Transcription profiling of human bladder cancers to develop a clinical classification according to microarray expression profiles

ABSTRACT: Using Affymetrix microarray technology we analyzed the gene expression profiles of the most important pathological categories of bladder cancer in order to detect potential marker genes. Applying an unsupervised cluster algorithm we observed clear differences between tumor and control samples, as well as between superficial and muscle invasive tumors. According to cluster results, the T1 high grade tumor type presented a global genetic profile which could not be distinguished from invasive cases. We described a new measure to classify differentially expressed genes and we compared it against the B-rank statistic as a standard method. According to this new classification method, the biological functions overrepresented in top differentially expressed genes when comparing tumor versus contr

ORGANISM(S): Homo sapiens

SUBMITTER: Moises Burset Albareda 

PROVIDER: E-GEOD-7476 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress