Spatial avascular growth of tumor in a homogeneous environment.

Describing tumor growth is a key issue in oncology for correctly understanding the underlying mechanisms leading to deleterious cancers. In order to take into account the micro-environment in tumor growth, we used a model describing - at the tissue level - the interactions between host (non malignant), effector immune and tumor cells to simulate the evolution of cancer. The spatial growth is described by a Laplacian operator for the diffusion of tumor cells. We investigated how the evolution of the tumor diameter is related to the dynamics (periodic or chaotic oscillations, stable singular points) underlying the interactions between the different populations of cells in proliferation sites. The sensitivity of this evolution to the key parameter responsible for the immuno-evasion, namely the growth rate of effector immune cells and their inhibition rate by tumor cells, is also investigated.

How the growth rate of host cells affects cancer risk in a deterministic way.

It is well known that cancers are significantly more often encountered in some tissues than in other ones. In this paper, by using a deterministic model describing the interactions between host, effector immune and tumor cells at the tissue level, we show that this can be explained by the dependency of tumor growth on parameter values characterizing the type as well as the state of the tissue considered due to the "way of life" (environmental factors, food consumption, drinking or smoking habits, etc.). Our approach is purely deterministic and, consequently, the strong correlation (r = 0.99) between the number of detectable growing tumors and the growth rate of cells from the nesting tissue can be explained without evoking random mutation arising during DNA replications in nonmalignant cells or "bad luck". Strategies to limit the mortality induced by cancer could therefore be well based on improving the way of life, that is, by better preserving the tissue where mutant cells randomly arise.

A cancer model for the angiogenic switch.

The occurrence of metastasis is an important feature in cancer development. In order to have a one-site model taking into account the interactions between host, effector immune and tumor cells which is not only valid for the early stages of tumor growth, we developed in this paper a new model where are incorporated interactions of these three cell populations with endothelial cells. These latter cells are responsible for the neo-vascularization of the tumor site which allows the migration of tumor cells to distant sites. It is then shown that, for some parameter values, the resulting model for the four cell populations reproduces the angiogenic switch, that is, the transition from avascular to vascular tumor.

Detecting lung cancer relapse using self-evaluation forms weekly filled at home: the sentinel follow-up.

PURPOSE: We aimed to assess if patients' ratings of symptoms can be used to provide an early indication of disease recurrence or progression in lung cancer. We proposed a simple self-evaluation form made of six clinical parameters weekly scored by patients at home as a follow-up--here named sentinel--to improve relapse detection. Its performances were compared to those of a routine imaging follow-up. METHODS: Patients with lung cancer were prospectively recruited to weekly fill a form at home for self-assessing weight, fatigue, pain, appetite, cough, and breathlessness during at least 4 months. Each patient reported weight and assessed the severity of each symptom by grading it from 0 (no symptom) to 3 (major symptom). A score was retrospectively designed for discriminating patients with relapse from those without. Accuracy of relapse detection was then compared to values of the routine planned imaging. RESULTS: Forty-three patients were included in our center and recruited for 16 weeks or more follow-up during which at least one tumor imaging assessment was performed (CT scan or PET-CT). Forty-one completed the form weekly. Sensitivity, specificity, and positive and negative predictive values of sentinel were high (86, 93, 86 % and 93 vs 79, 96, 92, and 90 % for routine imaging--p = ns) and well correlated with relapse (pχ2 > 0.001). Moreover, relapses were detectable with sentinel on average 6 weeks earlier than the planned imaging. CONCLUSION: This study suggests that a personalized cancer follow-up based on a weekly self-evaluation of six symptoms is feasible and may be accurate for earlier detection of lung cancer relapse, allowing integration in electronic devices for real-time patient outcome follow-up.

Detection of lung cancer relapse using self-reported symptoms transmitted via an internet web-application: pilot study of the sentinel follow-up.

PURPOSE: We aimed to investigate whether patient self-evaluated symptoms transmitted via Internet can be used between planned visits to provide an early indication of disease relapse in lung cancer. METHODS: Between 2/2013 and 8/2013, 42 patients with lung cancer having access to Internet were prospectively recruited to weekly fill a form of 11 self-assessed symptoms called "sentinel follow-up". Data were sent to the oncologist in real-time between planned visits. An alert email was sent to oncologist when self-scored symptoms matched some predefined criteria. Follow-up visit and imaging were then organized after a phone call for confirming suspect symptoms. Weekly and monthly compliances, easiness with which patients used the web-application and the accuracy of the sentinel follow-up for relapse detection were assessed and compared to a routine visit and imaging follow-up. RESULTS: Median follow-up duration was 18 weeks (8-32). Weekly and monthly average compliances were 79 and 94 %, respectively. Sixty percents of patients declared to be less anxious during the few days before planned visit and imaging with the sentinel follow-up than without. Sensitivity, specificity, positive, and negative predictive values provided by the sentinel (planned imaging) follow-up were 100 %(84 %), 89 %(96 %), 81 %(91 %), and 100 %(93 %), respectively and well correlated with relapse (pχ (2) < 0.001). On average, relapses were detectable 5 weeks earlier with sentinel than planned visit. CONCLUSION: An individualized cancer follow-up that schedule visit and imaging according to the patient status based on weekly self-reported symptoms transmitted via Internet is feasible with high compliance. It may even provide earlier detection of lung cancer relapse and care.

DNA break clustering as a predictor of cell death across various radiation qualities: influence of cell size, cell asymmetry, and beam orientation.

Cosmic radiation, composed of high charge and energy (HZE) particles, causes cellular DNA damage that can result in cell death or mutation that can evolve into cancer. In this work, a cell death model is applied to several cell lines exposed to HZE ions spanning a broad range of linear energy transfer (LET) values. We hypothesize that chromatin movement leads to the clustering of multiple double strand breaks (DSB) within one radiation-induced foci (RIF). The survival probability of a cell population is determined by averaging the survival probabilities of individual cells, which is function of the number of pairwise DSB interactions within RIF. The simulation code RITCARD was used to compute DSB. Two clustering approaches were applied to determine the number of RIF per cell. RITCARD outputs were combined with experimental data from four normal human cell lines to derive the model parameters and expand its predictions in response to ions with LET ranging from ~0.2 keV/µm to ~3000 keV/µm. Spherical and ellipsoidal nuclear shapes and two ion beam orientations were modeled to assess the impact of geometrical properties on cell death. The calculated average number of RIF per cell reproduces the saturation trend for high doses and high-LET values that is usually experimentally observed. The cell survival model generates the recognizable bell shape of LET dependence for the relative biological effectiveness (RBE). At low LET, smaller nuclei have lower survival due to increased DNA density and DSB clustering. At high LET, nuclei with a smaller irradiation area-either because of a smaller size or a change in beam orientation-have a higher survival rate due to a change in the distribution of DSB/RIF per cell. If confirmed experimentally, the geometric characteristics of cells would become a significant factor in predicting radiation-induced biological effects. Insight Box: High-charge and energy (HZE) ions are characterized by dense linear energy transfer (LET) that induce unique spatial distributions of DNA damage in cell nuclei that result in a greater biological effect than sparsely ionizing radiation like X-rays. HZE ions are a prominent component of galactic cosmic ray exposure during human spaceflight and specific ions are being used for radiotherapy. Here, we model DNA damage clustering at sub-micrometer scale to predict cell survival. The model is in good agreement with experimental data for a broad range of LET. Notably, the model indicates that nuclear geometry and ion beam orientation affect DNA damage clustering, which reveals their possible role in mediating cell radiosensitivity.

Dose, LET and Strain Dependence of Radiation-Induced 53BP1 Foci in 15 Mouse Strains Ex Vivo Introducing Novel DNA Damage Metrics.

We present a comprehensive comparative analysis on the repair of radiation-induced DNA damage ex vivo in 15 strains of mice, including 5 inbred reference strains and 10 collaborative-cross strains, of both sexes, totaling 5 million skin fibroblast cells imaged by three-dimensional highthroughput conventional microscopy. Non-immortalized primary skin fibroblasts derived from 76 mice were subjected to increasing doses of both low- and high-LET radiation (X rays; 350 MeV/n 40Ar; 600 MeV/n 56Fe), which are relevant to carcinogenesis and human space exploration. Automated image quantification of 53BP1 radiation-induced foci (RIF) formation and repair during the first 4-48 h postirradiation was performed as a function of dose and LET. Since multiple DNA double-strand breaks (DSBs) are induced in a dose- and LET-dependent manner, our data suggest that when DSBs are formed within the same discrete nuclear region, referred to as the "repair domain", novel mathematical formalisms used to report RIF allowed us to conclude that multiple DSBs can be present in single RIF. Specifically, we observed that the number of RIF per Gy was lower for higher X-ray doses or higher LET particles (i.e., 600 MeV/n 56Fe), suggesting there are more DSBs per RIF when the local absorbed dose increases in the nucleus. The data also clearly show that with more DSBs per RIF, it becomes more difficult for cells to fully resolve RIF. All 15 strains showed the same dose and LET dependence, but strain differences were preserved under various experimental conditions, indicating that the number and sizes of repair domains are modulated by the genetic background of each strain.