Transcription analysis of human equilibrative nucleoside transporter-1 predicts survival in pancreas cancer patients treated with gemcitabine

Elisa Giovannetti, Mario Del Tacca, Valentina Mey, Niccola Funel, Sara Nannizzi, Sergio Ricci, Cinzia Orlandini, Ugo Boggi, Daniela Campani, Marco Del Chiaro, Mauro Iannopollo, Generoso Bevilacqua, Franco Mosca, Romano Danesi

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Gene expression analysis may help the management of cancer patients, allowing the selection of subjects responding to treatment. The aim of this study was the characterization of expression pattern of genes involved in gemcitabine activity in pancreas tumor specimens and its correlation with treatment outcome. The role of drug transport and metabolism on gemcitabine cytotoxicity was examined with specific inhibitors, whereas transcription analysis of human equilibrative nucleoside transporter-1 (hENT1), deoxycytidine kinase (dCK), 5-nucleotidase (5′-NT), cytidine deaminase (CDA), and ribonucleotide reductase subunits M1 and M2 (RRM1 and RRM2) was done by quantitative reverse transcription-PCR in tumor tissue isolated by laser microdissection from surgical or biopsy samples of 102 patients. Association between clinical outcome and gene expression levels was estimated using Kaplan-Meier method and Cox's proportional hazards model. Transport and metabolism had a key role on gemcitabine sensitivity in vitro; moreover, hENT1, dCK, 5′-NT, CDA, RRM1, and RRM2 were detectable in most tumor specimens. hENT1 expression was significantly correlated with clinical outcome. Patients with high levels of hENT1 had a significantly longer overall survival [median, 25.7; 95% confidence interval (95% CI), 17.6-33.7 months in the higher expression tertile versus median, 8.5; 95% CI, 7.0-9.9 months in the lower expression tertile]. Similar results were obtained with disease-free survival and time to disease progression, and the multivariate analysis confirmed the prognostic significance of hENT1. This study suggests that the expression levels of hENT1 may allow the stratification of patients based on their likelihood of survival, thus offering a potential new tool for treatment optimization.

Original languageEnglish
Pages (from-to)3928-3935
Number of pages8
JournalCancer research
Issue number7
Publication statusPublished - 1 Apr 2006

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