Evidence map›Paper›PMID 33203360›Full record

ArticleBMC bioinformatics2020

A computational diffusion model to study antibody transport within reconstructed tumor microenvironments.

Ana Luísa Cartaxo, Jaime Almeida, Emilio J Gualda, Maria Marsal, Pablo Loza-Alvarez, Catarina Brito, Inês A Isidro

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 28% 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

5 citing papers in PubMed, 11 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 3 institutions in 2 countries.

Ana Luísa CartaxoiBET, Instituto de Biologia Experimental e Tecnológica, Oeiras, Portugal.
Jaime AlmeidaDepartamento de Geologia, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal.
Emilio J GualdaICFO, Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Castelldefels, Barcelona, Spain.
Maria MarsalICFO, Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Castelldefels, Barcelona, Spain.
Pablo Loza-AlvarezICFO, Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Castelldefels, Barcelona, Spain.
Catarina BritoiBET, Instituto de Biologia Experimental e Tecnológica, Oeiras, Portugal.
Inês A IsidroiBET, Instituto de Biologia Experimental e Tecnológica, Oeiras, Portugal. iaisidro@ibet.pt.ORCID http://orcid.org/0000-0002-0237-5805
Institute of Photonic Sciences · ESInstituto de Biologia Experimental e Tecnológica · PTUniversity of Lisbon · PT

Funding

Fundação para a Ciência e a Tecnologia PD/BD/114047/2015Fundação para a Ciência e a Tecnologia (PT) UIDB/04462/2020Generalitat de Catalunya CERCA programHorizon 2020 LASER LAB Europe 654148Ministerio de Economía y Competitividad RYC-2015-1793Ministerio de Economía y Competitividad SEV-2015-0522
6 · The paper itself

Abstract

backgroundAntibodies revolutionized cancer treatment over the past decades. Despite their successfully application, there are still challenges to overcome to improve efficacy, such as the heterogeneous distribution of antibodies within tumors. Tumor microenvironment features, such as the distribution of tumor and other cell types and the composition of the extracellular matrix may work together to hinder antibodies from reaching the target tumor cells. To understand these interactions, we propose a framework combining in vitro and in silico models. We took advantage of in vitro cancer models previously developed by our group, consisting of tumor cells and fibroblasts co-cultured in 3D within alginate capsules, for reconstruction of tumor microenvironment features.

resultsIn this work, an experimental-computational framework of antibody transport within alginate capsules was established, assuming a purely diffusive transport, combined with an exponential saturation effect that mimics the saturation of binding sites on the cell surface. Our tumor microenvironment in vitro models were challenged with a fluorescent antibody and its transport recorded using light sheet fluorescence microscopy. Diffusion and saturation parameters of the computational model were adjusted to reproduce the experimental antibody distribution, with root mean square error under 5%. This computational framework is flexible and can simulate different random distributions of tumor microenvironment elements (fibroblasts, cancer cells and collagen fibers) within the capsule. The random distribution algorithm can be tuned to follow the general patterns observed in the experimental models.

conclusionsWe present a computational and microscopy framework to track and simulate antibody transport within the tumor microenvironment that complements the previously established in vitro models platform. This framework paves the way to the development of a valuable tool to study the influence of different components of the tumor microenvironment on antibody transport.

Indexed as

Computer SimulationAlgorithmsAntibodiesCell CountCell Line, TumorDiffusionFluorescenceHumansNeoplasmsProtein TransportStochastic ProcessesTumor MicroenvironmentAntibodies3D in vitro cancer modelsAntibody diffusionComputational modellingLight sheet fluorescence microscopyTumor microenvironment

Identifiers

PMID33203360
PMCPMC7672975
OpenAlexW3103016901

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.