Glucocorticoids (GCs) are widely used to treat several diseases because of their powerful anti-inflammatory and immunomodulatory effects on immune cells and non-lymphoid tissues. The effects of GCs on T cells are the most relevant in this regard. In this review, we analyze how GCs modulate the survival, maturation, and differentiation of regulatory T (Treg) cell subsets into both murine models and humans. In this way, GCs change the Treg cell number with an impact on the mid-term and long-term efficacy of GC treatment. In vitro studies suggest that the GC-dependent expansion of Treg cells is relevant when they are activated. In agreement with this observation, the GC treatment of patients with established autoimmune, allergic, or (auto)inflammatory diseases causes an expansion of Treg cells. An exception to this appears to be the local GC treatment of psoriatic lesions. Moreover, the effects on Treg number in patients with multiple sclerosis are uncertain. The effects of GCs on Treg cell number in healthy/diseased subjects treated with or exposed to allergens/antigens appear to be context-dependent. Considering the relevance of this effect in the maturation of the immune system (tolerogenic response to antigens), the success of vaccination (including desensitization), and the tolerance to xenografts, the findings must be considered when planning GC treatment.

T cell gene signatures are used to evaluate T cell infiltration of non-lymphoid tissues and cancers in both experimental and clinical settings. However, some genes included in the available T cell signatures are not T cell-restricted. Herein, we propose a new human T cell signature that has been developed via a six-step procedure and comprises 15 T cell restricted genes. We demonstrate the new T cell signature, named signature-H, that differs from other gene signatures since it shows higher sensitivity and better predictivity in the evaluation of T cell infiltration in healthy tissues as well as 32 cancers. Further, results from signature-H are highly concordant with the immunohistochemistry methods currently used for assessing the prognosis of neuroblastoma, as demonstrated by the Kaplan–Meier curves of patients ranked by tumor T cell infiltration. Moreover, T cell infiltration levels calculated using signature-H correlate with the risk groups determined by the staging of the neuroblastoma. Finally, multiparametric analysis of tumor-infiltrating T cells based on signature-H let us favorably predict the response of melanoma to the anti-PD-1 antibody nivolumab. These findings suggest that signature-H evaluates T cell infiltration levels of tissues and may be used as a prognostic tool in the precision medicine perspective after appropriate clinical validation.