ArticleiScience2019
Exposing the Underlying Relationship of Cancer Metastasis to Metabolism and Epithelial-Mesenchymal Transitions.
Article in iScience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05587088 (Evaluation of the Safety and Efficacy of Esperanza Extract), which is not on this map. Cited by 23 papers.
What it found
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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.
Evaluation of the Safety and Efficacy of Esperanza Extract (Petiveria Alliacea) in Patients With Metastatic Gastrointestinal Tumors and Acute Leukemia
Who cites it
23 citing papers in PubMed.
- Article
- Reconstructing gene network structure and dynamics from single cell data.Bioinformatics (Oxford, England) · 2025Article
- Progressive Deactivation of Hydroxylases Controls Hypoxia-Inducible Factor-1α-Coordinated Cellular Adaptation to Graded Hypoxia.Research (Washington, D.C.) · 2025Article
- Energy Landscape Reveals the Underlying Mechanism of Cancer-Adipose Conversion in Gene Network Models.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Landscape quantifies the intermediate state and transition dynamics in ecological networks.PLoS computational biology · 2024Article
- Unbalanced response to growth variations reshapes the cell fate decision landscape.Nature chemical biology · 2023Article
- Decoding the coupled decision-making of the epithelial-mesenchymal transition and metabolic reprogramming in cancer.iScience · 2023Article
- Inferring structural and dynamical properties of gene networks from data with deep learning.NAR genomics and bioinformatics · 2022Article
- Tumor Cell Glycolysis-At the Crossroad of Epithelial-Mesenchymal Transition and Autophagy.Cells · 2022Review
- Review
- A mechanistic model captures the emergence and implications of non-genetic heterogeneity and reversible drug resistance in ER+ breast cancer cells.NAR cancer · 2021Article
- Towards decoding the coupled decision-making of metabolism and epithelial-to-mesenchymal transition in cancer.British journal of cancer · 2021Review
- Computational systems-biology approaches for modeling gene networks driving epithelial-mesenchymal transitions.Computational and systems oncology · 2021Article
- A Dimension Reduction Approach for Energy Landscape: Identifying Intermediate States in Metabolism-EMT Network.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021Article
- Coupled Feedback Loops Involving PAGE4, EMT and Notch Signaling Can Give Rise to Non-genetic Heterogeneity in Prostate Cancer Cells.Entropy (Basel, Switzerland) · 2021Article
- Quantifying the Landscape of Decision Making From Spiking Neural Networks.Frontiers in computational neuroscience · 2021Article
- Inference and multiscale model of epithelial-to-mesenchymal transition via single-cell transcriptomic data.Nucleic acids research · 2020Article
- Identifying inhibitors of epithelial-mesenchymal plasticity using a network topology-based approach.NPJ systems biology and applications · 2020Article
- Full-Length TrkB Variant in NSCLC Is Associated with Brain Metastasis.BioMed research international · 2020Article
- Observation and Control of Gene Expression Noise: Barrier Crossing Analogies Between Drug Resistance and Metastasis.Frontiers in genetics · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer is a disease governed by the underlying gene regulatory networks. The hallmarks of cancer have been proposed to characterize the cancerization, e.g., abnormal metabolism, epithelial to mesenchymal transition (EMT), and cancer metastasis. We constructed a metabolism-EMT-metastasis regulatory network and quantified its underlying landscape. We identified four attractors, characterizing epithelial, abnormal metabolic, mesenchymal, and metastatic cell states, respectively. Importantly, we identified an abnormal metabolic state. Based on the transition path theory, we quantified the kinetic transition paths among these different cell states. Our results for landscape and paths indicate that metastasis is a sequential process: cells tend to first change their metabolism, then activate the EMT and eventually reach the metastatic state. This demonstrates the importance of the temporal order for different gene circuits switching on or off during metastatic progression of cancer cells and underlines the cascading regulation of metastasis through an abnormal metabolic intermediate state.
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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.