| Literature DB >> 25765988 |
Pauline Duconseil1, Marine Gilabert1, Odile Gayet1, Celine Loncle1, Vincent Moutardier2, Olivier Turrini3, Ezequiel Calvo4, Jacques Ewald5, Marc Giovannini5, Mohamed Gasmi6, Erwan Bories5, Marc Barthet6, Mehdi Ouaissi7, Anthony Goncalves5, Flora Poizat5, Jean Luc Raoul5, Veronique Secq2, Stephane Garcia2, Patrice Viens5, Juan Iovanna8, Nelson Dusetti9.
Abstract
A major impediment to the effective treatment of patients with pancreatic ductal adenocarcinoma (PDAC) is the molecular heterogeneity of this disease, which is reflected in an equally diverse pattern of clinical outcome and in responses to therapies. We developed an efficient strategy in which PDAC samples from 17 consecutive patients were collected by endoscopic ultrasound-guided fine-needle aspiration or surgery and were preserved as breathing tumors by xenografting and as a primary culture of epithelial cells. Transcriptomic analysis was performed from breathing tumors by an Affymetrix approach. We observed significant heterogeneity in the RNA expression profile of tumors. However, the bioinformatic analysis of these data was able to discriminate between patients with long- and short-term survival corresponding to patients with moderately or poorly differentiated PDAC tumors, respectively. Primary culture of cells allowed us to analyze their relative sensitivity to anticancer drugs in vitro using a chemogram, similar to the antibiogram for microorganisms, establishing an individual profile of drug sensitivity. As expected, the response was patient dependent. We also found that transcriptomic analysis predicts the sensitivity of cells to the five anticancer drugs most frequently used to treat patients with PDAC. In conclusion, using this approach, we found that transcriptomic analysis could predict the sensitivity to anticancer drugs and the clinical outcome of patients with PDAC.Entities:
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Year: 2015 PMID: 25765988 DOI: 10.1016/j.ajpath.2014.11.029
Source DB: PubMed Journal: Am J Pathol ISSN: 0002-9440 Impact factor: 4.307