Multiscale modeling of  cancer growth and therapies

In summary, we investigate a multiscale model for virotherapy of cancer in which the cells are discrete agents. Our predictions are in qualitative agreement with results from clinical reports. Through extensive simulations, it was found that, for a single intratumoral virus administration, a solid tumor can completely be eradicated or keep growing after a transient remission. Furthermore, the model reveals undamped oscillatory dynamics of tumor cells and virus populations, which demands for new in vivo and in vitro quantitative experiments aiming to detect this oscillatory response. The conditions (regions in the model parameter space) for domination of each one of the different tumor responses, as well as the occurrence probabilities for the other nondominant therapeutic outcomes, were determined. From a clinical point of view, our findings indicate that a successful, single agent virotherapy requires a strong inhibition of the host immune response and the use of potent virus species with intratumoral high mobility. Moreover, due to the discrete and stochastic nature of cells and their responses, an optimal range for viral cytotoxicity is predicted because the virotherapy fails if the oncolytic virus demands either a too short or a very large time for killing the tumor cell. This finding suggests that the virus that kills cancer cells most rapidly is not necessarily the more effective agent to eradicate the tumor. The implications of such a result for the design of new replication-competent viruses are clear. (Cancer Research 69(3) 2009)

Here, the effects of oncolytic virotherapy on tumors having compact, papillary, and disconnected morphologies are investigated through computer simulations of a multiscale model coupling macroscopic reaction-diffusion equations for the nutrients with microscopic stochastic rules for the actions of individual cells and viruses. It was found that in immunosuppressed hosts, the antitumor efficacy of a virus is primarily determined by its entry efficiency, its replicative capacity within the tumor, and its ability to spread over the tissue. However, the optimal traits for oncolytic viruses depend critically on the tumor growth dynamics and do not necessarily include rapid replication, cytolysis, or spreading, currently assumed as necessary conditions for a successful therapeutic outcome.  (Phys. Rev. E 84, 041918 2011)

Here, a 3D model for chemotherapy based on anticancer nanoparticles is investigated. Therapeutic success is mainly determined by the nanoparticle endocytic rate. The eradication of highly vascularized tumors demands more aggressive therapies.  Our results discourage the use of therapies that normalize the tumor vasculature. 

Physica A: Statistical Mechanics and its Applications

Volume 455(1) 2016.

In this present book, I could join in a group of well-recognized specialists to discuss new ideas about the disease. These authors coming from solid backgrounds in physics, mathematics, medicine, molecular and cell biology, genetics, and anthropology have generously dedicated their time to write an authoritative text published under the open-access philosophy: quality academic texts that are worldwide free to access and read.

CANCER A COMPLEX DISEASE. Available from: http://scifunam.fisica.unam.mx/mir/copit/TS0017EN/TS0017EN.html

In this work, cancer chemotherapy using CP-NPs was evaluated through computer simulations of a multiscale model that combines diffusion equations for the nutrients, nanoparticle pharmacokinetics, and stochastic rules for the cell actions. Our results indicate that this therapy fails to eradicate solid tumors primarily due to the small CP-NP endocytic rates. Effective treatments should rely on CP-NPs exhibiting long residence time in the bloodstream, high selectivity for, and large endocytic rates by cancer cells. Such factors emerge as the main hurdles to be overcome in the search for efficient oncolytic nanotherapies. (Appl. Phys. Lett. 98, 053703 (2011))
 

Oncolytic virotherapy—the use of viruses that specifically kill tumor cells—is an innovative and highly promising route for treating cancer. However, its therapeutic outcomes are mainly impaired by the host immune response to the viral infection. In this paper, we propose a multiscale mathematical model to study how the immune response interferes with the viral oncolytic activity. The model assumes that cytotoxic T cells can induce apoptosis in infected cancer cells and that free viruses can be inactivated by neutralizing antibodies or cleared at a constant rate by the innate immune response. Our simulations suggest that reprogramming the immune microenvironment in tumors could substantially enhance the oncolytic virotherapy in immune-competent hosts. Viable routes to such reprogramming are either in situ virus-mediated impairing of CD8+ T cells motility or blockade of B and T lymphocytes recruitment. Our theoretical results can shed light on the design of viral vectors or new protocols with neat potential impacts on the clinical practice. Leticia R Paiva et al 2013 Phys. Biol. 10 025005