RESUMEN
Prostate cancer (PCa) is threatening the health of millions of people, the pathological mechanism of prostate cancer has not been fully elaborated, and needs to be further explored. Here, we found that the expression of DUSP26 is dramatically suppressed, and a positive connection of its expression with PCa prognosis was also observed. In vitro, overexpression of DUSP26 significantly inhibited the proliferative, migrative, and invasive capacities of PC3 cells, DUSP26 silencing presented opposite results. Tumor formation experiments in subcutaneous nude mice demonstrated that DUSP26 overexpression could significantly suppress PC3 growth in vivo. Moreover, the mechanism of DUSP26 gene and PCa was discovered by RNA-Seq analysis. We found that DUSP26 significantly inhibited MAPK signaling pathway activation, and further experiments displayed that DUSP26 could impair TAK1, p38, and JNK phosphorylation. Interestingly, treatment with the TAK1 inhibitor (iTAK1) attenuated the effect of DUSP26 on PC3 cells. Together, these results suggested that DUSP26 may serve as a novel therapeutic target for PC3 cell type PCa, the underlying mechanism may be through TAK1-JNK/p38 signaling.
RESUMEN
BACKGROUND: Prostate cancer (PCa) is a malignant tumor of the male reproductive system, and its incidence has increased significantly in recent years. This study aimed to further identify candidate biomarkers with prognostic and diagnostic significance by integrating gene expression and DNA methylation data from PCa patients through association analysis. MATERIAL AND METHODS: To this end, this paper proposes a sparse partial least squares regression algorithm based on hypergraph regularization (HR-SPLS) by integrating and clustering two kinds of data. Next, module 2, with the most significant weight, was selected for further analysis according to the weight of each module related to DNA methylation and mRNAs. Based on the DNA methylation sites in module 2, this paper uses multiple machine learning methods to construct a PCa diagnosis-related model of 10-DNA methylation sites. RESULTS: The results of Receiver Operating Characteristic (ROC) analysis showed that the DNA methylation-related diagnostic model we constructed could diagnose PCa patients with high accuracy. Subsequently, based on the mRNAs in module 2, we constructed a prognostic model for 7-mRNAs (MYH11, ACTG2, DDR2, CDC42EP3, MARCKSL1, LMOD1, and MYLK) using multivariate Cox regression analysis. The prognostic model could predict the disease free survival of PCa patients with moderate to high accuracy (area under the curve (AUC) =0.761). In addition, Gene Set EnrichmentAnalysis (GSEA) and immune analysis indicated that the prognosis of patients in the risk group might be related to immune cell infiltration. CONCLUSIONS: Our findings may provide new methods and insights for identifying disease-related biomarkers by integrating DNA methylation and gene expression data.
Asunto(s)
Algoritmos , Biomarcadores de Tumor , Metilación de ADN , Neoplasias de la Próstata , Humanos , Masculino , Neoplasias de la Próstata/genética , Neoplasias de la Próstata/diagnóstico , Neoplasias de la Próstata/patología , Pronóstico , Biomarcadores de Tumor/genética , Análisis de los Mínimos Cuadrados , ARN Mensajero/metabolismo , ARN Mensajero/genética , Regulación Neoplásica de la Expresión Génica , Aprendizaje Automático , Curva ROCRESUMEN
Clear cell renal cell carcinoma (ccRCC) is the most aggressive and deadly cancer of the urinary system and is regulated by multiple signaling pathways. However, the specific molecular mechanisms underlying ccRCC have not been fully studied or demonstrated. This study aimed to elucidate the function of lysosomal-associated transmembrane protein 5 (LAPTM5) in ccRCC cell lines and animal models and determine the potential underlying mechanisms. Our results demonstrated that LAPTM5 expression in patients with ccRCC was significantly higher in the tumor group than that in the adjacent nontumor group. Moreover, LAPTM5 promoted proliferation, migration, and invasion of ccRCC cells through the gain and loss of the function of LAPTM5 in 786-0 and Caki-1 cell lines. Similar results regarding LAPTM5 overexpression were obtained in BALB/c nude mice. In addition, LAPTM5 activated the Jun N-terminal kinase (JNK)/p38 signaling cascade by interacting with Ras-related C3 botulinum toxin substrate 1 (RAC1). Treatment with an RAC1 inhibitor eliminated the effects of LAPTM5 in ccRCC. In conclusion, these results indicate that LAPTM5 may be a new therapeutic target for ccRCC via activation of the RAC1-JNK/p38 axis.