Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

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

ABSTRACT: 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/).

ORGANISM(S): Homo sapiens

SUBMITTER: Fabien PETEL

PROVIDER: E-MTAB-1940 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Independent component analysis uncovers the landscape of the bladder tumor transcriptome and reveals insights into luminal and basal subtypes.

Biton Anne A Bernard-Pierrot Isabelle I Lou Yinjun Y Krucker Clémentine C Chapeaublanc Elodie E Rubio-Pérez Carlota C López-Bigas Nuria N Kamoun Aurélie A Neuzillet Yann Y Gestraud Pierre P Grieco Luca L Rebouissou Sandra S de Reyniès Aurélien A Benhamou Simone S Lebret Thierry T Southgate Jennifer J Barillot Emmanuel E Allory Yves Y Zinovyev Andrei A Radvanyi François F

Cell reports 20141113 4

Extracting relevant information from large-scale data offers unprecedented opportunities in cancerology. We applied independent component analysis (ICA) to bladder cancer transcriptome data sets and interpreted the components using gene enrichment analysis and tumor-associated molecular, clinicopathological, and processing information. We identified components associated with biological processes of tumor cells or the tumor microenvironment, and other components revealed technical biases. Applyi ...[more]

PMID: 25456126

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Project description:Patient-derived xenograft models are considered to represent the heterogeneity of human cancers and might be more relevant preclinical models to evaluate effective therapeutic agents. Our consortium joins efforts to extensively develop and characterize a new collection of patient-derived colorectal cancer models. From 86 unsupervised surgical colon sample collection, 54 tumors were successfully xenografted in immunodeficient mice and rats, representing 35 primary tumors, 5 peritoneal carcinosis and 14 metastases. Our histological and molecular characterization of patient tumors, first passage on mice and later passages includes the sequence of key genes involved in CRC (ie APC, KRAS, TP53), CGH array and transcriptomic analysis. This comprehensive characterization demonstrates that our collection recapitulates the clinical situation regarding the histopathological and molecular diversity of colorectal cancers. Moreover, patient tumors and corresponding models are clustering together which gives the opportunity to look for relevant signatures and comparison studies between clinical and preclinical data. Hence, we performed pharmacological monotherapy studies with standard of care for colon cancer (5-FU, oxaliplatin, irinotecan, cetuximab). Through this extensive in vivo analysis, we have compared the molecular profile with the drug sensitivity of each tumor models, and run an equivalent of a cetuximab phase II clinical trial in a preclinical setting. Our results confirm the key role of KRAS mutation in the cetuximab resistance and demonstrate that such collection could bring benefit to evaluate novel targeted therapeutic strategies and potentially help the stratification strategy for cancer patients according to molecular marker. This set correspond to 82 CGH profiles, with 7 samples from patient tumor and 75 samples from mouse xenograft at different passages P0 to P9. All hybridizations are performed with Human CGH 244K Agilent arrays (amadid 014693) in dual color with Human DNA Promega (sex matched) as reference. ID for biosources without an -Px suffix correspond to tumor patients. ID with a suffix correspond to xenograft with 0 for the first passage.

Dataset Information

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

Publications

Independent component analysis uncovers the landscape of the bladder tumor transcriptome and reveals insights into luminal and basal subtypes.

Similar Datasets

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