Evidence map›Paper›PMID 38184695›Full record

ArticleScientific reports2024

ROR2 expression predicts human induced pluripotent stem cell differentiation into neural stem/progenitor cells and GABAergic neurons.

Takuya Kuroda, Satoshi Yasuda, Satoko Matsuyama, Takumi Miura, Rumi Sawada, Akifumi Matsuyama, Yumiko Yamamoto, Masaki Suimye Morioka, Hideya Kawaji, Takeya Kasukawa and 4 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 33% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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

14 authors at 5 institutions in 1 country.

Takuya KurodaDivision of Cell-Based Therapeutic Products, National Institute of Health Sciences, Kawasaki, Kanagawa, Japan.
Satoshi YasudaDivision of Cell-Based Therapeutic Products, National Institute of Health Sciences, Kawasaki, Kanagawa, Japan.
Satoko MatsuyamaDivision of Cell-Based Therapeutic Products, National Institute of Health Sciences, Kawasaki, Kanagawa, Japan.
Takumi MiuraDivision of Cell-Based Therapeutic Products, National Institute of Health Sciences, Kawasaki, Kanagawa, Japan.
Rumi SawadaDivision of Cell-Based Therapeutic Products, National Institute of Health Sciences, Kawasaki, Kanagawa, Japan.
Akifumi MatsuyamaCenter for Reverse TR, Osaka Habikino Medical Center, Osaka Prefectural Hospital Organization, Habikino, Osaka, Japan.
Yumiko YamamotoRIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.
Masaki Suimye MoriokaRIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.
Hideya KawajiRIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.
Takeya KasukawaRIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.
Masayoshi ItohRIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.
Hidenori AkutsuCenter for Regenerative Medicine, National Center for Child Health and Development, Setagaya, Tokyo, Japan.
Jun KawaiLife Science Technology Project, Kanagawa Institute of Industrial Science and Technology, Kawasaki, Kanagawa, Japan.
Yoji SatoDivision of Cell-Based Therapeutic Products, National Institute of Health Sciences, Kawasaki, Kanagawa, Japan. yoji@nihs.go.jp.
RIKEN Center for Integrative Medical Sciences · JPNational Institute of Health Sciences · JPNational Center For Child Health and Development · JPOsaka Prefectural Medical Center · JPTokyo Metropolitan Institute of Medical Science · JP

Funding

Japan Agency for Medical Research and Development 19bk0104100Japan Agency for Medical Research and Development 23mk0101196j0103Japan Society for the Promotion of Science 22K12900
6 · The paper itself

Abstract

Despite the development of various in vitro differentiation protocols for the efficient derivation of specific cell types, human induced pluripotent stem cell (hiPSC) lines have varing ability to differentiate into specific lineages. Therefore, surrogate markers for accurately predicting the differentiation propensity of hiPSC lines may facilitate cell-based therapeutic product development and manufacture. We attempted to identify marker genes that could predict the differentiation propensity of hiPSCs into neural stem/progenitor cells (NS/PCs). Using Spearman's rank correlation coefficients, we investigated genes in the undifferentiated state, the expression levels of which were significantly correlated with the neuronal differentiation propensity of several hiPSC lines. Among genes significantly correlated with NS/PC differentiation (P < 0.01), we identified ROR2 as a novel predictive marker. ROR2 expression in hiPSCs was negatively correlated with NS/PC differentiation tendency, regardless of the differentiation method, whereas its knockdown enhanced differentiation. ROR2 regulates NS/PC differentiation, suggesting that ROR2 is functionally essential for NS/PC differentiation. Selecting cell lines with relatively low ROR2 expression facilitated identification of hiPSCs that can differentiate into NS/PCs. Cells with ROR2 knockdown showed increased efficiency of differentiation into forebrain GABAergic neurons compared to controls. These findings suggest that ROR2 is a surrogate marker for selecting hiPSC lines appropriate for NS/PC and GABAergic neuronal differentiations.

Indexed as

Induced Pluripotent Stem CellsCell DifferentiationCell LineCommerceGABAergic NeuronsHumansReceptor Tyrosine Kinase-like Orphan ReceptorsReceptor Tyrosine Kinase-like Orphan ReceptorsROR2 protein, human

Identifiers

PMID38184695
PMCPMC10771438
OpenAlexW4390638115

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.