Cyclic haemopoiesis at 7- or 8-day intervals

Space-velocity thermostatted kinetic theory model of tumor growth

The competition between cancer cells and immune system cells in inhomogeneous conditions is described at cell scale within the framework of the thermostatted kinetic theory. Cell learning is reproduced by increased cell activity during favorable interactions. The cell activity fluctuations are controlled by a thermostat. The direction of cell velocity is changed according to stochastic rules mimicking a dense fluid. We develop a kinetic Monte Carlo algorithm inspired from the direct simulation Monte Carlo (DSMC) method initially used for dilute gases. The simulations generate stochastic trajectories sampling the kinetic equations for the distributions of the different cell types. The evolution of an initially localized tumor is analyzed. Qualitatively different behaviors are observed as the field regulating activity fluctuations decreases. For high field values, i.e. efficient thermalization, cancer is controlled. For small field values, cancer rapidly and monotonously escapes from immunosurveillance. For the critical field value separating these two domains, the 3E's of immunotherapy are reproduced, with an apparent initial elimination of cancer, a long quasi-equilibrium period followed by large fluctuations, and the final escape of cancer, even for a favored production of immune system cells. For field values slightly smaller than the critical value, more regular oscillations of the number of immune system cells are spontaneously observed in agreement with clinical observations. The antagonistic effects that the stimulation of the immune system may have on oncogenesis are reproduced in the model by activity-weighted rate constants for the autocatalytic productions of immune system cells and cancer cells. Local favorable conditions for the launching of the oscillations are met in the fluctuating inhomogeneous system, able to generate a small cluster of immune system cells with larger activities than those of the surrounding cancer cells.

CRP identifies homeostatic immune oscillations in cancer patients: a potential treatment targeting tool?

The search for a suitable biomarker which indicates immune system responses in cancer patients has been long and arduous, but a widely known biomarker has emerged as a potential candidate for this purpose. C-Reactive Protein (CRP) is an acute-phase plasma protein that can be used as a marker for activation of the immune system. The short plasma half-life and relatively robust and reliable response to inflammation, make CRP an ideal candidate marker for inflammation. The high- sensitivity test for CRP, termed Low-Reactive Protein (LRP, L-CRP or hs-CRP), measures very low levels of CRP more accurately, and is even more reliable than standard CRP for this purpose. Usually, static sampling of CRP has been used for clinical studies and these can predict disease presence or recurrence, notably for a number of cancers. We have used frequent serial L-CRP measurements across three clinical laboratories in two countries and for different advanced cancers, and have demonstrated similar, repeatable observations of a cyclical variation in CRP levels in these patients. We hypothesise that these L-CRP oscillations are part of a homeostatic immune response to advanced malignancy and have some preliminary data linking the timing of therapy to treatment success. This article reviews CRP, shows some of our data and advances the reasoning for the hypothesis that explains the CRP cycles in terms of homeostatic immune regulatory cycles. This knowledge might also open the way for improved timing of treatment(s) for improved clinical efficacy.