Regulation of gonadotropins by urocortin 2 in gonadotropic tumor LβT2 cells

CRH-R2 signalling modulates feeding and circadian gene expression in hypothalamic mHypoA-2/30 neurons

The hypothalamic type 2 corticotropin releasing hormone receptor (CRH-R2) plays critical roles in homeostatic regulation, particularly in fine tuning stress recovery. During acute stress, the CRH-R2 ligands CRH and urocortins promote adaptive responses and feeding inhibition. However, in rodent models of chronic stress, over-exposure of hypothalamic CRH-R2 to its cognate agonists is associated with urocortin 2 (Ucn2) resistance; attenuated cAMP-response element binding protein (CREB) phosphorylation and increased food intake. The molecular mechanisms involved in these altered CRH-R2 signalling responses are not well described. In the present study, we used the adult mouse hypothalamus-derived cell line mHypoA-2/30 to investigate CRH-R2 signalling characteristics focusing on gene expression of molecules involved in feeding and circadian regulation given the role of clock genes in metabolic control. We identified functional CRH-R2 receptors expressed in mHypoA-2/30 cells that differentially regulate CREB and AMP-activated protein kinase (AMPK) phosphorylation and downstream expression of the appetite-regulatory genes proopiomelanocortin (Pomc) and neuropeptide Y (Npy) in accordance with an anorexigenic effect. We studied for the first time the effects of Ucn2 on clock genes in native and in a circadian bioluminescence reporter expressing mHypoA-2/30 cells, detecting enhancing effects of Ucn2 on mRNA levels and rhythm amplitude of the circadian regulator Aryl hydrocarbon receptor nuclear translocator-like protein 1 (Bmal1), which could facilitate anorexic responses in the activity circadian phase. These data uncover novel aspects of CRH-R2 hypothalamic signalling that might be important in regulation of circadian feeding during stress responses.

Construction of an immune-related prognostic model by exploring the tumor microenvironment of clear cell renal cell carcinoma

OBJECTIVE

In this study, bioinformatics methods were performed to screen the candidate prognosis-related genes of clear cell renal cell carcinoma (ccRCC) by analyzing the tumor microenvironment (TME).

METHODS

Gene expression and clinical data of ccRCC patients were accessed from TCGA, and R package ESTIMATE was applied to calculate immune, stromal, and ESTIMATE scores of the patients. Survival analysis was conducted per median of these three scores. Based on the scoring results, differentially expressed genes (DEGs) were screened. Regression algorithms were utilized to screen prognostic genes and establish a risk model. Finally, pathway activity differences were analyzed through GSEA.

RESULTS

Patients with the unfavorable prognosis had high immune scores. 619 DEGs (499 up-regulated and 120 down-regulated) were screened based on the differences in gene expression of the patients with high and low immune scores. These genes mainly participated in immune-related signaling pathways. A prognostic risk model for ccRCC patients was constructed and 7 immune-related signature genes (RORB, TNFSF14, UCN2, USP2, TOX3, KLRC2, SLAMF9) were obtained through regression analysis. The constructed prognostic risk model could be used for determining prognoses of patients with ccRCC.

CONCLUSION

We unraveled the association between TME and prognosis of ccRCC patients and established a prognostic risk model based on the differentially expressed genes. These results contributed to understanding of TME that affected patients' prognosis and progression of ccRCC and conduced to finding potential biomarkers of ccRCC.