Evidence map›Paper›PMID 39245180›Full record

ArticleSLAS discovery : advancing life sciences R & D2024

Development of an automated 3D high content cell screening platform for organoid phenotyping.

Suleyman B Bozal, Greg Sjogren, Antonio P Costa, Joseph S Brown, Shannon Roberts, Dylan Baker, Paul Gabriel, Benjamin T Ristau, Michael Samuels, William F Flynn and 2 more

Abstract read
In one paragraph

Article in SLAS discovery : advancing life sciences R & D, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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.

Suleyman B BozalThe Jackson Laboratory for Genomic Medicine, Farmington, CT, United States; Yale School of Medicine, Yale University, New Haven, CT, United States; Department of Biomedical Engineering, School of Engineering and Applied Sciences, Yale University, New Haven, CT, United States.
Greg SjogrenThe Jackson Laboratory for Genomic Medicine, Farmington, CT, United States.
Antonio P CostaDepartment of Pharmaceutical Sciences, School of Pharmacy, University of Connecticut, Storrs, CT, United States.
Joseph S BrownThe Jackson Laboratory for Genomic Medicine, Farmington, CT, United States.
Shannon RobertsThe Jackson Laboratory for Genomic Medicine, Farmington, CT, United States.
Dylan BakerThe Jackson Laboratory for Genomic Medicine, Farmington, CT, United States.
Paul GabrielThe Jackson Laboratory for Genomic Medicine, Farmington, CT, United States.
Benjamin T RistauDepartment of Urology, UConn Health, Farmington, CT, United States.
Michael SamuelsThe Jackson Laboratory for Genomic Medicine, Farmington, CT, United States.
William F FlynnThe Jackson Laboratory for Genomic Medicine, Farmington, CT, United States.
Paul RobsonThe Jackson Laboratory for Genomic Medicine, Farmington, CT, United States; Departments of Genetics & Genome Sciences and Cell Biology, UConn Health, Farmington, CT, United States. Electronic address: paul.robson@jax.org.
Elise T CourtoisThe Jackson Laboratory for Genomic Medicine, Farmington, CT, United States; Department of Obstetrics and Gynecology, UConn Health, Farmington, CT, United States. Electronic address: elise.courtois@jax.org.

Funding

Shared Resource ManagementP30CA034196 · NCI · JACKSON LABORATORY · PI William Carl Skarnes · 1985 to 2026
$61.9M
CSHL-JAX Patient-Derived Models of Pancreatic Cancer as Systems for Investigating Tumor HeterogeneityU01CA224013 · NCI · COLD SPRING HARBOR LABORATORY · PI ROBSON, PAUL, TUVESON, DAVID A · 2018 to 2022
$4.2M
NCI NIH HHS P30 CA034196NCI NIH HHS U01 CA224013
6 · The paper itself

Abstract

The use of organoid models in biomedical research has grown substantially since their inception. As they gain popularity among scientists seeking more complex and biologically relevant systems, there is a direct need to expand and clarify potential uses of such systems in diverse experimental contexts. Herein we outline a high-content screening (HCS) platform that allows researchers to screen drugs or other compounds against three-dimensional (3D) cell culture systems in a multi-well format (384-well). Furthermore, we compare the quality of robotic liquid handling with manual pipetting and characterize and contrast the phenotypic effects detected by confocal imaging and biochemical assays in response to drug treatment. We show that robotic liquid handling is more consistent and amendable to high throughput experimental designs when compared to manual pipetting due to improved precision and automated randomization capabilities. We also show that image-based techniques are more sensitive to detecting phenotypic changes within organoid cultures than traditional biochemical assays that evaluate cell viability, supporting their integration into organoid screening workflows. Finally, we highlight the enhanced capabilities of confocal imaging in this organoid screening platform as they relate to discerning organoid drug responses in single-well co-cultures of organoids derived from primary human biopsies and patient-derived xenograft (PDX) models. Altogether, this platform enables automated, imaging-based HCS of 3D cellular models in a non-destructive manner, opening the path to complementary analysis through integrated downstream methods.

Indexed as

High-Throughput Screening AssaysOrganoidsPhenotypeAnimalsCell Culture TechniquesCell SurvivalDrug Evaluation, PreclinicalHumansMice3D tissue cultureAutomationHigh-content imagingHigh-content screeningImage-based phenotypingOrganoid co-culture

Identifiers

PMID39245180
PMCPMC12380041

What OpenQuestion holds

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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.