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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…

Overview of attention for article published in Journal of Translational Medicine, September 2014
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Title
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
Published in
Journal of Translational Medicine, September 2014
DOI 10.1186/s12967-014-0248-4
Pubmed ID
Authors

Francesca Tavano, Andrea Fontana, Fabio Pellegrini, Francesca Paola Burbaci, Francesca Rappa, Francesco Cappello, Massimiliano Copetti, Evaristo Maiello, Lucia Lombardi, Paolo Graziano, Manlio Vinciguerra, Fabio Francesco di Mola, Pierluigi di Sebastiano, Angelo Andriulli, Valerio Pazienza

Abstract

BackgroundPancreatic 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.MethodsmRNA 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.ResultsRECPAM 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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 21%
Other 3 16%
Student > Master 3 16%
Researcher 3 16%
Student > Doctoral Student 2 11%
Other 2 11%
Unknown 2 11%
Readers by discipline Count As %
Medicine and Dentistry 8 42%
Biochemistry, Genetics and Molecular Biology 1 5%
Agricultural and Biological Sciences 1 5%
Nursing and Health Professions 1 5%
Psychology 1 5%
Other 1 5%
Unknown 6 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 September 2014.
All research outputs
#20,236,620
of 22,763,032 outputs
Outputs from Journal of Translational Medicine
#3,305
of 3,980 outputs
Outputs of similar age
#200,246
of 238,994 outputs
Outputs of similar age from Journal of Translational Medicine
#62
of 81 outputs
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We're also able to compare this research output to 81 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.