcinomas, which were found to be a group of highly aneuploid tumors. The acquisition of STAG2 mutations was shown to be an early event in the pathogenesis of urothelial carcinoma. STAG2 loss was significantly associated with lymph node invasion, increased disease recurrence, and reduced cancer-specific survival. These results identify STAG2 as one of the most commonly mutated genes in bladder cancer discovered to date, and demonstrate that STAG2 inactivation defines an aggressive subtype of bladder cancer with particularly poor prognosis. Affymetrix CytoScan HD Arrays were performed according to the manufacturer's directions on genomic DNA extracted directly from snap-frozen human urothelial carcinoma primary tumors. Copy number analysis using Affymetrix CytoScan HD Arrays was performed for 12 human urothelial carcinomas of the bladder with truncating mutations of the STAG2 gene.
2013-06-30 | E-GEOD-41581 | biostudies-arrayexpress
Project description:Genome-wide studies characterizing mutational landscape of bladder cancer revealed the exceptionally high rate of chromatin modifier genes in bladder cancer. Thus, epigenetic deregulation is a critical theme which needs further investigation for bladder cancer research. One of the highly mutated genes in bladder cancer is KDM6A, functioning as H3K27 demethylase and part of MLL3/4 complexes. To decipher the role of KDM6A in normal vs tumor setting, we identified the genomic localization profiles of KDM6A in normal, immortalized and cancer bladder cells. Our results showed differential occupancy of KDM6A at the genes involved in cell differentiation, chromatin organization and Notch signaling depending on the cell type and the mutation status of KDM6A. Transcription factor motif analysis revealed an enrichment for HES1 for the KDM6A peaks identified for T24 bladder cancer cell line, which has a truncating mutation in KDM6A and lacking demethylase domain and also for the other clusters showing KDM6A localization. For the first time, using co-immunoprecipitation experiments, we show that KDM6A is in complex with TLE co-repressors and HES1, and illustrate the potential interaction of KDM6A with TLE co-repressors, HES1, RUNX, HHEX transcription factors by computational structural biology models. Our work makes important contributions to the understanding of KDM6A malfunction in bladder cancer and provides models for the functioning of KDM6A independent of its demethylase activity.
2023-03-03 | GSE216625 | GEO
Project description:Background: Expression quantitative trait loci (eQTL) studies are a valuable approach for identifying genetic variants correlated with gene expression. However, identifying the causal variants is challenging due to linkage disequilibrium amongst variants in the same haplotype block. In this study, we aim to identify functional SNPs in key regulatory regions that alter transcriptional regulation and thus, potentially impact cellular function. The majority of disease-associated single-nucleotide polymorphisms (SNPs) are located in regulatory regions, which can result in allele-specific binding (ASB) of transcription factors and differential expression of the target gene alleles. Here, we present regSNPs-ASB, a generalized linear model-based approach to accurately identify regulatory SNPs that are located in transcription factor binding sites from ATAC-seq data. Results: Using regSNPs-ASB, we identified 53 regulatory SNPs in human MCF-7 breast cancer cells and 125 regulatory SNPs in human mesenchymal stem cells (MSC). By integrating the regSNPs-ASB output with RNA-seq experimental data and publicly available chromatin interaction data from MCF-7 cells, we found that these 53 regulatory SNPs were associated with 74 potential target genes and that 32 (43%) of these genes showed significant allele-specific expression (ASE). By comparing all of the MCF-7 and MSC regulatory SNPs to the eQTLs in the Genome-Tissue Expression (GTEx) Project database, we found that 30% (16/53) of the regulatory SNPs in MCF-7 and 43% (52/122) of the regulatory SNPs in MSC were also eQTLs. The enrichment of regulatory SNPs in eQTLs indicated that many of them are likely responsible for allelic differences in gene expression (chi-square test, p-value < 0.01). In sum, we conclude that regSNPs-ASB is a useful tool for identifying causal variants from ATAC-seq data. This new computational tool will enable efficient prioritization of genetic variants identified as eQTL for further studies to validate their causal regulatory function. Ultimately, identifying causal genetic variants will further our understanding of the underlying molecular mechanisms of disease and the eventual development of potential therapeutic targets.
2020-02-14 | GSE145245 | GEO
Project description:Functional Significance of Prostate Cancer risk-SNPs
| PRJNA294704 | ENA
Project description:Primary uveal melanomas show multiple genetic alterations. To determine mutational status of six human primary uveal melanomas, we performed whole exome sequencing (WES) and called Single Nucleotide Polimorphism (SNPs) to identify somatic mutations in these human primary uveal melanomas.
2021-01-25 | GSE138664 | GEO
Project description:Expression profiling of superficial bladder tumours to delineate the expression pattern differences between non-recurring and recurring tumours. Keywords = bladder cancer, superficial, recurrence, prediction Keywords: other
2002-12-08 | GSE88 | GEO