A mathematical model for predicting the spatiotemporal response of breast cancer cells treated with doxorubicin

Cancer Biology & Therapy, Год журнала: 2024, Номер 25(1)

Опубликована: Фев. 27, 2024

Tumor heterogeneity contributes significantly to chemoresistance, a leading cause of treatment failure. To better personalize therapies, it is essential develop tools capable identifying and predicting intra- inter-tumor heterogeneities. Biology-inspired mathematical models are attacking this problem, but tumor often overlooked in

Язык: Английский

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Tumor-immune ecosystem dynamics define an individual Radiation Immune Score to predict pan-cancer radiocurability

Neoplasia, Год журнала: 2021, Номер 23(11), С. 1110 - 1122

Опубликована: Окт. 5, 2021

Radiotherapy efficacy is the result of radiation-mediated cytotoxicity coupled with stimulation antitumor immune responses. We develop an in silico 3-dimensional agent-based model diverse tumor-immune ecosystems (TIES) represented as anti- or pro-tumor phenotypes. validate 10,469 patients across 31 tumor types by demonstrating that clinically detected tumors have TIES. then quantify likelihood radiation induces TIES shifts toward immune-mediated elimination developing individual Radiation Immune Score (iRIS). show iRIS distribution consistent clinical effectiveness radiotherapy, and combination a molecular radiosensitivity index (RSI) combines to predict pan-cancer radiocurability. correlates local control survival separate cohort 59 lung cancer treated radiation. In combination, RSI radiation-induced identify candidates for de-escalation treatment escalation. This first biologically validated computational simulate response outcomes via perturbation radiotherapy.

Язык: Английский

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Mathematical modelling of the dynamics of image-informed tumor habitats in a murine model of glioma

Scientific Reports, Год журнала: 2023, Номер 13(1)

Опубликована: Фев. 20, 2023

Abstract Tumors exhibit high molecular, phenotypic, and physiological heterogeneity. In this effort, we employ quantitative magnetic resonance imaging (MRI) data to capture heterogeneity through imaging-based subregions or “habitats” in a murine model of glioma. We then demonstrate the ability predict growth habitats using coupled ordinary differential equations (ODEs) presence absence radiotherapy. Female Wistar rats (N = 21) were inoculated intracranially with 10 6 C6 glioma cells, subset which received 20 Gy 5) 40 8) radiation. All underwent diffusion-weighted dynamic contrast-enhanced MRI at up seven time points. each visit subsequently clustered k -means identify tumor habitats. A family four models consisting three ODEs developed calibrated habitat series control treated evaluated for predictive capability. The Akaike Information Criterion was used selection, normalized sum-of-square-error (SSE) evaluate goodness-of-fit calibration prediction. Three significantly different characteristics ( p < 0.05) identified: high-vascularity high-cellularity, low-vascularity low-cellularity. Model selection resulted five-parameter whose predictions dynamics yielded SSEs that similar from model. It is thus feasible mathematically describe preclinical biology-based ODEs, showing promise forecasting heterogeneous behavior.

Язык: Английский

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Dynamics-Adapted Radiotherapy Dose (DARD) for Head and Neck Cancer Radiotherapy Dose Personalization

Journal of Personalized Medicine, Год журнала: 2021, Номер 11(11), С. 1124 - 1124

Опубликована: Ноя. 1, 2021

Standard of care radiotherapy (RT) doses have been developed as a one-size-fits all approach designed to maximize tumor control rates across population. Although this has led high for head and neck cancer with 66-70 Gy, is done without considering patient heterogeneity. We present framework estimate personalized RT dose individual patients, based on pre- early on-treatment volume dynamics-a dynamics-adapted (DDARD). also the results an in silico trial personalization using retrospective data from combined cohort n = 39 patients Moffitt MD Anderson Cancer Centers that received Gy 2-2.12 weekday fractions. This was repeated constraining DDARD between (54, 82) test more moderate adjustment. estimated range 8 186 our 77% treated standard were overdosed by average 23% underdosed 32 Gy. The constrained adjustment locoregional could be improved >10%. demonstrated feasibility treatment dynamics inform stratification escalation de-escalation. These demonstrate potential both de-escalate most while still improving population-level rates.

Язык: Английский

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Rethinking the immunotherapy numbers game

Journal for ImmunoTherapy of Cancer, Год журнала: 2022, Номер 10(7), С. e005107 - e005107

Опубликована: Июль 1, 2022

Immunotherapies are a major breakthrough in oncology, yielding unprecedented response rates for some cancers. Especially combination with conventional treatments or targeted agents, immunotherapeutics offer invaluable tools to improve outcomes many patients. However, why not all patients have favorable remains unclear. There is an increasing appreciation of the contributions complex tumor microenvironment, and tumor-immune ecosystem particular, treatment outcome. To date, however, there exists no immune biomarker explain two similar clinical stage molecular profile would different outcomes. We hypothesize that it critical understand both states how system will respond treatment. Here, we present integrated mathematical oncology approaches can help conceptualize effect various immunotherapies on patient's local environment, combinations immunotherapy cytotoxic therapy may be used control limit toxicity per patient basis.

Язык: Английский

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Dynamic Behaviors of a Periodic System with Threshold Policy-Guided Periodic and Intermittent Therapy of Tumor

SIAM Journal on Applied Mathematics, Год журнала: 2025, Номер 85(1), С. 366 - 392

Опубликована: Фев. 18, 2025

Язык: Английский

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Personalized radiotherapy doses from the integration of mathematical oncology and machine learning

Radiotherapy and Oncology, Год журнала: 2025, Номер unknown, С. 110902 - 110902

Опубликована: Апрель 1, 2025

Язык: Английский

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Modelling Radiation Cancer Treatment with a Death-Rate Term in Ordinary and Fractional Differential Equations

Bulletin of Mathematical Biology, Год журнала: 2023, Номер 85(6)

Опубликована: Апрель 25, 2023

Abstract Fractional calculus has recently been applied to the mathematical modelling of tumour growth, but its use introduces complexities that may not be warranted. Mathematical with differential equations is a standard approach study and predict treatment outcomes for population-level patient-specific responses. Here, we patient data radiation-treated tumours discuss benefits limitations introducing fractional derivatives into three models growth. The derivative history-dependence growth function, which requires continuous death-rate term radiation treatment. This newly proposed radiation-induced improves computational efficiency in both ordinary models. speed-up will benefit common simulation tasks such as model parameterization construction running virtual clinical trials.

Язык: Английский

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Mathematical modeling of radiotherapy: impact of model selection on estimating minimum radiation dose for tumor control

Frontiers in Oncology, Год журнала: 2023, Номер 13

Опубликована: Окт. 9, 2023

Introduction Radiation therapy (RT) is one of the most common anticancer therapies. Yet, current radiation oncology practice does not adapt RT dose for individual patients, despite wide interpatient variability in radiosensitivity and accompanying treatment response. We have previously shown that mechanistic mathematical modeling tumor volume dynamics can simulate volumetric response to patients estimation personalized optimal reduction. However, understanding implications choice underlying model critical when calculating dose. Methods In this study, we evaluate biological effects 2 models on personalization: (1) cytotoxicity cancer cells lead direct reduction (DVR) (2) responses microenvironment carrying capacity (CCR) subsequent shrinkage. Tumor growth was simulated as logistic with pre-treatment being described proliferation saturation index (PSI). The effect according each respective a standard schedule fractionated Gy weekday fractions. Parameter sweeps were evaluated intrinsic rate parameter both observe qualitative impact parameter. then calculated minimum required locoregional control (LRC) across all combinations full range radiosensitvity values. Results Both estimate higher will require lower achieve LRC. two make opposite estimates PSI LRC: DVR tumors values LRC, while CCR Discussion Ultimately, these results show importance which best describes particular setting, before using any such recommendations.

Язык: Английский

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From Fitting the Average to Fitting the Individual: A Cautionary Tale for Mathematical Modelers

Frontiers in Oncology, Год журнала: 2022, Номер 12

Опубликована: Апрель 28, 2022

An outstanding challenge in the clinical care of cancer is moving from a one-size-fits-all approach that relies on population-level statistics towards personalized therapeutic design. Mathematical modeling powerful tool treatment personalization, as it allows for incorporation patient-specific data so can be tailor-designed to individual. Herein, we work with mathematical model murine immunotherapy has been previously-validated against average an experimental dataset. We ask question: what happens if try use this same perform fits, and therefore make individualized recommendations? Typically, would done by choosing single fitting methodology, cost function, identifying best-fit parameters, extrapolating there recommendations. Our analyses show potentially problematic nature approach, predicted response proved sensitive methodology utilized. also demonstrate how small amount right additional measurements could go long way improve consistency fits. Finally, quantifying robustness help confidence

Язык: Английский

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