Evidence map›Paper›PMID 36813783›Full record

ReviewCell death discovery2023

Organoids and organs-on-chips: insights into predicting the efficacy of systemic treatment in colorectal cancer.

Jialong Zhu, Linlin Ji, Yitian Chen, Huiyu Li, Mengxi Huang, Zhe Dai, Jing Wang, Dan Xiang, Gongbo Fu, Zengjie Lei and 1 more

Open access · goldAbstract readReview
In one paragraph

Review in Cell death discovery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 1 pooled it
7.6field-weighted citation impact, top 2% 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

42 citing papers in PubMed, 1 synthesis or guideline pooled it, 69 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Re-Thinking Pharmacokinetics in Ovarian Cancer: What Do Organoids Add?International journal of molecular sciences · 2026
    Review
  5. Review
  6. Article
  7. Review
  8. Article
  9. Review
  10. Review
  11. Review
  12. Review
  13. Review
  14. Review
  15. Review
  16. Review
  17. Review
  18. Preclinical models in the study of lymph node metastasis.Journal of Zhejiang University. Science. B · 2025
    Review
  19. Review
  20. Organs on chips: fundamentals, bioengineering and applications.Journal of artificial organs : the official journal of the Japanese Society for Artificial Organs · 2025
    Review
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 at 2 institutions in 1 country.

Jialong Zhu *Department of Medical Oncology, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Nanjing, 210000, China.
Linlin Ji *Department of Medical Oncology, Affiliated Jinling Hospital, Medical School, Nanjing University, Nanjing, 210000, China.
Yitian Chen *Department of Medical Oncology, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Nanjing, 210000, China.
Huiyu LiDepartment of Medical Oncology, Affiliated Jinling Hospital, Medical School, Nanjing University, Nanjing, 210000, China.
Mengxi HuangDepartment of Medical Oncology, Affiliated Jinling Hospital, Medical School, Nanjing University, Nanjing, 210000, China.
Zhe DaiDepartment of Medical Oncology, Affiliated Jinling Hospital, Medical School, Nanjing University, Nanjing, 210000, China.
Jing WangDepartment of Medical Oncology, Affiliated Jinling Hospital, Medical School, Nanjing University, Nanjing, 210000, China.
Dan XiangDepartment of Medical Oncology, Affiliated Jinling Hospital, Medical School, Nanjing University, Nanjing, 210000, China.
Gongbo FuDepartment of Medical Oncology, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Nanjing, 210000, China. mhksfgb@126.com.ORCID http://orcid.org/0000-0002-0318-0348
Zengjie LeiDepartment of Medical Oncology, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Nanjing, 210000, China. leizengjie@163.com.
Xiaoyuan ChuDepartment of Medical Oncology, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Nanjing, 210000, China. chuxiaoyuan000@163.com.
Nanjing General Hospital of Nanjing Military Command · CNNanjing University of Chinese Medicine · CN

Funding

National Natural Science Foundation of China (National Science Foundation of China) 82002591
6 · The paper itself

Abstract

Cancer heterogeneity has posed a great challenge to traditional cancer treatment, with the reappearance of cancer heterogeneity of inter and intra patients being especially critical. Based on this, personalized therapy has emerged as significant research focus in recent and even future years. Cancer-related therapeutic models are developing, including cell lines, patient-derived xenografts, organoids, etc. Organoids are three-dimensional in vitro models emerged in the past dozen years and are able to reproduce the cellular and molecular composition of the original tumor. These advantages demonstrate the great potential for patient-derived organoids to develop personalized anticancer therapies, including preclinical drug screening and the prediction of patient treatment response. The impact of microenvironment on cancer treatment cannot be underestimated, and the remodeling of microenvironment also allows organoids to interact with other technologies, among which organs-on-chips is a representative one. This review highlights the use of organoids and organs-on-chips as complementary reference tools in treating colorectal cancer from the perspective of clinical efficacy predictability. We also discuss the limitations of both techniques and how they complement each other well.

Identifiers

PMID36813783
PMCPMC9947255
OpenAlexW4321490851

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.