Proteomic profiling of rhabdomyosarcoma-derived exosomes yield

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Proteomic profiling of rhabdomyosarcoma-derived exosomes yield insights into their functional role in paracrine signaling. Ghina Rammal, Assil Fahs, Firas Kobeissy, Yehia Mechref, Jingfu Zhao, Rui Zhu, Mona Diab-Assaf, Raya Saab, and Sandra E. Ghayad J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.9b00157 • Publication Date (Web): 26 Aug 2019 Downloaded from pubs.acs.org on August 27, 2019

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Journal of Proteome Research

Proteomic profiling of rhabdomyosarcoma-derived exosomes yield insights into their functional role in paracrine signaling Ghina Rammal1,2, Assil Fahs1,2, Firas Kobeissy3, Yehia Mechref 4, Jingfu Zhao4, Rui Zhu4, Mona Diab-Assaf5, Raya Saab2,6*, Sandra E. Ghayad1*.

1 Department

of Biology, Faculty of Science II, EDST, Lebanese University, Fanar, Lebanon.

2 Department

of Anatomy, Cell Biology and Physiology, American University of Beirut, Beirut,

Lebanon. 3 Department

of Biochemistry & Molecular Genetics, Faculty of Medicine, American University

of Beirut, Lebanon. 4 Department

of Chemistry & Biochemistry, Texas Tech University, Lubbock, United States.

5 Department

of Chemistry and Biochemistry, Faculty of Sciences II, EDST, Lebanese

University, Fanar, Lebanon. 6 Department

of Pediatric and Adolescent Medicine, American University of Beirut, Beirut,

Lebanon.

*Co-correspondence to: Sandra E. Ghayad, Lebanese University, Faculty of Science II, Department of Biology, Fanar, Jdeidet, P.O. Box 90656, Lebanon. Phone: +961-1-686981. Fax: +961-1-377384. Email: [email protected] Raya Saab, American University of Beirut, Pediatric Hematology/Oncology, Riad El Solh Street, Beirut 1107 2020, Lebanon. Phone: +961-1-350000, ext. 4780. Fax: +961-1-377384. Email: [email protected]

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Abstract Exosomes are important intercellular communication vehicles, secreted into body fluids by multiple cell types, including tumor cells. They have been demonstrated to contribute to the metastatic progression of tumor cells through paracrine signaling. Tumor exosomes contain intact and functional protein, mRNA and miRNA that may alter the cellular environment to favor tumor growth. We evaluated the protein cargo of exosomes derived from the childhood tumor rhabdomyosarcoma (RMS) and the molecular pathways they are implicated in, to decipher their role in the progression of this aggressive disease. We conducted a mass spectrometry (MS) analysis of exosome content isolated from 5 RMS cell lines: 3 of embryonal (ERMS) and 2 of alveolar (ARMS) histology, and verified results by multiple reaction monitoring (MRM) and Western blot analyses. Results revealed 161 common proteins in ERMS-derived exosomes and 122 common proteins in ARMS-derived exosomes, of which 81 proteins were common to both subtypes. Using both PANTHER gene classification and Pathway Studio software, we assessed the perturbed biological processes and altered pathways in which the exosomal proteins are involved. The 81 commonly expressed proteins included those involved in “cell-signaling”, “cell-movement” and “cancer”. Pathways engaging the identified proteins revealed 37 common pathways including “integrin signaling pathway”, “inflammation mediated by chemokine and cytokine signaling pathway” and “angiogenesis”. Finally, comparison of exosomal proteins of RMS cells with publically available datasets from other cancer cells revealed that 36 proteins are specific and endogenous to the RMS-exosomes. Taken together, our results reveal that RMSderived exosomes carry a protein cargo that contributes to conserved cellular signaling networks across multiple cell lines, and we also identify RMS exosome specific proteins that should be further evaluated as possible novel biomarkers for this tumor. Keywords: Rhabdomyosarcoma, exosomes, proteomics, pathways. 2 ACS Paragon Plus Environment

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Introduction Rhabdomyosarcoma (RMS) is a pediatric malignancy of the connective tissues, where the abnormal cells are thought to arise from primitive mesenchymal cells with evidence of myogenic differentiation.1-3 RMS can develop in a variety of anatomic locations and is classified into two primary histologic types: embryonal RMS (ERMS) that develops mostly in infancy and early childhood, and alveolar RMS (ARMS) that carries a worse prognosis and is more common in later childhood and adolescence.1,4,5 The ARMS subtype is tightly connected to the presence of a chromosomal translocation resulting in the fusion of the gene encoding the transcriptional activation domain of FOXO1 (forkhead box O1) on chromosome 13, with either the gene encoding the DNA binding domain of PAX3 on chromosome 2 (t(2;13)(q35;q14)), or with PAX7 on chromosome 1 (t(1;13)(p36;q14)), the latter being the less common.6-8 Exosomes are 40-150 nm sized lipid bound vesicles secreted by many cell types, including immune cells and tumor cells.9 The unique protein, mRNA and miRNA exosomal contents contribute to the complex intercellular communication that occurs between malignant and normal cells.10,11 As they are biologically active vesicles secreted to the extracellular compartment, exosomes participate in several different functional pathways in addition to their main role in cell-cell communication.12 Secreted exosomes are taken up either by the same cells secreting them or by neighboring and distant cells, but alternatively they can enter the systemic circulation and reach different tissues, which makes them a more accessible tool for diagnostic purposes.13,14 Exosomes express consistent proteins considered as exosomal markers, which include the adhesion molecules (e.g. tetraspanins, integrins), chaperones (e.g. Hsp70 and Hsp90), membrane trafficking molecules (e.g. annexins and Rab proteins), proteins involved in multivesicular body formation (e.g. Alix, Tsg101 and clathrin), signal transduction proteins (e.g. protein kinases, and heterotrimeric G proteins), cytoskeleton molecules (e.g. actin and tubulin) 3 ACS Paragon Plus Environment


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and cytoplasmic enzymes (e.g. GAPDH, peroxidases, and pyruvate kinases). Nuclear, mithochondrial, or endoplastic proteins have not been identified in exosomes, and this can be explained by the endosomal origin of exosomes.12,15,16 Furthermore, exosomes harbor specific sets of proteins depending on their parental cells, which makes exosomes an interesting reservoir for potential biomarker discovery. Particular expression of some proteins, such as the major histocompatibility complex class II (MHC II), has been described on exosomes derived from antigen-presenting cells (B-cells or dendritic cells), and some tumor antigens such as Mart1/MelanA, are found in exosomes derived from melanoma tumor cells.17,18 Recently the contribution of proteomic profiling has been highly investigated in exosomal trafficking, signaling and biomarker investigaton in several fields including neuroscience, diabetes and cancer research.19,20 In fact, proteomic profiling of exosomes isolated from human cerebrospinal fluid identified a set of proteins that could be used as biomarkers for neurological disorders such as Alzheimer’s disease and brain injury.21,22 Moreover, proteomic proﬁling of exosomes derived from colorectal cancer cells linked the exosomal expression of MET to the metastatic potential of the cells.23 In metastatic melanoma, exosomes expressing MET increased the metastatic behavior of primary tumors by promoting the education and mobilization of bone marrow progenitor cells.24 Exosomes isolated from serum of prostate cancer patients were found to enclose tumorspecific proteins that could be used for early detection of cancer.25 In our previous study, we characterized the miRNA content of RMS-derived exosomes using a panel of human RMS cell lines. Despite the differences found between exosomes derived from the two subtypes of ARMS and ERMS, the most significant predicted diseases and functions were related to processes relevant to cancer and tissue remodeling for both histologies. Functional analyses revealed that RMS-derived exosomes have a positive effect on cellular proliferation of recipient cancer and normal cells; they were also able to induce cellular 4 ACS Paragon Plus Environment

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migration and invasion of normal fibroblasts, and to promote angiogenesis of endothelial cells.26 Thus, RMS-derived exosomes seem to be important players in promoting recipient cell invasive properties. In addition to the previous work on exososomal mRNA and miRNA changes, recent work has identified protein cargo of exosomes to be important in mediating metastatic phenotypes.27 Thus in this study, we interrogated and surveyed the protein composition of exosomes purified from cell culture supernatants of 5 different RMS cell lines, by LC-MS/MS technology and analysis using bio-informatics tools. We attempted to characterize the differences and similarities between exosomes derived from ERMS and ARMS cells, that may explain paracrine contributions to the aggressive behavior of ARMS. We also explored common as well as unique characteristics of RMS exosome protein content when compared to that of other cancer and non-cancer cells using available databases. Our results identify novel exosomal proteins that may contribute to RMS paracrine signaling, and can be explored as potential biomarkers for RMS in future clinical studies.



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Experimental Section Cell lines and culture Human RMS cell lines JR1, Rh30, Rh36, and Rh41 were generously donated by Dr. Peter Houghton (Columbus, OH, USA); and RD cell line was purchased from ATCC (Manassas, VA). RMS cell lines JR1, RD, Rh41 and Rh30 cells were cultured in Dulbecco's Modified Eagles Medium (DMEM, Sigma), and Rh36 was cultured in RPMI-1640 medium (Sigma). All media were supplemented with 10% fetal bovine serum (FBS, Sigma), 1% glutamine (Sigma), and 1% Pen/Strep (Sigma). Standard incubator conditions (humidified atmosphere, 95% air, 5% CO2, 37ºC) were applied for cell culture and cells were passaged twice weekly by trypsinization.

Exosome isolation Cells were incubated in 150 mm plates in exosome-free medium for 72 hours at 37°C and 5% CO2. The conditioned media were collected and exosomes isolated by differential centrifugation as previously described.28 Briefly, the collected conditioned medium was centrifuged at 4°C at 300 × g for 10 min, 2,000 × g for 20 min and 10,000 × g for 30 min. The resulting supernatant was ultracentrifuged at 4°C at 100,000 × g for 70 min. After each step, the pellet was discarded and the supernatant was used for the following step. The resulting pellet was washed in PBS and ultracentrifuged at 100,000 × g for 70 min at 4°C. Finally, PBS or lysis buffer was added to the pellet for protein extraction. For each cell line, biological triplicates were prepared. To prepare exosome-free medium, complete medium supplemented with 20% FBS was subjected to ultracentrifugation at 100,000 × g overnight at 4°C to effectively deplete exosomes. The resulting supernatant was filtered with 0.22 μm filter (Millipore), and diluted 1:1 in FBSfree medium to reach 10% FBS concentration.


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Scanning electron microscopy (SEM) To visualize the obtained exosomes and measure their sizes, the exosome pellets were prepared by fixation in 2% paraformaldehyde and 1% glutaraldehyde (Sigma). The sample was then applied to a continuous carbon grid, washed 8 times in distilled H2O, then dehydrated with graded ethanol steps, left to dry, and observed using a Zeiss SEM at 30 kV. To quantify the diameter of the photographed exosomes, we used ImageJ software (http://rsbweb.nih.gov/ij/).

Protein extraction and immunoblotting Cells and exosomes were lysed using CHAPS lysis buffer (30 mM Tris-Cl, pH 7.5; 150 mM NaCl; 1% CHAPS) mixed with 25X protease inhibitor (Roche), and sonicated. Proteins were quantified by Bradford method (Bio-Rad). Electrophoresis was performed using 10% acrylamide gel, proteins were transferred to polyvinylidene difluoride (PVDF) membranes (Bio-Rad) and probed with the following antibodies: anti-TSG101 (Abcam), anti-Hsc70, anti-GAPDH, antiBasigin, anti-Calnexin (all from Santa Cruz Biotechnology), anti-Fibronectin (Company), βActin (sigma) and appropriate species-specific HRP-conjugated secondary antibodies (SantaCruz), then detected using ECL reagent (Bio-Rad).

Detergent Removal and Protein Digestion Extracted proteins were first cleaned up and digested using filter assisted sample preparation (FASP) method. Aliquots were diluted 10 folds by adding 8M urea in 0.1 M Tris/HCl, pH = 8.5 (UA solution), loaded into nominal molecular weight cutoff of 3,000 filtration devices (Millipore) and centrifuged at 14, 000 g for 15 min. The concentrated samples were diluted with 300 µl of UA solution and centrifuged again. This step was performed twice. After centrifugation, 8M urea in 0.1 M Tris/HCl solution was added to the concentrates to make the 7 ACS Paragon Plus Environment


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final volume 200 µl. Then, disulfide bridges were reduced by addition of 5 µl of 200mM dithiothreitol (DTT) in UA solution and the mixture were incubated at 60˚C for 45 min. Reduced sulfide was further alkylated by adding 20 µl of 200mM iodoacetamide (IAA) in UA solution and 45-min incubation in darkness at 37.5 ˚C. Following a centrifugation, the concentrates were diluted with 300 µl of 50 mM ammonium bicarbonate solution and concentrated again. This step was repeated for additional 2 times and followed by adding 50 mM ammonium bicarbonate solution to make the final volume 200 µl. A portion of the reduced and alkylated proteins were separated from each sample for BCA protein assay. The rest of proteins were digested by Trypsin. Typsin/Lys C Mix (Promega) was added at a ratio of 1:25 (enzyme to protein, w/w) and the mixture was incubated at 37.5 ˚C for 18 h. Finally, peptides were collected by centrifugation followed by 2 additional washes with 300 µl of 50 mM ammonium bicarbonate. Collected follow-through was dried and re-suspended in 0.1% formic acid prior to LC-MS/MS analysis.

LC-MS/MS Analysis Analysis was performed on a Dionex 300 Ultimate nano-LC system (Dionex, Sunnyvale, CA) interfaced to a ESI equipped LTQ Orbitrap Velos mass spectrometer (Thermo Scientific, San Jose, CA). Aliquots of 1 µg tryptic digests was injected and first purified on-line using an Acclaim PepMap100 C18 guard column (3 µm, 100 Å, Dionex) at a flow rate of 3 µl/min. The separation of purified peptides was achieved using an Acclaim PepMap100 C18 capillary column (75 µm id × 150 mm, 2 µm, 100 Å, Dionex) at 0.35 µl/min in 120 min. The LC gradient was as follow: Solvent B was kept at 5% for 0-10 min, increased from 5% to 20% for 10-65 min, 20%-30% for 65-90 min, 30-50% for 90-110 min, 50%-80% for 110-111 min, 80% for 111-115 min, decreased from 80% to 5% for 115-116 min and maintained at 5% over 4 min. Solvent B


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contained 99.9% acetonitrile and 0.1% formic acid, while solvent A was 2% ACN and 0.1% FA in water. The LTQ Orbitrap Velos was set to perform two scan events in data dependent acquisition mode. The first scan was a full MS scan of m/z 400-2000 at a mass resolution of 15,000. The second scan event was a CID MS/MS repeated on top 10 intense ions selected from the first scan event with an isolation window of m/z 3.0. The normalized collision energy was set to 35% with an activation Q value of 0.25 and activation time of 10 ms. The dynamic exclusion was enabled with repeat count of 2, repeat duration of 30 seconds and exclusion duration of 90 seconds. Results acquired from untargeted quantitative analysis were confirmed by multiple reactions monitoring (MRM) experiment. Samples subjected to the MRM experiment were from the same aliquots of samples used in the untargeted proteomic analysis. The transition list was generated using Pinpoint 1.4 (Thermo Scientific, San Jose, CA). Briefly, for each protein, one or two peptides were selected based on the following criteria: (i) identified in the untargeted analysis with a Scaffold probability higher than 95%; (ii) completely digested, (iii) 7–25 amino acid residues at the protein N-terminus; (iv) excluding peptides with M, RP, KP, potential glycosylation site (NXS/T), and ragged ends (cleaved between K/K, K/R, R/R and R/K); (v) fixed carbamidomethylation of Cysteine; (vi) with the length of 7-25 amino acid residues; and (vii) with m/z values of 300-1500. Next, five transitions of selected peptides were determined as follow: (i) generated from precursors with two or three charges, (ii) singly charged y series of fragment ions (greater than y3), (iii) the five most intense fragment ions in the MS/MS spectra from untargeted analysis, and (iv) with m/z values between 300 to 1500. In total, 45 common proteins in RD, Rh36 and JR1, with 88 peptides and 264 transitions were finally selected for the MRM experiment. A list of MRM transitions used is provided in Supplementary Table S1. Aliquots of 1.5 µg of peptides derived from exosomes were subjected to LC-MRM-MS analysis. 9 ACS Paragon Plus Environment


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LC gradient was as described above. The TSQ Vantage mass spectrometer was operated in positive ion mode with an ESI spray voltage of 1800 V. The MRM experiment was run with chromatogram filter peak width as 10.0 s and collision gas pressure as 1.5 mTorr. In the SRM setting, Q1 peak width (full width at half maximum) was set as 0.70 Da and cycle time was set as 6.0 s. The collision energy (CE) for each targeted peptide is predicted by Pinpoint using following equations: 𝐶𝐸( +2) = 0.034 × 𝑚 𝑧 +3.314(𝑒𝑉), 𝐶𝐸( +3) = 0.044 × 𝑚 𝑧 +3.314(𝑒𝑉). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD007755. For untargeted LC-MS/MS data, the aquired raw data were converted to mascot generic format (*.mgf) files using Proteome Discover version 1.2 (Thermo Scientific, San Jose, CA). The *.mgf files were subjected to MASCOT version 2.4 (Matrix Science Inc., Boston, MA) and searched against UniProt database (Homo sapiens, 20214 entries). Carbamidomethylation of cysteine set as fixed modification and oxidation of methionine was set as variable modification. Peptides were matched with tolerence of 6 ppm and 0.8 Da for precusor ions and fragments, respectively. Enzyme was specified as trypsin and a maxinum of 2 miscleavage was allowed. MASCOT searching results were then uploaded to Scaffold (version 3.6.3, Proteome Software, Portland, OR) for verification and quantification based on spectral count. Identifications considered for quantification were selected using following parameters: Peptide threshold = 95%, protein thresholds = 99% and the minimum number of identified peptides for a protein was 2. The subsequent bioinformatic analyses and PCA analysis were performed based on the untargeted analysis using all the identified proteins. MarkerView 1.1 (AB Sciex, Framingham, MA) was used for PCA analysis.


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For the MRM LC-MS/MS analysis, the quantitation was based on peak areas. All raw files acquired from MRM experiment were imported into Pinpoint 1.4 (Thermo Scientific, San Jose, CA) to determine peak areas. The abundance of a protein was presented by the summation of peak areas of all the corresponding transitions. Peak areas were averaged using triplicates for the comparison between groups. The protein abundance is the sum-up of peak areas of selected transitions. The resultant quantitative values of proteins acquired from MRM analysis were subjected to One-way ANOVA followed by Tukey HSD test (95% confidence interval, q-value ≤ 0.05) using IBM Statistics (IBM, version 25.0).

Bioinformatic Analysis For gene ontology (GO) analysis, including differential molecular function and biological processes, PANTHER software (Protein Analysis Through Evolutionary Relationships; http://www.pantherdb.org/genes/batchIdSearch.jsp) was used to classify genes into distinct categories of molecular functions and biological processes. Genes were classified into families and subfamilies of shared function, which are then categorized using a highly controlled vocabulary (ontology terms) by biological process and molecular function. Functional pathways and protein association were examined using the computation bioinformatics program, Pathway Studio® software (v.11.4.0.8; Elsevier) as previously described.29,30 This bioinformatics platform enables the analysis and visualization of altered pathways and protein network association needed to construct and recognize altered cellular processes and involved molecular functional pathways. The “Subnetwork Enrichment Analysis” (SNEA) algorithm was used to extract statistically significant altered biological and functional pathways pertaining to each identified set of exosomal proteins. SNEA utilizes Fisher's statistical test used to determine if there are nonrandom associations between two categorical variables 11 ACS Paragon Plus Environment


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organized by a specific relationship. SNEA starts by creating a central "seed" from all relevant entities in the database, and retrieving associated entities based on their relationship with the seed (binding partners, expression targets, protein modification targets, regulation). The algorithm compares the sub-network distribution to the background distribution using one-sided Mann-Whitney U-Test and calculates a p-value indicating the statistical significance of difference between two distributions. For the background reference, we used the human genome (protein) database, for absence of a more suitable background reference control for our experimental setup. Published datasets of exosomes were identified using the Exocarta repository (http://www.exocarta.org/), for comparison analyses with protein cargo of exosomes derived from other normal and cancerous human cell lines and physiological fluids.


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Results RMS cells secrete detectable amounts of exosomes with specific protein cargo To evaluate the protein content of RMS exosomes, we used a panel of 5 well-characterized human RMS cell lines, 3 of which (RD, JR1, Rh36 cells) are derived from ERMS tumors, and 2 (Rh30, Rh41) from ARMS tumors.31 We isolated exosomes by standard methodology of ultracentrifugation28, and verified that the isolated particles were indeed consistent with exosomes, via scanning electron microscopy to confirm shape and size, and Western blotting to evaluate exosomes protein markers, as previously described (Figure 1).26,32 We next subjected extracted exosome proteins to LC-MS/MS proteomics analysis, and the results showed excellent reproducibility within each cell line (Figure 2A,B). Only the proteins present in at least 2 replicates from the biological triplicates performed were taken into consideration for the rest of the study. LC-MS/MS analysis identified a total of 243 proteins in JR1-derived exosomes, 289 in RD-derived exosomes, and 364 in Rh36-derived exosomes. Of those, 161 proteins were common to all three ERMS-derived exosomes (Figure 2C). We noted that 134 proteins were exclusively identified in the Rh36-derived exosomes, while the other 2 cell lines had largely overlapping exosome protein content. This is in accordance with our results on the miRNA cargo where Rh36 cargo was notably different from the remainder of the examined cell lines. The complete lists of identified and quantified proteins derived from ERMS exosomes are provided in Supplementary Table S2. For the ARMS-derived exosomes, results revealed the presence of 157 proteins within Rh30 exosomes and 242 proteins within Rh41 exosomes, with 122 commonly expressed proteins (Figure 2D). The complete lists of identified and quantified proteins derived from ARMS exosomes are provided in Supplementary Table S3. In comparing both groups, we found 80 proteins common to all 5 cell lines, while 81 were specific to the ERMS group and 42 specific to the ARMS group (Figure 2E). 13 ACS Paragon Plus Environment


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LC-MS/MS results were then verified by multiple reactions monitoring (MRM)-mass spectrometry assays for a subset of proteins identified to be common among ERMS (Figure 3A). Quantitative results of the 45 proteins from MRM-LC-MS/MS analysis is summarized in Supplementary Table S4. The assessment of differentially expressed proteins was based on performing one-way ANOVA followed by Tukey HSD test. In the comparison of RD and JR1 cell lines, 6 proteins were differentially expressed between the two cell lines (q-value ≤ 0.05 at confidence interval of 095%). A total of 20 proteins were determined to be differentially expressed (q-value ≤ 0.05 at confidence interval of 095%) in the comparison of JR1 and Rh36 cell line. The contradictions between MRM and untargeted results are possibly due to the different quantitation methods used, especially for low abundant proteins. The quantitation employed in untargeted analysis was spectral counting, while the quantitation of MRM analysis 15 ACS Paragon Plus Environment


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was based on peak area values. We also used western blotting (Figure 3B) to verify a subset of proteins identified to be common among both ERMS and ARMS cell lines.


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Proteins common among RMS-derived exosomes map to a distinct set of molecular and biological functions To understand the potential role of RMS-derived exosomes in impacting tumor microenvironment as mediators of cell-cell communication, first we analyzed the identified proteins using PANTHER gene classification system (http://www.pantherdb.org), to unveil the relevant biological processes, molecular functions and pathways potentially influenced by these proteins. The analysis of the 80 common proteins (listed in Supplementary Table S5) depicted that the 4 major molecular function groups were catalytic, binding, structural, and receptor activities (Figure 4A). Importantly, analysis of biological processes revealed that 28% of proteins (n=47) were involved in cellular processes including cell communication in 50%, cell cycle in 24%, and cellular component movement in 16%. Another 27 proteins (16% of all proteins) were involved in metabolic processes, while other identified function groups included cellular component organization or biogenesis (n=18 proteins, 11%), localization (n=17, 10%), developmental process (n=12, 7%), immune system (n=12, 7%), among others (Figure 4B). We conclude that the identified molecular functions and biological processes are in accordance with paracrine signaling-related functions consistent with exosome role, as well as cell cycle and cell communication functions important in cancer growth and invasion.



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Exosome protein cargo of the different cell lines converge on common cancer-related biological pathways To identify whether protein cargo of exosomes from different cell lines could contain distinct proteins that may eventually converge on common cellular pathways, we separately analyzed the exosome protein content for each RMS cell line and identified both common and unique pathways influenced by the individual protein networks. Using Pathway Studio 9.0 software, the subnetwork enrichment analysis (SNEA) algorithm identified a set of pathways enriched within the protein cargo of each cell line. We then identified as present pathways that have at least 2 enriched proteins. Interestingly, we found that the exosome-derived proteins of the different cell 18 ACS Paragon Plus Environment

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lines shared a majority of pathways. Exosome proteins from the 3 ERMS cell lines shared 79 common pathways, exosome proteins from exosomes of the 2 ARMS cell lines shared 82 common pathways, and exosome proteins from all 5 cell lines shared 64 common pathways (Figure 5A-C). The 15 most significantly represented pathways in exosomes of all 5 cell lines were related to tumor cell invasion, proliferation and metastasis, such as “cell proliferation”, “apoptosis’, ‘differentiation”, “cell adhesion”, “cell migration”, “metastasis”, “vascularization” among others (Figure 5D, and Supplementary Table S6). Interestingly, there were 15 and 18 pathways exclusive to ERMS- and ARMS-derived exosome proteins, respectively, primarily related to immune modulation and inflammation in ARMS (Figure 5E), and cell adhesion, migration, and tumorigenesis in ERMS (Figure 5F). Together, this information shows that, even though the proteins in the exosomes of the different RMS cell lines may individually differ, they largely converge on a set of common biological pathways that are important in cellular invasion and cell communication, likely leading to similar functional outcome in recipient cells.



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Our previous work in these 5 RMS cell lines,26 and others’ work in other tumor cell types,24,33-35 have highlighted a primary role of tumor-derived exosomes in enhancing recipient cell invasion, migration, colony formation, and angiogenesis. We therefore focused on the specific identified pathways related to “cell invasion”, “cell migration” and “neoplasm metastasis”, to generate a network linking the identified exosome proteins. The identified networks showed a high degree of interrelatedness of the involved proteins (Figure 6), with several proteins being common 20 ACS Paragon Plus Environment

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between the three pathways, further corroborating the importance of these proteins in cellular functions related to invasion and metastasis in this context. To identify the specific signaling pathways influenced by each cell line exosome protein content, we next conducted a similar analysis using PANTHER gene classification. We found that proteins from all 3 ERMS-derived exosomes shared 40 identified signaling pathways, proteins from the 2 ARMS-derived exosomes shared 24 pathways, and exosome-derived proteins from all 5 cell lines shared 22 signaling pathways (Supplementary Figures S1A-C). Interestingly, the integrin signaling pathway was the most significantly represented in all 5 cell lines (Supplementary Figure S1D). Proteins identified in this pathway are listed in Supplementary Table S7. Some proteins were found common to all RMS cells, several were common to ERMS cells, and a few proteins were specific to one of the ARMS cell lines, whereas ACTC1 was present in both ARMS cells but not in ERMS. By western blotting, we verified expression of a subset of these proteins, specifically Beta-actin, Fibronectin and Basigin (Figure 3B). Other represented pathways included those involved in inflammation and immune modulation (inflammation/chemokine and cytokine release pathways, CCKR signaling, B-cell activation), growth signaling (Wnt, FGF, EGF, and Ras signaling pathways), among others (Supplementary Figures S1D and Supplementary Table S8). Interestingly, the 2 unique pathways identified in the ARMS group were related to DNA replication and FAS signaling pathway; while pathways uniquely identified in the ERMS group included TGF-beta, RAS, PI3 Kinase, IGF, and MAPK signaling pathways (Supplementary Figure S1E), all of which have been previously described to play an important role in ERMS biology. These findings further confirm that, while ARMS and ERMS tumors share common biologic behaviors likely mediated through common cellular pathways, they also utilize specific signaling mechanisms that contribute to the observed differences in clinical behavior including different propensity for invasion and metastatic spread. 21 ACS Paragon Plus Environment


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When comparing the two analyses: the Pathway Studio network represented in Figure 6 and PANTHER signaling pathways, we noted that several proteins in the Integrin signaling pathway were also identified within the Pathway Studio network, including ACTB, BSG, FN1, ITGB1, COL3A1, COL4A1 and COL5A1 (Figure 6 and Supplementary Table S7). This further underscores the relevance of the Integrin signaling pathway in this context, likely to have a specific role in cell invasion, migration and metastasis, all of which are relevant for the observed RMS aggressive clinical features.

RMS exosome content shows both overlapping and distinct proteins when compared to database of exosome proteins from other cell types Since exosomes are secreted by all tumor cell types, as well as by immune cells and normal stem cells,33,36,37 we sought to determine whether the protein cargo of the RMS tumor cells differs from that described for other cell lines. We used the publically available exosome protein


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database Exocarta (http://www.exocarta.org), to compare our identified protein sets with those identified for exosomes of normal cells, and of other tumor cell types. We found that RMSderived exosomes shared an average of 32% (S.D. ±16) of protein cargo with normal (noncancer) cells (Figure 7A). This ranged from a highest value of 57% overlap with proteins in exosomes of normal thymus cells, to a lowest of 9% overlap with those derived from endothelial cell exosomes (Figure 7A). When comparing to protein content of cancer-derived exosomes, we found an average of 50% overlap (S.D. ±15) (Figure 7B). Interestingly, this also depicted a wide range, with the highest overlap of 67% with ovarian cancer exosome cargo, to a lowest of 31% in common with bladder cancer-derived exosomes (Figure 7B). We then compared the RMS exosome protein content to the sum total of all proteins reported in Exocarta from normal cell-derived exosomes, and found that 441 proteins were common (Figure 7C), while 460 proteins were in common with all proteins reported for cancer cell-derived exosomes (Figure 7D). As would be expected, common proteins among RMS-exosomes, normal cell derived exosomes, and cancer derived exosomes, included previously characterized exosomal markers such as Heat shock proteins, vacuolar protein sorting-associated proteins (VPS28, and VPS37B), tetraspanins (CD9, CD81 and CD82), charged multivesicular body proteins (CHMP4B and CHMP5), annexins and cytoskeletal proteins. Importantly, 83 proteins identified in RMS-derived exosomes have not yet been reported in normal cell-derived exosomes (Figure 7C) and 63 proteins have not yet been reported in exosomes of other tumor types (Figure 7D). Of those, 36 proteins seem to be exclusively expressed in RMS exosomes (Figure 7E, listed in Supplementary Table S9). Thus, these proteins are of particular interest for further consideration as potential biomarkers of RMS, to be investigated in future studies.



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Discussion Rhabdomyosarcoma (RMS) is the most common soft tissue tumor in children.38 The two main subtypes are of embryonal (ERMS) and alveolar (ARMS) histologies, respectively.1 The chromosomal translocations that are selectively characteristic for ARMS are t(2;13)(q35;q14) and t(1;13)(p36;q14), which lead to the generation of fusion genes, PAX3-FOXO1 (2q35) or PAX7-FOXO1 (1p36), respectively.39 On the other hand, ERMS-type tumors show recurrent changes in a number of chromosome pairs, including Chr. 2, 7, 8, 11, 12, 13, and 20.8 As ARMS tumors are clinically more aggressive and associated with a higher rate of metastasis, it is likely that paracrine signaling pathways may differ and contribute to the particular metastatic phenotypes of the two tumor subtypes. Exosomes are small membrane-bound vesicles secreted by various cell types.40 Recently, several studies have proven that exosomes play important roles in cellular processes and communication. Studies in colorectal cancer,41 bladder cancer,42 prostate cancer,43 and pancreatic cancer44 have highlighted the roles of several exosomal molecules in cell communication important for tumor invasion and progression. In RMS, little is known about the role of paracrine signaling in tumor progression, and specifically no studies have previously focused on proteinmediated cellular communication via exosomes in this aggressive tumor type. Our current work has now identified a set of specific proteins involved in oncologically-relevant cellular and signaling pathways that are common to RMS tumor cells of both histologies, as well as a subset that is specific to ERMS and ARMS tumor cells, respectively. This key information now paves the way for mechanistic studies into the role of these specific pathways in paracrine RMS signaling in invasion and metastasis, with the aim of developing novel diagnostic and prognostic biomarkers, as well as potential therapeutic targets in RMS.



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Among the ERMS tumor cells, JR1 and RD cell lines had very similar protein cargo, with 219 proteins commonly expressed in their corresponding exosomes, whereas Rh36-derived exosomes had a set of 134 unique proteins. These findings are in accordance with our previous results where the exosomal miRNA cargo of Rh36 was found to be distinctive from the other ERMS-derived exosomes.26 However, when the exosome proteins were analyzed by pathways, the overlap was much higher among ERMS cells, with only 19 out of 100 pathways being unique to Rh36. This suggests that, even though proteins may differ, the majority are involved in similar signaling pathways and biologic processes. Importantly, we identified 80 commonly enriched exosomal proteins from all five RMS cell lines, with an additional 81 and 42 proteins that were specific to ERMS and ARMS exosomes, respectively. The common proteins were primarily involved in cell cycle checkpoint, cell communication, inflammation, and growth. When biologic pathways were analyzed using Pathway Studio, there were 64 common pathways, with only 15 and 18 additional pathways specific to ERMS and ARMS exosome proteins, respectively. Similarly, analysis of cellular signaling pathways using PANTHER showed a similarly high overlap, with 22 common signaling pathways, compared to 18 and 2 unique pathways to ERMS and ARMS exosome proteins, respectively. These results underscore the finding that, while different proteins may be identified in exosomes of similar tumor types, they may be involved in similar paracrine processes and end functions, contributing to a similar cellular phenotype. Our analysis of biologic (via Pathway Studio) and signaling (via PANTHER) pathways were complementary, as each gave a different insight into processes predicted to be affected by the protein cargo. The pathways identified by PANTHER (integrin, FGF, EGF, Wnt, inflammation, etc..), are likely integral to the biologic processes identified by Pathway Studio (cell proliferation, apoptosis, migration, adhesion, metastasis, etc..).


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PANTHER pathway analysis revealed enrichment with signal transduction proteins involved in immune regulation and inflammation (inflammation/chemokine and cytokine release pathways, CCKR signaling, B-cell activation), growth signaling (Wnt, FGF, EGF, and Ras signaling pathways), and integrin signaling. It is well recognized that inflammation and growth are important or even decisive factors for tumorigenesis.45 Interestingly, exosomes have been shown to induce inflammatory responses in different cancers such as lung cancer.46 The involvement of exosomal proteins of RMS tumors in “inflammation mediated by cytokines and chemokines” pathway might reflect a contribution of exosomes to immunomodulation during cancer spread, and should be further mechanistically investigated, using ex vivo and in vivo preclinical models. In addition, the identified growth signaling pathways are already well known to contribute to RMS biology, specifically Wnt, FGF, EGF, and Ras,3 and therefore our findings reflect the underlying biology of RMS cells as well. As for the integrin pathway, it has been implicated in several pro teomic studies of exosomes derived from different cancer cells. In fact, Liang et al. showed in an analysis of exosomal proteins of ovarian cancer cell lines, that the integrin signaling pathway included the highest number of overlapping proteins among the different cell lines.47 Recently, Hoshino et al. discovered that exosomal integrins could be used to predict organ-specific metastasis, where the exosomal integrins α6β4 and α6β1 were associated with lung metastasis, while exosomal integrin αvβ5 was linked to liver metastasis. These results suggest that exosomal integrins could act as organotropism biomarkers.27 Additionally, in an unsupervised IPA network analysis of proteins identified within pancreatic cancer-derived exosomes, a biological network function in cell-to-cell signaling and interaction centered upon 3 main integrin superfamily members.48 All this data underscores the relevance of the integrin pathway to exosome signaling in tumor cells, including RMS tumor cells, as identified in our analysis. 27 ACS Paragon Plus Environment


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In our previous study, we characterized the miRNA cargo of RMS-derived exosomes and revealed 10 commonly enriched miRNA among the 106 identified between the 2 subtypes.26 Importantly, 24 and 52 miRNA were specific to ERMS and ARMS-derived exosomes, respectively. Putting this information together with the currently generated protein data, we compared the signaling networks established from the commonly identified miRNA and proteins within ERMS- and ARMS-derived exosomes (Supplementary Figure S2). The resultant maps revealed 2 major nodes revolving around Ras and Vimentin. Ras is a well described oncoprotein that plays a crucial role in RMS biology, specifically in ERMS,3,8 and can serve as master regulator of signaling cascades involved in cell cycle progression, growth, migration, cytoskeletal changes, apoptosis, and senescence.49 Vimentin, which is a major constituent of the intermediate filament family of proteins is overexpressed in various cancers, including around 55% of RMS.50 Its overexpression has been correlated with accelerated tumor growth, invasion, and poor prognosis.51 These biologic pathways converged upon by both the miRNA and protein exosome cargo in RMS cells points to these two nodes as possible mediators of our observed effect of RMS-derived exosomes on inducing cellular invasion, migration, and proliferation in recipient cells.26 Further studies will now focus on specifically dissecting the molecular contribution of these two networks to RMS paracrine signaling in tumor invasion and progression. Moreover, of the 80 exosomal proteins common to all cell lines (Supplementary Table S5), several have been identified as potential biomarkers for diagnosis and prognosis of different types of cancer, including Annexin A2 (ANX A2) and 14-3-3 protein zeta (YWHAZ). ANX A2 is a multifunctional protein that mediates many aspects of intercellular and extracellular microenvironment communications and cell survival. Published data from clinical and experimental studies suggests that ANX A2 is a molecular signature for aggressive and 28 ACS Paragon Plus Environment

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metastatic cancers and may be considered as a biomarker for diagnosis and prognosis for glioma52, pancreatic ductal adenocarcinoma (PDA),53 lung cancer,54 and laryngeal cancer.55 Furthermore, ANX A2 is one of the most highly expressed proteins in exosomes, and it plays a role in angiogenesis and metastasis of breast cancer.56 As for YWHAZ, it has been reported to be widely expressed in various cancers and plays a critical role in tumorigenesis and progression via interacting with cellular proteins involved in intracellular signaling, cell transcription regulation, proliferation and apoptosis.57 The overexpression of YWHAZ is generally associated with malignant biological behavior and worse outcomes in many tumor types, such as ovarian,58 gastric,59 lung,60 and prostate cancer,61 and has been suggested as a promising prognostic biomarker. As expected, a proportion of identified proteins in exosomes of RMS cell lines included those common to other exosomes from various cell types. Such proteins include TSG101, Alix, heat shock proteins, tetraspanins, annexins, and cytoskeletal proteins, which are known to be associated with biogenesis, structure and trafficking of exosomes. By comparing the identified exosomal proteins with those deposited in the ExoCarta database, we found that 441 proteins (32%) were present in exosomes reported from normal cells, and 460 proteins (50%) in cancerderived exosomes. Interestingly, we found that 36 of the identified proteins have not been previously described in other cell type derived exosomes in the Exocarta database. Among those proteins, we identified molecules involved in cell proliferation, migration and invasion, such as BMP1,62 CDKN2A63 or ITGA7.64 Such proteins, if verified to indeed be specific to RMS exosomes, would be interesting candidates as RMS biomarkers. Further studies would need to investigate clinical serum samples of patients with RMS, compared to the appropriate serum sample controls of patients with other different tumor types, as well as serum from non-cancer



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controls, and utilize Elisa or western blotting techniques to identify and validate the relevant proteins from the generated list.


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Acknowledgements This work was supported by a grant from the Lebanese University (to SEG), and an MPP grant by the American University of Beirut Faculty of Medicine (to RS). GR had a PhD funding by Azm and Saade association. The authors thank the core facilities at the American University of Beirut Faculty of Medicine for the infrastructure and support.



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Figure Legends Figure 1. Isolation and characterization of RMS-derived exosomes. Schematic of the experimental workﬂow used in the study. ERMS and ARMS cells were grown in exosome-free media for 72 h. Small microvesicles were first isolated from the culture media by differential centrifugation. The supernatant was further centrifuged twice at 100 000×g for 70 minutes. Following ultracentrifugation, the pellets were resuspended in PBS for morphological identification by SEM, or lysed for protein extraction. The isolated microvesicles were validated as exosomes by western blot. The quantified proteins were subjected to LC-MS/MS analysis verified by MRM and western blot. Exosomal protein cargo was analyzed by bio-informatic tools.

Figure 2. Protein profiling of RMS-derived exosomes by LC-MS/MS. (A) and (B) Score plots obtained by principal component analysis (PCA) for exosomal proteins derived from: Rh36 (Red), RD (Blue), JR1 (green), Rh30 (orange) and Rh41 (purple) cell lines isolated from 3 biological replicates, using quantitative results of all the identified proteins from untargeted analysis. (C-F) Venn diagrams of the expressed proteins in exosomes derived from: (C) the 3 ERMS cell lines; (E) the 2 ARMS cell lines; and (F) the common ERMS and ARMS cell lines, as specified.

Figure 3. Verification of LC-MS/MS results. (A) MRM quantitation for 45 common proteins in ERMS-derived exosomes in terms of ratio between RD exosomes and Rh36 exosomes versus JR1 exosomes, respectively. Bars represent standard deviation among the triplicates. Asterisks denote a statistically significant difference (p-value < 0.05). (B) Western blot for the indicated


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proteins in exosomes “E” and respective cell “C” lysates, as indicated, for each of the RMS cell lines.

Figure 4. Molecular functions and biological processes of the 80 common proteins within ERMS- and ARMS-derived exosomes. Pie charts presenting: (A) the molecular functions and (B) the biological processes determined by PANTHER gene classification analysis with the percentage of proteins within each group and the sub-groups of the “Cellular Process”.

Figure 5. Exosome protein cargo is implicated in cancer-related biological pathways as identified by Pathway Studio. (A-C) Venn diagrams comparing pathways of exosomes derived from: (A) the 3 ERMS cell lines; (B) the 2 ARMS cell lines; and, (C) the common ERMS and ARMS cell lines, as specified.(D) Histograms displaying the commonly affected pathways in all RMS-derived exosomes involving more than 100 exosomal proteins in average between the 5 cell lines. (E-F) Histograms showing the pathways by number of proteins exclusive to, (E) the ERMS-derived exosomes and to, (F) the ARMS-derived exosomes.

Figure 6. Pathway Studio analysis of 3 commonly identified pathways in RMS-derived exosomes. A biological network was created using the Pathway Studio 9.0 program to visualize the role of different proteins in chosen cancer-related pathways.

Figure 7. RMS-derived exosomes contain specific signature proteins when compared to normal and cancer cells-derived exosomes datasets from Exocarta. Bar charts presenting the comparison of all RMS identified exosomal proteins with the exosomal protein cargoes of, (A) normal cells; and, (B) cancer cells downloaded from Exocarta database. (C-E) Venn diagrams 33 ACS Paragon Plus Environment


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comparing the proteins of RMS exosomes and all exosomal proteins of, (C) normal cells; (D) cancer cells and, (E) both.


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SUPPORTING INFORMATION: The following supporting information is available free of charge at ACS website http://pubs.acs.org TOC: - Suppl. Figure S1. Exosome protein cargo is implicated in cancer-related biological pathways as identified by PANTHER gene classification. - Suppl. Figure S2. Network analysis by IPA of the commonly expressed proteins and miRNAs in ERMS and in ARMS exosomes. - Suppl. Table S1. Transition list of 45 proteins analyzed in MRM-LC-MS/MS. - Suppl. Table S2. Complete information of identified proteins within ERMS-derived exosomes. - Suppl. Table S3. Complete information of identified proteins within ARMS-derived exosomes. - Suppl. Table S4. Quantitative results of 45 proteins from MRM-LC-MS/MS. - Suppl. Table S5. List of the 80 commonly enriched exosomal proteins. - Suppl. Table S6. List of all pathways identified by Pathway studio. - Suppl. Table S7. List of proteins implicated in the Integrin Signaling Pathway identified by PANTHER. - Suppl. Table S8. List of all pathways identified by PANTHER gene classifications. - Suppl. Table S9. List of the 36 proteins specific to RMS-exosomes.



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Proteomic profiling of rhabdomyosarcoma-derived exosomes yield

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