Evidence map›Paper›PMID 34822927›Full record

ReviewAdvanced drug delivery reviews2022

Strategies for developing complex multi-component in vitro tumor models: Highlights in glioblastoma.

Thomas J DePalma, Hemamylammal Sivakumar, Aleksander Skardal

Abstract readReview
In one paragraph

Review in Advanced drug delivery reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
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

14 citing papers in PubMed.

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  14. A predictive microfluidic model of human glioblastoma to assess trafficking of blood-brain barrier-penetrant nanoparticles.Proceedings of the National Academy of Sciences of the United States of America · 2022
    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

3 authors.

Thomas J DePalmaDepartment of Biomedical Engineering, The Ohio State University, Columbus, OH 43210, USA.
Hemamylammal SivakumarDepartment of Biomedical Engineering, The Ohio State University, Columbus, OH 43210, USA.
Aleksander SkardalDepartment of Biomedical Engineering, The Ohio State University, Columbus, OH 43210, USA; The Ohio State University and Arthur G. James Comprehensive Cancer Center, Columbus, OH 43210, USA.

Funding

Predicting Tumor Heterogeneity Evolution After Therapy In Patient-Derived Ex Vivo Glioblastoma OrganoidsR21CA229027 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI SKARDAL, ALEKSANDER, STROWD, ROY ERVIN · 2018 to 2019
$597k
NCI NIH HHS R21 CA229027
6 · The paper itself

Abstract

In recent years, many research groups have begun to utilize bioengineered in vitro models of cancer to study mechanisms of disease progression, test drug candidates, and develop platforms to advance personalized drug treatment options. Due to advances in cell and tissue engineering over the last few decades, there are now a myriad of tools that can be used to create such in vitro systems. In this review, we describe the considerations one must take when developing model systems that accurately mimic the in vivo tumor microenvironment (TME) and can be used to answer specific scientific questions. We will summarize the importance of cell sourcing in models with one or multiple cell types and outline the importance of choosing biomaterials that accurately mimic the native extracellular matrix (ECM) of the tumor or tissue that is being modeled. We then provide examples of how these two components can be used in concert in a variety of model form factors and conclude by discussing how biofabrication techniques such as bioprinting and organ-on-a-chip fabrication can be used to create highly reproducible complex in vitro models. Since this topic has a broad range of applications, we use the final section of the review to dive deeper into one type of cancer, glioblastoma, to illustrate how these components come together to further our knowledge of cancer biology and move us closer to developing novel drugs and systems that improve patient outcomes.

Indexed as

AnimalsBiocompatible MaterialsBioprintingExtracellular MatrixGlioblastomaHumansIn Vitro TechniquesLab-On-A-Chip DevicesPrecision MedicineTissue EngineeringTumor MicroenvironmentBiocompatible MaterialsBiofabricationBiomaterialsBioprintingIn vitroOrganoidsOrgan-on-a-chipTumor modelsTumor-on-a-chip

Identifiers

PMID34822927
PMCPMC10560581

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.