ArticleInterface focus2013
Mathematical models of immune-induced cancer dormancy and the emergence of immune evasion.
Article in Interface focus, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed.
- Within host dynamics of HPV infection with cellular immunity and HPV-infected dormant cells reactivation.Infectious Disease Modelling · 2026Article
- When effective anticancer therapies are, in fact, destabilizing the tumor's Group Phenotypic Composition.NPJ precision oncology · 2026Review
- Article
- Gaming the cancer-immunity cycle by synchronizing the dose schedules.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Distinct evolutionary patterns of tumour-immune escape and elimination determined by extracellular matrix architectures.Journal of the Royal Society, Interface · 2025Article
- The Impact of T-cell Exhaustion Dynamics on Tumour-Immune Interactions and Tumour Growth.Bulletin of mathematical biology · 2025Article
- How modulation of the tumor microenvironment drives cancer immune escape dynamics.Scientific reports · 2025Article
- A multiscale model of immune surveillance in micrometastases gives insights on cancer patient digital twins.NPJ systems biology and applications · 2024Article
- Integrative lymph node-mimicking models created with biomaterials and computational tools to study the immune system.Materials today. Bio · 2022Review
- Review
- Dormant Tumor Cell Vaccination: A Mathematical Model of Immunological Dormancy in Triple-Negative Breast Cancer.Cancers · 2021Article
- Cancer-induced immunosuppression can enable effectiveness of immunotherapy through bistability generation: A mathematical and computational examination.Journal of theoretical biology · 2020Article
- Tuning Cancer Fate: Tumor Microenvironment's Role in Cancer Stem Cell Quiescence and Reawakening.Frontiers in immunology · 2020Review
- Mathematical modeling of tumor-immune cell interactions.Journal of theoretical biology · 2019Review
- Mathematical Modeling Reveals That the Administration of EGF Can Promote the Elimination of Lymph Node Metastases by PD-1/PD-L1 Blockade.Frontiers in bioengineering and biotechnology · 2019Article
- Combining immune check-point blockade and cryoablation in an immunocompetent hormone sensitive murine model of prostate cancer.Prostate cancer and prostatic diseases · 2018Article
- Uncovering the underlying mechanism of cancer tumorigenesis and development under an immune microenvironment from global quantification of the landscape.Journal of the Royal Society, Interface · 2017Article
- A proliferation saturation index to predict radiation response and personalize radiotherapy fractionation.Radiation oncology (London, England) · 2015Article
- An agent-based modeling framework linking inflammation and cancer using evolutionary principles: description of a generative hierarchy for the hallmarks of cancer and developing a bridge between mechanism and epidemiological data.Mathematical biosciences · 2015Article
- Modeling putative therapeutic implications of exosome exchange between tumor and immune cells.Proceedings of the National Academy of Sciences of the United States of America · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Cancer dormancy, a state in which cancer cells persist in a host without significant growth, is a natural forestallment of progression to manifest disease and is thus of great clinical interest. Experimental work in mice suggests that in immune-induced dormancy, the longer a cancer remains dormant in a host, the more resistant the cancer cells become to cytotoxic T-cell-mediated killing. In this work, mathematical models are used to analyse the possible causative mechanisms of cancer escape from immune-induced dormancy. Using a data-driven approach, both decaying efficacy in immune predation and immune recruitment are analysed with results suggesting that decline in recruitment is a stronger determinant of escape than increased resistance to predation. Using a mechanistic approach, the existence of an immune-resistant cancer cell subpopulation is considered, and the effects on cancer dormancy and potential immunoediting mechanisms of cancer escape are analysed and discussed. The immunoediting mechanism assumes that the immune system selectively prunes the cancer of immune-sensitive cells, which is shown to cause an initially heterogeneous population to become a more homogeneous, and more resistant, population. The fact that this selection may result in the appearance of decreasing efficacy in T-cell cytotoxic effect with time in dormancy is also demonstrated. This work suggests that through actions that temporarily delay cancer growth through the targeted removal of immune-sensitive subpopulations, the immune response may actually progress the cancer to a more aggressive state.
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.