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Objective: To analyze outcomes and complications of cytoreductive prostatectomy (CRP) for oligometastatic prostate cancer (PCa) in order to elucidate its role in this space. Methods: We performed a systematic literature search using three databases (Medline, Scopus, and Web of Science). The primary endpoints were oncologic outcomes. The secondary endpoints were complication rates and functional results. Results: In all studies, overall survival was better or at least comparable variable in the groups with CRP compared to no local treatment. The greatest benefit from CRP in 5-year overall survival in one study was 67.4% for CRP versus 22.5% for no local treatment. Cancer-specific survival (CSS) showed the same trend. Several authors found significant benefits from CSS in the CRP group: from 79% vs. 46% to 100% vs. 61%. CRP was a predictor of better CSS (hazard ratio 0.264, p=0.004). Positive surgical margin rates differed widely from 28.6% to 100.0%. Urinary continence in CRP versus RP for localized PCa was significantly lower (57.4% vs. 90.8%, p

Ferroptosis induces significant changes in mitochondrial morphology, including membrane condensation, volume reduction, cristae alteration, and outer membrane rupture, affecting mitochondrial function and cellular fate. Recent reports have described the intrinsic cellular iron metabolism and its intricate connection to ferroptosis, a significant kind of cell death characterized by iron dependence and oxidative stress regulation. Furthermore, updated molecular insights have elucidated the significance of mitochondria in ferroptosis and its implications in various cancers. In the context of cancer therapy, understanding the dual role of anastasis and ferroptosis in chemoresistance is crucial. Targeting the molecular pathways involved in anastasis may enhance the efficacy of ferroptosis inducers, providing a synergistic approach to overcome chemoresistance. Research into how DNA damage response (DDR) proteins, metabolic changes, and redox states interact during anastasis and ferroptosis can offer new insights into designing combinatorial therapeutic regimens against several cancers associated with stemness. These treatments could potentially inhibit anastasis while simultaneously inducing ferroptosis, thereby reducing the likelihood of cancer cells evading death and developing resistance to chemotherapy. The objective of this study is to explore the intricate interplay between anastasis, ferroptosis, EMT and chemoresistance, and immunotherapeutics to better understand their collective impact on cancer therapy outcomes. We searched public research databases including google scholar, PubMed, relemed, and the national library of medicine related to this topic. In this review, we discussed the interplay between the tricarboxylic acid cycle and glycolysis implicated in modulating ferroptosis, adding complexity to its regulatory mechanisms. Additionally, the regulatory role of reactive oxygen species (ROS) and the electron transport chain (ETC) in ferroptosis has garnered significant attention. Lipid metabolism, particularly involving GPX4 and System Xc- plays a significant role in both the progression of ferroptosis and cancer. There is a need to investigate the intricate interplay between anastasis, ferroptosis, and chemoresistance to better understand cancer therapy clinical outcomes. Integrating anastasis, and ferroptosis into strategies targeting chemoresistance and exploring its potential synergy with immunotherapy represent promising avenues for advancing chemoresistant cancer treatment. Understanding the intricate interplay among mitochondria, anastasis, ROS, and ferroptosis is vital in oncology, potentially revolutionizing personalized cancer treatment and drug development.

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.

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.

Abstract Background The impact of number of endoscopic enucleation of the prostate techniques (holmium laser enucleation - HoLEP for example) on erectile function have already been investigated. However, the thulium-fiber laser, in this setting remains unstudied. In this study, we compared sexual function outcomes in patients with benign prostatic hyperplasia (BPH) treated with transurethral resection of the prostate (TURP) or thulium-fiber laser enucleation (ThuFLEP). Methods We performed a retrospective analysis of patients who underwent transurethral resection and endoscopic enucleation of the prostate for BPH; inclusion criteria was the presence of infravesical obstruction (IPSS > 20, Qmax