Unveiling the Etiology of Urological Tumors: A Systematic Review of Mendelian Randomization Applications in Renal Cell Carcinoma, Bladder Cancer, and Prostate Cancer.

BACKGROUND: Our study aims to address two pivotal questions: "What are the recent advancements in understanding the etiology of urological tumors through Mendelian Randomization?" and "How can Mendelian Randomization be more effectively applied in clinical settings to enhance patient health outcomes in the future?" METHODS: In our systematic review conducted in April 2023, we utilized databases like PubMed and Web of Science to explore the influence of Mendelian Randomization in urological oncological diseases. We focused on studies published from January 2018, employing keywords related to urological tumors and Mendelian Randomization, supplemented with MeSH terms and manual reference checks. Our inclusion criteria targeted original research studies, while we excluded reports and non-relevant articles.  Data extraction followed a PICO-based approach, and bias risk was independently evaluated, with discrepancies resolved through discussion. This systematic approach adhered to PRISMA guidelines for accuracy and thoroughness in reporting. RESULTS: From the initial 457 publications, we narrowed down to 43 full-text articles after screening and quality assessments.A deeper understanding of Mendelian Randomization can help us explore risk factors with a clear causal relationship to urological tumors.This insight may pave the way for future research in early diagnosis, treatment, and management of associated diseases. CONCLUSION: Our review underscores the value of MR in urogenital tumor research, highlighting its efficacy in establishing causality and its potential to clarify disease mechanisms. Despite challenges like large sample sizes and variant identification, MR offers new perspectives for understanding and managing these tumors, suggesting a trend towards more inclusive and diverse research approaches.

METTL3-dependent m6A modification mediates bladder remodeling after partial bladder outlet obstruction through CCN2 activation.

AIMS: N6-methyladenosine (m6A) modification is a critical posttranscriptional event in gene regulation. Thus, identifying methyltransferase, demethylase, or m6A binding protein-mediated m6A modifications in cancer or noncancer transcriptomes has become a promising novel strategy for disease therapy development. However, novel insights into m6A modification in partial bladder outlet obstruction (pBOO) and detailed information about the drivers of bladder remodeling remain to be elucidated. Here, we first characterized the m6A modification landscape in pBOO and investigated potential actionable pharmaceutical targets for future therapies. METHODS: We generated an improved animal model of pBOO in SD rats with urethral meatus stricture induced by suturing. Urodynamic investigations and cystometry were carried out to evaluate the physiologic changes elicited by pBOO. Whole-transcriptome sequencing (RNA-seq) and m6A-modified RNA immunoprecipitation sequencing (MeRIP-seq) were subsequently performed to analyze the expression pattern associated with bladder remodeling in pBOO. RESULTS: The cystometric evaluation of bladder function demonstrated obvious increases in pressure-related parameters in the pBOO group. Hematoxylin and eosin staining and Masson's trichrome staining validated the occurrence of bladder remodeling. A global elevation in m6A RNA methylation levels was observed in parallel to a increased expression of METTL3 in the pBOO group. High-throughput sequencing revealed the differences in expression patterns between the pBOO and sham-operated groups. Furthermore, potential m6A-modified genes, including CCN2, may serve as new pharmaceutical targets to reverse bladder remodeling. CONCLUSIONS: Exploring the roles of m6A-modified genes identified as associated with bladder remodeling by integrating RNA-seq and MeRIP-seq data can offer new insights for developing promising treatments for pBOO patients.

A comprehensive analysis of FBN2 in bladder cancer: A risk factor and the tumour microenvironment influencer.

Bladder cancer (BLCA) is a common and difficult-to-manage disease worldwide. Most common type of BLCA is urothelial carcinoma (UC). Fibrillin 2 (FBN2) was first discovered while studying Marfan syndrome, and its encoded products are associated with elastin fibres. To date, the role of FBN2 in BLCA remains unclear. The authors first downloaded data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The patients were divided into high FBN2 expression and low FBN2 expression groups, and the survival curve, clinical characteristics, tumour microenvironment (TME), and immune cell differences were analysed between the two groups. Then, the differentially expressed genes (DEGs) were filtered, and functional enrichment for DEGs was performed. Finally, chemotherapy drug susceptibility analysis based on the high and low FBN2 groups was conducted. The authors found upregulated expression of FBN2 in BLCA and proved that FBN2 could be an independent prognostic factor for BLCA. TME analysis showed that the expression of FBN2 affects several aspects of the TME. The upregulated expression of FBN2 was associated with a high stromal score, which may lead to immunosuppression and be detrimental to immunotherapy. In addition, the authors found that NK cells resting, macrophage M0 infiltration, and other phenomena of immune cell infiltration appeared in the high expression group of FBN2. The high expression of FBN2 was related to the high sensitivity of some chemotherapy drugs. The authors systematically investigated the effects and mechanisms of FBN2 on BLCA and provided a new understanding of the role of FBN2 as a risk factor and TME influencer in BLCA.

A novel autophagy-related long non-coding RNAs prognostic risk score for clear cell renal cell carcinoma.

BACKGROUND: As the main histological subtype of renal cell carcinoma, clear cell renal cell carcinoma (ccRCC) places a heavy burden on health worldwide. Autophagy-related long non-coding RNAs (ARlncRs) have shown tremendous potential as prognostic signatures in several studies, but the relationship between them and ccRCC still has to be demonstrated. METHODS: The RNA-sequencing and clinical characteristics of 483 ccRCC patients were downloaded download from the Cancer Genome Atlas and International Cancer Genome Consortium. ARlncRs were determined by Pearson correlation analysis. Univariate and multivariate Cox regression analyses were applied to establish a risk score model. A nomogram was constructed considering independent prognostic factors. The Harrell concordance index calibration curve and the receiver operating characteristic analysis were utilized to evaluate the nomogram. Furthermore, functional enrichment analysis was used for differentially expressed genes between the two groups of high- and low-risk scores. RESULTS: A total of 9 SARlncRs were established as a risk score model. The Kaplan-Meier survival curve, principal component analysis, and subgroup analysis showed that low overall survival of patients was associated with high-risk scores. Age, M stage, and risk score were identified as independent prognostic factors to establish a nomogram, whose concordance index in the training cohort, internal validation, and external ICGC cohort was 0.793, 0.671, and 0.668 respectively. The area under the curve for 5-year OS prediction in the training cohort, internal validation, and external ICGC cohort was 0.840, 0.706, and 0.708, respectively. GO analysis and KEGG analysis of DEGs demonstrated that immune- and inflammatory-related pathways are likely to be critically involved in the progress of ccRCC. CONCLUSIONS: We established and validated a novel ARlncRs prognostic risk model which is valuable as a potential therapeutic target and prognosis indicator for ccRCC. A nomogram including the risk model is a promising clinical tool for outcomes prediction of ccRCC patients and further formulation of individualized strategy.

Roles of DNA damage repair and precise targeted therapy in renal cancer (Review).

The primary subtypes of renal cell carcinoma (RCC) include clear cell, papillary and chromophobe RCC. RCC occurs often due to loss of von Hippel­Lindau (VHL) and accumulation of lipids and glycogen, and RCC cells may exhibit sensitivity to the disruption of normal metabolism or homologous recombination gene defect. Although the application of molecular­targeted drugs (tyrosine kinase inhibitors) and immune checkpoint inhibitors has been recommended for the treatment of advanced RCC, more targets of DNA damage repair (DDR) signaling pathway involved in the synthetic lethal effect have been investigated. However, although achievements has been made in the exploration of the roles of DDR genes on RCC progression, their association has not been systematically summarized. Poly (ADP­ribose) polymerase (PARP) 1 inhibitors are used in tumors with BRCA1/2 DNA repair­associated mutations. PARP family enzymes perform post­translational modification functions and participate in DDR and cell death. Inhibitors of PARP, ataxia telangiectasia mutant gene and polymerase θ serve key roles in the treatment of specific RCC subtypes. PARP1 may serve as an important biological marker to predict the therapeutic effect of immune checkpoint inhibitors and evaluate the prognosis of patients with ccRCC with polybromo 1 mutation. Therefore, the roles of DDR pathway on RCC progression or treatment may hold promises for the treatment of certain specific types of RCC.

A novel molecular subtypes and risk model based on inflammatory response-related lncrnas for bladder cancer.

BACKGROUND: Inflammation and long noncoding RNAs (lncRNAs) are gradually becoming important in the development of bladder cancer (BC). Nevertheless, the potential of inflammatory response-related lncRNAs (IRRlncRNAs) as a prognostic signature remains unexplored in BC. METHODS: The Cancer Genome Atlas (TCGA) provided RNA expression profiles and clinical information of BC samples, and GSEA Molecular Signatures database provided 1171 inflammation-related genes. IRRlncRNAs were identified using Pearson correlation analysis. After that, consensus clustering was performed to form molecular subtypes. After performing least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses, a risk model constructed based on the prognostic IRRlncRNAs was validated in an independent cohort. Kaplan-Meier (KM) analysis, univariate and multivariate Cox regression, clinical stratification analysis, and time-dependent receiver operating characteristic (ROC) curves were utilized to assess clinical effectiveness and accuracy of the risk model. In clusters and risk model, functional enrichment was investigated using GSEA and GSVA, and immune cell infiltration analysis was demonstrated by ESTIMATE and CIBERSORT analysis. RESULTS: A total of 174 prognostic IRRlncRNAs were confirmed, and 406 samples were divided into 2 clusters, with cluster 2 having a significantly inferior prognosis. Moreover, cluster 2 exhibited a higher ESTIMATE score, immune infiltration, and PD-L1 expression, with close relationships with the inflammatory response. Further, 12 IRRlncRNAs were identified and applied to construct the risk model and divide BC samples into low-risk and high-risk groups successfully. KM, ROC, and clinical stratification analysis demonstrated that the risk model performed well in predicting prognosis. The risk score was identified as an independently significant indicator, enriched in immune, cell cycle, and apoptosis-related pathways, and correlated with 9 immune cells. CONCLUSION: We developed an inflammatory response-related subtypes and steady prognostic risk model based on 12 IRRlncRNAs, which was valuable for individual prognostic prediction and stratification and outfitted new insight into inflammatory response in BC.

Construction of A Novel Ferroptosis-related Prognostic Risk Signature for Survival Prediction in Clear Cell Renal Cell Carcinoma Patients.

PURPOSE: Targeted ferroptosis is a reliable therapy to inhibit tumor growth and enhance immunotherapy. This study generated a novel prognostic risk signature based on ferroptosis-related genes (FRGs), and explored the ability in clinic for clear cell renal cell carcinoma (ccRCC). MATERIALS AND METHODS: The expression profile of mRNA and FRGs for ccRCC patients were exacted from The Cancer Genome Atlas (TCGA) database. A ferroptosis-related prognostic risk signature was constructed based on univariable and multivariable Cox-regression analysis. Kaplan-Meier (KM) survival curves and receiver operating characteristic (ROC) curves were performed to access prognostic value of riskscore. A nomogram integrating riskscore and clinical features was established to predict overall survival (OS). Based on differentially expressed genes between high- and low-OS groups with 5-year OS, function enrichment analyses and single-sample gene set enrichment analysis (ssGSEA) were investigated to immune status. RESULTS: A 9-FRGs prognostic risk signature was constructed based on 37 differentially expressed FRGs. ROC and KM curves showed that riskscore has excellent reliability and predictive ability; Cox regression disclosed the riskscore as an independent prognosis for ccRCC patients. Then, the C-index and calibration curve demonstrated the good performance of nomogram in training and validation cohort, and its predictive ability better than other features. Immune-related biological processes were enriched by function enrichment analysis, and the immune-related cells and functions were differential by ssGSEA between high- and low-OS groups. CONCLUSION: Our study identified and verified a novel 9-FRGs prognostic signature and nomogram to predict OS, providing a novel sight to explore targeted therapy of ferroptosis for ccRCC.

A Novel Inflammation-Related Gene Signature for Overall Survival Prediction and Comprehensive Analysis in Pediatric Patients with Wilms Tumor.

Wilms tumor (WT) is a common pediatric renal cancer, with a poor prognosis and high-risk recurrence in some patients. The inflammatory microenvironment is gradually gaining attention in WT. In this study, novel inflammation-related signatures and prognostic model were explored and integrated using bioinformatics analysis. The mRNA profile of pediatric patients with WT and inflammation-related genes (IRGs) were acquired from Therapeutically Available Research to Generate Effective Treatments (TARGET) and Gene Set Enrichment Analysis (GSEA) databases, respectively. Then, a novel prognostic model founded on 7-IRGs signature (BICC1, CSPP1, KRT8, MYCN, NELFA, NXN, and RNF113A) was established by the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression to stratify pediatric patients with WT into high- and low-risk groups successfully. And a stable performance of the prognostic risk model was verified in predicting overall survival (OS) by receiver-operating characteristic (ROC) curves, Kaplan-Meier (KM) curves, and independent prognostic analysis (p < 0.05). In addition, a novel nomogram integrating risk scores with good robustness was developed and validated by C-index, ROC, and calibration plots. The potential function and pathway were explored via Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and GSEA, with mainly inflammation and immune-related biological processes. The higher-risk scores, the lower immune infiltration, as shown in the single-sample GSEA (ssGSEA) and tumor microenvironment (TME) analysis. The drug sensitivity analysis showed that regulating 7-IRGs signature has a significant correlation with the chemotherapy drugs of WT patients. In summary, this study defined a prognostic risk model and nomogram based on 7-IRGs signature, which may provide novel insights into clinical prognosis and inflammatory study in WT patients. Besides, enhancing immune infiltration based on inflammatory response and regulating 7-IRGs signature are beneficial to ameliorating the efficacy in WT patients.

Prognosis Risk Model Based on Pyroptosis-Related lncRNAs for Bladder Cancer.

OBJECTIVE: Bladder cancer (BC) is the most common malignancy in the urinary system and is prone to recurrence and metastasis. Pyroptosis is a kind of cell necrosis that is triggered by the gasdermin protein family. lncRNAs are noncoding RNAs that are more than 200 nucleotides long. Both pyroptosis and lncRNAs are associated with tumor development and progression. This study is aimed at exploring and establishing a prognostic signature of BC based on pyroptosis-related lncRNAs. METHODS: In this study, The Cancer Genome Atlas (TCGA) database provided us with the RNA sequencing transcriptome data of bladder cancer patients, and we identified differentially expressed pyroptosis-related lncRNAs in bladder cancer. Then, the prognostic significance of these lncRNAs was assessed using univariate Cox regression analysis and LASSO regression analysis. Subsequently, 4 pyroptosis-related lncRNAs, namely, AL121652.1, AL161729.4, AC007128.1, and AC124312.3, were identified by multivariate Cox regression analysis, thus constructing the prognostic risk model. Then, we compared the levels of immune infiltration, differences in cell function, immune checkpoints, and m6A-related gene expression levels between the high- and low-risk groups. RESULT: Patients were divided into low-risk or high-risk groups based on the median risk score. Kaplan-Meier survival analysis indicated that the overall survival of bladder cancer patients in the low-risk group was substantially superior to that in the high-risk group (p < 0.001). The receiver operating characteristic (ROC) curve further confirmed the credibility of our model. Moreover, gene set enrichment analysis (GSEA) indicated that these were different signal pathways significantly enriched between the two groups. Immune infiltration, immune checkpoint, and N6-methyladenosine-related gene analysis also reflected that there were notable differences between the two groups. CONCLUSION: Therefore, this prognostic risk model is based on the level of pyroptotic lncRNAs, which is conducive to individualized assessment of the risk of patients and provides a reference for clinical treatment. This will also help provide insights into the prognosis and treatment of bladder cancer.

A 7-gene signature predicts the prognosis of patients with bladder cancer.

The biomarkers have an important guiding role in prognosis and treatment of patients with bladder cancer (BC). The aim of the present study was to identify and evaluate a prognostic gene signature in BC patients. The gene expression profiles of BC samples and the corresponding clinicopathological data were downloaded from GEO and TCGA. The differentially expressed genes (DEGs) were identified by R software. Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) Cox regression were applied to construct the prognostic score model. A nomogram was established with the identified prognostic factors to predict the overall survival rates of BC patients. The discriminatory and predictive capacity of the nomogram was evaluated based on the concordance index (C-index), calibration curves and decision curve analysis (DCA). A 7-gene signature (KLRB1, PLAC9, SETBP1, NR2F1, GRHL2, ANXA1 and APOL1) was identified from 285 DEGs by univariate and LASSO Cox regression analyses. Univariate and multivariate Cox regression analyses showed that age, lymphovascular invasion, lymphatic metastasis, metastasis and the 7-gene signature risk score was an independent predictor of BC patient prognosis. A nomogram that integrated these independent prognostic factors was constructed. The C-index (0.73, CI 95%, 0.693-0.767) and calibration curve demonstrated the good performance of the nomogram. DCA of the nomogram further showed that this model exhibited good net benefit. The combined 7-gene signature could serve as a biomarker for predicting BC prognosis. The nomogram built by risk score and other clinical factors could be an effective tool for predicting the prognosis of patients with BC.

53 years old is a reasonable cut-off value to define young and old patients in clear cell renal cell carcinoma: a study based on TCGA and SEER database.

BACKGROUND: The objectives of this study were to screen out cut-off age value and age-related differentially expressed genes (DEGs) in clear cell renal cell carcinoma (CCRCC) from Surveillance Epidemiology and End Results (SEER) database and The Cancer Genome Atlas (TCGA) database. METHODS: We selected 45,974 CCRCC patients from SEER and 530 RNA-seq data from TCGA database. The age cut-off value was defined using the X-tile program. Propensity score matching (PSM) was used to balance the differences between young and old groups. Hazard ratio (HR) was applied to evaluate prognostic risk of age in different subgroups. Age-related DEGs were identified via RNA-seq data. Survival analysis was used to assess the relationship between DEGs and prognosis. RESULTS: In this study, we divided the patients into young (n = 14,276) and old (n = 31,698) subgroups according to cut-off value (age = 53). Age > 53 years was indicated as independent risk factor for overall survival (OS) and cancer specific survival (CSS) of CCRCC before and after PSM. The prognosis of old group was worse than that in young group. Eleven gene were differential expression between the younger and older groups in CCRCC. The expression levels of PLA2G2A and SIX2 were related to prognosis of the elderly. CONCLUSION: Fifty-three years old was cut-off value in CCRCC. The prognosis of the elderly was worse than young people. It remind clinicians that more attention and better treatment should be given to CCRCC patients who are over 53 years old. PLA2G2A and SIX2 were age-related differential genes which might play an important role in the poor prognosis of elderly CCRCC patients.

The tumour microenvironment and metabolism in renal cell carcinoma targeted or immune therapy.

Renal cell carcinoma (RCC) is one of the most common tumours of the urinary system, and is insidious and not susceptible to chemoradiotherapy. As the most common subtype of RCC (70-80% of cases), clear cell renal cell carcinoma (ccRCC) is characterized by the loss of von Hippel-Lindau and the accumulation of robust lipid and glycogen. For advanced RCC, molecular-targeted drugs, tyrosine kinase inhibitors (TKIs) and the immune checkpoint inhibitors (ICIs) have been increasingly recommended and investigated. Due to the existence of a highly dynamic, adaptive and heterogeneous tumour microenvironment (TME), and due to the glucose and lipid metabolism in RCC, this cancer may be accompanied by various types of resistance to TKIs and ICIs. With the increased production of lactate, nitric oxide, and other new by-products of metabolism, novel findings of the TME and key metabolic enzymes drived by HIF and other factors have been increasingly clarified in RCC carcinogenesis and therapy. However, there are few summaries of the TME and tumour metabolism for RCC progression and therapy. Here, we summarize and discuss the relationship of the important implicated characteristics of the TME as well as metabolic molecules and RCC carcinogenesis to provide prospects for future treatment strategies to overcome TME-related resistance in RCC.

DNA Methylation Data-Based Classification and Identification of Prognostic Signature of Children With Wilms Tumor.

Background: As an epigenetic alteration, DNA methylation plays an important role in early Wilms tumorigenesis and is possibly used as marker to improve the diagnosis and classification of tumor heterogeneity. Methods: Methylation data, RNA-sequencing (RNA-seq) data, and corresponding clinical information were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. The prognostic values of DNA methylation subtypes in Wilms tumor were identified. Results: Four prognostic subtypes of Wilms tumor patients were identified by consensus cluster analysis performed on 312 independent prognostic CpG sites. Cluster one showed the best prognosis, whereas Cluster two represented the worst prognosis. Unique CpG sites identified in Cluster one that were not identified in other subtypes were assessed to construct a prognostic signature. The prognostic methylation risk score was closely related to prognosis, and the area under the curve (AUC) was 0.802. Furthermore, the risk score based on prognostic signature was identified as an independent prognostic factor for Wilms tumor in univariate and multivariate Cox regression analyses. Finally, the abundance of B cell infiltration was higher in the low-risk group than in the high-risk group, based on the methylation data. Conclusion: Collectively, we divided Wilms tumor cases into four prognostic subtypes, which could efficiently identify high-risk Wilms tumor patients. Prognostic methylation risk scores that were significantly associated with the adverse clinical outcomes were established, and this prognostic signature was able to predict the prognosis of Wilms tumor in children, which may be useful in guiding clinicians in therapeutic decision-making. Further independent studies are needed to validate and advance this hypothesis.

Prognostic Factors and Nomograms to Predict Overall and Cancer-Specific Survival for Children with Wilms' Tumor.

OBJECTIVE: This study is aimed at constructing and verifying nomograms that forecast overall survival (OS) and cancer-specific survival (CSS) of children with Wilms' tumor (WT). PATIENTS AND METHODS: Clinical information of 1613 WT patients who were under 18 years old between 1988 and 2010 was collected from the Surveillance, Epidemiology, and End Results (SEER) database. Using these data, we performed univariate as well as multivariate Cox's regression analyses to determine independent prognostic factors for WT. Then, nomograms to predict 3- and 5-year OS and CSS rates were constructed based on the identified prognostic factors. The nomograms were validated externally and internally. The nomograms' reliability was evaluated utilizing receiver operating characteristic (ROC) curves and concordance indices (C-indices). RESULTS: 1613 WT patients under 18 were involved in the study and randomly divided into the training (n = 1210) and validation (n = 403) cohorts. Age at diagnosis, tumor laterality, tumor size, tumor stage, and use of surgery were determined as independent prognostic factors for OS and CSS in WT and were further applied to construct prognostic nomograms. The C-index and area under the receiver operating characteristic curve (AUC) revealed the great performance of our nomograms. Internal and external calibration plots also showed excellent agreement between actual survival and nomogram prediction. CONCLUSION: Precise and convenient nomograms were developed for forecasting OS and CSS of children with WT. These nomograms were able to offer accurate and individualized prognosis and assisted clinicians in performing suitable therapy.

Competitive endogenous RNA (ceRNA) regulation network of lncRNAs, miRNAs, and mRNAs in Wilms tumour.

BACKGROUND: Competitive endogenous RNAs (ceRNAs) have revealed a new mechanism of interaction between RNAs. However, an understanding of the ceRNA regulatory network in Wilms tumour (WT) remains limited. METHODS: The expression profiles of mRNAs, miRNAs and lncRNAs in Wilms tumour samples and normal samples were obtained from the Therapeutically Applicable Research to Generate Effective Treatment (TARGET) database. The EdgeR package was employed to identify differentially expressed lncRNAs, miRNAs and mRNAs. Functional enrichment analyses via the ClusterProfile R package were performed, and the lncRNA-miRNA-mRNA interaction ceRNA network was established in Cytoscape. Subsequently, the correlation between the ceRNA network and overall survival was analysed. RESULTS: A total of 2037 lncRNAs, 154 miRNAs and 3609 mRNAs were identified as differentially expressed RNAs in Wilms tumour. Of those, 205 lncRNAs, 26 miRNAs and 143 mRNAs were included in the ceRNA regulatory network. The results of Gene Ontology (GO) analysis revealed that the differentially expressed genes (DEGs) were mainly enriched in terms related to response to mechanical stimuli, transcription factor complexes, and transcription factor activity (related to RNA polymerase II proximal promoter sequence-specific DNA binding). The results of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that the DEGs were mainly enriched in pathways related to the cell cycle. The survival analysis results showed that 16 out of the 205 lncRNAs, 1 out of 26 miRNAs and 5 out of 143 mRNAs were associated with overall survival in Wilms tumour patients (P < 0.05). CONCLUSIONS: CeRNA networks play an important role in Wilms tumour. This finding might provide effective, novel insights for further understanding the mechanisms underlying Wilms tumour.

Application of nomograms in the prediction of overall survival and cancer-specific survival in patients with T1 high-grade bladder cancer.

To predict survival outcomes for individual patients with clinical T1 high-grade (T1HG) bladder cancer (BC), data from the Surveillance Epidemiology and End Results (SEER) database were analyzed in the present study. The data of 6,980 cases of T1HG BC between 2004 and 2014 were obtained from the SEER database. Uni- and multivariate Cox analyses were performed to identify significant prognostic factors. Subsequently, prognostic nomograms for predicting 3- and 5-year overall survival (OS) and cancer-specific survival (CSS) rates were constructed based on the SEER database. Clinical information from the SEER database was divided into internal and external groups and used to validate the nomograms. In addition, calibration plot diagrams and concordance indices (C-indices) were used to verify the predictive performance of the nomogram. A total of 6,980 patients were randomly allocated to the training cohort (n=4,886) or the validation cohort (n=2094). Univariate and multivariate Cox analyses indicated that age, ethnicity, tumor size, marital status, radiation and surgical status were independent prognostic factors. These characteristics were used to establish nomograms. The C-indices for OS and CSS rate predictions for the training cohort were 0.707 (95% CI, 0.693-0.721) and 0.700 (95% CI, 0.679-0.721), respectively. Internal and external calibration plot diagrams exhibited an excellent consistency between actual survival rates and nomogram predictions, particularly for 3- and 5-year OS and CSS. The significant prognostic factors in patients with T1HG BC were age, ethnicity, marital status, tumor size, status of surgery and use of radiation. In the present study, a nomogram was developed that may serve as an effective and convenient evaluation tool to help surgeons perform individualized survival evaluations and mortality risk determination for patients with T1HG BC.

Serum Neuroendocrine Markers Predict Therapy Outcome of Patients with Metastatic Castration-Resistant Prostate Cancer: A Meta-Analysis.

PURPOSE: To evaluate whether serum neuroendocrine markers could effectively predict treatment outcomes in patients with metastatic castration-resistant prostate cancer (mCRPC). METHODS: The PubMed, Cochrane Library and Embase databases were sought to identify eligible studies concerning serum neuroendocrine markers and the prognosis of post-treatment mCRPC from inception to April 2018. The association between serum neuroendocrine markers, that is, chromogranin A (CgA) and neurone-specific enolase (NSE), levels and the prognosis of post-treatment mCRPC were summarized using a random-effects model and hazard ratio (HR) with 95% CI Sensitivity analyses were conducted to assess potential bias. RESULTS: A total of 234 participants are included in this meta-analysis (mean age = 71.3 years) from 6 studies. The pooled results show that higher markers' levels at baseline in patients were associated with unfavorable overall survival (OS; univariate analysis: HR 3.775, 95% CI 1.469-9.698, p = 0.006; multivariate analysis: HR 3.838, 95% CI 1.774-8.304, p = 0.001), and a similar situation was observed in progression-free survival (PFS; univariate analysis: HR 2.785, 95% CI 1.315-5.898, p = 0.007; multivariate analysis: HR 1.266, 95% CI 1.017-1.577, p = 0.035). Estimates of the total effects were generally consistent in the sensitivity analysis. Publication bias was observed when performing the univariate analysis of PFS, and we have the explanation accordingly. CONCLUSIONS: The results of this pooled analysis confirm serum neuroendocrine markers could be the effective predictor of treatment outcome in patients with mCRPC. In addition, a combination of CgA and NSE is more valuable to predict worse OS. Further randomized case-control trials are required to validate this relationship.

Analysis of differentially expressed genes, clinical value and biological pathways in prostate cancer.

The present study aimed to investigate the gene expression changes in prostate cancer (PC) and screen the hub genes and associated pathways of PC progression. The authors employed integrated analysis of GSE46602 downloaded from the Gene Expression Omnibus and The Cancer Genome Atlas databases to identify 484 consensual differentially expressed genes (DEGs) in PC, when compared with adjacent normal tissue samples. Functional annotation and pathway analysis were performed. The protein-protein interaction (PPI) networks and module were constructed. RT-qPCR was used to validate the results in clinical PC samples. Survival analysis of hub genes was performed to explore their clinical value. GO analysis results revealed that DEGs were significantly enriched in negative regulation of nitrobenzene metabolic process, extracellular space and protein homodimerization activity. KEGG pathway analysis results revealed that DEGs were most significantly enriched in focal adhesion. The top 10 hub genes were identified to be hub genes from the PPI network, and the model revealed that these genes were enriched in various pathways, including neuroactive ligand-receptor interaction, p53 and glutathione metabolism signaling pathways. RT-qPCR results validated that expression levels of eight genes (PIK3R1, BIRC5, ITGB4, RRM2, TOP2A, ANXA1, LPAR1 and ITGB8) were consistent with the bioinformatics analysis. ITGB4 and RRM2 with genetic alterations exhibited association with a poorer survival rate, compared with those without alterations. These results revealed that PC-related genes and pathways have an important role in tumor expansion, metastasis and prognosis. In summary, these hub genes and related pathways may act as biomarkers or therapeutic targets for PC.

Identification of differentially expressed genes and biological pathways in bladder cancer.

The purpose of the present study was to identify key genes and investigate the related molecular mechanisms of bladder cancer (BC) progression. From the Gene Expression Omnibus database, the gene expression dataset GSE7476 was downloaded, which contained 43 BC samples and 12 normal bladder tissues. GSE7476 was analyzed to screen the differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed for the DEGs using the DAVID database, and a protein­protein interaction (PPI) network was then constructed using Cytoscape software. The results of the GO analysis showed that the upregulated DEGs were significantly enriched in cell division, nucleoplasm and protein binding, while the downregulated DEGs were significantly enriched in 'extracellular matrix organization', 'proteinaceous extracellular matrix' and 'heparin binding'. The results of the KEGG pathway analysis showed that the upregulated DEGs were significantly enriched in the 'cell cycle', whereas the downregulated DEGs were significantly enriched in 'complement and coagulation cascades'. JUN, cyclin­dependent kinase 1, FOS, PCNA, TOP2A, CCND1 and CDH1 were found to be hub genes in the PPI network. Sub­networks revealed that these gene were enriched in significant pathways, including the 'cell cycle' signaling pathway and 'PI3K­Akt signaling pathway'. In summary, the present study identified DEGs and key target genes in the progression of BC, providing potential molecular targets and diagnostic biomarkers for the treatment of BC.