Jan Poleszczuk

Abscopal Benefits of Localized Radiotherapy Depend on Activated T-cell Trafficking and Distribution between Metastatic Lesions

It remains unclear how localized radiotherapy for cancer metastases can occasionally elicit a systemic antitumor effect, known as the abscopal effect, but historically, it has been speculated to reflect the generation of a host immunotherapeutic response. The ability to purposefully and reliably induce abscopal effects in metastatic tumors could meet many unmet clinical needs. Here, we describe a mathematical model that incorporates physiologic information about T-cell trafficking to estimate the distribution of focal therapy-activated T cells between metastatic lesions. We integrated a dynamic model of tumor-immune interactions with systemic T-cell trafficking patterns to simulate the development of metastases. In virtual case studies, we found that the dissemination of activated T cells among multiple metastatic sites is complex and not intuitively predictable. Furthermore, we show that not all metastatic sites participate in systemic immune surveillance equally, and therefore the success in triggering the abscopal effect depends, at least in part, on which metastatic site is selected for localized therapy. Moreover, simulations revealed that seeding new metastatic sites may accelerate the growth of the primary tumor, because T-cell responses are partially diverted to the developing metastases, but the removal of the primary tumor can also favor the rapid growth of preexisting metastatic lesions. Collectively, our work provides the framework to prospectively identify anatomically defined focal therapy targets that are most likely to trigger an immune-mediated abscopal response and therefore may inform personalized treatment strategies in patients with metastatic disease.

Evolution and Phenotypic Selection of Cancer Stem Cells

Cells of different organs at different ages have an intrinsic set of kinetics that dictates their behavior. Transformation into cancer cells will inherit these kinetics that determine initial cell and tumor population progression dynamics. Subject to genetic mutation and epigenetic alterations, cancer cell kinetics can change, and favorable alterations that increase cellular fitness will manifest themselves and accelerate tumor progression. We set out to investigate the emerging intratumoral heterogeneity and to determine the evolutionary trajectories of the combination of cell-intrinsic kinetics that yield aggressive tumor growth. We develop a cellular automaton model that tracks the temporal evolution of the malignant subpopulation of so-called cancer stem cells(CSC), as these cells are exclusively able to initiate and sustain tumors. We explore orthogonal cell traits, including cell migration to facilitate invasion, spontaneous cell death due to genetic drift after accumulation of irreversible deleterious mutations, symmetric cancer stem cell division that increases the cancer stem cell pool, and telomere length and erosion as a mitotic counter for inherited non-stem cancer cell proliferation potential. Our study suggests that cell proliferation potential is the strongest modulator of tumor growth. Early increase in proliferation potential yields larger populations of non-stem cancer cells(CC) that compete with CSC and thus inhibit CSC division while a reduction in proliferation potential loosens such inhibition and facilitates frequent CSC division. The sub-population of cancer stem cells in itself becomes highly heterogeneous dictating population level dynamics that vary from long-term dormancy to aggressive progression. Our study suggests that the clonal diversity that is captured in single tumor biopsy samples represents only a small proportion of the total number of phenotypes.

New approach to modeling of antiangiogenic treatment on the basis of Hahnfeldt et al. model

In the paper we propose a new methodology in modeling of antiangiogenic treatment on the basis of well recognized model formulated by Hahnfeldt et al. in 1999. On the basis of the Hahnfeldt et al. model, with the usage of the optimal control theory, some protocols of antiangiogenic treatment were proposed. However, in our opinion the formulation of that model is valid only for the antivascular treatment, that is treatment that is focused on destroying endothelial cells. Therefore, we propose a modification of the original model which is valid in the case of the antiangiogenic treatment, that is treatment which is focused on blocking angiogenic signaling. We analyze basic mathematical properties of the proposed model and present some numerical simulations.

Stochastic Models of Gene Expression with Delayed Degradation

In many biochemical reactions occurring in living cells, number of various molecules might be low which results in significant stochastic fluctuations. In addition, most reactions are not instantaneous, there exist natural time delays in the evolution of cell states. It is a challenge to develop a systematic and rigorous treatment of stochastic dynamics with time delays and to investigate combined effects of stochasticity and delays in concrete models.We propose a new methodology to deal with time delays in biological systems and apply it to simple models of gene expression with delayed degradation. We show that time delay of protein degradation does not cause oscillations as it was recently argued. It follows from our rigorous analysis that one should look for different mechanisms responsible for oscillations observed in biological experiments.We develop a systematic analytical treatment of stochastic models of time delays. Specifically we take into account that some reactions, for example degradation, are consuming, that is: once molecules start to degrade they cannot be part in other degradation processes.We introduce an auxiliary stochastic process and calculate analytically the variance and the autocorrelation function of the number of protein molecules in stationary states in basic models of delayed protein degradation.

Cancer Stem Cell Plasticity as Tumor Growth Promoter and Catalyst of Population Collapse

It is increasingly argued that cancer stem cells are not a cellular phenotype but rather a transient state that cells can acquire, either through intrinsic signaling cascades or in response to environmental cues. While cancer stem cell plasticity is generally associated with increased aggressiveness and treatment resistance, we set out to thoroughly investigate the impact of different rates of plasticity on early and late tumor growth dynamics and the response to therapy. We develop an agent-based model of cancer stem cell driven tumor growth, in which plasticity is defined as a spontaneous transition between stem and nonstem cancer cell states. Simulations of the model show that plasticity can substantially increase tumor growth rate and invasion. At high rates of plasticity, however, the cells get exhausted and the tumor will undergo spontaneous remission in the long term. In a series of in silico trials, we show that such remission can be facilitated through radiotherapy. The presented study suggests that stem cell plasticity has rather complex, nonintuitive implications on tumor growth and treatment response. Further theoretical, experimental, and integrated studies are needed to fully decipher cancer stem cell plasticity and how it can be harnessed for novel therapeutic approaches.

Therapeutic Implications from Sensitivity Analysis of Tumor Angiogenesis Models

Anti-angiogenic cancer treatments induce tumor starvation and regression by targeting the tumor vasculature that delivers oxygen and nutrients. Mathematical models prove valuable tools to study the proof-of-concept, efficacy and underlying mechanisms of such treatment approaches. The effects of parameter value uncertainties for two models of tumor development under angiogenic signaling and anti-angiogenic treatment are studied. Data fitting is performed to compare predictions of both models and to obtain nominal parameter values for sensitivity analysis. Sensitivity analysis reveals that the success of different cancer treatments depends on tumor size and tumor intrinsic parameters. In particular, we show that tumors with ample vascular support can be successfully targeted with conventional cytotoxic treatments. On the other hand, tumors with curtailed vascular support are not limited by their growth rate and therefore interruption of neovascularization emerges as the most promising treatment target.

A simple model of carcinogenic mutations with time delay and diffusion

In the paper we consider a system of delay differential equations (DDEs) of Lotka-Volterra type with diffusion reflecting mutations from normal to malignant cells. The model essentially follows the idea of Ahangar and Lin (2003) where mutations in three different environmental conditions, namely favorable, competitive and unfavorable, were considered. We focus on the unfavorable conditions that can result from a given treatment, e.g. chemotherapy. Included delay stands for the interactions between benign and other cells. We compare the dynamics of ODEs system, the system with delay and the system with delay and diffusion. We mainly focus on the dynamics when a positive steady state exists. The system which is globally stable in the case without the delay and diffusion is destabilized by increasing delay, and therefore the underlying kinetic dynamics becomes oscillatory due to a Hopf bifurcation for appropriate values of the delay. This suggests the occurrence of spatially non-homogeneous periodic solutions for the system with the delay and diffusion.

Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth

Computational modeling of tumor growth has become an invaluable tool to simulate complex cell-cell interactions and emerging population-level dynamics. Agent-based models are commonly used to describe the behavior and interaction of individual cells in different environments. Behavioral rules can be informed and calibrated by in vitro assays, and emerging population-level dynamics may be validated with both in vitro and in vivo experiments. Here, we describe the design and implementation of a lattice-based agent-based model of cancer stem cell driven tumor growth.

The different radiation response and radiation-induced bystander effects in colorectal carcinoma cells differing in p53 status.

Radiation-induced bystander effect, appearing as different biological changes in cells that are not directly exposed to ionizing radiation but are under the influence of molecular signals secreted by irradiated neighbors, have recently attracted considerable interest due to their possible implication for radiotherapy. However, various cells present diverse radiosensitivity and bystander responses that depend, inter alia, on genetic status including TP53, the gene controlling the cell cycle, DNA repair and apoptosis. Here we compared the ionizing radiation and bystander responses of human colorectal carcinoma HCT116 cells with wild type or knockout TP53 using a transwell co-culture system. The viability of exposed to X-rays (0-8 Gy) and bystander cells of both lines showed a roughly comparable decline with increasing dose. The frequency of micronuclei was also comparable at lower doses but at higher increased considerably, especially in bystander TP53-/- cells. Moreover, the TP53-/- cells showed a significantly elevated frequency of apoptosis, while TP53+/+ counterparts expressed high level of senescence. The cross-matched experiments where irradiated cells of one line were co-cultured with non-irradiated cells of opposite line show that both cell lines were also able to induce bystander effects in their counterparts, however different endpoints revealed with different strength. Potential mediators of bystander effects, IL-6 and IL-8, were also generated differently in both lines. The knockout cells secreted IL-6 at lower doses whereas wild type cells only at higher doses. Secretion of IL-8 by TP53-/- control cells was many times lower than that by TP53+/+ but increased significantly after irradiation. Transcription of the NFκBIA was induced in irradiated TP53+/+ mainly, but in bystanders a higher level was observed in TP53-/- cells, suggesting that TP53 is required for induction of NFκB pathway after irradiation but another mechanism of activation must operate in bystander cells.

Phosphate kinetics during weekly cycle of hemodialysis sessions: Application of mathematical modeling

Both hyperphosphatemia and hypophosphatemia are associated with increased morbidity and mortality among patients on dialysis. The control of serum phosphate concentration is a considerable clinical problem. Our study aimed to improve understanding of phosphate kinetics in patients on dialysis using mathematical modeling. Three consecutive hemodialysis sessions with breaks of 2-2-3 days were monitored in 25 patients. Phosphate concentration was measured every hour and 45 min after the end of dialysis in blood serum and every 30 min in dialysate during each session. Volume of fluid compartments and body composition were assessed by bioimpedance. The pseudo one-compartment model was applied to describe the profile of phosphate in blood serum during intra- and interdialytic periods of 1-week cycle of three hemodialysis sessions. Model parameters, such as phosphate internal clearance (KM ) and the rate of phosphate mobilization (RM ), were correlated with the reduction of serum phosphate concentration during dialysis (Cpost /Cpre ) and with equivalent continuous clearance (ECC) for phosphate. KM correlated negatively with predialysis serum phosphate concentration. There was significant positive correlation between RM and age. Postdialysis volume of phosphate central compartment was lower than, but correlated to, extracellular water volume. Parameters of the pseudo one-compartment model, phosphate internal clearance, and the rate of phosphate inflow to the central compartment (the one accessible for dialysis) from other phosphate body reservoirs correlated with the indices of dialysis adequacy, such as reduction of serum phosphate and ECC. The pseudo one-compartment model can be successfully extended from a single hemodialysis to the standard weekly cycle of sessions and the model parameters strongly correlate with the adequacy parameters of dialytic removal of phosphate.