Urothelial cancer gene regulatory networks inferred from large-scale RNAseq, Bead and Oligo gene expression data

BACKGROUND: Urothelial pathogenesis is a complex process driven by an underlying network of interconnected genes. The identification of novel genomic target regions and gene targets that drive urothelial carcinogenesis is crucial in order to improve our current limited understanding of urothelial cancer (UC) on the molecular level. The inference of genome-wide gene regulatory networks (GRN) from large-scale gene expression data provides a promising approach for a detailed investigation of the underlying network structure associated to urothelial carcinogenesis.

METHODS: In our study we inferred and compared three GRNs by the application of the BC3Net inference algorithm to large-scale transitional cell carcinoma gene expression data sets from Illumina RNAseq (179 samples), Illumina Bead arrays (165 samples) and Affymetrix Oligo microarrays (188 samples). We investigated the structural and functional properties of GRNs for the identification of molecular targets associated to urothelial cancer.

RESULTS: We found that the urothelial cancer (UC) GRNs show a significant enrichment of subnetworks that are associated with known cancer hallmarks including cell cycle, immune response, signaling, differentiation and translation. Interestingly, the most prominent subnetworks of co-located genes were found on chromosome regions 5q31.3 (RNAseq), 8q24.3 (Oligo) and 1q23.3 (Bead), which all represent known genomic regions frequently deregulated or aberated in urothelial cancer and other cancer types. Furthermore, the identified hub genes of the individual GRNs, e.g., HID1/DMC1 (tumor development), RNF17/TDRD4 (cancer antigen) and CYP4A11 (angiogenesis/ metastasis) are known cancer associated markers. The GRNs were highly dataset specific on the interaction level between individual genes, but showed large similarities on the biological function level represented by subnetworks. Remarkably, the RNAseq UC GRN showed twice the proportion of significant functional subnetworks. Based on our analysis of inferential and experimental networks the Bead UC GRN showed the lowest performance compared to the RNAseq and Oligo UC GRNs.

CONCLUSION: To our knowledge, this is the first study investigating genome-scale UC GRNs. RNAseq based gene expression data is the data platform of choice for a GRN inference. Our study offers new avenues for the identification of novel putative diagnostic targets for subsequent studies in bladder tumors.

Network signatures based on gene pair expression ratios improve classification and the analysis of muscle-invasive urothelial cancer

Urothelial cancer (UC) is highly recurrent and can progress from non-invasive (NMIUC) to a more aggressive muscle-invasive (MIUC) subtype that invades the muscle tissue layer of the bladder. We present a proof of principle study that network-based features of gene pairs can be used to improve classifier performance and the functional analysis of urothelial cancer gene expression data. In the first step of our procedure each individual sample of a UC gene expression dataset is inflated by gene pair expression ratios that are defined based on a given network structure. In the second step an elastic net feature selection procedure for network-based signatures is applied to discriminate between NMIUC and MIUC samples. We performed a repeated random subsampling cross validation in three independent datasets. The network signatures were characterized by a functional enrichment analysis and studied for the enrichment of known cancer genes. We observed that the network-based gene signatures from meta collections of proteinprotein interaction (PPI) databases such as CPDB and the PPI databases HPRD and BioGrid improved the classification performance compared to single gene based signatures. The network based signatures that were derived from PPI databases showed a prominent enrichment of cancer genes (e.g., TP53, TRIM27 and HNRNPA2Bl). We provide a novel integrative approach for large-scale gene expression analysis for the identification and development of novel diagnostical targets in bladder cancer. Further, our method allowed to link cancer gene associations to network-based expression signatures that are not observed in gene-based expression signatures.

The impact of biomarkers in multivariate algorithms for bladder cancer diagnosis in patients with hematuria

BACKGROUND: We appraised 23 biomarkers previously associated with urothelial cancer in a case-control study. Our aim was to determine whether single biomarkers and/or multivariate algorithms significantly improved on the predictive power of an algorithm based on demographics for prediction of urothelial cancer in patients presenting with hematuria. METHODS: Twenty-two biomarkers in urine and carcinoembryonic antigen (CEA) in serum were evaluated using enzyme-linked immunosorbent assays (ELISAs) and biochip array technology in 2 patient cohorts: 80 patients with urothelial cancer, and 77 controls with confounding pathologies. We used Forward Wald binary logistic regression analyses to create algorithms based on demographic variables designated prior predicted probability (PPP) and multivariate algorithms, which included PPP as a single variable. Areas under the curve (AUC) were determined after receiver-operator characteristic (ROC) analysis for single biomarkers and algorithms. RESULTS: After univariate analysis, 9 biomarkers were differentially expressed (t test; P

Comprehensive profiling and localisation of the matrix metalloproteinases in urothelial carcinoma

The matrix metalloproteinases (MMPs) are endopeptidases which break down the extracellular matrix and regulate cytokine and growth factor activity. Several MMPs have been implicated in the promotion of invasion and metastasis in a broad range of tumours including urothelial carcinoma. In this study, RNA from 132 normal bladder and urothelial carcinoma specimens was profiled for each of the 24 human MMPs, the four endogenous tissue inhibitors of MMPs (TIMPs) and several key growth factors and their receptors using quantitative real time RT-PCR. Laser capture microdissection (LCM) of RNA from 22 tumour and 11 normal frozen sections was performed allowing accurate RNA extraction from either stromal or epithelial compartments. This study confirms the over expression in bladder tumour tissue of well-documented MMPs and highlights a range of MMPs which have not previously been implicated in the development of urothelial cancer. In summary, MMP-2, MT1-MMP and the previously unreported MMP-28 were very highly expressed in tumour samples while MMPs 1, 7, 9, 11, 15, 19 and 23 were highly expressed. There was a significant positive correlation between transcript expression and tumour grade for MMPs 1, 2, 8, 10, 11, 12, 13, 14, 15 and 28 (P < 0.001). At the same confidence interval, TIMP-1 and TIMP-3 also correlated with increasing tumour grade. LCM revealed that most highly expressed MMPs are located primarily within the stromal compartment except MMP-13 which localised to the epithelial compartment. This work forms the basis for further functional studies, which will help to confirm the MMPs as potential diagnostic and therapeutic targets in early bladder cancer.

Collectives of diagnostic biomarkers identify high-risk subpopulations of hematuria patients: exploiting heterogeneity in large-scale biomarker data

Background: Ineffective risk stratification can delay diagnosis of serious disease in patients with hematuria. We applied a systems biology approach to analyze clinical, demographic and biomarker measurements (n = 29) collected from 157 hematuric patients: 80 urothelial cancer (UC) and 77 controls with confounding pathologies.

Methods: On the basis of biomarkers, we conducted agglomerative hierarchical clustering to identify patient and biomarker clusters. We then explored the relationship between the patient clusters and clinical characteristics using Chi-square analyses. We determined classification errors and areas under the receiver operating curve of Random Forest Classifiers (RFC) for patient subpopulations using the biomarker clusters to reduce the dimensionality of the data.

Results: Agglomerative clustering identified five patient clusters and seven biomarker clusters. Final diagnoses categories were non-randomly distributed across the five patient clusters. In addition, two of the patient clusters were enriched with patients with ‘low cancer-risk’ characteristics. The biomarkers which contributed to the diagnostic classifiers for these two patient clusters were similar. In contrast, three of the patient clusters were significantly enriched with patients harboring ‘high cancer-risk” characteristics including proteinuria, aggressive pathological stage and grade, and malignant cytology. Patients in these three clusters included controls, that is, patients with other serious disease and patients with cancers other than UC. Biomarkers which contributed to the diagnostic classifiers for the largest ‘high cancer- risk’ cluster were different than those contributing to the classifiers for the ‘low cancer-risk’ clusters. Biomarkers which contributed to subpopulations that were split according to smoking status, gender and medication were different.

Conclusions: The systems biology approach applied in this study allowed the hematuric patients to cluster naturally on the basis of the heterogeneity within their biomarker data, into five distinct risk subpopulations. Our findings highlight an approach with the promise to unlock the potential of biomarkers. This will be especially valuable in the field of diagnostic bladder cancer where biomarkers are urgently required. Clinicians could interpret risk classification scores in the context of clinical parameters at the time of triage. This could reduce cystoscopies and enable priority diagnosis of aggressive diseases, leading to improved patient outcomes at reduced costs. © 2013 Emmert-Streib et al; licensee BioMed Central Ltd.

Urinary thrombomodulin levels were significantly higher following occupational exposure to chemicals, in the presence of dipstick protein, but not in the presence of dipstick blood

Currently, there are no biomarkers which can identify patients with an increased risk of developing urothelial cancer as a result of occupational chemical exposure. The aim of this study was to evaluate the relationships between final diagnosis and 22 biomarkers measured in urine, serum and plasma collected from 156 hematuric patients. Fourteen of the 80 patients (17.5%) with urothelial cancer and 13/76 (17.1%) of the controls were deemed to have a history of chemical exposure. We applied Fisher's exact tests to explore associations between chemical exposure and final diagnosis, and tumor stage and grade, where applicable; ANOVA and t-test to compare age across patients with and without chemical exposure; and Zelen's exact test to evaluate relationships across final diagnosis, chemical exposure and smoking. Following pre-selection of biomarkers using Lasso, we identified biomarkers with differential levels across patients with and without chemical exposure using Welch's t-test. Using a one-sided t-test and considering multiple testing using FDR, we observed that TM levels in urine were significantly higher in samples from patients with a history of chemical exposure regardless of their diagnosis as control or urothelial cancer (one-sided t-test, p_UC = 0.014 and p_CTL = 0.043); in the presence of dipstick protein and when urinary pH levels ≤ 6 (p = 0.003), but not in the presence of dipstick blood (p = 0.115). Urothelial cancer patients with a history of chemical exposure were significantly younger (64.1 years) than those without chemical exposure (70.2 years) (one-sided t-test p-value = 0.012); and their tumors were higher grade (Fisher's exact test; p = 0.008). There was a strong association between a history of chemical exposure and smoking in urothelial cancer patients (Zelen's exact test; p = 0.025). Elevated urinary thrombomodulin levels could have the potential to identify chemical exposure in hematuric patients at high risk of developing urothelial cancer.

Bystander-induced differentiation: a major response to targeted irradiation of a urothelial explant model.

A ureter primary explant technique, using porcine tissue sections was developed to study bystander effects under in vivo like conditions where dividing and differentiated cells are present. Targeted irradiations of ureter tissue fragments were performed with the Gray Cancer Institute charged particle microbeam at a single location (2 microm precision) with 10 3He2+ particles (5 MeV; LET 70 keV/microm). After irradiation the ureter tissue section was incubated for 7 days allowing explant outgrowth to be formed. Differentiation was estimated using antibodies to Uroplakin III, a specific marker of terminal urothelial differentiation. Even although only a single region of the tissue section was targeted, thousands of additional cells were found to undergo bystander-induced differentiation in the explant outgrowth. This resulted in an overall increase in the fraction of differentiated cells from 63.5+/-5.4% to 76.6+/-5.6%. These changes are much greater than that observed for the induction of damage in this model. One interpretation of these results is that in the tissue environment, differentiation is a much more significant response to targeted irradiation and potentially a protective mechanism.

Recurrence of Urothelial Carcinoma of the Bladder: A Role for Insulin-Like Growth Factor-II Loss of Imprinting and Cytoplasmic E-Cadherin Immunolocalization

Purpose:This study documents the frequency of insulin-like growth factor-II (IGF-II) loss of imprinting (LOI) in a series of 87 bladder tissues. E-cadherin (CDH1) immunolocalization was also investigated due to the known redistribution of this adherence protein to the cytoplasm following exogenous exposure to IGF-II.
Experimental Design: Informative IGF-II cases were identified following DNA-PCR amplification and subsequent sequencing of the transcribable ApaI RFLP in exon 9 of IGF-II. Similar approaches using primer-specific cDNA templates identified the imprinting status of IGF-II in these informative cases. CDH1cellular localization was assessed on a tissue microarray platform of 114 urothelial carcinoma of the bladder (UCB) cases (70 pTanoninvasive and 44 pT1laminapropria invasive) using the commercially available Novocastra antibody.
Results: IGF-IILOI was evident in 7 of17 (41%) UCB tumors and 4 of11 (36%) tumor-associated normal urothelial samples.Two of four pT1grade 3 tumors, the subject of much debate concerning their suitability for radical cystectomy, showed LOI at the IGF-II locus. In those tumors showing IGF-II LOI, 4 of 7 (57%) displayed concomitant CDH1cytoplasmic staining. In contrast, only 3 of 10 (30%) IGF-IImaintenance ofimprinting tumorshad concomitant CDH1cytoplasmiclocalization. UCB cell lines displaying cytoplasmic CDH1immunolocalization expressed significantly higher levels of IGF-II (CAL29, HT1376, and RT112) compared with RT4, a cell line displaying crisp membranous CDH1staining. Finally, cytoplasmic CDH1staining was an independent predictor of a shorter time to recurrence independent of tumor grade and stage.
Conclusions: We suggest that CDH1 cytoplasmic immunolocalization as a result of increased IGF-II levels identifies those nonmuscle invasive presentations most likely to recur and therefore might benefit from more radical nonconserving bladder surgery

AURKA overexpression accompanies dysregulation of DNA-damage response genes in invasive urothelial cell carcinoma

Invasive urothelial cell carcinoma (UCC) is characterized by increased chromosomal instability and follows an aggressive clinical course in contrast to non-invasive disease. To identify molecular processes that confer and maintain an aggressive malignant phenotype, we used a high-throughput genome-wide approach to interrogate a cohort of high and low clinical risk UCC tumors. Differential expression analyses highlighted cohesive dysregulation of critical genes involved in the G(2)/M checkpoint in aggressive UCC. Hierarchical clustering based on DNA Damage Response (DDR) genes separated tumors according to a pre-defined clinical risk phenotype. Using array-comparative genomic hybridization, we confirmed that the DDR was disrupted in tumors displaying high genomic instability. We identified DNA copy number gains at 20q13.2-q13.3 (AURKA locus) and determined that overexpression of AURKA accompanied dysregulation of DDR genes in high risk tumors. We postulated that DDR-deficient UCC tumors are advantaged by a selective pressure for AURKA associated override of M phase barriers and confirmed this in an independent tissue microarray series. This mechanism that enables cancer cells to maintain an aggressive phenotype forms a rationale for targeting AURKA as a therapeutic strategy in advanced stage UCC.

MT1-MMP regulates urothelial cell invasion via transcriptional regulation of Dickkopf-3

Membrane type-1 matrix metalloproteinase (MT1-MMP) is a zinc-binding endopeptidase, which plays a crucial role in tumour growth, invasion and metastasis. We have shown previously that MT1-MMP has higher expression levels in the human urothelial cell carcinoma (UCC) tissue. We show here that siRNA against MT1-MMP blocks invasion in UCC cell lines. Invasion is also blocked by broad-spectrum protease and MMP inhibitors including tissue inhibitor of metalloproteinase-1 and -2. Membrane type-1-MMP can also regulate transcription. We have used expression arrays to identify genes that are differentially transcribed when siRNA is used to suppress MT1-MMP expression. Upon MT1-MMP knockdown, Dickkopf-3 (DKK3) expression was highly upregulated. The stability of DKK3 mRNA was unaffected under these conditions, suggesting transcriptional regulation of DKK3 by MT1-MMP. Dickkopf-3 has been previously shown to inhibit invasion. We confirm that the overexpression of DKK3 leads to decreased invasive potential as well as delayed wound healing. We show for the first time that the effects of MT1-MMP on cell invasion are mediated in part through changes in DKK3 gene transcription.