As molecular profiling data continues to accumulate, the design of integrative computational analyses that can provide insights into the dynamic aspects of cancer progression becomes feasible. Here, we present a novel computational method for the construction of cancer progression models based on the analysis of static tumor samples. We demonstrate the reliability of the method with simulated data, and describe the application to breast cancer data. Our findings support a linear, branching model for breast cancer progression. An interactive model facilitates the identification of key molecular events in the advance of disease to malignancy.
BackgroundTo validate the expression of a urine-based bladder cancer associated diagnostic signature comprised of 10 targets; ANG, CA9, MMP9, MMP10, SERPINA1, APOE, SDC1, VEGFA, SERPINE1 and IL8 in bladder tumor tissues.MethodsImmunohistochemical analyses were performed on tumor specimens from 213 bladder cancer patients (transitional cell carcinoma only) and 74 controls. Staining patterns were digitally captured and quantitated (Aperio, Vista, CA), and expression was correlated with tumor stage, tumor grade and outcome measures.ResultsWe revealed a positive association of 9 of the 10 proteins (excluding VEGF) in bladder cancer. Relative to control cases, a reduction in SDC1 and overexpression of MMP9, MMP10, SERPINE1, IL8, APOE, SERPINA1, ANG were associated with high stage bladder cancer. Reduced VEGF and increased SERPINA1 were associated with high-grade bladder cancer. Disease-specific survival was significantly reduced in tumors with high expression of SERPINE1 and/or IL8.ConclusionsThese findings confirm that the proteins in a urine-based diagnostic signature are aberrantly expressed in bladder tumor tissues, and support the potential additional utility of selected biomarkers for the clinicopathological evaluation of excised tissue or biopsy material.Virtual SlidesThe virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/13000_2014_200.
Because of the faltering sensitivity and/or specificity, urine-based assays currently have a limited role in the management of patients with bladder cancer. The aim of this study was to externally validate our previously reported protein biomarker panel from multiple sites in the United States and Europe.
Up to 70% of patients with non-muscle-invasive bladder cancer (NMIBC) experience disease recurrence, making it one of the most prevalent cancers in the United States. The purpose of this study was to test the performance of a multiplex urinary biomarker assay for the monitoring of voided urine for recurrent bladder cancer.
The ability to accurately measure multiple proteins simultaneously in a single assay has the potential to markedly improve the efficiency of a myriad of clinical assays. Here, we tested the performance of a new, multiplex protein array platform to quantitate three bladder cancer-associated proteins in urine samples. The following analytes, interleukin 8 (IL8), matrix metallopeptidase 9 (MMP9), and vascular endothelial growth factor A (VEGFA) were monitored using Q-plex, a customized multiplex ELISA system from Quansys Biosciences, and individual target commercial ELISA kits. The performance of the two approaches was compared by evaluating the diagnostic accuracy of the biomarker assays in samples from a cohort of 73 subjects of known bladder cancer status.
Tumor angiogenesis is essential for tumor growth and metastasis and is dependent on key angiogenic factors. Angiogenin (ANG), a 14.2-kDa polypeptide member of the RNase A superfamily, is an angiogenic protein that has been reported to be upregulated and associated with poor prognosis in some human cancers. The mechanisms through which aberrant ANG levels promote specific steps in tumor progression are unknown. Here, we show that ANG expression in human tissues is strongly correlated with an invasive cancer phenotype. We also show that ANG induces cellular survival, proliferation, endothelial tube formation and xenograft angiogenesis and growth. Novel mechanistic investigations revealed that ANG expression stimulated matrix metallopeptidase-2 (MMP2) expression through the phosphorylation of ERK1/2. Targeting ANG in vivo with N65828, a small-molecule inhibitor of the ribonucleolytic activity of human ANG, resulted in the diminution of xenograft tumoral growth through the inhibition of angiogenesis. Our findings support an unrecognized interplay between ANG, ERK1/2 and MMP2 that can impact tumor growth and progression. The targeting of ANG and associated factors could provide a novel strategy to inhibit tumor establishment and growth.Oncogene advance online publication, 24 February 2014; doi:10.1038/onc.2014.2.
While significant progress continues to be made in the early detection and therapeutic management of primary tumors, the incidence of metastatic disease remains the major cause of mortality. Accordingly, the development of novel effective therapies that can ameliorate dissemination and secondary tumor growth are a clinical priority. The identification of genetic and functional alterations in cancer cells that affect factors implicated in the metastatic process is critical for designing preventive and therapeutic strategies. Evidence implicating the protein deleted in liver cancer-1 (DLC1), a Rho GTPase activator, in metastasis has accumulated to a point where DLC1 may be considered as a metastasis suppressor gene. This review presents evidence supporting an anti-metastatic role for DLC1 in several human cancers and discusses the mechanisms contributing to its inhibitory effects. In addition, promising opportunities for therapeutic interventions based on DLC1 function and downstream pathways involved in the metastatic process are considered.
The canonical function of plasminogen activator inhibitor-1 (PAI-1/SERPINE1) is as an inhibitor of urokinase-type plasminogen activator for blood clot maintenance, but it is now also considered a pleiotropic factor that can exert diverse cellular and tumorigenic effects. However, the mechanism controlling its pleiotropic effects is far from being understood. To elucidate the tumorigenic role of PAI-1, we tested the effects of PAI-1 after manipulation of its expression or through the use of a small-molecule inhibitor, tiplaxtinin. Downregulation of PAI-1 significantly reduced cellular proliferation through an inability to progress from the G(0-G1) phase of the cell cycle. Accordingly, overexpression of PAI-1 augmented proliferation by encouraging S-phase entry. Biochemically, cell-cycle arrest was associated with the depletion of the G(1)-phase transition complexes, cyclin D3/cdk4/6 and cyclin E/cdk2, in parallel with the upregulation of the cell-cycle inhibitors p53, p21Cip1/Waf1, and p27Kip1. PAI-1 depletion significantly decreased the tumor size of urothelial T24 and UM-UC-14 xenografts, and overexpression of PAI-1 substantially increased the tumor size of HeLa xenografts. Finally, immunohistochemical analysis of human bladder and cervical tumor tissue microarrays revealed increased expression of PAI-1 in cancerous tissue, specifically in aggressive tumors, supporting the relevance of this molecule in human tumor biology. Implications: Targeting PAI-1 has beneficial antitumoral effects and should be further investigated clinically.
Cancer invasion and metastasis develops through a series of steps that involve the loss of cell to cell and cell to matrix adhesion, degradation of extracellular matrix and induction of angiogenesis. Different protease systems (e.g., matrix metalloproteinases, MMPs) are involved in these steps. MMP-10, one of the lesser studied MMPs, is limited to epithelial cells and can facilitate tumor cell invasion by targeting collagen, elastin and laminin. Enhanced MMP-10 expression has been linked to poor clinical prognosis in some cancers, however, mechanisms underlying a role for MMP-10 in tumorigenesis and progression remain largely unknown. Here, we report that MMP-10 expression is positively correlated with the invasiveness of human cervical and bladder cancers.
Intravesical Bacillus Calmette-Guérin (BCG) has been shown to induce a specific immunologic response (i.e., activation of IL-2 and effector T-cells), while preclinical studies using ALT-803 (mutated IL-15 analogue combined with IL-15R?-Fc fusion) have shown promising results by prolonging the agent's half-life and stimulating CD8+ T-cells. Based on these results, we hypothesized that the intravesical administration of ALT-803 along with BCG will generate an immunologic response leading to significant bladder tumor burden reduction. Using a well-established carcinogen induced rat non-muscle invasive bladder cancer (NMIBC) model, we studied the effects of intravesical ALT-803 with and without BCG. Rat tissues were evaluated to document treatment response. Intravesical ALT-803 was safe and well tolerated alone and in combination with BCG. As a single treatment agent, ALT-803 reduced tumor burden by 35% compared to control whereas BCG alone only reduced tumor burden by 15%. However, the combination of ALT-803 plus BCG reduced tumor burden by 46% compared to control. Immune monitoring suggested that the antitumor response was linked to the production and secretion of IL-1?, IL-1? and RANTES, which in turn, induced the proliferation and activation of NK cells. Lastly, tumoral responses of the combinational treatment were associated with 76% reduction in angiogenesis, which is significantly higher than when assessed with either agent alone. The enhanced therapeutic index seen with this duplet provides justification for the development of this regimen for future clinical trials.
This study was designed to investigate whether an individual and parental history of functional pain syndromes (FPS) is found more often in adolescents suffering from chronic pain than in their pain-free peers.
Bladder cancer is one of the most prevalent cancers worldwide. Early detection of bladder tumors is critical for improved patient outcomes. The standard method for detection and surveillance of bladder tumors is cystoscopy with urinary cytology. Limitations of cystoscopy and urinary cytology have brought to light the need for more robust diagnostic assays. Ideally, such assays would be applicable to noninvasively obtained, voided urine, and be designed not only for diagnosis, but also for monitoring disease recurrence and response to therapy. Consequently, the development of a noninvasive urine-based assay would be of tremendous benefit to both patients and healthcare systems. This article reports some of the more prominent urine-based biomarkers reported in the literature. In addition, some new technologies that have been used to identify novel urinary biomarkers are highlighted.
Erythropoietin (EPO) provides an alternative to transfusion for increasing red blood cell mass and treating anemia in cancer patients. However, recent studies have reported increased adverse events and/or reduced survival in patients receiving both EPO and chemotherapy, potentially related to EPO-induced cancer progression. Additional preclinical studies that elucidate the possible mechanism underlying EPO cellular growth stimulation are needed.
The small molecule, Tolfenamic acid (TA) has shown anti-cancer activity in pre-clinical models and is currently in Phase I clinical trials at MD Anderson Cancer Center Orlando. Since specificity and toxicity are major concerns for investigational agents, we tested the effect of TA on specific targets, and assessed the cellular and organismal toxicity representing pre-clinical studies in cancer.
Accurate urine assays for bladder cancer detection would benefit patients and health care systems. Through extensive genomic and proteomic profiling of urine components we previously identified a panel of 8 biomarkers that can facilitate the detection of bladder cancer in voided urine samples. In this study we confirmed this diagnostic molecular signature in a diverse multicenter cohort.
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.
In this study, we further investigated the association of two biomarkers, CCL18 and A1AT, with bladder cancer (BCa) and evaluated the influence of potentially confounding factors in an experimental model.
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).
Chemokines, including chemokine (C-X-C motif) ligand 1 (CXCL1), may enhance tumor epithelial-stromal interactions facilitating tumor growth and invasion. Studies have linked CXCL1 expression to gastric, colon and skin cancers, however, no study to date has been reported describing CXCL1 in human prostate tumors. Herein, we set out to describe the expression pattern of CXCL1 in human prostate tumors. Utilizing a commercial tissue microarray, immunohistochemical staining was used to monitor CXCL1 protein expression in 90 primary prostate tumors and 20 benign prostate tissues. CXCL1 protein expression was noted to be predominantly in the cytoplasm of both the benign epithelia glands and cancerous epithelia glands) with >75% of benign or cancerous glands demonstrating immunoreactivity. However, staining intensity was noted to be significantly different between benign and cancerous tissue with 84% of cancerous tissue staining moderate (++) to strong (+++) compared to only 30% of benign prostate samples staining moderate (++) to strong (+++) (p<0.0001). Increased CXCL1 protein levels were associated with higher-grade tumors (Gleason?6 vs. Gleason score 7-10, p=0.038). An increase in CXCL1 protein was present in of high-grade malignancy. Further studies are warranted to clearly define the role of CXCL1 in prostate cancer.
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.
Breast cancer affects one in eight women in the United States, with a mortality rate that is second only to lung cancer. Although chemotherapy is widely used in breast cancer treatment, its side effects remain a challenge. One way to address this problem is through drug delivery by the internalization of cell-type-specific probes. Although nucleic acid aptamers are excellent probes for molecular recognition, only a few studies have demonstrated that aptamers can be internalized into living cells. Therefore, herein we report the development of a cancer-cell-specific DNA aptamer probe, KMF2-1a. By using the cell-SELEX method, this aptamer was selected against breast cancer cell line MCF-10AT1. Our results show that KMF2-1a is internalized efficiently and specifically to the endosome of target breast cancer cells. These results indicate that KMF2-1a is a promising agent for cell-type-specific intracellular delivery with both diagnostic and therapeutic implications.
Mycoplasma genitalium is one of the smallest organisms capable of self-replication and its sequence is considered a starting point for understanding the minimal genome required for life. MG289, a putative phosphonate substrate binding protein, is considered to be one of these essential genes. The crystal structure of MG289 has been solved at 1.95 Å resolution. The structurally identified thiamine binding region reveals possible mechanisms for ligand promiscuity. MG289 was determined to be an extracytoplasmic thiamine binding lipoprotein. Computational analysis, size exclusion chromatography, and small angle X-ray scattering indicates that MG289 homodimerizes in a concentration-dependant manner. Comparisons to the thiamine pyrophosphate binding homolog Cypl reveal insights into the metabolic differences between mycoplasmal species including identifying possible kinases for cofactor phosphorylation and describing the mechanism of thiamine transport into the cell. These results provide a baseline to build our understanding of the minimal metabolic requirements of a living organism.
Previous reports demonstrate that the ?2-integrin (?2) mediates pancreatic ductal adenocarcinoma (PDAC) cell interactions with collagens. We found that while well-differentiated cells use ?2 exclusively to adhere and migrate on collagenI, poorly differentiated PDAC cells demonstrate reduced reliance on, or complete loss of, ?2. Since well-differentiated PDAC lines exhibit reduced in vitro invasion and ?2-blockade suppressed invasion of well-differentiated lines exclusively, we hypothesized that ?2 may suppress the malignant phenotype in PDAC. Accordingly, ectopic expression of ?2 retarded in vitro invasion and maintenance on collagenI exacerbated this effect. Affymetrix profiling revealed that kallikrein-related peptidase-5 (KLK5) was specifically upregulated by ?2, and reduced ?2 and KLK5 expression was observed in poorly differentiated PDAC cells in situ. Accordingly, well-differentiated PDAC lines express KLK5, and KLK5 blockade increased the invasion of KLK5-positive lines. The ?2-cytoplasmic domain was dispensable for these effects, demonstrating that the ?2-ectodomain and KLK5 coordinately regulate a less invasive phenotype in PDAC.
More than one million prostate biopsies are performed in the United States every year. A failure to find cancer is not definitive in a significant percentage of patients due to the presence of equivocal structures or continuing clinical suspicion. We have identified gene expression changes in stroma that can detect tumor nearby. We compared gene expression profiles of 13 biopsies containing stroma near tumor and 15 biopsies from volunteers without prostate cancer. About 3,800 significant expression changes were found and thereafter filtered using independent expression profiles to eliminate possible age-related genes and genes expressed at detectable levels in tumor cells. A stroma-specific classifier for nearby tumor was constructed on the basis of 114 candidate genes and tested on 364 independent samples including 243 tumor-bearing samples and 121 nontumor samples (normal biopsies, normal autopsies, remote stroma, as well as stroma within a few millimeters of tumor). The classifier predicted the tumor status of patients using tumor-free samples with an average accuracy of 97% (sensitivity = 98% and specificity = 88%) whereas classifiers trained with sets of 100 randomly generated genes had no diagnostic value. These results indicate that the prostate cancer microenvironment exhibits reproducible changes useful for categorizing the presence of tumor in patients when a prostate sample is derived from near the tumor but does not contain any recognizable tumor.
Gold nanoparticles (AuNPs) scatter light intensely at or near their surface plasmon wavelength region. Using AuNPs coupled with dynamic light scattering (DLS) detection, we developed a facile nanoparticle immunoassay for serum protein biomarker detection and analysis. A serum sample was first mixed with a citrate-protected AuNP solution. Proteins from the serum were adsorbed to the AuNPs to form a protein corona on the nanoparticle surface. An antibody solution was then added to the assay solution to analyze the target proteins of interest that are present in the protein corona. The protein corona formation and the subsequent binding of antibody to the target proteins in the protein corona were detected by DLS.
Cancers of the urinary bladder are the fifth most commonly diagnosed malignancy in the United States. Early clinical diagnosis of bladder cancer remains a major challenge, and the development of noninvasive methods for detection and surveillance is desirable for both patients and health care providers.
Recent epidemiologic, genetic, and molecular studies suggest infection and inflammation initiate certain cancers, including cancers of the prostate. Over the past several years, our group has been studying how mycoplasmas could possibly initiate and propagate cancers of the prostate. Specifically, Mycoplasma hyorhinis encoded protein p37 was found to promote invasion of prostate cancer cells and cause changes in growth, morphology and gene expression of these cells to a more aggressive phenotype. Moreover, we found that chronic exposure of benign human prostate cells to M. hyorhinis resulted in significant phenotypic and karyotypic changes that ultimately resulted in the malignant transformation of the benign cells. In this study, we set out to investigate another potential link between mycoplasma and human prostate cancer.
Transcription factors are proteins that regulate gene expression by binding to specific DNA sequences within gene promoter regions. Specificity protein (Sp) family transcription factors play a critical role in various cellular processes and have been shown to be associated with tumorigenesis. The Sp family consists of several members that contain a highly conserved DNA-binding domain composed of three zinc fingers at the C-terminus and serine/threonine- and glutamine-rich transactivation domains at the N-terminal. Sp1 is elevated in several cancers including prostate and is associated with the prognosis of patients. Sp1, Sp3, and Sp4 regulate a variety of cancer associated genes that are involved in cell cycle, proliferation, cell differentiation, and apoptosis. Studies have shown that in prostate cancer, Sp1 regulates important genes like androgen receptor, TGF-?, c-Met, fatty acid synthase, matrix metalloprotein (MT1-MMP), PSA, and ?-integrin. These results highlight the importance of Sp1 in prostate cancer and emphasize the potential therapeutic value of targeting Sp1. Several strategies, including the use of natural and synthetic compounds, have been used to inhibit Sp1 in prostate cancer. These include polyphenol quercetin, betulinic acid, acetyl-11-keto-beta-boswellic acid, tea phenols, isothiocyanates, thiazolidinediones, arsenic trioxide, and selenium. This review will describe the association of Sp proteins in prostate cancer with a special emphasis on some of the agents tested to target Sp proteins for the treatment of this malignancy.
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.
With the aid of next-generation sequencing technology, researchers can now obtain millions of microbial signature sequences for diverse applications ranging from human epidemiological studies to global ocean surveys. The development of advanced computational strategies to maximally extract pertinent information from massive nucleotide data has become a major focus of the bioinformatics community. Here, we describe a novel analytical strategy including discriminant and topology analyses that enables researchers to deeply investigate the hidden world of microbial communities, far beyond basic microbial diversity estimation. We demonstrate the utility of our approach through a computational study performed on a previously published massive human gut 16S rRNA data set. The application of discriminant and topology analyses enabled us to derive quantitative disease-associated microbial signatures and describe microbial community structure in far more detail than previously achievable. Our approach provides rigorous statistical tools for sequence-based studies aimed at elucidating associations between known or unknown organisms and a variety of physiological or environmental conditions.
This paper considers feature selection for data classification in the presence of a huge number of irrelevant features. We propose a new feature-selection algorithm that addresses several major issues with prior work, including problems with algorithm implementation, computational complexity, and solution accuracy. The key idea is to decompose an arbitrarily complex nonlinear problem into a set of locally linear ones through local learning, and then learn feature relevance globally within the large margin framework. The proposed algorithm is based on well-established machine learning and numerical analysis techniques, without making any assumptions about the underlying data distribution. It is capable of processing many thousands of features within minutes on a personal computer while maintaining a very high accuracy that is nearly insensitive to a growing number of irrelevant features. Theoretical analyses of the algorithms sample complexity suggest that the algorithm has a logarithmical sample complexity with respect to the number of features. Experiments on 11 synthetic and real-world data sets demonstrate the viability of our formulation of the feature-selection problem for supervised learning and the effectiveness of our algorithm.
Alterations in cellular phosphorylation patterns have been implicated in a number of diseases, including cancer, through multiple mechanisms. Herein we present a survey of the phosphorylation profiles of an isogenic pair of human cancer cell lines with opposite metastatic phenotype. Phosphopeptides were enriched from tumor cell lysates with titanium dioxide and zirconium dioxide, and identified with nano-LC-MS/MS using an automatic cross-validation of MS/MS and MS/MS/MS (MS2+MS3) data-dependent neutral loss method. A spectral counting quantitative strategy was applied to the two cell line samples on the MS2-only scan, which was implemented successively after each MS2+MS3 scan in the same sample. For all regulated phosphopeptides reported by spectral counting analysis, sequence and phosphorylation site assignments were validated by a MS2+MS3 data-dependent neutral loss method. With this approach, we identified over 70 phosphorylated sites on 27 phosphoproteins as being differentially expressed with respect to tumor cell phenotype. The altered expression levels of proteins identified by LC-MS/MS were validated using Western blotting. Using network pathway analysis, we observed that the majority of the differentially expressed proteins were highly interconnected and belong to two major intracellular signaling pathways. Our findings suggest that the phosphorylation of isoform A of lamin A/C and GTPase activating protein binding protein 1 is associated with metastatic propensity. The study demonstrates a quantitative and comparative proteomics strategy to identify differential phosphorylation patterns in complex biological samples.
We have identified the nonreceptor tyrosine kinase syk as a marker of differentiation/tumor suppressor in pancreatic ductal adenocarcinoma (PDAC). Syk expression is lost in poorly differentiated PDAC cells in vitro and in situ, and stable reexpression of syk in endogenously syk-negative Panc1 (Panc1/syk) cells retarded their growth in vitro and in vivo and reduced anchorage-independent growth in vitro. Panc1/syk cells exhibited a more differentiated morphology and down-regulated cyclin D1, akt, and CD171, which are overexpressed by Panc1 cells. Loss of PDAC syk expression in culture is due to promoter methylation, and reversal of promoter methylation caused reexpression of syk and concomitant down-regulation of CD171. Moreover, suppression of syk expression in BxPC3 cells caused de novo CD171 expression, consistent with the reciprocal expression of syk and CD171 we observe in situ. Importantly, Panc1/syk cells demonstrated dramatically reduced invasion in vitro. Affymetrix analysis identified statistically significant regulation of >2000 gene products by syk in Panc1 cells. Of these, matrix metalloproteinase-2 (MMP2) and tissue inhibitor of metalloproteinase-2 were down-regulated, suggesting that the MMP2 axis might mediate Panc1/mock invasion. Accordingly, MMP2 inhibition suppressed the in vitro invasion of Panc1/mock cells without effect on Panc1/syk cells. This study demonstrates a prominent role for syk in regulating the differentiation state and invasive phenotype of PDAC cells.
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.
Classification of cancers based on gene expressions produces better accuracy when compared to that of the clinical markers. Feature selection improves the accuracy of these classification algorithms by reducing the chance of overfitting that happens due to large number of features. We develop a new feature selection method called Biological Pathway-based Feature Selection (BPFS) for microarray data. Unlike most of the existing methods, our method integrates signaling and gene regulatory pathways with gene expression data to minimize the chance of overfitting of the method and to improve the test accuracy. Thus, BPFS selects a biologically meaningful feature set that is minimally redundant. Our experiments on published breast cancer datasets demonstrate that all of the top 20 genes found by our method are associated with cancer. Furthermore, the classification accuracy of our signature is up to 18% better than that of vant Veers 70 gene signature, and it is up to 8% better accuracy than the best published feature selection method, I-RELIEF.
Bladder cancer is one of the most prevalent cancers worldwide. Furthermore, nonmuscle invasive bladder cancer has a 70% rate of recurrence, making it a considerable strain to the healthcare system. Patients with bladder cancer require repeat cystoscopic examinations of the bladder to monitor for tumor recurrence. The reason these patients have to undergo these costly, painful, invasive procedures is owing to the absence of accurate urine-based assays to detect the presence of bladder cancer noninvasively. Consequently, the development of a urine-based test to detect bladder cancer would be of tremendous benefit to both patients and healthcare systems. This article reports some of the more prominent urine markers in use today. In addition, the article will highlight some new technologies that are used to investigate novel urinary markers.
Recent epidemiologic, genetic, and molecular studies suggest infection and inflammation initiate certain cancers, including those of the prostate. The American Cancer Society, estimates that approximately 20% of all worldwide cancers are caused by infection. Mycoplasma, a genus of bacteria that lack a cell wall, are among the few prokaryotes that can grow in close relationship with mammalian cells, often without any apparent pathology, for extended periods of time. In this study, the capacity of Mycoplasma genitalium, a prevalent sexually transmitted infection, and Mycoplasma hyorhinis, a mycoplasma found at unusually high frequency among patients with AIDS, to induce a malignant phenotype in benign human prostate cells (BPH-1) was evaluated using a series of in vitro and in vivo assays. After 19 weeks of culture, infected BPH-1 cells achieved anchorage-independent growth and increased migration and invasion. Malignant transformation of infected BPH-1 cells was confirmed by the formation of xenograft tumors in athymic mice. Associated with these changes was an increase in karyotypic entropy, evident by the accumulation of chromosomal aberrations and polysomy. This is the first report describing the capacity of M. genitalium or M. hyorhinis infection to lead to the malignant transformation of benign human epithelial cells and may serve as a model to further study the relationship between prostatitis and prostatic carcinogenesis.
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.
Immobilized lectin chromatography can be employed for glycoprotein enrichment, but commonly used columns have limitations of yield and resolution. To improve efficiency and to make the technique applicable to minimal sample material, we have developed a nanoscale chelating Concanavalin A (Con A) monolithic capillary prepared using GMA-EDMA (glycidyl methacrylate-co-ethylene dimethacrylate) as polymeric support. Con A was immobilized on Cu(II)-charged iminodiacetic acid (IDA) regenerable sorbents by forming a IDA:Cu(II):Con A sandwich affinity structure that has high column capacity, as well as stability. When compared with conventional Con A lectin chromatography, the monolithic capillary enabled the better reproducible detection of over double the number of unique N-glycoproteins in human urine samples. Utility for analysis of minimal biological samples was confirmed by the successful elucidation of glycoprotein profiles in mouse urine samples at the microliter scale. The improved efficiency of the nanoscale monolithic capillary will impact the analysis of glycoproteins in complex biological samples, especially where only limited material may be available.
We previously demonstrated that Bcl-2 overexpression stimulates angiogenesis in PC-3 human prostate cancer cells, thus giving these tumors a growth advantage. To further elucidate the relationship between Bcl-2 and vascular endothelial growth factor (VEGF) in PC-3-Bcl-2 cells, tumorigenicity and angiogenesis were evaluated in our in vitro and in vivo model treated with antisense Bcl-2 oligodeoxynucleotide (ASO) and bevacizumab. In vitro and in vivo angiogenesis assays, as well as a xenograft tumor model of the human prostate cancer cell line PC-3-Bcl-2, were subjected to ASO alone, bevacizumab alone, or the combination of ASO and bevacizumab. Protein-based assays (e.g., immunohistochemical staining and enzyme-linked immunosorbent assay [ELISA]) were utilized to detect molecular changes. Interestingly, targeting Bcl-2 with ASO resulted in the inhibition of in vitro tube formation and inhibition of angiogenesis in Matrigel plugs similar to treatment with bevacizumab. In our PC-3-Bcl-2 xenograft model, ASO alone resulted in 41% reduction in tumor size, bevacizumab alone resulted in a 50% reduction in tumor size, whereas the combination of ASO with bevacizumab was associated with >95% reduction in tumor volume. Reduction in tumor size in all groups was associated with reduction in Bcl-2 and VEGF expression, induction of apoptosis, and inhibition of angiogenesis and its associated chemokine production. These findings confirm that Bcl-2 is a pivotal target for cancer therapy and thus, further study of this novel combination of Bcl-2 reduction and angiogenic targeting in human tumors is warranted.
We previously demonstrated that Bcl-2 overexpression enhances the radiation resistance of PC-3 human prostate cancer cells and xenografts by inhibiting apoptosis, increasing proliferation, and promoting angiogenesis. To further elucidate the relationship between Bcl-2 expression and the angiogenic potential of PC-3-Bcl-2 cells, tumorigenicity, angiogenesis, and lymphangiogenesis were evaluated and compared in a Bcl-2 overexpressing clone in vitro and in vivo.
The Mycoplasma hyorhinis protein p37 has been implicated in tumorigenic transformation for more than 20 years. Though there are many speculations as to its function, based solely on sequence homology, the issue has remained unresolved. Presented here is the 1.6-A-resolution refined crystal structure of M. hyorhinis p37, renamed the extracytoplasmic thiamine-binding lipoprotein (Cypl). The structure shows thiamine pyrophosphate (TPP) and two calcium ions are bound to Cypl and give the first insights into possible functions of the Cypl-like family of proteins. Sequence alignments of Cypl-like proteins between several different species of mycoplasma show that the thiamine-binding site is likely conserved and structural alignments reveal the similarity of Cypl to various binding proteins. While the experimentally determined function of Cypl remains unknown, the structure shows that the protein is a TPP-binding protein, opening up many avenues for future mechanistic studies and making Cypl a possible target for combating mycoplasma infections and tumorigenic transformation.
The biological and molecular events that regulate the invasiveness of breast tumour cells need to be further revealed to develop effective therapies that stop breast cancer from expanding and metastasising.
Bladder cancer is the fifth most commonly diagnosed malignancy in the United States and one of the most prevalent worldwide. It harbors a probability of recurrence of >50%; thus, rigorous, long-term surveillance of patients is advocated. Flexible cystoscopy coupled with voided urine cytology is the primary diagnostic approach, but cystoscopy is an uncomfortable, invasive procedure and the sensitivity of voided urine cytology is poor in all but high-grade tumors. Thus, improvements in noninvasive urinalysis assessment strategies would benefit patients. We applied gene expression microarray analysis to exfoliated urothelia recovered from bladder washes obtained prospectively from 46 patients with subsequently confirmed presence or absence of bladder cancer. Data from microarrays containing 56,000 targets was subjected to a panel of statistical analyses to identify bladder cancer-associated gene signatures. Hierarchical clustering and supervised learning algorithms were used to classify samples on the basis of tumor burden. A differentially expressed geneset of 319 gene probes was associated with the presence of bladder cancer (P < 0.01), and visualization of protein interaction networks revealed vascular endothelial growth factor and angiotensinogen as pivotal factors in tumor cells. Supervised machine learning and a cross-validation approach were used to build a 14-gene molecular classifier that was able to classify patients with and without bladder cancer with an overall accuracy of 76%. Our results show that it is possible to achieve the detection of bladder cancer using molecular signatures present in exfoliated tumor urothelia. Further investigation and validation of the cancer-associated profiles may reveal important biomarkers for the noninvasive detection and surveillance of bladder cancer.
Classification and regression trees have long been used for cancer diagnosis and prognosis. Nevertheless, instability and variable selection bias, as well as overfitting, are well-known problems of tree-based methods. In this article, we investigate whether ensemble tree classifiers can ameliorate these difficulties, using data from two recent studies of radical prostatectomy in prostate cancer.
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.
Bladder cancer is among the five most common malignancies worldwide, and due to high rates of recurrence, one of the most prevalent. Improvements in noninvasive urine-based assays to detect bladder cancer would benefit both patients and health care systems. In this study, the goal was to identify urothelial cell transcriptomic signatures associated with bladder cancer.
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 data show 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.
The ability to reliably diagnose bladder cancer in voided urine samples would be a major advance. Using high throughput technologies, we identified a panel of bladder cancer associated biomarkers with potential clinical usefulness. In this study we tested 4 potential biomarkers for the noninvasive detection of bladder cancer.
The commercial NMP-22 urine assays for bladder cancer (BCa) detect nuclear mitotic apparatus protein 1 (NUMA1) using monoclonal antibodies. It remains unclear whether these assays are monitoring a tumor antigen or some other phenomenon associated with the disease state. In this study, we investigated the influence of urinary cellular and protein concentration, and hematuria on the performance of the NMP-22 tests in an experimental model.
Details of metastasis, the deadliest aspect of cancer, are unclear. Cell surface proteins play central roles in adhesive contacts between the tumor cell and the stroma during metastasis. We optimized a fast, small-scale isolation of biotinylated cell surface proteins to reveal novel metastasis-associated players from an isogenic pair of human MDA-MB-435 cancer cells with opposite metastatic phenotypes. Isolated proteins were trypsin digested and analyzed using LC-MS/MS followed by quantitation with the Progenesis LC-MS software. Sixteen proteins displayed over twofold expression differences between the metastatic and non-metastatic cells. Interestingly, overexpression of most of them (14/16) in the metastatic cells indicates a gain of novel surface protein profile as compared to the non-metastatic ones. All five validated, differentially expressed proteins showed higher expression in the metastatic cells in culture, and four of these were further validated in vivo. Moreover, we analyzed expression of two of the identified proteins, CD109 and ITGA6 in 3-dimensional cultures of six melanoma cell lines. Both proteins marked the surface of cells derived from melanoma metastasis over cells derived from primary melanoma. The unbiased identification and validation of both known and novel metastasis-associated proteins indicate a reliable approach for the identification of differentially expressed surface proteins.
The early detection of urological cancers is pivotal for successful patient treatment and management. The development of molecular assays that can diagnose disease accurately, or that can augment current methods of evaluation, would be a significant advance. Ideally, such molecular assays would be applicable to non-invasively obtained body fluids, enabling not only diagnosis of at risk patients, but also asymptomatic screening, monitoring disease recurrence and response to treatment. The advent of advanced proteomics and genomics technologies and associated bioinformatics development is bringing these goals into focus. In this article we will discuss the promise of biomarkers in urinalysis for the detection and clinical evaluation of the major urological cancers, including bladder, kidney and prostate. The development of urine-based tests to detect urological cancers would be of tremendous benefit to both patients and the healthcare system.
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.
A crucial step in the metastatic spread of ovarian cancer (OC) is the adhesion and implantation of tumor cells to the peritoneal mesothelium. In order to study this step in the cascade, we derived a pro-metastatic human ovarian carcinoma cell line (MFOC3) from the non-metastatic FOC3 line.
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