Evidence map›Paper›PMID 37086259›Full record

ArticleAdvanced healthcare materials2023

An Automation Workflow for High-Throughput Manufacturing and Analysis of Scaffold-Supported 3D Tissue Arrays.

Ruonan Cao, Nancy T Li, Simon Latour, Jose L Cadavid, Cassidy M Tan, Ari Forman, Hartland W Jackson, Alison P McGuigan

Open access · bronzeAbstract read
In one paragraph

Article in Advanced healthcare materials, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.1field-weighted citation impact, top 26% 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

6 citing papers in PubMed, 10 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

8 authors at 3 institutions in 1 country.

Ruonan CaoInstitute of Biomedical Engineering, University of Toronto, 164 College Street, Toronto, ON, M5S 3G9, Canada.ORCID 0000-0003-4947-8905
Nancy T LiDepartment of Chemical Engineering and Applied Chemistry, University of Toronto, 200 College Street, Toronto, ON, M5R 3S5, Canada.ORCID 0000-0002-2663-5245
Simon LatourInstitute of Biomedical Engineering, University of Toronto, 164 College Street, Toronto, ON, M5S 3G9, Canada.ORCID 0000-0002-7300-354X
Jose L CadavidInstitute of Biomedical Engineering, University of Toronto, 164 College Street, Toronto, ON, M5S 3G9, Canada.ORCID 0000-0002-9966-7352
Cassidy M TanDepartment of Chemical Engineering and Applied Chemistry, University of Toronto, 200 College Street, Toronto, ON, M5R 3S5, Canada.
Ari FormanLunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, 600 University Ave, Toronto, ON, M5G 1X5, Canada.
Hartland W JacksonLunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, 600 University Ave, Toronto, ON, M5G 1X5, Canada.ORCID 0000-0001-6423-2415
Alison P McGuiganInstitute of Biomedical Engineering, University of Toronto, 164 College Street, Toronto, ON, M5S 3G9, Canada.ORCID 0000-0003-2803-0917
University of Toronto · CAUniversity of New Brunswick · CAMount Sinai Hospital · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patient-derived organoids have emerged as a useful tool to model tumour heterogeneity. Scaling these complex culture models while enabling stratified analysis of different cellular sub-populations, however, remains a challenge. One strategy to enable higher throughput organoid cultures is the scaffold-supported platform for organoid-based tissues (SPOT). SPOT allows the generation of flat, thin, and dimensionally-defined microtissues in both 96- and 384-well plate footprints that are compatible with longitudinal image-based readouts. SPOT is currently manufactured manually, however, limiting scalability. In this study, an automation approach to engineer tumour-mimetic 3D microtissues in SPOT using a liquid handler is optimized and comparable within- and between-sample variation to standard manual manufacturing is shown. Further, a liquid handler-supported cell extraction protocol to support single-cell-based end-point analysis using high-throughput flow cytometry and multiplexed cytometry by time of flight is developed. As a proof-of-value demonstration, 3D complex tissues containing different proportions of tumour and stromal cells are generated to probe the reciprocal impact of co-culture. It is also demonstrated that primary patient-derived organoids can be incorporated into the pipeline to capture patient-level tumour heterogeneity. It is envisioned that this automated 96/384-SPOT workflow will provide opportunities for future applications in high-throughput screening for novel personalized therapeutic targets.

Indexed as

NeoplasmsAutomationCoculture TechniquesHigh-Throughput Screening AssaysHumansOrganoidsWorkflow3D in vitro cancer modelsautomationtumour microenvironments

Identifiers

PMID37086259
PMCPMC11468893
OpenAlexW4366742258

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.