Dc34fc72-04e7-4627-96ec-7b054f1a79bf - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001010065 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Improved risk stratification and predictive biomarkers of treatment response are needed for non–muscle-invasive bladder cancer (NMIBC). Here we assessed the clinical utility of targeted RNA and DNA molecular profiling in NMIBC. We performed RNA-based profiling by NanoString nCounter on non–muscle-invasive bladder cancer (NMIBC) clinical specimens and found that a novel expression signature of an inflamed tumor microenvironment (TME), but not molecular subtyping, was associated with improved recurrence-free survival after bacillus Calmette-Guérin (BCG) immunotherapy. We further demonstrated that immune checkpoint gene expression was not associated with higher recurrence rates after BCG.
2021-10-05 | GSE185264 | 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: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.
2012-02-22 | GSE23732 | GEO
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.
2012-02-22 | E-GEOD-23732 | biostudies-arrayexpress
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:Although the intravesical instillation of Bacillus Calmette-Guerin (BCG) is widely used as adjuvant treatment for nonmuscle-invasive bladder cancers, the clinical benefit is variable across patients, and the molecular mechanisms underlying the sensitivity to BCG administration and disease progression are poorly understood. To establish the molecular signatures that predict the responsiveness and disease progression of bladder cancers treated with BCG, we performed transcriptome sequencing (RNA-seq) for 13 treatment-naïve and 22 post-treatment specimens obtained from 14 bladder cancer patients. To overcome disease heterogeneity, we used non-negative matrix factorization to identify the latent molecular features associated with drug responsiveness and disease progression. At least 12 molecular features were present, among which the immune-related feature was associated with drug responsiveness, indicating that pre-treatment anti-cancer immunity might dictate BCG responsiveness. We also identified disease progression-associated molecular features indicative of elevated cellular proliferation in post-treatment specimens. The progression-associated molecular features were validated in an extended cohort of BCG-treated bladder cancers. Our study advances understanding of the molecular mechanisms of BCG activity in bladder cancers and provides clinically relevant gene markers for evaluating and monitoring patients.
2023-12-25 | GSE244895 | GEO
Project description:Intravesical Bacillus Calmette-Guerin (BCG) is an effective immunotherapy for non-muscle invasive bladder cancer (NMIBC). However, recurrence and progression remain frequent warranting deeper insights into its mechanism. We herein comprehensively profiled blood and tissues obtained from NMIBC patients before, during and after BCG treatment using cytometry by time-of-flight (CyTOF) and RNA sequencing to identify the key immune subsets crucial for anti-tumour activity.
| EGAS00001004764 | EGA
Project description:This ordinary differential equation model, simulating the tumor-immune interactions involved in BCG immunotherapy to treat superficial bladder cancer, is described by the publication:
Bunimovich-Mendrazitsky, S., Shochat, E., Stone, L. "Mathematical Model of BCG Immunotherapy in Superficial Bladder Cancer". Bull. Math. Biol. 69, 1847–1870 (2007). DOI: 10.1007/s11538-007-9195-z
Comment:
This model is based on the system of ODEs given in Equation 4 of the publication manuscript.
Reproduction of Figure 4 was achieved by setting p4 = 0.085.
Abstract:
Immunotherapy with Bacillus Calmette-Guérin (BCG)-an attenuated strain of Mycobacterium bovis (M. bovis) used for anti tuberculosis immunization-is a clinically established procedure for the treatment of superficial bladder cancer. However, the mode of action has not yet been fully elucidated, despite much extensive biological experience. The purpose of this paper is to develop a first mathematical model that describes tumor-immune interactions in the bladder as a result of BCG therapy. A mathematical analysis of the ODE model identifies multiple equilibrium points, their stability properties, and bifurcation points. Intriguing regimes of bistability are identified in which treatment has potential to result in a tumor-free equilibrium or a full-blown tumor depending only on initial conditions. Attention is given to estimating parameters and validating the model using published data taken from in vitro, mouse and human studies. The model makes clear that intensity of immunotherapy must be kept in limited bounds. While small treatment levels may fail to clear the tumor, a treatment that is too large can lead to an over-stimulated immune system having dangerous side effects for the patient.
2024-09-02 | BIOMD0000001034 | BioModels