Search

• FOXP3 controls Treg differentiation and activity. • FOXP3 induces metabolic versatility in intra-tumoral Tregs. • Treg subsets show different reliance on FOXP3. Dysregulation of regulatory T cells (Tregs) is described in the context of inflammatory and autoimmune diseases, and cancer. Forkhead box P3 (FOXP3) is a transcription factor that its activity is an indicator of Treg identity. FOXP3 induces metabolic versatility in intra-tumoral Tregs, so that its deficiency mediates Treg instability or even gives rise to the acquisition of effector T cell phenotype. FOXP3 dysregulation and defectiveness occurs upon ubiquitination, methylation and presumably acetylation. Stimulators of PTEN, mammalian target of rapamycin complex 2 (mTORC2), and nucleus accumbens–associated protein-1 (NAC1), and inhibitors of B lymphocyte-induced maturation protein-1 (Blimp-1), Deltex1 (DTX1) and ubiquitin-specific peptidase 22 (USP22) are suggested to hamper FOXP3 stability, and to promote its downregulation and further Treg depletion. A point is that Treg subsets reveal different reliance on FOXP3, which indicates that not all Tregs are strictly dependent on FOXP3, and presumably Tregs with different origin rely on diverse regulators of FOXP3 stability. The focus of this review is over the current understanding toward FOXP3, its activity in Tregs and influence from different regulators within tumor microenvironment (TME). Implication of FOXP3 targeting in cancer immunotherapy is another focus of this paper. [ABSTRACT FROM AUTHOR]

In this paper, we propose and analyse a mathematical model for chronic myelogenous leukemia (CML), a cancer of the blood. We model the interaction between naive T cells, effector T cells, and CML cancer cells in the body, using a system of ordinary differential equations which gives rates of change of the three cell populations. One of the difficulties in modeling CML is the scarcity of experimental data which can be used to estimate parameters values. To compensate for the resulting uncertainties, we use Latin hypercube sampling (LHS) on large ranges of possible parameter values in our analysis. A major goal of this work is the determination of parameters which play a critical role in remission or clearance of the cancer in the model. Our analysis examines 12 parameters, and identifies two of these, the growth and death rates of CML, as critical to the outcome of the system. Our results indicate that the most promising research avenues for treatments of CML should be those that affect these two significant parameters (CML growth and death rates), while altering the other parameters should have little effect on the outcome. [Copyright &y& Elsevier]