Theo M. Luider

Proteomic analysis of exosomes secreted by human mesothelioma cells.

Exosomes are small membrane vesicles secreted into the extracellular compartment by exocytosis. Tumor exosomes may be involved in the sampling of antigens to antigen presenting cells or as decoys allowing the tumor to escape immune-directed destruction. The proteins present in exosomes secreted by tumor cells have been poorly defined. This study describes the protein composition of mesothelioma cell-derived exosomes in more detail. After electrophoresis of exosome preparations, matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) was used to characterize the protein spots. MHC class I was found to be present together with the heat shock proteins HSC70 and HSP90. In addition, we found annexins and PV-1, proteins involved in membrane transport and function. Cytoskeleton proteins and their associated proteins ezrin, moesin, actinin-4, desmoplakin, and fascin were also detected. Besides the molecular motor kinesin-like protein, many enzymes were detected revealing the cytoplasmic orientation of exosomes. Most interesting was the detection of developmental endothelial locus-1 (DEL-1), which can act as a strong angiogenic factor and can increase the vascular development in the neighborhood of the tumor. In conclusion, mesothelioma cells release exosomes that express a discrete set of proteins involved in antigen presentation, signal transduction, migration, and adhesion. Exosomes may play an important role in the interaction between tumor cells and their environment.

Exosomes as biomarker treasure chests for prostate cancer.

CONTEXT Although progress has been made with regard to types of markers (protein, DNA, RNA, and metabolites) and implementation of improved technologies (mass spectrometry, arrays, and deep sequencing), the discovery of novel biomarkers for prostate cancer (PCa) in complex fluids, such as serum and urine, remains a challenge. Meanwhile, recent studies have reported that many cancer-derived proteins and RNAs are secreted through small vesicles known as exosomes. OBJECTIVE This narrative review describes recent progress in exosome research, focusing on the potential role of exosomes as novel biomarkers for PCa. The purpose of this review is to acquaint clinicians and researchers in the field of urology with the potential role of exosomes as biomarker treasure chests and with their clinical value. EVIDENCE ACQUISITION Medline and Embase entries between 1966 and September 2010 were searched using the keywords exosomes, microvesicles, prostasomes, biomarkers, prostate cancer, and urology. Leading publications and articles constructively contributing to exosome research were selected for this review. EVIDENCE SYNTHESIS Exosomes are small vesicles (50-100 nm) secreted by almost all tissues; they represent their tissue origin. Purification of prostate- and PCa-derived exosomes will allow us to profile exosomes, providing a promising source of protein and RNA biomarkers for PCa. This profiling will contribute to the discovery of novel markers for the early diagnosis and reliable prognosis of PCa. CONCLUSIONS Although the initial results are promising, further investigations are required to assess the clinical value of these exosomes in PCa.

Sample preparation issues for tissue imaging by imaging MS.

Imaging MS is a powerful technique that combines the chemical and spatial analysis of surfaces. It allows spatial localization of multiple different compounds that are recorded in parallel without the need of a label. It is currently one of the rapidly developing techniques in the proteomics toolbox. Different complementary imaging MS methods, i.e. MALDI and secondary ion MS imaging for direct tissue analysis, can be applied on exactly the same tissue sample. This allows the identification of small molecules, peptides and proteins present on the same sample surface. Sample preparation is crucial to obtain high quality, reliable and reproducible complementary molecular images. It is essential to optimize the conditions for each step in the sample preparation protocol, ranging from sample collection and storage to surface modification. In this article, we review and discuss the importance of correct sample treatment in case of MALDI and secondary ion MS imaging experiments and describe the experimental requirements for optimal sample preparation.

Quantitative Proteomics and Metabolomics Analysis of Normal Human Cerebrospinal Fluid Samples

The analysis of cerebrospinal fluid (CSF) is used in biomarker discovery studies for various neurodegenerative central nervous system (CNS) disorders. However, little is known about variation of CSF proteins and metabolites between patients without neurological disorders. A baseline for a large number of CSF compounds appears to be lacking. To analyze the variation in CSF protein and metabolite abundances in a number of well-defined individual samples of patients undergoing routine, non-neurological surgical procedures, we determined the variation of various proteins and metabolites by multiple analytical platforms. A total of 126 common proteins were assessed for biological variations between individuals by ESI-Orbitrap. A large spread in inter-individual variation was observed (relative standard deviations [RSDs] ranged from 18 to 148%) for proteins with both high abundance and low abundance. Technical variation was between 15 and 30% for all 126 proteins. Metabolomics analysis was performed by means of GC-MS and nuclear magnetic resonance (NMR) imaging and amino acids were specifically analyzed by LC-MS/MS, resulting in the detection of more than 100 metabolites. The variation in the metabolome appears to be much more limited compared with the proteome: the observed RSDs ranged from 12 to 70%. Technical variation was less than 20% for almost all metabolites. Consequently, an understanding of the biological variation of proteins and metabolites in CSF of neurologically normal individuals appears to be essential for reliable interpretation of biomarker discovery studies for CNS disorders because such results may be influenced by natural inter-individual variations. Therefore, proteins and metabolites with high variation between individuals ought to be assessed with caution as candidate biomarkers because at least part of the difference observed between the diseased individuals and the controls will not be caused by the disease, but rather by the natural biological variation between individuals.

Biomedical application of MALDI mass spectrometry for small-molecule analysis

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) is an emerging analytical tool for the analysis of molecules with molar masses below 1,000 Da; that is, small molecules. This technique offers rapid analysis, high sensitivity, low sample consumption, a relative high tolerance towards salts and buffers, and the possibility to store sample on the target plate. The successful application of the technique is, however, hampered by low molecular weight (LMW) matrix-derived interference signals and by poor reproducibility of signal intensities during quantitative analyses. In this review, we focus on the biomedical application of MALDI-MS for the analysis of small molecules and discuss its favorable properties and its challenges as well as strategies to improve the performance of the technique. Furthermore, practical aspects and applications are presented.

Identification of a putative protein-profile associating with tamoxifen therapy-resistance in breast cancer

Tamoxifen resistance is a major cause of death in patients with recurrent breast cancer. Current clinical factors can correctly predict therapy response in only half of the treated patients. Identification of proteins that are associated with tamoxifen resistance is a first step toward better response prediction and tailored treatment of patients. In the present study we intended to identify putative protein biomarkers indicative of tamoxifen therapy resistance in breast cancer using nano-LC coupled with FTICR MS. Comparative proteome analysis was performed on ∼5,500 pooled tumor cells (corresponding to ∼550 ng of protein lysate/analysis) obtained through laser capture microdissection (LCM) from two independently processed data sets (n = 24 and n = 27) containing both tamoxifen therapy-sensitive and therapy-resistant tumors. Peptides and proteins were identified by matching mass and elution time of newly acquired LC-MS features to information in previously generated accurate mass and time tag reference databases. A total of 17,263 unique peptides were identified that corresponded to 2,556 non-redundant proteins identified with ≥2 peptides. 1,713 overlapping proteins between the two data sets were used for further analysis. Comparative proteome analysis revealed 100 putatively differentially abundant proteins between tamoxifen-sensitive and tamoxifen-resistant tumors. The presence and relative abundance for 47 differentially abundant proteins were verified by targeted nano-LC-MS/MS in a selection of unpooled, non-microdissected discovery set tumor tissue extracts. ENPP1, EIF3E, and GNB4 were significantly associated with progression-free survival upon tamoxifen treatment for recurrent disease. Differential abundance of our top discriminating protein, extracellular matrix metalloproteinase inducer, was validated by tissue microarray in an independent patient cohort (n = 156). Extracellular matrix metalloproteinase inducer levels were higher in therapy-resistant tumors and significantly associated with an earlier tumor progression following first line tamoxifen treatment (hazard ratio, 1.87; 95% confidence interval, 1.25–2.80; p = 0.002). In summary, comparative proteomics performed on laser capture microdissection-derived breast tumor cells using nano-LC-FTICR MS technology revealed a set of putative biomarkers associated with tamoxifen therapy resistance in recurrent breast cancer.

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.

Differential expression and prognostic significance of SOX genes in pediatric medulloblastoma and ependymoma identified by microarray analysis

The objective of this study was to identify differentially expressed and prognostically important genes in pediatric medulloblastoma and pediatric ependymoma by Affymetrix microarray analysis. Among the most discriminative genes, three members of the SOX transcription factor family were differentially expressed. Both SOX4 and SOX11 were significantly overexpressed in medulloblastoma (median, 11-fold and 5-fold, respectively) compared with ependymoma and normal cerebellum. SOX9 had greater expression in ependymoma (median, 16-fold) compared with normal cerebellum and medulloblastoma (p<0.001 for all comparisons). The differential expression of the SOX genes was confirmed at the protein level by immunohistochemical analysis. Survival analysis of the most discriminative probe sets for each subgroup showed that 35 and 13 probe sets were predictive of survival in patients with medulloblastoma and ependymoma, respectively. There was a trend toward better survival with increasing SOX4 expression in medulloblastoma. SOX9 expression was predictive for favorable outcome in ependymoma. The mRNA levels of BCAT1, a mediator of amino acid breakdown, were higher (median, 15-fold) in medulloblastoma patients with metastases compared with those without metastasized disease (p<0.01). However, the correlation between BCAT1 expression and metastatic medulloblastoma could not be confirmed at the protein level. The potential prognostic effect of the genes associated with outcome should be evaluated in ongoing studies using larger groups of patients. Furthermore, our findings support further analysis of the functional properties of the selected genes, especially SOX4 and BCAT1 for medulloblastoma and SOX9 for ependymoma, to evaluate the use of these genes as potential tumor markers, prognostic markers, and drug targets in pediatric brain tumors.

Identification of Differentially Regulated Splice Variants and Novel Exons in Glial Brain Tumors Using Exon Expression Arrays

Aberrant splice variants are involved in the initiation and/or progression of glial brain tumors. We therefore set out to identify splice variants that are differentially expressed between histologic subgroups of gliomas. Splice variants were identified using a novel platform that profiles the expression of virtually all known and predicted exons present in the human genome. Exon-level expression profiling was done on 26 glioblastomas, 22 oligodendrogliomas, and 6 control brain samples. Our results show that Human Exon arrays can identify subgroups of gliomas based on their histologic appearance and genetic aberrations. We next used our expression data to identify differentially expressed splice variants. In two independent approaches, we identified 49 and up to 459 exons that are differentially spliced between glioblastomas and oligodendrogliomas, a subset of which (47% and 33%) were confirmed by reverse transcription-PCR (RT-PCR). In addition, exon level expression profiling also identified >700 novel exons. Expression of approximately 67% of these candidate novel exons was confirmed by RT-PCR. Our results indicate that exon level expression profiling can be used to molecularly classify brain tumor subgroups, can identify differentially regulated splice variants, and can identify novel exons. The splice variants identified by exon level expression profiling may help to detect the genetic changes that cause or maintain gliomas and may serve as novel treatment targets.

Exosomal Secretion of Cytoplasmic Prostate Cancer Xenograft-derived Proteins

Novel markers for prostate cancer (PCa) are needed because current established markers such as prostate-specific antigen lack diagnostic specificity and prognostic value. Proteomics analysis of serum from mice grafted with human PCa xenografts resulted in the identification of 44 tumor-derived proteins. Besides secreted proteins we identified several cytoplasmic proteins, among which were most subunits of the proteasome. Native gel electrophoresis and sandwich ELISA showed that these subunits are present as proteasome complexes in the serum from xenograft-bearing mice. We hypothesized that the presence of proteasome subunits and other cytoplasmic proteins in serum of xenografted mice could be explained by the secretion of small vesicles by cancer cells, so-called exosomes. Therefore, mass spectrometry and Western blotting analyses of the protein content of exosomes isolated from PCa cell lines was performed. This resulted in the identification of mainly cytoplasmic proteins of which several had previously been identified in the serum of xenografted mice, including proteasome subunits. The isolated exosomes also contained RNA, including the gene fusion TMPRSS2-ERG product. These observations suggest that although their function is not clearly defined cancer-derived exosomes offer possibilities for the identification of novel biomarkers for PCa.