6533b821fe1ef96bd127af0c
RESEARCH PRODUCT
Modeling interactions between Human Equilibrative Nucleoside Transporter-1 and other factors involved in the response to gemcitabine treatment to predict clinical outcomes in pancreatic ductal adenocarcinoma patients.
Valerio PazienzaMassimiliano CopettiLucia LombardiFrancesca Paola BurbaciFabio PellegriniFrancesca TavanoManlio VinciguerraManlio VinciguerraFabio F. Di MolaAndrea FontanaPierluigi Di SebastianoFrancesco CappelloFrancesca RappaEvaristo MaielloPaolo GrazianoAngelo Andriullisubject
MaleOncologyCHOPEquilibrative nucleoside transporter 1BioinformaticsDeoxycytidineCohort StudiesPancreatic ductal adenocarcinomachemistry.chemical_compoundMedicine(all)Transcription Factor CHOPbiologyDCKGeneral MedicineMiddle AgedSurvival RateDisease ProgressionAdenocarcinomaFemaleMRP1DeoxycytidineMultidrug Resistance-Associated ProteinsCarcinoma Pancreatic Ductalmedicine.drugmedicine.medical_specialtyAntineoplastic AgentsAdenocarcinomaMalignancyhENT1General Biochemistry Genetics and Molecular BiologyEquilibrative Nucleoside Transporter 1Internal medicinemedicineHumansRNA MessengerSurvival rateAgedBiochemistry Genetics and Molecular Biology(all)business.industryResearchRECPAMmedicine.diseaseGemcitabineGemcitabinechemistrybiology.proteinPancreatic ductal adenocarcinoma hENT1 CHOP MRP1 DCK RECPAMbusinessTranscription Factor CHOPCHOPdescription
Background Pancreatic ductal adenocarcinoma (PDAC) is an extremely aggressive malignancy, characterized by largely unsatisfactory responses to the currently available therapeutic strategies. In this study we evaluated the expression of genes involved in gemcitabine uptake in a selected cohort of patients with PDAC, with well-defined clinical-pathological features. Methods mRNA levels of hENT1, CHOP, MRP1 and DCK were evaluated by means of qRT-PCR in matched pairs of tumor and adjacent normal tissue samples collected from PDAC patients treated with gemcitabine after surgical tumor resection. To detect possible interaction between gene expression levels and to identify subgroups of patients at different mortality/progression risk, the RECursive Partitioning and Amalgamation (RECPAM) method was used. Results RECPAM analysis showed that DCK and CHOP were most relevant variables for the identification of patients with different mortality risk, while hENT1 and CHOP were able to identify subgroups of patients with different disease progression risk. Conclusion: hENT1, CHOP, MRP1 and DCK appear correlated to PDAC, and this interaction might influence disease behavior.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2014-09-10 |