Chemokines, including chemokine (C-X-C motif) ligand 1 (CXCL1), may regulate tumor epithelial-stromal interactions that facilitate tumor growth and invasion. Studies have linked CXCL1 expression to gastric, colon and skin cancers, but limited studies to date have described CXCL1 protein expression in human bladder cancer (BCa).
CXCL1 protein expression was examined in 152 bladder tissue specimens (142 BCa) by immunohistochemical staining. The expression of CXCL1 was scored by assigning a combined score based on the proportion of cells staining and intensity of staining. CXCL1 expression patterns were correlated with clinicopathological features and follow-up data.
CXCL1 protein expression was present in cancerous tissues, but was entirely absent in benign tissue. CXCL1 combined immunostaining score was significantly higher in high-grade tumors relative to low-grade tumors (p = 0.012). Similarly, CXCL1 combined immunostaining score was higher in high stage tumors (T2-T4) than in low stage tumors (Ta-T1) (p < 0.0001). An increase in the combined immunostaining score of CXCL1 was also associated with reduced disease-specific survival.
To date, this is the largest study describing increased CXCL1 protein expression in more aggressive phenotypes in human BCa. Further studies are warranted to define the role CXCL1 plays in bladder carcinogenesis and progression.
Bladder Cancer; Chemokine Ligand 1 (CXCL1); Tumor Grade; Tumor Stage
To investigate whether elevated urinary levels of vascular endothelial growth factor (VEGF), carbonic anhydrase 9 (CA9) and angiogenin are associated with BCa.
This is a case-control study in which voided urines from 127 patients: control subjects (n = 63) and tumor bearing subjects (n = 64) were analyzed. The urinary concentrations of VEGF, CA9, angiogenin and BTA were assessed by enzyme-linked immunosorbent assay (ELISA). We used the area under the curve (AUC) of receiver operating characteristic curves to determine the ability of VEGF, CA9, and angiogenin to detect BCa in voided urine samples. Data were also compared to a commercial ELISA-based BCa detection assay (BTA-Trak©). Sensitivity, specificity, positive and negative predictive values were calculated.
Urinary concentrations of VEGF, CA9, angiogenin and BTA were significantly elevated in BCa. VEGF was the most accurate urinary biomarker (AUC: 0.886; 95% confidence interval [CI]: 0.8301–0.9418). Furthermore, multivariate regression analysis highlighted VEGF (OR: 5.90; 95% CI: 2.60–13.40, p < 0.0001) as an independent variable. The sensitivities and specificities for VEGF (sensitivity, 83% and specificity, 87%) outperformed BTA (sensitivity, 80% and specificity, 84%).
VEGF may be a valuable addition to voided urine sample analysis for the detection of BCa. Larger, prospective studies are needed to determine the clinical utility of urinary VEGF and angiogenin as biomarkers in the non-invasive evaluation of BCa patients.
angiogenin; bladder cancer; biomarkers; diagnosis; VEGF
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.
Mycoplasma hyorhinis is a eubacterium belonging to the Mollicutes class and is responsible for porcine respiratory and arthritic diseases. It is also the major contaminant of mammalian tissue cultures in laboratories worldwide. Here, we report the complete genome sequence of M. hyorhinis strain SK76.
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.
We have previously demonstrated that prostate tumors that highly express Bcl-2 are not only more tumorigenic, but also more angiogenic than low Bcl-2 expressing tumors. Observed increased rates of angiogenesis are likely due to the secretion of multiple factors from the tumor cells.
Human endothelial cells were subjected to exogenous VEGF or conditioned media from PC-3 cells and assayed by several in vitro systems to better characterize the eVects of tumor microenvironment on endothelial cells.
VEGF stimulation increased Bcl-2 expression in human microvascular endothelial cells (HMVECs), at least partially through stabilization of Bcl-2 mRNA transcripts, and protected these cells from apoptosis. These effects were mimicked by treatment of HMVECs with conditioned media from cultured PC-3 prostate tumor cells manipulated to overexpress Bcl-2. Through the use of kinase inhibitors and molecular profiling, several distinct pathways were implicated in the regulation of Bcl-2 in HMVECs, including those involving PI3K/AKT, PKC, mTOR, STAT-1, and IL-8, factors associated with tumor survival and growth.
This study identifies molecular elements of a link between Bcl-2 expression in distinct cell types within a tumor and reaffirms that strategies designed to target Bcl-2 are desirable as they might enhance treatment response through dual effects.
Bcl-2; VEGF; Angiogenesis; Cancer; Gene expression; Prostate
Proteomic profiling of an experimental tumor metastasis model has the potential to identify gene products that can influence this fatal phenotype of tumor cells. In this study, we focused on the notoriously difficult to assess ribosomal protein component of a pair of cell lines which originate from the same tumor but have opposite metastatic capabilities.
Materials and Methods
Cell lysate proteins were separated using a two-dimensional liquid chromatographic system directly coupled to an ESI-TOF mass spectrometer for accurate intact protein MW analysis. Characterization of distinct post-translational modifications and sequence variation within several ribosomal proteins was obtained using monolithic capillary LC/MS/MS, MALDI-MS and -MS/MS.
The combination of these techniques enabled the identification of 45 unique ribosomal proteins, several of which were differentially expressed in metastatic M4A4 cells.
The described proteomic profiling approach enables the identification of phenotype-associated ribosomal proteins for subsequent functional analyses and disease biomarker development.
Ribosomal proteins; cancer biomarkers; electrospray ionization time-of-flight mass spectrometry; liquid chromatography; monolith
The ability to detect and monitor bladder cancer in noninvasively obtained urine samples is a major goal. While a number of protein biomarkers have been identified and commercially developed, none have greatly improved the accuracy of sample evaluation over invasive cystoscopy. The ongoing development of high-throughput proteomic profiling technologies will facilitate the identification of molecular signatures that are associated with bladder disease. The appropriate use of these approaches has the potential to provide efficient biomarkers for the early detection and monitoring of recurrent bladder cancer. Identification of disease-associated proteins will also advance our knowledge of tumor biology, which, in turn, will enable development of targeted therapeutics aimed at reducing morbidity from bladder cancer. In this article, we focus on the accumulating proteomic signatures of urine in health and disease, and discuss expected future developments in this field of research.
biomarker; bladder cancer detection; molecular signature; oncoproteomics; urinalysis
The ability to predict the metastatic behavior of a patient’s cancer, as well as to detect and eradicate such recurrences, remain major clinical challenges in oncology. While many potential molecular biomarkers have been identified and tested previously, none have greatly improved the accuracy of specimen evaluation over routine histopathological criteria and, to date, they predict individual outcomes poorly. The ongoing development of high-throughput proteomic profiling technologies is opening new avenues for the investigation of cancer and, through application in tissue-based studies and animal models, will facilitate the identification of molecular signatures that are associated with breast tumor cell phenotype. The appropriate use of these approaches has the potential to provide efficient biomarkers, and to improve our knowledge of tumor biology. This, in turn, will enable the development of targeted therapeutics aimed at ameliorating the lethal dissemination of breast cancer. In this review, we focus on the accumulating proteomic signatures of breast tumor progression, particularly those that correlate with the occurrence of distant metastases, and discuss some of the expected future developments in the field.
2D separation; biomarkers; breast cancer; laser-capture microdissection; molecular prognostics; oncoproteomics; tissue microarray
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.
Current urine-based assays for bladder cancer (BCa) diagnosis lack accuracy, so the search for improved biomarkers continues. Through genomic and proteomic profiling of urine, we have identified a panel of biomarkers associated with the presence of BCa. In this study, we evaluated the utility of three of these biomarkers, interleukin 8 (IL-8), Matrix metallopeptidase 9 (MMP-9) and Syndecan in the diagnosis of BCa through urinalysis.
Voided urines from 127 subjects, cancer subjects (n = 64), non-cancer subjects (n = 63) were analyzed. The protein concentrations of IL-8, MMP-9, and Syndecan were assessed by enzyme-linked immunosorbent assay (ELISA). Data were also compared to a commercial ELISA-based BCa detection assay (BTA-Trak©) and urinary cytology. We used the area under the curve of a receiver operating characteristic (AUROC) to compare the performance of each biomarker.
Urinary protein concentrations of IL-8, MMP-9 and BTA were significantly elevated in BCa subjects. Of the experimental markers compared to BTA-Trak©, IL-8 was the most prominent marker (AUC; 0.79; 95% confidence interval [CI], 0.72-0.86). Multivariate regression analysis revealed that only IL-8 (OR; 1.51; 95% CI, 1.16-1.97, p = 0.002) was an independent factor for the detection of BCa.
These results suggest that the measurement of IL-8 in voided urinary samples may have utility for urine-based detection of BCa. These findings need to be confirmed in a larger, prospective cohort.
IL-8; Biomarkers; Diagnosis; Bladder cancer
The ability to compare genome-wide expression profiles in human tissue samples has the potential to add an invaluable molecular pathology aspect to the detection and evaluation of multiple diseases. Applications include initial diagnosis, evaluation of disease subtype, monitoring of response to therapy and the prediction of disease recurrence. The derivation of molecular signatures that can predict tumor recurrence in breast cancer has been a particularly intense area of investigation and a number of studies have shown that molecular signatures can outperform currently used clinicopathologic factors in predicting relapse in this disease. However, many of these predictive models have been derived using relatively simple computational algorithms and whether these models are at a stage of development worthy of large-cohort clinical trial validation is currently a subject of debate. In this review, we focus on the derivation of optimal molecular signatures from high-dimensional data and discuss some of the expected future developments in the field.
Previous studies have demonstrated the potential value of gene expression signatures in assessing the risk of post-surgical breast cancer recurrence, however, many of these predictive models have been derived using simple computational algorithms and validated internally or using one-way validation on a single dataset. We have recently developed a new feature selection algorithm that overcomes some limitations inherent to high-dimensional data analysis. In this study, we applied this algorithm to two publicly available gene expression datasets obtained from over 400 patients with breast cancer to investigate whether we could derive more accurate prognostic signatures and reveal common predictive factors across independent datasets. We compared the performance of three advanced computational algorithms using a robust two-way validation method, where one dataset was used for training and to establish a prediction model that was then blindly tested on the other dataset. The experiment was then repeated in the reverse direction. Analyses identified prognostic signatures that while comprised of only 10–13 genes, significantly outperformed previously reported signatures for breast cancer evaluation. The cross-validation approach revealed CEGP1 and PRAME as major candidates for breast cancer biomarker development.
Microarray; Breast cancer prognosis; Predictive model; PRAME
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 α-1B-glycoprotein that was detected in all tumor-bearing patient samples but in none of the samples obtained from non-tumor-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.
glycosylation; bladder cancer; lectin
A combination of LC and MS was applied to an isogenic breast tumor metastasis model to identify proteins associated with a cellular phenotype. Chromatofocusing followed by nonporous-RP-HPLC/ESI-TOF MS was applied to cell lysates of a pair of monoclonal cell lines from the human breast carcinoma cell line MDA-MB-435 that have different metastatic phenotypes in immune-compromised mice. This method was developed to separate proteins based on pI and hydrophobicity. The high resolution and mass accuracy of ESI-TOF measurements provided a good correlation of theoretical MW and experimental Mr values of intact proteins measured in mass maps obtained in the pH range 3.8–6.4. The isolated proteins were digested by trypsin and analyzed by MALDI-TOF MS, MALDI-QIT-TOF MS, and monolith-based HPLC/MS/MS. The unique combination of the techniques provided valuable information including quantitation and modification of proteins. We identified 89 selected proteins, of which 43 were confirmed as differentially expressed. Metastasis-associated proteins included galectin-1, whereas annexin I and annexin II were associated with the nonmetastatic phenotype. In this study, we demonstrate that combining a variety of MS tools with a multidimensional liquid-phase separation provides the ability to map cellular protein content, to search for modified proteins, and to correlate protein expression with cellular phenotype.
Cancer biomarkers; Electrospray ionization time-of-flight mass spectrometry; Liquid chromatography; Metastasis; Monolith
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)
For most cancer cell types, the acquisition of metastatic ability leads to clinically incurable disease. The identification of molecules whose expression is specifically correlated with the metastatic spread of cancer would facilitate the design of therapeutic interventions to inhibit this lethal process. In order to facilitate metastasis gene discovery we have previously characterized a pair of monoclonal cell lines from the human breast carcinoma cell line MDA-MB-435 that have different metastatic phenotypes in immune-compromised mice. In this study, serum-free conditioned media was collected from the cultured monoclonal cell lines and a mass mapping technique was applied in order to profile a component of each cell line proteome. We utilized chromatofocusing in the first dimension to obtain a high resolution separation based on protein pI, and nonporous silica reverse-phase high performance liquid chromatography was used for the second dimension. Selected proteins were identified on the basis of electrospray ionization time of flight mass spectrometry (ESI-TOF MS) intact protein mapping and matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) peptide mass fingerprinting. Using this approach we were able to map over 400 proteins and plot them as a 2-D map of pI versus accurate Mr. This was performed over a pI range of 4.0–6.2, and a mass range of 6–80 kDa. ESI-TOF MS data and further analysis using MALDI-TOF MS confirmed and identified 27 differentially expressed proteins. Proteins associated with the metastatic phenotype included osteopontin and extracellular matrix protein 1, whereas the matrix metalloproteinase-1 and annexin 1 proteins were associated with the non-metastatic phenotype. These findings demonstrate that the mass mapping technique is a powerful tool for the detection and identification of proteins in complex biological samples and which are specifically associated with a cellular phenotype.
Biomarkers ; Breast tumor metastasis mass mapping; CF, chromato-focusing; NPS, nonporous silica
In order to facilitate the identification of genes involved in the metastatic phenotype we have previously developed a pair of cell lines from the human breast carcinoma cell line MDA-MB-435, which have diametrically opposite metastatic potential in athymic mice. Differential display analysis of this model previously identified a novel gene, DRIM (down regulated in metastasis), the decreased expression of which correlated with metastatic capability. DRIM encodes a protein comprising 2785 amino acids with significant homology to a protein in yeast and C. elegans, but little else is currently known about its function or pattern of expression. In a detailed analysis of the DRIM gene locus we quantitatively evaluated gene dosage and the expression of DRIM transcripts in a panel of breast cell lines of known metastatic phenotype.
Fluorescent in situ hybridization (FISH) analyses mapped a single DRIM gene locus to human chromosome 12q23~24, a region of conserved synteny to mouse chromosome 10. We confirmed higher expression of DRIM mRNA in the non-metastatic MDA-MB-435 clone NM2C5, relative to its metastatic counterpart M4A4, but this appeared to be due to the presence of an extra copy of the DRIM gene in the cell line's genome. The other non-metastatic cell lines in the series (T47D MCF-7, SK-BR-3 and ZR-75-1) contained either 3 or 4 chromosomal copies of DRIM gene. However, the expression level of DRIM mRNA in M4A4 was found to be 2–4 fold higher than in unrelated breast cells of non-metastatic phenotype.
Whilst DRIM expression is decreased in metastatic M4A4 cells relative to its non-metastatic isogenic counterpart, neither DRIM gene dosage nor DRIM mRNA levels correlated with metastatic propensity in a series of human breast tumor cell lines examined. Collectively, these findings indicate that the expression pattern of the DRIM gene in relation to the pathogenesis of breast tumor metastasis is more complex than previously recognized.
Our previous characterization of a human breast tumor metastasis model identified several candidate metastasis genes. The expression of osteopontin (OPN) correlated with the metastatic phenotype, whereas thrombospondin-1 (TSP-1) and tyrosinase-related protein-1 (TYRP-1) correlated with the nonmetastatic phenotype of independent MDA-MB-435 cell lines implanted orthotopically into athymic mice. The aim of the present study was to examine the cellular distribution of these molecules in human breast tissue and to determine whether the relative expression level of these three genes is associated with human breast tumor metastasis.
Sixty-eight fresh, frozen specimens including 31 primary infiltrating ductal carcinomas, 22 nodal metastases, 10 fibroadenomas, and five normal breast tissues were evaluated for OPN expression, TSP-1 expression and TYRP-1 expression. Immunohistochemistry was performed to monitor the cellular distribution and to qualitatively assess expression. Quantitative analysis was achieved by enrichment of breast epithelial cells using laser-capture microdissection and subsequent real-time, quantitative PCR.
The epithelial components of the breast tissue were the source of OPN and TSP-1 expression, whereas TYRP-1 was present in both the epithelial and stromal components. Both OPN and TSP-1 expression were significantly higher in malignant epithelial sources over normal and benign epithelial sources, but no difference in expression levels was evident between primary tumors with or without metastases, nor between primary and metastatic carcinomas.
Elevated expression of OPN and TSP-1 may play a role in the pathogenesis of breast cancer. The multiplex analysis of these molecules may enhance our ability to diagnose and/or prognosticate human breast malignancy.
breast carcinoma; immunohistochemistry; metastasis; microdissection; quantitative PCR