Down-regulation and clinical significance of Sorbin and SH3 domain-containing protein 1 in bladder cancer tissues.

Bladder cancer (BC) is a common cancer worldwide with a high prevalence. This study was conducted to elucidate the expression and clinical significance of Sorbin and SH3 domain-containing protein 1 (SORBS1) in BC as well as to explore its molecular mechanism in BC tumourigenesis. RNA-sequencing data, microarray, and Immunohistochemistry (IHC) were applied to elucidated the SORBS1 expression at multiple levels. After that, the relationship between tumour-immune infiltration and SORBS1 was also explored. Finally, SORBS1-related genes in BC were identified to perform functional enrichment analyses. The expression integration revealed that the comprehensive expression of SORBS1 at the mRNA level was -1.02 and that at the protein level was -3.73, based on 12 platforms, including 1221 BC and 187 non-BC samples. SORBS1 was negatively correlated with tumour purity (correlation = -0.342, p < 0.001) and positively correlated with macrophage (correlation = 0.358, p < 0.001). The results of enrichment analyses revealed that the most significant biological pathways of SORBS1-related genes were epithelial-mesenchymal transition. SORBS1 was significantly down-regulated in BC and may play a role as tumour suppressor. This study provides new directions and biomarkers for future BC diagnosis.

Integrative Single-Cell Analysis Reveals Transcriptional and Epigenetic Regulatory Features of Clear Cell Renal Cell Carcinoma.

Clear cell renal cell carcinoma (ccRCC) frequently features a high level of tumor heterogeneity. Elucidating the chromatin landscape of ccRCC at the single-cell level could provide a deeper understanding of the functional states and regulatory dynamics underlying the disease. Here, we performed single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) on 19 ccRCC samples, and whole-exome sequencing was used to understand the heterogeneity between individuals. Single-cell transcriptome and chromatin accessibility maps of ccRCC were constructed to reveal the regulatory characteristics of different tumor cell subtypes in ccRCC. Two long noncoding RNAs (RP11-661C8.2 and CTB-164N12.1) were identified that promoted the invasion and migration of ccRCC, which was validated with in vitro experiments. Taken together, this study comprehensively characterized the gene expression and DNA regulation landscape of ccRCC, which could provide new insights into the biology and treatment of ccRCC. SIGNIFICANCE: A comprehensive analysis of gene expression and DNA regulation in ccRCC using scATAC-seq and scRNA-seq reveals the DNA regulatory programs of ccRCC at the single-cell level.

Metadherin Promotes the Development of Bladder Cancer by Enhancing Cell Division.

Background: Bladder cancer (BLCA) is a malignant tumor occurring in bladder mucosa. Metadherin (MTDH) has been implicated in tumor progression; however, its molecular biological mechanisms in BLCA remain unclear. Materials and Methods: Cell functions were tested after BLCA cells were transfected by both short hairpin RNAs and small interfering RNAs to silence MTDH. Furthermore, in-house RNA sequencing (RNA-seq) was performed with T24 cells after the knockdown of MTDH. In addition, MTDH-related pathways were explored. Finally, MTDH mRNA and protein expression levels were examined using multiple detection methods in BLCA tissues. Results: MTDH knockdown could largely inhibit cell proliferation, viability, and migration and induce apoptosis of BLCA cells. In-house RNA-seq showed that MTDH knockdown led to extracellular matrix organization and cell division. The integrated analysis showed that the comprehensive expression of MTDH at the mRNA level was 0.47 and that at the protein level was 0.54, based on 11 platforms, including 1485 BLCA and 180 non-BLCA samples. Conclusions: MTDH promotes the growth of BLCA cells through the pathway of cell division. This study provides new directions and biomarkers for future treatment.

Single-Cell RNA Sequencing of Metastatic Testicular Seminoma Reveals the Cellular and Molecular Characteristics of Metastatic Cell Lineage.

Background: Testicular cancer is the most common solid malignancy in young men. Given the many histological classifications of testicular tumors, seminoma is one of the most treatable cancers. The survival rate in early-stage disease was more than 90%. Thus, seminoma at the cellular and molecular levels, especially at the single-cell level, is worth studying. Methods: We performed a single-cell RNA sequencing (scRNA-seq) study on a patient who was diagnosed with testicular seminoma with lymph node metastasis. This study presented tumor tissue, PBMC, pelvic and renal hilus lymph node in a total of 18,206 high-quality single-cell transcriptome information. The characteristics of metastatic cell lineage were revealed by the comparison between different tumor cell subtypes at the scRNA level. Results: A single-cell map of testicular seminoma with lymph node metastasis was constructed by scRNA-seq. We discovered the gene expression characteristics of the tumor cells in testicular seminoma, especially metastatic tumor cells. KRT8 and KRT18 were commonly expressed in the three tumor cell subtypes. However, TCF7L1, SCG3 and SV2C were the specifically expressed genes of tumor cell subtypes in primary tumor sites. Some molecular markers specifically expressed by the metastatic cell lineage, such as POU5F1, were identified. Conclusions: We revealed the molecular characteristics of testicular seminoma at the single-cell level, especially the metastatic tumor cells. This study could provide new insights into the diagnosis and treatment of testicular seminoma.

Decreased expression of transcription factor Homeobox A11 and its potential target genes in bladder cancer.

Bladder cancer (BC) ranks as the ninth most commonly diagnosed cancer worldwide. The presence of a transcription factor (TF) has been uncovered as a significant contributor to the pathophysiological changes of cancers. In present study, we elucidated the expression and clinical significance of Homeobox A11 (HOXA11) in BC for the first time, and originally investigated HOXA11 as a TF. Employing in-house immunohistochemistry (IHC), we incorporated 137 BC and 34 non-BC cases to detect the expression of HOXA11 protein in BC tissues. HOXA11-related RNA-sequencing (RNA-seq) expression and RNA microarrays were collected from public databases, the "sva" and "limma" R packages were implemented to integrate and normalize the RNA-seq data and microarrays separately. Integration expression was carried out to further evaluate the HOXA11 expression by utilizing the standard mean difference (SMD). The expression level of HOXA11 in various BC cell lines was also evaluated. We further systematically analyzed the downstream target genes of HOXA11 in BC by utilizing Chromatin Immunoprecipitation Sequencing (ChIP-seq) profiles, differentially expressed genes (DEGs), and HOXA11-related genes. Modification of histone marks on the promoter region of target genes were also discovered by histone ChIP-seq data. Results of the IHC and RNA-seq revealed the protein and mRNA expression of HOXA11 was significantly decreased in BC tissues compared to non-BC tissues (2.98 ± 1.48 vs. 8.23 ± 2.64; 6.87 ± 1.54 vs. 8.38 ± 1.42). Five platforms significantly revealed the down-regulation of HOXA11 expression in BC (GPL96, GPL570, GPL6102, GPL6884, and GPL13497). A similar decreased trend was discovered in BC tissues in expression integration with the incorporated SMD reaching -0.843 (-1.362 ~ -0.325, p = 0.001) and -1.051 (-1.674 ~ -0.428, p = 0.001). Expression of HOXA11 was down-regulated in most of the BC cell lines. COL1A1 was considered as a final HOXA11 target gene and positively related to HOXA11 with the correlation coefficient as 0.584 (95% CI: 0.371-0.739, p < 0.001). HOXA11 regulates COL1A1 expression in BC via H3K27ac modification. The expression of COL1A1 was down-regulated with the SMD reached -0.312 (p < 0.001). In conclusion, HOXA11 expression is markedly decreased and might promote the transcription of COL1A1 to inhibit BC.

Single-cell transcriptomics reveals cell type diversity of human prostate.

Extensive studies have been performed to describe the phenotypic changes occurring during malignant transformation of the prostate. However, the cell types and associated changes that contribute to the development of prostate diseases and cancer remain elusive, largely due to the heterogeneous composition of prostatic tissues. Here, we conduct a comprehensive evaluation of four human prostate tissues by single-cell RNA sequencing (scRNA-seq) to analyze their cellular compositions. We identify 18 clusters of cell types, each with distinct gene expression profiles and unique features; of these, one cluster of epithelial cells (Ep) is found to be associated with immune function. In addition, we characterize a special cluster of fibroblasts and aberrant signaling changes associated with prostate cancer (PCa). Moreover, we provide insights into the epithelial changes that occur during the cellular senescence and aging. These results expand our understanding of the unique functional associations between the diverse prostatic cell types and the contributions of specific cell clusters to the malignant transformation of prostate tissues and PCa development.

Single-Cell RNA Sequencing in Multiple Pathologic Types of Renal Cell Carcinoma Revealed Novel Potential Tumor-Specific Markers.

BACKGROUND: Renal cell carcinoma (RCC) is the most common type of kidney cancer. Studying the pathogenesis of RCC is particularly important, because it could provide a direct guide for clinical treatment. Given that tumor heterogeneity is probably reflected at the mRNA level, the study of mRNA in RCC may reveal some potential tumor-specific markers, especially single-cell RNA sequencing (scRNA-seq). METHODS: We performed an exploratory study on three pathological types of RCC with a small sample size. This study presented clear-cell RCC (ccRCC), type 2 pRCC, and chRCC in a total of 30,263 high-quality single-cell transcriptome information from three pathological types of RCC. In addition, scRNA-seq was performed on normal kidneys. Tumor characteristics were well identified by the comparison between different pathological types of RCC and normal kidneys at the scRNA level. RESULTS: Some new tumor-specific markers for different pathologic types of RCC, such as SPOCK1, PTGIS, REG1A, CP and SPAG4 were identified and validated. We also discovered that NDUFA4L2 both highly expressed in tumor cells of ccRCC and type 2 pRCC. The presence of two different types of endothelial cells in ccRCC and type 2 pRCC was also identified and verified. An endothelial cell in ccRCC may be associated with fibroblasts and significantly expressed fibroblast markers, such as POSTN and COL3A1. At last, by applying scRNA-seq results, the activation of drug target pathways and sensitivity to drug responses was predicted in different pathological types of RCC. CONCLUSIONS: Taken together, these findings considerably enriched the single-cell transcriptomic information for RCC, thereby providing new insights into the diagnosis and treatment of RCC.

Single-Cell RNA-seq Identification of the Cellular Molecular Characteristics of Sporadic Bilateral Clear Cell Renal Cell Carcinoma.

Bilateral renal cell carcinoma (RCC) is a rare disease that can be classified as either familial or sporadic. Studying the cellular molecular characteristics of sporadic bilateral RCC is important to provide guidance for clinical treatment. Cellular molecular characteristics can be expressed at the RNA level, especially at the single-cell degree. Single-cell RNA sequencing (scRNA-seq) was performed on bilateral clear cell RCC (ccRCC). A total of 3,575 and 3,568 high-quality single-cell transcriptome data were captured from the left and right tumour tissues, respectively. Gene characteristics were identified by comparing left and right tumours at the scRNA level. The complex cellular environment of bilateral ccRCC was presented by using scRNA-seq. Single-cell transcriptomic analysis revealed high similarity in gene expression among most of the cell types of bilateral RCCs but significant differences in gene expression among different site tumour cells. Additionally, the potential biological function of different tumour cell types was determined by gene ontology (GO) analysis. The transcriptome characteristics of tumour tissues in different locations at the single-cell transcriptome level were revealed through the scRNA-seq of bilateral sporadic ccRCC. This work provides new insights into the diagnosis and treatment of bilateral RCC.

Novel Blood Indicators of Progression and Prognosis in Renal Cell Carcinoma: Red Cell Distribution Width-to-Lymphocyte Ratio and Albumin-to-Fibrinogen Ratio.

OBJECTIVE: To evaluate the value of preoperative red cell distribution width-to-lymphocyte ratio (RLR) and albumin-to-fibrinogen ratio (AFR) to the prognosis of patients after renal cell carcinoma (RCC). METHODS: From 2012 to 2016, a total of 273 RCC patients underwent radical nephrectomy or partial nephrectomy. This study retrospectively analyzed this group of patients. X-tile software was used to determine the optimal values of RLR and AFR in the peripheral blood. The nomogram constructed with independent factors was used to predict the survival outcome of the patients after RCC. RESULTS: The RLR of the RCC group was higher than that of the normal control group (P=0.002), whereas the AFR of the RCC group was lower than that of the normal control group (P < 0.001). RLR and AFR are related to tumour type and tumour-node-metastasis (TNM) stage (P < 0.05 for all). Cox regression analysis showed that the independent prognostic factors affecting overall survival and disease-free survival in the RCC group were symptom, tumour type, TNM stage, Fuhrman grade, RLR, and AFR (P < 0.05 for all). The nomogram constructed by multiple factors has better predictive power for patients after RCC. CONCLUSION: Preoperative RLR and AFR can serve as potential biomarkers to predict the prognosis of postoperative RCC patients and improve the predictability of patient recurrence and survival.

Downregulation of miRNA-205 Expression and Biological Mechanism in Prostate Cancer Tumorigenesis and Bone Metastasis.

BACKGROUND: The expression and mechanism of microRNA-205 (miRNA-205) in prostate cancer (PCa) and its bone metastasis remain controversial. MATERIALS AND METHODS: The expression and discriminating capability of miRNA-205 were assessed by drawing a forest plot and a summarized receiver operating characteristic (SROC) curve, using data available from 27 miRNA-array and miRNA-sequencing datasets. The miRNA-205 target genes were acquired from online prediction tools, differentially upregulated genes in PCa, and differentially expressed genes (DEGs) after miRNA-205 transfection into PCa cell lines. Functional enrichment analysis was conducted to explore the biological mechanism of miRNA-205 targets. Immunohistochemistry (IHC) was applied to verify the protein level of the hub gene. RESULTS: The expression of miRNA-205 in the PCa group (1,461 samples) was significantly lower than that in the noncancer group (510 samples), and the downregulation of miRNA-205 showed excellent sensitivity and specificity in differentiating between the two groups. In bone metastatic PCa, the miRNA-205 level was further reduced than in nonbone metastatic PCa, and it showed a good capability in distinguishing between the two groups. In total, 153 miRNA-205 targets were screened through the three aforementioned methods. Based on the results of functional enrichment analysis, the targets of miRNA-205 were mainly enriched during chromosome segregation and phospholipid-translocating ATPase activity and in the spindle microtubule and the p53 signaling pathway. CDK1 had the highest connectivity in the PPI network analysis and was screened as one of the hub genes. A statistically significant negative correlation between miRNA-205 and CDK1 was observed. The expression of CDK1 in PCa samples was pronouncedly upregulated in terms of both the mRNA level and the protein level when compared with noncancer samples. CONCLUSION: miRNA-205 may play a vital role in PCa tumorigenesis and bone metastasis by targeting CDK1.

Small Nucleolar RNAs (snoRNAs)-Based Risk Score Classifier Predicts Overall Survival in Bladder Carcinoma.

BACKGROUND Bladder carcinoma (BLCA) is a leading cause of cancer-related deaths worldwide. The aim of this work was to develop an accurate stratification in predicting the prognosis and directing the treatment of BLCA patients based on small nucleolar RNAs (snoRNAs). MATERIAL AND METHODS Expression profiles of snoRNAs were downloaded from the SNORic database. The expression profiles and clinical outcomes of BLCA patients were analyzed. Survival-associated snoRNAs were identified and used to develop a novel risk score classifier. Genes in the whole genome that were significantly correlated with the included prognostic snoRNAs were used for functional enrichment analysis. RESULTS The results showed that age, American Joint Committee on Cancer (AJCC) stage, and tumor status were significantly correlated with overall survival (OS) of BLCA patients. We selected 12 survival-associated snoRNAs to build a prognostic signature. Patients were separated into high- and low-risk groups based on the median value of the risk score. Patients in the high-risk group and low-risk group have distinct clinical outcomes. The AJCC TNM stage showed moderate utility as a prognostic indicator for clinical outcome prediction. Then, clinical parameters and risk scores were entered in multivariate Cox analysis. Notably, the prognostic signature remained an independent significant prognostic risk factor. The pathway analysis suggested that these genes were enriched in several types of cancer and "Focal adhesion" pathways. CONCLUSIONS The prognostic signature defined by expression profiles of 12 survival-associated snoRNAs appears to be an excellent predictor of the clinical outcome of BLCA patients.

Genome-wide Analysis of the Alternative Splicing Profiles Revealed Novel Prognostic Index for Kidney Renal Cell Clear Cell Carcinoma.

Alternative splicing (AS) is a major mechanism that greatly enhanced the diversity of proteome. Mounting evidence demonstrated that aberration of AS are important steps for the initiation and progression of human cancers. Here, we comprehensively investigated the association between whole landscape of AS profiles and the survival outcome of renal cell carcinoma (RCC) patients using RNA-seq data from TCGA SpliceSeq. Because of the limited number size of deaths in kidney chromophobe renal cell carcinoma (KICH) and papillary renal cell carcinoma (KIRP) TCGA cohorts, we only conducted survival analysis in kidney clear renal cell carcinoma (KIRC). We further constructed prognostic index (PI) based on prognosis-related AS events and built correlation network for splicing factors and prognosis-related AS events. According to the results, a total of 5351 AS events in 3522 genes were significantly correlated with the overall survival (OS) of kidney clear cell renal cell carcinoma (KIRC) patients. Seven of the PI models exhibited preferable prognosis-predicting capacity for KIRC with PI-ALL reaching the highest area under curve value of 0.875. The splicing regulatory network between splicing factors and prognosis-related AS events depicted a tangled web of relationships between them. One of the splicing factors: KHDRBS3 was validated by immunohistochemistry to be down-regulated in KIRC tissues. In conclusion, the powerful efficiency of risk stratification of PI models indicated the potential of AS signature as promising prognostic markers for KIRC and the splicing regulation network provided possible genetic mechanism of KIRC.

Development and validation of an immune prognostic classifier for clear cell renal cell carcinoma.

BACKGROUND: Tumor-infiltrating immune cells are indispensable to the progression and prognosis of clear cell renal cell carcinoma (ccRCC). OBJECTIVE: The aim of this study was to explore the clinical implications of immune cell infiltrates in ccRCC. METHODS: The Cancer Genome Atlas (TCGA) database (N= 515) and E-MTAB-1980 cohort of patients (N= 101) were adopted to estimate the prognostic value of immune cell infiltration. Twenty-four types of immune cells were evaluated using single-sample gene set enrichment analysis. Cox regression analyses were conducted to develop an immune risk score. RESULTS: Survival analyses revealed that 13 genes significantly associated with the overall survival (OS). Furthermore, multivariate Cox analysis identified an immune risk score on the basis of mast cells, natural killer CD56bright cells, T helper 17 (Th17) cells, and Th2 cells. The immune risk score was associated with OS, with hazard ratios of 2.72 (95% CI 2.17-3.40) and 3.24 (95% CI 1.64-6.44) in TCGA and E-MTAB-1980 datasets, respectively. This immune risk score was significantly correlated with some immunotherapy-related biomarkers. CONCLUSIONS: We profiled a prognostic signature and established an immune risk score model for ccRCC, which could provide novel predictive markers for patients with ccRCC and an indicator for immunotherapy response measurement.

A radiogenomics signature for predicting the clinical outcome of bladder urothelial carcinoma.

OBJECTIVES: To determine the integrative value of contrast-enhanced computed tomography (CECT), transcriptomics data and clinicopathological data for predicting the survival of bladder urothelial carcinoma (BLCA) patients. METHODS: RNA sequencing data, radiomics features and clinical parameters of 62 BLCA patients were included in the study. Then, prognostic signatures based on radiomics features and gene expression profile were constructed by using least absolute shrinkage and selection operator (LASSO) Cox analysis. A multi-omics nomogram was developed by integrating radiomics, transcriptomics and clinicopathological data. More importantly, radiomics risk score-related genes were identified via weighted correlation network analysis and submitted to functional enrichment analysis. RESULTS: The radiomics and transcriptomics signatures significantly stratified BLCA patients into high- and low-risk groups in terms of the progression-free interval (PFI). The two risk models remained independent prognostic factors in multivariate analyses after adjusting for clinical parameters. A nomogram was developed and showed an excellent predictive ability for the PFI in BLCA patients. Functional enrichment analysis suggested that the radiomics signature we developed could reflect the angiogenesis status of BLCA patients. CONCLUSIONS: The integrative nomogram incorporated CECT radiomics, transcriptomics and clinical features improved the PFI prediction in BLCA patients and is a feasible and practical reference for oncological precision medicine. KEY POINTS: • Our radiomics and transcriptomics models are proved robust for survival prediction in bladder urothelial carcinoma patients. • A multi-omics nomogram model which integrates radiomics, transcriptomics and clinical features for prediction of progression-free interval in bladder urothelial carcinoma is established. • Molecular functional enrichment analysis is used to reveal the potential molecular function of radiomics signature.

Identification and validation of an individualized autophagy-clinical prognostic index in bladder cancer patients.

Purpose: Autophagy is a major catabolic system by which eukaryotic cells undergo self-degradation of damaged, defective, or unwanted intracellular components. An abnormal autophagic level is implicated in the pathogenesis of multiple diseases, including cancers. The aim of this study is to explore the prognostic value of autophagy in bladder cancer (BC), which is a major cause of cancer-related death globally. Patients and methods: First, 27 differentially expressed autophagy-related genes (ARGs) were identified in BC patients based on The Cancer Genome Atlas (TCGA) database. Functional enrichment analyses hinted that autophagy may act in a tumor-suppressive role in the initiation of BC. Then, the Cox proportional hazard regression model were employed to identify three key prognostic ARGs (JUN, MYC, and ITGA3), which were related with overall survival (OS) significantly in BC. The three genes represented important clinical significance and prognostic value in BC. Then a prognostic index (PI) was constructed. Results: The PI was constructed based on the three genes, and significantly stratified BC patients into high- and low-risk groups in terms of OS (HR=1.610, 95% CI=1.200-2.160, P=0.002). PI remained as an independent prognostic factor in multivariate analyses (HR=2.355, 95% CI=1.483-3.739, P<0.001). When integrated with clinical characteristics of age and stage, an autophagy-clinical prognostic index (ACPI) was finally validated, which had improved performance in predicting OS of BC patients (HR=2.669, 95% CI=1.986-3.587, P<0.001). The ACPI was confirmed in datasets of GSE13507 (HR=7.389, 95% CI=3.645-14.980, P<0.001) and GSE31684 (HR=1.665, 95% CI=0.872-3.179, P=0.122). Conclusion: This study provides a potential prognostic signature for predicting prognosis of BC patients and molecular insights of autophagy in BC.

The underlying molecular mechanism and potential drugs for treatment in papillary renal cell carcinoma: A study based on TCGA and Cmap datasets.

Papillary renal cell carcinoma (PRCC) accounts for 15­20% of all kidney neoplasms and continually attracts attention due to the increase in the incidents in which it occurs. The molecular mechanism of PRCC remains unclear and the efficacy of drugs that treat PRCC lacks sufficient evidence in clinical trials. Therefore, it is necessary to investigate the underlying mechanism in the development of PRCC and identify additional potential anti­PRCC drugs for its treatment. The differently expressed genes (DEGs) of PRCC were identified, followed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses for functional annotation. Then, potential drugs for PRCC treatment were predicted by Connectivity Map (Cmap) based on DEGs. Furthermore, the latent function of query drugs in PRCC was explored by integrating drug­target, drug­pathway and drug­protein interactions. In total, 627 genes were screened as DEGs, and these DEGs were annotated using KEGG pathway analyses and were clearly associated with the complement and coagulation cascades, amongst others. Then, 60 candidate drugs, as predicted based on DEGs, were obtained from the Cmap database. Vorinostat was considered as the most promising drug for detailed discussion. Following protein­protein interaction (PPI) analysis and molecular docking, vorinostat was observed to interact with C3 and ANXN1 proteins, which are the upregulated hub genes and may serve as oncologic therapeutic targets in PRCC. Among the top 20 metabolic pathways, several significant pathways, such as complement and coagulation cascades and cell adhesion molecules, may greatly contribute to the development and progression of PRCC. Following the performance of the PPI network and molecular docking tests, vorinostat exhibited a considerable and promising application in PRCC treatment by targeting C3 and ANXN1.

Clinical significance and effect of MTDH/AEG-1 in bladder urothelial cancer: a study based on immunohistochemistry, RNA-seq, and in vitro verification.

BACKGROUND: Overexpression of metadherin/astrocyte elevated gene-1 (MTDH/AEG-1) has been implicated in various cancers. However, the clinical significance and the potential biological functions of MTDH/AEG-1 in bladder urothelial carcinoma (BUC) are not established. METHODS: In this study, the expression of MTDH/AEG-1in BUC was measured using the Cancer Genome Atlas (TCGA) database and immunohistochemistry, together with a meta-analysis, to investigate the expression and diagnostic value of MTDH/AEG-1. The possible association between MTDH/AEG-1 expression and the viability, proliferation, and apoptosis in BUC cell lines (T24, HT1376, and RT4) was also assessed in vitro by viability, MTS, colony formation, and caspase-3/7 assays, as well as Hoechst 33342 and propidium iodide (PI) double staining. RESULTS: MTDH/AEG-1 expression was significantly higher in BUC tissues than in normal bladder tissues, according to the TCGA and immunohistochemistry results, and these findings were verified by the meta-analysis. Functional knockdown of MTDH/AEG-1 suppressed BUC cell growth and induced apoptosis. Bioinformatics analyses indicated an involvement of MTDH/AEG-1 in several processes, including RNA binding, protein transport, intracellular transport, and the insulin signaling pathway. CONCLUSION: We hypothesize that MTDH/AEG-1 could play essential roles in BUC, especially in cell growth and apoptosis, via the insulin signaling pathway."

Exploration of the diagnostic value and molecular mechanism of miR­1 in prostate cancer: A study based on meta­analyses and bioinformatics.

Prostate cancer (PCa) remains a principal issue to be addressed in male cancer­associated mortality. Therefore, the present study aimed to examine the clinical value and associated molecular mechanism of microRNA (miR)­1 in PCa. A meta­analysis was conducted to evaluate the diagnosis of miR­1 in PCa via Gene Expression Omnibus and ArrayExpress datasets, The Cancer Genome Atlas miR­1 expression data and published literature. It was identified that expression of miR­1 was significantly downregulated in PCa. Decreased miR­1 expression possessed moderate diagnostic value, with area under the curve, sensitivity, specificity and odds ratio values at 0.73, 0.77, 0.57 and 4.60, respectively. Using bioinformatics methods, it was revealed that a number of pathways, including the 'androgen receptor signaling pathway', 'androgen receptor activity', 'transcription factor binding' and 'protein processing in the endoplasmic reticulum', were important in PCa. A total of seven hub genes, including phosphoribosylaminoimidazole carboxylase and phosphoribosylaminoimidazolesuccinocarboxamide synthase (PAICS), cadherin 1 (CDH1), SRC proto­oncogene, non­receptor tyrosine kinase, twist family bHLH transcription factor 1 (TWIST1), ZW10 interacting kinetochore protein (ZWINT), PCNA clamp associated factor (KIAA0101) and androgen receptor, among which, five (PAICS, CDH1, TWIST1, ZWINT and KIAA0101) were significantly upregulated and negatively correlated with miR­1, were identified as key miR­1 target genes in PCa. Additionally, it was investigated whether miR­1 and its hub genes were associated with clinical features, including age, tumor status, residual tumor, lymph node metastasis, pathological T stage and prostate specific antigen level. Collectively the results suggest that miR­1 may be involved in the progression of PCa, and consequently be a promising diagnostic marker. The 'androgen receptor signaling pathway', 'androgen receptor activity', 'transcription factor binding' and 'protein processing in the endoplasmic reticulum' may be crucial interactive pathways in PCa. Furthermore, PAICS, CDH1, TWIST1, ZWINT and KIAA0101 may serve as crucial miR­1 target genes in PCa.

Expression of microRNA-99a-3p in Prostate Cancer Based on Bioinformatics Data and Meta-Analysis of a Literature Review of 965 Cases.

BACKGROUND microRNAs (miRNAs) have a role as biomarkers in human cancer. The aim of this study was to use bioinformatics data, and review of cases identified from the literature, to investigate the role of microRNA-99a-3p (miR-99a-3p) in prostate cancer, including the identification of its target genes and signaling pathways. MATERIAL AND METHODS Meta-analysis from a literature review included 965 cases of prostate cancer. Bioinformatics databases interrogated for miR-99a-3p in prostate cancer included The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and ArrayExpress. Twelve computational predictive algorithms were developed to integrate miR-99a-3p target gene prediction data. Bioinformatics analysis data from Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) network analysis were used investigate the possible pathways and target genes for miR-99a-3p in prostate cancer. RESULTS TCGA data showed that miR-99a was down-regulated in prostate cancer when compared with normal prostate tissue. Receiver-operating characteristic (ROC) curve area under the curve (AUC) for miR-99a-3p was 0.660 (95% CI, 0.587-0.732) or a moderate level of discriminations. Pathway analysis showed that miR-99a-3p was associated with the Wnt and vascular endothelial growth factor (VEGF) signaling pathways. The PPP3CA and HYOU1 genes, selected from the PPI network, were highly expressed in prostate cancer tissue compared with normal prostate tissue, and negatively correlated with the expression of miR-99a-3p. CONCLUSIONS In prostate cancer, miR-99a-3p expression was associated with the Wnt and VEGF signaling pathways, which might inhibit the expression of PPP3CA or HYOU1.