An endothelial-related prognostic index for bladder cancer patients.

BACKGROUND: Within the tumor microenvironment, endothelial cells hold substantial sway over bladder cancer (BC) prognosis. Herein, we aim to elucidate the impact of endothelial cells on BC patient outcomes by employing an integration of single-cell and bulk RNA sequencing data. METHODS: All data utilized in this study were procured from online databases. R version 3.6.3 and relevant packages were harnessed for the development and validation of an endothelial-associated prognostic index (EPI). RESULTS: EPI was formulated, incorporating six genes (CYTL1, FAM43A, GSN, HSPG2, RBP7, and SLC2A3). EPI demonstrated significant prognostic value in both The Cancer Genome Atlas (TCGA) and externally validated dataset. Functional results revealed a profound association between EPI and endothelial cell functionality, as well as immune-related processes. Our findings suggest that patients with low-risk EPI scores are more likely to respond positively to immunotherapy, as indicated by immune checkpoint activity, immune infiltration, tumor mutational burden, stemness index, TIDE, and IMvigor210 analyses. Conversely, individuals with high-risk EPI scores exhibited heightened sensitivity to cisplatin, docetaxel, and gemcitabine treatment regimens. CONCLUSION: We have effectively discerned pivotal genes from the endothelial cell perspective and constructed an EPI for BC patients, thereby offering promising prospects for precision medicine.

The implications of single-cell RNA-seq analysis in prostate cancer: unraveling tumor heterogeneity, therapeutic implications and pathways towards personalized therapy.

In recent years, advancements in single-cell and spatial transcriptomics, which are highly regarded developments in the current era, particularly the emerging integration of single-cell and spatiotemporal transcriptomics, have enabled a detailed molecular comprehension of the complex regulation of cell fate. The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine. Currently, single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors. Starting from the perspective of RNA sequencing technology, this review outlined the significance of single-cell RNA sequencing (scRNA-seq) in prostate cancer research, encompassing preclinical medicine and clinical applications. We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies, as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis, treatment, and drug resistance characteristics of prostate cancer. These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer. Furthermore, we explore the potential clinical applications stemming from other single-cell technologies in this review, paving the way for future research in precision medicine.

Identification of endothelial-related molecular subtypes for bladder cancer patients.

Background: Bladder cancer (BC) is a disease with significant heterogeneity and poor prognosis. The prognosis and therapeutic response of BC patients are significantly influenced by endothelial cells in the tumor microenvironment. In order to understand BC from the perspective of endothelial cells, we orchestrated molecular subtypes and identified key genes. Methods: Single-cell and bulk RNA sequencing data were extracted from online databases. R and its relative packages were used to analyze these data. Cluster analysis, prognostic value analysis, function analysis, immune checkpoints, tumor immune environment and immune prediction were conducted. Results: Five endothelial-related genes (CYTL1, FAM43A, HSPG2, RBP7, and TCF4) divided BC patients in the TCGA, GSE13507, and GSE32894 datasets into two clusters, respectively. In prognostic value analysis, patients in the cluster 2 were substantially associated with worse overall survival than those in the cluster 1 according to the results of TCGA, GSE13507 and GSE32894 datasets. In the results of functional analysis, the endothelial-related clusters was enriched in immune-related, endothelial-related and metabolism-related pathways. Samples in the cluster 1 had a statistically significant increase in CD4+ T cells and NK-cell infiltration. Cluster 1 was positively correlated with the cancer stem score and tumor mutational burden score. The results of immune prediction analysis indicated that 50.6% (119/235) of patients in the cluster 1 responded to immunotherapy, while the response rate in the cluster 2 decreased to 16.7% (26/155). Conclusion: In this study, we categorized and discovered distinctive prognosis-related molecular subtypes and key genes from the perspective of endothelial cells at the genetic level by integrating single-cell and bulk RNA sequencing data, primarily to provide a roadmap for precision medicine.

M7G-related molecular subtypes can predict the prognosis and correlate with immunotherapy and chemotherapy responses in bladder cancer patients.

BACKGROUND: N7-methylguanosine (m7G) is closely associated with tumor prognosis and immune response in many cancer types. The correlation between m7G and bladder cancer (BC) needs further study. We aimed to orchestrate molecular subtypes and identify key genes for BC from the perspective of m7G. METHODS: RNA-seq and clinical data of BC patients were extracted from TCGA and GSE13507 datasets. The patients were subtyped by "ConsensusClusterPlus" and "limma." The clusters were validated by the Kaplan‒Meier curves, univariable and multivariate Cox regression models, the concordance index, and calibration curves. The immunotherapy response was evaluated by immune checkpoints, immune infiltration, TIDE score, and IMvigor210 cohort. Genomics of Drug Sensitivity in Cancer was utilized to predict the chemotherapy response between the clusters. RESULTS: The m7G-related cluster was ultimately established by EIF4G1, NUDT11, NUDT10, and CCNB1. The independent prognostic value of the m7G-related cluster was validated by the TCGA and GSE13507 datasets. The cluster was involved in immune-associated pathways, such as neutrophil degranulation, antigen processing cross-presentation, and signaling by interleukins pathways. Meanwhile, cluster 2 was positively correlated with many immune checkpoints, such as CD274, CTLA4, HAVCR2, LAG3, PDCD1, and PDCD1LG2. The cluster 2 was significantly correlated with a higher TIDE score than the cluster 1. Furthermore, in the IMvigor210 cohort, patients in the cluster 1 had a higher response rate than those in the cluster 2. Patients in the cluster 2 were sensitive to many chemotherapies. CONCLUSIONS: We successfully determined molecular subtypes and identified key genes for BC from the perspective of m7G, thereby providing a roadmap for the evolution of immunotherapy and precision medicine.

Identification of senescence-related molecular subtypes and key genes for prostate cancer.

We identified distinct senescence-related molecular subtypes and critical genes among prostate cancer (PCa) patients undergoing radical prostatectomy (RP) or radical radiotherapy (RT). We conducted all analyses using R software and its suitable packages. Twelve genes, namely, secreted frizzled-related protein 4 (SFRP4), DNA topoisomerase II alpha (TOP2A), pleiotrophin (PTN), family with sequence similarity 107 member A (FAM107A), C-X-C motif chemokine ligand 14 (CXCL14), prostate androgen-regulated mucin-like protein 1 (PARM1), leucine zipper protein 2 (LUZP2), cluster of differentiation 38 (CD38), cartilage oligomeric matrix protein (COMP), vestigial-like family member 3 (VGLL3), apolipoprotein E (APOE), and aldehyde dehydrogenase 2 family member (ALDH2), were eventually used to subtype PCa patients from The Cancer Genome Atlas (TCGA) database and GSE116918, and the molecular subtypes showed good correlations with clinical features. In terms of the tumor immune environment (TME) analysis, compared with cluster 1, cancer-associated fibroblasts (CAFs) scored significantly higher, while endothelial cells scored lower in cluster 2 in TCGA database. There was a statistically significant correlation between both CAFs and endothelial cells with biochemical recurrence (BCR)-free survival for PCa patients undergoing RP. For the GSE116918 database, cluster 2 had significantly lower levels of CAFs and tumor purity and higher levels of stromal, immune, and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) scores than cluster 1; in addition, patients with high levels of CAFs, stromal scores, immune scores, and ESTIMATE scores and low levels of tumor purity tended to suffer from BCR. Based on the median of differentially expressed checkpoints, high expression of CD96, hepatitis A virus cellular receptor 2 (HAVCR2), and neuropilin 1 (NRP1) in GSE116918 and high expression of CD160 and tumor necrosis factor (ligand) superfamily member 18 (TNFSF18) in TCGA database were associated with a significantly higher risk of BCR than their counterparts. In conclusion, we first constructed distinct molecular subtypes and critical genes for PCa patients undergoing RP or RT from the fresh perspective of senescence.

Circadian rhythm in prostate cancer: time to take notice of the clock.

The circadian clock is an evolutionary molecular product that is associated with better adaptation to changes in the external environment. Disruption of the circadian rhythm plays a critical role in tumorigenesis of many kinds of cancers, including prostate cancer (PCa). Integrating circadian rhythm into PCa research not only brings a closer understanding of the mechanisms of PCa but also provides new and effective options for the precise treatment of patients with PCa. This review begins with patterns of the circadian clock, highlights the role of the disruption of circadian rhythms in PCa at the epidemiological and molecular levels, and discusses possible new approaches to PCa therapy that target the circadian clock.

An autophagy-related gene prognostic index predicting biochemical recurrence, metastasis, and drug resistance for prostate cancer.

Given the dual role of autophagy presenting in tumorigenesis and inhibition, we established an autophagy-related gene prognostic index (ARGPI) with validation to well predict the biochemical recurrence (BCR), metastasis, as well as chemoresistance for patients with prostate cancer (PCa) who underwent radical radiotherapy or prostatectomy. Then, Lasso and COX regression was used to develop the ARGPI. We performed the whole analyses through R packages (version 3.6.3). Secreted phosphoprotein 1 (SPP1), single-minded 2 (SIM2), serine protease inhibitor b5 (SERPINB5), aldehyde dehydrogenase 2 (ALDH2), and acyl-CoA synthetase long-chain 3 (ACSL3) were eventually used to establish the ARGPI score. Patients were divided into two different-risk groups based on the median ARGPI score, high-risk patients with a higher risk of BCR than low-risk patients (hazard ratio [HR]: 5.46, 95% confidence interval [CI]: 3.23-9.24). The risk of metastasis of high-risk patients was higher than low-risk patients (HR: 11.31, 95% CI: 4.89-26.12). In The Cancer Genome Atlas (TCGA) dataset, we observed similar prognostic value of ARGPI in terms of BCR-free survival (HR: 1.79, 95% CI: 1.07-2.99) and metastasis-free survival (HR: 1.80, 95% CI: 1.16-2.78). ARGPI score showed a diagnostic accuracy of 0.703 for drug resistance. Analysis of gene set enrichment analysis (GSEA) indicated that patients in the high-risk group were significantly positively related to interleukin (IL)-18 signaling pathway. Moreover, ARGPI score was significantly related to cancer-related fibroblasts (CAFs; r = 0.36), macrophages (r = 0.28), stromal score (r = 0.38), immune score (r = 0.35), estimate score (r = 0.39), as well as tumor purity (r = -0.39; all P < 0.05). Drug analysis showed that PI-103 was the common sensitive drug and cell line analysis indicated that PC3 was the common cell line of PI-103 and the definitive gene. In conclusion, we found that ARGPI could predict BCR, metastasis, and chemoresistance in PCa patients who underwent radical radiotherapy or prostatectomy.

Lymphocyte-to-Monocyte Ratio (LMR) During Induction Is a Better Predictor Than Preoperative LMR in Patients Receiving Intravesical Bacillus Calmette -Guerin for Non-Muscle-Invasive Bladder Cancer.

The prognostic value of the lymphocyte-to-monocyte ratio during induction (ILMR) remains unclear in non-muscle-invasive bladder cancer (NMIBC) patients receiving Bacillus Calmette-Guérin (BCG). We aimed to determine and compare the prognostic value of the ILMR, preoperative lymphocyte-to-monocyte ratio (PLMR) and their dynamic changes (PILMR). This study collected the data from NMIBC patients receiving BCG treatment in our institution. The prognostic value of the PLMR, ILMR and PILMR was analyzed by the Kaplan-Meier method and Cox proportional hazard regression models. The concordance index and receiver operating characteristic curve analysis were employed to compare the prognostic value of these three factors. Our study enrolled 197 patients. These patients included 170 male patients, and the mean age was 64.17 years. During the follow-up time, 85 patients experienced recurrence, and 55 patients experienced progression. According to the results of COX multivariable analysis, PLMR (P=0.011) and ILMR (P<0.001) could independently predict the recurrence of NMIBC patients receiving BCG. Meanwhile, ILMR (P=0.001) and PILMR (P=0.036) were also the independent prognostic factors of progression. Compared with PLMR and PILMR, ILMR was associated with better accuracy for NMIBC patients receiving BCG. This study first found that the ILMR could independently predict the prognosis of NMIBC patients receiving BCG. Furthermore, we also identified that ILMR was associated with higher prognostic value than PLMR and PILMR, which might help to select an optimal treatment schedule for patients with NMIBC.

Prognostic value of preoperative neutrophil-to-lymphocyte ratio in histological variants of non-muscle-invasive bladder cancer.

PURPOSE: Many studies identified that the preoperative neutrophil-to-lymphocyte ratio (PNLR) was associated with patient prognosis in non-muscle-invasive bladder cancer (NMIBC). We hypothesized that PNLR could be prognostic in patients with histological variants of NMIBC (VH-NMIBC). MATERIALS AND METHODS: This retrospective study included patients with VH-NMIBC admitted at our center between January 2009 and May 2019. The best cut-off value of NLR was measured by the receiver operating characteristic curve and Youden index. The Kaplan-Meier method and Cox proportional hazard regression models were employed to evaluate the association between PNLR and disease prognosis, including recurrence-free survival (RFS), progression-free survival (PFS), cancer-specific survival (CSS), and overall survival (OS). RESULTS: A total of 243 patients with VH-NMIBC were enrolled in our study. According to the Kaplan-Meier method results, patients with PNLR ≥2.2 were associated with poor RFS (p<0.001), PFS (p<0.001), CSS (p<0.001), and OS (p<0.001). Multivariable analyses indicated that PNLR ≥ 2.2 was an independent prognostic factor of RFS (hazard ratio [HR], 2.11; 95% confidence interval [CI, 1.57-1.83; p<0.001), PFS (HR, 2.34; 95% CI, 1.70-3.21; p<0.001), CCS (HR, 2.87; 95% CI, 1.96-4.18; p< 0.001), and OS (HR, 2.83; 95% CI, 1.96-4.07; p<0.001). CONCLUSIONS: This study identified that PNLR ≥2.2 was usually associated with a poor prognosis for patients with VH-NMIBC.

Development of nanotechnology in andrology.

Since first introduced in 1980s, nanotechnology has always been the eye-catching point as its providing us with new approaches to explore the microscopic world. Many nanotechnology-associated novel technologies have been brought into clinical use in the past decades and uncountable patients benefited from them, which convinces us of a bright prospect of nanotechnology in the field of medicine. In this review, literatures concerning nanotechnology applications in andrology were retrieved and we made a comprehensive discussion on drug delivery, gene therapy and stem cell therapy use in andrology, which calls for the engagement of nanotechnology.

Distinction between recurrent glioma and radiation injury using magnetic resonance spectroscopy in combination with diffusion-weighted imaging.

PURPOSE: The aim of this study was to explore the diagnostic effectiveness of magnetic resonance (MR) spectroscopy with diffusion-weighted imaging on the evaluation of the recurrent contrast-enhancing areas at the site of treated gliomas. METHODS AND MATERIALS: In 55 patients who had new contrast-enhancing lesions in the vicinity of the previously resected and irradiated high-grade gliomas, two-dimensional MR spectroscopy and diffusion-weighted imaging were performed. Spectral data for N-acetylaspartate (NAA), choline (Cho), creatine (Cr), lipid (Lip), and lactate (Lac) were analyzed in conjunction with the apparent diffusion coefficient (ADC) in all patients. Diagnosis of these lesions was assigned by means of follow-up or histopathology. RESULTS: The Cho/NAA and Cho/Cr ratios were significantly higher in recurrent tumor than in regions of radiation injury (p < 0.01). The ADC value and ADC ratios (ADC of contrast-enhancing lesion to matching structure in the contralateral hemisphere) were significantly higher in radiation injury regions than in recurrent tumor (p < 0.01). With MR spectroscopic data, two variables (Cho/NAA and Cho/Cr ratios) were shown to differentiate recurrent glioma from radiation injury, and 85.5% of total subjects were correctly classified into groups. However, with discriminant analysis of MR spectroscopy imaging plus diffusion-weighted imaging, three variables (Cho/NAA, Cho/Cr, and ADC ratio) were identified and 96.4% of total subjects were correctly classified. There was a significant difference between the diagnostic accuracy of the two discriminant analyses (Chi-square = 3.96, p = 0.046). CONCLUSION: Using discriminant analysis, this study found that MR spectroscopy in combination with ADC ratio, rather than ADC value, can improve the ability to differentiate recurrent glioma and radiation injury.