Article
Mathematics
Chayu Yang, Jin Wang
Summary: We propose a mathematical model based on ordinary differential equations to study the homogeneous state of tumor growth under virotherapy. The model focuses on the interaction among tumor cells, oncolytic viruses, and the host immune system, which generate innate and adaptive immune responses. Through rigorous equilibrium analysis, we derive threshold conditions that determine tumor growth or decay under different scenarios. Numerical simulations validate our analytical predictions and offer additional insights into tumor growth dynamics.
Article
Pharmacology & Pharmacy
Vincent Lemaire, David Bassen, Mike Reed, Roy Song, Samira Khalili, Yi Ting Kayla Lien, Lu Huang, Aman P. Singh, Spyros Stamatelos, Dean Bottino, Fei Hua
Summary: Immuno-oncology is a rapidly growing field in cancer treatment, and quantitative systems pharmacology modeling plays a significant role in addressing the challenges in this field.
CLINICAL PHARMACOLOGY & THERAPEUTICS
(2023)
Article
Biology
Milad Mousavi, Mahsa Dehghan Manshadi, Madjid Soltani, Farshad M. Kashkooli, Arman Rahmim, Amir Mosavi, Michal Kvasnica, Peter M. Atkinson, Levente Kovacs, Andras Koltay, Norbert Kiss, Hojjat Adeli
Summary: Accurate simulation of tumor growth during chemotherapy can optimize clinical trials and reduce the risk of unknown side effects. This study developed a 3D simulation model to evaluate the efficacy of different anti-angiogenic drugs and proposed comprehensive mechanisms for accurate predictions of drug treatments. The results showed that Beovu was the most effective drug, and machine learning techniques were used to extract additional features for understanding tumor growth and drug efficacy.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Oncology
Mitsuaki Takaki, Hiroshi Haeno
Summary: Locoregional recurrence after surgery is a major challenge in cancer treatment, with premalignant lesions playing a significant role in driving cancer recurrence. A mathematical model combining Moran and branching processes was used to study cancer initiation and recurrence, shedding light on the process of cancer development.
FRONTIERS IN ONCOLOGY
(2021)
Article
Oncology
Mariusz Bodzioch, Piotr Bajger, Urszula Forys
Summary: Chemotherapy drug resistance is a major concern, and one proposed solution is to use metronomic therapy to maintain cancer instead of completely eradicating it. Mathematical modeling and optimal control techniques indicate that low doses of chemotherapy are beneficial for patients, leading to longer survival times.
JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY
(2021)
Article
Biology
Jesse Milzman, Wanqiang Sheng, Doron Levy
Summary: This study developed a mathematical model to investigate the immunogenic effects of LSD1 inhibition, which showed that LSD1 inhibition accelerates anti-tumor cytotoxicity. However, cytotoxicity alone does not explain the slower tumor growth observed in LSD1-inhibited tumors, indicating potential immune-mediation of this effect.
BULLETIN OF MATHEMATICAL BIOLOGY
(2021)
Article
Thermodynamics
Graziella Marino, Maria Valeria De Bonis, Laura Lagonigro, Giuseppe La Torre, Antonella Prudente, Alessandro Sgambato, Gianpaolo Ruocco
Summary: Mathematical modeling in oncological research is used to predict the evolution of tumors at different scales. This study focuses on utilizing mass transfer modeling to gain insights into breast carcinoma proliferation and therapy at the tissue scale, aiming to develop personalized predictive methods for patients. The flexible model has potential for replication across large patient cohorts and can serve as a basis for decision support systems for surgeons and personalized treatment optimization of breast tumors.
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER
(2021)
Article
Mathematics, Applied
Irina Bashkirtseva, Anna Chukhareva, Lev Ryashko
Summary: This study examines the effects of treatment on tumor-immune dynamics using a conceptual two-dimensional model. The research finds that increasing chemotherapy intensity can lead to a complication of tumor-immune interaction with multiple tumor states potentially coexisting. The results of the study contribute to evaluating the efficiency of treatment programs combining chemotherapy and radiotherapy.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2022)
Review
Cell Biology
Karla F. Corral-Jara, Goncalo Rosas da Silva, Nora A. Fierro, Vassili Soumelis
Summary: CD4 + T cell differentiation is controlled by gene regulatory and metabolic networks, with Th17 and Tregs playing crucial roles in cancer, influenced by the tumor microenvironment. The modeling of biological systems has emerged as a promising solution for understanding CD4 + T cell differentiation and cancer cell behavior better. Integration of mechanistic models with omics data can predict transcriptomic and metabolomic reprogramming of Th17 and Tregs cells for potential clinical applications, particularly in cancer immunotherapy.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2021)
Article
Biology
Daniel R. Bergman, Matthew K. Karikomi, Min Yu, Qing Nie, Adam L. MacLean
Summary: Bergman, Karikomi et al. propose a multiscale evolutionary model to describe tumor-immune-EMT interactions and their impact on epithelial cancer progression, which highlights a controllable region that maximizes invasion-free survival. Using EMT-inflammation associated TCGA data, the authors find EMT association worsens invasion-free survival and identify genes that influence outcomes in bladder and uterine cancer.
COMMUNICATIONS BIOLOGY
(2021)
Article
Thermodynamics
Rosj Gallicchio, Paolo Caccavale, Maria Valeria De Bonis, Anna Nardelli, Graziella Marino, Alessandro Sgambato, Gianpaolo Ruocco, Giovanni Storto
Summary: Mathematical modeling in oncology research has potential applications for predicting tumor evolution, particularly for aggressive malignancies like DLBCL. Utilizing mass transfer modeling can provide deeper insights into tumor growth dynamics at the tissue scale, supporting personalized treatment optimization for solid tumors.
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER
(2021)
Article
Computer Science, Interdisciplinary Applications
Emad Farjami, Mohammad Mahjoob
Summary: A comprehensive model of chemotherapy treatment of cancer has been developed to predict tumor response and progression. The model includes multiple factors such as drug administration, immune cells, and nutrient competition, and has been validated with experimental and clinical data.
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING
(2023)
Article
Mathematics, Applied
Xinyue Evelyn Zhao, Wenrui Hao, Bei Hu
Summary: Free boundary problems involve systems of partial differential equations with unknown domain boundaries. In this paper, a novel approach based on neural network discretization is developed for solving a modified Hele-Shaw problem, the existence of the numerical solution is theoretically established. The approach is further verified by computing symmetry-breaking solutions near the radially-symmetric branch, as well as non-radially symmetric solutions not characterized by any theorems.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2021)
Article
Multidisciplinary Sciences
Sarah C. Brueningk, Jeffrey Peacock, Christopher J. Whelan, Hsiang-Hsuan M. Yu, Solmaz Sahebjam, Heiko Enderling, Renee Brady-Nicholls
Summary: Recurrent high grade glioma patients currently face poor prognosis without a curative treatment option. A personalized treatment strategy involving high dose intermittent radiation treatment (iRT) showed promising results compared to traditional high dose hypofractionated stereotactic radiotherapy (HFSRT) in a simulation analysis, especially for patients responsive to pembrolizumab and bevacizumab. Time to progression could be prolonged through intermittently delivered fractions, making iRT a potential treatment option for recurrent high grade glioma patients.
SCIENTIFIC REPORTS
(2021)
Article
Physics, Multidisciplinary
Hossein Heidari, Mahdi Rezaei Karamati, Hossein Motavalli
Summary: This study presents a stochastic tumor growth model based on the Morse potential and investigates the growth rate and geometry of breast cancer with and without radiation therapy effects using the solution of the Fokker-Planck equation. Breast data from the Surveillance, Epidemiology, and End Results program and a machine learning algorithm are used to estimate unknown parameters. Results show that tumor size increases over time while the growth rate decreases, and older women have a slower growth rate. Simulation results of breast tumors in mice confirm the consistency of the findings with experimental evidence. The study suggests that the present model is more accurate than the Gompertz model in predicting tumor size in the treatment case.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
