Improvement of a Predictive Model of Castration-Resistant Prostate Cancer: Functional Genetic Variants in TGFβ1 Signaling Pathway Modulation

Ana L Teixeira, Mónica Gomes, Augusto Nogueira, Andreia S Azevedo, Joana Assis, Francisca Dias, Juliana I Santos, Francisco Lobo, António Morais, Joaquina Maurício and Rui Medeiros

PLOS ONE, 2013, vol. 8, issue 8, 1-

Abstract: Prostate cancer (PC) is the most frequently diagnosed cancer in men. The acquisition of castration-resistant (CR) phenotype is associated with the activation of signaling pathways mediated by growth factors. The TGFβ1 and its receptors have an important role in tumor progression, being the pro-apoptotic function modulated by the expression of TGFBR2. A single nucleotide polymorphism -875 G > A in TGFBR2 gene has been described, which may influence the expression levels of the receptor. Our purpose was to investigate the potential role of TGFBR2-875G>A in PC risk and in the response to androgen deprivation therapy (ADT). TGFBR2-875G>A polymorphism was studied by allelic discrimination using real-time polymerase chain reaction (PCR) in 891 patients with PC and 874 controls. A follow-up study was undertaken to evaluate response to ADT. The TGFBR2 and SMAD7 mRNA expression were analyzed by a quantitative real-time PCR. We found that TGFBR2-875GG homozygous patients present lower expression levels of TGFBR2 mRNA (AA/AG: 2-ΔΔCT =1.5, P=0.016). GG genotype was also associated with higher Gleason grade (OR=1.51, P=0.019) and increased risk of an early relapse after ADT (HR=1.47, P=0.024). The concordance (c) index analysis showed that the definition of profiles that contains information regarding tumor characteristics associated with genetic information present an increased capacity to predict the risk for CR development (c-index model 1: 0.683 vs model 2: 0.736 vs model 3: 0.746 vs model 4: 0.759). The TGFBR2-875G>A contribution to an early relapse in ADT patients, due to changes in mRNA expression, supports the involvement of TGFβ1 pathway in CRPC. Furthermore, according to our results, we hypothesize the potential benefits of the association of genetic information in predictive models of CR development.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0072419

DOI: 10.1371/journal.pone.0072419

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