Dataset Information

Silybin Prevents Prostate Cancer by Inhibited the ALDH1A1 Expression in the Retinol Metabolism Pathway.

ABSTRACT: Background:Silybin was known to exert inhibition in prostate cancer, but the underlying mechanism remained largely unknown. This study was designed to find out the potential target of Silybin on prostate cancer and explore the relative mechanisms. Methods:Firstly, we screened the possible targets of Silybin through the PubChem database and Subpathway - GM. Then DU145 cells were transferred to investigate the correction about related targets, magnetic bead sorting and flow cytometry were used to sort and identify the cells. Proliferation, migration and invasion ability of DU145 cells were detected by MTT assay, Transwell assay, plate clonality and sphere formation assay. BALB/c nude mice were constructed models with implanted sarcoma and measured the tumor volume every 5 days as wells tumor weight. The levels of proteins were detected by Western blot and immunocytochemistry. RT-PCR was selected to test the expression of protein's mRNA. Results:It was screened out the ALDH1A1 was highly correlated with subpathways of the Silybin risk metabolic pathway. And ALDH1A1 expression was positively correlated RAR? with Ets1 by interfering with the ALDH1A1 gene. Importantly, ALDH1A1(+) cells showed proliferation, migration and invasion ability. In addition, it showed that Silybin exerted the inhibition on prostate cells by suppressed the proliferation, migration and invasion ability of cells in vitro experiment. Silybin also reduced the tumor volume and weight. And Silybin displayed obviously reduced the proteins and mRNA of ALDH1A1, RAR?, Ets1 and MMP9 expressions. Conclusion:Our results indicated that Silybin showed inhibition of prostate cancer and the mechanism was involving with downregulating ALDH1A1 expression, thereby inhibiting the activation of RAR? and preventing the activation of Ets1 to inhibit the growth and invasion of prostate cancer.

SUBMITTER: Jiang Y

PROVIDER: S-EPMC7487981 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Silybin Prevents Prostate Cancer by Inhibited the ALDH1A1 Expression in the Retinol Metabolism Pathway.

Jiang Ying Y Song Hanbing H Jiang Ling L Qiao Yu Y Yang Dan D Wang Donghua D Li Ji J

Frontiers in cell and developmental biology 20200831

<h4>Background</h4>Silybin was known to exert inhibition in prostate cancer, but the underlying mechanism remained largely unknown. This study was designed to find out the potential target of Silybin on prostate cancer and explore the relative mechanisms.<h4>Methods</h4>Firstly, we screened the possible targets of Silybin through the PubChem database and Subpathway - GM. Then DU145 cells were transferred to investigate the correction about related targets, magnetic bead sorting and flow cytometr ...[more]

PMID: 32984354

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Project description:Background Tyrosine metabolism pathway-related genes were related to prostate cancer progression, which may be used as potential prognostic markers. Aims To dissect the dysregulation of tyrosine metabolism in prostate cancer and build a prognostic signature based on tyrosine metabolism-related genes for prostate cancer. Materials and Method. Cross-platform gene expression data of prostate cancer cohorts were collected from both The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Based on the expression of tyrosine metabolism-related enzymes (TMREs), an unsupervised consensus clustering method was used to classify prostate cancer patients into different molecular subtypes. We employed the least absolute shrinkage and selection operator (LASSO) Cox regression analysis to evaluate prognostic characteristics based on TMREs to obtain a prognostic effect. The nomogram model was established and used to synthesize molecular subtypes, prognostic characteristics, and clinicopathological features. Kaplan–Meier plots and logrank analysis were used to clarify survival differences between subtypes. Results Based on the hierarchical clustering method and the expression profiles of TMREs, prostate cancer samples were assigned into two subgroups (S1, subgroup 1; S2, subgroup 2), and the Kaplan–Meier plot and logrank analysis showed distinct survival outcomes between S1 and S2 subgroups. We further established a four-gene-based prognostic signature, and both in-group testing dataset and out-group testing dataset indicated the robustness of this model. By combining the four gene-based signatures and clinicopathological features, the nomogram model achieved better survival outcomes than any single classifier. Interestingly, we found that immune-related pathways were significantly concentrated on S1-upregulated genes, and the abundance of memory B cells, CD4+ resting memory T cells, M0 macrophages, resting dendritic cells, and resting mast cells were significantly different between S1 and S2 subgroups. Conclusions Our results indicate the prognostic value of genes related to tyrosine metabolism in prostate cancer and provide inspiration for treatment and prevention strategies.

Dataset Information

Silybin Prevents Prostate Cancer by Inhibited the ALDH1A1 Expression in the Retinol Metabolism Pathway.

Publications

Silybin Prevents Prostate Cancer by Inhibited the ALDH1A1 Expression in the Retinol Metabolism Pathway.

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