Gene Expression In Bladder Cancer Research Articles

An immune biomarker associated with EMT serves as a predictor for prognosis and drug response in bladder cancer.

Bladder cancer (BLCA), which develops from the upper endometrial of the bladder, is the sixth most prevalent cancer across the globe. WDHD1 (WD repeat and HMG-box DNA binding protein 1 gene) directly affects signaling, the cell cycle, and the development of the cell skeleton. Uncertainty surrounds WDHD1's function in BLCA immunity and prognosis, though. Using weighed gene co-expression network analysis (WGCNA), initially, we first identified 32 risk factors in genes with differential expression for this investigation. Then, using a variety of bioinformatic techniques and experimental validation, we examined the connections between WDHD1 and BLCA expression, clinical pathological traits, WDHD1-related proteins, upper-skin-intermediate conversion (EMT), immune cell immersion, convergence factors, immune markers, and drug sensitivity. The findings demonstrated that we constructed a 32-gene risk-predicting model where WDHD1 was elevated as a representative gene expression in BLCA and related to a range of clinical traits. Furthermore, high WDHD1 expression was a standalone predictor associated with a worse survival rate. The most commonly recruited cells and their evolutionary patterns were highlighted to better comprehend WDHD1's function in cancer. High WDHD1 expression was associated with many aspects of immunology. Finally, the study found that individuals with high expression of WDHD1 were drug-sensitive to four different broad-spectrum anti-cancer drugs. These results describe dynamic changes in the tumor microenvironment in BLCA and provide evidence for the hypothesis that WDHD1 is a novel biomarker of tumor development. WDHD1 may therefore be a useful target for the detection and management of BLCA.

Clinical significance and immune landscape of angiogenesis-related genes in bladder cancer.

Angiogenesis is a major promotor of tumor progression and metastasis. Nevertheless, it is undetermined how angiogenesis-related genes (ARGs) influence bladder cancer. The profiles of bladder cancer gene expression were collected from the TCGA-BLCA cohort. The LASSO regression analysis was used to build an angiogenesis-related signature (ARG_score) with the prognostic ARGs. Verification analyses were conducted across the GSE48075 dataset to demonstrate the robustness of the signature. Differences between the two risk groups based on clinical outcomes, immune landscape, mutation status, chemotherapeutic effectiveness for anticancer drugs, and immunotherapy efficacy were analyzed. A nomogram was developed to improve the clinical efficacy of this predictive tool. The expression levels of model genes in normal bladder epithelial cell lines (SV-HUC-1) and bladder cancer cell lines (T24 and 5637) were detected by qRT-PCR assay. Four angiogenesis-associated gene signature was constructed based on the LASSO regression algorithm. The signature showed independent risk factors of overall survival for bladder cancer, validated using two external survival datasets. Additionally, we built a prognostic nomogram to improve the practicality of the ARG_score. High-risk individuals showed stronger immunocyte infiltration, immune-related functions, elevated expression of immune checkpoints, reduced TIDE score, and higher combined IPS-PD-1 and IPS-CTLA4 scores, suggesting a heightened responsiveness to immune checkpoint inhibitors. Furthermore, patients with low and high risk showed distinct responsiveness to anticancer drugs. The expression levels of 5 model genes (COL5A2, JAG1, MSX1, OLR1, and STC) were significantly increased in bladder cancer cell lines (T24 and 5637) compared with the normal bladder epithelial cell line SV-HUC-1. The model constructed based on ARGs may have wide application in predicting outcomes and therapeutic responses.

Bladder cancer gene expression prediction with explainable algorithms

Bladder cancer gene expression prediction with explainable algorithms

A genome-wide CRISPR screen maps endogenous regulators of PPARG gene expression in bladder cancer

Peroxisome proliferator-activated receptor gamma (PPARγ) is a nuclear receptor central in the regulation of key cellular processes including cell metabolism, tissue differentiation, and regulation of the immune system. PPARγ is required for normal differentiation of the urothelium and is thought to be an essential driver of the luminal subtype of bladder cancer. However, the molecular components that regulate PPARG gene expression in bladder cancer remain unclear. Here, we developed an endogenous PPARG reporter system in luminal bladder cancer cells and performed genome-wide CRISPR knockout screening to identify bona fide regulators of PPARG gene expression. Functional validation of the dataset confirmed GATA3, SPT6, and the cohesin complex components SMC1A, and RAD21, as permissive upstream positive regulators of PPARG gene expression in luminal bladder cancer. In summary, this work provides a resource and biological insights to aid our understanding of PPARG regulation in bladder cancer.

Methylation analysis of histone 4-related gene HIST1H4F and its effect on gene expression in bladder cancer

Recently, aberrant DNA methylation of the HIST1H4F gene (encodes Histone 4 protein) has been shown in many types of cancer, which may serve as a promising biomarker for early cancer diagnosis. However, the correlation between DNA methylation of the HIST1H4F gene and its role in gene expression is unclear in bladder cancer. Therefore, the first objective of this study is to explore the DNA methylation pattern of the HIST1H4F gene and then further elucidate its effects on HIST1H4F mRNA expression in bladder cancer. To this end, the methylation pattern of the HIST1H4F gene was analyzed by pyrosequencing and the effects of the methylation profiles of this gene on HIST1H4F mRNA expression in bladder cancer were examined by qRT-PCR. Sequencing analysis revealed significantly higher methylation frequencies of the HIST1H4F gene in bladder tumor samples compared to normal samples (p < 0,0001). However, when we evaluated the correlations between hypermethylation of HIST1H4F and the clinicopathological parameters (tumor stage, tumor grade, lymph node metastasis, muscle-invasion), no significant difference was found between the groups (p > 0.05). In addition, we examined the role of hypermethylation of the HIST1H4F gene on HIST1H4F mRNA expression. We found that hypermethylation of HIST1H4F in the exon have no effect HIST1H4F mRNA expression in bladder cancer (p > 0.05). We also confirmed our finding in cultured T24 cell line which HIST1H4F gene is hypermethylated. Our results suggest that hypermethylation of the HIST1H4F seems to be a promising early diagnostic biomarker in bladder cancer patients. However, further studies are needed to determine the role of HIST1H4F hypermethylation in tumorigenesis.

Deep learning approach for cancer subtype classification using high-dimensional gene expression data

MotivationStudies have shown that classifying cancer subtypes can provide valuable information for a range of cancer research, from aetiology and tumour biology to prognosis and personalized treatment. Current methods usually adopt gene expression data to perform cancer subtype classification. However, cancer samples are scarce, and the high-dimensional features of their gene expression data are too sparse to allow most methods to achieve desirable classification results.ResultsIn this paper, we propose a deep learning approach by combining a convolutional neural network (CNN) and bidirectional gated recurrent unit (BiGRU): our approach, DCGN, aims to achieve nonlinear dimensionality reduction and learn features to eliminate irrelevant factors in gene expression data. Specifically, DCGN first uses the synthetic minority oversampling technique algorithm to equalize data. The CNN can handle high-dimensional data without stress and extract important local features, and the BiGRU can analyse deep features and retain their important information; the DCGN captures key features by combining both neural networks to overcome the challenges of small sample sizes and sparse, high-dimensional features. In the experiments, we compared the DCGN to seven other cancer subtype classification methods using breast and bladder cancer gene expression datasets. The experimental results show that the DCGN performs better than the other seven methods and can provide more satisfactory classification results.

Core promoter mutation contributes to abnormal gene expression in bladder cancer

BackgroundBladder cancer is one of the most mortal cancers. Bladder cancer has distinct gene expression signature, highlighting altered gene expression plays important roles in bladder cancer etiology. However, the mechanism for how the regulatory disorder causes the altered expression in bladder cancer remains elusive. Core promoter controls transcriptional initiation. We hypothesized that mutation in core promoter abnormality could cause abnormal transcriptional initiation thereby the altered gene expression in bladder cancer.MethodsIn this study, we performed a genome-wide characterization of core promoter mutation in 77 Spanish bladder cancer cases.ResultsWe identified 69 recurrent somatic mutations in 61 core promoters of 62 genes and 28 recurrent germline mutations in 20 core promoters of 21 genes, including TERT, the only gene known with core promoter mutation in bladder cancer, and many oncogenes and tumor suppressors. From the RNA-seq data from bladder cancer, we observed altered expression of the core promoter-mutated genes. We further validated the effects of core promoter mutation on gene expression by using luciferase reporter gene assay. We also identified potential drugs targeting the core promoter-mutated genes.ConclusionsData from our study highlights that core promoter mutation contributes to bladder cancer development through altering gene expression.

PO-1924 Exploring the association between radiomics and gene expression in bladder cancer: a pilot study

PO-1924 Exploring the association between radiomics and gene expression in bladder cancer: a pilot study

SHOX2 promotes migration, invasion and stemness of bladder cancer cells in vitro

To explore the role of human short stature homeobox 2 (SHOX2) in regulating the migration, invasion and stemness of human bladder cancer cells. We analyzed SHOX2 gene expression in bladder cancer and adjacent tissues based on TCGA database. Univariate survival analysis of SHOX2 gene expression in TCGA-BLCA data was performed using GEPIA. The probable function of SHOX2 was predicted using GSEA. Human bladder cancer T24 cell models of SHOX2 knockdown or overexpression were assessed for changes in migration and invasion abilities using wound healing assay and Transwell assay, and their cancer stem cell-like characteristics were evaluated using tumorsphere formation assay and colony formation assay. Western blotting was used to detect the expressions of epithelial mesenchymal transition (EMT) markers Ecadherin and vimentin and the TGF-β signaling network component TβR-I in the cells. SHOX2 expression was significantly higher in bladder cancer tissues than in the adjacent tissues (P < 0.05), especially in paired tissue specimens (P < 0.01), and was negatively correlated with the overall survival of the patients (P < 0.05). SHOX2 gene expression was correlated positively with EMT-related (P < 0.05) and stemness-related gene signatures (P < 0.01). In T24 cells, SHOX2 knockdown significantly suppressed cell migration and invasion, which was significantly enhanced by SHOX2 overexpression (P < 0.01). The cancer stem cell-like characteristics of T24 cells was repressed by SHOX2 knockdown but significantly enhanced by SHOX2 overexpression (P < 0.01). SHOX2 knockdown induced morphological changes of the cells into epithelioid cells, whereas SHOX2 overexpression induced a mesenchymal morphology of the cells. SHOX2 knockdown increased E-cadherin expression and decreased vimentin and TβR-I expression, while SHOX2 overexpression increased the expressions of vimentin and TβR-I in the cells. SHOX2 promotes the migration, invasion and stemness of human bladder cancer cells possibly by regulating EMT via the TGF-β signaling pathway.

Analysis of Gene Expression in Bladder Cancer: Possible Involvement of Mitosis and Complement and Coagulation Cascades Signaling Pathway.

This study focused on identifying bladder cancer (BC)-associated genes, transcription factors (TFs), and microRNAs (miRNAs). Two microarray data sets GSE37815 and GSE40355 were utilized to screen common differentially expressed genes (DEGs) associated with BC. Then, functional enrichment analysis was performed for elucidating the involved functions of DEGs. Subsequently, the protein-protein interaction (PPI) network and submodule of PPI network were analyzed. Finally, the regulation relationships of TF-DEGs and miRNA-DEGs were obtained to construct miRNA-target-TF regulatory network. DEGs were identified across BC and normal bladder tissues samples. Functional enrichment analysis results showed that most upregulated DEGs were closely associated with the Gene Ontology function of "mitotic spindle assembly checkpoint" and pathway of "Cell cycle," whereas most downregulated DEGs were significantly associated with "Complement and coagulation cascades" pathway (e.g., A2M and F13A1) and "Ras signaling pathway" (e.g., GNG11). DEGs such as F13A1 and A2M were highlighted in the PPI network and Submodule 1. In addition, three centromere-associated CENPK, CENPF, and CENPO were enriched in Submodule 2. Moreover, miR-519d had high degree in the regulatory network and CENPO was predicted to be one target of miR-519d. The upregulated CENPK, CENPF, and CENPO, and downregulated A2M, F13A1, and GNG11 might contribute to the progression of BC. In addition, the downregulated miR-519d might lead to the development of BC by upregulating the expression of CENPO. However, future investigation of those findings should be needed.

Abstract 4343: Molecular identification of bladder cancer gene expression subtypes

Abstract Bladder urothelial carcinoma (BLCA) comprises two main types: non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC). To discovery the subtype of BLCA, we used gene expression data from 165 patient cohort (102 NMIBC, 63 MIBC). Three other gene expression data sets including the Sweden 1 cohort (97 NMIBC, 45 MIBC), the Sweden 2 cohort (213 NMIBC, 93 MIBC), and 408 MIBC sample from The Cancer Genome Atlas (TCGA) and 476 sample (460 NMIBC, 16 MIBC, the multicenter European UROMOL consortium). For selection of subtype-specific gene set, we used significance analysis of microarrays (SAM). Then, subtype-specific genes were trained by prediction analysis for microarrays (PAM) to build a classifier. Clustering analyses were applied to gene expression data of training set identified four molecular subtypes with different clinical outcomes. The majority of patients with class 1 were the low-grade NMIBC and associated with the prognosis of NMIBC, for cancer-specific survival (P =0.003, log-rank test). Class 2 patients, characterized by FGFR3 overexpression and downregulated immune pathways, showed the intermediate prognosis. Class 3 tumors showed high expression of cell-cycle genes and downregulated notch signaling pathway. Furthermore, high-grade NMIBC were predominantly found in class 3, indicating that NMIBC patients classified as class 3 would be more likely to progress to MIBC. Class 4 tumors, mainly composed of MIBC, were characterized by high expression of immune-related genes which is positively associated with potential response to immunotherapy. We further validated the BLCA subtypes in four independent data sets (n = 1,471), including the RNA-seq data set, by applying the 786-gene classifier onto the data sets. As expected, the progression rate of NMIBC patients classified as class 3 was significantly increased compared with other three classes in the RNA-seq data set (P &amp;lt; 0.001, log-rank test). Citation Format: In-Sun Chu, Bic-Na Song, Sun-Hee Leem. Molecular identification of bladder cancer gene expression subtypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4343.

Bladder cancer gene expression subtypes (60 gene signature) to define prognosis, differential immune response, and biomarker associations.

4538Background: Gene expression subtypes provide valuable insight into tumor biology and potential therapeutic response. Differential expression of immune infiltrating cells and biomarkers, tumor m...

MP06-03 RACE BASED DISPARITIES IN GENE EXPRESSION AND MUTATIONS IN BLADDER CANCER

You have accessJournal of UrologyBladder Cancer: Epidemiology & Evaluation I1 Apr 2018MP06-03 RACE BASED DISPARITIES IN GENE EXPRESSION AND MUTATIONS IN BLADDER CANCER Kalen Rimar, Joshua Meeks, Sarah Psutka, and Edward Schaeffer Kalen RimarKalen Rimar More articles by this author , Joshua MeeksJoshua Meeks More articles by this author , Sarah PsutkaSarah Psutka More articles by this author , and Edward SchaefferEdward Schaeffer More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2018.02.195AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES African Americans (AA) with urothelial carcinoma (UC) of the bladder have been shown to have worse cancer-specific (CSS) and overall survival (OS). Though several factors including socioeconomic status, access to care, and advanced stage at presentation have been proposed, the cause of this disparity remains undefined. Our objective was to compare bladder cancer gene expression and mutations between AA and Caucasian patients to assess whether the observed disparities in oncologic outcomes could be explained by associated mutational differences. METHODS Using the Bladder/Urothelial Carcinoma Cancer Genome Atlas (BC-TCGA, Provisional) we compared mutation type, frequency, signature, and gene expression between AA and Caucasian patients. We also compared differentially expressed genes according to race across all TCGA provisional cancer datasets that contained a minimum of 10 AA and 10 Caucasian patients per arm (19 of 33). RESULTS We identified 23 AA and 323 non-AA patients in the UC-TCGA dataset with available whole genome and RNA sequencing. There was no significant difference in the total mutation load between Caucasian and AA (range = 1 to 4472 variants/genome, n = 316, median = 240.5 vs. range = 82 to 562 variants/genome; n = 22, median=225.5, p=0.228). The majority of DNA substitution mutations in both Caucasian and AA patients were C->T, and there was no significant difference in frequency (p=0.33). There were no significant differences in Catalogue of Somatic Mutations in Cancer (COSMIC) signatures between the two groups (p=0.3). There was no significant difference in mutation frequency of known UC driver genes (TP53, MLL4, KDM6A, MLL3, PIK3CA, RB1, EP300, ERBB2) by race. Yet, we were able to identify 14 genes with significant differential expression according to race of which HIST1H2BD, L1TD1, and LRRC37A2 were associated with inferior OS (p<0.005, p=0.03, p=0.02). Notably, analyses of TCGA datasets revealed a conserved panel of genes differentially expressed by race across multiple cancers types involved in cell division and nucleosome function. CONCLUSIONS AA and Caucasians with UC have similar mutation type, frequency, and signature. However several differentially expressed genes within the UC were observed between AA and Caucasians and these differences remain consistent across many cancer types within the TCGA suggesting epigenetic regulation. Some of these gene expression differences may be independent of cancer. Nevertheless, the extent to which this differential gene expression may predispose to variable disease outcomes across race warrants further study. © 2018FiguresReferencesRelatedDetails Volume 199Issue 4SApril 2018Page: e52-e53 Advertisement Copyright & Permissions© 2018MetricsAuthor Information Kalen Rimar More articles by this author Joshua Meeks More articles by this author Sarah Psutka More articles by this author Edward Schaeffer More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

Functional analysis of gene expression profiling-based prediction in bladder cancer.

The present study aimed to analyze the modification of gene expression in bladder cancer (BC) by identifying significant differentially expressed genes (DEGs) and functionally assess them using bioinformatics analysis. To achieve this, two microarray datasets, GSE24152 (which included 10 fresh tumor tissue samples from urothelial bladder carcinoma patients and 7 benign mucosa samples from the bladder), and GSE42089 (which included 10 tissues samples from urothelial cell carcinoma patients and 8 tissues samples from the normal bladder), were downloaded from the Gene Expression Omnibus database for further analysis. Differentially expressed genes (DEGs) were screened between benign the mucosa and control groups in GSE24152 and GSE42089 datasets. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analysis were performed on overlapping DEGs identified in GSE24152 and GSE42089. Protein-protein interaction (PPI) networks and sub-networks were then constructed to identify key genes and main pathways. GO terms analysis was also performed for the selected clusters. In total, 1,325 DEGs in GSE24152 and 647 DEGs in GSE42089 were screened, in which 619 common DEGs were identified. The DEGs were mainly enriched in pathways and GO terms associated with mitotic and chromosome assembly, including nucleosome assembly, spindle checkpoint and DNA replication. In the interaction network, progesterone receptor (PGR), MAF bZIP transcription factor G (MAFG), cell division cycle 6 (CDC6) and members of the minichromosome maintenance family (MCMs) were identified as key genes. Histones were also considered to be significant factors in BC. Nucleosome assembly and sequence-specific DNA binding were the most significant clustered GO terms. In conclusion, the DEGs, including PGR, MAFG, CDC6 and MCMs, and those encoding the core histone family were closely associated with the development of BC via pathways associated with mitotic and chromosome assembly.

HOXD-AS1/miR-130a sponge regulates glioma development by targeting E2F8.

Glioma development is an extremely complex process with changes occurring in numerous genes. HOXD antisense growth-associated long noncoding RNA (HOXD-AS1), an important long noncoding RNA (lncRNA), is known to regulate metastasis-related gene expression in bladder cancer, ovarian cancer and neuroblastoma. Here, we elucidated the function and possible molecular mechanisms of lncRNA HOXD-AS1 in human glioma cells. Our results proved that HOXD-AS1 expression was upregulated in glioma tissues and in glioma cell lines. HOXD-AS1 overexpression promoted cell migration and invasion in vitro, whereas knockdown of HOXD-AS1 expression repressed these cellular processes. Mechanistic studies further revealed that HOXD-AS1 could compete with the transcription factor E2F8 to bind with miR-130a, thus affecting E2F8 expression. Additionally, reciprocal repression was observed between HOXD-AS1 and miR-130a, and miR-130a mediated the tumor-suppressive effects of HOXD-AS1 knockdown. Taken together, these results provide a comprehensive analysis of the role of HOXD-AS1 in glioma cells and offer important clues to understand the key roles of competing endogenous RNA (ceRNA) mechanisms in human glioma.

Development and Application of a Microfluidics-Based Panel in the Basal/Luminal Transcriptional Characterization of Archival Bladder Cancers.

In the age of personalized medicine stratifying tumors into molecularly defined subtypes associated with distinctive clinical behaviors and predictable responses to therapies holds tremendous value. Towards this end, we developed a custom microfluidics-based bladder cancer gene expression panel for characterization of archival clinical samples. In silico analysis indicated that the content of our panel was capable of accurately segregating bladder cancers from several public datasets into the clinically relevant basal and luminal subtypes. On a technical level, our bladder cancer panel yielded robust and reproducible results when analyzing formalin-fixed, paraffin-embedded (FFPE) tissues. We applied our panel in the analysis of a novel set of 204 FFPE samples that included non-muscle invasive bladder cancers (NMIBCs), muscle invasive disease (MIBCs), and bladder cancer metastases (METs). We found NMIBCs to be mostly luminal-like, MIBCs to include both luminal- and basal-like types, and METs to be predominantly of a basal-like transcriptional profile. Mutational analysis confirmed the expected enrichment of FGFR3 mutations in luminal samples, and, consistently, FGFR3 IHC showed high protein expression levels of the receptor in these tumors. Our bladder cancer panel enables basal/luminal characterization of FFPE tissues and with further development could be used for stratification of bladder cancer samples in the clinic.

An online tool for evaluating diagnostic and prognostic gene expression biomarkers in bladder cancer.

BackgroundIn the past ~15 years, the identification of diagnostic and prognostic biomarkers from gene expression data has increased our understanding of cancer biology and has led to advances in the personalized treatment of many cancers. A diagnostic biomarker is indicative of tumor status such as tumor stage, while a prognostic biomarker is indicative of disease outcome. Despite these advances, however, there are no clinically approved biomarkers for the treatment of bladder cancer, which is the fourth most common cancer in males in the United States and one of the most expensive cancers to treat. Although gene expression profiles of bladder cancer patients are publicly available, biomarker identification requires bioinformatics expertise that is not available to many research laboratories.DescriptionWe collected gene expression data from 13 publicly available patient cohorts (N = 1454) and developed BC-BET, an online Bladder Cancer Biomarker Evaluation Tool for evaluating candidate diagnostic and prognostic gene expression biomarkers in bladder cancer. A user simply selects a gene, and BC-BET evaluates the utility of that gene’s expression as a diagnostic and prognostic biomarker. Specifically, BC-BET calculates how strongly a gene’s expression is associated with tumor presence (distinguishing tumor from normal samples), tumor grade (distinguishing low- from high-grade tumors), tumor stage (distinguishing non-muscle invasive from muscle invasive samples), and patient outcome (e.g., disease-specific survival) across all patients in each cohort. Patients with low-grade, non-muscle invasive tumors and patients with high-grade, muscle invasive tumors are also analyzed separately in order to evaluate whether the biomarker of interest has prognostic value independent of grade and stage.ConclusionAlthough bladder cancer gene expression datasets are publicly available, their analysis is computationally intensive and requires bioinformatics expertise. BC-BET is an easy-to-use tool for rapidly evaluating bladder cancer gene expression biomarkers across multiple patient cohorts.Electronic supplementary materialThe online version of this article (doi:10.1186/s12894-015-0056-z) contains supplementary material, which is available to authorized users.

MP22-18 IDENTIFICATION OF NOVEL GENE EXPRESSION MARKERS FOR BLADDER CANCER DIAGNOSTICS

You have accessJournal of UrologyBladder Cancer: Detection & Screening1 Apr 2014MP22-18 IDENTIFICATION OF NOVEL GENE EXPRESSION MARKERS FOR BLADDER CANCER DIAGNOSTICS Boris Alekseev, Nikolay Vorobyev, Petr Shegay, Anastasia Zabolotneva, Igor Rusakov, Anton Buzdin, Nurshat Gaifullin, and Olga Kovalchuk Boris AlekseevBoris Alekseev More articles by this author , Nikolay VorobyevNikolay Vorobyev More articles by this author , Petr ShegayPetr Shegay More articles by this author , Anastasia ZabolotnevaAnastasia Zabolotneva More articles by this author , Igor RusakovIgor Rusakov More articles by this author , Anton BuzdinAnton Buzdin More articles by this author , Nurshat GaifullinNurshat Gaifullin More articles by this author , and Olga KovalchukOlga Kovalchuk More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2014.02.866AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Molecular diagnostics may play key role in developing techniques for the early detection of non-muscle-invasive bladder cancer (BC) and is based on the detection of molecular changes that occur on initial stages of oncological disease. The aim of our study was to identify new potential BC gene expression markers and to evaluate its sensitivity in BC patients. METHODS To identify new gene expression BC markers we performed both bioinformatic and experimental research. For the bioinformatic assays we analysed publically available gene expression data in the Gene Expression Omnibus database. Experimental research consisted in characterization of the gene expression profiles in transitional cell carcinoma (TCC) and normal bladder tissues samples using two alternative approaches: suppression subtractive hybridization (SSH) and microarray hybridization. By using these approaches we have been able to identify 13 novel gene expression markers with area-under-the-curve (AUC) values >0.7 that, to our knowledge, were not associated with TCC in previous studies, but demonstrated a strong correlation with TCC in our tests (p<0,05). Among these entries, there were six top genes with the AUC scores varying from 0.85 to 0.92. To further characterize these novel potential TCC molecular markers, we performed a quantitative RT-PCR (qRT-PCR) assay of the six “top” genes on the 15 normal bladder and 30 surgically-resected TCC samples. RESULTS The transcriptional profiles for ten genes (including five “top” genes): BCL2, CCNE1, CDH1, IGFBP3, STAT1, TRIB1, NUSAP1, PRC1, UBE2C and TFDP1 correlated not only between the experimental and GEO database datasets, but also with the data obtained using SSH. However, the remaining “top” gene, KIFC1, although clearly differential according to our experimental microarray data, demonstrated an intact expression level in the SSH test. The qRT-PCR data confirmed upregulation of the genes: KIFC1, TRIB1, NUSAP1, PRC1, UBE2C, TFDP1, AURKA1 and UHRF1 in the TCC samples. These data suggest that our top six potential BC biomarkers demonstrate strong association with TCC, as reflected by the AUC qRT-PCR values - KIFC1 (0,77), TRIB1 (0,85), NUSAP1 (0,89), PRC1 (0,89), UBE2C (0,91), TFDP1 (0,87). The overall calculated AUC values place them among the best nine known TCC gene expression markers investigated in this study. CONCLUSIONS The top six new gene expression markers - KIFC1, TRIB1, NUSAP1, PRC1, UBE2C and TFDP1 showed excellent sensitivity and reproducibility. Overall, we present a list of potential BC genetic markers possessing a high diagnostic value. © 2014FiguresReferencesRelatedDetails Volume 191Issue 4SApril 2014Page: e241-e242 Advertisement Copyright & Permissions© 2014MetricsAuthor Information Boris Alekseev More articles by this author Nikolay Vorobyev More articles by this author Petr Shegay More articles by this author Anastasia Zabolotneva More articles by this author Igor Rusakov More articles by this author Anton Buzdin More articles by this author Nurshat Gaifullin More articles by this author Olga Kovalchuk More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

1140 EVALUATION OF URINARY EXOSOMES IN BLADDER CANCER PATIENTS

You have accessJournal of UrologyBladder Cancer: Basic Research (III)1 Apr 20131140 EVALUATION OF URINARY EXOSOMES IN BLADDER CANCER PATIENTS Jennifer J. Ahn, Guillermo Salazar, Matthew Seaman, Anna Scott, Piruz Motamedinia, Crystal Castaneda, Wayne Comper, James M. McKiernan, and Leileata Russo Jennifer J. AhnJennifer J. Ahn New York, NY More articles by this author , Guillermo SalazarGuillermo Salazar New York, NY More articles by this author , Matthew SeamanMatthew Seaman New York, NY More articles by this author , Anna ScottAnna Scott New York, NY More articles by this author , Piruz MotamediniaPiruz Motamedinia New York, NY More articles by this author , Crystal CastanedaCrystal Castaneda New York, NY More articles by this author , Wayne ComperWayne Comper New York, NY More articles by this author , James M. McKiernanJames M. McKiernan New York, NY More articles by this author , and Leileata RussoLeileata Russo New York, NY More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2013.02.755AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Despite significant strides in understanding the molecular pathogenesis of bladder cancer (BCa), diagnosis and surveillance continue to rely upon cystoscopy and cytology. As a result, there has been substantial interest in the use of biomarkers for diagnosis and risk stratification. However, current assays rely on tumor cells to be shed into the urine, or examine proteins that may not be specific for cancer. We have previously shown that urinary exosomes and microvesicles (collectively referred to as exosomes) are a consistent and reproducible means of sampling high integrity genetic material, but this has yet to be investigated in the context of BCa. Here, we examined the feasibility of evaluating the urinary exosomes of bladder cancer patients. METHODS Following Columbia University Medical Center IRB approval, voided urine samples were collected from 12 patients. BCa status at time of collection, as determined by cystoscopy and biopsy, was high-grade (HG) tumor (n = 5), low-grade (LG) tumor (n = 2), or no evidence of disease (NED) (n = 5). Samples were stored at 4°C and 0.8 μm filtration was used to remove whole cells and debris. Urinary exosomal RNA (exoRNA) was isolated using an in-house technique (Exosome Diagnostics, NY) and analyzed using RT-qPCR for 18 genes previously described as being differentially expressed in BCa. To compare expression levels, genes were standardized to 18S and relative quantitation (RQ) was calculated using DataAssist software (v.3.0). RESULTS Of the 18 genes analyzed, ICAM1 showed significantly higher expression in patients with HG BCa, as compared to NED patients (RQ 37.0, p = 0.0084). A similar trend was seen when comparing patients with any BCa (HG or LG) to NED patients (RQ 14.2, p = 0.051). UPK2 expression levels were not significantly different between the groups HG versus NED (RQ 1.6, p = 0.958) or LG versus NED (RQ 1.0, p = 0.975). CONCLUSIONS We successfully isolated exosomal RNA from the voided urine of patients with concurrent bladder cancer, as well as those with no evidence of disease. Additionally, significant upregulation of ICAM1 was seen in patients with HG disease. Ultimately, this technique shows promise as a non-invasive method of assessing gene expression in bladder cancer, independent of examining urothelial cells. © 2013 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 189Issue 4SApril 2013Page: e465-e466 Advertisement Copyright & Permissions© 2013 by American Urological Association Education and Research, Inc.MetricsAuthor Information Jennifer J. Ahn New York, NY More articles by this author Guillermo Salazar New York, NY More articles by this author Matthew Seaman New York, NY More articles by this author Anna Scott New York, NY More articles by this author Piruz Motamedinia New York, NY More articles by this author Crystal Castaneda New York, NY More articles by this author Wayne Comper New York, NY More articles by this author James M. McKiernan New York, NY More articles by this author Leileata Russo New York, NY More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

Downregulation of protocadherin-10 expression correlates with malignant behaviour and poor prognosis in human bladder cancer

This study retrospectively evaluated the prognostic significance of downregulated protocadherin-10 (PCDH10) gene expression in bladder cancer. To evaluate the prognostic significance of downregulated PCDH10 protein levels, immunohistochemistry was used to assess the level of PCDH10 protein in surgically-resected formalin-fixed, paraffin wax-embedded transitional cell carcinoma specimens. Relationships between PCDH10 protein levels, clinicopathological characteristics and overall survival were also evaluated. A total of 105 bladder transitional cell carcinoma specimens and 33 normal bladder epithelial samples were investigated using immunohistochemical staining. PCDH10 protein levels were downregulated in 63.8% (67/105) of bladder cancer specimens compared with control samples. Downregulated levels of PCDH10 were significantly associated with advanced stage, higher grade, larger tumour size, nonpapillary shape, tumour recurrence and decreased overall survival rates. Multivariate analysis indicated that downregulated PCDH10 levels were independently associated with decreased overall survival and had a relative risk of death of 4.571. Downregulated PCDH10 levels correlated with malignant behaviour and poor overall survival in patients with bladder cancer. Downregulated PCDH10 levels might be useful as a prognostic biomarker for bladder cancer.