Study of the physical meaning of the binding parameters involved in effector-target conjugation using monoclonal antibodies against adhesion molecules and cholera toxin

Nurse-like cells promote CLL survival through LFA-3/CD2 interactions

In the tumoral micro-environment (TME) of chronic lymphocytic leukemia (CLL), nurse-like cells (NLC) are tumor-associated macrophages which play a critical role in the survival and chemoresistance of tumoral cells. This pro-survival activity is known to involve soluble factors, but few data are available on the relative role of cells cross-talk. Here, we used a transcriptome-based approach to systematically investigate the expression of various receptor/ligand pairs at the surface of NLC/CLL cells. Their relative contribution to CLL survival was assessed both by fluorescent microscopy to identify cellular interactions and by the use of functional tests to measure the impact of uncoupling these pairs with blocking monoclonal antibodies. We found for the first time that lymphocyte function-associated antigen 3 (LFA-3), expressed in CLL at significantly higher levels than in healthy donor B-cells, and CD2 expressed on NLC, were both key for the specific pro-survival signals delivered by NLC. Moreover, we found that NLC/CLL interactions induced the shedding of soluble LFA-3. Importantly, in an exploratory cohort of 60 CLL patients receiving frontline immunochemotherapy, increased levels of soluble LFA-3 were found to correlate with shorter overall survival. Altogether, these data suggest that LFA-3/CD2 interactions promote the survival of CLL cells in the tumor microenvironment.

NF-κ B-dependent upregulation of ICAM-1 by HPV16-E6/E7 facilitates NK cell/target cell interaction

NK cell recognition of tumor cells is mediated by a delicate balance of signals received by MHC class I-binding inhibitory NK cell receptors and activating NK cell receptors, which mainly bind to virus-, stress- or tumor-induced ligands. In addition, adhesion molecules such as the intercellular adhesion molecule-1 (ICAM-1) and its receptors, the lymphocyte function-associated antigen-1 (LFA-1) and Mac-1, are crucial for immune synapse formation and NK cell-mediated killing. In this study, we show that expression of the adhesion molecule ICAM-1 was rapidly induced by E6 and -E7 oncoproteins of HPV16, -18, -5 and -8, but not of HPV38 and -6 in primary human keratinocytes after retroviral transduction. ICAM-1 was upregulated in E6E7-expressing keratinocytes both at mRNA and protein levels. The observed ICAM-1 upregulation in HPV16-E6E7-expressing keratinocytes was partially dependent on activation of the NF-κB pathway. Importantly, the upregulated ICAM-1 expression in HPV16-E6E7-expressing keratinocytes led to enhanced conjugate formation with NK cells. We previously showed that HPV16-positive cervical carcinomas frequently express low levels of inhibitory NK cell ligands and high levels of activating NK cell ligands. Moreover, levels of the adhesion molecule ICAM-1 are enhanced by HPV16-E6/E7. Therefore, strategies that aim at harnessing NK cells might be beneficial for the treatment of cervical carcinoma.

Chemotherapy for tumors: an analysis of the dynamics and a study of quadratic and linear optimal controls

We investigate a mathematical model of tumor-immune interactions with chemotherapy, and strategies for optimally administering treatment. In this paper we analyze the dynamics of this model, characterize the optimal controls related to drug therapy, and discuss numerical results of the optimal strategies. The form of the model allows us to test and compare various optimal control strategies, including a quadratic control, a linear control, and a state-constraint. We establish the existence of the optimal control, and solve for the control in both the quadratic and linear case. In the linear control case, we show that we cannot rule out the possibility of a singular control. An interesting aspect of this paper is that we provide a graphical representation of regions on which the singular control is optimal.

Mixed immunotherapy and chemotherapy of tumors: modeling, applications and biological interpretations

We develop and analyze a mathematical model, in the form of a system of ordinary differential equations (ODEs), governing cancer growth on a cell population level with combination immune, vaccine and chemotherapy treatments. We characterize the ODE system dynamics by locating equilibrium points, determining stability properties, performing a bifurcation analysis, and identifying basins of attraction. These system characteristics are useful not only to gain a broad understanding of the specific system dynamics, but also to help guide the development of combination therapies. Numerical simulations of mixed chemo-immuno and vaccine therapy using both mouse and human parameters are presented. We illustrate situations for which neither chemotherapy nor immunotherapy alone are sufficient to control tumor growth, but in combination the therapies are able to eliminate the entire tumor.