Discovery of a glucocorticoid receptor (GR) activity signature correlates with immune cell infiltration in adrenocortical carcinoma

BACKGROUND: Adrenocortical carcinoma (ACC) is a rare and highly aggressive endocrine malignancy, of which >40% present with glucocorticoid excess. Glucocorticoids and glucocorticoid receptor (GR) signaling have long been thought to suppress immunity and promote tumor progression by acting on immune cells. Here, we provide new insights into the interaction between GR signaling activity and the immune signature of ACC as a potential explanation for immune escape and resistance to immunotherapy. METHODS: First, GR immunohistochemical staining and immunofluorescence analysis of tumor-infiltrating lymphocyte (CD4 T, CD8 T cells, natural killer (NK) cells, dendritic cells and macrophages) were performed in 78 primary ACC tissue specimens. Quantitative data of immune cell infiltration in ACC were correlated with clinical characteristics. Second, we discovered a GR activity signature (GRsig) using GR-targeted gene networks derived from global gene expression data of primary ACC. Finally, we identified two GRsig-related subtypes based on the GRsig and assessed the differences in immune characteristics and prognostic stratification between the two subtypes. RESULTS: GR was expressed in 90% of the ACC tumors, and CD8+ cytotoxic T lymphocytes were the most common infiltrating cell type in ACC specimens (88%, 8.6 cells/high power field). GR expression positively correlated with CD8+ T cell (Phi=0.342, p<0.001), CD4+ T cell (Phi=0.280, p<0.001), NK cell (Phi=0.280, p<0.001), macrophage (Phi=0.285, p<0.001), and dendritic cell (Phi=0.397, p<0.001) infiltration. Clustering heatmap analysis also displayed high immune cell infiltration in GR high-expressing tumors and low immune cell infiltration in GR-low tumors. High GR expression and high immune cell infiltration were significantly associated with better survival. Glucocorticoid excess is associated with low immune cell abundance and unfavorable prognosis. A GRsig comprizing n=34 GR-associated genes was derived from Gene Expression Omnibus/The Cancer Genome Atlas (TCGA) data sets and used to define two GRsig-related subtypes in the TCGA cohort. We demonstrated distinct differences in the immune landscape and clinical outcomes between the two subtypes. CONCLUSION: GR expression positively correlates with tumor-infiltrating immune cells in ACC. The GRsig could serve as a prognostic biomarker and may be helpful for prognosis prediction and response to immunotherapy. Consequently, targeting the GR signaling pathway might be pivotal and should be investigated in clinical studies.