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https://hdl.handle.net/2445/21368
Title: | Generation of biological association networks: A novel strategy to detect new targets in cancer therapy |
Author: | Selga i Coma, Elisabet Almagro García, Ma. Cristina de Oleaga Sancho, Carlota Mencía Trinchant, Núria Ramírez, Sara Ruiz, F. Xavier Farrés i Vicén, Jaume Parés i Casasampera, Xavier Thibaut, Rémi Porte Visa, Cinta Noé Mata, Verónica Ciudad i Gómez, Carlos Julián |
Keywords: | Càncer Quimioteràpia Farmacogenètica Cancer Chemotherapy Pharmacogenetics |
Issue Date: | 2011 |
Publisher: | Transworld Research Network |
Abstract: | The aim of this work was to design a novel strategy to detect new targets for anticancer treatments. The rationale was to build Biological Association Networks from differentially expressed genes in drug-resistant cells to identify important nodes within the Networks. These nodes may represent putative targets to attack in cancer therapy, as a way to destabilize the gene network developed by the resistant cells to escape from the drug pressure. As a model we used cells resistant to methotrexate (MTX), an inhibitor of DHFR. Selected node-genes were analyzed at the transcriptional level and from a genotypic point of view. In colon cancer cells, DHFR, the AKR1 family, PKC¿, S100A4, DKK1, and CAV1 were overexpressed while E-cadherin was lost. In breast cancer cells, the UGT1A family was overexpressed, whereas EEF1A1 was overexpressed in pancreatic cells. Interference RNAs directed against these targets sensitized cells towards MTX. |
Note: | Podeu consultar el llibre complet a: http://www.trnres.com/ebookcontents.php?id=149 |
Note: | Reproducció del capítol 1 del llibre publicat a: http://www.trnres.com/ebookcontents.php?id=106 |
It is part of: | Recent Advances in Pharmaceutical Sciences, 2011, Chapter 1, p. 1-33. Editor: Diego Muñoz-Torrero |
URI: | https://hdl.handle.net/2445/21368 |
Related resource: | http://hdl.handle.net/2445/32392 |
Appears in Collections: | Llibres / Capítols de llibre (Bioquímica i Biomedicina Molecular) |
Files in This Item:
File | Description | Size | Format | |
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249207.pdf | 1.06 MB | Adobe PDF | View/Open |
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