ArticleBMC systems biology2016
Attractor landscape analysis of colorectal tumorigenesis and its reversion.
Article in BMC systems biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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.
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.
Who cites it
27 citing papers in PubMed.
- Control-guided refinement of partially specified Boolean networks: applications to RTK signaling.Bioinformatics (Oxford, England) · 2026Article
- Harnessing the analog computing power of regulatory networks with the Regulatory Network Machine.iScience · 2025Article
- CanSeer: a translational methodology for developing personalized cancer models and therapeutics.Scientific reports · 2025Article
- Deep learning untangles the resistance mechanism of p53 reactivator in lung cancer cells.iScience · 2023Article
- Normalizing Input-Output Relationships of Cancer Networks for Reversion Therapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- A systems biology approach to define mechanisms, phenotypes, and drivers in PanNETs with a personalized perspective.NPJ systems biology and applications · 2023Article
- Critical transition and reversion of tumorigenesis.Experimental & molecular medicine · 2023Review
- NETISCE: a network-based tool for cell fate reprogramming.NPJ systems biology and applications · 2022Article
- Article
- Personalized logical models to investigate cancer response to BRAF treatments in melanomas and colorectal cancers.PLoS computational biology · 2021Article
- A Personalized Therapeutics Approach Using anFrontiers in oncology · 2021Article
- Data-Driven Modeling of Breast Cancer Tumors Using Boolean Networks.Frontiers in big data · 2021Article
- Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics.Frontiers in oncology · 2021Review
- Feedback analysis identifies a combination target for overcoming adaptive resistance to targeted cancer therapy.Oncogene · 2020Article
- A Middle-Out Modeling Strategy to Extend a Colon Cancer Logical Model Improves Drug Synergy Predictions in Epithelial-Derived Cancer Cell Lines.Frontiers in molecular biosciences · 2020Article
- Signal flow control of complex signaling networks.Scientific reports · 2019Article
- Minimal intervening control of biomolecular networks leading to a desired cellular state.Scientific reports · 2019Article
- Next Generation Networks: Featuring the Potential Role of Emerging Applications in Translational Oncology.Journal of clinical medicine · 2019Article
- Attractor - a new turning point in drug discovery.Drug design, development and therapy · 2019Review
- ATLANTIS - Attractor Landscape Analysis Toolbox for Cell Fate Discovery and Reprogramming.Scientific reports · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundColorectal cancer arises from the accumulation of genetic mutations that induce dysfunction of intracellular signaling. However, the underlying mechanism of colorectal tumorigenesis driven by genetic mutations remains yet to be elucidated.
resultsTo investigate colorectal tumorigenesis at a system-level, we have reconstructed a large-scale Boolean network model of the human signaling network by integrating previous experimental results on canonical signaling pathways related to proliferation, metastasis, and apoptosis. Throughout an extensive simulation analysis of the attractor landscape of the signaling network model, we found that the attractor landscape changes its shape by expanding the basin of attractors for abnormal proliferation and metastasis along with the accumulation of driver mutations. A further hypothetical study shows that restoration of a normal phenotype might be possible by reversely controlling the attractor landscape. Interestingly, the targets of approved anti-cancer drugs were highly enriched in the identified molecular targets for the reverse control.
conclusionsOur results show that the dynamical analysis of a signaling network based on attractor landscape is useful in acquiring a system-level understanding of tumorigenesis and developing a new therapeutic strategy.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.