RESUMEN
Breast cancer patients often have a poor prognosis largely due to lack of effective targeted therapy. It is now well established that monosaccharide enhances growth retardation and chemotherapy sensitivity in tumor cells. We investigated whether D-arabinose has capability to restrict the proliferation of tumor cells and its mechanism. Here, we report that D-arabinose induced cytotoxicity is modulated by autophagy and p38 MAPK signaling pathway in breast cancer cell lines. The proliferation of cells was evaluated by CCK-8 and Colony formation assay. The distribution of cells in cell cycle phases was analyzed by flow cytometry. Cell cycle, autophagy and MAPK signaling related proteins were detected by western blotting. Mouse xenograft model was used to evaluate the efficacy of D-arabinose in vivo. The proliferation of cells was dramatically inhibited by D-arabinose exposure in a dose-dependent manner, which was relevant to cell cycle arrest, as demonstrated by G2/M cell cycle restriction and ectopic expression of cell cycle related proteins. Mechanistically, we further identified that D-arabinose is positively associated with autophagy and the activation of the p38 MAPK signaling in breast cancer. In contrast, 3-Ma or SB203580, the inhibitor of autophagy or p38 MAPK, reversed the efficacy of D-arabinose. Additionally, D-arabinose in vivo treatment could significantly inhibit xenograft growth of breast cancer cells. Our findings were the first to reveal that D-arabinose triggered cell cycle arrest by inducing autophagy through the activation of p38 MAPK signaling pathway in breast cancer cells.
Asunto(s)
Arabinosa , Autofagia , Neoplasias de la Mama , Puntos de Control del Ciclo Celular , Proliferación Celular , Sistema de Señalización de MAP Quinasas , Proteínas Quinasas p38 Activadas por Mitógenos , Autofagia/efectos de los fármacos , Humanos , Neoplasias de la Mama/metabolismo , Neoplasias de la Mama/tratamiento farmacológico , Neoplasias de la Mama/patología , Animales , Femenino , Proteínas Quinasas p38 Activadas por Mitógenos/metabolismo , Ratones , Arabinosa/farmacología , Puntos de Control del Ciclo Celular/efectos de los fármacos , Línea Celular Tumoral , Proliferación Celular/efectos de los fármacos , Sistema de Señalización de MAP Quinasas/efectos de los fármacos , Ensayos Antitumor por Modelo de Xenoinjerto , Ratones Desnudos , Ratones Endogámicos BALB CRESUMEN
Objective: Using bioinformatics machine learning methods, our research aims to identify the potential key genes associated with Lung adenocarcinoma (LUAD). Methods: We obtained two gene expression profiling microarrays (GSE68571 and GSE74706) from the public Gene Expression Omnibus (GEO) database at the National Centre for Biotechnology Information (NCBI). The purpose was to identify Differentially Expressed Genes (DEGs) between the lung adenocarcinoma group and the healthy control group. The limma R package in R was utilized for this analysis. For the differential gene diagnosis of lung adenocarcinoma, we employed the least absolute shrinkage and selection operator (LASSO) regression and SVM-RFE screening crossover. To evaluate the performance, ROC curves were plotted. We performed immuno-infiltration analysis using CIBERSORT. Finally, we validated the key genes through qRT-PCR and Western-blot verification, then downregulated MMP17 gene expression, upregulated SH3GL2 gene expression, and performed CCK8 experiments. Results: A total of 32 Differentially Expressed Genes (DEGs) were identified. Two diagnostic marker genes, SH3GL2 and MMP17, were selected by employing LASSO and SVM-RFE machine learning methods. In Lung adenocarcinoma cells, the expression of MMP17 was observed to be elevated compared to normal lung epithelial cells in the control group (P < 0.05). In contrast, a down-regulation of SH3GL2 was found in Lung adenocarcinoma cells (P < 0.05). Finally, we downregulated MMP17 and upregulated SH3GL2 gene expression, then the CCK8 showed that the proliferation of both lung cancer cells was inhibited. Conclusion: SH3GL2 and MMP17 are expected to be potential biomarkers for Lung adenocarcinoma.