Evidence map›Paper›PMID 35484598›Full record

ArticleGenome biology2022

Systematic evaluation of colorectal cancer organoid system by single-cell RNA-Seq analysis.

Rui Wang, Yunuo Mao, Wendong Wang, Xin Zhou, Wei Wang, Shuai Gao, Jingyun Li, Lu Wen, Wei Fu, Fuchou Tang

Abstract read
In one paragraph

Article in Genome biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 1 pooled it
–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

70 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Single-cell transcriptomic analysis reveals cellular heterogeneity and prognostic subtypes in colorectal cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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  18. Multiscale Construction, Evaluation, and Application of Organoids.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
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  20. Article

10 more citing papers are in PubMed but not listed here.

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

10 authors.

Rui Wang *Department of General Surgery, School of Life Sciences, Biomedical Pioneering Innovation Center, Third Hospital, Peking University, Beijing, 100871, People's Republic of China.
Yunuo Mao *Department of General Surgery, School of Life Sciences, Biomedical Pioneering Innovation Center, Third Hospital, Peking University, Beijing, 100871, People's Republic of China.
Wendong Wang *Department of General Surgery, School of Life Sciences, Biomedical Pioneering Innovation Center, Third Hospital, Peking University, Beijing, 100871, People's Republic of China.
Xin Zhou *Department of General Surgery, School of Life Sciences, Biomedical Pioneering Innovation Center, Third Hospital, Peking University, Beijing, 100871, People's Republic of China.
Wei Wang *Department of General Surgery, School of Life Sciences, Biomedical Pioneering Innovation Center, Third Hospital, Peking University, Beijing, 100871, People's Republic of China.
Shuai GaoDepartment of General Surgery, School of Life Sciences, Biomedical Pioneering Innovation Center, Third Hospital, Peking University, Beijing, 100871, People's Republic of China.
Jingyun LiDepartment of General Surgery, School of Life Sciences, Biomedical Pioneering Innovation Center, Third Hospital, Peking University, Beijing, 100871, People's Republic of China.
Lu WenDepartment of General Surgery, School of Life Sciences, Biomedical Pioneering Innovation Center, Third Hospital, Peking University, Beijing, 100871, People's Republic of China.
Wei FuDepartment of General Surgery, School of Life Sciences, Biomedical Pioneering Innovation Center, Third Hospital, Peking University, Beijing, 100871, People's Republic of China. fuwei@bjmu.edu.cn.
Fuchou TangDepartment of General Surgery, School of Life Sciences, Biomedical Pioneering Innovation Center, Third Hospital, Peking University, Beijing, 100871, People's Republic of China. tangfuchou@pku.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatient-derived organoid culture is a powerful system for studying the molecular mechanisms of cancers, especially colorectal cancer (CRC), one of the most prevalent cancers worldwide. There are two main types of 3D culture methods for colonic cells, but the similarities and differences between gene expression patterns in different culture media remain largely unexplored.

resultsHere, we establish patient-derived organoids from colorectal cancer patients and perform single-cell RNA-Seq for pairwise samples from seven patients for both organoids and their corresponding tumor and normal tissues in vivo. We find that organoids derived from tumor tissues faithfully recapitulate the main gene expression signatures of cancer cells in vivo. On the other hand, organoids derived from normal tissues exhibited some tumor-like features at the whole transcriptome level but retained normal genomic features, such as CNVs, point mutations, and normal global DNA methylation levels, for both cultural media. More importantly, we show that conditioned medium outperforms chemical-defined medium in long-term culture of tumor epithelial cells. Finally, we mutually exchange the culture medium for the organoids and find that after interchanging the medium, the organoid cells basically maintain the transcriptome characteristics of the original medium.

conclusionsOur work gives a thorough evaluation of both the cultural conditions and the biological features of organoids of CRC patients.

Indexed as

Colorectal NeoplasmsOrganoidsDNA MethylationHumansSequence Analysis, RNA

Identifiers

PMID35484598
PMCPMC9047329

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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.