Evidence map›Paper›PMID 23710709›Full record

ArticleBMC medicine2013

Tissue-derived mesenchymal stromal cells used as vehicles for anti-tumor therapy exert different in vivo effects on migration capacity and tumor growth.

Carolina Belmar-Lopez, Gracia Mendoza, Daniel Oberg, Jerome Burnet, Carlos Simon, Irene Cervello, Maite Iglesias, Juan Carlos Ramirez, Pilar Lopez-Larrubia, Miguel Quintanilla and 1 more

Open access · goldAbstract readComparative Study
In one paragraph

Article in BMC medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 pooled it
4.1field-weighted citation impact, top 5% 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

44 citing papers in PubMed, 1 synthesis or guideline pooled it, 71 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Engineered tumor-tropic mesenchymal stem cells as targeted therapeutic delivery systems for refractory Ovarian cancer.Journal of controlled release : official journal of the Controlled Release Society · 2026
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  20. NoninvasiveWorld journal of stem cells · 2020
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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

11 authors at 8 institutions in 3 countries.

Carolina Belmar-LopezInstituto Aragones de Ciencias de la Salud-IIS Aragon, Zaragoza, Spain.
Gracia Mendoza
Daniel Oberg
Jerome Burnet
Carlos Simon
Irene Cervello
Maite Iglesias
Juan Carlos Ramirez
Pilar Lopez-Larrubia
Miguel Quintanilla
Pilar Martin-Duque
Instituto de Investigaciones Biomédicas Sols-Morreale · ESInstituto de Investigación Sanitaria Aragón · ESUniversitat de València · ESFundacion Agencia Aragonesa para la Investigacion y el Desarrollo · ESQueen Mary University of London · GBSpanish National Centre for Cardiovascular Research · ESUniversidad Francisco de Vitoria · ESUppsala University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMesenchymal stem cells (MSCs) have been promoted as an attractive option to use as cellular delivery vehicles to carry anti-tumor agents, owing to their ability to home into tumor sites and secrete cytokines. Multiple isolated populations have been described as MSCs, but despite extensive in vitro characterization, little is known about their in vivo behavior.The aim of this study was to investigate the efficacy and efficiency of different MSC lineages derived from five different sources (bone marrow, adipose tissue, epithelial endometrium, stroma endometrium, and amniotic membrane), in order to assess their adequacy for cell-based anti-tumor therapies. Our study shows the crucial importance of understanding the interaction between MSCs and tumor cells, and provides both information and a methodological approach, which could be used to develop safer and more accurate targeted therapeutic applications.

methodsWe first measured the in vivo migration capacity and effect on tumor growth of the different MSCs using two imaging techniques: (i) single-photon emission computed tomography combined with computed tomography (SPECT-CT), using the human sodium iodine symporter gene (hNIS) and (ii) magnetic resonance imaging using superparamagnetic iron oxide. We then sought correlations between these parameters and expression of pluripotency-related or migration-related genes.

resultsOur results show that migration of human bone marrow-derived MSCs was significantly reduced and slower than that obtained with the other MSCs assayed and also with human induced pluripotent stem cells (hiPSCs). The qPCR data clearly show that MSCs and hiPSCs exert a very different pluripotency pattern, which correlates with the differences observed in their engraftment capacity and with their effects on tumor growth.

conclusionThis study reveals differences in MSC recruitment/migration toward the tumor site and the corresponding effects on tumor growth. Three observations stand out: 1) tracking of the stem cell is essential to check the safety and efficacy of cell therapies; 2) the MSC lineage to be used in the cell therapy needs to be carefully chosen to balance efficacy and safety for a particular tumor type; and 3) different pluripotency and mobility patterns can be linked to the engraftment capacity of the MSCs, and should be checked as part of the clinical characterization of the lineage.

Indexed as

AnimalsCell DifferentiationCell MovementCells, CulturedFemaleHeLa CellsHumansInduced Pluripotent Stem CellsMagnetic Resonance ImagingMesenchymal Stem CellsMesenchymal Stem Cell TransplantationMiceMice, Inbred BALB CMice, NudeNeoplasmsTomography, Emission-Computed, Single-Photon

Identifiers

PMID23710709
PMCPMC3670996
OpenAlexW2171794027

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.