Identification of Androgen Receptor Metabolic Correlome Reveals the Repression of Ceramide Kinase by Androgens.
Prostate cancer (PCa) is one of the most prevalent cancers in men. Androgen receptor signaling plays a major role in this disease, and androgen deprivation therapy is a common therapeutic strategy in recurrent disease. Sphingolipid metabolism plays a central role in cell death, survival, and therapy resistance in cancer. Ceramide kinase (CERK) catalyzes the phosphorylation of ceramide to ceramide 1-phosphate, which regulates various cellular functions including cell growth and migration. Here we show that activated androgen receptor (AR) is a repressor of CERK expression. We undertook a bioinformatics strategy using PCa transcriptomics datasets to ascertain the metabolic alterations associated with AR activity. CERK was among the most prominent negatively correlated genes in our analysis. Interestingly, we demonstrated through various experimental approaches that activated AR reduces the mRNA expression of CERK: (i) expression of CERK is predominant in cell lines with low or negative AR activity; (ii) AR agonist and antagonist repress and induce CERK mRNA expression, respectively; (iii) orchiectomy in wildtype mice or mice with PCa (harboring prostate-specific Pten deletion) results in elevated Cerk mRNA levels in prostate tissue. Mechanistically, we found that AR represses CERK through interaction with its regulatory elements and that the transcriptional repressor EZH2 contributes to this process. In summary, we identify a repressive mode of AR that influences the expression of CERK in PCa.
['Camacho|Laura|L|', 'Zabala-Letona|Amaia|A|', 'Cortazar|Ana R|AR|', 'Astobiza|Ianire|I|', 'Dominguez-Herrera|Asier|A|', 'Ercilla|Amaia|A|0000-0001-8999-7131', 'Crespo|Jana|J|', 'Viera|Cristina|C|', 'Fernández-Ruiz|Sonia|S|', 'Martinez-Gonzalez|Ainara|A|', 'Torrano|Veronica|V|', 'Martín-Martín|Natalia|N|', 'Gomez-Muñoz|Antonio|A|', 'Carracedo|Arkaitz|A|0000-0001-5957-1260']
ceramide kinase prostate cancer sphingolipid metabolism bioinformatics mouse models