Evidence map›Paper›PMID 23239976›Full record

ArticlePloS one2012

Algorithmic modeling quantifies the complementary contribution of metabolic inhibitions to gemcitabine efficacy.

Ozan Kahramanoğullari, Gianluca Fantaccini, Paola Lecca, Daniele Morpurgo, Corrado Priami

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-weighted citation impact, top 33% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. Graphical Modeling Meets Systems Pharmacology.Gene regulation and systems biology · 2017
    Article
  4. Article
  5. The development of orally administrable gemcitabine prodrugs with D-enantiomer amino acids: enhanced membrane permeability and enzymatic stability.European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V · 2014
    Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Ozan KahramanoğullariThe Microsoft Research-University of Trento Centre for Computational and Systems Biology, Rovereto (Trento), Italy. ozan@cosbi.eu
Gianluca Fantaccini
Paola Lecca
Daniele Morpurgo
Corrado Priami
University of Trento · ITThe Microsoft Research - University of Trento Centre for Computational and Systems Biology · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gemcitabine (2,2-difluorodeoxycytidine, dFdC) is a prodrug widely used for treating various carcinomas. Gemcitabine exerts its clinical effect by depleting the deoxyribonucleotide pools, and incorporating its triphosphate metabolite (dFdC-TP) into DNA, thereby inhibiting DNA synthesis. This process blocks the cell cycle in the early S phase, eventually resulting in apoptosis. The incorporation of gemcitabine into DNA takes place in competition with the natural nucleoside dCTP. The mechanisms of indirect competition between these cascades for common resources are given with the race for DNA incorporation; in clinical studies dedicated to singling out mechanisms of resistance, ribonucleotide reductase (RR) and deoxycytidine kinase (dCK) and human equilibrative nucleoside transporter1 (hENT1) have been associated to efficacy of gemcitabine with respect to their roles in the synthesis cascades of dFdC-TP and dCTP. However, the direct competition, which manifests itself in terms of inhibitions between these cascades, remains to be quantified. We propose an algorithmic model of gemcitabine mechanism of action, verified with respect to independent experimental data. We performed in silico experiments in different virtual conditions, otherwise difficult in vivo, to evaluate the contribution of the inhibitory mechanisms to gemcitabine efficacy. In agreement with the experimental data, our model indicates that the inhibitions due to the association of dCTP with dCK and the association of gemcitabine diphosphate metabolite (dFdC-DP) with RR play a key role in adjusting the efficacy. While the former tunes the catalysis of the rate-limiting first phosphorylation of dFdC, the latter is responsible for depletion of dCTP pools, thereby contributing to gemcitabine efficacy with a dependency on nucleoside transport efficiency. Our simulations predict the existence of a continuum of non-efficacy to high-efficacy regimes, where the levels of dFdC-TP and dCTP are coupled in a complementary manner, which can explain the resistance to this drug in some patients.

Indexed as

AlgorithmsComputer SimulationDeoxycytidineDeoxycytidine KinaseDeoxycytosine NucleotidesDNAEquilibrative Nucleoside Transporter 1GemcitabineHumansModels, TheoreticalNeoplasmsRibonucleotide Reductases2'-deoxycytidine 5'-triphosphateDeoxycytidineDeoxycytidine KinaseDeoxycytosine NucleotidesDNAEquilibrative Nucleoside Transporter 1GemcitabineRibonucleotide ReductasesSLC29A1 protein, human

Identifiers

PMID23239976
PMCPMC3519828
OpenAlexW1975075402

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.