Evidence map›Paper›PMID 27906188›Full record

ArticleCell death & disease2016

Large-scale pharmacological profiling of 3D tumor models of cancer cells.

Lesley A Mathews Griner, Xiaohu Zhang, Rajarshi Guha, Crystal McKnight, Ian S Goldlust, Madhu Lal-Nag, Kelli Wilson, Sam Michael, Steve Titus, Paul Shinn and 2 more

Open access · goldAbstract read
In one paragraph

Article in Cell death & disease, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

23 citing papers in PubMed, 30 citations in OpenAlex.

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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

12 authors at 2 institutions in 1 country.

Lesley A Mathews GrinerNational Center for Advancing Translational Sciences, Division of Pre-Clinical Innovation, National Institutes of Health, Bethesda, MD, USA.
Xiaohu ZhangNational Center for Advancing Translational Sciences, Division of Pre-Clinical Innovation, National Institutes of Health, Bethesda, MD, USA.
Rajarshi GuhaNational Center for Advancing Translational Sciences, Division of Pre-Clinical Innovation, National Institutes of Health, Bethesda, MD, USA.
Crystal McKnightNational Center for Advancing Translational Sciences, Division of Pre-Clinical Innovation, National Institutes of Health, Bethesda, MD, USA.
Ian S GoldlustNational Center for Advancing Translational Sciences, Division of Pre-Clinical Innovation, National Institutes of Health, Bethesda, MD, USA.
Madhu Lal-NagNational Center for Advancing Translational Sciences, Division of Pre-Clinical Innovation, National Institutes of Health, Bethesda, MD, USA.
Kelli WilsonNational Center for Advancing Translational Sciences, Division of Pre-Clinical Innovation, National Institutes of Health, Bethesda, MD, USA.
Sam MichaelNational Center for Advancing Translational Sciences, Division of Pre-Clinical Innovation, National Institutes of Health, Bethesda, MD, USA.
Steve TitusNational Center for Advancing Translational Sciences, Division of Pre-Clinical Innovation, National Institutes of Health, Bethesda, MD, USA.
Paul ShinnNational Center for Advancing Translational Sciences, Division of Pre-Clinical Innovation, National Institutes of Health, Bethesda, MD, USA.
Craig J ThomasNational Center for Advancing Translational Sciences, Division of Pre-Clinical Innovation, National Institutes of Health, Bethesda, MD, USA.
Marc FerrerNational Center for Advancing Translational Sciences, Division of Pre-Clinical Innovation, National Institutes of Health, Bethesda, MD, USA.
National Center for Advancing Translational Sciences · USNational Institutes of Health · US

Funding

Research Services Section (RSS)ZICTR000242 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI WILSON, KELLI · 2015 to 2025
$64.9M
Trans-NIH RNAi Facility (TNRF)ZICTR000041 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI CHENG, KEN · 2015 to 2025
$9.4M
HTS enabled examination of drug combinationsZIATR000047 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI THOMAS, CRAIG · 2015 to 2025
$7.1M
6 · The paper itself

Abstract

The discovery of chemotherapeutic agents for the treatment of cancer commonly uses cell proliferation assays in which cells grow as two-dimensional (2D) monolayers. Compounds identified using 2D monolayer assays often fail to advance during clinical development, most likely because these assays do not reproduce the cellular complexity of tumors and their microenvironment in vivo. The use of three-dimensional (3D) cellular systems have been explored as enabling more predictive in vitro tumor models for drug discovery. To date, small-scale screens have demonstrated that pharmacological responses tend to differ between 2D and 3D cancer cell growth models. However, the limited scope of screens using 3D models has not provided a clear delineation of the cellular pathways and processes that differentially regulate cell survival and death in the different in vitro tumor models. Here we sought to further understand the differences in pharmacological responses between cancer tumor cells grown in different conditions by profiling a large collection of 1912 chemotherapeutic agents. We compared pharmacological responses obtained from cells cultured in traditional 2D monolayer conditions with those responses obtained from cells forming spheres versus cells already in 3D spheres. The target annotation of the compound library screened enabled the identification of those key cellular pathways and processes that when modulated by drugs induced cell death in all growth conditions or selectively in the different cell growth models. In addition, we also show that many of the compounds targeting these key cellular functions can be combined to produce synergistic cytotoxic effects, which in many cases differ in the magnitude of their synergism depending on the cellular model and cell type. The results from this work provide a high-throughput screening framework to profile the responses of drugs both as single agents and in pairwise combinations in 3D sphere models of cancer cells.

Indexed as

Models, BiologicalAntineoplastic AgentsApoptosisCell Culture TechniquesCell Line, TumorCell ProliferationDose-Response Relationship, DrugHumansSpheroids, CellularAntineoplastic Agents

Identifiers

PMID27906188
PMCPMC5261027
OpenAlexW2557643461

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.