ArticleScientific reports2015
Increased signaling entropy in cancer requires the scale-free property of protein interaction networks.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Robust signalling entropy estimation for biological process characterisation.Briefings in bioinformatics · 2025Article
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- BioNAR: an integrated biological network analysis package in bioconductor.Bioinformatics advances · 2023Article
- Pan-Cancer Prediction of Cell-Line Drug Sensitivity Using Network-Based Methods.International journal of molecular sciences · 2022Article
- Statistical mechanics meets single-cell biology.Nature reviews. Genetics · 2021Review
- A unified resource and configurable model of the synapse proteome and its role in disease.Scientific reports · 2021Article
- Entropy as a Robustness Marker in Genetic Regulatory Networks.Entropy (Basel, Switzerland) · 2020Article
- Central Proteins of Plasma in Response to Low-Level Laser Therapy Involve in Body Hemostasis and Wound Repair.Journal of lasers in medical sciences · 2020Article
- Article
- Multi-Omic Data Interpretation to Repurpose Subtype Specific Drug Candidates for Breast Cancer.Frontiers in genetics · 2019Article
- Signaling Complexity Measured by Shannon Entropy and Its Application in Personalized Medicine.Frontiers in genetics · 2019Article
- Differential network as an indicator of osteoporosis with network entropy.Experimental and therapeutic medicine · 2018Article
- scEpath: energy landscape-based inference of transition probabilities and cellular trajectories from single-cell transcriptomic data.Bioinformatics (Oxford, England) · 2018Article
- Relation extraction for biological pathway construction using node2vec.BMC bioinformatics · 2018Article
- Analysis of Cell Signal Transduction Based on Kullback-Leibler Divergence: Channel Capacity and Conservation of Its Production Rate during Cascade.Entropy (Basel, Switzerland) · 2018Article
- The Conservation of Average Entropy Production Rate in a Model of Signal Transduction: Information Thermodynamics Based on the Fluctuation Theorem.Entropy (Basel, Switzerland) · 2018Article
- Information Thermodynamics of the Cell Signal Transduction as a Szilard Engine.Entropy (Basel, Switzerland) · 2018Article
- Biological Networks Entropies: Examples in Neural Memory Networks, Genetic Regulation Networks and Social Epidemic Networks.Entropy (Basel, Switzerland) · 2018Article
- Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome.Nature communications · 2017Article
- Disentangling Interactions in the Microbiome: A Network Perspective.Trends in microbiology · 2017Review
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5 authors.
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Abstract
One of the key characteristics of cancer cells is an increased phenotypic plasticity, driven by underlying genetic and epigenetic perturbations. However, at a systems-level it is unclear how these perturbations give rise to the observed increased plasticity. Elucidating such systems-level principles is key for an improved understanding of cancer. Recently, it has been shown that signaling entropy, an overall measure of signaling pathway promiscuity, and computable from integrating a sample's gene expression profile with a protein interaction network, correlates with phenotypic plasticity and is increased in cancer compared to normal tissue. Here we develop a computational framework for studying the effects of network perturbations on signaling entropy. We demonstrate that the increased signaling entropy of cancer is driven by two factors: (i) the scale-free (or near scale-free) topology of the interaction network, and (ii) a subtle positive correlation between differential gene expression and node connectivity. Indeed, we show that if protein interaction networks were random graphs, described by Poisson degree distributions, that cancer would generally not exhibit an increased signaling entropy. In summary, this work exposes a deep connection between cancer, signaling entropy and interaction network topology.
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