Mathematical Models of Cancer: When to Predict Novel Therapies, and When Not to

Bulletin of Mathematical Biology, Journal Year: 2019, Volume and Issue: 81(10), P. 3722 - 3731

Published: July 23, 2019

The number of publications on mathematical modeling cancer is growing at an exponential rate, according to PubMed records, provided by the US National Library Medicine and Institutes Health. Seminal papers have initiated promoted helped define field oncology (Norton Simon in J Natl Cancer Inst 58:1735–1741, 1977; Norton Can Res 48:7067–7071, 1988; Hahnfeldt et al. 59:4770–4775, 1999; Anderson Comput Math Methods Med 2:129–154, 2000. https://doi.org/10.1080/10273660008833042 ; Michor Nature 435:1267–1270, 2005. https://doi.org/10.1038/nature03669 Cell 127:905–915, 2006. https://doi.org/10.1016/j.cell.2006.09.042 Benzekry PLoS Biol 10:e1003800, 2014. https://doi.org/10.1371/journal.pcbi.1003800 ). Following introduction undergraduate graduate programs biology, we begun see curricula developing with specific exclusive focus oncology. In 2018, 218 articles were published various journals, including not only traditional journals like Bulletin Mathematical Biology Journal Theoretical Biology, but also renowned science, tremendous impact (Cell, Research, Clinical Discovery, Scientific Reports, PNAS, Communications, eLife, etc). This shows breadth models that are being developed for multiple purposes. While some phenomenological nature following a bottom-up approach, other more top-down data-driven. Here, discuss emerging trend predict novel, optimal, sometimes even patient-specific treatments, propose convention when use model novel treatments and, probably importantly, to.

Language: Английский

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Multiscale Agent-Based and Hybrid Modeling of the Tumor Immune Microenvironment

Processes, Journal Year: 2019, Volume and Issue: 7(1), P. 37 - 37

Published: Jan. 13, 2019

Multiscale systems biology and pharmacology are powerful methodologies that playing increasingly important roles in understanding the fundamental mechanisms of biological phenomena clinical applications. In this review, we summarize state art applications agent-based models (ABM) hybrid modeling to tumor immune microenvironment cancer response, including immunotherapy. Heterogeneity is a hallmark cancer; heterogeneity at molecular, cellular, tissue scales major determinant metastasis, drug resistance, low response rate molecular targeted therapies immunotherapies. Agent-based an effective methodology obtain understand quantitative characteristics these processes propose solutions aimed overcoming current obstacles treatment. We review focusing on intra-tumor heterogeneity, particularly interactions between cells stromal cells, role tumor-associated vasculature immune-related mechanobiology, discuss digital pathology parameterizing validating spatial computational potential therapeutics.

Language: Английский

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Oncolytic viruses encoding bispecific T cell engagers: a blueprint for emerging immunovirotherapies

Journal of Hematology & Oncology, Journal Year: 2021, Volume and Issue: 14(1)

Published: April 16, 2021

Bispecific T cell engagers (BiTEs) are an innovative class of immunotherapeutics that redirect cells to tumor surface antigens. While efficacious against certain hematological malignancies, limited bioavailability and severe toxicities have so far hampered broader clinical application, especially solid tumors. Another emerging cancer immunotherapy oncolytic viruses (OVs) which selectively infect replicate in malignant cells, thereby mediating vaccination effects. These oncotropic can serve as vectors for tumor-targeted immunomodulation synergize with other immunotherapies. In this article, we discuss the use OVs overcome challenges BiTE therapy. We review current state field, covering published preclinical studies well ongoing investigations. systematically introduce OV-BiTE vector design characteristics evidence immune-stimulating anti-tumor Moreover, address additional combination regimens, including CAR immune checkpoint inhibitors, further strategies modulate microenvironment using OV-BiTEs. The inherent complexity these novel therapeutics highlights importance translational research correlative early-phase trials. More broadly, OV-BiTEs a blueprint diverse OV-based

Language: Английский

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Multiscale modelling of cancer response to oncolytic viral therapy

Mathematical Biosciences, Journal Year: 2019, Volume and Issue: 310, P. 76 - 95

Published: Feb. 5, 2019

Language: Английский

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The rapidly evolving state of gene therapy

The FASEB Journal, Journal Year: 2018, Volume and Issue: 32(4), P. 1733 - 1740

Published: March 29, 2018

Gene therapy is emerging as a viable option for clinical of monogenic disorders and other genetically defined diseases, with approved gene therapies available in Europe newly the United States. In past 10 years, has moved from distant possibility, even minds much scientific community, to being widely realized valuable therapeutic tool wide-ranging potential. The U.S. Food Drug Administration recently Luxturna (Spark Therapeutics Inc, Philadelphia, PA, USA), recombinant adeno-associated virus (rAAV) 2 one type Leber congenital amaurosis (1, 2). European Medicines Agency (EMA) 3 viral vector products: Glybera (UniQure, Amsterdam, Netherlands), an rAAV lipoprotein lipase deficiency; Strimvelis (Glaxo Smith-Kline, Brentford, Kingdom), ex vivo gammaretrovirus-based patients adenosine deaminase-deficient severe combined immune deficiency (ADA-SCID); Kymriah (Novartis, Basel, Switzerland), lentivirus-based engineer autologous chimeric antigen-receptor T (CAR-T) cells targeting CD19–positive acute lymphoblastic leukemia. These examples will be followed by approval products this field matures. review we provide overview state discussing where stands respect different platforms types that are available.— Gruntman, A. M., Flotte, T. R. rapidly evolving therapy. FASEB J. 32, 1733–1740 (2018). www.fasebj.org

Language: Английский

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Computational modelling of modern cancer immunotherapy

Physics in Medicine and Biology, Journal Year: 2020, Volume and Issue: 65(24), P. 24TR01 - 24TR01

Published: Oct. 22, 2020

Modern cancer immunotherapy has revolutionised oncology and carries the potential to radically change approach treatment. However, numerous questions remain be answered understand response better further improve benefit for future patients. Computational models are promising tools that can contribute accelerated research by providing new clues hypotheses could tested in trials, based on preceding simulations addition empirical rationale. In this topical review, we briefly summarise history of immunotherapy, including computational modelling traditional comprehensively review modern such as immune checkpoint inhibitors (as monotherapy combination treatment), co-stimulatory agonistic antibodies, bispecific chimeric antigen receptor T cells. The approaches classified into one following categories: data-driven top-down vs mechanistic bottom-up, simplistic detailed, continuous discrete, hybrid. Several common summarised, pharmacokinetic/pharmacodynamic models, Lotka-Volterra evolutionary game theory quantitative systems pharmacology spatio-temporal agent-based logic-based models. Pros cons each critically discussed, particularly with focus successful translation immuno-oncology routine clinical practice. Specific attention is paid calibration validation model, which a necessary prerequisite any at same time, main obstacles. Lastly, provide guidelines suggestions development field.

Language: Английский

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Applications of Intravital Imaging in Cancer Immunotherapy

Bioengineering, Journal Year: 2024, Volume and Issue: 11(3), P. 264 - 264

Published: March 8, 2024

Currently, immunotherapy is one of the most effective treatment strategies for cancer. However, efficacy any specific anti-tumor can vary based on dynamic characteristics immune cells, such as their rate migration and cell-to-cell interactions. Therefore, understanding dynamics among cells involved in response inform optimization improvement existing strategies. In vivo imaging technologies use optical microscopy techniques to visualize movement behavior vivo, including response, thereby showing great potential application field cancer immunotherapy. this review, we briefly introduce technical aspects required imaging, fluorescent protein labeling, construction transgenic mice, various window chamber models. Then, discuss elucidation new phenomena mechanisms relating tumor that has been made possible by technology. Specifically, supported characterization T during checkpoint inhibitor therapy kinetic analysis dendritic cell vaccine therapy. Finally, provide a perspective challenges future research directions technology

Language: Английский

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Developing a Minimally Structured Mathematical Model of Cancer Treatment with Oncolytic Viruses and Dendritic Cell Injections

Computational and Mathematical Methods in Medicine, Journal Year: 2018, Volume and Issue: 2018, P. 1 - 14

Published: Oct. 30, 2018

Mathematical models of biological systems must strike a balance between being sufficiently complex to capture important features, while simple enough that they remain tractable through analysis or simulation. In this work, we rigorously explore how these competing interests when modeling murine melanoma treatment with oncolytic viruses and dendritic cell injections. Previously, developed system six ordinary differential equations containing fourteen parameters well describes experimental data on the efficacy treatments. Here, whether previously model is minimal needed accurately describe data. Using variety techniques, including sensitivity analyses parameter sloppiness analysis, find our can be reduced by one variable three still give excellent fits We also argue not too dynamics data, original make similar predictions about robustness protocols considered in experiments. Reducing its form allows us increase tractability face parametric uncertainty.

Language: Английский

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Oscillations in a Spatial Oncolytic Virus Model

Bulletin of Mathematical Biology, Journal Year: 2024, Volume and Issue: 86(8)

Published: June 19, 2024

Language: Английский

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A mathematical model of viral oncology as an immuno-oncology instigator

Mathematical Medicine and Biology A Journal of the IMA, Journal Year: 2019, Volume and Issue: unknown

Published: March 27, 2019

We develop and analyse a mathematical model of tumour-immune interaction that explicitly incorporates heterogeneity in tumour cell cycle duration by using distributed delay differential equation. derive necessary sufficient condition for local stability the cancer-free equilibrium which amount completely characterizes disease progression. Consistent with immunoediting hypothesis, we show decreasing leads to expansion. Finally, simulating model, strength determines long-term success or failure viral therapy.

Language: Английский

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