Comparative efficacy of commercial oral poly-herbal traditional Chinese medicine formulations combined with western medicine in benign prostatic hyperplasia management: a systematic review and network meta-analysis.

Background: Benign prostatic hyperplasia (BPH) is prevalent among the aging male population and often presents with distressing lower urinary tract symptoms. There is emerging evidence that commercial oral poly-herbal traditional Chinese medicine (TCM) formulation combined with Western medicine (WM) may offer enhanced therapeutic effects compared to WM alone in BPH treatment. Nevertheless, determining the optimal formulations for BPH remains controversial. We aimed to employ a network meta-analysis to compare and assess differences among commonly used and recommended poly-herbal TCM formulations outlined in the Chinese guidelines for BPH treatment, providing clinical medication recommendations and guidance. Methods: We extensively searched for RCTs of BPH patients that had oral poly-herbal TCM formulations and WM treatment, covering both English and Chinese databases up to 31 October 2023. The quality of the included studies was evaluated using the Cochrane risk-of-bias tool Version 2 (ROB2). A Bayesian network meta-analysis was performed to assess the effectiveness of various formulations, followed by sensitivity and subgroup analyses. Results: Our meta-analysis included 107 RCTs involving 11,037 patients across 16 oral poly-herbal TCM formulations. The quality of the selected studies was assessed as "Some concerns". Most formulations combined with WM demonstrated superior therapeutic efficacy compared to WM alone. For clinical effective rate, Jingui Shenqi pill (JGSQ) + WM had the highest-ranking probability (87.38%). Concerning International Prostate Symptom Score (IPSS) and maximum flow rate of urine, Guizhi Fuling capsule (GZFL) + WM was most effective (91.10% and 98.55%). Regarding the quality of life score and postvoid residual urine, Pulean tablet (PLA) + WM ranked first (86.71% and 91.81%). In controlling prostate volume, Huange capsule (HE) + WM demonstrated the highest efficacy (95.65%). Additionally, among the interventions, Lingze (LZ) + WM capsule exhibited the lowest incidence of adverse drug reactions (2.32%). Conclusion: Combining oral poly-herbal TCM formulations with WM may provide greater therapeutic benefits in BPH treatment compared to WM alone. JGSQ, GZFL, PLA, and HE emerged as promising treatment options. However, further rigorous empirical studies are essential to substantiate these findings. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=459651, CRD 42023459651.

Measurements of peri-prostatic adipose tissue by MRI predict bone metastasis in patients with newly diagnosed prostate cancer.

Objectives: To investigate the role of MRI measurements of peri-prostatic adipose tissue (PPAT) in predicting bone metastasis (BM) in patients with newly diagnosed prostate cancer (PCa). Methods: We performed a retrospective study on 156 patients newly diagnosed with PCa by prostate biopsy between October 2010 and November 2022. Clinicopathologic characteristics were collected. Measurements including PPAT volume and prostate volume were calculated by MRI, and the normalized PPAT (PPAT volume/prostate volume) was computed. Independent predictors of BM were determined by univariate and multivariate logistic regression analysis, and a new nomogram was developed based on the predictors. Receiver operating characteristic (ROC) curves were used to estimate predictive performance. Results: PPAT and normalized PPAT were associated with BM (P<0.001). Normalized PPAT positively correlated with clinical T stage(cT), clinical N stage(cN), and Grading Groups(P<0.05). The results of ROC curves indicated that PPAT and normalized PPAT had promising predictive value for BM with the AUC of 0.684 and 0.775 respectively. Univariate and multivariate analysis revealed that high normalized PPAT, cN, and alkaline phosphatase(ALP) were independently predictors of BM. The nomogram was developed and the concordance index(C-index) was 0.856. Conclusions: Normalized PPAT is an independent predictor for BM among with cN, and ALP. Normalized PPAT may help predict BM in patients with newly diagnosed prostate cancer, thus providing adjunctive information for BM risk stratification and bone scan selection.

Inflammation-related signature for prognostic prediction, tumor immune, genomic heterogeneity, and drug choices in prostate cancer: Integrated analysis of bulk and single-cell RNA-sequencing.

Background: Prostate cancer (PCa) ranks as the second most prevalent malignancy among males on a global scale. Accumulating evidence suggests that inflammation has an intricate relationship with tumorigenesis, tumor progression and tumor immune microenvironment. However, the overall impact of inflammation-related genes on the clinical prognosis and tumor immunity in PCa remains unclear. Methods: Machine learning methods were utilized to construct and validate a signature using The Cancer Genome Atlas (TCGA) for training, while the Memorial Sloan Kettering Cancer Center (MSKCC) and GSE70769 cohorts for independent validation. The efficacy of the signature in predicting outcomes and its clinical utility were assessed through a series of investigations encompassing in vitro experiments, survival analysis, and nomogram development. The association between the signature and precision medicine was explored via tumor immunity, genomic heterogeneity, therapeutic response, and molecular docking analyses, using bulk and single-cell RNA-sequencing data. Results: We identified 7 inflammation-related genes with prognostic significance and developed an inflammation-related prognostic signature (IRPS) with 6 genes. Furthermore, we demonstrated that both the IRPS and a nomogram integrating risk score and pathologic T stage exhibited excellent predictive ability for the survival outcomes in PCa patients. Moreover, the IRPS was found to be significantly associated with the tumor immune, genomic heterogeneity, therapeutic response, and drug selection. Conclusion: IRPS can serve as a reliable predictor for PCa patients. The signature may provide clinicians with valuable information on the efficacy of therapy and help personalize treatment for PCa patients.

Integrated machine learning identifies epithelial cell marker genes for improving outcomes and immunotherapy in prostate cancer.

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.

Multi-omics analysis reveals a macrophage-related marker gene signature for prognostic prediction, immune landscape, genomic heterogeneity, and drug choices in prostate cancer.

Introduction: Macrophages are components of the innate immune system and can play an anti-tumor or pro-tumor role in the tumor microenvironment owing to their high heterogeneity and plasticity. Meanwhile, prostate cancer (PCa) is an immune-sensitive tumor, making it essential to investigate the value of macrophage-associated networks in its prognosis and treatment. Methods: Macrophage-related marker genes (MRMGs) were identified through the comprehensive analysis of single-cell sequencing data from GSE141445 and the impact of macrophages on PCa was evaluated using consensus clustering of MRMGs in the TCGA database. Subsequently, a macrophage-related marker gene prognostic signature (MRMGPS) was constructed by LASSO-Cox regression analysis and grouped based on the median risk score. The predictive ability of MRMGPS was verified by experiments, survival analysis, and nomogram in the TCGA cohort and GEO-Merged cohort. Additionally, immune landscape, genomic heterogeneity, tumor stemness, drug sensitivity, and molecular docking were conducted to explore the relationship between MRMGPS and the tumor immune microenvironment, therapeutic response, and drug selection. Results: We identified 307 MRMGs and verified that macrophages had a strong influence on the development and progression of PCa. Furthermore, we showed that the MRMGPS constructed with 9 genes and the predictive nomogram had excellent predictive ability in both the TCGA and GEO-Merged cohorts. More importantly, we also found the close relationship between MRMGPS and the tumor immune microenvironment, therapeutic response, and drug selection by multi-omics analysis. Discussion: Our study reveals the application value of MRMGPS in predicting the prognosis of PCa patients. It also provides a novel perspective and theoretical basis for immune research and drug choices for PCa.

Survival Analysis and a Novel Nomogram Model for Progression-Free Survival in Patients with Prostate Cancer.

Background: This study sought to perform a survival analysis and construct a prognostic nomogram model based on the Gleason grade, total prostate-specific antigen (tPSA), alkaline phosphate (ALP), and TNM stage in patients with prostate cancer (PCa). Methods: The progression-free survival (PFS) of 255 PCa patients was analyzed in this study. The prognostic value of tPSA and ALP was evaluated using the Kaplan-Meier survival curves and Cox regression analysis, and a nomogram model based on the Gleason grade, tPSA, ALP, and TNM stage was further established for PFS prediction in PCa patients. Results: PCa patients with different Gleason grades, tPSA and ALP levels, and TNM stages presented distinct PFS. The Gleason grade, tPSA, ALP, and TNM stage were four independent prognostic indicators. The C-index of the established nomogram was 0.705 for PFS in the test cohort and 0.687 for the validation cohort, and the calibration curves indicated a good consistency between predicted and actual PFS in PCa patients. Conclusion: The data of this study demonstrated that the Gleason grade, tPSA, ALP, and TNM stage of PCa patients are independently correlated with PFS, and a nomogram model based on these indicators may be valuable for the PFS prediction in PCa patient.

HJURP promotes proliferation in prostate cancer cells through increasing CDKN1A degradation via the GSK3ß/JNK signaling pathway.

Genes with cross-cancer aberrations are most likely to be functional genes or potential therapeutic targets. Here, we found a total of 137 genes were ectopically expressed in eight cancer types, of which Holliday junction recognition protein (HJURP) was significantly upregulated in prostate cancer (PCa). Moreover, patients with higher HJURP mRNA and protein levels had poorer outcomes, and the protein levels served as an independent prognosis factor for the overall survival of PCa patients. Functionally, ectopic HJURP expression promoted PCa cells proliferation in vitro and in vivo. Mechanistically, HJURP increased the ubiquitination of cyclin-dependent kinase inhibitor 1 (CDKN1A) via the GSK3ß/JNK signaling pathway and decreased its stability. This study investigated the role of HJURP in PCa proliferation and may provide a novel prognostic and therapeutic target for PCa.

GTSE1 promotes prostate cancer cell proliferation via the SP1/FOXM1 signaling pathway.

G2 and S phase-expressed-1 (GTSE1) has been implicated in the pathogenesis of several malignant tumors. However, its specific role in prostate cancer (PCa) remains unclear. In this study, RNA-Seq data from patients with PCa and controls were downloaded from the FIREBROWSE database, and it was found that the GTSE1 mRNA level was significantly upregulated in PCa. Moreover, patients with higher GTSE1 mRNA levels had higher Gleason scores (P < 0.001), a more advanced pT stage (P = 0.011), and a more advanced pN stage (P = 0.006) as well as a shorter time to biochemical recurrence (P = 0.005). In addition, overexpression of GTSE1 could promote proliferation in LNCaP cells, whereas silencing GTSE1 could inhibit the growth of C4-2 cells in vitro and in vivo. Mechanistically, GTSE1 enhanced the expression of FOXM1 by upregulating the SP1 protein level, a transcription factor of FOXM1, which ultimately promoted PCa cell proliferation. In summary, GTSE1 is a new candidate oncogene in the development and progression of PCa, and it can promote PCa cell proliferation via the SP1/FOXM1 signaling pathway.

MicroRNA Derived from Circulating Exosomes as Noninvasive Biomarkers for Diagnosing Renal Cell Carcinoma.

PURPOSE: Renal cell carcinoma (RCC) is the most common type of kidney cancer in adults. Exosomes are membrane-enclosed extracellular vesicles, and exosomal RNA can be a biomarker for cancer diagnosis and prognosis in RCC patients. We aim to identify differences in miRNA expression profiles in peripheral blood exosomes between RCC patients and healthy subjects as well as to investigate novel markers of RCC. METHODS: We performed exosomal miRNA sequencing of plasma samples obtained from five RCC patients and five control subjects, subsequently 22 RCC patients and 16 control subjects were investigated using qPCR to confirm the differential miRNA which from plasma exosomal RNA sequencing. ROC curves were constructed to assess the diagnostic accuracy of exosomal miRNAs as diagnostic biomarkers of RCC. RESULTS: Exosomes were isolated with the exoeasy maxi kit and confirmed using TEM and NTA. They have a spherical structure with a diameter of approximately 40-180 nm. The exosomal miRNA sequence results showed that a total of 2357 miRNAs were detected, and 245 miRNAs were differentially expressed between RCC patients and healthy controls (p<0.001, average counts >5, log|fc|>1). Further analysis revealing that, versus the control, 17 miRNAs are up-regulated and 5 miRNAs are down-regulated under selection conditions with average miRNAs counts >100. qPCR was performed using 38 subjects-the results showed that the expression levels of hsa-mir-149-3p and hsa-mir-424-3p were upregulated; the expression levels of hsa-mir-92a-1-5p were significantly downregulated in the plasma exosomes of RCC. For diagnosis of RCC, the AUC of hsa-mir-92a-1-5p, hsa-mir-149-3p and hsa-mir-424-3p was 0.8324, 0.7188 and 0.7727, with the sensitivity of 0.875, 0.750 and 0.750, and the specificity of 0.773,0.727 and 0.818, respectively, at the best cutoff value. CONCLUSION: Our study revealed that the expression levels of hsa-mir-92a-1-5p, hsa-mir-149-3p and hsa-mir-424-3p were significantly abnormal in RCC patients, which may be novel biomarkers for RCC diagnosis.

MicroRNA-488 inhibits proliferation and glycolysis in human prostate cancer cells by regulating PFKFB3.

Prostate cancer (PCa) remains the second leading cause of cancer-related death among men in the United States, and its molecular mechanism remains to be elucidated. Recent studies have suggested that microRNAs may play an important role in cancer development and progression. By analyzing the Gene Expression Omnibus dataset, we found lower expression for miR-488 in PCa than in normal tissues. Moreover, CCK-8, EdU, glucose uptake, and lactate secrete assays revealed that overexpression of miR-488 in PCa cell lines PC3 and DU145 resulted in inhibition of proliferation and glycolysis. In contrast, downregulation of miR-488 expression promoted proliferation and glycolysis in PCa cells. Using a bioinformatic approach and dual-luciferase reporter assays, we identified 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase, isoform3 (PFKFB3), as a direct target of miR-488. Inhibition of PFKFB3 also suppressed PCa cell glycolysis and proliferation. Our study suggests that miR-488 inhibits PCa cell proliferation and glycolysis by targeting PFKFB3, and thus, miR-488 may be a novel therapeutic candidate for PCa.

Effect of yeast species on the terpenoids profile of Chinese light-style liquor.

Terpenoids are important trace flavour constituents in Chinese light-style liquors, and are formed by the various yeast species present during fermentation of liquor from cereal and legume materials. Saccharomyces cerevisiae, Pichia kudriavzevii and Wickerhamomyces anomalus are three such yeast species, and we found S. cerevisiae capable of generating thirteen different terpenoids in cereal and legume extract fermentation, by both de novo and biotransformation pathways. We also found that cereals such as sorghum and barley, and legumes such as peas, contained different terpenoids precursors, which differentially affected the formation and profile of terpenoids mixtures. This work gives new insights into the role of yeast species in generating the various terpenoids mixtures found in Chinese light-style liquors.