Evidence map›Paper›PMID 34893868›Full record

ArticleNucleic acids research2022

Grouped-seq for integrated phenotypic and transcriptomic screening of patient-derived tumor organoids.

Yushuai Wu, Kaiyi Li, Yaqian Li, Tao Sun, Chang Liu, Chunhui Dong, Tian Zhao, Decong Tang, Xiaojie Chen, Xiaofang Chen and 1 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 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

11 authors.

Yushuai WuDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China.
Kaiyi LiDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China.
Yaqian LiSchool of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China.
Tao SunDepartment of General Surgery, Peking University Third Hospital, Beijing 100191, China.
Chang LiuDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China.
Chunhui DongSchool of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China.
Tian ZhaoBeijing Organobio Corporation, Beijing 102206, China.
Decong TangBeijing NeoAntigen Biotechnology Co. Ltd, Beijing 102206, China.
Xiaojie ChenBeijing NeoAntigen Biotechnology Co. Ltd, Beijing 102206, China.
Xiaofang ChenSchool of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China.
Peng LiuDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China.ORCID 0000-0003-3000-3168

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patient-derived tumor organoids (PDOs) have emerged as a reliable in vitro model for drug discovery. However, RNA sequencing-based analysis of PDOs treated with drugs has not been realized in a high-throughput format due to the limited quantity of organoids. Here, we translated a newly developed pooled RNA-seq methodology onto a superhydrophobic microwell array chip to realize an assay of genome-wide RNA output unified with phenotypic data (Grouped-seq). Over 10-fold reduction of sample and reagent consumption together with a new ligation-based barcode synthesis method lowers the cost to ∼$2 per RNA-seq sample. Patient-derived colorectal cancer (CRC) organoids with a number of 10 organoids per microwell were treated with four anti-CRC drugs across eight doses and analyzed by the Grouped-seq. Using a phenotype-assisted pathway enrichment analysis (PAPEA) method, the mechanism of actions of the drugs were correctly derived, illustrating the great potential of Grouped-seq for pharmacological screening with tumor organoids.

Indexed as

NeoplasmsOrganoidsColorectal NeoplasmsDrug DiscoveryDrug Screening Assays, AntitumorHumansPhenotypeTranscriptome

Identifiers

PMID34893868
PMCPMC8934649

What OpenQuestion holds

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Registered trials

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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.