Evidence map›Paper›PMID 29228953›Full record

ArticleBMC systems biology2017

A simple and accurate rule-based modeling framework for simulation of autocrine/paracrine stimulation of glioblastoma cell motility and proliferation by L1CAM in 2-D culture.

Justin Caccavale, David Fiumara, Michael Stapf, Liedeke Sweitzer, Hannah J Anderson, Jonathan Gorky, Prasad Dhurjati, Deni S Galileo

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC systems biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 48% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
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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

8 authors at 3 institutions in 1 country.

Justin CaccavaleDepartment of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE, 19716, USA.
David FiumaraDepartment of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE, 19716, USA.
Michael StapfDepartment of Mathematical Sciences, University of Delaware, Newark, DE, 19716, USA.
Liedeke SweitzerDepartment of Mathematical Sciences, University of Delaware, Newark, DE, 19716, USA.
Hannah J AndersonDepartment of Biological Sciences, University of Delaware, Newark, DE, 19716, USA.
Jonathan GorkyDepartment of Pathology, Anatomy, and Cell Biology, Thomas Jefferson University, Philadelphia, PA, USA.
Prasad DhurjatiDepartment of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE, 19716, USA.
Deni S GalileoDepartment of Biological Sciences, University of Delaware, Newark, DE, 19716, USA. dgalileo@udel.edu.ORCID http://orcid.org/0000-0002-0089-2198
University of Delaware · USChristiana Care Health System · USThomas Jefferson University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGlioblastoma multiforme (GBM) is a devastating brain cancer for which there is no known cure. Its malignancy is due to rapid cell division along with high motility and invasiveness of cells into the brain tissue. Simple 2-dimensional laboratory assays (e.g., a scratch assay) commonly are used to measure the effects of various experimental perturbations, such as treatment with chemical inhibitors. Several mathematical models have been developed to aid the understanding of the motile behavior and proliferation of GBM cells. However, many are mathematically complicated, look at multiple interdependent phenomena, and/or use modeling software not freely available to the research community. These attributes make the adoption of models and simulations of even simple 2-dimensional cell behavior an uncommon practice by cancer cell biologists.

resultsHerein, we developed an accurate, yet simple, rule-based modeling framework to describe the in vitro behavior of GBM cells that are stimulated by the L1CAM protein using freely available NetLogo software. In our model L1CAM is released by cells to act through two cell surface receptors and a point of signaling convergence to increase cell motility and proliferation. A simple graphical interface is provided so that changes can be made easily to several parameters controlling cell behavior, and behavior of the cells is viewed both pictorially and with dedicated graphs. We fully describe the hierarchical rule-based modeling framework, show simulation results under several settings, describe the accuracy compared to experimental data, and discuss the potential usefulness for predicting future experimental outcomes and for use as a teaching tool for cell biology students.

conclusionsIt is concluded that this simple modeling framework and its simulations accurately reflect much of the GBM cell motility behavior observed experimentally in vitro in the laboratory. Our framework can be modified easily to suit the needs of investigators interested in other similar intrinsic or extrinsic stimuli that influence cancer or other cell behavior. This modeling framework of a commonly used experimental motility assay (scratch assay) should be useful to both researchers of cell motility and students in a cell biology teaching laboratory.

Indexed as

Cell MovementCell ProliferationComputer SimulationSoftwareAutocrine CommunicationCell Culture TechniquesGlioblastomaHumansNeural Cell Adhesion Molecule L1Paracrine CommunicationTumor Cells, CulturedNeural Cell Adhesion Molecule L1Biological modeling frameworkCancerCell cultureCell motilityGlioblastomaL1CAMNetLogo2-DRule-based modelScratch assay

Identifiers

PMID29228953
PMCPMC5725844
OpenAlexW2775485833

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.