A mechanistic insight into the anti-metastatic role of the prostate specific antigen

AimSince its discovery Prostate Specific Antigen (PSA), also referred to as kallikrein-3 (KLK3), has been used as standard circulating biomarker for prostate cancer (PCa). However, its specificity remains not adequate and its mechanism of action still elusive. Therefore, deciphering PSA role throughout PCa-pathobiology would be relevant in improving both cancer diagnosis and outcome prediction. We investigated the possible role played by PSA on/in the tumor microenvironment and over the first steps of cancer invasion.MethodsFresh PCa-specimens and cell lines were used for ex-vivo/in-vitro invasion assays and assessment of prostate tissue-PSA (tPSA), type 1 collagen (COL1A1) and ß1-integrin expression. Tissue Cancer Genome Atlas (TCGA) and Decipher® datasets were considered to estimate tPSA clinical relevance.ResultsA more precise, inverse, correspondence between tPSA and clinical/pathological parameters was found than for circulating PSA. KLK3 combined with Gleason grade and pathologic stage, better predicted cancer-related mortality. Consistently, we demonstrated that PSA inhibits prostate extracellular-matrix (ECM) invasion by PCa cells. As for the mechanism of action, we provided novel information that PSA is able to cleave COL1A1, a main component of the ECM. Finally, ß1-integrin, a crucial COL1A1 transducing-receptor involved in tumor adhesion/invasion, resulted to be downregulated in PCa specimens with higher levels of tPSA.ConclusionsBy interfering with type 1 collagen and its downstream targets, PSA may hamper adhesion and path of the cancer cells through ECM and their migration ability, thus explaining the inverse correlation highlighted between prostate tPSA levels and clinically significant disease.     

Eph receptors and their ligands: Promising molecular biomarkers and therapeutic targets in prostate cancer

Although at present, there is a high incidence of prostate cancer, particularly in the Western world, mortality from this disease is declining and occurs primarily only from clinically significant late stage tumors with a poor prognosis. A major current focus of this field is the identification of new biomarkers which can detect earlier, and more effectively, clinically significant tumors from those deemed “low risk”, as well as predict the prognostic course of a particular cancer. This strategy can in turn offer novel avenues for targeted therapies. The large family of Receptor Tyrosine Kinases, the Ephs, and their binding partners, the ephrins, has been implicated in many cancers of epithelial origin through stimulation of oncogenic transformation, tumor angiogenesis, and promotion of increased cell survival, invasion and migration. They also show promise as both biomarkers of diagnostic and prognostic value and as targeted therapies in cancer. This review will briefly discuss the complex roles and biological mechanisms of action of these receptors and ligands and, with regard to prostate cancer, highlight their potential as biomarkers for both diagnosis and prognosis, their application as imaging agents, and current approaches to assessing them as therapeutic targets. This review demonstrates the need for future studies into those particular family members that will prove helpful in understanding the biology and potential as targets for treatment of prostate cancer.     

Biomarkers for prostate cancer

The detection of prostate cancer using a blood test has by many standards changed the face of the disease. Despite this tremendous success, there are limitations attributed to the use of prostate specific antigen (PSA) as a means to screen and detect prostate cancer. PSA, as its name implies, is not specific for prostate cancer and as such is often found elevated in other prostatic diseases/symptoms associated with the aging male. Clearly, more specific marker(s) that could identify which individuals actually have prostate cancer and differentiate them from those without the disease would be of tremendous value. The search for more accurate and clinically useful biomarkers of prostate cancer has been extensive. This has focused on individual markers, as well as groups of markers. Included among these are PSA isoforms, pathological indicators and stains, nucleic acids and others. This article highlights the discovery of PSA as a first blood‐based biomarker for prostate cancer detection, as well as other molecular biomarkers and their potential application in detection of the disease. J. Cell. Biochem. 108: 3–9, 2009. © 2009 Wiley‐Liss, Inc.     

Mass spectrometric identification of human prostate cancer-derived proteins in serum of xenograft-bearing mice

Lack of sensitivity and specificity of current tumor markers has intensified research efforts to find new biomarkers. The identification of potential tumor markers in human body fluids is hampered by large variability and complexity of both control and patient samples, laborious biochemical analyses, and the fact that the identified proteins are unlikely produced by the diseased cells but are due to secondary body defense mechanisms. In a new approach presented here, we eliminate these problems by performing proteomic analysis in a prostate cancer xenograft model in which human prostate cancer cells form a tumor in an immune-incompetent nude mouse. Using this concept, proteins present in mouse serum that can be identified as human will, by definition, originate from the human prostate cancer xenograft and might have potential diagnostic and prognostic value. Using one-dimensional gel electrophoresis, liquid chromatography, and mass spectrometry, we identified tumor-derived human nm23/nucleoside-diphosphate kinase (NME) in the serum of a nude mouse bearing the androgen-independent human prostate cancer xenograft PC339. NME is known to be involved in the metastatic potential of several tumor cells, including prostate cancer cells. Furthermore we identified six human enzymes involved in glycolysis (fructose-bisphosphate aldolase A, triose-phosphate isomerase, glyceraldehyde-3-phosphate dehydrogenase, alpha enolase, and lactate dehydrogenases A and B) in the serum of the tumor-bearing mice. The presence of human NME and glyceraldehyde-3-phosphate dehydrogenase in the serum of PC339-bearing mice was confirmed by Western blotting. Although the putative usefulness of these proteins in predicting prognosis of prostate cancer remains to be determined, the present data illustrate that our approach is a promising tool for the focused discovery of new prostate cancer biomarkers.     

Biomarker Discovery in Human Prostate Cancer: an Update in Metabolomics Studies

Prostate cancer (PCa) is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA) levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection.     

Explication of the roles of prostate health index (PHI) and urokinase plasminogen activator (uPA) as diagnostic and predictor tools for prostate cancer in equivocal PSA range of 4–10 ng/mL

BackgroundProstate cancer (PCa) is one of the most commonly encountered cancers and the leading cause of death worldwide. Currently used biomarkers accounts difficulties in discriminating benign from malignant cases or predicting outcome, so investigating new biomarkers performance is needed.ObjectivesAssessment of diagnostic and predictor roles of prostate health index (PHI) and urokinase plasminogen activator (uPA) in PCa.Methods194 males with initial tPSA of 4–10 ng/mL were categorized into three groups: PCa, benign prostatic hyperplasia (BPH) and healthy control. Serum levels of tPSA, fPSA, p2PSA, and uPA were performed by ELISA with calculation of PHI as (p2PSA/fPSA) × √PSA.ResultsPHI and uPA were significantly higher in PCa patients relevant to BPH and healthy control (p ≤ 0.001). Both markers outperformed all assessed biomarkers and showed the highest area under the curve (AUC) in ROC curve analysis. Both were significantly higher in PCa patients with {Gleason score ≥ 7, late stages (cT2b,c; T3), LN extension and distant metastasis}relative to their counterparts. Additionally, PHI and uPA and were independent predictors of distant metastasis and Gleason score ≥ 7, while PHI was predictor of LN invasion (β = 0.25, p = 0.004).ConclusionPHI and uPA would be of potential value in discriminating between PCa, BPH and healthy men in addition, both are promising as independent predictors of adverse pathological features.     

MicroRNAs associated with metastatic prostate cancer

Objective

Metastasis is the most common cause of death of prostate cancer patients. Identification of specific metastasis biomarkers and novel therapeutic targets is considered essential for improved prognosis and management of the disease. MicroRNAs (miRNAs) form a class of non-coding small RNA molecules considered to be key regulators of gene expression. Their dysregulation has been shown to play a role in cancer onset, progression and metastasis, and miRNAs represent a promising new class of cancer biomarkers. The objective of this study was to identify down- and up-regulated miRNAs in prostate cancer that could provide potential biomarkers and/or therapeutic targets for prostate cancer metastasis.

Methods

Next generation sequencing technology was applied to identify differentially expressed miRNAs in a transplantable metastatic versus a non-metastatic prostate cancer xenograft line, both derived from one patient''s primary cancer. The xenografts were developed via subrenal capsule grafting of cancer tissue into NOD/SCID mice, a methodology that tends to preserve properties of the original cancers (e.g., tumor heterogeneity, genetic profiles).

Results

Differentially expressed known miRNAs, isomiRs and 36 novel miRNAs were identified. A number of these miRNAs (21/104) have previously been reported to show similar down- or up-regulation in prostate cancers relative to normal prostate tissue, and some of them (e.g., miR-16, miR-34a, miR-126*, miR-145, miR-205) have been linked to prostate cancer metastasis, supporting the validity of the analytical approach.

Conclusions

The use of metastatic and non-metastatic prostate cancer subrenal capsule xenografts derived from one patient''s cancer makes it likely that the differentially expressed miRNAs identified in this study include potential biomarkers and/or therapeutic targets for human prostate cancer metastasis.     

Mass spectrometry-based expression profiling of clinical prostate cancer

The maturation of MS technologies has provided a rich opportunity to interrogate protein expression patterns in normal and disease states by applying expression protein profiling methods. Major goals of this research strategy include the identification of protein biomarkers that demarcate normal and disease populations, and the identification of therapeutic biomarkers for the treatment of diseases such as cancer (Celis, J. E., and Gromov, P. (2003) Proteomics in translational cancer research: Toward an integrated approach. Cancer Cell 3, 9-151). Prostate cancer is one disease that would greatly benefit from implementing MS-based expression profiling methods because of the need to stratify the disease based on molecular markers. In this review, we will summarize the current MS-based methods to identify and validate biomarkers in human prostate cancer. Lastly, we propose a reverse proteomic approach implementing a quantitative MS research strategy to identify and quantify biomarkers implicated in prostate cancer development. With this approach, the absolute levels of prostate cancer biomarkers will be identified and quantified in normal and diseased samples by measuring the levels of native peptide biomarkers in relation to a chemically identical but isotopically labeled reference peptide. Ultimately, a centralized prostate cancer peptide biomarker expression database could function as a repository for the identification, quantification, and validation of protein biomarker(s) during prostate cancer progression in men.     

Prostate cancer proteomics: clinically useful protein biomarkers and future perspectives

Introduction: Although prostate cancer constitutes one of the most important, death-related diseases in the male population, there is still a need for identification of sensitive biomarkers that could precociously detect the disease and differentiate aggressive from indolent cancers, in order to decrease overtreatment. Proteomics research has improved understanding on mechanisms underlying tumorigenesis, cancer cells migration and invasion potential, and castration resistance. This review has focused on proteomic studies of prostate cancer published in the recent years, with a special emphasis on determination of biomarkers for cancer progression and diagnosis.

Areas covered: Shotgun and targeted-proteomic studies of prostate cancer in different matrices are reviewed, i.e., prostate tissue, prostate cell lines, blood (serum and plasma), urine, seminal plasma, and exosomes. The most important biomarkers for cancer diagnosis and aggressiveness characterization are highlighted.

Expert commentary: In general, results demonstrate alteration in cell cycle control, DNA repair, proteasomal degradation, and metabolic activity. However, these studies suffer from low reproducibility due to heterogeneity of the cancer itself, as well as to techniques utilized for protein identification/quantification. Downstream confirmatory studies in separate cohorts are warranted in order to demonstrate accuracy of these results.     

Identification of Plasma Lipid Biomarkers for Prostate Cancer by Lipidomics and Bioinformatics

Background

Lipids have critical functions in cellular energy storage, structure and signaling. Many individual lipid molecules have been associated with the evolution of prostate cancer; however, none of them has been approved to be used as a biomarker. The aim of this study is to identify lipid molecules from hundreds plasma apparent lipid species as biomarkers for diagnosis of prostate cancer.

Methodology/Principal Findings

Using lipidomics, lipid profiling of 390 individual apparent lipid species was performed on 141 plasma samples from 105 patients with prostate cancer and 36 male controls. High throughput data generated from lipidomics were analyzed using bioinformatic and statistical methods. From 390 apparent lipid species, 35 species were demonstrated to have potential in differentiation of prostate cancer. Within the 35 species, 12 were identified as individual plasma lipid biomarkers for diagnosis of prostate cancer with a sensitivity above 80%, specificity above 50% and accuracy above 80%. Using top 15 of 35 potential biomarkers together increased predictive power dramatically in diagnosis of prostate cancer with a sensitivity of 93.6%, specificity of 90.1% and accuracy of 97.3%. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) demonstrated that patient and control populations were visually separated by identified lipid biomarkers. RandomForest and 10-fold cross validation analyses demonstrated that the identified lipid biomarkers were able to predict unknown populations accurately, and this was not influenced by patient''s age and race. Three out of 13 lipid classes, phosphatidylethanolamine (PE), ether-linked phosphatidylethanolamine (ePE) and ether-linked phosphatidylcholine (ePC) could be considered as biomarkers in diagnosis of prostate cancer.

Conclusions/Significance

Using lipidomics and bioinformatic and statistical methods, we have identified a few out of hundreds plasma apparent lipid molecular species as biomarkers for diagnosis of prostate cancer with a high sensitivity, specificity and accuracy.     

Polyamines and prostatic cancer

The importance of polyamines in prostatic growth and differentiation has prompted studies to evaluate the clinical relevance of the ornithine decarboxylase/polyamine system in prostatic cancer. These studies show that differences in biological behaviour of prostatic (cancer) cells are associated with changes in polyamine levels and/or the activity of their metabolic enzymes. Faulty antizyme regulation of polyamine homoeostasis may play an important role in the growth and progression of prostatic carcinoma. Treatment of human prostate carcinoma cells with inhibitors of polyamine metabolic enzymes or polyamine analogues induces cell growth arrest or (apoptotic) cell death. Our recent in vitro studies using conformationally restricted polyamine analogues show that these compounds inhibit cell growth, probably by inducing antizyme-mediated degradation of ornithine decarboxylase. Sensitivity of human prostate cancer cells for these compounds was increased in the absence of androgens. These results suggest that these analogues might have chemotherapeutic potential in case prostatic cancer has become androgen-independent. Pilot data in an in vivo model show that these analogues have effects on tumour cell proliferation, vascularity, blood perfusion and tissue hypoxia. Overall, these studies show that polyamines may serve as important biomarkers of prostatic malignancy and provide a promising target for chemotherapy of prostatic cancer.     

High-sensitivity blood-based detection of breast cancer by multi photon detection diagnostic proteomics

We have developed several new methods for blood-based cancer detection by diagnostic proteomics. Ultrasensitive methods of immunoassay using multiphoton-detection (IA/MPD) increase sensitivity by 200- to 1,000-fold (1 femtogram/mL). This has allowed the measurement of cancer biomarkers with very low concentrations in blood that could not be measured for full patient cohorts with conventional immunoassays. Sensitivity and specificity in cancer detection have been found to be potentiated by use of immunoassay panels which include tissue-specific cancer biomarkers as well as cytokines and angiogenic factors. The ultrasensitive immunoassays revealed that patient to patient variations in the concentrations of individual biomarkers in blood can extend over many orders of magnitude (up to six) and that the distributions of biomarker concentrations over patient cohorts are non-Gaussian. New methods of data analysis which correlate abundances of multiple, different biomarkers have been developed to deal with such data sets. Sensitivity and specificity of about 95% have been achieved for blood-based detection of breast cancer in pilot studies on 250 patients and 95 controls. Pilot studies indicate that this methodology may also allow differentiation of malignant breast cancer from benign lesions and can provide similar sensitivity and specificity for other epithelial cancers such as prostate cancer, ovarian cancer and melanoma. The methods developed for selection, application, and evaluation of very high sensitivity biomarker panels are expected to have general relevance for diagnostic proteomics.     

Integrated Analysis Reveals together miR-182, miR-200c and miR-221 Can Help in the Diagnosis of Prostate Cancer

Research has shown that microRNAs are promising biomarkers that can be used to promote a more accurate diagnosis of cancer. In this study, we developed an integrated multi-step selection process to analyze available high-throughput datasets to obtain information on microRNAs as cancer biomarkers. Applying this approach to the microRNA expression profiles of prostate cancer and the datasets in The Cancer Genome Atlas Data Portal, we identified miRNA-182, miRNA-200c and miRNA-221 as possible biomarkers for prostate cancer. The associations between the expressions of these three microRNAs with clinical parameters as well as their diagnostic capability were studied. Several online databases were used to predict the target genes of these three microRNAs, and the results were confirmed by significant statistical correlations. Comparing with the other 18 types of cancers listed in The Cancer Genome Atlas Data Portal, we found that the combination of both miRNA-182 and miRNA-200c being up-regulated and miRNA-221 being down-regulated only happens in prostate cancer. This provides a unique biological characteristic for prostate cancer that can potentially be used for diagnosis based on tissue testing. In addition, our study also revealed that these three microRNAs are associated with the pathological status of prostate cancer.     

Proteomic analysis of microvesicles released by the human prostate cancer cell line PC-3

Cancer biomarkers are invaluable tools for cancer detection, prognosis, and treatment. Recently, microvesicles have appeared as a novel source for cancer biomarkers. We present here the results from a proteomic analysis of microvesicles released to the extracellular environment by the metastatic prostate cancer cell line PC-3. Using nanocapillary liquid chromatography-tandem mass spectrometry 266 proteins were identified with two or more peptide sequences. Further analysis showed that 16% of the proteins were classified as extracellular and that intracellular proteins were annotated in a variety of locations. Concerning biological processes, the proteins found in PC-3 cell-released microvesicles are mainly involved in transport, cell organization and biogenesis, metabolic process, response to stimulus, and regulation of biological processes. Several of the proteins identified (tetraspanins, annexins, Rab proteins, integrins, heat shock proteins, cytoskeletal proteins, 14-3-3 proteins) have previously been found in microvesicles isolated from other sources. However, some of the proteins seem to be more specific to the vesicular population released by the metastatic prostate cancer PC-3 cell line. Among these proteins are the tetraspanin protein CD151 and the glycoprotein CUB domain-containing protein 1. Interestingly, our results show these proteins are promising biomarkers for prostate cancer and therefore candidates for clinical validation studies in biological fluids.     

Integrative analysis of N-linked human glycoproteomic data sets reveals PTPRF ectodomain as a novel plasma biomarker candidate for prostate cancer

In an attempt to identify prostate cancer biomarkers with greater diagnostic and prognostic capabilities, we have developed an integrative proteomic discovery workflow focused on N-linked glycoproteins that refines the target selection process. In this work, hydrazide-based chemistry was used to identify N-linked glycopeptides from 22Rv1 prostate cancer cells cultured in vitro, which were compared with glycopeptides identified from explanted 22Rv1 murine tumor xenografts. One hundred and four human glycoproteins were identified in the former analysis and 75 in the latter, with 40 proteins overlapping between data sets. Of the 40 overlapping proteins, 80% have multiple literature references to the neoplastic process and ～40% to prostatic neoplasms. These include a number of well-known prostate cancer-associated biomarkers, such as prostate-specific membrane antigen (PSMA). By integrating gene expression data and available literature, we identified members of the overlap data set that deserve consideration as potential prostate cancer biomarkers. Specifically, the identification of the extracellular domain of protein tyrosine phosphatase receptor type F (PTPRF) was of particular interest due to the direct involvement of PTPRF in the control of β-catenin signaling, as well as dramatically elevated gene expression levels in the prostate compared to other tissues. In this investigation, we demonstrate that the PTPRF E-subunit is more abundant in human prostate tumor tissue compared to normal control and also detectable in murine plasma by immunoblot and ELISA. Specifically, PTPRF distinguishes between animals xenografted with the 22Rv1 cells and control animals as early as 14 days after implantation. This result suggests that the ectodomain of PTPRF has the potential to function as a novel plasma or tissue-based biomarker for prostate cancer. The workflow described adds to the literature of potential biomarker candidates for prostate cancer and demonstrates a pathway to developing new diagnostic assays.     

Proteomics in prostate cancer biomarker discovery

Despite advances in molecular medicine, genomics, proteomics and translational research, prostate cancer remains the second most common cause of cancer-related mortality for men in the Western world. Clearly, early detection, targeted treatment and post-treatment monitoring are vital tools to combat this disease. Tumor markers can be useful for diagnosis and early detection of cancer, assessment of prognosis, prediction of therapeutic effect and treatment monitoring. Such tumor markers include prostate-specific antigen (prostate), cancer antigen (CA)15.3 (breast), CA125 (ovarian), CA19.9 (gastrointestinal) and serum α-fetoprotein (testicular cancer). However, all of these biomarkers lack sensitivity and specificity and, therefore, there is a large drive towards proteomic biomarker discovery. Current research efforts are directed towards discovering biosignatures from biological samples using novel proteomic technologies that provide high-throughput, in-depth analysis and quantification of the proteome. Several of these studies have revealed promising biomarkers for use in diagnosis, assessment of prognosis, and targeting treatment of prostate cancer. This review focuses on prostate cancer proteomic biomarker discovery and its future potential.     

Prostate cancer radiation therapy: A physician’s perspective

Prostate cancer is the second most common cancer in men and a major cause of cancer deaths worldwide. Ionizing radiation has played a substantial role in the curative treatment of this disease. The historical evolution of radiotherapy techniques through 3D-conformal radiotherapy (3D-CRT), intensity-modulated radiotherapy (IMRT), and image-guided radiotherapy (IGRT) has allowed more accurate and precise treatments toward significant improvements in the therapeutic ratio. The addition of androgen deprivation therapy has significantly improved overall survival becoming the standard therapy for intermediate- and high-risk disease. Many randomized controlled trials have shown improved local control with dose escalation, and hypofractionated RT has been consolidated with proven efficacy and safe clinical results. However, several questions remain open in the radiotherapeutic management of prostate cancer patients and hopefully ongoing studies will shed light on these uncertainties. More individualized approaches are essential through better prognostic and novel predictive biomarkers of prostate radiotherapy response. Clinicians should critically interpret the evolving technologies in prostate cancer radiotherapy with important optimism but balancing the costs and the actual magnitude of clinical benefit. This article provides an overview of the basic aspects of radiotherapy treatment in localized prostate cancer from a physician’s perspective.