Evidence map›Paper›PMID 31138163›Full record

ArticleBMC cancer2019

An image-based assay to quantify changes in proliferation and viability upon drug treatment in 3D microenvironments.

Vasanth S Murali, Bo-Jui Chang, Reto Fiolka, Gaudenz Danuser, Murat Can Cobanoglu, Erik S Welf

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.7field-weighted citation impact, top 17% 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

15 citing papers in PubMed, 31 citations in OpenAlex.

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  8. Three-Dimensional Spheroids for Cancer Research.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  9. 3D cancer models: One step closer toFrontiers in immunology · 2023
    Review
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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

6 authors at 1 institution in 1 country.

Vasanth S MuraliDepartment of Cell Biology, UT Southwestern Medical Center, Dallas, TX, USA.
Bo-Jui ChangDepartment of Cell Biology, UT Southwestern Medical Center, Dallas, TX, USA.
Reto FiolkaDepartment of Cell Biology, UT Southwestern Medical Center, Dallas, TX, USA.
Gaudenz DanuserDepartment of Cell Biology, UT Southwestern Medical Center, Dallas, TX, USA.
Murat Can CobanogluLyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX, USA.
Erik S WelfDepartment of Cell Biology, UT Southwestern Medical Center, Dallas, TX, USA. Erik.Welf@UTSouthwestern.edu.ORCID http://orcid.org/0000-0002-5968-3323
Southwestern Medical Center · US

Funding

Multiscale microscope for 3D cancer imaging in model organisms and organoidsR33CA235254 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI FIOLKA, RETO PAUL · 2019 to 2021
$930k
Mechanisms of melanoma migration and survival in 3D microenvironmentsK25CA204526 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI WELF, ERIK S · 2016 to 2020
$585k
National Institutes of Health K25CA204526NCI NIH HHS K25 CA204526NCI NIH HHS R33 CA235254
6 · The paper itself

Abstract

backgroundEvery biological experiment requires a choice of throughput balanced against physiological relevance. Most primary drug screens neglect critical parameters such as microenvironmental conditions, cell-cell heterogeneity, and specific readouts of cell fate for the sake of throughput.

methodsHere we describe a methodology to quantify proliferation and viability of single cells in 3D culture conditions by leveraging automated microscopy and image analysis to facilitate reliable and high-throughput measurements. We detail experimental conditions that can be adjusted to increase either throughput or robustness of the assay, and we provide a stand alone image analysis program for users who wish to implement this 3D drug screening assay in high throughput.

resultsWe demonstrate this approach by evaluating a combination of RAF and MEK inhibitors on melanoma cells, showing that cells cultured in 3D collagen-based matrices are more sensitive than cells grown in 2D culture, and that cell proliferation is much more sensitive than cell viability. We also find that cells grown in 3D cultured spheroids exhibit equivalent sensitivity to single cells grown in 3D collagen, suggesting that for the case of melanoma, a 3D single cell model may be equally effective for drug identification as 3D spheroids models. The single cell resolution of this approach enables stratification of heterogeneous populations of cells into differentially responsive subtypes upon drug treatment, which we demonstrate by determining the effect of RAK/MEK inhibition on melanoma cells co-cultured with fibroblasts. Furthermore, we show that spheroids grown from single cells exhibit dramatic heterogeneity to drug response, suggesting that heritable drug resistance can arise stochastically in single cells but be retained by subsequent generations.

conclusionIn summary, image-based analysis renders cell fate detection robust, sensitive, and high-throughput, enabling cell fate evaluation of single cells in more complex microenvironmental conditions.

Indexed as

Cell Line, TumorCell ProliferationCell SurvivalCoculture TechniquesDrug Resistance, NeoplasmDrug Screening Assays, AntitumorFibroblastsHigh-Throughput Screening AssaysHumansImage Processing, Computer-AssistedMelanomaMitogen-Activated Protein Kinase KinasesProtein Kinase Inhibitorsraf KinasesSingle-Cell AnalysisSpheroids, CellularMitogen-Activated Protein Kinase KinasesProtein Kinase Inhibitorsraf KinasesCell fateDrug screenExtracellular matrixHigh throughputImage analysisMAPK pathwayMelanomaOrganoidRAF inhibitorSpheroid

Identifiers

PMID31138163
PMCPMC6537405
OpenAlexW2947104118

What OpenQuestion 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 OpenQuestion graph.