Background: The early detection of high-grade prostate cancer (HGPCa) is of great importance. However, the current detection strategies result in a high rate of negative biopsies and high medical costs. In this study, the authors aimed to establish an Asian Prostate Cancer Artificial intelligence (APCA) score with no extra cost other than routine health check-ups to predict the risk of HGPCa. Patients and methods: A total of 7476 patients with routine health check-up data who underwent prostate biopsies from January 2008 to December 2021 in eight referral centres in Asia were screened. After data pre-processing and cleaning, 5037 patients and 117 features were analyzed. Seven AI-based algorithms were tested for feature selection and seven AI-based algorithms were tested for classification, with the best combination applied for model construction. The APAC score was established in the CH cohort and validated in a multi-centre cohort and in each validation cohort to evaluate its generalizability in different Asian regions. The performance of the models was evaluated using area under the receiver operating characteristic curve (ROC), calibration plot, and decision curve analyses. Results: Eighteen features were involved in the APCA score predicting HGPCa, with some of these markers not previously used in prostate cancer diagnosis. The area under the curve (AUC) was 0.76 (95% CI:0.74–0.78) in the multi-centre validation cohort and the increment of AUC (APCA vs. PSA) was 0.16 (95% CI:0.13–0.20). The calibration plots yielded a high degree of coherence and the decision curve analysis yielded a higher net clinical benefit. Applying the APCA score could reduce unnecessary biopsies by 20.2% and 38.4%, at the risk of missing 5.0% and 10.0% of HGPCa cases in the multi-centre validation cohort, respectively. Conclusions: The APCA score based on routine health check-ups could reduce unnecessary prostate biopsies without additional examinations in Asian populations. Further prospective population-based studies are warranted to confirm these results.

We performed this study to investigate the diagnostic performance of prostate-specific antigen density (PSAD) in a multicenter cohort of the Chinese Prostate Cancer Consortium. Outpatients with prostate-specific antigen (PSA) levels ≥4.0 ng ml⁻¹ regardless of digital rectal examination (DRE) results or PSA levels <4.0 ng ml⁻¹ and abnormal DRE results were included from 18 large referral hospitals in China. The diagnostic performance of PSAD and the sensitivity and specificity for the diagnosis of prostate cancer (PCa) and high-grade prostate cancer (HGPCa) at different cutoff values were evaluated. A total of 5220 patients were included in the study, and 2014 (38.6%) of them were diagnosed with PCa. In patients with PSA levels ranging from 4.0 to 10.0 ng ml⁻¹, PSAD was associated with PCa and HGPCa in both univariate (odds ratio [OR] = 45.15, P < 0.0001 and OR = 25.38, P < 0.0001, respectively) and multivariate analyses (OR = 52.55, P < 0.0001 and OR = 26.05, P < 0.0001, respectively). The areas under the receiver operating characteristic curves (AUCs) of PSAD in predicting PCa and HGPCa were 0.627 and 0.630, respectively. With the PSAD cutoff of 0.10 ng ml⁻², we obtained a sensitivity of 88.7% for PCa, and nearly all (89.9%) HGPCa cases could be detected and biopsies could be avoided in 20.2% of the patients (359/1776 cases). Among these patients who avoided biopsies, only 30 cases had HGPCa. We recommend 0.10 ng ml⁻² as the proper cutoff value of PSAD, which will obtain a sensitivity of nearly 90% for both PCa and HGPCa. The results of this study should be validated in prospective, population-based multicenter studies.

In the absence of early detection and initial treatment, prostate cancer often progresses to an advanced stage, frequently spreading to the bones and significantly impacting patients’ well-being and healthcare resources. Therefore, managing patients with prostate cancer that has spread to the bones often involves using bone-targeted medications like bisphosphonates and denosumab to enhance bone structure and minimize skeletal complications. Additionally, researchers are studying the tumor microenvironment and biomarkers to understand the mechanisms and potential treatment targets for bone metastases in prostate cancer. A literature search was conducted to identify clinical studies from 2013 to 2023 that focused on pain, performance status, or quality of life as primary outcomes. The analysis included details such as patient recruitment, prior palliative therapies, baseline characteristics, follow-up, and outcome reporting. The goal was to highlight the advancements and trends in bone metastasis research in prostate cancer over the past decade, with the aim of developing strategies to prevent and treat bone metastases and improve the quality of life and survival rates for prostate cancer patients.

Clear cell renal cell carcinoma (ccRCC) with venous tumor thrombus (VTT) is associated with poor prognosis. Our integrative analyses of transcriptome and proteome reveal distinctive molecular features of ccRCC with VTT, and yield the development of a prognostic classifier to facilitate ccRCC molecular subtyping and treatment. The RNA sequencing and mass spectrometry were performed in normal-tumor-thrombus tissue triples of five ccRCC patients. Statistical analysis, GO and KEGG enrichment analysis, and protein–protein interaction network construction were used to interpret the transcriptomic and proteomic data. A six-gene-based classifier was developed to predict patients’ survival using Cox regression, which was validated in an independent cohort. Transcriptomic analysis identified 1131 tumorigenesis-associated differentially expressed genes (DEGs) and 856 invasion-associated DEGs. Overexpression of transcription factor EGR2 in VTT indicated its important role in tumor invasion. Furthermore, proteomic analysis showed 597 tumorigenesis-associated differentially expressed proteins (DEPs) and 452 invasion-associated DEPs. The invasion-associated DEPs showed unique enrichment in DNA replication, lysine degradation, and PPAR signaling pathway. Integration of transcriptome and proteome reveals 142 tumorigenesis-associated proteins and 84 invasion-associated proteins displaying changes consistent with corresponding genes in transcriptomic profiling. Based on their different expression patterns among normal-tumor-thrombus triples, RAB25 and GGT5 were supposed to play a consistent role in both tumorigenesis and invasion processes, while SHMT2 and CADM4 might play the opposite roles in tumorigenesis and thrombus invasion. A prognostic classifier consisting of six DEGs (DEPTOR, DPEP1, NAT8, PLOD2, SLC7A5, SUSD2) performed satisfactorily in predicting survival of ccRCC patients (HR = 4.41, P < 0.001), which was further validated in an independent cohort of 40 cases (HR = 5.52, P = 0.026). Our study revealed the transcriptomic and proteomic profiles of ccRCC patients with VTT, and identified the distinctive molecular features associated with VTT. The six-gene-based prognostic classifier developed by integrative analyses may facilitate ccRCC molecular subtyping and treatment.

Background. As a common urological disease with a high recurrence rate, nephrolithiasis caused by CaOx may elicit a strong immunologic response. We present a CyTOF-based atlas of the immune landscape in nephrolithiasis models to understand how the immune system contributes to, and is affected by, the underlying response caused by SIRT3 knockout and CaOx inducement. Materials and Methods. We performed a large-scale CyTOF analysis of immune cell abundance profiles in nephrolithiasis. The immunophenotyping data were collected from four different mouse models, including the SIRT3 wild-type or knockout, including and excluding CaOx inducement. Unsupervised analysis strategies, such as SPADE and viSNE, revealed the intrarenal resident immune components and the immune alterations caused by SIRT3 knockout and CaOx-induced renal injury. Results. An overview analysis of the immune landscape identified T cells and macrophages as the main immune cell population in nephrolithiasis models. Highly similar phenotypes were observed among CD4⁺ and CD8⁺ T cell subsets, including cells expressing Ki67, Ly6C, Siglec-F, and TCRβ. Macrophages expressed a characteristic panel of markers with varied expression levels including MHC II, SIRPα, CD11c, Siglec-F, F4/80, CD64, and CD11b, indicating more subtle differences in marker expression than T cells. The SIRT3^KO/CaOx and SIRT3^WT/CaOx groups exhibited global differences in the intrarenal immune landscape, whereas only small differences existed between the SIRT3^KO/CaOx and SIRT3^KO/Ctrl groups. Among the major immune lineages, the response of CD4⁺ T cells, NK cells, monocytes, and M1 to CaOx inducement was regulated by SIRT3 expression in contrast to the expression changes of B cells, DCs, and granulocytes caused by CaOx inducement. The panel of immune markers influenced by CaOx inducement significantly varied with and without SIRT3 knockout. Conclusion. In a CaOx-induced nephrolithiasis model, SIRT3 has a critical role in regulating the immune system, especially in reducing inflammatory injury. The characteristic panel of altered immune clusters and markers provides novel insights leading to improved prediction and management of nephrolithiasis.