Objective: MicroRNA-100 (miR-100) has been demonstrated to be downregulated in bladder cancer tissues, and enforced expression of this miRNA may inhibit cell growth and colony formation of human bladder cancer 5637 cells in vitro. However, the clinical significance of miR-100 in human bladder cancer has not yet been elucidated. Thus, the aim of this study was to investigate the diagnostic and prognostic values of miR-100 in this disease. Methods: Expression levels of miR-100 in 126 pairs of bladder cancer and adjacent normal tissues were detected by TaqMan real-time quantitative RT-PCR assay. In order to determine its prognostic value, overall survival (OS) and progression-free survival (PFS) were evaluated using the Kaplan-Meier method, and multivariate analysis was performed using the Cox proportional hazard analysis. Results: Expression levels of miR-100 in bladder cancer tissues were significantly lower than those in adjacent normal tissues (mean expression level: 2.6 ± 1.2 vs. 3.9 ± 1.5, P < 0.001). When categorized into low vs. high expression, low miR-100 expression was negatively associated with the stage (P = 0.01), the recurrence (P = 0.008), the progression (P = 0.01), and the death (P < 0.001) of patients with bladder cancer. Moreover, low miR-100 expression clearly predicted poorer PFS (P = 0.001) and OS (P < 0.001). In the multivariate analysis, low miR-100 expression was an independent prognostic factor for both PFS (P = 0.01) and OS (P = 0.008). Conclusion: Our data offer the convincing evidence that miR-100 may play an important role in the progression of bladder cancer and that the reduced expression of this miRNA may be independently associated with shorter PFS and OS of patients, suggesting that miR-100 might be a potential marker for further risk stratification in the treatment of this cancer. Virtual slides: The virtual slides’ for this article can be found here:http://www.diagnosticpathology.diagnomx.eu/vs/1105483419841671

Purpose: To evaluate the diagnostic performance of apparent diffusion coefficient (ADC) values for the detection of clinically significant prostate cancer (csPCa) in patients with equivocal Prostate Imaging-Reporting and Data System (PI-RADS) 3 lesions. Materials and methods: In this multicenter retrospective study, data from 460 eligible patients meeting predefined inclusion criteria were analyzed. Following the establishment of a standardized region of interest delineation protocol, ADC measurements were obtained for all PI-RADS 3 lesions. Univariate and multivariate logistic regression analyses were performed to identify independent predictors. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curves with calculation of the area under the curve (AUC). The multivariate model’s discriminative ability was assessed through ROC analysis, while calibration was evaluated using calibration plots. Clinical utility was quantified via decision curve analysis. A risk stratification system was subsequently developed to optimize clinical decision-making. Results: For the 460 patients with PI-RADS 3 lesions, 108 (23.5%) were diagnosed with any grade prostate cancer, and 62 (13.5%) were diagnosed with csPCa. The results of the multivariate analysis indicated that prostate volume (OR = 0.957, 95% CI: 0.931–0.984, P = 0.002), minimum ADC (ADCmin) (OR = 0.009, 95% CI: <0.001–0.381, P = 0.014), and lesions in the peripheral zone (OR = 6.269, 95% CI: 2.332–16.850, P < 0.001) were independent predictors of csPCa. Among the ADC parameters, ADCmin demonstrated superior diagnostic accuracy with an AUC of 0.773 (95% CI: 0.717–0.823) for csPCa. The multivariate prediction model incorporating prostate volume, ADCmin and lesion location showed good discrimination and satisfactory calibration in validation cohorts. Applying the threshold prostate volume <50 mL or ADCmin <0.65 × 10 ⁻³ mm ² /s as the diagnostic criteria of csPCa achieved very high sensitivity (93.5%) and negative predictive value (98.3%). Conclusions: Among the ADC parameters, ADCmin exhibits the highest diagnostic accuracy for identifying csPCa in patients presenting with PI-RADS 3 lesions. Furthermore, we developed a prediction model and a risk stratification system to aid in clinical decision-making regarding prostate biopsy.

Background: Establishment of a reliable prognostic model and identification of novel biomarkers are urgently needed to develop precise therapy strategies for clear cell renal cell carcinoma (ccRCC). Stress response stated T cells (Tstr) are a new T-cell subtype, which are related to poor disease stage and immunotherapy response in various cancers. Methods: 10 machine-learning algorithms and their combinations were applied in this work. A stable Tstr-related score (TCs) was constructed to predict the outcomes and PD-1 blockade treatment response in ccRCC patients. A nomogram based on TCs for personalized prediction of patient prognosis was constructed. Functional enrichment analysis and TimiGP algorithm were used to explore the underlying role of Tstr in ccRCC. The key TCs-related gene was identified by comprehensive analysis, and the bioinformatics results were verified by immunohistochemistry using a tissue microarray. Results: A robust TCs was constructed and validated in four independent cohorts. TCs accurately predicted the prognosis and PD-1 blockade treatment response in ccRCC patients. The novel nomogram was able to precisely predict the outcomes of ccRCC patients. The underlying biological process of Tstr was related to acute inflammatory response and acute-phase response. Mast cells were identified to be involved in the role of Tstr as a protective factor in ccRCC. TNFS13B was shown to be the key TCs-related gene, which was an independent predictor of unfavorable prognosis. The protein expression analysis of TNFSF13B was consistent with the mRNA analysis results. High expression of TNFSF13B was associated with poor response to PD-1 blockade treatment. Conclusions: This study provides a Tstr cell-related score for predicting outcomes and PD-1 blockade therapy response in ccRCC. Tstr cells may exert their pro-tumoral role in ccRCC, acting against mast cells, in the acute inflammatory tumor microenvironment. TNFSF13B could serve as a key biomarker related to TCs.

Objective. This study was to construct a ceRNA (lncRNA-miRNA-mRNA) regulatory network for prostate cancer (PCa) and to explore the prognostic correlation, key biological functions, and pathways of core RNAs. Methods. Three subgene expression matrices (miRNA, lncRNA, and mRNA expression matrix) were taken from the TCGA database and used in this investigation. Differential expression analysis and differential expression miRNAs were carried out. Next, the ceRNA (lncRNA-miRNA-mRNA) regulatory complex was used to visualize our data and show how they interacted. Ultimately, the primary molecular roles and biological pathways of PCa were identified using enrichment analysis by the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). An effect of AC016773.1 on prostate cancer cell proliferation was investigated by knocking out AC016773.1 in an animal model. The interrelationship between AC016773.1 and hsa-mir-25 was validated using RNA immunoprecipitation technology. Results. The lncRNA, miRNA, and mRNA expression matrices obtained from the TCGA database contain 16901, 1881, and 19962 transcripts, respectively. Through differential expression analysis, we obtained 2010 de lncRNA comparative information, 75 lncRNA and miRNA interaction pairs, and 31 targeted de mRNAs. Through the differential expression analysis of RNA nodes in the ceRNA regulatory network, we found that compared with the NP group, in the PCa group, there were 14 lncRNAs upregulated and 25 lncRNAs downregulated, 1 miRNA upregulated and 3 miRNA downregulated, and 10 mRNA upregulated and 21 mRNA downregulated. In KEGG enrichment analysis, the pathways identified by targeted DE-mRNAs were mainly related to calcium signaling pathway, EGFR tyrosine kinase inhibitor resistance, melanoma, PI3K−Akt signaling pathway, and proteoglycans in cancer. In animal models, it was found that knocking down AC016773.1 significantly reduced tumor volume and weight, indicating that AC016773.1 may promote the proliferation of PCa cells. The use of RNA immunoprecipitation technology indicates a direct binding between AC016773.1 and hsa-mir-25. Conclusion. We elucidated the network regulatory relationship of lncRNA-miRNA-mRNA in PCa and further explored the key molecular functions, biological pathways, and prognostic value of targeted DE-mRNAs.