Evidence map›Paper›PMID 39840939›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Attractor Landscape Analysis Reveals a Reversion Switch in the Transition of Colorectal Tumorigenesis.

Dongkwan Shin, Jeong-Ryeol Gong, Seoyoon D Jeong, Youngwon Cho, Hwang-Phill Kim, Tae-You Kim, Kwang-Hyun Cho

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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  5. 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

7 authors.

Dongkwan ShinDepartment of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea.
Jeong-Ryeol GongDepartment of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea.
Seoyoon D JeongDepartment of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea.
Youngwon ChoDepartment of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, 03080, Republic of Korea.
Hwang-Phill KimDepartment of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, 03080, Republic of Korea.
Tae-You KimDepartment of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, 03080, Republic of Korea.
Kwang-Hyun ChoDepartment of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea.ORCID https://orcid.org/0000-0002-7380-7142

Funding

Korean Government, the Ministry of Science and ICT 2022R1A2C1010532Korean Government, the Ministry of Science and ICT 2023R1A2C3002619Korean Government, the Ministry of Science and ICT RS-2024-00405360Ministry of Health & Welfare, Republic of Korea HI21C0071National Cancer Center NCC-2410750
6 · The paper itself

Abstract

A cell fate change such as tumorigenesis incurs critical transition. It remains a longstanding challenge whether the underlying mechanism can be unraveled and a molecular switch that can reverse such transition is found. Here a systems framework, REVERT, is presented with which can reconstruct the core molecular regulatory network model and a reversion switch based on single-cell transcriptome data over the transition process is identified. The usefulness of REVERT is demonstrated by applying it to single-cell transcriptome of patient-derived matched organoids of colon cancer and normal colon. REVERT is a generic framework that can be applied to investigate various cell fate transition phenomena.

Indexed as

CarcinogenesisColorectal NeoplasmsGene Regulatory NetworksHumansOrganoidsSingle-Cell AnalysisTranscriptomeattractor landscape analysiscancer reversioncolon cancercritical transitiondynamic network modelpatient‐derived organoidsingle cell transcriptome data

Identifiers

PMID39840939
PMCPMC11848608

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.