ReviewTheoretical biology & medical modelling2017
Perspective on the dynamics of cancer.
Review in Theoretical biology & medical modelling, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 17 citations in OpenAlex.
- New Quinoline Kinase Inhibitors With Good Selectivity for NAK Kinases and Anti-Tumor Activity Against Ewing Sarcoma.Archiv der Pharmazie · 2026Article
- The potential of real-time dynamic disease monitoring with circulating tumor DNA: important lessons from Epstein-Barr virus-related nasopharyngeal carcinoma.The Lancet regional health. Western Pacific · 2025Article
- Chronic arsenic exposure induces malignant transformation of human HaCaT cells through both deterministic and stochastic changes in transcriptome expression.Toxicology and applied pharmacology · 2024Article
- Globally invariant behavior of oncogenes and random genes at population but not at single cell level.NPJ systems biology and applications · 2023Article
- Deltex E3 ubiquitin ligase 3 inhibits colorectal cancer cell growth and regulates cell cycle progression via upregulating E2F transcription factor 1.Molecular biology reports · 2022Article
- Application of Advanced Mass Spectrometry-Based Proteomics to Study Hypoxia Driven Cancer Progression.Frontiers in oncology · 2021Review
- Review
- Contribution of Angiogenesis to Inflammation and Cancer.Frontiers in oncology · 2019Review
- How do cancer cells replenish their fuel supply?Cancer reports (Hoboken, N.J.) · 2018Review
- Immuno-Oncology: Emerging Targets and Combination Therapies.Frontiers in oncology · 2018Review
- The Adaptive Complexity of Cancer.BioMed research international · 2018Review
- An Introduction to the Mathematical Modeling in the Study of Cancer Systems Biology.Cancer informatics · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe genetic diversity of cancer and the dynamic interactions between heterogeneous tumor cells, the stroma and immune cells present daunting challenges to the development of effective cancer therapies. Although cancer biology is more understood than ever, this has not translated into therapies that overcome drug resistance, cancer recurrence and metastasis. The future development of effective therapies will require more understanding of the dynamics of homeostatic dysregulation that drives cancer growth and progression.
resultsCancer dynamics are explored using a model involving genes mediating the regulatory interactions between the signaling and metabolic pathways. The exploration is informed by a proposed genetic dysregulation measure of cellular processes. The analysis of the interaction dynamics between cancer cells, cancer associated fibroblasts, and tumor associate macrophages suggests that the mutual dependence of these cells promotes cancer growth and proliferation. In particular, MTOR and AMPK are hypothesized to be concurrently activated in cancer cells by amino acids recycled from the stroma. This leads to a proliferative growth supported by an upregulated glycolysis and a tricarboxylic acid cycle driven by glutamine sourced from the stroma. In other words, while genetic aberrations ignite carcinogenesis and lead to the dysregulation of key cellular processes, it is postulated that the dysregulation of metabolism locks cancer cells in a state of mutual dependence with the tumor microenvironment and deepens the tumor's inflammation and immunosuppressive state which perpetuates as a result the growth and proliferation dynamics of cancer.
conclusionsCancer therapies should aim for a progressive disruption of the dynamics of interactions between cancer cells and the tumor microenvironment by targeting metabolic dysregulation and inflammation to partially restore tissue homeostasis and turn on the immune cancer kill switch. One potentially effective cancer therapeutic strategy is to induce the reduction of lactate and steer the tumor microenvironment to a state of reduced inflammation so as to enable an effective intervention of the immune system. The translation of this therapeutic approach into treatment regimens would however require more understanding of the adaptive complexity of cancer resulting from the interactions of cancer cells with the tumor microenvironment and the immune system.
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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.