Based on PI-RADS v2.1 combining PHI and ADC values to guide prostate biopsy in patients with PSA 4-20 ng/mL.

PURPOSE: The study aimed to investigate the diagnostic accuracy of prostate health index (PHI) and apparent diffusion coefficient (ADC) values in predicting prostate cancer (PCa) and construct a nomogram for the prediction of PCa and clinically significant PCa (CSPCa) in Prostate Imaging-Reporting and Data System (PI-RADS) three lesions cohort. METHODS: This study prospectively enrolled 301 patients who underwent multiparametric magnetic resonance (mpMRI) and were scheduled for prostate biopsy. The receiver operating characteristic curve (ROC) was performed to estimate the diagnostic accuracy of each predictor. Univariable and multivariable logistic regression analysis was conducted to ascertain hidden risk factors and constructed nomograms in PI-RADS three lesions cohort. RESULTS: In the whole cohort, the area under the ROC curve (AUC) of PHI is relatively high, which is 0.779. As radiographic parameters, the AUC of PI-RADS and ADC values was 0.702 and 0.756, respectively. The utilization of PHI and ADC values either individually or in combination significantly improved the diagnostic accuracy of the basic model. In PI-RADS three lesions cohort, the AUC for PCa was 0.817 in the training cohort and 0.904 in the validation cohort. The AUC for CSPCa was 0.856 in the training cohort and 0.871 in the validation cohort. When applying the nomogram for predicting PCa, 50.0% of biopsies could be saved, supplemented by 6.9% of CSPCa being missed. CONCLUSION: PHI and ADC values can be used as predictors of CSPCa. The nomogram included PHI, ADC values and other clinical predictors demonstrated an enhanced capability in detecting PCa and CSPCa within PI-RADS three lesions cohort.

Adenoviral Vector for Enhanced Prostate Cancer Specific Transferrin Conjugated Drug Targeted Therapy.

Prostate cancer (PCa) is one of the leading causes of death for men worldwide. Unlike some other types of cancer, there is a lack of targeted therapy for prostate cancer patients that can kill cancer cells but do much less damage to the normal tissue. In this paper, we report on an adenoviral vector enhanced prostate cancer specific transferrin conjugated drug targeted therapy. In particular, a functional PCa-specific gene probe is introduced to drive and up-regulate the transferrin receptor expression on the PCa via adenoviral vector. As a result, significantly enhanced accumulation of nanoscale transferrin-doxorubicin (Tf-DOX) protein drug conjugates and concomitant notably elevated PCa tumor inhibition are observed. This conceptual strategy provides the proof-of-concept for the targeted therapy of PCa that is highly desired but not yet developed.

Chitosan Phytate Nanoparticles: A Synergistic Strategy for Effective Dental Caries Prevention.

Dental caries is a widespread oral disease that poses a significant medical challenge. Traditional caries prevention methods, primarily the application of fluoride, often fall short in effectively destroying biofilms and preventing enamel demineralization, thereby providing limited efficacy in halting the progression of caries over time. To address this issue, we have developed a green and cost-effective synergistic strategy for the prevention of dental caries. By combining natural sodium phytate and chitosan, we have created chitosan-sodium phytate nanoparticles that offer both the antimicrobial properties of chitosan and the enamel demineralization-inhibiting capabilities of sodium phytate. In an ex vivo biofilm model of human teeth, we found that these nanoparticles effectively prevent biofilm buildup and acid damage to the mineralized tissue. Additionally, topical treatment of dental caries in rodent models has shown that these nanoparticles effectively suppress disease progression without negatively impacting oral microbiota diversity or causing harm to the gingival-mucosal tissues, unlike traditional prevention methods.

Expanding the Potential of Neoantigen Vaccines: Harnessing Bacille Calmette-Guérin Cell-Wall-Based Nanoscale Adjuvants for Enhanced Cancer Immunotherapy.

Personalized antitumor immunotherapy utilizing neoantigen vaccines holds great promise. However, the limited immunogenicity of existing recognized neoantigens and the inadequate stimulation of antitumor immune responses by conventional adjuvants pose significant challenges. To address these limitations, we developed a nanovaccine that combines a BCG bacterial cell wall skeleton (BCG-CWS) based nanoscale adjuvant (BCNA) with peptide neoantigens (M27 and M30). This integrated approach provides an efficient translational strategy for cancer immunotherapy. The BCNA nanovaccine, formulated with PLGA as an emulsifier, exhibits excellent biocompatibility and superior antigen presentation compared with conventional BCG-CWS adjuvants. Subcutaneous immunization with the BCNA-based nanovaccine effectively targets lymph nodes, eliciting robust innate and tumor-specific immune responses. Importantly, our findings demonstrate that BCNAs significantly enhance neoantigen immunogenicity while minimizing acute systemic toxicity. Furthermore, when combined with a mouse PD-L1 antibody, our strategy achieves complete tumor elimination in 60% of cases and prevents 25% of tumor growth in a melanoma mouse model. In conclusion, our BCNA-based nanovaccine represents a promising avenue for advancing personalized therapeutic neoantigen vaccines and holds significant implications for enhancing personalized immunotherapy and improving patient outcomes in the field of cancer treatment.

Drug-Loaded Bacillus Calmette-Guérin Bacteria for Immuno-Chemo Combo Therapy in Bladder Cancer.

Intravesical Bacillus Calmette-Guérin (BCG) is a well-established strategy for managing high-risk nonmuscle-invasive bladder cancer (NMIBC); however, over half of patients still experience disease recurrence or progression. Although the combined intravesical instillation of various chemotherapeutic drugs is implemented in clinical trials to enhance the BCG therapy, the outcome is far from satisfying due to severe irritative effects and treatment intolerance at high doses. Therefore, it is adopted the "biotin-streptavidin strategy" to doxorubicin (DOX)-encapsulated nanoparticles within live BCG bacteria (DOX@BCG) to improve treatment outcomes. Adherence of BCG to the bladder epithelium helps precisely target DOX@BCG to the local tumor cells and simultaneously increases intratumoral transport of therapeutic drugs. DOX@BCG effectively inhibits cancer progression and prolongs the survival of rats/mice with orthotopic bladder cancer owing to synergism between BCG-immunotherapy, DOX-chemotherapy, and DOX-induced immunogenic tumor cell death; furthermore, it exhibits improved tolerance and biosafety, and establishes antitumor immunity in the tumor microenvironment. Therefore, the drug-loaded live BCG bacterial delivery system holds considerable potential for clinical translation in the intravesical treatment of bladder cancer.

A novel lysosome-related gene signature coupled with gleason score for prognosis prediction in prostate cancer.

Background: Prostate cancer (PCa) is highly heterogeneous, which makes it difficult to precisely distinguish the clinical stages and histological grades of tumor lesions, thereby leading to large amounts of under- and over-treatment. Thus, we expect the development of novel prediction approaches for the prevention of inadequate therapies. The emerging evidence demonstrates the pivotal role of lysosome-related mechanisms in the prognosis of PCa. In this study, we aimed to identify a lysosome-related prognostic predictor in PCa for future therapies. Methods: The PCa samples involved in this study were gathered from The Cancer Genome Atlas database (TCGA) (n = 552) and cBioPortal database (n = 82). During screening, we categorized PCa patients into two immune groups based on median ssGSEA scores. Then, the Gleason score and lysosome-related genes were included and screened out by using a univariate Cox regression analysis and the least absolute shrinkage and selection operation (LASSO) analysis. Following further analysis, the probability of progression free interval (PFI) was modeled by using unadjusted Kaplan-Meier estimation curves and a multivariable Cox regression analysis. A receiver operating characteristic (ROC) curve, nomogram and calibration curve were used to examine the predictive value of this model in discriminating progression events from non-events. The model was trained and repeatedly validated by creating a training set (n = 400), an internal validation set (n = 100) and an external validation (n = 82) from the cohort. Results: Following grouping by ssGSEA score, the Gleason score and two LRGs-neutrophil cytosolic factor 1 (NCF1) and gamma-interferon-inducible lysosomal thiol reductase (IFI30)-were screened out to differentiate patients with or without progression (1-year AUC = 0.787; 3-year AUC = 0.798; 5-year AUC = 0.772; 10-year AUC = 0.832). Patients with a higher risk showed poorer outcomes (p < 0.0001) and a higher cumulative hazard (p < 0.0001). Besides this, our risk model combined LRGs with the Gleason score and presented a more accurate prediction of PCa prognosis than the Gleason score alone. In three validation sets, our model still achieved high prediction rates. Conclusion: In conclusion, this novel lysosome-related gene signature, coupled with the Gleason score, works well in PCa for prognosis prediction.