Steroids hormones possess two distinct actions, a delayed genomic effect and a rapid non-genomic effect. Rapid steroid-triggered signaling is mediated by specific receptors localized most often to the plasma membrane. The nature of these receptors is of great interest and accumulated data suggest that G protein-coupled receptors (GPCRs) are appealing candidates. Increasing evidence regarding the interaction between steroids and specific membrane proteins, as well as the involvement of G protein and corresponding downstream signaling, have led to identification of physiologically relevant GPCRs as steroid extranuclear receptors. Examples include G protein-coupled receptor 30 (GPR30) for estrogen, membrane progestin receptor for progesterone, G protein-coupled receptor family C group 6 member A (GPRC6A) and zinc transporter member 9 (ZIP9) for androgen, and trace amine associated receptor 1 (TAAR1) for thyroid hormone. These receptor-mediated biological effects have been extended to reproductive development, cardiovascular function, neuroendocrinology and cancer pathophysiology. However, although great progress have been achieved, there are still important questions that need to be answered, including the identities of GPCRs responsible for the remaining steroids (e.g., glucocorticoid), the structural basis of steroids and GPCRs’ interaction and the integration of extranuclear and nuclear signaling to the final physiological function. Here, we reviewed the several significant developments in this field and highlighted a hypothesis that attempts to explain the general interaction between steroids and GPCRs.

Background: Good syndrome is a rare adult-onset immunodeficiency characterized by thymoma and hypogammaglobulinemia. Its clinical manifestations are highly heterogeneous, ranging from various infections to autoimmunity.Objective: This study was to summarize patient characteristics, identify prognostic factors and define clinical subgroups of Good syndrome.Methods: A systematic literature review was conducted to include patients with Good syndrome identified in PubMed, Embase and Cochrane databases between January 2010 and November 2020. Logistic and Cox regressions were used to identify prognostic factors impacting outcomes. Clinical subgroups were defined by multiple correspondence analysis and unsupervised hierarchical clustering. A decision tree was constructed to characterize the subgroup placement of cases.Results: Of 162 patients included in the current study, the median age at diagnosis was 58 years and 51% were male. Type AB was the most common histological subtype of thymoma, and infections as well as concurrent autoimmune disorders were identified in 92.6% and 51.2% patients, respectively. Laboratory workup showed typical findings of combined immunodeficiency. Thymoma status (odds ratio [OR] 4.157, confidence interval [CI] 1.219-14.177, p = 0.023), infections related to cellular immunity defects (OR 3.324, 95% CI 1.100-10.046, p = 0.033), infections of sinopulmonary tract (OR 14.351, 95% CI 2.525-81.576, p = 0.003), central nerve system (OR 6.403, 95% CI 1.205-34.027, p = 0.029) as well as bloodstream (OR 6.917, 95% CI 1.519-31.505, p = 0.012) were independent prognostic factors. The 10-year overall survival was 53.7%. Cluster analysis revealed three clinical subgroups with distinct characteristics and prognosis (cluster 1, infections related to cellular immunity defects; cluster 2, infections related to other immunity defects; cluster 3, infections related to humoral and phagocytic immunity defects). A decision tree using infection types (related to humoral and cellular immunity defects) could place patients into corresponding clusters with an overall correct prediction of 72.2%.Conclusions: Infection type and site were the main prognostic factors impacting survival of patients with Good syndrome. We identified three subgroups within Good syndrome associated with distinct clinical features, which may facilitate the study of underlying pathogenesis as well as development of targeted therapy.