Evidence map›Paper›PMID 31075118›Full record

ReviewPloS one2019

Integrated cancer tissue engineering models for precision medicine.

Michael E Bregenzer, Eric N Horst, Pooja Mehta, Caymen M Novak, Shreya Raghavan, Catherine S Snyder, Geeta Mehta

Abstract readReview
In one paragraph

Review in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

38 citing papers in PubMed.

  1. Review
  2. Advanced Microfluidics for Single Cell-Based Cancer Research.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  3. Article
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  5. Article
  6. Review
  7. Article
  8. Article
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  11. Article
  12. Review
  13. Article
  14. Article
  15. Engineering complexity in human tissue models of cancer.Advanced drug delivery reviews · 2022
    Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Review
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.

Michael E BregenzerDepartment of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.
Eric N HorstDepartment of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.
Pooja MehtaDepartment of Materials Science and Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.
Caymen M NovakDepartment of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.
Shreya RaghavanDepartment of Materials Science and Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.ORCID 0000-0002-4631-7762
Catherine S SnyderDepartment of Materials Science and Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.ORCID 0000-0002-6636-2798
Geeta MehtaDepartment of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.ORCID 0000-0001-5967-6425

Funding

XenograftP30CA046592 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Eric R. Fearon · 1988 to 2026
$178.2M
Tissue Engineering and RegenerationT32DE007057 · NIDCR · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DAVID H. KOHN · 1985 to 2026
$17.3M
NCI NIH HHS P30 CA046592NIDCR NIH HHS T32 DE007057
6 · The paper itself

Abstract

Tumors are not merely cancerous cells that undergo mindless proliferation. Rather, they are highly organized and interconnected organ systems. Tumor cells reside in complex microenvironments in which they are subjected to a variety of physical and chemical stimuli that influence cell behavior and ultimately the progression and maintenance of the tumor. As cancer bioengineers, it is our responsibility to create physiologic models that enable accurate understanding of the multi-dimensional structure, organization, and complex relationships in diverse tumor microenvironments. Such models can greatly expedite clinical discovery and translation by closely replicating the physiological conditions while maintaining high tunability and control of extrinsic factors. In this review, we discuss the current models that target key aspects of the tumor microenvironment and their role in cancer progression. In order to address sources of experimental variation and model limitations, we also make recommendations for methods to improve overall physiologic reproducibility, experimental repeatability, and rigor within the field. Improvements can be made through an enhanced emphasis on mathematical modeling, standardized in vitro model characterization, transparent reporting of methodologies, and designing experiments with physiological metrics. Taken together these considerations will enhance the relevance of in vitro tumor models, biological understanding, and accelerate treatment exploration ultimately leading to improved clinical outcomes. Moreover, the development of robust, user-friendly models that integrate important stimuli will allow for the in-depth study of tumors as they undergo progression from non-transformed primary cells to metastatic disease and facilitate translation to a wide variety of biological and clinical studies.

Indexed as

Disease ProgressionHumansModels, BiologicalNeoplasmsPrecision MedicineTissue EngineeringTumor Microenvironment

Identifiers

PMID31075118
PMCPMC6510431

What Socratic 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 Socratic graph.