Lymphocyte migration and retention properties affected by ibrutinib in chronic lymphocytic leukemia.

The Bruton tyrosine kinase (BTK) inhibitor ibrutinib is widely used for treatment of patients with relapsed/refractory or treatment-naïve chronic lymphocytic leukemia (CLL). A prominent effect of ibrutinib is to disrupt the retention of CLL cells from supportive lymphoid tissues, by altering BTK-dependent adhesion and migration. To further explore the mechanism of action of ibrutinib and its potential impact on non-leukemic cells, we quantified multiple motility and adhesion parameters of human primary CLL cells and non-leukemic lymphoid cells. In vitro, ibrutinib affected CCL19-, CXCL12- and CXCL13-evoked migration behavior of CLL cells and non-neoplastic lymphocytes, by reducing both motility speed and directionality. De-phosphorylation of BTK induced by ibrutinib in CLL cells was associated with defective polarization over fibronectin and inability to assemble the immunological synapse upon B-cell receptor engagement. In patients' samples collected during a 6-month monitoring of therapy, chemokine-evoked migration was repressed in CLL cells and marginally reduced in T cells. This was accompanied by profound modulation of the expression of chemokine receptors and adhesion molecules. Remarkably, the relative expression of the receptors governing lymph node entry (CCR7) versus exit (S1PR1) stood out as a reliable predictive marker of the clinically relevant treatment-induced lymphocytosis. Together, our data reveal a multifaceted modulation of motility and adhesive properties of ibrutinib on both CLL leukemic cell and T-cell populations and point to intrinsic differences in CLL recirculation properties as an underlying cause for variability in treatment response.

Stochastic asymmetric repartition of lytic machinery in dividing CD8+ T cells generates heterogeneous killing behavior.

Cytotoxic immune cells are endowed with a high degree of heterogeneity in their lytic function, but how this heterogeneity is generated is still an open question. We therefore investigated if human CD8+ T cells could segregate their lytic components during telophase, using imaging flow cytometry, confocal microscopy, and live-cell imaging. We show that CD107a+-intracellular vesicles, perforin, and granzyme B unevenly segregate in a constant fraction of telophasic cells during each division round. Mathematical modeling posits that unequal lytic molecule inheritance by daughter cells results from the random distribution of lytic granules on the two sides of the cleavage furrow. Finally, we establish that the level of lytic compartment in individual cytotoxic T lymphocyte (CTL) dictates CTL killing capacity.

Multiparametric analysis of CD8+ T cell compartment phenotype in chronic lymphocytic leukemia reveals a signature associated with progression toward therapy.

CD8+ T cells are frontline defenders against cancer and primary targets of current immunotherapies. In CLL, specific functional alterations have been described in circulating CD8+ T cells, yet a global view of the CD8+ T cell compartment phenotype and of its real impact on disease progression is presently elusive. We developed a multidimensional statistical analysis of CD8+ T cell phenotypic marker expression based on whole blood multi-color flow-cytometry. The analysis comprises both unsupervised statistics (hClust and PCA) and supervised classification methods (Random forest, Adaboost algorithm, Decision tree learning and logistic regression) and allows to cluster patients by comparing multiple phenotypic markers expressed by CD8+ T cells. Our results reveal a global CD8+ T cell phenotypic signature in CLL patients that is significantly modified when compared to healthy donors. We also uncover a CD8+ T cell signature characteristic of patients evolving toward therapy within 6 months after phenotyping. The unbiased, not predetermined and multimodal approach highlights a prominent role of the memory compartment in the prognostic signature. The analysis also reveals that imbalance of the central/effector memory compartment in CD8+ T cells can occur irrespectively of the elapsed time after diagnosis. Taken together our results indicate that, in CLL patients, CD8+ T cell phenotype is imprinted by disease clinical progression and reveal that CD8+ T cell memory compartment alteration is not only a hallmark of CLL disease but also a signature of disease evolution toward the need for therapy.

Individual Human Cytotoxic T Lymphocytes Exhibit Intraclonal Heterogeneity during Sustained Killing.

The killing of antigen-bearing cells by clonal populations of cytotoxic T lymphocytes (CTLs) is thought to be a rapid phenomenon executed uniformly by individual CTLs. We combined bulk and single-CTL killing assays over a prolonged time period to provide the killing statistics of clonal human CTLs against an excess of target cells. Our data reveal efficiency in sustained killing at the population level, which relied on a highly heterogeneous multiple killing performance at the individual level. Although intraclonal functional heterogeneity was a stable trait in clonal populations, it was reset in the progeny of individual CTLs. In-depth mathematical analysis of individual CTL killing data revealed a substantial proportion of high-rate killer CTLs with burst killing activity. Importantly, such activity was delayed and required activation with strong antigenic stimulation. Our study implies that functional heterogeneity allows CTL populations to calibrate prolonged cytotoxic activity to the size of target cell populations.

A biased competition theory of cytotoxic T lymphocyte interaction with tumor nodules.

The dynamics of the interaction between Cytotoxic T Lymphocytes (CTL) and tumor cells has been addressed in depth, in particular using numerical simulations. However, stochastic mathematical models that take into account the competitive interaction between CTL and tumors undergoing immunoediting, a process of tumor cell escape from immunesurveillance, are presently missing. Here, we introduce a stochastic dynamical particle interaction model based on experimentally measured parameters that allows to describe CTL function during immunoediting. The model describes the competitive interaction between CTL and melanoma cell nodules and allows temporal and two-dimensional spatial progression. The model is designed to provide probabilistic estimates of tumor eradication through numerical simulations in which tunable parameters influencing CTL efficacy against a tumor nodule undergoing immunoediting are tested. Our model shows that the rate of CTL/tumor nodule productive collisions during the initial time of interaction determines the success of CTL in tumor eradication. It allows efficient cytotoxic function before the tumor cells acquire a substantial resistance to CTL attack, due to mutations stochastically occurring during cell division. Interestingly, a bias in CTL motility inducing a progressive attraction towards a few scout CTL, which have detected the nodule enhances early productive collisions and tumor eradication. Taken together, our results are compatible with a biased competition theory of CTL function in which CTL efficacy against a tumor nodule undergoing immunoediting is strongly dependent on guidance of CTL trajectories by scout siblings. They highlight unprecedented aspects of immune cell behavior that might inspire new CTL-based therapeutic strategies against tumors.

Selection of biologically relevant genes with a wrapper stochastic algorithm.

We investigate an important issue of a meta-algorithm for selecting variables in the framework of microarray data. This wrapper method starts from any classification algorithm and weights each variable (i.e. gene) relative to its efficiency for classification. An optimization procedure is then inferred which exhibits important genes for the studied biological process. Theory and application with the SVM classifier were presented in Gadat and Younes, 2007 and we extend this method with CART. The classification error rates are computed on three famous public databases (Leukemia, Colon and Prostate) and compared with those from other wrapper methods (RFE, lo norm SVM, Random Forests). This allows the assessment of the statistical relevance of the proposed algorithm. Furthermore, a biological interpretation with the Ingenuity Pathway Analysis software outputs clearly shows that the gene selections from the different wrapper methods raise very relevant biological information, compared to a classical filter gene selection with T-test.