The CD44 proteins form a ubiquitously expressed family of cell surface adhesion molecules involved in cell-cell and cellmatrix interactions. The multiple protein isoforms are encoded by a single gene by alternative splicing and are further modified by a range of post-translational modifications. CD44 proteins are single chain molecules comprising an N-terminal extracellular domain, a membrane proximal region, a transmembrane domain, and a cytoplasmic tail. The CD44 gene has only been detected in higher organisms and the amino acid sequence of most of the molecule is highly conserved between mammalian species. The principal ligand of CD44 is hyaluronic acid, an integral component of the extracellular matrix. Other CD44 ligands include osteopontin, serglycin, collagens, fibronectin, and laminin. The major physiological role of CD44 is to maintain organ and tissue structure via cell-cell and cell-matrix adhesion, but certain variant isoforms can also mediate lymphocyte activation and homing, and the presentation of chemical factors and hormones. Increased interest has been directed at the characterisation of this molecule since it was observed that expression of multiple CD44 isoforms is greatly upregulated in neoplasia. CD44, particularly its variants, may be useful as a diagnostic or prognostic marker of malignancy and, in at least some human cancers, it may be a potential target for cancer therapy. This review describes the structure of the CD44 gene and discusses some of its roles in physiological and pathological processes.

The identification of molecular signatures characteristic of tumor cells that are capable of metastatic spread is required for the development of therapeutic interventions to abrogate this lethal process. To facilitate this, we have previously characterized an experimental system in which the role of candidate metastasis-related genes can be screened and tested. Monoclonal cell lines M4A4 and NM2C5 are spontaneously occurring sublines of the MDA-MB-435 cell breast tumor cell line that exhibit phenotypic differences in growth, invasion, and metastatic efficiency in athymic mice. In this study, transcriptional profiles of these cell lines were created using oligonucleotide microarrays representing over 12,000 genes. Intensity modeling and hierarchical clustering analysis identified a 171-gene expression signature that correlated with metastatic phenotype and highlighted several GTPase signaling components. Restoration of one of these GTPases, deleted in liver cancer-1 (DLC-1), in metastatic M4A4 cells to levels observed in the nonmetastatic NM2C5 cell line resulted in the inhibition of migration and invasion in vitro and a significant reduction in the ability of these cells to form pulmonary metastases in athymic mice. These studies show the utility of expression profiling, in an appropriate experimental system, to identify genetic determinants of metastatic sufficiency. The finding that DLC-1 can act as a metastasis-suppressor gene supports an influential role for GTPase signaling in tumor progression. (Cancer Res 2005; 65(14): 6042-53)

Current methods in the noninvasive detection and surveillance of bladder cancer via urine analysis include voided urine cytology (VUC) and some diagnostic urinary protein biomarkers; however, due to the poor sensitivity of VUC and high false-positive rates of currently available protein assays, detection of bladder cancer via urinalysis remains a challenge. In the study presented here, a rapid, high-sensitivity technique was developed to profile the N-linked glycoprotein component in naturally micturated human urine specimens. Concanavalin A (Con A) affinity chromatography coupled to nanoflow liquid chromatography was utilized to separate the complex peptide mixture prior to a linear ion trap MS analysis. Of 186 proteins identified with high confidence by multiple analyses, 40% were secreted proteins, 18% membrane proteins, and 14% extracellular proteins. In this study, the presence of several proteins appeared to be associated with the presence of bladder cancer, including R-1B-glycoprotein that was detected in all tumor-bearing patient samples but in none of the samples obtained from nontumor-bearing individuals. The combination of Con A affinity chromatography and nano-LC/MS/MS provides an initial investigation of N-glycoproteins in complex biological samples and facilitates the identification of potential biomarkers of bladder cancer in noninvasively obtained human urine.

Accurate urinary assays for bladder cancer (BCa) detection would benefit both patients and healthcare systems. Through genomic and proteomic profiling of urine components, we have previously identified a panel of biomarkers that can outperform current urine-based biomarkers for the non-invasive detection of BCa. Herein, we report the diagnostic utility of various multivariate combinations of these biomarkers. We performed a case-controlled validation study in which voided urines from 127 patients (64 tumor bearing subjects) were analyzed. The urinary concentrations of 14 biomarkers (IL-8, MMP-9, MMP-10, SDC1, CCL18, PAI-1, CD44, VEGF, ANG, CA9, A1AT, OPN, PTX3, and APOE) were assessed by enzyme-linked immunosorbent assay (ELISA). Diagnostic performance of each biomarker and multivariate models were compared using receiver operating characteristic curves and the chi-square test. An 8-biomarker model achieved the most accurate BCa diagnosis (sensitivity 92%, specificity 97%), but a combination of 3 of the 8 biomarkers (IL-8, VEGF, and APOE) was also highly accurate (sensitivity 90%, specificity 97%). For comparison, the commercial BTA-Trak ELISA test achieved a sensitivity of 79% and a specificity of 83%, and voided urine cytology detected only 33% of BCa cases in the same cohort. These datashow that a multivariate urine-based assay can markedly improve the accuracy of non-invasive BCa detection. Further validation studies are under way to investigate the clinical utility of this panel of biomarkers for BCa diagnosis and disease monitoring.

Endothelial cell growth and proliferation are critical for angiogenesis; thus, greater insight into the regulation of pathological angiogenesis is greatly needed. Previous studies have reported on chemokine (C-X-C motif) ligand 1 (CXCL1) expression in epithelial cells and that secretion of CXCL1 from these epithelial cells induces angiogenesis. However, limited reports have demonstrated CXCL1 expression in endothelial cells. In this report, we present data that expand on the role of CXCL1 in human endothelial cells inducing angiogenesis. Specifically, CXCL1 is expressed and secreted from human endothelial cells. Interference of CXCL1 function using neutralizing antibodies resulted in a reduction in endothelial cell migration and viability/proliferation, the latter associated with a decrease in levels of cyclin D and cdk4. In vitro studies revealed that CXCL1 influenced neoangiogenesis through the regulation of epidermal growth factor and ERK1/2. In a xenograft angiogenesis model, interference of CXCL1 function resulted in inhibition of angiogenesis. A better understanding of the role of CXCL1 in the interactions between the endothelial and epithelial components will provide insight into how human tissues use CXCL1 to survive and thrive in a hostile environment.

Background Bladder cancer (BCa) is among the five most common malignancies world-wide, and due to high rates of recurrence, one of the most prevalent. Improvements in non-invasive urine-based assays to detect BCa would benefit both patients and healthcare systems. In this study, the goal was to identify urothelial cell transcriptomic signatures associated with BCa. Methods Gene expression profiling (Affymetrix U133 Plus 2.0 arrays) was applied to exfoliated urothelia obtained from a cohort of 92 subjects with known bladder disease status. Computational analyses identified candidate biomarkers of BCa and an optimal predictive model was derived. Selected targets from the profiling analyses were monitored in an independent cohort of 81 subjects using quantitative real-time PCR (RT-PCR), Results Transcriptome profiling data analysis identified 52 genes associated with BCa (p≤0.001), and gene models that optimally predicted class label were derived. RT-PCR analysis of 48 selected targets in an independent cohort identified a 14-gene diagnostic signature that predicted the presence of BCa with high accuracy. Conclusions Exfoliated urothelia sampling provides a robust analyte for the evaluation of patients with suspected BCa. The refinement and validation of the multi-gene urothelial cell signatures identified in this preliminary study may lead to accurate, non-invasive assays for the detection of BCa. Impact The development of an accurate, non-invasive BCa detection assay would benefit both the patient and healthcare systems through better detection, monitoring and control of disease.

Bladder cancer is one of the most prevalent cancers worldwide, but the treatment and management of this disease can be very successful if the disease is detected early. The development of molecular assays that could diagnose bladder cancer accurately, and at an early stage, would be a significant advance. Ideally, such molecular assays would be applicable to non-invasively obtained body fluids, and be designed not only for diagnosis but also for monitoring disease recurrence and response to treatment. In this article, we assess the performance of current diagnostic assays for bladder cancer and discuss some of the emerging biomarkers that could be developed to augment current bladder cancer detection strategies.

The early detection of bladder cancer (BCa) is pivotal for successful patient treatment and management. Through genomic and proteomic studies, we have identified a number of bladder cancer-associated biomarkers that have potential clinical utility. In a case-control study, we examined voided urines from 127 subjects: 64 tumor-bearing subjects and 63 controls. The urine concentrations of the following proteins were assessed by enzyme-linked immunosorbent assay (ELISA); C-C motif chemokine 18 (CCL18), Plasminogen Activator Inhibitor 1 (PAI-1) and CD44. Data were compared to a commercial ELISA-based BCa detection assay (BTA-Trak©) and voided urinary cytology. We used analysis of the area under the curve of receiver operating characteristic curves to compare the ability of CCL18, PAI-1, CD44, and BTA to detect BCa in voided urine samples. Urinary concentrations of CCL18, PAI-1, and BTA were significantly elevated in subjects with BCa. CCL18 was the most accurate biomarker (AUC; 0.919; 95% confidence interval [CI], 0.8704-0.9674). Multivariate regression analysis highlighted CCL18 (OR; 18.31; 95% CI, 4.95-67.70, p<0.0001) and BTA (OR; 6.43; 95% CI, 1.86-22.21, p = 0.0033) as independent predictors of BCa in voided urine samples. The combination of CCL18, PAI-1 and CD44 improved the area under the curve to0.938. Preliminary results indicate that CCL18 was a highly accurate biomarker for BCa detection in this cohort. Monitoring CCL18 in voided urine samples has the potential to improve non-invasive tests for BCa diagnosis. Furthermore using the combination of CCL18, PAI-1 and CD44 may make the model more robust to errors to detect BCa over the individual biomarkers or BTA.