Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Gene expression data from muscle-invasive bladder cancer samples II

ABSTRACT: Gene signatures based on the median expression of a preselected set of genes can provide prognostic and treatment outcome prediction and so be valuable clinically. Different health care services use different gene expression platforms to derive gene expression data. Here we have derived gene expression data using a microarray platform.

ORGANISM(S): Homo sapiens

PROVIDER: GSE245953 | GEO | 2023/12/31

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Gene expression data from muscle-invasive bladder cancer samples

Project description:Gene signatures based on the median expression of a preselected set of genes can provide prognostic and treatment outcome prediction and so be valuable clinically. Different health care services use different gene expression platforms to derive gene expression data. Here we have derived gene expression data using a microarray platform.

2022-12-31 | GSE203149 | GEO

Recurrence in non-muscle invasive bladder cancer

Project description: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.

2014-04-07 | E-MEXP-3625 | biostudies-arrayexpress

Less invasive diagnostics for cancer using hair follicle

Project description:Primary outcome(s): Comparison of the gene expression profile in hair follicle between cancer patients and healthy volunteer

| 2628246 | ecrin-mdr-crc

Gene expression signatures predict outcome in non-muscle invasive bladder carcinoma - a multi-center validation study

Project description:Background Clinically useful molecular markers predicting the clinical course of patients diagnosed with non-muscle invasive bladder cancer are needed to improve treatment outcome. Methods We used custom designed oligonucleotide microarrays to validate four previously reported gene expression signatures for molecular diagnosis of disease stage and carcinoma in situ, and for predicting disease recurrence and progression. We analyzed tumors from 404 patients diagnosed with bladder cancer in hospitals in Denmark, Sweden, England, Spain and France. Molecular classifications were compared to pathological diagnosis and clinical outcome. The median follow-up time for the patients was 3.5 years. Results Classification of disease stage using a 52-gene classifier was found to be highly significantly correlated with pathological stage (P<0.001). Furthermore, the classifier added information regarding future disease progression of Ta or T1 tumors (P<0.001). The molecular 77-gene progression classifier was highly significantly correlated with progression free survival (P<0.001) and cancer specific survival (P=0.001). Furthermore, multivariate Cox´s regression analysis showed the progression classifier to be an independently significant variable associated with disease progression after adjustment for age, sex, stage, grade and treatment (hazard ratio 2.4, P=0.005). The diagnosis of carcinoma in situ (CIS) using a 68-gene classifier showed a highly significant correlation with histopathological CIS diagnosis (odds ratio 5.8, P<0.001) in multivariate logistic regression analysis. Conclusions We conclude that this multicenter validation study confirms the clinical utility of molecular classifiers to guide treatment decisions for patients initially diagnosed with non-muscle invasive bladder cancer. Keywords: Multi center validation study of gene expression signatures

2007-06-15 | GSE5479 | GEO

Genome-wide analysis in ESET+/+ and ESET-/- thymocytes

Project description:Analysis of ESET deficient thymocytes at gene expression level. Each thymocyte developmental stage (preselected DP, postselected DP and CD4SP) was analysed.

2016-01-01 | GSE73951 | GEO

Comparison of gene expression profiling of human non-muscle invasive bladder cancer and muscle invasive bladder cancer

Project description:The biological behaviors, clinical treatment, prognosis of nonmuscle-invasive bladder cancers (NMIBCs) and muscle-invasive bladder cancers (MIBCs) are distinct. Therefore, we performed high-through microarray screening of mRNA expression in 30 bladder tumors, to filter out some of the differential expression genes in NMIBCs and MIBCs.A total of 11 Genes in MIBCs versus in NMIBCs were considered differentially transcribed if they were transcribed ≤2.0 fold change and p<0.001 by unpaired T-test, including 9 up-regulated genes and 2 down-regulated genes in MIBCs (NR4A2, PLK3, CYR61, APOLD1, C13ORF33, LIG4, RBMS3, PCK2, AK098422, HSD17B3, RTN4). These candidate genes were validated in further and provide further insight into the discovery of new putative markers to identify MIBCs preoperatively.

2018-12-01 | GSE77952 | GEO

Collagen stiffness promoted non-muscle-invasive bladder cancer progression to muscle-invasive bladder cancer.

Project description: Not available

| S-EPMC6511250 | biostudies-literature

Kinome expression profiling of muscle invasive bladder cancer (MIBC) patients

Project description:Muscle invasive bladder cancer (MIBC) is one of the aggressive cancer with limited treatment options. Targeted gene expression profiling in normal and tumor samples from MIBC patients could aid in identification of potential therapeutic targets. Thus we used kinase specific panel to study their expression pattern and to identify targetable genes.

2020-04-20 | GSE130598 | GEO

Expression profile of non-muscle invasive (superficial) bladder carcinoma

Project description:Gene expression profiling of 82 human non-muscle invasive bladder carcinoma and 4 normal bladder samples, for a total of 86 tissues. A Cartes d‚àö‚â†Identite des Tumeurs (CIT) study from the 'Institut Curie' and the french 'Ligue Nationale Contre le Cancer' (http://cit.ligue-cancer.net/).

2015-01-01 | E-MTAB-1940 | biostudies-arrayexpress

Identification of consensus molecular subtypes in muscle-invasive bladder cancer: A comparison of two sequencing methods and gene sets using FFPE specimens

Project description:To evaluate two methods for analysis of gene expression data from FFPE and to compare different gene-sets to call subtypes.

2023-06-02 | GSE225376 | GEO