Purpose: N⁶-methyladenosine (m⁶A) is the most abundant internal modification on eukaryotic mRNA and gained increasing attention recently. More and more evidence suggest that m⁶A methylation plays crucial role in tumor genesis and development. However, its role in prostate cancer remains largely unknown. Methods: METTL3 expression status in prostate cancer was analyzed by using TCGA database and Western blotting. m⁶A content was analyzed by using RNA Methylation Quantification Kit. The role of METTL3 in prostate cancer cells was determined by proliferation, survival, colony formation, and invasion assays. The m⁶A level of GLI1 RNA was detected by methylated RNA immunoprecipitation (MeRIP) assay. In vivo role of METTL3 was studied on xenograft models. Results: We found that m⁶A methyltransferase METTL3 was overexpressed in prostate cancer cell lines, together with increased m⁶A content. Functionally, silencing of METTL3 by shRNA in prostate cancer cell lines resulted in decreased m⁶A content, cell proliferation, survival, colony formation, and invasion. Interestingly, overexpression of wild-type METTL3 abrogated the repression effect of METTL3 depletion on m⁶A content, cell proliferation, survival, colony formation, and invasion, while the overexpression of m⁶A catalytic site mutant METTL3 was unable to rescue the inhibitory effect caused by METTL3 depletion. Further mechanism analysis demonstrated that METTL3 silence decreased the m⁶A modification and expression of GLI1, an important component of hedgehog pathway, which led to cell apoptosis. Moreover, depletion of METTL3 inhibited tumor growth in vivo. Conclusion: Our results suggested that the m⁶A methyltransferase METTL3 promotes the growth and motility of prostate cancer cells by regulating hedgehog pathway.

Background: Prostate cancer (PCa), a globally prevalent malignancy, displays intricate heterogeneity within its epithelial cells, closely linked with disease progression and immune modulation. However, the clinical significance of genes and biomarkers associated with these cells remains inadequately explored. To address this gap, this study aimed to comprehensively investigate the roles and clinical value of epithelial cell-related genes in PCa. Methods: Leveraging single-cell sequencing data from GSE176031, we conducted an extensive analysis to identify epithelial cell marker genes (ECMGs). Employing consensus clustering analysis, we evaluated the correlations between ECMGs, prognosis, and immune responses in PCa. Subsequently, we developed and validated an optimal prognostic signature, termed the epithelial cell marker gene prognostic signature (ECMGPS), through synergistic analysis from 101 models employing 10 machine learning algorithms across five independent cohorts. Additionally, we collected clinical features and previously published signatures from the literature for comparative analysis. Furthermore, we explored the clinical utility of ECMGPS in immunotherapy and drug selection using multi-omics analysis and the IMvigor cohort. Finally, we investigated the biological functions of the hub gene, transmembrane p24 trafficking protein 3 (TMED3), in PCa using public databases and experiments. Results: We identified a comprehensive set of 543 ECMGs and established a strong correlation between ECMGs and both the prognostic evaluation and immune classification in PCa. Notably, ECMGPS exhibited robust predictive capability, surpassing traditional clinical features and 80 published signatures in terms of both independence and accuracy across five cohorts. Significantly, ECMGPS demonstrated significant promise in identifying potential PCa patients who might benefit from immunotherapy and personalized medicine, thereby moving us nearer to tailored therapeutic approaches for individuals. Moreover, the role of TMED3 in promoting malignant proliferation of PCa cells was validated. Conclusions: Our findings highlight ECMGPS as a powerful tool for improving PCa patient outcomes and supply a robust conceptual framework for in-depth examination of PCa complexities. Simultaneously, our study has the potential to develop a novel alternative for PCa diagnosis and prognostication.

Bladder cancer (BC) is one of the most common malignant urinary system tumors, and its prognosis is poor. In recent years, autophagy has been closely linked to the development of BC. Therefore, we investigated the potential prognostic role of autophagy-related long non-coding RNA (lncRNA) in patients with BC. We obtained the lncRNA information and autophagy genes, respectively, from The Cancer Genome Atlas (TCGA) data set and the human autophagy database (HADb) and performed a co-expression analysis to identify autophagy gene-associated lncRNAs. Then, we divided the data into training group and testing group. In the training group, 15 autophagy-related lncRNAs were found to have a prognostic value (AC026369.3, USP30-as1, AC007991.2, AC104785.1, AC010503.4, AC037198.1, AC010331.1, AF131215.6, AC084357.2, THUMPD3-AS1, U62317.4, MAN1B1-DTt, AC024060.1, AL662844.4, and AC005229.4). The patients were divided into low-risk group and high-risk group based on the prognostic lncRNAs. The overall survival (OS) time for the high-risk group was shorter than that for the low-risk group [risk ratio (hazard ratio, HR) = 1.08, 95% CI: 1.06–1.10; p < 0.0001]. Using our model, the defined risk value can predict the prognosis of a patient. Next, the model was assessed in the TCGA testing group to further validate these results. A total of 203 patients with BC were recruited to verify the lncRNA characteristics. We divided these patients into high-risk group and low-risk group. The results of testing data set show that the survival time of high-risk patients is shorter than that of low-risk patients. In the training group, the area under the curve (AUC) was more than 0.7, indicating a high level of accuracy. The AUC for a risk model was greater than that for each clinical feature alone, indicating that the risk value of a model was the best indicator for predicting the prognosis. Further training data analysis showed that the gene set was significantly enriched in cancer-related pathways, including actin cytoskeleton regulation and gap junctions. In conclusion, our 15 autophagy-related lncRNAs have a prognostic potential for BC, and may play key roles in the biology of BC.

Nanoscopic therapeutic systems that incorporate therapeutic agents, molecular targeting, and imaging capabilities have gained momentum and exhibited significant therapeutic potential. In this study, multifunctional polymeric nanoparticles with controlled drug delivery, cancer‐targeted capability, and efficient magnetic resonance imaging (MRI) contrast characteristics were formulated and applied in the treatment of castration‐resistant prostate cancer (CRPC). The “core‐shell” targeted nanoparticles (NPs) were synthesized by the self‐assembly of a prefunctionalized amphiphilic triblock copolymer composed of poly(lactic‐co‐glycolic‐acid) (PLGA), polyethylene glycol (PEG), and the Wy5a aptamer (Apt), which have been screened for targeting the CRPC cell line PC‐3 by cell‐SELEX technique as described in our previous study. Docetaxel (Dtxl) and a cluster of hydrophobic superparamagnetic iron oxide (SPIO) nanoparticles were simultaneously encapsulated into the targeted nanoparticles. The targeted NPs showed a controlled drug release and an increased contrast‐enhanced MRI capability. The presence of Wy5a on the nanoparticle surface resulted in the cancer‐targeted delivery to PC‐3 cells in vitro and in vivo. In vitro MRI and cytotoxicity studies demonstrated the ultrasensitive MRI and increased cytotoxicity of these targeted NPs. In vivo studies revealed that the targeted NPs exhibited a more efficacious antitumor capability without significant systemic toxicity. Our data suggested that these targeted NPs may be a promising drug delivery system for the efficacious treatment of CRPC.

Transient receptor potential melastatin subfamily member 7 (TRPM7) was essential in the growth and metastatic ability of prostate cancer cells. However, the effects and the relevant molecular mechanisms of TRPM7 on metastasis of prostate cancer under hypoxic atmosphere remain unclear. This study investigated the role of TRPM7 in the metastatic ability of androgen-independent prostate cancer cells under hypoxia. First, data mining was carried out to disclose the relationship between the TRPM7 gene level and the survival of prostate cancer patients. Specific siRNAs were used to knockdown target genes. Western blotting and qPCR were employed to determine protein and gene expression, respectively. The gene transcription activity was evaluated by luciferase activity assay of promoter gene. The protein interaction was determined by coimmunoprecipitation. Wound healing and transwell assays were employed to evaluated cell migration and invasion, respectively. Open access database results showed that high expression of TRPM7 was closely related to the poor survival of prostate cancer patients. Hypoxia simultaneously increased TRPM7 expression and induced HIF-1α accumulation in androgen-independent prostate cancer cells. Knockdown of TRPM7 significantly promoted HIF-1α degradation through the proteasome and inhibited EMT changes in androgen-independent prostate cancer cells under hypoxic condition. Moreover, TRPM7 knockdown increased the phosphorylation of RACK1 and strengthened the interaction between RACK1 and HIF-1α but attenuated the binding of HSP90 to HIF-1α. Whereas knockdown of RACK1 increased the binding of HSP90 to HIF-1α. Furthermore, both TRPM7 and HIF-1α knockdown significantly suppressed hypoxia-induced Annexin A1 protein expression, and suppression of HIF-1α/Annexin A1 signaling significantly inhibited hypoxia-induced cell migration and invasion of androgen-independent prostate cancer cells. Our findings demonstrate that TRPM7 knockdown promotes HIF-1α degradation via an oxygen-independent mechanism involving increased binding of RAKC1 to HIF-1α, and TRPM7-HIF-1α-Annexin A1 signaling axis plays a crucial role in the EMT, cell migration, and invasion of androgen-independent prostate cancer cells under hypoxic conditions.