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Related papers: Tumor containment for Norton-Simon models

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Adaptive therapy (AT) is designed to postpone the emergence of drug resistance by exploiting evolutionary competition among tumor subclones. Most mathematical models of AT assume a binary population structure of drug-sensitive and…

Populations and Evolution · Quantitative Biology 2026-05-19 Rui Yue , Chenghang Li , Jinzhi Lei

Theoretical and computational tools that can be used in the clinic to predict neoplastic progression and propose individualized optimal treatment strategies to control cancer growth is desired. To develop such a predictive model, one must…

Cell Behavior · Quantitative Biology 2015-05-20 Salvatore Torquato

This research presents a mathematical model of glioma growth dynamics with drug resistance, capturing interactions among five cell populations: glial cells, sensitive glioma cells, resistant glioma cells, endothelial cells, and neuron…

Dynamical Systems · Mathematics 2023-08-23 Latifah Hanum , Nanang Susyanto , Dwi Ertiningsih

This paper focuses on the analytic modelling of responses of cells in the body to ionizing radiation. The related mechanisms are consecutively taken into account and discussed. A model of the dose- and time-dependent adaptive response is…

One of the barriers to the development of effective adoptive cell transfer therapies (ACT), specifically for genetically engineered T-cell receptors (TCRs), and chimeric antigen receptor (CAR) T-cells, is target antigen heterogeneity. It is…

Targeted therapies on the basis of genomic aberrations analysis of the tumor have shown promising results in cancer prognosis and treatment. Regardless of tumor type, trials that match patients to targeted therapies for their particular…

Applications · Statistics 2018-04-18 Yanxun Xu , Peter Mueller , Apostolia M Tsimberidou , Donald Berry

In a previous paper we have introduced a phenomenological model of cell metabolism and of the cell cycle to simulate the behavior of large tumor cell populations (Chignola R and Milotti E, Phys. Biol. 2 (2005) 8-22). Here we describe a…

Biological Physics · Physics 2009-11-13 Roberto Chignola , Alessio Del Fabbro , Chiara Dalla Pellegrina , Edoardo Milotti

Cancer is a disease driven by random DNA mutations and the interaction of many complex phenomena. To improve the understanding and ultimately find more effective treatments, researchers leverage computer simulations mimicking the tumor…

Computational Physics · Physics 2024-01-26 Tobias Duswald , Ernesto A. B. F. Lima , J. Tinsley Oden , Barbara Wohlmuth

Development of resistance limits efficiency of present anticancer therapies and preventing it remains big challenge in cancer research. It is accepted, at intuitive level, that the resistance emerges as a consequence of cancer cells…

Quantitative Methods · Quantitative Biology 2015-06-02 Branislav Brutovsky , Denis Horvath

Brain tumours are masses of abnormal cells that can grow in an uncontrolled way in the brain. There are different types of malignant brain tumours. Gliomas are malignant brain tumours that grow from glial cells and are identified as…

Computational systems and methods are often being used in biological research, including the understanding of cancer and the development of treatments. Simulations of tumor growth and its response to different drugs are of particular…

In this paper, we study a tumor growth model with nutrients. The contact inhibition for the tumor cells, presented in the model, results in the evolution of a congested tumor patch. We study the regularity of the tumor patch as the…

Analysis of PDEs · Mathematics 2022-12-01 Inwon Kim , Jona Lelmi

Cancer development is driven by mutations and selective forces, including the action of the immune system and interspecific competition. When administered to patients, anti-cancer therapies affect the development and dynamics of tumours,…

Dynamical Systems · Mathematics 2021-09-30 Elena Piretto , Marcello Delitala , Peter S. Kim , Federico Frascoli

Tumor development is characterized by a compromised balance between cell life and death decision mechanisms, which are tighly regulated in normal cells. Understanding this process provides insights for developing new treatments for fighting…

Molecular Networks · Quantitative Biology 2013-01-14 Andrei Zinovyev , Simon Fourquet , Laurent Tournier , Laurence Calzone , Emmanuel Barillot

Large variability between cell lines brings a difficult optimization problem of drug selection for cancer therapy. Standard approaches use prediction of value for this purpose, corresponding e.g. to expected value of their distribution.…

Quantitative Methods · Quantitative Biology 2022-09-15 Jarek Duda

Metastasis, the spread of cancer cells from a primary tumor to secondary location(s) in the human organism, is the ultimate cause of death for the majority of cancer patients. That is why, it is crucial to understand metastases evolution in…

Populations and Evolution · Quantitative Biology 2020-06-24 Maroussia Slavtchova-Bojkova , Kaloyan Vitanov

The problem of chemotherapy treatment optimization can be defined in order to minimize the size of the tumor without endangering the patient's health; therefore, chemotherapy requires to achieve a number of objectives, simultaneously. For…

Neural and Evolutionary Computing · Computer Science 2023-03-21 Mina Jafari , Behnam Ghavami , Vahid Sattari Naeini

The concept of personalised medicine in cancer therapy is becoming increasingly important. There already exist drugs administered specifically for patients with tumours presenting well-defined mutations. However, the field is still in its…

Biomolecules · Quantitative Biology 2024-08-26 Abbi Abdel-Rehim , Oghenejokpeme Orhobor , Gareth Griffiths , Larisa Soldatova , Ross D. King

The majority of cancer treatments end in failure due to Intra-Tumor Heterogeneity (ITH). ITH in cancer is represented by clonal evolution where different sub-clones compete with each other for resources under conditions of Darwinian natural…

The appearance of cancer in a tissue is thought to be the result of two or more successive mutations. We propose a stochastic model that allows for an exact computation of the distribution of the waiting time for a second mutation. This…

Probability · Mathematics 2014-03-05 Rinaldo B. Schinazi