Monitoring gene expression profile changes in bladder transitional cell carcinoma using cDNA microarray

A Specific Blood Signature Reveals Higher Levels of S100A12: A Potential Bladder Cancer Diagnostic Biomarker Along With Urinary Engrailed-2 Protein Detection

Urothelial carcinoma of the urinary bladder (UCB) or bladder cancer remains a major health problem with high morbidity and mortality rates, especially in the western world. UCB is also associated with the highest cost per patient. In recent years numerous markers have been evaluated for suitability in UCB detection and surveillance. However, to date none of these markers can replace or even reduce the use of routine tools (cytology and cystoscopy). Our current study described UCB's extensive expression profile and highlighted the variations with normal bladder tissue. Our data revealed that JUP, PTGDR, KLRF1, MT-TC, and RNU6-135P are associated with prognosis in patients with UCB. The microarray expression data identified also S100A12, S100A8, and NAMPT as potential UCB biomarkers. Pathway analysis revealed that natural killer cell mediated cytotoxicity is the most involved pathway. Our analysis showed that S100A12 protein may be useful as a biomarker for early UCB detection. Plasma S100A12 has been observed in patients with UCB with an overall sensitivity of 90.5% and a specificity of 75%. S100A12 is highly expressed preferably in high-grade and high-stage UCB. Furthermore, using a panel of more than hundred urine samples, a prototype lateral flow test for the transcription factor Engrailed-2 (EN2) also showed reasonable sensitivity (85%) and specificity (71%). Such findings provide confidence to further improve and refine the EN2 rapid test for use in clinical practice. In conclusion, S100A12 and EN2 have shown potential value as biomarker candidates for UCB patients. These results can speed up the discovery of biomarkers, improving diagnostic accuracy and may help the management of UCB.

Genome-wide screening and identification of long noncoding RNAs and their interaction with protein coding RNAs in bladder urothelial cell carcinoma

To understand lncRNAs expression profiling and their potential functions in bladder cancer, we investigated the lncRNA and coding RNA expression on human bladder cancer and normal bladder tissues. Bioinformatic analysis revealed thousands of significantly differentially expressed lncRNAs and coding mRNA in bladder cancer relative to normal bladder tissue. Co-expression analysis revealed that 50% of lncRNAs and coding RNAs expressed in the same direction. A subset of lncRNAs might be involved in mTOR signaling, p53 signaling, cancer pathways. Our study provides a large scale of co-expression between lncRNA and coding RNAs in bladder cancer cells and lays biological basis for further investigation.

A history of microarrays in biomedicine

The fundamental strategy of the current postgenomic era or the era of functional genomics is to expand the scale of biologic research from studying single genes or proteins to studying all genes or proteins simultaneously using a systematic approach. As recently developed methods for obtaining genome-wide mRNA expression data, oligonucleotide and DNA microarrays are particularly powerful in the context of knowing the entire genome sequence and can provide a global view of changes in gene expression patterns in response to physiologic alterations or manipulation of transcriptional regulators. In biomedical research, such an approach will ultimately determine biologic behavior of both normal and diseased tissues, which may provide insights into disease mechanisms and identify novel markers and candidates for diagnostic, prognostic and therapeutic intervention. However, microarray technology is still in a continuous state of evolution and development, and it may take time to implement microarrays as a routine medical device. Many limitations exist and many challenges remain to be achieved to help inclusion of microarrays in clinical medicine. In this review, a brief history of microarrays in biomedical research is provided, including experimental overview, limitations, challenges and future developments.

Gene expression is highly correlated on the chromosome level in urinary bladder cancer

OBJECTIVE

Chromosome correlation maps display correlations between gene expression patterns on the same chromosome. Our goal was to map the genes on chromosome regions and to identify correlations through their location on chromosome regions.

MATERIALS AND METHODS

Following microarray analysis we used Ingenuity Pathway Analysis (IPA) to construct gene networks of the co-deregulated genes in bladder cancer. Chromosome mapping, mathematical modeling and data simulations were performed using the WebGestalt and Matlab(®) softwares.

RESULTS

The top deregulated molecules among 129 bladder cancer samples were implicated in the PI3K/AKT signaling, cell cycle, Myc-mediated apoptosis signaling and ERK5 signaling pathways. Their most prominent molecular and cellular functions were related to cell cycle, cell death, gene expression, molecular transport and cellular growth and proliferation. Chromosome correlation maps allowed us to detect significantly co-expressed genes along the chromosomes. We identified strong correlations among tumors of Tα-grade 1, as well as for those of Tα-grade 2, in chromosomes 1, 2, 3, 7, 12 and 19. Chromosomal domains of gene co-expression were revealed for the normal tissues, as well. The expression data were further simulated, exhibiting an excellent fit (0.7 < R(2) < 0.9). The simulations revealed that along the different samples, genes on same chromosomes are expressed in a similar manner.

CONCLUSIONS

Gene expression is highly correlated on the chromosome level. Chromosome correlation maps of gene expression signatures can provide further information on gene regulatory mechanisms. Gene expression data can be simulated using polynomial functions.

Identification of common differentially expressed genes in urinary bladder cancer

Background

Current diagnosis and treatment of urinary bladder cancer (BC) has shown great progress with the utilization of microarrays.

Purpose

Our goal was to identify common differentially expressed (DE) genes among clinically relevant subclasses of BC using microarrays.

Methodology/Principal Findings

BC samples and controls, both experimental and publicly available datasets, were analyzed by whole genome microarrays. We grouped the samples according to their histology and defined the DE genes in each sample individually, as well as in each tumor group. A dual analysis strategy was followed. First, experimental samples were analyzed and conclusions were formulated; and second, experimental sets were combined with publicly available microarray datasets and were further analyzed in search of common DE genes. The experimental dataset identified 831 genes that were DE in all tumor samples, simultaneously. Moreover, 33 genes were up-regulated and 85 genes were down-regulated in all 10 BC samples compared to the 5 normal tissues, simultaneously. Hierarchical clustering partitioned tumor groups in accordance to their histology. K-means clustering of all genes and all samples, as well as clustering of tumor groups, presented 49 clusters. K-means clustering of common DE genes in all samples revealed 24 clusters. Genes manifested various differential patterns of expression, based on PCA. YY1 and NFκB were among the most common transcription factors that regulated the expression of the identified DE genes. Chromosome 1 contained 32 DE genes, followed by chromosomes 2 and 11, which contained 25 and 23 DE genes, respectively. Chromosome 21 had the least number of DE genes. GO analysis revealed the prevalence of transport and binding genes in the common down-regulated DE genes; the prevalence of RNA metabolism and processing genes in the up-regulated DE genes; as well as the prevalence of genes responsible for cell communication and signal transduction in the DE genes that were down-regulated in T1-Grade III tumors and up-regulated in T2/T3-Grade III tumors. Combination of samples from all microarray platforms revealed 17 common DE genes, (BMP4, CRYGD, DBH, GJB1, KRT83, MPZ, NHLH1, TACR3, ACTC1, MFAP4, SPARCL1, TAGLN, TPM2, CDC20, LHCGR, TM9SF1 and HCCS) 4 of which participate in numerous pathways.

Conclusions/Significance

The identification of the common DE genes among BC samples of different histology can provide further insight into the discovery of new putative markers.

Increased CYP1A1 expression in human exfoliated urothelial cells of cigarette smokers compared to non-smokers

Polycyclic aromatic hydrocarbons, arylamines and nitrosamines, constituents of cigarette smoke, are known inducers of bladder cancer. The biochemical response of the target tissue, the bladder urothelium, following inhalation of cigarette smoke has not been studied so far. We used exfoliated transitional urothelial cells from human urine samples to analyze effects of smoking on induction of the cytochrome P450 enzyme CYP1A1. Samples of 40 subjects, including male and female smokers and non-smokers, were examined. A prerequisite for the immunofluorescence microscopic analysis of the cells was the enrichment of the urothelial cell population. This was achieved by a new method which is based on magnetic cell sorting exploiting specific binding of immobilized Griffonia simplicifolia lectin to the surface of urothelial cells. Immunostaining of the final cell preparation with a monoclonal antibody to CYP1A1 showed that about 6% of the urothelial cells of non-smokers stained positive for CYP1A1. However, this fraction of positive cells was more than 44% of the urothelial cells in samples from cigarette smokers. In spite of the individual variation, the difference was statistically significant. There were no gender-related differences in the portion of CYP1A1 expressing urothelial cells of smokers and non-smokers. In essence, we show for the first time that human urothelial cells respond to cigarette smoking by induction of CYP1A1. The approach opens new fields of mechanistic and biomarker research with respect to the pathogenetic processes of cancer development in the human bladder.

Differences in gene expression between noninvasive and invasive transitional cell carcinoma of the human bladder using complementary deoxyribonucleic acid microarray: Preliminary results

This study was performed to identify differences in gene expression between superficial noninvasive and invasive transitional cell carcinoma (TCC) of the bladder in human beings. We used complementary deoxyribonucleic acid microarrays containing 14,551 different genes to analyze gene expression among 6 cases of superficial and 6 cases of invasive TCC of the bladder to identify differences in gene expression, which might explain differences in the biology and clinical outcomes of these histologic subtypes of TCC. Quantitative real-time polymerase chain reaction was performed for selected genes to validate the microarray data. Significant up-regulation of 40 genes was associated with cases of superficial noninvasive, but not in invasive, TCC of the urinary bladder. This effect included genes involved in epithelial cell dedifferentiation and keratinization, as well as genes related to cell cycle, cell adhesion, transcription, and apoptosis. Conversely, significant up-regulation of 34 genes was associated with cases of invasive TCC, but not in superficial TCC, including genes related to extracellular matrix degradation, immune responses, cell cycling, and angiogenesis. This study shows the usefulness of complementary deoxyribonucleic acid microarray technology for identifying differences in gene expression among different histotypes of bladder cancer.

Gene Expression Profiling of Progressive Papillary Noninvasive Carcinomas of the Urinary Bladder

PURPOSE

The aim of the present study was to define gene expression profiles of noninvasive and invasive bladder cancer, to identify potential therapeutic or screening targets in bladder cancer, and to define genetic changes relevant for tumor progression of recurrent papillary bladder cancer (pTa).

EXPERIMENTAL DESIGN

Overall, 67 bladder neoplasms (46 pTa, 3 pTis, 10 pT1, and 8 pT2) and eight normal bladder specimens were investigated by a combination of laser microdissection and gene expression profiling. Eight of 16 patients with recurrent noninvasive papillary bladder tumors developed carcinoma in situ (pTis) or invasive bladder cancer (> or = pT1G2) in the course of time. RNA expression results of the putative progression marker cathepsin E (CTSE) were confirmed by immunohistochemistry using high-throughput tissue microarray analysis (n = 776). Univariate analysis of factors regarding overall survival, progression-free survival, and recurrence-free survival in patients with urothelial bladder cancer was done.

RESULTS

Hierarchical cluster analyses revealed no differences between pTaG1 and pTaG2 tumors. However, distinct groups of invasive cancers with different gene expression profiles in papillary and solid tumors were found. Progression-associated gene profiles could be defined (e.g., FABP4 and CTSE) and were already present in the preceding noninvasive papillary tumors. CTSE expression (P = 0.003) and a high Ki-67 labeling index of at least 5% (P = 0.01) were the only factors that correlated significantly with progression-free survival of pTa tumors in our gene expression approach.

CONCLUSIONS

Gene expression profiling revealed novel genes with potential clinical utility to select patients that are more likely to develop aggressive disease.