A branching process model of heterogeneous DNA damages caused by radiotherapy in in vitro cell cultures.

This paper deals with the dynamic modeling and simulation of cell damage heterogeneity and associated mutant cell phenotypes in the therapeutic responses of cancer cell populations submitted to a radiotherapy session during in vitro assays. Each cell is described by a finite number of phenotypic states with possible transitions between them. The population dynamics is then given by an age-dependent multi-type branching process. From this representation, we obtain formulas for the average size of the global survival population as well as the one of subpopulations associated with 10 mutation phenotypes. The proposed model has been implemented into Matlab© and the numerical results corroborate the ability of the model to reproduce four major types of cell responses: delayed growth, anti-proliferative, cytostatic and cytotoxic.

Tumor growth modeling based on cell and tumor lifespans.

This paper deals with the lifespan modeling of heterogenous tumors treated by radiotherapy. A bi-scale model describing the cell and tumor lifespans by random variables is proposed. First- and second-order moments as well as the cumulative distribution functions and confidence intervals are expressed for the two lifespans with respect to the model parameters. One interesting result is that the mean value of the tumor lifespan can be approached by a logarithmic function of the initial cancer cell number. Moreover, we show that TCP and NTCP, used in radiotherapy to evaluate, optimize and compare treatment plans, can be derived from the tumor lifespan and the surrounding healthy tissue, respectively. Finally, we propose a ROC curve, entitled ECT (Efficiency-Complication Trade-off), suited to the selection by clinicians of the appropriate treatment planning.

Multinomial model-based formulations of TCP and NTCP for radiotherapy treatment planning.

Hit and target models of tumor growth, typically assume that all surviving cells have a constant and homogeneous sensitivity during the radiotherapy period. In this study, we propose a new multinomial model based on a discrete-time Markov chain, able to take into account cell repair, cell damage heterogeneity and cell proliferation. The proposed model relies on the 'Hit paradigm' and 'Target' theory in radiobiology and assumes that a cancer cell contains m targets which must be all deactivated to produce cell death. The surviving cell population is then split up into m categories to introduce the variation of cancer cell radio-sensitivity according to their damage states. New expressions of the Tumor Control Probability (TCP) and Normal Tissue Complication Probability (NTCP) are provided. Moreover, we show that hit and target models may be regarded as particular cases of the multinomial model. Numerical results should permit to keep the efficiency of treatment with a lower total radiation dose then that given by the typical hit models, which allow to decrease side effects.

A novel immunoassay using recombinant allergens simplifies peanut allergy diagnosis.

BACKGROUND: Double-blind placebo-controlled food challenge (DBPCFC) is currently considered the gold standard for peanut allergy diagnosis. However, this procedure that requires the hospitalization of patients, mostly children, in specialized centers for oral exposure to allergens may cause severe reactions requiring emergency measures. Thus, a simpler and safer diagnosis procedure is needed. The aim of this study was to evaluate the diagnostic performance of a new set of in vitro blood tests for peanut allergy. METHODS: The levels of IgE directed towards peanut extract and recombinant peanut allergens Ara h 1, Ara h 2, Ara h 3, Ara h 6, Ara h 7, and Ara h 8 were measured in 3 groups of patients enrolled at 2 independent centers: patients with proven peanut allergy (n=166); pollen-sensitized subjects without peanut allergy (n=61), and control subjects without allergic disease (n=10). RESULTS: Seventy-nine percent of the pollen-sensitized patients showed IgE binding to peanut, despite their tolerance to peanut. In contrast, combining the results of specific IgE to peanut extract and to recombinant Ara h 2 and Ara h 6 yielded a peanut allergy diagnosis with a 98% sensitivity and an 85% specificity at a positivity threshold of 0.10 kU/l. Use of a threshold of 0.23 kU/l for recombinant Ara h 2 increased specificity (96%) at the cost of sensitivity (93%). CONCLUSION: A simple blood test can be used to diagnose peanut allergy with a high level of precision. However, DBPCFC will remain useful for the few cases where immunological and clinical observations yield conflicting results.

Phenomenological modeling of tumor diameter growth based on a mixed effects model.

Over the last few years, taking advantage of the linear kinetics of the tumor growth during the steady-state phase, tumor diameter-based rather than tumor volume-based models have been developed for the phenomenological modeling of tumor growth. In this study, we propose a new tumor diameter growth model characterizing early, late and steady-state treatment effects. Model parameters consist of growth rhythms, growth delays and time constants and are meaningful for biologists. Biological experiments provide in vivo longitudinal data. The latter are analyzed using a mixed effects model based on the new diameter growth function, to take into account inter-mouse variability and treatment factors. The relevance of the tumor growth mixed model is firstly assessed by analyzing the effects of three therapeutic strategies for cancer treatment (radiotherapy, concomitant radiochemotherapy and photodynamic therapy) administered on mice. Then, effects of the radiochemotherapy treatment duration are estimated within the mixed model. The results highlight the model suitability for analyzing therapeutic efficiency, comparing treatment responses and optimizing, when used in combination with optimal experiment design, anti-cancer treatment modalities.