Evidence map›Paper›PMID 32698872›Full record

ArticleStem cell research & therapy2020

Formation and optimization of three-dimensional organoids generated from urine-derived stem cells for renal function in vitro.

Guoliang Sun, Beichen Ding, Meimei Wan, Liang Chen, John Jackson, Anthony Atala

Open access · goldAbstract read
In one paragraph

Article in Stem cell research & therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

25 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Review
  6. Review
  7. Article
  8. Review
  9. Review
  10. Review
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. The sugar daddy: the role of the renal proximal tubule in glucose homeostasis.American journal of physiology. Cell physiology · 2022
    Review
  18. Review
  19. Article
  20. 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

6 authors at 3 institutions in 2 countries.

Guoliang SunDepartment of Urology, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, 1095 Jiefang Avenue, Qiaokou, Wuhan, 430030, HB, China.
Beichen DingDepartment of Urology, First Affiliated Hospital of Harbin Medical University, Harbin, HLJ, China.
Meimei WanWake Forest Institute for Regenerative Medicine, Wake Forest University, Winston Salem, NC, USA.
Liang ChenDepartment of Urology, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, 1095 Jiefang Avenue, Qiaokou, Wuhan, 430030, HB, China. Chenliang@tjh.tjmu.edu.cn.ORCID 0000-0001-9720-7099
John JacksonWake Forest Institute for Regenerative Medicine, Wake Forest University, Winston Salem, NC, USA.
Anthony AtalaWake Forest Institute for Regenerative Medicine, Wake Forest University, Winston Salem, NC, USA.
Forest Institute · USHarbin Medical University · CNTongji Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOrganoids play an important role in basic research, drug screening, and regenerative medicine. Here, we aimed to develop a novel kind of three-dimensional (3D) organoids generated from urine-derived stem cells (USCs) and to explore whether kidney-specific extracellular matrix (kECM) could enable such organoids for renal function in vitro.

methodsUSCs were isolated from human urine samples and cultured with kECM extraction to generate 3D organoids in vitro. Eight densities from 1000 to 8000 cells per organoids were prepared, and both ATP assay and Live/Dead staining were used to determine the optimal USC density in forming organoids and kECM additive concentration. The morphology and histology of as-made organoids were evaluated by hematoxylin and eosin (H.E.) staining, immunofluorescence staining and whole mount staining. Additionally, RT-qPCR was implemented to detect renal-related gene expression. Drug toxicity test was conducted to evaluate the potential application for drug screening. The renal organoids generated from whole adult kidney cells were used as a positive control in multiple assessments.

resultsThe optimized cell density to generate ideal USC-derived organoids (USC-organoids) was 5000 cells/well, which was set as applying density in the following experiments. Besides, the optimal concentration of kECM was revealed to be 10%. On this condition, Live/Dead staining showed that USC-organoids were well self-organized without significant cell death. Moreover, H.E. staining showed that compact and viable organoids were generated without obvious necrosis inside organoids, which were very close to renal organoids morphologically. Furthermore, specific proximal tubule marker Aquaporin-1 (AQP1), kidney endocrine product erythropoietin (EPO), kidney glomerular markers Podocin and Synaptopodin were detected positively in USC-organoids with kECM. Nephrotoxicity testing showed that aspirin, penicillin G, and cisplatin could exert drug-induced toxicity on USC-organoids with kECM.

conclusionsUSC-organoids could be developed from USCs via an optimal procedure. Combining culture with kECM, USC-organoid properties including morphology, histology, and specific gene expression were identified to be similar with real renal organoids. Additionally, USC-organoids posed kECM in vitro showed the potential to be a drug screening tool which might take the place of renal organoids to some extent in the future.

Indexed as

OrganoidsUrinary TractAdultCisplatinHumansKidneyStem CellsCisplatinDrug screeningExtracellular matrixOrganoidsRenal functionUrine-derived stem cells

Identifiers

PMID32698872
PMCPMC7374873
OpenAlexW3044503291

What OpenQuestion holds

Textmetadata
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.