Proteomic Profiling of Exosomes Leads to the Identification of Novel Biomarkers for Prostate Cancer

Background

Current markers for prostate cancer, such as PSA lack specificity. Therefore, novel biomarkers are needed. Unfortunately, the complexity of body fluids often hampers biomarker discovery. An attractive alternative approach is the isolation of small vesicles, i.e. exosomes, ∼100 nm, which contain proteins that are specific to the tissue from which they are derived and therefore can be considered as treasure chests for disease-specific biomarker discovery.

Materials and Methods

Exosomes were isolated from 2 immortalized primary prostate epithelial cells (PNT2C2 and RWPE-1) and 2 PCa cell lines (PC346C and VCaP) by ultracentrifugation. After tryptic digestion, proteomic analyses utilized a nanoLC coupled with an LTQ-Orbitrap operated in tandem MS (MS/MS) mode. Accurate Mass and Time (AMT) tag approach was employed for peptide identification and quantitation. Candidate biomarkers were validated by Western blotting and Immunohistochemistry.

Results

Proteomic characterization resulted in the identification of 248, 233, 169, and 216 proteins by at least 2 peptides in exosomes from PNT2C2, RWPE-1, PC346C, and VCaP, respectively. Statistical analyses revealed 52 proteins differently abundant between PCa and control cells, 9 of which were more abundant in PCa. Validation by Western blotting confirmed a higher abundance of FASN, XPO1 and PDCD6IP (ALIX) in PCa exosomes.

Conclusions

Identification of exosomal proteins using high performance LC-FTMS resulted in the discovery of PDCD6IP, FASN, XPO1 and ENO1 as new candidate biomarkers for 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.     

Identification,prioritization, and evaluation of glycoproteins for aggressive prostate cancer using quantitative glycoproteomics and antibody‐based assays on tissue specimens

Prostate cancer is highly heterogeneous in nature; while the majority of cases are clinically insignificant, some cases are lethal. Currently, there are no reliable screening methods for aggressive prostate cancer. Since most established serum and urine biomarkers are glycoproteins secreted or leaked from the diseased tissue, the current study seeks to identify glycoprotein markers specific to aggressive prostate cancer using tissue specimens. With LC‐MS/MS glycoproteomic analysis, we identified 350 glycopeptides with 17 being altered in aggressive prostate cancer. ELISA assays were developed/purchased to evaluate four candidates, that is, cartilage oligomeric matrix protein (COMP), periostin, membrane primary amine oxidase (VAP‐1), and cathepsin L, in independent tissue sets. In agreement with the proteomic analysis, we found that COMP and periostin expressions were significantly increased in aggressive prostate tumors while VAP‐1 expression was significantly decreased in aggressive tumor. In addition, the expression of these proteins in prostate metastases also follows the same pattern observed in the proteomic analysis. This study provides a workflow for biomarker discovery, prioritization, and evaluation of aggressive prostate cancer markers using tissue specimens. Our data suggest that increase in COMP and periostin and decrease in VAP‐1 expression in the prostate may be associated with aggressive prostate cancer.     

Monitoring mouse prostate development by profiling and imaging mass spectrometry

Mass spectrometry-based tissue profiling and imaging are technologies that allow identification and visualization of protein signals directly on thin sections cut from fresh frozen tissue specimens. These technologies were utilized to evaluate protein expression profiles in the normal mouse prostate during development (1-5 weeks of age), at sexual maturation (6 weeks of age), and in adult prostate (at 10, 15, or 40 weeks of age). The evolution of protein expression during normal prostate development and maturation were subsequently compared with 15-week prostate tumors derived from genetically engineered mice carrying the Large T antigen gene under regulation of the prostate-specific probasin promoter (LPB-Tag mouse model for prostate cancer). This approach identified proteins differentially expressed at specific time points during prostate development. Furthermore expression of some of these proteins, for example probasin and spermine-binding protein, were associated with prostate maturation, and prostate tumor formation resulted in their loss of expression. Cyclophilin A, a protein found in other cancers, was differentially alpha-acetylated on the N terminus, and both isoforms appeared during normal prostate and prostate tumor development. Imaging mass spectrometry localized the protein signals to specific prostatic lobes or regions. Thus, tissue profiling and imaging can be utilized to analyze the ontogeny of protein expression during prostate morphogenesis and tumorigenesis and identify proteins that could potentially serve as biomarkers for prostate cancer.     

Application of mass spectrometry to the discovery of biomarkers for detection of prostate cancer

There has been an impressive emergence of mass spectrometry based technologies applied toward the study of proteins. Equally notable is the rapid adaptation of these technologies to biomedical approaches in the realm of clinical proteomics. Concerted efforts toward the elucidation of the proteomes of organ sites or specific disease state are proliferating and from these efforts come the promise of better diagnostics/prognostics and therapeutic intervention. Prostate cancer has been a focus of many such studies with the promise of improved care to patients via biomarkers derived from these proteomic approaches. The newer technologies provide higher analytical capabilities, employ automated liquid handling systems, fractionation techniques and bioinformatics tools for greater sensitivity and resolving power, more robust and higher throughput sample processing, and greater confidence in analytical results. In this prospects, we summarize the proteomic technologies applied to date in prostate cancer, along with their respective advantages and disadvantages. The development of newer proteomic strategies for use in future applications is also discussed.     

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.     

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.     

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.     

Proteomics of human prostate cancer biospecimens: the global,systems-wide perspective for Protein markers with potential clinical utility

Despite intense global efforts, no new clinical and/or viable biomarkers have been established to overcome the limitation of the prostate specific antigen in the early diagnosis and prognosis of prostate cancer (PCa). The current proteomic approaches to PCa biomarker discovery, each have distinct advantages and disadvantages, yet when combined hold real promise in the coming years. One key approach to this effort is the development of non-targeted, depletion-free and quantitative liquid chromatography–ultra high resolution tandem mass spectrometry (LC–MS) pipelines for the systems-wide interrogation of the diverse proteomes encompassed in whole tissue and blood serum or plasma. Derived quantitative proteomes can be decoded for their biomedical relevance with advanced bioinformatics and bibliographic mining to yield promising ‘molecular portraits’ that can gauge prostatic disease at the serological level. Their functional annotation, although potentially useful, is beyond our current level of biological understanding and should not be requisite for their effective use in the clinical monitoring of prostatic disease.     

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.     

Proteomic analysis of formalin-fixed prostate cancer tissue

Proteomic analysis of formalin-fixed paraffin-embedded (FFPE) tissue would enable retrospective biomarker investigations of this vast archive of pathologically characterized clinical samples that exist worldwide. These FFPE tissues are, however, refractory to proteomic investigations utilizing many state of the art methodologies largely due to the high level of covalently cross-linked proteins arising from formalin fixation. A novel tissue microdissection technique has been developed and combined with a method to extract soluble peptides directly from FFPE tissue for mass spectral analysis of prostate cancer (PCa) and benign prostate hyperplasia (BPH). Hundreds of proteins from PCa and BPH tissue were identified, including several known PCa markers such as prostate-specific antigen, prostatic acid phosphatase, and macrophage inhibitory cytokine-1. Quantitative proteomic profiling utilizing stable isotope labeling confirmed similar expression levels of prostate-specific antigen and prostatic acid phosphatase in BPH and PCa cells, whereas the expression of macrophage inhibitory cytokine-1 was found to be greater in PCa as compared with BPH cells.     

A Preliminary Proteomic Investigation of Circulating Exosomes and Discovery of Biomarkers Associated with the Progression of Osteosarcoma in a Clinical Model of Spontaneous Disease

Circulating cancer exosomes are microvesicles which originate from malignant cells and other organs influenced by the disease and can be found in blood. The exosomal proteomic cargo can often be traced to the cells from which they originated, reflecting the physiological status of these cells. The similarities between cancer exosomes and the tumor cells they originate from exhibit the potential of these vesicles as an invaluable target for liquid biopsies. Exosomes were isolated from the serum of eight osteosarcoma-bearing dogs, five healthy dogs, and five dogs with traumatic fractures. We also characterized exosomes which were collected longitudinally from patients with osteosarcoma prior and 2 weeks after amputation, and eventually upon detection of lung metastasis. Exosomal proteins fraction were analyzed by label-free mass spectrometry proteomics and were validated with immunoblots of selected proteins. Ten exosomal proteins were found that collectively discriminate serum of osteosarcoma patients from serum healthy or fractured dogs with an accuracy of 85%. Additionally, serum from different disease stages could be distinguished with an accuracy of 77% based on exosomal proteomic composition. The most discriminating protein changes for both sample group comparisons were related to complement regulation, suggesting an immune evasion mechanism in early stages of osteosarcoma as well as in advanced disease.     

外泌体作为疾病诊断标志物及药物载体的应用前景

作为一种纳米级别的囊泡,外泌体的相关研究近年来逐渐成为热点。外泌体来源于细胞内的多囊泡胞内体,经由细胞膜释放到细胞外。由于来自特定细胞类型的外泌体含有多种特异性的蛋白质和microRNA,使其成为了可以广泛用于疾病诊断及预后的新型生物标志物。相较于其他外源性药物载体,外泌体具有更低的免疫原性,并能够靶向作用于病变细胞。这使得由细胞天然产生或经过人工改造的外泌体作为一种新兴的药物载体具有良好的发展前景。特别是近几年,外泌体在临床应用领域的发展潜力不断获得拓展,针对肿瘤、糖尿病、心脑血管疾病、神经退行性病变等重大疾病,以外泌体为基础的疾病诊断和药物的研发都取得了快速的进步。本篇综述重点介绍了外泌体作为一种生物标志物在疾病诊断和预后中的应用,同时阐述了外泌体作为一种新兴的药物载体所具有的优势以及存在的问题。     

Multidrug resistant tumour cells shed more microvesicle-like EVs and less exosomes than their drug-sensitive counterpart cells

BackgroundMultidrug resistance (MDR) is a serious impediment to cancer treatment, with overexpression of drug efflux pumps such as P-glycoprotein (P-gp) playing a significant role. In spite of being a major clinical challenge, to date there is no simple, minimally invasive and clinically validated method for diagnosis of the MDR phenotype using non-tumour biological samples. Recently, P-gp has been found in extracellular vesicles (EVs) shed by MDR cancer cells. This study aimed to compare the EVs shed by MDR cells and their drug-sensitive cellular counterparts, in order to identify biomarkers of MDR.MethodsTwo pairs of MDR and drug-sensitive counterpart tumour cell lines were studied as models. EVs were characterized in terms of size and molecular markers and their protein content was investigated by proteomic analysis and Western blot.ResultsWe found that MDR cells produced more microvesicle-like EVs and less exosomes than their drug-sensitive counterpart. EVs from MDR cells contained P-gp and presented a different content of proteins known to be involved in the biogenesis of EVs, particularly in the biogenesis of exosomes.ConclusionsThe determination of the size and of this particular protein content of EVs shed by tumour cells may allow the development of a minimally-invasive simple method of detecting and predicting MDR.General significanceThis work describes for the first time that cancer multidrug resistant cells shed more microvesicle-like EVs and less exosomes than their drug-sensitive counterpart cells, carrying a specific content of proteins involved in EV biogenesis that could be further studied as biomarkers of MDR.     

The Role of Exosomes in Pancreatic Cancer Microenvironment

Exosomes are nanovesicles shed by cells as a means of communication with other cells. Exosomes contain mRNAs, microRNAs (miRs) and functional proteins. In the present paper, we develop a mathematical model of tumor–immune interaction by means of exosomes shed by pancreatic cancer cells and dendritic cells. Cancer cells’ exosomes contain miRs that promote their proliferation and that inhibit immune response by dendritic cells, and by CD4+ and CD8+ T cells. Dendritic cells release exosomes with proteins that induce apoptosis of cancer cells and that block regulatory T cells. Simulations of the model show how the size of the pancreatic cancer can be determined by measurement of specific miRs (miR-21 and miR-203 in the case of pancreatic cancer), suggesting these miRs as biomarkers for cancer.     

Isolation and proteomic analysis of exosomes secreted by human cancer cells in vitro

Exosomes are 20-100 nm membrane vesicles of endocytic origin secreted by most cell types in vitro and in vivo. Since exosomes contain both RNA (mRNA and microRNA) and proteins, which can be transferred to another cell, and be functional in that new environment, these vesicles may be involved in the communication between cells. The secretion of exosomes by tumor cells and their implication in the transport and propagation of infectious cargo suggest their participation in pathological situations. Our purpose here is to describe methods for the production, purification, and proteomic characterization of exosomes derived from human cancer cells in vitro. Based on exosomes' unique lipidic composition, we have developed the new approach to increase production of exosomes by cells in vitro. Secondly, we have developed quality control by laser correlation spectroscopy for exosomal assays based on the amount of MHC class I and CD63 molecules on their surface. At last, matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry was used after 2D electrophoresis for the proteomic analysis of exosomes derived from cancer cell lines. This study describes the protein composition of brain tumor cell-derived exosomes in more detail.     

Exosomes: Extracellular organelles important in intercellular communication

In addition to intracellular organelles, eukaryotic cells also contain extracellular organelles that are released, or shed, into the microenvironment. These membranous extracellular organelles include exosomes, shedding microvesicles (SMVs) and apoptotic blebs (ABs), many of which exhibit pleiotropic biological functions. Because extracellular organelle terminology is often confounding, with many preparations reported in the literature being mixtures of extracellular vesicles, there is a growing need to clarify nomenclature and to improve purification strategies in order to discriminate the biochemical and functional activities of these moieties. Exosomes are formed by the inward budding of multivesicular bodies (MVBs) and are released from the cell into the microenvironment following the fusion of MVBs with the plasma membrane (PM). In this review we focus on various strategies for purifying exosomes and discuss their biophysical and biochemical properties. An update on proteomic analysis of exosomes from various cell types and body fluids is provided and host-cell specific proteomic signatures are also discussed. Because the ectodomain of ~ 42% of exosomal integral membrane proteins are also found in the secretome, these vesicles provide a potential source of serum-based membrane protein biomarkers that are reflective of the host cell. ExoCarta, an exosomal protein and RNA database (http://exocarta.ludwig.edu.au), is described.