RESUMO
Autophagy plays an important role in prostate cancer development. It promotes tumor cell survival and was found to be associated with androgen pathway. In the present study, we found that GABA(A) receptor-associated protein like 1 (Gabarapl1), a ubiquitin-like modifier, participates in the regulation of autophagy. Gabarapl1 is transcriptionally regulated by androgen receptor (AR) and has a repressive role in autophagy. Androgen deprivation downregulates Gabarapl1 in an AR dependent manner, resulting in the increase of autophagy flux. Elevated Gabarapl1 also represses the proliferation of prostate cancer cells. In summary, our study provides evidence to show that Gabarapl1 is a mediator involved in androgen-regulated autophagy process.
Assuntos
Proteínas Adaptadoras de Transdução de Sinal/biossíntese , Androgênios/metabolismo , Proteínas Associadas aos Microtúbulos/biossíntese , Neoplasias da Próstata/genética , Receptores Androgênicos/biossíntese , Proteínas Adaptadoras de Transdução de Sinal/genética , Androgênios/genética , Autofagia/genética , Linhagem Celular Tumoral , Proliferação de Células , Regulação Neoplásica da Expressão Gênica , Humanos , Masculino , Proteínas Associadas aos Microtúbulos/genética , Neoplasias da Próstata/patologia , Receptores Androgênicos/genéticaRESUMO
BACKGROUND/PURPOSE: Nasopharyngeal carcinoma (NPC) is a malignant neoplasm of the head and neck. This study aims to use integrated bioinformatics technologies to develop a predictive miRNA-signature correlated with the prognosis of NPC. MATERIALS AND METHODS: Initially, the differentially expressed miRNAs (DEMs) in NPC were identified, and then DEMs related to the prognosis of NPC were further screened. Subsequently, the relatively important DEMs identified by random forest algorithm were used to construct a predictive signature by multivariate COX regression analysis. Moreover, PCA, Kaplan-Meier analysis, time-dependent ROC analysis, and univariate and multivariate COX regression analysis were performed to evaluate the ability of the signature in risk identification and prognosis prediction in NPC. RESULTS: Hsa-miR-29c, hsa-miR-30e and hsa-miR-93 were selected from DEMs to construct a signature, and their abnormal expression was significantly associated with poor prognosis of NPC. The average AUC values of 1- to 5-year OS, DFS and DMFS predicted by the signature were all above 0.7, and showed better clinical independence than other indexes. In addition, 295 differentially expressed mRNAs could be used as potential target genes of the 3 DEMs. Among them, 56 differentially expressed mRNAs were related to PFS. GO and KEGG enrichment analysis indicated that the poor prognosis of NPC was related to the abnormality of chromosomes, cytokines, and chemokines. CONCLUSION: We constructed a three-miRNA signature with good independent performance in predicting the prognosis for NPC. This study may lay the foundation for exploring new therapeutic targets and improving survival outcomes in NPC patients.