Evidence map›Paper›PMID 26649886›Full record

ArticlePloS one2015

Model-Based Tumor Growth Dynamics and Therapy Response in a Mouse Model of De Novo Carcinogenesis.

Charalambos Loizides, Demetris Iacovides, Marios M Hadjiandreou, Gizem Rizki, Achilleas Achilleos, Katerina Strati, Georgios D Mitsis

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. 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
2.2field-weighted citation impact, top 12% 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, 25 citations in OpenAlex.

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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

7 authors at 2 institutions in 3 countries.

Charalambos LoizidesDepartment of Electrical & Electronic Engineering & KIOS Research Center for Intelligent Systems & Networks, University of Cyprus, Nicosia, Cyprus.
Demetris IacovidesDepartment of Biological Sciences, University of Cyprus, Nicosia, Cyprus.
Marios M HadjiandreouDepartment of Electrical & Electronic Engineering & KIOS Research Center for Intelligent Systems & Networks, University of Cyprus, Nicosia, Cyprus.
Gizem RizkiDepartment of Biological Sciences, University of Cyprus, Nicosia, Cyprus.
Achilleas AchilleosDepartment of Electrical & Electronic Engineering & KIOS Research Center for Intelligent Systems & Networks, University of Cyprus, Nicosia, Cyprus.
Katerina StratiDepartment of Biological Sciences, University of Cyprus, Nicosia, Cyprus.
Georgios D MitsisDepartment of Electrical & Electronic Engineering & KIOS Research Center for Intelligent Systems & Networks, University of Cyprus, Nicosia, Cyprus.
University of Cyprus · CYMassachusetts Institute of Technology · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumorigenesis is a complex, multistep process that depends on numerous alterations within the cell and contribution from the surrounding stroma. The ability to model macroscopic tumor evolution with high fidelity may contribute to better predictive tools for designing tumor therapy in the clinic. However, attempts to model tumor growth have mainly been developed and validated using data from xenograft mouse models, which fail to capture important aspects of tumorigenesis including tumor-initiating events and interactions with the immune system. In the present study, we investigate tumor growth and therapy dynamics in a mouse model of de novo carcinogenesis that closely recapitulates tumor initiation, progression and maintenance in vivo. We show that the rate of tumor growth and the effects of therapy are highly variable and mouse specific using a Gompertz model to describe tumor growth and a two-compartment pharmacokinetic/ pharmacodynamic model to describe the effects of therapy in mice treated with 5-FU. We show that inter-mouse growth variability is considerably larger than intra-mouse variability and that there is a correlation between tumor growth and drug kill rates. Our results show that in vivo tumor growth and regression in a double transgenic mouse model are highly variable both within and between subjects and that mathematical models can be used to capture the overall characteristics of this variability. In order for these models to become useful tools in the design of optimal therapy strategies and ultimately in clinical practice, a subject-specific modelling strategy is necessary, rather than approaches that are based on the average behavior of a given subject population which could provide erroneous results.

Indexed as

CarcinogenesisCell Transformation, NeoplasticDisease Models, AnimalMice, TransgenicAnimalsCarcinogensHumansMiceNeoplasmsCarcinogens

Identifiers

PMID26649886
PMCPMC4674149
OpenAlexW2193448558

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.