Identification and validation of screening models for breast cancer with 3 serum miRNAs in an 11,349 samples mixed cohort.

PURPOSE: The study focuses on enhancing breast cancer (BC) prognosis through early detection, aiming to establish a non-invasive, clinically viable BC screening method using specific serum miRNA levels. METHODS: Involving 11,349 participants across BC, 11 other cancer types, and control groups, the study identified serum biomarkers through feature selection and developed two BC screening models using six machine learning algorithms. These models underwent evaluation across test, internal, and external validation sets, assessing performance metrics like accuracy, sensitivity, specificity, and the area under the curve (AUC). Subgroup analysis was conducted to test model stability. RESULTS: Based on the three serum miRNA biomarkers (miR-1307-3p, miR-5100, and miR-4745-5p), a BC screening model, SM4BC3miR model, was developed. This model achieved AUC performances of 0.986, 0.986, and 0.939 on the test, internal, and external sets, respectively. Furthermore, the SSM4BC model, utilizing ratio scores of miR-1307-3p/miR-5100 and miR-4745-5p/miR-5100, showed AUCs of 0.973, 0.980, and 0.953, respectively. Subgroup analyses underscored both models' robustness and stability. CONCLUSION: This research introduced the SM4BC3miR and SSM4BC models, leveraging three specific serum miRNA biomarkers for breast cancer screening. Demonstrating high accuracy and stability, these models present a promising approach for early detection of breast cancer. However, their practical application and effectiveness in clinical settings remain to be further validated.

An In Vivo Assessment of a Novel Temperature Control Flexible Ureteroscope System for Monitoring and Controlling Intrarenal Temperature During Flexible Ureteroscopy.

OBJECTIVE: To evaluate the efficacy of a novel temperature control flexible ureteroscope system in the precise monitoring and control of intrarenal temperature (IRT) during ureteroscopy. METHODS: We developed a novel temperature control flexible ureteroscope system (PT-Scope), including a temperature-monitoring ureteroscope and a irrigation-suction platform for temperature regulation. A porcine thermometry model was established to observe temperature changes under varying holmium laser powers (10, 20, 30 W) and irrigation rates (0, 20, 50 mL/min), utilizing percutaneous nephrostomy thermometry and PT-Scope measurements, with subsequent evaluation of temperature variations at different distances from the laser fiber tip. A porcine kidney stone model was established while porcine was randomly assigned to two groups: In the temperature control group, PT-Scope was connected to the irrigation-suction platform with temperature regulation, while in the nontemperature control group without temperature regulation. Comparative analysis was performed to evaluate differences in IRT between the two groups. RESULTS: Across various laser powers and irrigation rates, the temperature measurement capability of the PT-Scope was precise, demonstrating consistency with percutaneous nephrostomy temperature measurements. The temperature obtained from the PT-Scope reflect the temperature approximately 0.05 cm away from the fiber tip, whereas temperatures close to fiber tip were significantly higher. The peak temperature of the temperature control group vs nontemperature control group were 31.70 ± 2.609°C and 44.37 ± 3.318 °C, respectively (P < 0.01). The mean temperature of the temperature control group vs nontemperature control group was 27.40 ± 2.107 °C vs 35.9 ± 1.921 °C (P < 0.01). CONCLUSION: PT-Scope has demonstrated the capability to precisely monitor and control IRT within a safe threshold.

Developing and validating a nomogram for penile cancer survival: A comprehensive study based on SEER and Chinese data.

OBJECTIVE: The primary aim of this study was to create a nomogram for predicting survival outcomes in penile cancer patients, utilizing data from the Surveillance, Epidemiology, and End Results (SEER) and a Chinese organization. METHODS: Our study involved a cohort of 5744 patients diagnosed with penile cancer from the SEER database, spanning from 2004 to 2019. In addition, 103 patients with penile cancer from Sun Yat-sen Memorial Hospital of Sun Yat-sen University were included during the same period. Based on the results of regression analysis, a nomogram is constructed and validated internally and externally. The predictive performance of the model was evaluated by concordance index (c-index), area under the curve, decision curve analysis, and calibration curve, in internal and external datasets. Finally, the prediction efficiency is compared with the TNM staging model. RESULTS: A total of 3154 penile patients were randomly divided into the training group and the internal validation group at a ratio of 2:1. Nine independent risk factors were identified, including age, race, marital status, tumor grade, histology, TNM stage, and the surgical approach. Based on these factors, a nomogram was constructed to predict OS. The nomogram demonstrated relatively better consistency, predictive accuracy, and clinical relevance, with a c-index over 0.73 (in the training cohort, the validation cohort, and externally validation cohort.) These evaluation indexes are far better than the TNM staging system. CONCLUSION: Penile cancer, often overlooked in research, has lacked detailed investigative focus and guidelines. This study stands as the first to validate penile cancer prognosis using extensive data from the SEER database, supplemented by data from our own institution. Our findings equip surgeons with an essential tool to predict the prognosis of penile cancer better suited than TNM, thereby enhancing clinical decision-making processes.

Elucidating the role of MICAL1 in pan-cancer using integrated bioinformatics and experimental approaches.

Molecule interacting with CasL 1 (MICAL1) is a crucial protein involved in cell motility, axon guidance, cytoskeletal dynamics, and gene transcription. This pan-cancer study analyzed MICAL1 across 33 cancer types using bioinformatics and experiments. Dysregulated expression, diagnostic potential, and prognostic value were assessed. Associations with tumor characteristics, immune factors, and drug sensitivity were explored. Enrichment analysis revealed MICAL1's involvement in metastasis, angiogenesis, metabolism, and immune pathways. Functional experiments demonstrated its impact on renal carcinoma cells. These findings position MICAL1 as a potential biomarker and therapeutic target in specific cancers, warranting further investigation into its role in cancer pathogenesis.

The predictive significance of chromobox family members in prostate cancer in humans.

PURPOSE: The Chromobox (CBX) family proteins are crucial elements of the epigenetic regulatory machinery and play a significant role in the development and advancement of cancer. Nevertheless, there is limited understanding regarding the role of CBXs in development or progression of prostate cancer (PCa). Our objective is to develop a unique prognostic model associated with CBXs to improve the accuracy of predicting outcomes of patients with PCa. METHODS: Data from TCGA and GEO databases were analyzed to assess differential expression, prognostic value, gene pathway enrichment, and immune cell infiltration. COX regression analysis was utilized to identify the independent prognostic factors that impact disease-free survival (DFS). The expression of CBX2 and FOXP3+ cells infiltration was verified by immunohistochemical staining of clinical tissue sections. In vitro proliferation, migration and invasion assay were conducted to examine the function of CBX2. RNA-seq was employed to examine the CBX2 related pathway enrichment. RESULTS: CBX2, CBX3, CBX4, and CBX8 were upregulated, while CBX6 and CBX7 were downregulated in PCa tissues. CBXs expression varied by stage and grade. Elevated expression of CBX1, CBX2, CBX3, CBX4 and CBX8 is correlated with poor outcome. CBX2 expression, T stage, and Gleason score were independent prognostic factors. The expression level of CBX2 in PCa tissues was significantly higher than that in adjacent normal tissues. More Treg infiltration was observed in the group with high CBX2 expression. CBX2 expression affected PCa cell growth, migration, and invasion. CONCLUSIONS: CBX2 is involved in the development and advancement of PCa, suggesting its potential as a reliable prognostic indicator for PCa patients.

Establishment of a prognostic risk prediction model incorporating disulfidptosis-related lncRNA for patients with prostate cancer.

PURPOSE: Prostate cancer (PCa) is one of the major tumor diseases that threaten men's health globally, and biochemical recurrence significantly impacts its prognosis. Disulfidptosis, a recently discovered cell death mechanism triggered by intracellular disulfide accumulation leading to membrane rupture, is a new area of research in the context of PCa. Currently, its impact on PCa remains largely unexplored. This study aims to investigate the correlation between long non-coding RNAs (lncRNAs) associated with disulfidptosis and the prognosis of PCa, seeking potential connections between the two. METHODS: Transcriptomic data for a PCa cohort were obtained from the Cancer Genome Atlas database. Disulfidptosis-related lncRNAs (DDRLs) were identified through differential expression and Pearson correlation analysis. DDRLs associated with biochemical recurrence-free survival (BRFS) were precisely identified using univariate Cox and LASSO regression, resulting in the development of a risk score model. Clinical factors linked to BRFS were determined through both univariate and multivariate Cox analyses. A prognostic nomogram combined the risk score with key clinical variables. Model performance was assessed using Receiver Operating Characteristic (ROC) curves, Decision Curve Analysis (DCA), and calibration curves. The functional impact of a critical DDRL was substantiated through assays involving CCK8, invasion, migration, and cell cloning. Additionally, immunohistochemical (IHC) staining for the disulfidptosis-related protein SLC7A11 was conducted. RESULTS: The prognostic signature included AC026401.3, SNHG4, SNHG25, and U73166.1 as key components. The derived risk score from these signatures stood as one of the independent prognostic factor for PCa patients, correlating with poorer BRFS in the high-risk group. By combining the risk score with clinical variables, a practical nomogram was created, accurately predicting BRFS of PCa patients. Notably, silencing AC026401.3 significantly hindered PCa cell proliferation, invasion, migration, and colony formation. IHC staining revealed elevated expression of the dithiosulfatide-related protein SLC7A11 in tumor tissue. CONCLUSIONS: A novel prognostic signature for PCa DDRLs, possessing commendable predictive power, has been constructed, simultaneously providing potential therapeutic targets associated with disulfidptosis, among which AC026401.3 has been validated in vitro and demonstrated inhibition of PCa tumorigenesis after its silencing.

Single-cell analysis extracted CAFs-related genes to established online app to predict clinical outcome and radiotherapy prognosis of prostate cancer.

BACKGROUND: Cancer-associated fibroblasts (CAFs) play a significant role in regulating the clinical outcome and radiotherapy prognosis of prostate cancer (PCa). The aim of this study is to identify CAFs-related genes (CAFsRGs) using single-cell analysis and evaluate their potential for predicting the prognosis and radiotherapy prognosis in PCa. METHODS: We acquire transcriptome and single-cell RNA sequencing (scRNA-seq) results of PCa and normal adjacent tissues from The GEO and TCGA databases. The "MCPcounter" and "EPIC" R packages were used to assess the infiltration level of CAFs and examine their correlation with PCa prognosis. ScRNA-seq and differential gene expression analyses were used to extract CAFsRGs. We also applied COX and LASSO analysis to further construct a risk score (CAFsRS) to assess biochemical recurrence-free survival (BRFS) and radiotherapy prognosis of PCa. The predictive efficacy of CAFsRS was evaluated by ROC curves and subgroup analysis. Finally, we integrated the CAFsRS gene signature with relevant clinical features to develop a nomogram, enhancing the predictive accuracy. RESULTS: The abundance of CAFs is associated with a poor prognosis of PCa patients. ScRNA-seq and differential gene expression analysis revealed 323 CAFsRGs. After COX and LASSO analysis, we obtained seven CAFsRGs with prognostic significance (PTGS2, FKBP10, ENG, CDH11, COL5A1, COL5A2, and SRD5A2). Additionally, we established a risk score model based on the training set (n = 257). The ROC curve was used to confirm the performance of CAFsRS (The AUC values for 1, 3 and 5-year survival were determined to be 0.732, 0.773, and 0.775, respectively.). The testing set (n = 129), GSE70770 set (n = 199) and GSE116918 set (n = 248) revealed that the model exhibited exceptional predictive performance. This was also confirmed by clinical subgroup analysis. The violin plot demonstrated a statistically significant disparity in the CAFs infiltrations between the high-risk and low-risk groups of CAFsRS. Further analysis confirmed that both CAFsRS and T stage were independent prognostic factors for PCa. The nomogram was then established and its excellent predictive performance was demonstrated through calibration and ROC curves. Finally, we developed an online prognostic prediction app ( https://sysu-symh-cafsnomogram.streamlit.app/ ) to facilitate the practical application of the nomogram. CONCLUSIONS: The prognostic prediction risk score model we constructed could accurately predict BRFS and radiotherapy prognosis PCa, which can provide new ideas for clinicians to develop personalized PCa treatment and follow-up programs.

Mechanism of prognostic marker SPOCK3 affecting malignant progression of prostate cancer and construction of prognostic model.

BACKGROUND: SPOCK3 is a secreted extracellular matrix proteoglycan. This study aimed to investigate the effect of SPOCK3 on the malignant progression of prostate cancer and to construct a prognostic model to predict DFS of patients with prostate cancer. METHODS: Clinical and transcriptome sequencing data for prostate cancer were download from the TCGA and GEO databases. The survival curve showed that SPOCK3 has prognostic significance. GO, KEGG, and GSEA enrichment analysis were used to investigate how SPOCK3 affects the malignant progression of prostate cancer. Based on ESTIMATE and ssGSEA, the relationship between SPOCK3 and immune cell infiltration in prostate cancer tissue was clarified. Univariate and multivariate COX regression analysis was used to identify the independent prognostic factors of prostate cancer OS and to construct a nomogram. The calibration curve and ROC curves were drawn to assess the nomogram's predictive power. RESULTS: The survival curve revealed that patients in the low-expression group of SPOCK3 had a poor prognosis. According to enrichment analysis, SOPCK3-related genes were enriched in collagen-containing extracellular matrix, PI3K-Akt, and MAPK signaling pathway. ESTIMATE analysis revealed that SPOCK3 expression was positively correlated with the interstitial score, immune score, and ESTIMATE score. The results of ssGSEA analysis revealed that the infiltration levels of Mast cells, NK cells, and B cells were higher in the SPOCK3 high expression group. Cox regression analysis showed that SPOCK3 expression level, T and Gleason score were independent risk factors of patient prognosis, and a nomogram was constructed. The ROC curve showed the AUCs of DFS at 2, 3, and 5 years. CONCLUSION: SPOCK3 is a protective factor for DFS in prostate cancer patients. SPOCK3 is significantly associated with immune cell infiltration. The prognostic model constructed based on SPOCK3 has excellent predictive performance.

Circular RNA circARHGEF28 inhibited the progression of prostate cancer via the miR-671-5p/LGALS3BP/NF-κB axis.

Circular RNAs (circRNAs) play crucial roles in various biological processes, including prostate cancer (PCa). However, the precise roles and mechanism of circRNAs are complicated. Hence, we studied the function of a circRNA that might be involved in the progression of PCa. In this study, we found that circARHGEF28 was frequently downregulated in PCa tissues and cell lines. Furthermore, gain- and loss-of function experiments in vitro showed that circARHGEF28 inhibited proliferation, migration, and invasion of PCa. Additionally, circARHGEF28 suppressed PCa progression in vivo. Bioinformatics analysis and RNA pull-down and capture assay found that circARHGEF28 sponged miR-671-5p in PCa cells. Importantly, qRT-PCR and dual luciferase assays found that Lectin galactoside-binding soluble 3 binding protein (LGALS3BP) was downstream of miR-671-5p, and western blot analysis further confirmed that LGALS3BP negatively regulated the nuclear factor kappa-B (NF-κB) pathway. These results demonstrated that circARHGEF28 abolished the degradation of LGALS3BP by sponging miR-671-5p, thus blocking the activation of the NF-κB pathway. Our findings revealed that circARHGEF28/miR-671-5p/LGALS3BP/NF-κB may be an important axis that regulates PCa progression.

HMMR promotes prostate cancer proliferation and metastasis via AURKA/mTORC2/E2F1 positive feedback loop.

Although dysregulated HMMR is linked to prostate cancer (PCa) prognosis, the precise mechanisms remain unclear. Here, we sought to elucidate the role of HMMR in PCa progression as well as underlying mechanism. Herein, we found that upregulation of HMMR frequently observed in PCa samples and was associated with poor prognosis. Additionally, HMMR significantly promoted PCa proliferation and metastasis through gain- and loss-of function approaches in vitro and in vivo. Mechanistically, HMMR may interact with AURKA and elevated AURKA protein level through inhibiting ubiquitination-mediated degradation, which subsequently activated mTORC2/AKT pathway to ensure the reinforcement of PCa progression. Moreover, upregulated E2F1 caused from sustained activation of mTORC2/AKT pathway in turn function as transcription factor to promote HMMR transcription, thereby forming a positive feedback loop to trigger PCa progression. Importantly, administration of the mTOR inhibitor partially antagonised HMMR-mediated PCa progression in vivo. In summary, we not only reveal a novel possible post-translation mechanism mediated by HMMR involved in AURKA regulation, but also describe a positive feedback loop that contributes to PCa deterioration, suggesting HMMR may serve as a potential promising therapeutic target in PCa.

Identification of a potential structure-based GPCR drug for interstitial cystitis/bladder pain syndrome: in silico protein structure analysis and molecular docking.

INTRODUCTION AND HYPOTHESIS: There is currently no effective treatment for interstitial cystitis / bladder pain syndrome (IC/BPS) and thus seriously reduces the quality of life of patients. The purpose of this study is to analyze the structure and function of G protein coupled receptors related to IC/BPS by integrating bioinformatics and provide basis for the development of new drugs for IC/BPS. METHODS: We used ProtParam and DNAMAN to analyze the physical and chemical properties of GPR18 and GPR183 proteins. The secondary and tertiary structure, conservative domain, phosphorylation site of both proteins were predicted by ProtScale, PredictProtein, SWISS-MODEL and GPS5.0 respectively. Multiple sequence alignment of the proteins were carried out by DNAMAN and the phylogenetic tree was constructed by MEGA. Further, the molecular docking verification of cannabidiol and both proteins were carried out by using AutoDock Vin. RESULTS: GPR18 and GPR183 proteins were composed of 331 and 361 amino acids respectively. α-helix is the highest in the secondary structure of the two proteins. Both proteins contain seven transmembrane domains specific to G protein coupled receptors. And homology analysis showed that the two proteins had high homology. In terms of molecular docking, cannabidiol, a non psychoactive component extracted from the cannabis, can form effective molecular binding with GPR18 and GPR183 proteins. CONCLUSIONS: We identified the structures of GPR18 and GPR183 proteins and their highly homologous evolutionary properties. Furthermore, both proteins can form effective binding with cannabidiol which provides new insights for the development of IC/BPS drugs by targeting G protein coupled receptors.

A Scoring System for Optimal Selection of Endoscopic Treatment for 1-2cm Lower Pole Renal Calculi.

PURPOSE: To explore the establishment of a scoring system that can provide a reference for clinical decision making regarding the endoscopic treatment of 1-2 cm lower pole stones (LPS). MATERIALS AND METHODS: The data of patients with renal calculi who were treated with percutaneous nephrolithotomy (PCNL) or retrograde intrarenal surgery (RIRS) in three hospitals from January 2013 to December 2017 were analyzed retrospectively. Multivariable logistic analysis was performed to determine the statistically significant indicators and regression coefficients, which were used to construct the scoring system. The stone-free rate (SFR) and postoperative complication rates of PCNL and RIRS within the two fractional segments of the scoring system were compared to select the optimal procedures. RESULTS: A total of 137 patients in the PCNL group and 152 patients in the RIRS group were included in this study. Five factors were found to be most predictive of endoscopic treatment choice: stone number, stone diameter, infundibulopelvic angle (IPA), infundibular length (IL), and infundibular width (IW), yielding a total score ranging from 0-5. In the 0-2 segments, the RIRS group had better outcomes than the PCNL group in terms of the postoperative complication rates (6.8% versus 18.0%, P = .026). In segments 3-5, the SFR of the PCNL group was significantly higher than that of the RIRS group (88.5% versus 70.6%, P = .017). CONCLUSION: Our scoring system was based on the patient's preoperative imaging examination to measure the stone number, stone diameter, IPA, IL and IW. RIRS was recommended at 0-2 segments, and PCNL was recommended at 3-5 segments. This new scoring system is expected to provide guidance for urologists to make endoscopic treatment decisions for 1-2 cm LPS.

WGCNA and molecular docking reveal key hub genes and potential natural inhibitor in interstitial cystitis/bladder pain syndrome.

INTRODUCTION AND HYPOTHESIS: The etiology and treatment of interstitial cystitis/bladder pain syndrome are still controversial. The purpose of this study is to determine the key genes and specific regulatory pathways related to it and to find potential drug-active components through integrated bioinformatics. METHODS: The data set GSE11783 was downloaded from GEO database. The modules significantly related to interstitial cystitis/bladder pain syndrome were identified by weighted correlation network analysis. The genes in the key modules were analyzed by functional enrichment and protein interaction by Cytoscape software, and finally the core hub genes were screened. Furthermore, the molecular docking verification of active components and key proteins was carried out by using AutoDock Vin software. RESULTS: Among the 14 modules derived from WGCNA, turquoise module had the highest correlation with IC/BPS (r = 0.85, P < 0.001). The genes in the module were mainly enriched in the biological processes such as the interaction between cytokines and cytokine receptors and chemokine signaling pathway. The genes in the related modules of differentially expressed genes and WGCNA traits were intersected to obtain the core hub genes. Protein-protein interaction network analysis showed that the key genes were upregulated genes CCR7 and CCL19. In terms of molecular docking, triptolide, the active component in the traditional anti-inflammatory drug Tripterygium wilfordii, can form effective molecular binding with both core hub genes. CONCLUSIONS: Our study identified the core hub genes CCR7 and CCL19, which acted as essential components in interstitial cystitis/bladder pain syndrome. Furthermore, CCR7 and CCL19 can form effective binding with triptolide, which will provide new insights into the development of new therapies for interstitial cystitis/bladder pain syndrome.

A Prognostic Model of Bladder Cancer Based on Metabolism-Related Long Non-Coding RNAs.

Background: Some studies have revealed a close relationship between metabolism-related genes and the prognosis of bladder cancer. However, the relationship between metabolism-related long non-coding RNAs (lncRNA) regulating the expression of genetic material and bladder cancer is still blank. From this, we developed and validated a prognostic model based on metabolism-associated lncRNA to analyze the prognosis of bladder cancer. Methods: Gene expression, lncRNA sequencing data, and related clinical information were extracted from The Cancer Genome Atlas (TCGA). And we downloaded metabolism-related gene sets from the human metabolism database. Differential expression analysis is used to screen differentially expressed metabolism-related genes and lncRNAs between tumors and paracancer tissues. We then obtained metabolism-related lncRNAs associated with prognosis by correlational analyses, univariate Cox analysis, and logistic least absolute shrinkage and selection operator (LASSO) regression. A risk scoring model is constructed based on the regression coefficient corresponding to lncRNA calculated by multivariate Cox analysis. According to the median risk score, patients were divided into a high-risk group and a low-risk group. Then, we developed and evaluated a nomogram including risk scores and Clinical baseline data to predict the prognosis. Furthermore, we performed gene-set enrichment analysis (GSEA) to explore the role of these metabolism-related lncRNAs in the prognosis of bladder cancer. Results: By analyzing the extracted data, our research screened out 12 metabolism-related lncRNAs. There are significant differences in survival between high and low-risk groups divided by the median risk scoring model, and the low-risk group has a more favorable prognosis than the high-risk group. Univariate and multivariate Cox regression analysis showed that the risk score was closely related to the prognosis of bladder cancer. Then we established a nomogram based on multivariate analysis. After evaluation, the modified model has good predictive efficiency and clinical application value. Furthermore, the GSEA showed that these lncRNAs affected bladder cancer prognosis through multiple links. Conclusions: A predictive model was established and validated based on 12 metabolism-related lncRNAs and clinical information, and we found these lncRNA affected bladder cancer prognosis through multiple links.

A Novel Risk Factor Model Based on Glycolysis-Associated Genes for Predicting the Prognosis of Patients With Prostate Cancer.

BACKGROUND: Prostate cancer (PCa) is one of the most prevalent cancers among males, and its mortality rate is increasing due to biochemical recurrence (BCR). Glycolysis has been proven to play an important regulatory role in tumorigenesis. Although several key regulators or predictors involved in PCa progression have been found, the relationship between glycolysis and PCa is unclear; we aimed to develop a novel glycolysis-associated multifactor prediction model for better predicting the prognosis of PCa. METHODS: Differential mRNA expression profiles derived from the Cancer Genome Atlas (TCGA) PCa cohort were generated through the "edgeR" package. Glycolysis-related genes were obtained from the GSEA database. Univariate Cox and LASSO regression analyses were used to identify genes significantly associated with disease-free survival. ROC curves were applied to evaluate the predictive value of the model. An external dataset derived from Gene Expression Omnibus (GEO) was used to verify the predictive ability. Glucose consumption and lactic production assays were used to assess changes in metabolic capacity, and Transwell assays were used to assess the invasion and migration of PC3 cells. RESULTS: Five glycolysis-related genes were applied to construct a risk score prediction model. Patients with PCa derived from TCGA and GEO (GSE70770) were divided into high-risk and low-risk groups according to the median. In the TCGA cohort, the high-risk group had a poorer prognosis than the low-risk group, and the results were further verified in the GSE70770 cohort. In vitro experiments demonstrated that knocking down HMMR, KIF20A, PGM2L1, and ANKZF1 separately led to less glucose consumption, less lactic production, and inhibition of cell migration and invasion, and the results were the opposite with GPR87 knockdown. CONCLUSION: The risk score based on five glycolysis-related genes may serve as an accurate prognostic marker for PCa patients with BCR.

A nomogram to predict stricture-free survival in patients with ureteral stricture after balloon dilation.

BACKGROUND: Balloon dilation is a commonly used minimally invasive endourological treatment of ureteral stricture, but the postoperative recurrence rate is relatively high. And factors contributing to recurrence after treatment are poorly understood. Herein, we sought to develop a novel clinical nomogram to predict ureteral stricture-free survival in patients suffering from ureter stricture and performed balloon dilation. METHODS: The nomogram was established based on a retrospective analysis of 321 patients who received endoscopic balloon dilation alone for ureter strictures from January 2016 to January 2020 in Sun Yat-sen Memorial Hospital using the Cox regression model. Perioperative clinical data and disease outcomes were analyzed. The primary endpoint was the onset of ureteral re-stricture after ureter balloon dilation. Discrimination of the nomogram was assessed by the concordance index (C-index) and the calibration curve. The results were internally validated using bootstrap resampling. RESULTS: Overall, 321 patients with a median follow-up of 590 days were enrolled in the study, among which 97 patients (30.2%) developed recurrence of ureteral stricture during follow-up. Five variables remained significant predictors of ureteral re-stricture after multivariable analyses: stricture nature (P < 0.001), urinary nitrite (P = 0.041), CKD (P = 0.005), stent retention time (P < 0.001), and balloon size (P = 0.029). The calibration craves for the probability of 1-, 3-, and 5-years stricture-free survival (SFS) presented satisfied with the consistency of nomogram prediction and actual observation. The C-index of the model was 0.74 (95% CI 0.70-0.79). CONCLUSIONS: Our study developed the first nomogram to effectively predict stricture-free survival in patients suffering from ureter stricture after balloon dilation. It is helpful to identify the optimal patients with ureter stricture for balloon dilation and improve treatment outcomes. However, further external validation of the nomogram is warranted.

Identification of a Novel Glycolysis-Related LncRNA Signature for Predicting Overall Survival in Patients With Bladder Cancer.

BACKGROUND: Both lncRNAs and glycolysis are considered to be key influencing factors in the progression of bladder cancer (BCa). Studies have shown that glycolysis-related lncRNAs are an important factor affecting the overall survival and prognosis of patients with bladder cancer. In this study, a prognostic model of BCa patients was constructed based on glycolysis-related lncRNAs to provide a point of reference for clinical diagnosis and treatment decisions. METHODS: The transcriptome, clinical data, and glycolysis-related pathway gene sets of BCa patients were obtained from The Cancer Genome Atlas (TCGA) database and the Gene Set Enrichment Analysis (GSEA) official website. Next, differentially expressed glycolysis-related lncRNAs were screened out, glycolysis-related lncRNAs with prognostic significance were identified through LASSO regression analysis, and a risk scoring model was constructed through multivariate Cox regression analysis. Then, based on the median of the risk scores, all BCa patients were divided into either a high-risk or low-risk group. Kaplan-Meier (KM) survival analysis and the receiver operating characteristic (ROC) curve were used to evaluate the predictive power of the model. A nomogram prognostic model was then constructed based on clinical indicators and risk scores. A calibration chart, clinical decision curve, and ROC curve analysis were used to evaluate the predictive performance of the model, and the risk score of the prognostic model was verified using the TCGA data set. Finally, Gene Set Enrichment Analysis (GSEA) was performed on glycolysis-related lncRNAs. RESULTS: A total of 59 differentially expressed glycolysis-related lncRNAs were obtained from 411 bladder tumor tissues and 19 pericarcinomatous tissues, and 9 of those glycolysis-related lncRNAs (AC099850.3, AL589843.1, MAFG-DT, AC011503.2, NR2F1-AS1, AC078778.1, ZNF667-AS1, MNX1-AS1, and AC105942.1) were found to have prognostic significance. A signature was then constructed for predicting survival in BCa based on those 9 glycolysis-related lncRNAs. ROC curve analysis and a nomogram verified the accuracy of the signature. CONCLUSION: Through this study, a novel prognostic prediction model for BCa was established based on 9 glycolysis-related lncRNAs that could effectively distinguish high-risk and low-risk BCa patients, and also provide a new point of reference for clinicians to make individualized treatment and review plans for patients with different levels of risk.

An atlas of bacterial secondary metabolite biosynthesis gene clusters.

Bacterial secondary metabolites are rich sources of novel drug leads. The diversity of secondary metabolite biosynthetic gene clusters (BGCs) in genome-sequenced bacteria, which will provide crucial information for the efficient discovery of novel natural products, has not been systematically investigated. Here, the distribution and genetic diversity of BGCs in 10 121 prokaryotic genomes (across 68 phyla) were obtained from their PRISM4 outputs using a custom python script. A total of 18 043 BGCs are detected from 5743 genomes with non-ribosomal peptide synthetases (25.4%) and polyketides (15.9%) as the dominant classes of BGCs. Bacterial strains harbouring the largest number of BGCs are revealed and BGC count in strains of some genera vary greatly, suggesting the necessity of individually evaluating the secondary metabolism potential. Additional analysis against 102 strains of discovered bacterial genera with abundant amounts of BGCs confirms that Kutzneria, Kibdelosporangium, Moorea, Saccharothrix, Cystobacter, Archangium, Actinosynnema, Kitasatospora, and Nocardia, may also be important sources of natural products and worthy of priority investigation. Comparative analysis of BGCs within these genera indicates the great diversity and novelty of the BGCs. This study presents an atlas of bacterial secondary metabolite BGCs that provides a lot of key information for the targeted discovery of novel natural products.

A robust signature of immune-related long non-coding RNA to predict the prognosis of bladder cancer.

BACKGROUND: Bladder cancer is the second most common malignant tumor in the urogenital system. The research investigated the prognostic role of immune-related long non-coding RNA (lncRNA) in bladder cancer. METHODS: We extracted 411 bladder cancer samples from The Cancer Genome Atlas database. Single-sample gene set enrichment analysis was employed to assess the immune cell infiltration of these samples. We recognized differentially expressed lncRNAs between tumors and paracancerous tissues, and differentially expressed lncRNAs between the high and low immune cell infiltration groups. Venn diagram analysis detected differentially expressed lncRNAs that intersected the above groups. LncRNAs with prognostic significance were identified by regression analysis. Multivariate Cox analysis was used to establish the risk score model. Then we established and evaluated the nomogram. Additionally, we performed gene set enrichment analysis to explore the potential functions of the screened lncRNAs in tumor pathogenesis. RESULTS: Three hundred and twenty differentially expressed lncRNAs were recognized. We randomly divided patients into the training data set and the testing data set at a 2: 1 ratio. In the training data set, 9 immune-related lncRNAs with prognostic significance were identified. The risk score model was constructed to classify patients as high- and low-risk cohorts. Patients in the low-risk cohort had better survival outcomes than those in the high-risk cohort. The nomogram was established based on the indicators including age, gender, tumor-node-metastases stage, and risk score. The model's predictive performance was confirmed by the receiver operating characteristic curve analysis, concordance index method, calibration curve, and decision curve analysis. The testing data set also achieved similar results. Bioinformatics analysis suggested that the 9-lncRNA signature was involved in the modulation of various immune responses, antigen processing and presentation, and T cell receptor signaling pathway. CONCLUSIONS: Our study uncovered the prognostic value of immune-related lncRNAs for bladder cancer and showed that they may regulate tumor pathogenesis in various ways.

Clinicopathological significance and prognostic value of cancer-associated fibroblasts in prostate cancer patients.

INTRODUCTION: Cancer-associated fibroblasts (CAFs) in the tumor microenvironment were considered to play an essential role in tumor growth and development. However, few studies have assessed the prognostic and clinicopathological significance of CAFs in prostate cancer (PCa) patients. METHODS: One hundred thirty pairs of PCa tissues and normal adjacent tissues (NATs) were immunostained with fibroblast activation protein and α-smooth muscle actin to quantify CAFs. Bioinformatics analysis was used to uncover the possible biological functions of CAFs. RESULTS: More CAFs were identified in PCa tissues than in NATs. High density of CAFs may be associated with advanced-stage disease, higher Gleason scores, lymphatic metastases, higher PSA, and poor biochemical recurrence-free survival in PCa. Bioinformatics analysis showed that CAFs may regulate tumor progression and recurrence through ECM modification, PI3K-Akt signaling pathway and regulation of cytoskeleton. CONCLUSION: In summary, our study uncovered the clinicopathological significance and potential mechanism of CAFs and indicated that CAFs may be a useful prognostic biomarker in PCa.