Evidence map›Paper›PMID 30155271›Full record

ArticleNPJ systems biology and applications2018

A landscape view on the interplay between EMT and cancer metastasis.

Chunhe Li, Gabor Balazsi

Abstract read
In one paragraph

Article in NPJ systems biology and applications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing 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

43 citing papers in PubMed.

  1. Review
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  6. Review
  7. Article
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  9. Canalizing kernel for cell fate determination.Briefings in bioinformatics · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Minimal frustration underlies the usefulness of incomplete regulatory network models in biology.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Quantitative cell imaging approaches to metastatic state profiling.Frontiers in cell and developmental biology · 2022
    Review
  20. Journal of biosciences · 2022
    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

2 authors.

Chunhe Li1Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China.ORCID 0000-0002-9127-3930
Gabor Balazsi3The Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, USA.

Funding

Dynamics and evolution of synthetic and natural gene regulatory networksR35GM122561 · NIGMS · STATE UNIVERSITY NEW YORK STONY BROOK · PI BALAZSI, GABOR · 2017 to 2025
$4.2M
Spatially-delineated System-level Analyses and Control of Cytoskeletal RegulationR01GM106027 · NIGMS · RICE UNIVERSITY · PI BALAZSI, GABOR, DIEHL, MICHAEL R · 2013 to 2016
$1.2M
NIGMS NIH HHS R01 GM106027NIGMS NIH HHS R35 GM122561
6 · The paper itself

Abstract

The epithelial-mesenchymal transition (EMT) is a basic developmental process that converts epithelial cells to mesenchymal cells. Although EMT might promote cancer metastasis, the molecular mechanisms for it remain to be fully clarified. To address this issue, we constructed an EMT-metastasis gene regulatory network model and quantified the potential landscape of cancer metastasis-promoting system computationally. We identified four steady-state attractors on the landscape, which separately characterize anti-metastatic (A), metastatic (M), and two other intermediate (I1 and I2) cell states. The tetrastable landscape and the existence of intermediate states are consistent with recent single-cell measurements. We identified one of the two intermediate states I1 as the EMT state. From a MAP approach, we found that for metastatic progression cells need to first undergo EMT (enter the I1 state), and then become metastatic (switch from the I1 state to the M state). Specifically, for metastatic progression, EMT genes (such as ZEB) should be activated before metastasis genes (such as BACH1). This suggests that temporal order is important for the activation of cellular programs in biological systems, and provides a possible mechanism of EMT-promoting cancer metastasis. To identify possible therapeutic targets from this landscape view, we performed sensitivity analysis for individual molecular factors, and identified optimal interventions for landscape control. We found that minimizing transition actions more effectively identifies optimal combinations of targets that induce transitions between attractors than single-factor sensitivity analysis. Overall, the landscape view not only suggests that intermediate states increase plasticity during cell fate decisions, providing a possible source for tumor heterogeneity that is critically important in metastatic progress, but also provides a way to identify therapeutic targets for preventing cancer progression.

Identifiers

PMID30155271
PMCPMC6107626

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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.