Expression of 5-methylcytosine regulators is highly associated with the clinical phenotypes of prostate cancer and DNMTs expression predicts biochemical recurrence

Raltitrexed induces apoptosis through activating ROS-mediated ER stress by impeding HSPA8 expression in prostate cancer cells

Prostate cancer is the most common malignant tumor in males, which frequently develops into castration-resistant prostate cancer (CRPC). CRPC metastasis is the main reason for its high mortality rate. At present, it lacks effective treatment for patients with CRPC. Raltitrexed (RTX) has been shown to be effective in the treatment of colorectal cancer. However, the effect of RTX on prostate cancer and the underlying mechanism remain unknown. In the current study, we found that RTX could dose-dependently inhibit proliferation, migration, colony formation and induce apoptosis in DU145 and PC-3 cells. RTX also increased ROS generation in prostate cancer cells. Pretreatment with N-acetyl-L-cysteine (NAC) significantly prevented RTX-induced cell apoptosis and endoplasmic reticulum (ER) stress signaling activation in prostate cancer cells. Additionally, we found RTX-induced ROS generation and ER stress activation depended on the expression of heat shock protein family A member 8 (HSPA8). Over-expression of HSPA8 could alleviate RTX-induced cell apoptosis, ROS generation and ER stress signaling activation. Finally, our study also showed that RTX attenuated the tumor growth of prostate cancer in the DU145 xenograft model and significantly downregulated HSPA8 expression and activated ER stress signaling pathway in tumor tissues. Our study is the first to reveal that RTX induces prostate cancer cells apoptosis through inhibiting the expression of HSPA8 and further inducing ROS-mediated ER stress pathway action. This study suggests that RTX may be a novel promising candidate drug for prostate cancer therapy.

Genome-Wide Analysis on Transcriptome and Methylome in Prevention of Mammary Tumor Induced by Early Life Combined Botanicals

Breast cancer (BC) is the most common malignancy and the second leading cause of cancer death among women in the United States. The consumption of natural dietary components such as broccoli sprouts (BSp) and green tea polyphenols (GTPs) has demonstrated exciting potential in reducing the risk of BC through the regulation of epigenetic mechanisms. However, little is known about their impacts on reversing epigenomic aberrations that are centrally involved in the initiation and progression of BC. Previously, we have determined the efficacy of combined BSp and GTPs treatment on the inhibition of the growth of a mammary tumor in a transgenic Her2/neu mouse model. We sought to extend our previous study to identify universal biomarkers that represent common mechanistic changes among different mouse models in response to this dietary regime by including a new transgenic mouse model, C3(1)-SV40 TAg (SV40). As a result, we identified novel target genes that were differentially expressed and methylated in response to dietary botanicals when administered singly (BSp and GTPs) and in combination (BSp + GTPs) in both mouse models. We discovered more differentially expressed and methylated genes in the combination treatment group compared to the singly administered groups. Subsequently, several biological pathways related to epigenetic regulations were identified in response to the combination treatment. Furthermore, when compared to the BSp and GTPs treatment alone, the combinatorial treatment showed a more significant impact on the regulation of the epigenetic modifier activities involved in DNA methylation and histone modifications. Our study provides key insights about the impact of the combined administration of BSp and GTPs on BC using a multi-omics analysis, suggesting a combinatorial approach is more efficacious in preventing and inhibiting BC by impacting key tumor-related genes at transcriptomic and methylomic levels. Our findings could be further extrapolated as a comprehensive source for understanding the epigenetic modifications that are associated with the effects of these dietary botanicals on BC prevention.

Epigenetic and Epitranscriptomic Control in Prostate Cancer

The initiation of prostate cancer has been long associated with DNA copy-number alterations, the loss of specific chromosomal regions and gene fusions, and driver mutations, especially those of the Androgen Receptor. Non-mutational events, particularly DNA and RNA epigenetic dysregulation, are emerging as key players in tumorigenesis. In this review we summarize the molecular changes linked to epigenetic and epitranscriptomic dysregulation in prostate cancer and the role that alterations to DNA and RNA modifications play in the initiation and progression of prostate cancer.

Expression of 5-methylcytosine regulators is highly associated with the clinical phenotypes of prostate cancer and DNMTs expression predicts biochemical recurrence

In patients with prostate cancer (PCa), there is a high rate of overdiagnosis and frequent overtreatment. Therefore, there is an urgent need for more accurate prediction of biochemical recurrence (BCR). DNA methylation regulation patterns play crucial roles in tumorigenicity, progression, and treatment efficacy in PCa. However, the global relationship between epigenetic alterations, changes in mRNA levels, and pathologic phenotypes of PCa remain largely undefined. Here, we conducted a systematic analysis to identify global coexpression and comethylation modules in PCa. We identified coregulated methylation and expression modules and the relationships between epigenetic modifications, tumor progression, and the corresponding immune microenvironment in PCa. Our results show that DNA methyltransferases (DNMTs) are strongly associated with pathologic phenotypes and immune infiltration patterns in PCa. We built a two-factor predictive model using the expression features of DNMT3B and DNMT1. The model was used to predict the BCR status of patients with PCa and achieved area under the receiver operating characteristic curve values of 0.70 and 0.88 in the training and independent testing datasets, respectively.