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Series GSE7476 Query DataSets for GSE7476
Status Public on Jul 01, 2007
Title Analysis of clinical bladder cancer classification according to microarray expression profiles
Organism Homo sapiens
Experiment type Expression profiling by array
Summary 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 control samples were associated with growth, differentiation, immune system response, communication, cellular matrix and enzyme regulation. Comparing superficial versus invasive samples, the most important overrepresented biological category was growth and, specifically, DNA synthesis and mitotic cytoskeleton. On the other hand, some under expressed genes have been clearly related to muscular tissue contamination in control samples. Finally, we demonstrated that a pool strategy could be a good option to detect the best differentially expressed genes between two compared conditions.
Keywords: disease state analysis
 
Overall design We analyzed gene expression profiles in normal bladder tissues (controls), low grade superficial tumor samples (pathologically classified as Ta low grade, named as Ta), high grade superficial tumors with an unclear clinical behavior (T1 high grade, named as T1) and high grade muscle invasive tumors (pathologically classified as T2, T3 or T4, named as T2+). We analyzed data using a sub-pooling strategy. The number of individual samples on every pool was: controls (4, 4, 4), Ta (5, 5, 5), T1 (5, 4, 4) and T2+ (5, 5, 5).
 
Citation(s) 19539325
Submission date Apr 07, 2007
Last update date Mar 25, 2019
Contact name Moises Burset Albareda
E-mail(s) [email protected]
Organization name Fundacio Puigvert
Department Molecular biology
Street address Cartagena, 340-350
City Barcelona
State/province Barcelona
ZIP/Postal code 08025
Country Spain
 
Platforms (1)
GPL570 [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array
Samples (12)
GSM180991 bladder_control_pool-1
GSM180992 bladder_control_pool-2
GSM180993 bladder_control_pool-3
Relations
BioProject PRJNA100283

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Supplementary file Size Download File type/resource
GSE7476_RAW.tar 53.1 Mb (http)(custom) TAR (of CEL)

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