Mathematical modeling of cancer immunotherapy for personalized clinical translation

Nature Computational Science, Год журнала: 2022, Номер 2(12), С. 785 - 796

Опубликована: Дек. 19, 2022

Язык: Английский

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An Overview of Mathematical Modelling in Cancer Research: Fractional Calculus as Modelling Tool

Fractal and Fractional, Год журнала: 2023, Номер 7(8), С. 595 - 595

Опубликована: Авг. 1, 2023

Cancer is a complex disease, responsible for significant portion of global deaths. The increasing prioritisation know-why over know-how approaches in biological research has favoured the rising use both white- and black-box mathematical techniques cancer modelling, seeking to better grasp multi-scale mechanistic workings its phenomena (such as tumour-immune interactions, drug resistance, tumour growth diffusion, etc.). In light this wide-ranging mathematics unique memory non-local properties Fractional Calculus (FC) have been sought after last decade replace ordinary differentiation hypothesising FC’s superior modelling oncological phenomena, which shown possess an accumulated knowledge past states. As such, review aims present thorough structured survey about main guiding trends categories research, emphasising field oncology employment whole. most pivotal questions, challenges future perspectives are also outlined.

Язык: Английский

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Innovative cancer therapy: Unleashing the potential of macromolecule-loaded mesoporous bioactive glasses for precision diagnosis and treatment

International Journal of Pharmaceutics, Год журнала: 2024, Номер unknown, С. 124847 - 124847

Опубликована: Окт. 1, 2024

Язык: Английский

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Data-Driven Mathematical Model of Osteosarcoma

Cancers, Год журнала: 2021, Номер 13(10), С. 2367 - 2367

Опубликована: Май 14, 2021

As the immune system has a significant role in tumor progression, this paper, we develop data-driven mathematical model to study interactions between cells and osteosarcoma microenvironment. Osteosarcoma tumors are divided into three clusters based on their relative abundance of as estimated from gene expression profiles. We then analyze progression effects cancer growth each cluster. Cluster 3, which had approximately same number naive M2 macrophages, slowest growth, cluster 2, with highest population at steady states. also found that fastest occurred when anti-tumor cytokines, including dendritic cells, helper T cytotoxic IFN-γ, switched increasing decreasing, while dynamics regulatory decreasing increasing. Importantly, most impactful parameters total were activation decay rates macrophages for all clusters. This work presents first model, can be later extended investigate effectiveness various treatments.

Язык: Английский

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Advancing cancer drug development with mechanistic mathematical modeling: bridging the gap between theory and practice

Journal of Pharmacokinetics and Pharmacodynamics, Год журнала: 2024, Номер 51(6), С. 581 - 604

Опубликована: Июнь 21, 2024

Язык: Английский

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A Mathematical Model of Breast Tumor Progression Based on Immune Infiltration

Journal of Personalized Medicine, Год журнала: 2021, Номер 11(10), С. 1031 - 1031

Опубликована: Окт. 15, 2021

Breast cancer is the most prominent type of among women. Understanding microenvironment breast and interactions between cells cytokines will lead to better treatment approaches for patients. In this study, we developed a data-driven mathematical model investigate dynamics key involved in development. We used gene expression profiles tumors estimate relative abundance each immune cell group patients based on their patterns. Dynamical results show complex interplay molecules, sensitivity analysis emphasizes direct effects macrophages adipocytes growth. addition, observed dual effect IFN-γ proliferation, either through inhibition or by increasing cytotoxicity CD8+ T-cells.

Язык: Английский

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Uncertainty-based Gompertz growth model for tumor population and its numerical analysis

An International Journal of Optimization and Control Theories & Applications (IJOCTA), Год журнала: 2022, Номер 12(2), С. 137 - 150

Опубликована: Июль 14, 2022

For treating cancer, tumor growth models have shown to be a valuable resource, whether they are used develop therapeutic methods paired with process control or simulate and evaluate treatment processes. In addition, fuzzy mathematical model is tool for monitoring the influences of various elements creating behavioral assessments. It has been designed decrease ambiguity parameters obtain reliable development by employing logic.The Gompertz equation in an imprecise environment this study. considers whole cancer cell population vague at any given time, possibility distribution function determined initial population, net rate, carrying capacity tumor. Moreover, work provides information on expected maximum period. This study examines modeling insights based fuzziness reduce uncertainty achieve degree realism. Finally, numerical simulations utilized show significant conclusions proposed

Язык: Английский

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Dose optimization of an adjuvanted peptide-based personalized neoantigen melanoma vaccine

PLoS Computational Biology, Год журнала: 2024, Номер 20(3), С. e1011247 - e1011247

Опубликована: Март 1, 2024

The advancements in next-generation sequencing have made it possible to effectively detect somatic mutations, which has led the development of personalized neoantigen cancer vaccines that are tailored unique variants found a patient’s cancer. These can provide significant clinical benefit by leveraging immune response eliminate malignant cells. However, determining optimal vaccine dose for each patient is challenge due heterogeneity tumors. To address this challenge, we formulate mathematical optimization problem based on previous model encompasses cascade produced patient. We propose an approach identify doses, considering fixed vaccination schedule, while simultaneously minimizing overall number tumor and activated T validate our approach, perform silico experiments six real-world trial patients with advanced melanoma. compare results applying those suboptimal (the used its deviations). Our simulations reveal regimen higher initial doses lower final may lead reduction size certain patients. offers promising improving outcomes.

Язык: Английский

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Modeling Physical Forces Experienced by Cancer and Stromal Cells Within Different Organ-Specific Tumor Tissue

IEEE Journal of Translational Engineering in Health and Medicine, Год журнала: 2024, Номер 12, С. 413 - 434

Опубликована: Янв. 1, 2024

Mechanical force exerted on cancer cells by their microenvironment have been reported to drive toward invasive phenotypes altering cells' motility, proliferation, and apoptosis. These mechanical forces include compressive, tensile, hydrostatic, shear forces. The importance of is then hypothesized be an alteration microenvironment's biophysical properties as the indicator a tumor's malignancy state. Our objective investigate quantify correlation between state experienced components microenvironment. In this study, we developed multicomponent, three-dimensional model tumor tissue consisting cell surrounded fibroblasts extracellular matrix (ECM). results three different organs including breast, kidney, pancreas show that: A) stresses within are impacted organ specific ECM's properties, B) more experience higher stresses, C) in which has softer ECM (Young modulus 1.0 kPa) stiffer 2.4 kPa 1.7 than breast significantly D) contact with compared but area stroma experiencing high maximum length 40 μm when 12 for vicinity ECM. This study serves important first step understanding how cells, fibroblasts, associated states organs. quantification organ-specific at stages will help, develop theranostic strategies, second predict accurately tumors become highly malignant, third establish accurate criteria controlling progression malignancy. Furthermore, our silico can yield critical, useful information guiding ex vivo or vitro experiments, narrowing down variables investigated, what factors could impacting treatments even biomarkers looking for.

Язык: Английский

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Optimal regulation of tumour-associated neutrophils in cancer progression

Royal Society Open Science, Год журнала: 2022, Номер 9(2)

Опубликована: Фев. 1, 2022

In a tumour microenvironment, tumour-associated neutrophils could display two opposing differential phenotypes: anti-tumour (N1) and pro-tumour (N2) effector cells. Converting N2 to N1 provides innovative therapies for cancer treatment. this study, mathematical model N1-N2 dynamics describing the survival immune inhibition in response TGF-β IFN-β is considered. The effects of exogenous intervention inhibitor are examined order enhance recruitment combat progression. Our approach employs optimal control theory determine drug infusion protocols that minimize volume with least administration cost possible. Four scenarios corresponding different therapeutic strategies explored, namely, only, concomitant controls, alternating controls. For each scheme, initial conditions varied depict pathophysiological condition patient, leading adaptive treatment schedule. dosages, total amount, times relative administrations obtained under various circumstances. achieved guide designing individualized protocols.

Язык: Английский

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