Identification of DNA hypermethylation of SOX9 in association with bladder cancer progression using CpG microarrays

CpG island arrays represent a high-throughput epigenomic discovery platform to identify global disease-specific promoter hypermethylation candidates along bladder cancer progression. DNA obtained from 10 pairs of invasive bladder tumours were profiled vs their respective normal urothelium using differential methylation hybridisation on custom-made CpG arrays (n=12 288 clones). Promoter hypermethylation of 84 clones was simultaneously shown in at least 70% of the tumours. SOX9 was selected for further validation by bisulphite genomic sequencing and methylation-specific polymerase chain reaction in bladder cancer cells (n=11) and primary bladder tumours (n=101). Hypermethylation was observed in bladder cancer cells and associated with lack of gene expression, being restored in vitro by a demethylating agent. In primary bladder tumours, SOX9 hypermethylation was present in 56.4% of the cases. Moreover, SOX9 hypermethylation was significantly associated with tumour grade and overall survival. Thus, this high-throughput epigenomic strategy has served to identify novel hypermethylated candidates in bladder cancer. In vitro analyses supported the role of methylation in silencing SOX9 gene. The association of SOX9 hypermethylation with tumour progression and clinical outcome suggests its relevant clinical implications at stratifying patients affected with bladder cancer

A simple method for detecting oncofetal chondroitin sulfate glycosaminoglycans in bladder cancer urine

Proteoglycans in bladder tumors are modified with a distinct oncofetal chondroitin sulfate (ofCS) glycosaminoglycan that is normally restricted to placental trophoblast cells. This ofCS-modification can be detected in bladder tumors by the malarial VAR2CSA protein, which in malaria pathogenesis mediates adherence of parasite-infected erythrocytes within the placenta. In bladder cancer, proteoglycans are constantly shed into the urine, and therefore have the potential to be used for detection of disease. In this study we investigated whether recombinant VAR2CSA (rVAR2) protein could be used to detect ofCS-modified proteoglycans (ofCSPGs) in the urine of bladder cancer patients as an indication of disease presence. We show that ofCSPGs in bladder cancer urine can be immobilized on cationic nitrocellulose membranes and subsequently probed for ofCS content by rVAR2 protein in a custom-made dot-blot assay. Patients with high-grade bladder tumors displayed a marked increase in urinary ofCSPGs as compared to healthy individuals. Urine ofCSPGs decreased significantly after complete tumor resection compared to matched urine collected preoperatively from patients with bladder cancer. Moreover, ofCSPGs in urine correlated with tumor size of bladder cancer patients. These findings demonstrate that rVAR2 can be utilized in a simple biochemical assay to detect cancer-specific ofCS-modifications in the urine of bladder cancer patients, which may be further developed as a noninvasive approach to detect and monitor the disease

On dynamic network entropy in cancer

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network to induce a stochastic dynamics on the network, we here demonstrate that cancer cells are characterised by an increase in the dynamic network entropy, compared to cells of normal physiology. Using a fundamental relation between the macroscopic resilience of a dynamical system and the uncertainty (entropy) in the underlying microscopic processes, we argue that cancer cells will be more robust to random gene perturbations. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local dynamic entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local network dynamics. In particular, we also find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in the dynamic network entropy. In summary, our results support the view that the observed increased robustness of cancer cells to perturbation and therapy may be due to an increase in the dynamic network entropy that allows cells to adapt to the new cellular stresses. Conversely, genes that exhibit local flux entropy decreases in cancer may render cancer cells more susceptible to targeted intervention and may therefore represent promising drug targets.Comment: 10 pages, 3 figures, 4 tables. Submitte

Oncoprotein DEK as a tissue and urinary biomarker for bladder cancer

<p>Abstract</p> <p>Background</p> <p>Bladder cancer is a significant healthcare problem in the United States of America with a high recurrence rate. Early detection of bladder cancer is essential for removing the tumor with preservation of the bladder, avoiding metastasis and hence improving prognosis and long-term survival. The objective of this study was to analyze the presence of DEK protein in voided urine of bladder cancer patients as a urine-based bladder cancer diagnostic test.</p> <p>Methods</p> <p>We examined the expression of DEK protein by western blot in 38 paired transitional cell carcinoma (TCC) bladder tumor tissues and adjacent normal tissue. The presence of DEK protein in voided urine was analyzed by western blot in 42 urine samples collected from patients with active TCC, other malignant urogenital disease and healthy individuals.</p> <p>Results</p> <p>The DEK protein is expressed in 33 of 38 bladder tumor tissues with no expression in adjacent normal tissue. Based on our sample size, DEK protein is expressed in 100% of tumors of low malignant potential, 92% of tumors of low grade and in 71% of tumors of high grade. Next, we analyzed 42 urine samples from patients with active TCC, other malignant urogenital disease, non-malignant urogenital disease and healthy individuals for DEK protein expression by western blot analysis. We are the first to show that the DEK protein is present in the urine of bladder cancer patients. Approximately 84% of TCC patient urine specimens were positive for urine DEK.</p> <p>Conclusion</p> <p>Based on our pilot study of 38 bladder tumor tissue and 42 urine samples from patients with active TCC, other malignant urogenital disease, non-malignant urogenital disease and healthy individuals; DEK protein is expressed in bladder tumor tissue and voided urine of bladder cancer patients. The presence of DEK protein in voided urine is potentially a suitable biomarker for bladder cancer and that the screening for the presence of DEK protein in urine can be explored as a noninvasive diagnostic test for bladder cancer.</p

Assessment and optimisation of normalisation methods for dual-colour antibody microarrays

<p>Abstract</p> <p>Background</p> <p>Recent advances in antibody microarray technology have made it possible to measure the expression of hundreds of proteins simultaneously in a competitive dual-colour approach similar to dual-colour gene expression microarrays. Thus, the established normalisation methods for gene expression microarrays, e.g. loess regression, can in principle be applied to protein microarrays. However, the typical assumptions of such normalisation methods might be violated due to a bias in the selection of the proteins to be measured. Due to high costs and limited availability of high quality antibodies, the current arrays usually focus on a high proportion of regulated targets. Housekeeping features could be used to circumvent this problem, but they are typically underrepresented on protein arrays. Therefore, it might be beneficial to select invariant features among the features already represented on available arrays for normalisation by a dedicated selection algorithm.</p> <p>Results</p> <p>We compare the performance of several normalisation methods that have been established for dual-colour gene expression microarrays. The focus is on an invariant selection algorithm, for which effective improvements are proposed. In a simulation study the performances of the different normalisation methods are compared with respect to their impact on the ability to correctly detect differentially expressed features. Furthermore, we apply the different normalisation methods to a pancreatic cancer data set to assess the impact on the classification power.</p> <p>Conclusions</p> <p>The simulation study and the data application demonstrate the superior performance of the improved invariant selection algorithms in comparison to other normalisation methods, especially in situations where the assumptions of the usual global loess normalisation are violated.</p

Neuropilin-2 Mediated β-Catenin Signaling and Survival in Human Gastro-Intestinal Cancer Cell Lines

NRP-2 is a high-affinity kinase-deficient receptor for ligands belonging to the class 3 semaphorin and vascular endothelial growth factor families. NRP-2 has been detected on the surface of several types of human cancer cells, but its expression and function in gastrointestinal (GI) cancer cells remains to be determined. We sought to determine the function of NRP-2 in mediating downstream signals regulating the growth and survival of human gastrointestinal cancer cells. In human gastric cancer specimens, NRP-2 expression was detected in tumor tissues but not in adjacent normal mucosa. In CNDT 2.5 cells, shRNA mediated knockdown NRP-2 expression led to decreased migration and invasion in vitro (p<0.01). Focused gene-array analysis demonstrated that loss of NRP-2 reduced the expression of a critical metastasis mediator gene, S100A4. Steady-state levels and function of β-catenin, a known regulator of S100A4, were also decreased in the shNRP-2 clones. Furthermore, knockdown of NRP-2 sensitized CNDT 2.5 cells in vitro to 5FU toxicity. This effect was associated with activation of caspases 3 and 7, cleavage of PARP, and downregulation of Bcl-2. In vivo growth of CNDT 2.5 cells in the livers of nude mice was significantly decreased in the shNRP-2 group (p<0.05). Intraperitoneal administration of NRP-2 siRNA-DOPC decreased the tumor burden in mice (p = 0.01). Collectively, our results demonstrate that tumor cell–derived NRP-2 mediates critical survival signaling in gastrointestinal cancer cells

Mdm2-SNP309 polymorphism in prostate cancer: no evidence for association with increased risk or histopathological tumour characteristics

The search for inherited cancer susceptibility factors is a major focus of epidemiologic cancer studies. Analyses of single-nucleotide polymorphisms (SNP) in a variety of genes revealed a correlation between a specific allele variant and cancer predisposition. Human mouse double-minute 2 protein (Mdm2) is a cellular E3 ligase capable of ubiquitination and degradation of p53. Therefore, Mdm2 is a crucial factor of cell cycle control and cell survival. The Mdm2 promoter SNP309 was shown to increase Mdm2 expression and can, thereby, inhibit the p53 pathway. This SNP was found to be associated with increased risk and early onset of various malignancies. For prostate cancer no studies are reported to date. In a case–control study we determined the distribution of the Mdm2 SNP309 in 145 male subjects with prostate cancer and in 124 male controls without any malignancy using RFLP analysis. Cases and controls showed a similar distribution of the SNP (P=0.299). Genotype distribution showed neither an association with histopathological characteristics of the tumours nor with prognosis. Age at disease onset was also not modified by the SNP. This first study of the Mdm2 SNP309 in prostate cancer patients suggests no correlation between a certain allelic variant and an increased cancer risk

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