Treatment of metastatic hormone-sensitive prostate cancer: from doublet therapy to triplet therapy.

For metastatic prostate cancer, androgen deprivation therapy (ADT) is the key strategy to control the disease. However, after 18-24 months of treatment, most patients will progress from metastatic hormone-sensitive prostate cancer (mHSPC) to metastatic castration-resistant prostate cancer (mCRPC) even with ADT. Once patients enter into mCRPC, they face with significant declines in quality of life and a dramatically reduced survival period. Thus, doublet therapy, which combines ADT with new hormone therapy (NHT) or ADT with docetaxel chemotherapy, substitutes ADT alone and has become the "gold standard" for the treatment of mHSPC. In recent years, triplet therapy, which combines ADT with NHT and docetaxel chemotherapy, has also achieved impressive effects in mHSPC. This article provides a comprehensive review of the recent applications of the triplet therapy in the field of mHSPC.

In vitro anti-hepatocellular carcinogenesis of 1,2,3,4,6-Penta-O-galloyl-ß-D-glucose.

Background: 1,2,3,4,6-Penta-O-galloyl-ß-D-glucose (ß-PGG) is a polyphenol ellagic compound with a variety of pharmacological effects and has an inhibitory effect on lots of cancers. Objective: To explore the antitumor effects and mechanism of 1,2,3,4,6-Penta-O-galloyl-ß-D-glucose on human hepatocellular carcinoma HepG2 cells. Design: A network pharmacology method was first used to predict the possible inhibition of hepatocellular carcinoma growth by 1,2,3,4,6-Penta-O-galloyl-ß-D-glucose (ß-PGG) through the p53 signaling pathway. Next, the Cell Counting Kit (CCK-8) assay was performed to evaluate changes in the survival rate of human hepatocellular carcinoma HepG2 cells treated with different concentrations of the drug; flow cytometry was used to detect changes in cell cycle, apoptosis, mitochondrial membrane potential (MMP) and intracellular Ca2+ concentration; real-time fluorescence quantification and immunoblotting showed that the expression of P53 genes and proteins associated with the p53 signaling pathway was significantly increased by ß-PGG treatment. Reasult: It was found that ß-PGG significantly inhibited survival of HepG2 cells, promoted apoptosis, decreased MMP and intracellular Ca2+ concentration, upregulated P53 gene and protein expression, increased CASP3 expression, and induced apoptosis in HepG2 cells. Conclusion: This study has shown that network pharmacology can accurately predict the target of ß-PGG's anti-hepatocellular carcinoma action. Moreover, it was evident that ß-PGG can induce apoptosis in HepG2 cells by activating the p53 signaling pathway to achieve its anti-hepatocellular carcinoma effect in vitro.

Investigation of the inhibition effect of 1,2,3,4,6-pentagalloyl-ß-D-glucose on gastric cancer cells based on a network pharmacology approach and experimental validation.

Background: Gastric cancer (GC) is ranked as the third leading cause of cancer-related mortality worldwide. 1,2,3,4,6-Pentagalloyl-ß-D-glucose (ß-PGG) has various pharmacological activities and has been shown to suppress cancer development. However, the mechanism by which ß-PGG inhibits gastric cancer has not been elucidated. Objective: This study explored the potential targets and mechanism of ß-PGG in GC using the network pharmacology approach combined with in-vitro experiments. Methods: The PharmMapper software was used to predict the potential targets of ß-PGG, and GC-related genes were identified on the GeneCards database. PPI analysis of common genes was performed using the STRING database. The potential regulatory mechanism of ß-PGG in GC was explored through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The binding ability of key genes and target proteins was verified by molecular docking. The effects of ß-PGG on genes and proteins were evaluated using the CCK-8 assay, cell cycle analysis, apoptosis assay, real-time fluorescence quantification polymerase chain reaction (qRT-PCR), and Western blotting. Results: Eight hub genes involved in cell cycle progression and apoptosis were identified. Cancer-related signaling pathways were identified using the Cytoscape tool. Some of those genes were significantly enriched in the p53 signaling pathway. The CCK-8 assay showed that ß-PGG inhibited the proliferation of GC cells. Cell cycle and apoptosis experiments revealed that ß-PGG induced cell cycle arrest and apoptosis of gastric cancer cells. qRT-PCR and Western blot analysis showed that ß-PGG inhibited ß-PGG cells by modulating the p53 signaling pathway. Conclusion: In the present study, the targets and mechanism of ß-PGG in gastric cancer were explored. The results indicate that ß-PGG can be used to develop treatments for GC.

Integrative Analysis of the Transcriptome and Metabolome Reveals Genes Involved in Phenylpropanoid and Flavonoid Biosynthesis in the Trapa bispinosa Roxb.

Background: Trapa bispinosa Roxb. is grown worldwide as an important aquatic cash crop. Current research on Trapa bispinosa primarily focuses on the separation and identification of active ingredients, as well as the inhibitory effect on tumors; however, research on the molecular mechanism of secondary metabolite accumulation is rather limited. Consequently, an integrative analysis of transcriptome and metabolome is required to identify the key metabolic pathways, and key genes, and to explain the molecular mechanism of Trapa bispinosa. Results: The biosynthesis pathways of phenolics in Trapa bispinosa were examined through transcriptome and metabolome analyses. Transcriptome analysis yielded 42.76 million clean reads representing 81,417 unigenes with an average length of 1,752 bp. KEGG pathway analysis revealed that 1,623 unigenes, including 88 candidate unigenes related to phenolics biosynthesis, were up-regulated in Trapa bispinosa shell (FR) when compared to leaves (LF), root (RT), and stem (ST). The FR vs. LF group had the highest number of specific genes involved in phenylpropanoid, flavonoid, flavone, and flavonol biosynthesis pathways compared to all other comparison groups. In addition, RNA sequencing revealed 18,709 SSRs spanning 14,820 unigenes and 4,387 unigenes encoding transcription factors. Metabolome analysis identified 793 metabolites, including 136 flavonoids and 31 phenylpropane compounds. In the FR group compared to the LF group, there were 202 differentially accumulated metabolites (DAMs). The combined transcriptome and metabolome analyses indicated a significant correlation between 1,050 differentially expressed genes (DEGs) and 62 DAMs. This view proposes a schematic of flavonoid biosynthesis in the FR vs. LF group, providing evidence for the differences in genes and metabolites between FR and LF. Conclusion: In this study, through de novo transcriptome assembly and metabolome analysis, several DEGs and DAMs were identified, which were subsequently used to build flavonoid biosynthesis pathways and a correlation network. The findings pave the way for future research into the molecular mechanisms and functional characterization of Trapa bispinosa candidate genes for phenolics biosynthesis.