Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Recurrence in non-muscle invasive bladder cancer

ABSTRACT: Although non muscle-invasive bladder cancer can be treated successfully by surgical resection, there is a high rate of recurrence, which frequently develops into an invasive form of cancer. Due to the lack of marker molecules to predict recurrence, it is currently recommended that after resection each patient is screened via cystoscopy at least twice a year. This results in a psychic burden to the patient and substantial economic costs to the health care system. Using antibody microarrays targeting 724 different cancer-related proteins, we studied protein profiles of patients with and without recurrence. The analysis revealed 255 proteins of differential abundance. Most are involved in the regulation and execution of apoptosis and cell proliferation. For prognosis, a signature of 20 proteins was determined that predicts bladder cancer recurrence with 100% sensitivity and 80% specificity. As a measure of overall accuracy, the area under the curve (AUC) value was found to be 90%. This is well within a clinically relevant window of quality and should support decision making about the stringency of surveillance or even different treatment options.

ORGANISM(S): Homo sapiens

SUBMITTER: Christoph Schroeder

PROVIDER: E-MEXP-3625 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

Project description:Full title: Predictive Gene Signatures as Strong Prognostic Indicators of the Effectiveness of Bacillus Calmetteâ??GuÃ©rin (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.).

Dataset Information

Recurrence in non-muscle invasive bladder cancer

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure