Programmed cell death ligand 1 (PD-L1) blockade has achieved great success in cancer immunotherapy. PD-L1 siRNA can restore the immune anti-tumor activity of T cells by downregulating the level of PD-L1 on tumor cells, but the efficiency of PD-1/PD-L1 monotherapy is relatively low. Doxorubicin (DOX) can induce tumor cell apoptosis, and then increase the release of tumor antigen. But the expression of PD-L1 in tumor tissues treated with DOX will be enhanced adaptively. Therefore, DOX combination with PD-L1 siRNA can produce a good synergistic anti-tumor effect. In this study, stem cell membrane (SCM) camouflaged polydopamine nanoparticles carrying DOX and PD-L1 siRNA (PDA–DOX/siPD-L1@SCM) were constructed for targeting prostate cancer (PCa) bone metastases. PDA–DOX/siPD-L1@SCM NPs could effectively enhance blood retention and improve accumulation at tumor sites. In vitro and in vivo studies demonstrated that PDA–DOX/siPD-L1@SCM NPs showed excellent performance in synergistic chemoimmunotherapy for PCa bone metastases. Hence, this study provided an effective strategy for developing biomimetic multifunctional nanoparticles for PCa bone metastasis treatment.

Multiparametric magnetic resonance imaging (mpMRI) has emerged as a first-line screening and diagnostic tool for prostate cancer, aiding in treatment selection and noninvasive radiotherapy guidance. However, the manual interpretation of MRI data is challenging and time-consuming, which may impact sensitivity and specificity. With recent technological advances, artificial intelligence (AI) in the form of computer-aided diagnosis (CAD) based on MRI data has been applied to prostate cancer diagnosis and treatment. Among AI techniques, deep learning involving convolutional neural networks contributes to detection, segmentation, scoring, grading, and prognostic evaluation of prostate cancer. CAD systems have automatic operation, rapid processing, and accuracy, incorporating multiple sequences of multiparametric MRI data of the prostate gland into the deep learning model. Thus, they have become a research direction of great interest, especially in smart healthcare. This review highlights the current progress of deep learning technology in MRI-based diagnosis and treatment of prostate cancer. The key elements of deep learning-based MRI image processing in CAD systems and radiotherapy of prostate cancer are briefly described, making it understandable not only for radiologists but also for general physicians without specialized imaging interpretation training. Deep learning technology enables lesion identification, detection, and segmentation, grading and scoring of prostate cancer, and prediction of postoperative recurrence and prognostic outcomes. The diagnostic accuracy of deep learning can be improved by optimizing models and algorithms, expanding medical database resources, and combining multi-omics data and comprehensive analysis of various morphological data. Deep learning has the potential to become the key diagnostic method in prostate cancer diagnosis and treatment in the future.

Prostate cancer (PCa) is the most common new cancer case and the second most fatal malignancy in men. Surgery, endocrine therapy, radiotherapy and chemotherapy are the main clinical treatment options for PCa. However, most prostate cancers can develop into castration-resistant prostate cancer (CRPC), and due to the invasiveness of prostate cancer cells, they become resistant to different treatments and activate tumor-promoting signaling pathways, thereby inducing chemoresistance, radioresistance, ADT resistance, and immune resistance. Nanotechnology, which can combine treatment with diagnostic imaging tools, is emerging as a promising treatment modality in prostate cancer therapy. Nanoparticles can not only promote their accumulation at the pathological site through passive targeting techniques for enhanced permeability and retention (EPR), but also provide additional advantages for active targeting using different ligands. This property results in a reduced drug dose to achieve the desired effect, a longer duration of action within the tumor and fewer side effects on healthy tissues. In addition, nanotechnology can create good synergy with radiotherapy, chemotherapy, thermotherapy, photodynamic therapy and gene therapy to enhance their therapeutic effects with greater scope, and reduce the resistance of prostate cancer. In this article, we intend to review and discuss the latest technologies regarding the use of nanomaterials as therapeutic and diagnostic tools for prostate cancer.

Prostate cancer (PCa) is a prevalent malignancy with increasing incidence in middle-aged and older men. Despite various treatment options, advanced metastatic PCa remains challenging with poor prognosis and limited effective therapies. Nanomedicine, with its targeted drug delivery capabilities, has emerged as a promising approach to enhance treatment efficacy and reduce adverse effects. Prostate-specific membrane antigen (PSMA) stands as one of the most distinctive and highly selective biomarkers for PCa, exhibiting robust expression in PCa cells. In this review, we explore the applications of PSMA-targeted nanomedicines in advanced PCa management. Our primary objective is to bridge the gap between cutting-edge nanomedicine research and clinical practice, making it accessible to the medical community. We discuss mainstream treatment strategies for advanced PCa, including chemotherapy, radiotherapy, and immunotherapy, in the context of PSMA-targeted nanomedicines. Additionally, we elucidate novel treatment concepts such as photodynamic and photothermal therapies, along with nano-theragnostics. We present the content in a clear and accessible manner, appealing to general physicians, including those with limited backgrounds in biochemistry and bioengineering. The review emphasizes the potential benefits of PSMA-targeted nanomedicines in enhancing treatment efficiency and improving patient outcomes. While the use of PSMA-targeted nano-drug delivery has demonstrated promising results, further investigation is required to comprehend the precise mechanisms of action, pharmacotoxicity, and long-term outcomes. By meticulous optimization of the combination of nanomedicines and PSMA ligands, a novel horizon of PSMA-targeted nanomedicine-based combination therapy could bring renewed hope for patients with advanced PCa.

Recent immunotherapy research has focused on chimeric antigen receptor-modified T cells (CAR-Ts). CAR-T therapies have been clinically applied to manage hematologic malignancies with satisfactory effectiveness. However, the application of CAR-T immunotherapy in solid tumors remains challenging. Even so, current CAR-T immunotherapies for prostate cancer (PCa) have shown some promise, giving hope to patients with advanced metastatic PCa. This review aimed to elucidate different types of prostate tumor-associated antigen targets, such as prostate-specific membrane antigen and prostate stem cell antigen, and their effects. The current status of the corresponding targets in clinical research through their applications was also discussed. To improve the efficacy of CAR-T immunotherapy, we addressed the possible applications of multimodal immunotherapy, chemotherapy, and CAR-T combined therapies. The obstacles of solid tumors were concisely elaborated. Further studies should aim to discover novel potential targets and establish new models by overcoming the inherent barriers of solid tumors, such as tumor heterogeneity and the immunosuppressive nature of the tumor microenvironment.

Introduction: Immune regulatory small molecule JQ1 can block its downstream effector PD-L1 pathway and effectively reverse the PD-L1 upregulation induced by doxorubicin (DOX). So the synergistic administration of chemotherapeutic drug DOX and JQ1 is expected to increase the sensitivity of tumors to immune checkpoint therapy and jointly enhance the body’s own immunity, thus effectively killing tumor cells. Therefore, a drug delivery system loaded with DOX and JQ1 was devised in this study. Methods: Polydopamine nanoparticles (PDA NPs) were synthesized through spontaneous polymerization. Under appropriate pH conditions, DOX and JQ1 were loaded onto the surface of PDA NPs, and the release of DOX and JQ1 were measured using UV-Vis or high performance liquid chromatography (HPLC). The mechanism of fabricated nanocomplex in vitro was investigated by cell uptake experiment, cell viability assays, apoptosis assays, and Western blot analysis. Finally, the tumor-bearing mouse model was used to evaluate the tumor-inhibiting efficacy and the biosafety in vivo. Results: JQ1 and DOX were successfully loaded onto PDA NPs. PDA-DOX/JQ1 NPs inhibited the growth of prostate cancer cells, reduced the expression of apoptosis related proteins and induced apoptosis in vitro. The in vivo biodistribution indicated that PDA-DOX/JQ1 NPs could accumulated at the tumor sites through the EPR effect. In tumor-bearing mice, JQ1 delivered with PDA-DOX/JQ1 NPs reduced PD-L1 expression at tumor sites, generating significant tumor suppression. Furthermore, PDA-DOX/JQ1 NPs could reduce the side effects, and produce good synergistic treatment effect in vivo. Conclusion: We have successfully prepared a multifunctional platform for synergistic prostate cancer therapy.