Evidence map›Paper›PMID 37734323›Full record

ArticleCell systems2023

A microwell platform for high-throughput longitudinal phenotyping and selective retrieval of organoids.

Alexandra Sockell, Wing Wong, Scott Longwell, Thy Vu, Kasper Karlsson, Daniel Mokhtari, Julia Schaepe, Yuan-Hung Lo, Vincent Cornelius, Calvin Kuo and 3 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell systems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
3.0field-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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 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

13 authors at 4 institutions in 1 country.

Alexandra SockellDepartment of Genetics, Stanford University, Stanford, CA 94305, USA.
Wing WongDepartment of Genetics, Stanford University, Stanford, CA 94305, USA; Department of Medicine, Stanford University, Stanford, CA 94305, USA.
Scott LongwellDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Thy VuDepartment of Biochemistry, UT Austin, Austin, TX 78712, USA.
Kasper KarlssonDepartment of Genetics, Stanford University, Stanford, CA 94305, USA; Department of Medicine, Stanford University, Stanford, CA 94305, USA.
Daniel MokhtariDepartment of Biochemistry, Stanford University, Stanford, CA 94305, USA.
Julia SchaepeDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Yuan-Hung LoDepartment of Medicine, Stanford University, Stanford, CA 94305, USA.
Vincent CorneliusDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Calvin KuoDepartment of Medicine, Stanford University, Stanford, CA 94305, USA.
David Van ValenDivision of Biology and Bioengineering, California Institute of Technology, Pasadena, CA 91125, USA.
Christina CurtisDepartment of Genetics, Stanford University, Stanford, CA 94305, USA; Department of Medicine, Stanford University, Stanford, CA 94305, USA; Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA; Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94110, USA. Electronic address: cncurtis@stanford.edu.
Polly M FordyceDepartment of Genetics, Stanford University, Stanford, CA 94305, USA; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94110, USA; ChEM-H Institute, Stanford University, Stanford, CA 94305, USA. Electronic address: pfordyce@stanford.edu.
Stanford University · USChan Zuckerberg Initiative (United States) · USCalifornia Institute of Technology · USThe University of Texas at Austin · US

Funding

Forecasting tumor evolution: can the past reveal the future?DP1CA238296 · NCI · STANFORD UNIVERSITY · PI CURTIS, CHRISTINA N · 2018 to 2022
$5.5M
Leveraging spectral encoding for high dimensional biological multiplexingDP2GM123641 · NIGMS · STANFORD UNIVERSITY · PI FORDYCE, POLLY MORRELL · 2016 to 2016
$2.4M
Functional characterization of novel oncogenic loci driving progression and immune response in gastrointestinal cancerR00CA263014 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LO, YUAN-HUNG · 2023 to 2025
$747k
TRANSCRIPTION FACTORS IN INTESTINAL DIFFERENTIATION AND CANCERK00CA212433 · NCI · STANFORD UNIVERSITY · PI LO, YUAN-HUNG · 2017 to 2020
$345k
Functional characterization of novel oncogenic loci driving progression and immune response in gastrointestinal cancerK99CA263014 · NCI · STANFORD UNIVERSITY · PI LO, YUAN-HUNG · 2021 to 2022
$343k
NCI NIH HHS DP1 CA238296NCI NIH HHS K00 CA212433NCI NIH HHS K99 CA263014NCI NIH HHS R00 CA263014NIGMS NIH HHS DP2 GM123641
6 · The paper itself

Abstract

Organoids are powerful experimental models for studying the ontogeny and progression of various diseases including cancer. Organoids are conventionally cultured in bulk using an extracellular matrix mimic. However, bulk-cultured organoids physically overlap, making it impossible to track the growth of individual organoids over time in high throughput. Moreover, local spatial variations in bulk matrix properties make it difficult to assess whether observed phenotypic heterogeneity between organoids results from intrinsic cell differences or differences in the microenvironment. Here, we developed a microwell-based method that enables high-throughput quantification of image-based parameters for organoids grown from single cells, which can further be retrieved from their microwells for molecular profiling. Coupled with a deep learning image-processing pipeline, we characterized phenotypic traits including growth rates, cellular movement, and apical-basal polarity in two CRISPR-engineered human gastric organoid models, identifying genomic changes associated with increased growth rate and changes in accessibility and expression correlated with apical-basal polarity. A record of this paper's transparent peer review process is included in the supplemental information.

Indexed as

Clustered Regularly Interspaced Short Palindromic RepeatsExtracellular MatrixCell MovementGenomicsHumansOrganoidscell polaritydeep learninggenotype-to-phenotypehigh-throughput imagingmicrowell arraysorganoidsquantitative phenotypingsingle-organoid sequencingtumorigenesis

Identifiers

PMID37734323
PMCPMC12126083
OpenAlexW4386885921

What OpenQuestion holds

Textmetadata
LicenceTDM
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.