From ERα66 to ERα36: a generic method for validating a prognosis marker of breast tumor progression
| Autor: | Chamard-Jovenin, Clémence, Jung, Alain C., Chesnel, Amand, Abecassis, Joseph, Flament, Stéphane, Ledrappier, Sonia, Macabre, Christine, Boukhobza, Taha, Dumond, Hélène |
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| Přispěvatelé: | Centre de Recherche en Automatique de Nancy (CRAN), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Centre Paul Strauss, CRLCC Paul Strauss, Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Retrospective study
ERalpha36 Structural Biology Modelling and Simulation Applied Mathematics Distance based tumor classification Breast tumor Gene network identification [SDV.CAN]Life Sciences [q-bio]/Cancer Molecular Biology Metastatic potential Nonlinear correlation [SPI.AUTO]Engineering Sciences [physics]/Automatic |
| Zdroj: | BMC Systems Biology BMC Systems Biology, BioMed Central, 2015, 9, pp.28. ⟨10.1186/s12918-015-0178-7⟩ |
| ISSN: | 1752-0509 |
| Popis: | International audience; Background: Estrogen receptor alpha36 (ERalpha36), a variant of estrogen receptor alpha (ER) is expressed in about half of breast tumors, independently of the [ER+]/[ER-] status. In vitro, ERalpha36 triggers mitogenic non-genomic signaling and migration ability in response to 17beta-estradiol and tamoxifen. In vivo, highly ERalpha36 expressing tumors are of poor outcome especially as [ER+] tumors are submitted to tamoxifen treatment which, in turn, enhances ERalpha36 expression. Results: Our study aimed to validate ERalpha36 expression as a reliable prognostic factor for cancer progression from an estrogen dependent proliferative tumor toward an estrogen dispensable metastatic disease. In a retrospective study, we tried to decipher underlying mechanisms of cancer progression by using an original modeling of the relationships between ERalpha36, other estrogen and growth factor receptors and metastatic marker expression. Nonlinear correlation analyses and mutual information computations led to characterize a complex network connecting ERalpha36 to either non-genomic estrogen signaling or to metastatic process. Conclusions: This study identifies ERalpha36 expression level as a relevant classifier which should be taken into account for breast tumors clinical characterization and [ER+] tumor treatment orientation, using a generic approach for the rapid, cheap and relevant evaluation of any candidate gene expression as a predictor of a complex biological process. |
| Databáze: | OpenAIRE |
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