Evidence map›Paper›PMID 31431182›Full record

ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2019

Applicability of drug response metrics for cancer studies using biomaterials.

Elizabeth A Brooks, Sualyneth Galarza, Maria F Gencoglu, R Chase Cornelison, Jennifer M Munson, Shelly R Peyton

Open access · greenAbstract read
In one paragraph

Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
3.3field-weighted citation impact, top 8% 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

43 citing papers in PubMed, 66 citations in OpenAlex.

  1. Trial
  2. Article
  3. Harmonization and integration of pharmacogenomics screens.Bioinformatics (Oxford, England) · 2026
    Article
  4. Article
  5. Article
  6. Genetic and Cheminformatic Characterization ofACS infectious diseases · 2025
    Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Engineered bone marrow as a clinically relevant ex vivo model for primary bone cancer research and drug screening.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  20. 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

6 authors at 2 institutions in 1 country.

Elizabeth A BrooksDepartment of Chemical Engineering, University of Massachusetts Amherst, 240 Thatcher Road, Amherst, MA 01003-9364, USA.
Sualyneth GalarzaDepartment of Chemical Engineering, University of Massachusetts Amherst, 240 Thatcher Road, Amherst, MA 01003-9364, USA.
Maria F GencogluDepartment of Chemical Engineering, University of Massachusetts Amherst, 240 Thatcher Road, Amherst, MA 01003-9364, USA.
R Chase CornelisonDepartment of Biomedical Engineering and Mechanics, Virginia Tech, 325 Stanger Street, Blacksburg, VA 24061, USA.
Jennifer M MunsonDepartment of Biomedical Engineering and Mechanics, Virginia Tech, 325 Stanger Street, Blacksburg, VA 24061, USA.
Shelly R PeytonDepartment of Chemical Engineering, University of Massachusetts Amherst, 240 Thatcher Road, Amherst, MA 01003-9364, USA.
University of Massachusetts Amherst · USVirginia Tech · US

Funding

CHEMISTRY-BIOLOGY INTERFACE PREDOCTORAL TRAINING GRANTST32GM008515 · NIGMS · UNIVERSITY OF MASSACHUSETTS AMHERST · PI THOMPSON, LYNMARIE K. · 1995 to 2020
$4.3M
Interstitial Fluid Flow Regulates Glioma Cell InvasionR37CA222563 · NCI · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI MUNSON, JENNIFER M · 2018 to 2024
$4.0M
Tissue-specific stem cells and breast cancer tissue tropism in bioengineered microenvironmentsDP2CA186573 · NCI · UNIVERSITY OF MASSACHUSETTS AMHERST · PI PEYTON, SHELLY R. · 2013 to 2015
$2.6M
NCI NIH HHS DP2 CA186573NCI NIH HHS R37 CA222563NIGMS NIH HHS T32 GM008515
6 · The paper itself

Abstract

Bioengineers have built models of the tumour microenvironment (TME) in which to study cell-cell interactions, mechanisms of cancer growth and metastasis, and to test new therapies. These models allow researchers to culture cells in conditions that include features of the in vivo TME implicated in regulating cancer progression, such as extracellular matrix (ECM) stiffness, integrin binding to the ECM, immune and stromal cells, growth factor and cytokine depots, and a three-dimensional geometry more representative of the in vivo TME than tissue culture polystyrene (TCPS). These biomaterials could be particularly useful for drug screening applications to make better predictions of efficacy, offering better translation to preclinical models and clinical trials. However, it can be challenging to compare drug response reports across different biomaterial platforms in the current literature. This is, in part, a result of inconsistent reporting and improper use of drug response metrics, and vast differences in cell growth rates across a large variety of biomaterial designs. This study attempts to clarify the definitions of drug response measurements used in the field, and presents examples in which these measurements can and cannot be applied. We suggest as best practice to measure the growth rate of cells in the absence of drug, and follow our 'decision tree' when reporting drug response metrics. This article is part of a discussion meeting issue 'Forces in cancer: interdisciplinary approaches in tumour mechanobiology'.

Indexed as

Antineoplastic AgentsBenchmarkingBiocompatible MaterialsCell CommunicationExtracellular MatrixHumansNeoplasmsTumor MicroenvironmentAntineoplastic AgentsBiocompatible Materialsbioengineeringbreast cancerdrug resistanceextracellular matrixovarian cancertumour microenvironment

Identifiers

PMID31431182
PMCPMC6627013
OpenAlexW2955021173

What OpenQuestion holds

Textmetadata
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.