Proteomic Analysis of Cancer Associated Fibroblasts Reveal a

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Proteomic Analysis of Cancer Associated Fibroblasts Reveal a Paracrine Role for MFAP5 in Human Oral Tongue Squamous Cell Carcinoma Simona Principe, Salvador Mejia-Guerrero, Vladimir Ignatchenko, Ankit Sinha, Alex Ignatchenko, Wei Shi, Keira Pereira, Susie Su, Shao Hui Huang, Brian O'Sullivan, Wei Xu, David Goldstein, Ilan Weinreb, Laurie Ailles, Fei-Fei Liu, and Thomas Kislinger J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.7b00925 • Publication Date (Web): 22 Apr 2018 Downloaded from http://pubs.acs.org on April 22, 2018

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Journal of Proteome Research

Proteomic Analysis of Cancer Associated Fibroblasts Reveal a Paracrine Role for MFAP5 in Human Oral Tongue Squamous Cell Carcinoma Simona Principe1, Salvador Mejia-Guerrero1, Vladimir Ignatchenko1, Ankit Sinha3, Alexandr Ignatchenko1, Willa Shi2, Keira Pereira3, Susie Su1,4, Shao Hui Huang2, Brian O'Sullivan2, Wei Xu1,4, David P. Goldstein1,5, Ilan Weinreb1,6, Laurie Ailles1,3, Fei-Fei Liu1,2,3, Thomas Kislinger1,3,* 1

Princess Margaret Cancer Centre, University Health Network, Toronto, Canada

2

University of Toronto, Department of Radiation Oncology, Toronto, Canada

3

University of Toronto, Department of Medical Biophysics, Toronto, Canada

4

Department of Biostatistics, Princess Margaret Cancer Centre, Toronto, Canada

5

Department of Otolaryngology-Head and neck Surgery, Princess Margaret Cancer, University Health Network, Department of Otolaryngology, University of Toronto, Toronto, Canada

6

University of Toronto, Department of Pathology, Toronto, Canada

*

Corresponding author

Dr. Thomas Kislinger: MaRS Centre, Princess Margaret Cancer Research Tower; 101 College Street, Toronto, Ontario, Canada, M5G 1L7; Email: [email protected]; Phone: 416581-7627

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Abstract Bidirectional communication between cells and their microenvironment is crucial for both normal tissue homeostasis and tumor growth. During the development of oral tongue squamous cell carcinoma (OTSCC), cancer-associated fibroblasts (CAFs) create a supporting niche by maintaining a bidirectional crosstalk with cancer cells, mediated by classically secreted factors and various nanometer-sized vesicles, termed as extracellular vesicles (EVs). To better understand the role of CAFs within the tumor stroma and elucidate the mechanism by which secreted proteins contribute to OTSCC progression, we isolated and characterized patientderived CAFs from resected tumors with matched adjacent tissue fibroblasts (AFs). Our strategy employed shotgun proteomics to comprehensively characterize the proteomes of these matched fibroblast populations. Our goals were to identify CAF secreted factors (EVs and soluble) that can functionally modulate OTSCC cells in vitro and to identify novel CAF-associated biomarkers. Comprehensive proteomic analysis identified 4,247 proteins, the most detailed description of a pro-tumorigenic stroma to date. We demonstrated functional effects of CAF secretomes (EVs and conditioned media) on OTSCC cell growth and migration. Comparative proteomics identified novel proteins associated with a CAF-like state. Specifically, MFAP5, a protein component of extracellular microfibrils, was enriched in CAF secretomes. Using in vitro assays, we demonstrated that MFAP5 activated OTSCC cell growth and migration via activation of MAPK and AKT pathways. Using a tissue microarray (TMA) of richly annotated primary human OTSCCs, we demonstrated an association of MFAP5 expression with patient survival. In summary, our proteomics data of patient derived stromal fibroblasts provide a useful resource for future mechanistic and biomarker studies.


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Keywords: Proteomics, cancer-associated fibroblasts, tumor microenvironment, intercellular signaling, extracellular vesicles, secretomes, tongue squamous cell carcinoma



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Introduction OTSCC is the most prevalent cancer of the oral cavity, with an estimated 16,400 new cases in the US in 2017 1. Despite advances in treatment of OTSCC, patients still develop relapses and the 5-year overall survival has not greatly improved over the decades 2. A deeper understanding of the molecular determinants of OTSCC is therefore crucial in order to develop novel therapeutic strategies that can improve patient outcome. One critical component of tumor development is the surrounding microenvironment (i.e. the stroma), which involves a complex network of signals that can directly or indirectly affect tumor growth and metastasis 3. Cancerassociated fibroblasts (CAFs) are often the most abundant stromal cell type; thereby representing a potentially important target for cancer therapies. CAFs are highly secretory cells that produce cytokines, chemokines, growth factors, and extracellular matrix (ECM) components that create a permissive tumor-promoting niche 4. The study of CAF secretomes is therefore key to uncover autocrine and paracrine factors that modulate tumor progression, which might also serve as novel biomarkers to define an activated fibroblast phenotype. Our proteomics approach was designed to investigate classically secreted factors as well as non-classical secretion of nanometer-sized (40–100 nm) exosome-enriched EVs 5. Exosomes have emerged as important mediators of intercellular communication in cancer, and recent studies have demonstrated that exosomes released from immortalized fibroblasts promote cancer progression and invasion in breast cancer 6,7

. We combined matched pairs of patient-derived fibroblasts, isolated from resected tumors and

adjacent tissue, with extensive proteomics profiling, to acquire novel insights into the role of CAF-secreted factors in OTSCC. Using this resource of fibroblast-derived proteomes, we first characterized differences in the secreted fractions and then evaluated functional effects of fibroblast-derived EVs on growth and migration of OTSCC cells in vitro. Proteome-wide relative


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quantification highlighted CAF-enriched protein signatures, leading to the identification of microfibrillar-associated protein 5 (MFAP5), as a novel CAF-enriched protein. A series of molecular studies using recombinant MFAP5 and immunohistochemical staining of primary patient tumor tissues suggested a functional role for MFAP5 in tongue cancer, through activation of key oncogenic pathways, such as MAPK and AKT. The results of the current study provided novel insights into the role of CAF secreted factors within the oral cancer microenvironment. A deeper understanding of the molecular factors that regulate tumor-stromal communication could lead to the development of novel therapeutic targets and more effective treatments for patients with head and neck cancers.



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Materials and Methods Tumor Collection and Isolation of CAFs and AFs Tissues were collected from OTSCC patients who underwent surgical resection of their tumors at the University Health Network (UHN) and provided written consent under UHN Research Ethics Board approval (REB# 12-5639-CE). Both tumor and corresponding normal appearing tissue beyond the surgical margins were harvested and used to establish primary cultures of CAFs and AFs. The tissue was minced into small pieces and incubated in Media 199 (UHN media facility) containing collagenase/hyaluronidase (STEMCELL Technologies, Vancouver, BC) and DNAse (Worthington Biochemical, NJ, US) at 37°C for 2-3 hours. The mixture was periodically stirred to dissociate the cells. Once a single cell suspension was obtained, the cells were centrifuged and washed with sterile phosphate-buffered saline (PBS). Dissociated cells were re-suspended in 1 mL of cold ACK lysing buffer (Gibco, New York, USA) to remove contaminating red blood cells, followed by another wash with PBS. Finally, cells were plated in Iscove’s Modified Dulbecco’s Medium (IMDM, UHN media facility) containing 10% FBS and 1% Penicillin/Streptomycin (VWR International, Mississauga, Canada). Fibroblasts adherent to the tissue culture plastic were grown to a confluent monolayer, then passaged by trypsinization. Other cell types did not survive culture in this media. CAF cultures were verified by immunohistochemistry, positive for Vimentin and negative for pan-Cytokeratin, and flow cytometry was used to confirm the absence of CD45+ immune cells, CD31+ vascular endothelial cells, or EpCAM+ epithelial cells, as previously described 8. All the fibroblasts used in the experiments were at less than 10 passages.

Cell Lines and Culture Conditions


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All cell lines (primary CAF, AF and SCC25, SCC4) were cultured in IMDM with 10% FBS and Penicillin-Streptomycin-Glutamine (PSG) (100 U/ml penicillin, 100 µg/ml streptomycin, 292 µg/ml L-glutamine, Gibco, New York, USA). Primary fibroblasts and OTSCC cells were incubated at 37°C, in 5% CO2/2% O2, and 21% O2, respectively. Cell culture media was replaced every two to three days, and cultures were passaged at confluence with 0.25 % Trypsin (Wisent) and split between 1:2 and 1:5, depending on growth rate.

Collagen Gel Contraction Assay Collagen gel contraction assays were performed to measure cell contractility, as described previously 9. Briefly, a fibroblast cell suspension (final concentration 150,000 cells/ml) was mixed with 500 µl of collagen, cast into each well of a 24-well tissue culture plate, and incubated for 2 hours at room temperature. After collagen polymerization, gels were released from the surface of the well using a sterile tip. The gels were photographed at time 0 hours, then at indicated time points (6, 12 and 24 hours). The area of fibroblast gels was measured using ImageJ software, and expressed as a percentage of the original well area. The final data were averaged from three technical replicates and two independent experiments for each pair of CAFs and AFs.

Conditioned Media and Extracellular Vesicles Preparations Confluent fibroblasts were incubated with IMDM supplemented with PSG and 0% FBS. Two days later, the conditioned media (CM) was collected, cleared at 2,000g for 10 min and concentrated from 200mL to ~1mL by using Amicon® Ultra-15 Centrifugal Filters (Millipore, Etobicoke, Canada). Exosomes were isolated from freshly collected CM of CAFs and AFs by



differential ultracentrifugation, as previously described

10

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. Briefly, collected CM was subjected

to multiple centrifugations steps: 300g for 10 min, 2,000g for 10 min, and two times 10,000g for 30 min. The remaining supernatant was further spun at 110,000g for 2 hrs, the final pellet was gently washed with PBS and ultracentrifuged again at 110,000g for 2 hrs. The exosomalenriched fraction (EXO) was resuspended in PBS or RIPA lysis buffer (150mM NaCl, 1% NP40, 0.1 SDS, 50mM Tris, pH 8.0), 5mM EDTA, 20 mM beta-glycerophosphate, 5mM NaF, 4mM Na3VO4, cOmplete™ Protease Inhibitor Cocktail tablets as directed by the manufacturer (Sigma-Aldrich, St. Louis, MO), and stored at 4°C or -80°C. The supernatant resulting from the last 110,000g spin, labeled as exosome-free media (EFM, or exosome-depleted media), was further concentrated to ~500µl, stored at -80°C and used for functional assays.

Transmission Electron Microscopy (TEM) Exosome pellets prepared as described above were resuspended in PBS buffer. Fixation, embedding and image acquisition by TEM was performed at the Nanoscale Biomedical Imaging Facility, Department of Pathology & Laboratory Medicine at Mount Sinai Hospital, Toronto, Canada.

Mass Spectrometry and Data Analysis All three fractions: whole cell lysate, conditioned media and exosomes (WCL, CM and EXO), isolated from primary CAFs and AFs were processed as previously described 11. Briefly, proteins were solubilized using 50% 2,2,2-trifluoroethanol (TFE) at 60°C for 2 h. Following reduction with 5 mM DTT and alkylation with 25 mM iodoacetamide, samples were diluted with 100 mM ammonium bicarbonate pH 8.5 (final TFE 10%), and proteins were digested overnight at 37°C


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using 2 µg trypsin. The reaction was quenched by the addition of trifluoroacetic acid. Desalting was performed by solid-phase extraction using C18 MacroSpin Columns (The Nest Group, Southborough, MA). Solvents were removed by vacuum centrifugation, and peptides were reconstituted in 5% acetonitrile and 0.1% formic acid. Peptide concentration was determined by BCA assay or NanoDrop analysis (Thermo Fisher Scientific, San Jose, CA). For each sample, 1 µg of total peptides was analyzed in triplicate, using an Easy-LC 1000 (Thermo Fisher Scientific, San Jose, CA) with a heated nano-UHPLC (50 cm C18 reverse phase column, Thermo Fisher Scientific, San Jose, CA) interfaced to a Q-Exactive tandem mass spectrometer (Thermo Fisher Scientific, San Jose, CA), equipped with an EASY-Spray source (Thermo Fisher Scientific, San Jose, CA). Raw data were analyzed using the MaxQuant computational proteomics platform (version 1.5.1.0) with a fragment ion mass tolerance of ±20 ppm and a parent ion mass tolerance of ±10 ppm. We allowed up to two missed tryptic cleavages. Carbamidomethylation of cysteine was specified as a fixed modification, and oxidation of methionine as a variable modification. Proteins were identified with a minimum of two unique peptides, the maximum false peptide discovery rate was specified as 1% and “match between runs” was enabled. The resulting protein group file was processed with an in-house developed tool, as recently described

12

. Briefly, the

distribution of iBAQ values was adjusted to the distribution of LFQ values based on the median for each sample, which enabled impute-adjusted iBAQ values for those proteins that did not have LFQ values across the samples. All other missing values were replaced by random numbers drawn from a simulated normal distribution of width 0.3 of standard deviation and shifted downwards for 1.8 of standard deviation (method described in Perseus 13. This resulted in a final list of 4247 protein groups identified and quantified in our samples (Supplementary Table 1).



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All proteomics data have been deposited to the MassIVE database and are available at the following link (ftp://massive.ucsd.edu/MSV000081585). Gene Ontology Annotation and Data Comparison To identify differences in protein expression among the three groups (WCL, CM and EXO) we used one-way analysis of variance (ANOVA) in conjunction with Tukey’s HSD (Honest Significant Difference) post hoc test. This model was carried out for comparison of the three fractions, and the level of statistical significance was set at p ≤ 0.05. Exosome and CM upregulated proteins were selected for Gene Ontology (GO) analysis. GO annotations were performed using g:Profiler (http://biit.cs.ut.ee/gprofiler/) 14. The list of upregulated proteins was queried for GO: Biological process (BP) with the entire list of identified proteins as background. Level 4 terms with p-value ≤ 0.05 were selected. We also used a multivariate analysis approach, the Principal Component Analysis (PCA), to show how the three groups were segregated based on protein composition. Annotation scatterplots, heat map and PCA were performed using the R programing environment (version 3.1.0). Metabolic pathway analysis was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) (http://www.genome.jp/kegg/) 15.

Western Blotting For Western blotting, 10-30 µg of total protein was separated on 8% or 10% SDS-PAGE gels and blotted onto PVDF membranes (0.2 µm; Bio-Rad Laboratories, Hercules, CA). Membranes were blocked with 5% milk in TBS-Tween (0.2%) for 1 hr at room temperature, and incubated overnight at 4°C with the following primary antibodies: anti-α smooth muscle actin (1:500 #ab7817, Abcam, Cambridge, UK), anti-MFAP5 (1:500, #HPA010553, Sigma-Aldrich, St. Louis, MO), anti-phospho-p44/42 MAPK (Erk1/2) (Thr202/Tyr204) (1: 1000, #9106s), anti-


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p44/42 MAPK (Erk1/2) (1:1000, #9102s), anti-MEK1/2 (1:1000, #9122s), anti-phosphoMEK1/2 (Ser217/221) (1:1000, #9121s) and anti-phospho-Akt Pathway Antibody Sampler Kit (1:1000, #9916); all from Cell Signaling Technology (Beverly, MA, USA). After three 10-min washes with TBS-Tween (0.2%), membranes were incubated with anti-mouse/anti-rabbit IgGHRP secondary antibody (Invitrogen, Carlsbad, CA) at a dilution of 1:25,000 for 1 hr at room temperature, washed and visualized with the SuperSignal West Femto Maximum Sensitivity chemiluminescent substrate (Thermo Fisher Scientific, San Jose, CA). Bands were detected using a MicroChemi Chemiluminescence image analysis system (DNR Bio-imaging Systems, Jerusalem, Israel).

Immunofluorescence Primary fibroblasts were grown to sub-confluence on coverslips in 24-well plates and fixed in 4% paraformaldehyde for 10 min at room temperature. Cells were then permeabilized in PBS/0.2% Triton X-100 for 10 min at room temperature, then blocked in PBS/3% BSA for 30 min. Cells were incubated with anti-α smooth muscle actin (1:50 #ab7817) overnight at 4°C. At the end of incubation, samples were washed at least three times with PBS, and incubated with secondary antibody Goat Anti-mouse IgG H&L (Alexa Fluor 488) (1:100, #ab150113, Abcam, Cambridge, UK). Images were analyzed by Spinning Disk Confocal Microscopy using a Zeiss microscope equipped with a high-speed camera (Rolera, Surrey, Canada).

TMA Construction and Clinical Data A tissue microarray was built for patients with OTSCC managed at the Princess Margaret Hospital between 1994 and 2011. The patients included in the TMA were those that were



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included in a clinical database of patients with newly diagnosed previously untreated OTSCC and in whom adequate tissue was available. Patients for the clinical database and thus the TMA were identified from Princess Margaret Cancer Registry. Specimens for the TMA were built from tissue in the biobank repository and if not available in the biobank were built from archived pathology specimens. For each specimen, two 0.6 mm cores of tumor were taken. The TMA used for this study consisted of 91 OTSCC, some of the cores were lost during the heat-induced antigen retrieval step (see immunohistochemistry of TMA). A total number of 69 patients was evaluated and annotated with clinical outcomes (Table I).

Immunohistochemistry of TMA A tissue microarray (TMA) with a set of 91 OTSCC samples was used to perform immunohistochemistry for MFAP5 expression, using an anti-MFAP5 antibody (#HPA010553, Sigma-Aldrich, St. Louis, MO). Briefly, 4µm tumor sections were deparaffinized, rehydrated and blocked with 3% hydrogen peroxide in methanol. The slides were antigen retrieved in a microwave oven with 10mM citrate buffer (pH 6.0), and incubated overnight at 4oC with 1:500 anti-MFAP5 antibody. MFAP5 positive reaction was detected with the LSAB2 System (Dako, Carpinteria, CA, US). All slides were scanned, analyzed using ZEN Lite imaging software (ZEISS Microscopy), and subsequently evaluated for MFAP5 expression by two researchers blinded to the clinical characteristics of the patients. Quantification of MFAP5 expression was successfully scored in a total number of 69 cores using 2 parameters: 1) proportion (as a percentage) of stromal cells with positive staining over the entire core field; 2) intensity of immunostaining (1+, 2+, 3+). The final immunostaining score was calculated by multiplying the proportion of positive staining with the intensity scores.


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Statistical Analysis of the TMA Descriptive statistics (mean, standard deviation, median, minimum, maximum, frequency, percentage) were used to characterize the patient samples. Kruskal Wallis tests were applied for continuous variable comparisons while Fisher exact tests were used for categorical variable comparisons. Kaplan-Meier curves and Cox proportional hazards (PH) regression models were utilized for the survival analysis on OS and DFS. Analyses were performed using SAS 9.4 (SAS Institute, Cary, NC, US) and R 3.1.2.

Exosome Uptake Fibroblast secreted exosomes were isolated as described above and labeled with PKH67 (SigmaAldrich, St. Louis, MO) according to the manufacturer’s protocol. Briefly, 50-80 µg protein equivalents of exosomes were resuspended in 50 µl PBS and mixed with 50 µl of PHK67 dye for 10 min at room temperature. The mixture was centrifuged at 110,000g to pellet the PKH-67 labeled exosomes, washed with PBS, resuspended in complete medium, and then used for uptake studies. SCC25 cells were grown on coverslips and treated with 20 µg/ml of labeled exosomes for 1, 6 or 24 hours. Cells were counterstained with Rhodamine Phalloidin (ThermoFisher Scientific, San Jose, CA), nuclei were labeled with NucBlue® Reagent (ThermoFisher Scientific, San Jose, CA) and final samples were analyzed using Spinning Disk Confocal Microscopy with a Zeiss microscope equipped with a high-speed camera (Rolera, Surrey, Canada).



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Proliferation and Wound Healing Assays For proliferation assays, 1-2x103 SCC4 or SCC25 cells were seeded in 96-well plates, allowed to adhere overnight, then treated with CAF-EFM (exosome-free/exosome-depleted media) (50 ng/mL), CAF-EXO (10 ng/mL) or IMDM (CTRL), or with HuRecMFAP5 at 125, 250 ng/mL and incubated at 37°C 5% CO2. Cell confluency was monitored using an IncuCyte ZOOM® System (Essen BioScience, Ann Arbor, US). For scratch wound assays, 2-3x104 SCC4 or SCC25 cells were seeded in 96-well plates and allowed to adhere overnight. Scratches were made with the Essen Biosciences scratch wound maker according to the manufacturer’s protocol. OTSCC cells were then treated with CAF-EFM (50 ng/mL), CAF-EXO (10 ng/mL) or IMDM (CTRL), or with HuRecMFAP5 at 125, 250 ng/mL and incubated at 37°C 5% CO2. Cell confluency and wound closure were monitored using an IncuCyte ZOOM® System (Essen BioScience, Ann Arbor, US). Cell proliferation was quantified using the metric Phase Object Confluence (POC), a measure of the area of field of view covered by cells; wound healing was quantified using Relative Wound Density (RWD), expressed as cell density in the wound area relative to the cell density outside of the wound area. All graphs are expressed as mean percentage (%) of three-tofive independent experiments with samples isolated from different patients.

Results and Discussion Phenotypic and Proteomic Characterization of Patient-derived Fibroblasts Although thought to be genetically stable, the CAF phenotype has been reported to be highly heterogeneous 16 and composed of both fibroblasts and α-smooth muscle actin (α-SMA)-positive myofibroblasts

17

. CAFs have previously been defined as α-SMA positive cells with large

spindle-shaped morphology that reflect their contractile properties

18

; α-SMA expression has 14

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been associated with a pro-tumorigenic microenvironment and significantly correlated with the development of metastatic disease and with a poorer overall survival rate

19

. Consistent with

these findings, we screened our matched pairs of adjacent fibroblasts (AF) and CAF from OTSCC resections, based on α-SMA expression. As shown by immunoblot and immunofluorescence microscopy (Figure 1A/B), CAFs expressed higher intracellular levels of α-SMA and displayed an elongated, mesenchymal morphology compared to their matched AFs (Figure 1C). To further verify a CAF activated phenotype, we measured fibroblast contractility, as a known marker of fibroblast activation 20. We seeded CAFs and AFs in 3-D collagen type I gels, and monitored the degree of gel contraction over time. Figure 1D depicts representative collagen gels and their respective area measurements (Figure 1E). As expected, CAFs have a greater effect on collagen contraction when compared to their matched adjacent counterparts. Based on these data, we hypothesized that our matched pairs of primary CAFs and AFs could lead to the identification of secreted factors involved in promoting a permissive tumor microenvironment. We used MS-based proteomics to comprehensively characterize the fibroblast’ proteome by comparing whole cell lysate (WCL), conditioned media (CM), and exosome (EXO) fractions of four matched pairs of AFs and CAFs (each fraction analyzed in processing triplicates; 72 total runs). These protein identification criteria (MaxQuant version 1.5.1.0; two unique peptides per protein; 1% FDR setting) 21 resulted in 4247 protein groups for functional investigation, one of the largest descriptions of patient-derived fibroblasts to date (Figure 1F).

Detailed Analyses of the Fibroblast Proteome



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We first performed a principal component analysis (PCA) of our entire proteomic data (72 runs), analyzed for each fraction (24 runs), as an indicator of the variance in our dataset. We observed that the three fractions clustered separately, in that WCL and secreted proteins (EXO and CM) could be distinguished (Figure 2A). To further validate the reproducibility of our MS data, we performed unsupervised hierarchical clustering of all 72 analyzed samples, using Pearson correlation (Supplementary Figure 1A), and we also generated scatter plots showing high reproducibility between technical replicates (R2=0.93, R2=0.94, R2=0.92; Supplementary Figure 1B/1C/1D) and between matched CAF and AF (R2=0.88; Supplementary Figure 1E). As expected, correlations are more dispersed between different patients (R2=0.75; Supplementary Figure 1F), and between different fractions (R2=0.26; Supplementary Figure 1G). We then evaluated differences in protein abundance amongst the three analyzed fractions, focusing on proteins that were enriched in the fibroblast secretomes (EXO and CM). The heat map in Figure 2B for all identified proteins, demonstrated differentially-expressed proteins using p ≤ 0.05 and >2-fold change (one-way ANOVA), across all analyzed fractions, resulting in five distinct clusters. Cluster 1 (red) contained 858 proteins that were significantly up-regulated in the EXO fraction ‘EXO-enriched’; Cluster 2 (green) consisted of 221 proteins that were significantly enriched only in the CM; Cluster 3 (orange) contained 273 proteins significantly enriched in both the CM and EXO compared to the WCL; for simplicity, these two clusters were collapsed as ‘CM-enriched’. Cluster 4 (blue) comprised of 1951 proteins that were significantly enriched in the cellular lysate ‘WCL-enriched’, which were mainly intracellular proteins; lastly, Cluster 5 (grey), consisted of 944 proteins that were commonly expressed across all three fractions. Since the goal of our study was the identification of stromal-derived paracrine factors that might support tumor growth and progression, we specifically focused on Clusters 1-3, which we termed


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as ‘secretome-enriched’ proteins. To further validate our EV enrichment strategy and better characterize our isolated fraction, we verified the structure of our microparticles by transmission electron microscopy (TEM), the gold standard in the field. In accordance with recent literature 22, exosomes derived from fibroblasts featured singular cup-shaped particles of less than 150 nm in diameter with intact continuous bilayer membranes (Figure 2C, Supplementary Figure 2A/B). The characteristics of our microparticles were similar to those reported in numerous papers 23-25, where the vesicles had been described as exosomes. To further characterize this fraction, we evaluated the enrichment of specific known exosomal markers. Based on our proteomics data, exosomes display high levels of common protein markers such as CD81, CD9, TST101, ALIX and CD63, and reduced expression of endoplasmic reticulum (CALR and CALX), Golgi apparatus (GOLM1), mitochondrial (VDAC1), cytoplasmic (ACTBL2) markers or extracellular secreted proteins (IL6, LUM, COL3A1, LGALS1, MMP1) (Figure 2D). Our comprehensive analysis of the secretome revealed a total of 4,063 identified proteins. Of these, 415 proteins were uniquely identified in EXO, 95 proteins were exclusive to CM, while 3,553 proteins were identified in both fractions (Figure 2E). We performed an in-depth GO analysis to better characterize the protein content of the two fractions. Cellular component analysis of EXOenriched versus CM-enriched proteins using the FunRich 3.1.3 software, which allows to calculate protein enrichment between two datasets, showed that EXO are significantly (p ≤ 0.001) enriched in cytoplasmic, exosomal, lysosomal, plasma membrane and nuclear proteins whereas the CM fraction is enriched in extracellular proteins (Figure 2F). Similarly, GO analysis of molecular functions showed that EXO are significantly (p ≤ 0.001) enriched in transporter activity, GTPase activity and ubiquitin-specific protease activity, whereas CM



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contains significantly more growth factor activity, hydrolase activity and extracellular matrix structural proteins (Figure 2G).

Exosome and conditioned media secretomes express distinct proteins To obtain better insights into proteins enriched in the secretome fractions, we performed enrichment analyses, based on Gene Ontology annotation for Biological Process g:Profiler

14

26

, using

. The significantly-enriched terms (p ≤ 0.05) are presented in Figures 3A/3B,

demonstrating that different sub-sets of GO terms were significantly enriched in the EXOenriched and the CM-enriched fractions. For example, tissue polarity, transport and cell communication, protein metabolism, wounding and cell motility were exclusive to the exosome sub-proteome (Figure 3A), whereas ECM organization, immune response, tissue development and cell differentiation were significantly enriched in the CM sub-proteome (Figure 3B). Moreover, some of the functional categories specifically enriched in the exosome proteome, such as signal transduction, motility and wounding, could mediate cancer progression. Thus, we queried our proteomics data and observed a higher number of cancer-associated proteins in the EXO fraction compared to the CM fraction. To further investigate this finding, additional analyses were performed to better characterize the differences between these two fibroblast secretomes. We selected the ‘EXO-enriched’ fraction, which contained 858 proteins that were significantly up-regulated in EXO versus the whole dataset (see heat map, red cluster, Figure 2B) and annotated this list using the DAVID GAD-disease database

27

. This resulted in the

identification of 624 records, of which 175 proteins were associated with the term ‘cancer’ or ‘neoplasm’, and 46 proteins were specifically annotated as ‘oral’, ‘head and neck’ or ‘esophageal cancer’. Figure 3C shows the higher expression of these 46 proteins in the


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exosomes when compared to CM. Among these 46 proteins were numerous proto-oncogenes, including CTNN1 TNFRSF1A

31

28

, PLAU

and RAN

32

29

, WNT11

30

, members of the TNF superfamily TNFRSF10D,

that have already been clearly associated with signal transduction,

cellular transformation and cancer progression.

Exosome and conditioned media fractions exhibit functional effects on cancer cells To functionally validate the differences observed in the proteomes of the two fractions, and determine whether exosomes released by fibroblasts could affect cancer cell behavior, we first tested if tongue cancer epithelial cells could up-take fluorescently labeled fibroblast-derived exosomes. Representative images demonstrate that SCC25 cells internalized fibroblast exosomes in a time-dependent manner (Figure 3D). Considering the important role of exosomes and extracellular proteins on cancer cell growth and migration

6,33,34

, we next investigated the

differential effects of fibroblasts-secreted exosomes (EXO) and exosome-free media (EFM) on OTSCC cell line SCC25. We treated SCC25 with CAF-derived EXO and/or EFM and assessed whether these fractions could affect proliferation and migration of SCC25 cells. We observed that proliferation and migration of SCC25 were significantly greater when cells were incubated with EXO as compared to EFM (even at a 10-fold higher total protein concentration, Supplementary Figure 3A) or a control condition (media only) (Figures 3E/F). Furthermore, we verified that after subjecting EXO to heat denaturation, these effects were abrogated (Supplementary Figure 3B), suggesting that intact exosome morphology and/or protein components are playing an important role in stimulating cancer cell proliferation or migration. Herein, we described for the first time, that CAF secreted exosomes significantly increased OTSCC cell proliferation and migration when compared to exosome-depleted media or control,



Page 20 of 42

likely contributing to OTSCC progression. Although we did not observe significant differences between CAF and AF exosomes on cancer cells at this stage of our analysis (Supplementary Figures 3C/3D), possibly due to the close spatial proximity of “adjacent normal tissue” in the case of tongue cancer or due to the particular functional assays chosen. Since we did observe significant differences between CAFs and AFs in our proteomics data we used these quantitative differences to identify proteins for further functional analyses. Interestingly, the GO analysis suggested a significant (p ≤ 0.05) enrichment of proteins involved in metabolism and energy pathways in CAFs vs. AFs (Supplementary Figure 3E). Recent studies have highlighted a central role for CAF secreted exosomes in modulating cancer cell metabolism

35,36

, a model

known as the ‘Reverse Warburg Effect’37, which emphasizes the importance of CAFs in supplying energy metabolites and chemical building blocks to support cancer cell proliferation 38

. Our findings highlight a strong association of CAF exosome cargo with metabolism and

energy pathways, suggesting a distinct role for CAF exosomes in supporting cancer cells’ metabolic functions. These analyses corroborate previous reports that exosomes have a fundamental role in shuttling paracrine signals between stromal and cancer cells the metabolic environment and supporting tumor progression

35

39

; modifying

. Consistent with the recent

literature, where it has been shown that cells can traffic metabolic enzymes via EVs, our proteomics data demonstrated that the CAF exosomes upregulated protein list (1150 proteins, CAF vs. AF FC ≥ 1.5) contained 125 (11.3 %) enzymes that mapped to the KEGG metabolic pathways database. Interestingly, Iraci et al.

36

had recently described a new role for EVs which

can function as independent metabolic units altering the physiology of the surrounding microenvironment. Beyond the numerous attempts to characterize the metabolic activity of EVs 35,40,41

, the precise mechanism of action of these components remains to be further elucidated.


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Quantitative proteomics identifies MFAP5 as a CAF-enriched protein We then interrogated the proteomic and functional differences between exosomes and conditioned media and developed a strategy to highlight a CAF-enriched secretome signature. To identify CAF-enriched proteins, we quantitatively compared matched CAF and AF pairs (≥ 1.5fold change CAF/AF, Figure 4A) and focused only on proteins that fulfilled this criteria in all four pairs. By applying these criteria, we identified 47 upregulated proteins in the CAF EXO fraction (Supplementary Table 2), and 43 upregulated proteins in the CAF CM (Figure 4A). Initially we focused on proteins robustly enriched in CAFs (CM and EXO) for further functional evaluations. In agreement with the global differences between these proteomes, we only found two proteins (MFAP5 and CNPY3) that overlapped between the EXO and CM, which were also enriched in the CAFs (Figure 4B). CNPY3 is a toll-like receptor (TLR)-specific co-chaperone that, together with HSP90B1, is required for the folding of multiple TOLL-like receptors 42. This protein is involved in regulating both innate and adaptive immune responses and to date, there is no evidence of its role in cancer. Furthermore, our MS data suggested that CNPY3 is more abundant in the WCL fraction compared to the CM or EXO fraction (Supplementary Figure 4). Since the main focus of this study is to identify CAF-enriched secreted molecules that are shuttled between fibroblasts and cancer cells and that can affect cancer cells progression, we selected MFAP5 for further investigations. MFAP5 is more abundant in the secretome (CM/EXO versus WCL, Supplementary Figure 4), highly expressed in CAFs (Figure 4C), and has commercial antibodies and a soluble recombinant protein available for functional validation. Previous reports in HNC have indicated that CAFs affect cancer cell growth by secreting prooncogenic factors that can stimulate proliferation, angiogenesis and invasion 3,43,44. Interestingly,



Page 22 of 42

Microfibrillar-associated protein 5 (MFAP5 or MAGP2), a multifunctional secreted protein and important component of microfibrils

45

, was first associated with ovarian cancer reported by

Mock et al. in 2009, 46 and just recently reported in tongue carcinoma by Yang and colleagues as a potential marker for prognosis and metastasis 47. The role of this protein in mediating ovarian cancer cell motility and invasion through calcium-dependent FAK/CREB/TNNC1 signaling, has been recently investigated by Leung et al

48

. The same group also reported high MFAP5

expression in cancer stroma, and significant association with TNNC1 expression, wherein high TNNC1 expression was significantly correlated with poor OS 48

. To the best of our knowledge however, the functional role of MFAP5 in tongue cancer has not

yet been investigated; hence further studies are required to elucidate its biology in head and neck cancers (HNCs). According to our proteomics data, MFAP5 was significantly enriched in CAFs (Figure 4D); as well, we showed that MFAP5 was secreted as both a soluble protein and part of the exosomal cargo (Supplementary Figure 4). In addition, our proteomics data on SCC4 and SCC25 cells, suggested that MFAP5 is not detected in the OTSCC cells (T.K and S.P. unpublished data). These data encouraged us to investigate MFAP5 expression in patient tumor tissues using a richly annotated OTSCC TMA. These analyses confirmed the elevated expression of MFAP5 in the cancer-associated stroma (Figure 4E). Next, the prognostic value of MFAP5 expression was evaluated using the Kaplan-Meier method for determination of overall survival (OS) and diseasefree survival (DFS). Patients were dichotomized based on the median IHC staining intensity score for MFAP5: high vs. low expression. The 5-year OS was 84% (95% confidence interval [CI] = 72% to 98%) in patients with low MFAP5 expression, vs. 64% (95% CI = 47% to 87%) for patients with high MFAP5 expression (p =0.079) (Figure 4F). Similarly, the 5-year DFS was


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62% (95% CI = 47% to 82%) vs. 39% (95% CI = 24% to 63%) for patients with low vs. high MFAP5 expression respectively (p =0.06) (Figure 4G). While these results did not reach statistical significance (OS, p =0.079; DFS, p =0.06), the consistent trend suggested that elevated MFAP5 protein was associated with poor prognosis. Our results are consistent with the only other data available on MFAP5 prognostic relevance, where the authors reported that tongue cancer patients with positive MFAP5 expression experienced a significantly shorter DFS than patients with negative MFAP5 expression

47

. However, further studies are clearly required to

validate the association between stromal MFAP5 expression with clinico-pathological features in OTSCC, likely using a larger patient cohort. Paracrine effects of MFAP5 on tongue cancer cells Although α-SMA is the most commonly used marker for activated fibroblasts 49, the mechanisms contributing to CAF activation are still poorly characterized

3,50

. CAFs are known to produce

other mesenchymal-specific proteins, such as fibroblast-specific protein (FSP-1), fibroblastactivation protein (FAP), podoplanin (PDPN) and vimentin

51

, but due to the heterogeneity of

these cells, a reliable CAF-specific marker is still lacking. From our comprehensive proteomics analyses, it emerged that primary patient-derived tongue CAFs expressed high levels of MFAP5 protein. To further validate the high MFAP5 expression in CAFs, we examined another independent group of five patient-matched pairs of CAF/AF, previously screened for α-SMA expression (Figure 1A/1B, Pair 5 to Pair 9). Consistent with our previous results, immunoblot analyses (Figure 5A) confirmed that MFAP5 protein was higher in the majority of CAFs, yet also demonstrated a considerable degree of variability, as expected from patient-derived samples. Previous reports have demonstrated that MFAP5 modulates ovarian cancer cell survival and endothelial cell motility through activation of αVβ3 integrin

52

. To investigate whether MFAP5



Page 24 of 42

is involved in paracrine signaling in HNC, we treated OTSCC cells with human recombinant MFAP5 (hrecMFAP5), and assayed its effects on cell growth and migration. Exogenous treatment with hrecMFAP5 at 125 and 250 ng/mL significantly increased SCC25 cell proliferation (p ≤ 0.05) (Figure 5B). Similarly, induction of SCC25 migratory capacity by a wound healing assay was observed following treatment with hrecMFAP5 (Figure 5B). Similar results were obtained in the SCC4 cell line (Supplementary Figure 5A/B). Next, we sought to better characterize the effects of MFAP5 on cancer cell proliferation and migration by investigating key signaling pathways such as MAPK and AKT. Mitogen-activated protein kinase (MAPK) pathways are widely known to control cellular processes such as growth, differentiation, migration and apoptosis; with its deregulation observed in almost one-third of all human cancers 53. The AKT pathway also plays a crucial role in cancer development; wherein its activation is an early event in HNC progression, being detected in 50% of pre-neoplastic tongue lesions

54

. Thus, we investigated the effects of hrecMFAP5 on OTSCC cell signaling, and

observed that hrecMFAP5 induced a rapid activation of both MAPK and AKT pathways in OTSCC cells (Figure 5D/5E). Consistent with the biological effects observed in SCC4 cells, the levels of phospho-MEK and phospho-ERK were rapidly increased after treatment with HuRecMFAP5. Similarly, the phosphorylation of AKT was increased at both sites (Ser473 and Thr308), together with the phosphorylation of its major upstream activator PDK1. Other downstream effectors of AKT pathways involved in cell cycle regulation, such as GSK3β, and apoptosis inhibition, such as cRAF and PTEN, were also rapidly induced within 5 mins of MFAP5 exposure. Taken together, our data suggested that MFAP5 is a CAF-enriched protein that plays an important role in the stroma-tumor crosstalk by inducing activation of MAPK and AKT pathways in OTSCC cells, leading to increased cell proliferation and motility. MAPK and


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AKT pathways are both essential mediators of malignant transformation; others have shown that, constitutive activation of MAPK and AKT, led to increased proliferation, survival and invasion 55

; additionally, MAPK and AKT are important regulators of epithelial-mesenchymal transition,

a process involved in the initiation of cancer metastasis

56

. Although the activation of these

signaling routes are known to contribute to progression in HNC 57, further investigations will be required to elucidate the exact mechanism of action of MFAP5 on OTSCC cells.

Conclusions The main goal of this study was to investigate the crosstalk between stromal and cancer cells by generating a comprehensive proteomic analysis of the CAF secretome. The secretome of activated fibroblasts consists of soluble proteins and extracellular vesicles, CAF-synthesized ECM components, cytokines and chemokines that create a pro-inflammatory niche and signaling pathway gradients, thereby inducing phenotypic changes in the tumor

58,59

. Numerous studies

have shown that paracrine signaling between intratumoral fibroblasts and cancer cells promote cell proliferation, motility, epithelial-to-mesenchymal transition (EMT), and metastasis

60-62

.

Here, we conducted a comprehensive and detailed analysis of fibroblast secretomes by employing a LC-MS-based proteomics approach. The high-resolution, high mass accuracy and exquisite sensitivity of the QExactive mass spectrometer has significantly improved our analyses of complex protein mixtures and the ability to access low-abundance proteins in cellular subfractions. With a total of 4247 identified proteins, this study provided additional information regarding the CAF secretome when compared to previous proteomic studies

63,64

, and the first

report in tongue cancers.



Page 26 of 42

It has been previously demonstrated that CAF-secreted exosomes promote cell motility in breast cancer through WNT-PCP signaling 6. More recently, our group has demonstrated that CAF ADAM10-rich exosomes promote cell motility by activating RhoA and Notch signaling in several cancer types 7. Herein, we described that CAF-derived exosomes promote in vitro cancer cell growth and migration, likely contributing to OTSCC progression. We demonstrated that MFAP5 was highly expressed in CAF secreted fractions (conditioned media and exosomes), suggesting that its expression could be used as a marker of the CAF phenotype in the context of OTSCC. Given that most up-regulated CAF secreted molecules have been shown to harbor oncogenic functions

65

, we investigated the role of stromal MFAP5 on OTSCC growth and migration.

Overall, our study provided the first comprehensive proteomic characterization of the HNC protumorigenic microenvironment, and new evidence for the involvement of CAF-secreted MFAP5 in stroma-tumor crosstalk. Future studies are required to define possible interactors and putative receptors of MFAP5, as well as confirming its role as a prognostic marker in HNC. Despite therapeutic advancements, the survival rate in HNC has not changed over the last 40 years. The complexity of the tumor microenvironment has made therapeutic interventions challenging

66

.

The prognostic importance of some CAF-specific proteins has been previously demonstrated in HNC and other cancers, including PDPN 67, SPARC 68, Tenascin-C and FAP

69

and PDGFR 70.

CAFs have been also reported to induce MMP-mediated cetuximab resistance in head and neck squamous cell carcinoma cells

71

. This suggests that novel therapeutic strategies targeting both

epithelial and stromal components need to be developed to improve cancer therapies and to potentially overcome drug resistance. For these reasons, a deeper understanding of CAFs and the


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complex stroma-tumor crosstalk is fundamental to uncover novel targets within the tumor stroma that can effectively guide new therapeutic interventions in this disease.

References (1) (2)

(3) (4) (5) (6)

(7)

(8)

(9) (10)

(11)

(12)

(13)

Siegel, R. L.; Miller, K. D.; Jemal, A. Cancer Statistics, 2017. CA Cancer J Clin 2017, 67 (1), 7–30. Dogan, E.; Cetinayak, H. O.; Sarioglu, S.; Erdag, T. K.; Ikiz, A. O. Patterns of cervical lymph node metastases in oral tongue squamous cell carcinoma: implications for elective and therapeutic neck dissection. J Laryngol Otol 2014, 128 (3), 268–273. Kalluri, R.; Zeisberg, M. Fibroblasts in cancer. Nat. Rev. Cancer 2006, 6 (5), 392–401. Öhlund, D.; Elyada, E.; Tuveson, D. Fibroblast heterogeneity in the cancer wound. J. Exp. Med. 2014, 211 (8), 1503–1523. Nazarenko, I.; Rupp, A.-K.; Altevogt, P. Exosomes as a potential tool for a specific delivery of functional molecules. Methods Mol. Biol. 2013, 1049 (Chapter 37), 495–511. Luga, V.; Zhang, L.; Viloria-Petit, A. M.; Ogunjimi, A. A.; Inanlou, M. R.; Chiu, E.; Buchanan, M.; Hosein, A. N.; Basik, M.; Wrana, J. L. Exosomes mediate stromal mobilization of autocrine Wnt-PCP signaling in breast cancer cell migration. Cell 2012, 151 (7), 1542–1556. Shimoda, M.; Principe, S.; Jackson, H. W.; Luga, V.; Fang, H.; Molyneux, S. D.; Shao, Y. W.; Aiken, A.; Waterhouse, P. D.; Karamboulas, C.; et al. Loss of the Timp gene family is sufficient for the acquisition of the CAF-like cell state. Nat. Cell Biol. 2014, 16 (9), 889–901. Young, M.; Rodenhizer, D.; Dean, T.; D'Arcangelo, E.; Xu, B.; Ailles, L.; McGuigan, A. P. A TRACER 3D Co-Culture tumour model for head and neck cancer. Biomaterials 2018, 164, 54–69. Ngo, P.; Ramalingam, P.; Phillips, J. A.; Furuta, G. T. Collagen gel contraction assay. Methods Mol. Biol. 2006, 341, 103–109. Théry, C.; Amigorena, S.; Raposo, G.; Clayton, A. Isolation and characterization of exosomes from cell culture supernatants and biological fluids. Curr Protoc Cell Biol 2006, Chapter 3, Unit3.22–3.22.29. Sinha, A.; Alfaro, J.; Kislinger, T. Characterization of Protein Content Present in Exosomes Isolated from Conditioned Media and Urine. Curr Protoc Protein Sci 2017, 87, 24.9.1–24.9.12. Wojtowicz, E. E.; Lechman, E. R.; Hermans, K. G.; Schoof, E. M.; Wienholds, E.; Isserlin, R.; van Veelen, P. A.; Broekhuis, M. J. C.; Janssen, G. M. C.; Trotman-Grant, A.; et al. Ectopic miR-125a Expression Induces Long-Term Repopulating Stem Cell Capacity in Mouse and Human Hematopoietic Progenitors. Cell Stem Cell 2016, 19 (3), 383–396. Tyanova, S.; Temu, T.; Sinitcyn, P.; Carlson, A.; Hein, M. Y.; Geiger, T.; Mann, M.; Cox, J. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 2016, 13 (9), 731–740.



(14)

(15) (16) (17) (18) (19)

(20)

(21)

(22)

(23)

(24)

(25)

(26)

(27) (28)

(29)

Page 28 of 42

Reimand, J.; Kull, M.; Peterson, H.; Hansen, J.; Vilo, J. g:Profiler--a web-based toolset for functional profiling of gene lists from large-scale experiments. Nucleic Acids Res. 2007, 35 (Web Server issue), W193–W200. Kanehisa, M.; Goto, S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000, 28 (1), 27–30. Orimo, A.; Weinberg, R. A. Heterogeneity of stromal fibroblasts in tumors. Cancer Biol. Ther. 2007, 6 (4), 618–619. Shimoda, M.; Mellody, K. T.; Orimo, A. Carcinoma-associated fibroblasts are a ratelimiting determinant for tumour progression. Semin. Cell Dev. Biol. 2010, 21 (1), 19–25. Chaponnier, C.; Gabbiani, G. Pathological situations characterized by altered actin isoform expression. J. Pathol. 2004, 204 (4), 386–395. Yamashita, M.; Ogawa, T.; Zhang, X.; Hanamura, N.; Kashikura, Y.; Takamura, M.; Yoneda, M.; Shiraishi, T. Role of stromal myofibroblasts in invasive breast cancer: stromal expression of alpha-smooth muscle actin correlates with worse clinical outcome. Breast Cancer 2012, 19 (2), 170–176. Smithmyer, M. E.; Sawicki, L. A.; Kloxin, A. M. Hydrogel scaffolds as in vitro models to study fibroblast activation in wound healing and disease. Biomater Sci 2014, 2 (5), 634–650. Cox, J.; Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 2008, 26 (12), 1367–1372. Lyu, L.; Wang, H.; Li, B.; Qin, Q.; Qi, L.; Nagarkatti, M.; Nagarkatti, P.; Janicki, J. S.; Wang, X. L.; Cui, T. A critical role of cardiac fibroblast-derived exosomes in activating renin angiotensin system in cardiomyocytes. J. Mol. Cell. Cardiol. 2015, 89 (Pt B), 268– 279. Admyre, C.; Johansson, S. M.; Qazi, K. R.; Filén, J.-J.; Lahesmaa, R.; Norman, M.; Neve, E. P. A.; Scheynius, A.; Gabrielsson, S. Exosomes with immune modulatory features are present in human breast milk. J. Immunol. 2007, 179 (3), 1969–1978. Bhatnagar, S.; Shinagawa, K.; Castellino, F. J.; Schorey, J. S. Exosomes released from macrophages infected with intracellular pathogens stimulate a proinflammatory response in vitro and in vivo. Blood 2007, 110 (9), 3234–3244. van Niel, G.; Raposo, G.; Candalh, C.; Boussac, M.; Hershberg, R.; Cerf-Bensussan, N.; Heyman, M. Intestinal epithelial cells secrete exosome-like vesicles. Gastroenterology 2001, 121 (2), 337–349. Ashburner, M.; Ball, C. A.; Blake, J. A.; Botstein, D.; Butler, H.; Cherry, J. M.; Davis, A. P.; Dolinski, K.; Dwight, S. S.; Eppig, J. T.; et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 2000, 25 (1), 25–29. Huang, D. W.; Sherman, B. T.; Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 2009, 4 (1), 44–57. Wang, Y.; Wang, S.; Wu, Y.; Ren, Y.; Li, Z.; Yao, X.; Zhang, C.; Ye, N.; Jing, C.; Dong, J.; et al. Suppression of the Growth and Invasion of Human Head and Neck Squamous Cell Carcinomas via Regulating STAT3 Signaling and the miR-21/β-catenin Axis with HJC0152. Mol. Cancer Ther. 2017, 16 (4), 578–590. Sepiashvili, L.; Hui, A.; Ignatchenko, V.; Shi, W.; Su, S.; Xu, W.; Huang, S. H.; O'Sullivan, B.; Waldron, J.; Irish, J. C.; et al. Potentially novel candidate biomarkers for


Page 29 of 42 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(30)

(31) (32)

(33)

(34)

(35)

(36)

(37) (38)

(39)

(40)

(41)

head and neck squamous cell carcinoma identified using an integrated cell line-based discovery strategy. Mol. Cell Proteomics 2012, 11 (11), 1404–1415. Wang, X.; Liu, D.; Zhou, K.; Wang, B.; Liu, Q.; Deng, F.; Li, Q.; Ma, Y. Expression of Wnt11 and Rock2 in esophageal squamous cell carcinoma by activation of the WNT/PCP pathway and its clinical significance. Pathol. Res. Pract. 2016, 212 (10), 880–885. Croft, M.; Benedict, C. A.; Ware, C. F. Clinical targeting of the TNF and TNFR superfamilies. Nat Rev Drug Discov 2013, 12 (2), 147–168. Martens-de Kemp, S. R.; Nagel, R.; Stigter-van Walsum, M.; van der Meulen, I. H.; van Beusechem, V. W.; Braakhuis, B. J. M.; Brakenhoff, R. H. Functional genetic screens identify genes essential for tumor cell survival in head and neck and lung cancer. Clin. Cancer Res. 2013, 19 (8), 1994–2003. Barderas, R.; Mendes, M.; Torres, S.; Bartolomé, R. A.; López-Lucendo, M.; VillarVázquez, R.; Peláez-García, A.; Fuente, E.; Bonilla, F.; Casal, J. I. In-depth characterization of the secretome of colorectal cancer metastatic cells identifies key proteins in cell adhesion, migration, and invasion. Mol. Cell Proteomics 2013, 12 (6), 1602–1620. Karagiannis, G. S.; Pavlou, M. P.; Diamandis, E. P. Cancer secretomics reveal pathophysiological pathways in cancer molecular oncology. Mol Oncol 2010, 4 (6), 496–510. Zhao, H.; Yang, L.; Baddour, J.; Achreja, A.; Bernard, V.; Moss, T.; Marini, J. C.; Tudawe, T.; Seviour, E. G.; San Lucas, F. A.; et al. Tumor microenvironment derived exosomes pleiotropically modulate cancer cell metabolism. Elife 2016, 5, e10250. Iraci, N.; Gaude, E.; Leonardi, T.; Costa, A. S. H.; Cossetti, C.; Peruzzotti-Jametti, L.; Bernstock, J. D.; Saini, H. K.; Gelati, M.; Vescovi, A. L.; et al. Extracellular vesicles are independent metabolic units with asparaginase activity. Nat. Chem. Biol. 2017, 13 (9), 951–955. Hanahan, D.; Weinberg, R. A. Hallmarks of cancer: the next generation. Cell 2011, 144 (5), 646–674. Pavlides, S.; Whitaker-Menezes, D.; Castello-Cros, R.; Flomenberg, N.; Witkiewicz, A. K.; Frank, P. G.; Casimiro, M. C.; Wang, C.; Fortina, P.; Addya, S.; et al. The reverse Warburg effect: aerobic glycolysis in cancer associated fibroblasts and the tumor stroma. Cell Cycle 2009, 8 (23), 3984–4001. Richards, K. E.; Zeleniak, A. E.; Fishel, M. L.; Wu, J.; Littlepage, L. E.; Hill, R. Cancerassociated fibroblast exosomes regulate survival and proliferation of pancreatic cancer cells. Oncogene 2017, 36 (13), 1770–1778. Commisso, C.; Davidson, S. M.; Soydaner-Azeloglu, R. G.; Parker, S. J.; Kamphorst, J. J.; Hackett, S.; Grabocka, E.; Nofal, M.; Drebin, J. A.; Thompson, C. B.; et al. Macropinocytosis of protein is an amino acid supply route in Ras-transformed cells. Nature 2013, 497 (7451), 633–637. Minciacchi, V. R.; You, S.; Spinelli, C.; Morley, S.; Zandian, M.; Aspuria, P.-J.; Cavallini, L.; Ciardiello, C.; Reis Sobreiro, M.; Morello, M.; et al. Large oncosomes contain distinct protein cargo and represent a separate functional class of tumor-derived extracellular vesicles. Oncotarget 2015, 6 (13), 11327–11341.



(42)

(43)

(44)

(45)

(46)

(47)

(48)

(49)

(50)

(51) (52)

(53) (54)

(55)

(56)

Page 30 of 42

Liu, B.; Yang, Y.; Qiu, Z.; Staron, M.; Hong, F.; Li, Y.; Wu, S.; Li, Y.; Hao, B.; Bona, R.; et al. Folding of Toll-like receptors by the HSP90 paralogue gp96 requires a substrate-specific cochaperone. Nat Commun 2010, 1 (6), 79–10. Koontongkaew, S. The tumor microenvironment contribution to development, growth, invasion and metastasis of head and neck squamous cell carcinomas. J Cancer 2013, 4 (1), 66–83. Kayamori, K.; Katsube, K.-I.; Sakamoto, K.; Ohyama, Y.; Hirai, H.; Yukimori, A.; Ohata, Y.; Akashi, T.; Saitoh, M.; Harada, K.; et al. NOTCH3 Is Induced in CancerAssociated Fibroblasts and Promotes Angiogenesis in Oral Squamous Cell Carcinoma. PLoS ONE 2016, 11 (4), e0154112. Penner, A. S.; Rock, M. J.; Kielty, C. M.; Shipley, J. M. Microfibril-associated glycoprotein-2 interacts with fibrillin-1 and fibrillin-2 suggesting a role for MAGP-2 in elastic fiber assembly. J. Biol. Chem. 2002, 277 (38), 35044–35049. Mok, S. C.; Bonome, T.; Vathipadiekal, V.; Bell, A.; Johnson, M. E.; Wong, K.-K.; Park, D.-C.; Hao, K.; Yip, D. K. P.; Donninger, H.; et al. A gene signature predictive for outcome in advanced ovarian cancer identifies a survival factor: microfibril-associated glycoprotein 2. Cancer Cell 2009, 16 (6), 521–532. Yang, X.; Wu, K.; Li, S.; Hu, L.; Han, J.; Zhu, D.; Tian, X.; Liu, W.; Tian, Z.; Zhong, L.; et al. MFAP5 and TNNC1: Potential markers for predicting occult cervical lymphatic metastasis and prognosis in early stage tongue cancer. Oncotarget 2017, 8 (2), 2525– 2535. Leung, C. S.; Yeung, T.-L.; Yip, K.-P.; Pradeep, S.; Balasubramanian, L.; Liu, J.; Wong, K.-K.; Mangala, L. S.; Armaiz-Pena, G. N.; Lopez-Berestein, G.; et al. Calciumdependent FAK/CREB/TNNC1 signalling mediates the effect of stromal MFAP5 on ovarian cancer metastatic potential. Nat Commun 2014, 5, 5092. Marsh, D.; Suchak, K.; Moutasim, K. A.; Vallath, S.; Hopper, C.; Jerjes, W.; Upile, T.; Kalavrezos, N.; Violette, S. M.; Weinreb, P. H.; et al. Stromal features are predictive of disease mortality in oral cancer patients. J. Pathol. 2011, 223 (4), 470–481. Kartha, V. K.; Stawski, L.; Han, R.; Haines, P.; Gallagher, G.; Noonan, V.; Kukuruzinska, M.; Monti, S.; Trojanowska, M. PDGFRβ Is a Novel Marker of Stromal Activation in Oral Squamous Cell Carcinomas. PLoS ONE 2016, 11 (4), e0154645. Augsten, M. Cancer-associated fibroblasts as another polarized cell type of the tumor microenvironment. Front Oncol 2014, 4 (7069), 62. Spivey, K. A.; Banyard, J. A prognostic gene signature in advanced ovarian cancer reveals a microfibril-associated protein (MAGP2) as a promoter of tumor cell survival and angiogenesis. Cell Adh Migr 2010, 4 (2), 169–171. Dhillon, A. S.; Hagan, S.; Rath, O.; Kolch, W. MAP kinase signalling pathways in cancer. Oncogene 2007, 26 (22), 3279–3290. Massarelli, E.; Liu, D. D.; Lee, J. J.; El-Naggar, A. K.; Muzio, Lo, L.; Staibano, S.; De Placido, S.; Myers, J. N.; Papadimitrakopoulou, V. A. Akt activation correlates with adverse outcome in tongue cancer. Cancer 2005, 104 (11), 2430–2436. Dawson, J. C.; Timpson, P.; Kalna, G.; Machesky, L. M. Mtss1 regulates epidermal growth factor signaling in head and neck squamous carcinoma cells. Oncogene 2012, 31 (14), 1781–1793. Lamouille, S.; Xu, J.; Derynck, R. Molecular mechanisms of epithelial-mesenchymal transition. Nat. Rev. Mol. Cell Biol. 2014, 15 (3), 178–196. 30 ACS Paragon Plus Environment

Page 31 of 42 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(57)

(58)

(59) (60)

(61) (62)

(63)

(64)

(65)

(66)

(67)

(68) (69)

(70) (71)

Molinolo, A. A.; Amornphimoltham, P.; Squarize, C. H.; Castilho, R. M.; Patel, V.; Gutkind, J. S. Dysregulated molecular networks in head and neck carcinogenesis. Oral Oncol. 2009, 45 (4-5), 324–334. Gangoda, L.; Boukouris, S.; Liem, M.; Kalra, H.; Mathivanan, S. Extracellular vesicles including exosomes are mediators of signal transduction: are they protective or pathogenic? Proteomics 2015, 15 (2-3), 260–271. Nickel, W. Pathways of unconventional protein secretion. Curr. Opin. Biotechnol. 2010, 21 (5), 621–626. Karagiannis, G. S.; Poutahidis, T.; Erdman, S. E.; Kirsch, R.; Riddell, R. H.; Diamandis, E. P. Cancer-associated fibroblasts drive the progression of metastasis through both paracrine and mechanical pressure on cancer tissue. Mol. Cancer Res. 2012, 10 (11), 1403–1418. Hanahan, D.; Coussens, L. M. Accessories to the crime: functions of cells recruited to the tumor microenvironment. Cancer Cell 2012, 21 (3), 309–322. Kamińska, K.; Szczylik, C.; Bielecka, Z. F.; Bartnik, E.; Porta, C.; Lian, F.; Czarnecka, A. M. The role of the cell-cell interactions in cancer progression. J. Cell. Mol. Med. 2015, 19 (2), 283–296. Torres, S.; Bartolomé, R. A.; Mendes, M.; Barderas, R.; Fernandez-Aceñero, M. J.; Peláez-García, A.; Peña, C.; López-Lucendo, M.; Villar-Vázquez, R.; de Herreros, A. G.; et al. Proteome profiling of cancer-associated fibroblasts identifies novel proinflammatory signatures and prognostic markers for colorectal cancer. Clin. Cancer Res. 2013, 19 (21), 6006–6019. Sharon, Y.; Raz, Y.; Cohen, N.; Ben-Shmuel, A.; Schwartz, H.; Geiger, T.; Erez, N. Tumor-derived osteopontin reprograms normal mammary fibroblasts to promote inflammation and tumor growth in breast cancer. Cancer Res. 2015, 75 (6), 963–973. Tian, B.; Chen, X.; Zhang, H.; Li, X.; Wang, J.; Han, W.; Zhang, L.-Y.; Fu, L.; Li, Y.; Nie, C.; et al. Urokinase plasminogen activator secreted by cancer-associated fibroblasts induces tumor progression via PI3K/AKT and ERK signaling in esophageal squamous cell carcinoma. Oncotarget 2017, 8 (26), 42300–42313. New, J.; Arnold, L.; Ananth, M.; Alvi, S.; Thornton, M.; Werner, L.; Tawfik, O.; Dai, H.; Shnayder, Y.; Kakarala, K.; et al. Secretory Autophagy in Cancer-Associated Fibroblasts Promotes Head and Neck Cancer Progression and Offers a Novel Therapeutic Target. Cancer Res. 2017, 77 (23), 6679–6691. Schoppmann, S. F.; Jesch, B.; Riegler, M. F.; Maroske, F.; Schwameis, K.; Jomrich, G.; Birner, P. Podoplanin expressing cancer associated fibroblasts are associated with unfavourable prognosis in adenocarcinoma of the esophagus. Clin. Exp. Metastasis 2013, 30 (4), 441–446. Vaz, J.; Ansari, D.; Sasor, A.; Andersson, R. SPARC: A Potential Prognostic and Therapeutic Target in Pancreatic Cancer. Pancreas 2015, 44 (7), 1024–1035. Yang, Z.-T.; Yeo, S.-Y.; Yin, Y.-X.; Lin, Z.-H.; Lee, H.-M.; Xuan, Y.-H.; Cui, Y.; Kim, S.-H. Tenascin-C, a Prognostic Determinant of Esophageal Squamous Cell Carcinoma. PLoS ONE 2016, 11 (1), e0145807. Paulsson, J.; Micke, P. Prognostic relevance of cancer-associated fibroblasts in human cancer. Semin. Cancer Biol. 2014, 25, 61–68. Johansson, A.-C.; Ansell, A.; Jerhammar, F.; Lindh, M. B.; Grénman, R.; MunckWikland, E.; Östman, A.; Roberg, K. Cancer-associated fibroblasts induce matrix 31 ACS Paragon Plus Environment


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metalloproteinase-mediated cetuximab resistance in head and neck squamous cell carcinoma cells. Mol. Cancer Res. 2012, 10 (9), 1158–1168.

Acknowledgements TK, FFL and LA were funded through a CCSRI Innovation Grant (703777). S.P. was supported by an EIRR21 post-doctoral fellowship. This research was funded in part by the Ontario Ministry of Health and Long-Term Care. We thank Drs. Anthony Gramolini and Jake Cosme, Department of Physiology, University of Toronto, for assistance with confocal microscopy; Jalna Meens, University Health Network, for primary fibroblasts cultures; and Colleen Simpson, University Health Network, for TMA annotation.

Conflict of Interest Statement All authors declare that they have no conflicts of interest.


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Figure Legends Figure 1. Phenotypic characterization of patient-derived fibroblasts isolated from resected OTSCC cells and proteomics workflow. (A) Immunoblot analysis on total lysates of nine matched AF/CAF pairs revealed significantly higher αSMA levels in CAF compared with matched AFs. GAPDH was utilized as a loading control. (B) Representative IF staining for αSMA (green) in AF/CAF pairs demonstrating increased α-SMA expression in CAFs vs. matched AFs. Scale bar, 20 µm. Samples were divided into a ‘discovery group’ (4 pairs) used for MS analyses and a ‘validation group’ (5 pairs) used for functional assays. (C) Phase contrast representative images of CAFs and AFs grown at different cell densities (subconfluent top; confluent bottom) showing fibroblasts’ morphology, with a highlighted area magnified to the right. AF in culture exhibited a typical spindle-shaped fibroblast-like appearance, while CAFs appeared more irregular and flattened. Scale bars, 100 µm. (D) Collagen gel contraction representative images showing CAF increased gel contraction (indicating fibroblast activation) relative to AF, after 12 hours. The areas circled with black dashed lines denote the sizes of collagen gels at t=12hrs, normalized to the area of the whole well.

(E) Collagen area

measurements (%) calculated using Image J software. *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001. (F) Schematic illustrating the proteomics strategy investigating the secretome of human primary AF/CAFs isolated from resected OTSCC cells. Briefly, CAF and AF were grown to confluence; three main fractions (WCL, CM and EXO) were collected, processed and analyzed by UHPLCMS/MS.

Figure 2. In-depth analyses of fibroblast proteomes. (A) PCA of total proteome data (72 runs), analyzed for each fraction (24 runs = 4 CAF and 4 AF lines, run in triplicate)



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demonstrating a clear separation of the EXO and CM clusters (secretome) from the WCL. Each dot in the graph represents a single sample. Samples were grouped as follows; blue: WCL, red: EXO, green: CM. (B) Heat map representing differentially expressed proteins (one-way ANOVA, p ≤ 0.05) in the proteomic dataset. Five major groups can be identified based on protein abundance: EXO-enriched (red), CM-enriched (green), secretome-enriched (EXO+CM, orange), WCL-enriched (blue) and commonly expressed proteins (grey). Red represents higher protein abundance, while blue denotes lower. On the x-axis: all 72 analyzed samples; y-axis: all 4247 identified proteins. (C) Electron microscopy representative images of fibroblast exosomes prepared using our differential ultracentrifugation protocol. Scale bar, 100 nm. (D) Internal validation of exosome enrichment efficiency. Based on the proteomics data, exosomes display high levels of common protein markers (red bars), and reduced expression of intracellular (blue bars) or secreted proteins (green bars). (E) Venn diagram depicting the overlap of proteins identified in CM (green) and EXO (red), respectively. (F, G) Bar charts depict GO analyses performed using the FunRich 3.1.3 software representing Cellular Component (F) and Molecular Function (G) categories enriched in exosomes (red), and conditioned media (green).

Figure 3. Exosome and conditioned media fractions exhibit distinct protein composition and different functional effects on cancer cells. Scatter plot depicts the GO analysis performed using g: Profiler representing Biological Process categories enriched in exosomes (A), and conditioned media (B). Blue dots: p ≤ 0.05; grey dots: p ≥ 0.05. (C) Heat map displays a list of 46 proteins upregulated in EXO versus CM, associated with ‘oral’, ‘head and neck’ and ‘esophageal cancer’ according to DAVID GAD-disease database (D) Graphical representation of exosome uptake showing SCC25 cells treated with 20 ug/ml of exosomes labeled with


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fluorescent dye PHK67 (green), after incubation for 0, 1, 6 or 24 hours. SCC25 were counterstained with phalloidin (red) for intracellular cytoskeleton f-actin, and NucBlue® for nuclei (blue). Scale bars, 20 µm. SCC25 proliferation (E), and migration (F) in the presence of IMDM (Ctrl), CAF exosome-free media (Cefm 50 ng/mL) and CAF exosomes (Cexo 10 ng/mL). Cells were incubated at 37°C/5% CO2 in the IncuCyte live-cell imaging system as described in “Methods”. The figure below is a representative photomicrograph at a single time point of 114 h for proliferation (E), and 9 h for migration (F). Bar charts displayed multiple data points, results were presented as mean ± standard deviation (SD) of 5 independent experiments, where Cefm and Cexo were isolated from 5 different patients; *p ≤ 0.05 relative to control.

Figure 4. Quantitative proteomic analysis identified MFAP5 as a CAF-enriched protein. (A) Protein prioritization scheme for the selection of candidate proteins enriched in CAF secretome. (B) Venn diagram depicting the overlap of proteins respectively enriched in CAF EXO (red) or CAF CM (green). (C) Bar chart comparing expression of MFAP5 and CNPY3 in CAF vs. AF in WCL (blue bars), CM (green bars) and EXO (red bars). (D) Heat map representing MFAP5 abundance in the samples analysed (CAF and AF), for both EXO and CM. Red correlated with higher protein expression; yellow denoted lower. (E) Independent IHC validation of MFAP5 expression in 69 tongue cancer TMAs. Example of MFAP5 IHC staining (resolution 20X) representing staining intensity 3+, with a highlighted area magnified on the right. (F, G) Kaplan-Meier analyses of overall survival (OS) (F), and disease-free survival (DFS) (G) as a function of high (red dashed line) vs. low (black line) MFAP5 expression. The high MFAP5 expression group was associated with worse OS and DFS probabilities (OS p =0.079; DFS, p =0.06).



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Figure 5. MFAP5 in vitro validation and functional role on tongue cancer cells. (A) Western Blot validation of MFAP5 expression in an independent group of patient-derived fibroblasts. SCC25 proliferation (B) and migration (C) in the presence of IMDM (Ctrl) or HuRecMFAP5 (125 and 250 ng/mL). Cells were incubated at 37°C/5% CO2 in the IncuCyte live-cell imaging system as described in “Methods.” The figure represents the photomicrograph of a single time point of 132 h for proliferation (B), and 9 h for migration (C). Bar charts displayed multiple data points, results were presented as mean ± standard deviation (SD) of 3 independent experiments, *p ≤ 0.05 relative to control. (D) HuRecMFAP5 activated the MAPK signaling pathway, and the AKT signaling pathway in SCC4 cells as detected by western blot analysis. (E) Relative intensity values from band densitometry were presented as mean ± standard deviation (SD) of 3 independent experiments, **p≤0.01, *p ≤ 0.05 relative to control.

Table I. Clinico‐pathological characteristics of Feature Age Mean (SD) Median (Min,Max) Gender F M cTNM n (%) T1T2 T3T4 Tumor Grade moderate poor well Follow up (alive pt.) Median (Min,Max)

Full Sample (n=69)

patients

60.7 (14.4) 60.6 (20.7,87.3) 34 35 48 (70%) 21 (30%) 51 15 3 3.1 years (0.3,6.6)


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SD: standard deviation; Min: minimum; Max: maximum; cTNM: clinical staging; Pt: patient. Table of Contents graphic



Figure 1

CAF

C o lla g e n a r e a ( % )

CAF

AF

CAF

AF

AF

CAF

AF

A1 C1 A2 C2 A3 C3 A4 C4 A5 C5 A6 C6 A7 C7 A8 C8 A9 C9 A 1 2 α-SMA 3 4 GAPDH 5 Pair 1 Pair 2 Pair 3 Pair 4 Pair 9 Pair 5 Pair 6 Pair 7 Pair 8 B 6 7 8 9 10 11 12 13 14 Discovery Group Validation Group 15 Pair 3 Pair 4 Pair 1 Pair 2 C D 16 17 18 19 20 21 22 23 E 120 AF 24 CA F 25 * * 100 26 *** 27 ** 80 28 29 60 30 31 40 F P A IR 1 P A IR 2 P A IR 3 P A IR 4 32 33 OTSCCs 34 35 Patients fibroblasts 36 CAF AF 37 38 39 40 WCL CM EXO 41 Protein extraction 42 TFE 43 Tryptic peptides Concentration 44 45 UC UPLC-QExactive 46 47 MaxQuant (1%FDR) 48 49 4247 protein groups 50 51 52 53 ACS Paragon Plus Environment 54 55 56

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Figure 2

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Conditioned Media

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Conditioned Media

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R e la tiv e W o u n d D e n s ity (% )

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Figure 4

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R e la t iv e I n t e n s it y (a d j v s . t o t )

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A5 C5 A6 C6 A7 C7 A8 C8 A9 C9 1 A 2 MFAP5 3 (EXO) 4 5 A5 C5 A6 C6 A7 C7 A8 C8 A9 C9 6 MFAP5 7 (EFM) 8 9 B * * C 100 10 * * 70 90 11 60 12 80 13 50 70 14 40 60 15 30 50 16 17 20 40 CTR L M FA P 125 M FA P 250 CTR L M FA P 125 M FA P 250 18 19 20 21 22 5min 10min 15min 23 D E CTRL MFAP MFAP MFAP 24 4 p-MEK1/2 p -M E K 1 /2 p -E R K 1 /2 25 (S 2 1 7 / S 2 2 1 ) (T 2 0 2 / Y 2 0 4 ) (S217/S221) 26 27 3 t-MEK1/2 * 28 p-ERK1/2 29 2 * (T202/Y204) 30 31 t-ERK1/2 1 32 33 p-PDK1 0 34 (S241) 35 p-AKT 36 (S473) 5 p -P D K 1 p -A K T p -A K T 37 (S 2 4 1 ) (S 4 7 3 ) (T 3 0 8 ) p-AKT 38 * 4 (T308) 39 ** 40 3 t-AKT * * 41 * p-GSK3β 2 42 (S9) 43 1 p-cRAF 44 (S259) 45 0 46 p-PTEN (S380) 47 48 49 50 51 52 53 ACS Paragon Plus Environment 54 55 56

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