Ten Years of Extracellular Matrix Proteomics: Accomplishments, Challenges, and Future Perspectives

•ECM alterations cause or accompany diseases and disorders of all organ systems.•Proteomics is a method of choice to profile the composition of the ECM of tissues.•ECM proteomics can identify novel prognostic and diagnostic biomarkers.•ECM proteomics can uncover proteins playing functional roles in disease etiology.•Further technical advances are needed to capture the diversity of ECM proteoforms The extracellular matrix (ECM) is a complex assembly of hundreds of proteins forming the architectural scaffold of multicellular organisms. In addition to its structural role, the ECM conveys signals orchestrating cellular phenotypes. Alterations of ECM composition, abundance, structure, or mechanics have been linked to diseases and disorders affecting all physiological systems, including fibrosis and cancer. Deciphering the protein composition of the ECM and how it changes in pathophysiological contexts is thus the first step toward understanding the roles of the ECM in health and disease and toward the development of therapeutic strategies to correct disease-causing ECM alterations. Potentially, the ECM also represents a vast, yet untapped reservoir of disease biomarkers. ECM proteins are characterized by unique biochemical properties that have hindered their study: they are large, heavily and uniquely posttranslationally modified, and highly insoluble. Overcoming these challenges, we and others have devised mass-spectrometry–based proteomic approaches to define the ECM composition, or "matrisome," of tissues. This first part of this review provides a historical overview of ECM proteomics research and presents the latest advances that now allow the profiling of the ECM of healthy and diseased tissues. The second part highlights recent examples illustrating how ECM proteomics has emerged as a powerful discovery pipeline to identify prognostic cancer biomarkers. The third part discusses remaining challenges limiting our ability to translate findings to clinical application and proposes approaches to overcome them. Lastly, the review introduces readers to resources available to facilitate the interpretation of ECM proteomics datasets. The ECM was once thought to be impenetrable. Mass spectrometry–based proteomics has proven to be a powerful tool to decode the ECM. In light of the progress made over the past decade, there are reasons to believe that the in-depth exploration of the matrisome is within reach and that we may soon witness the first translational application of ECM proteomics. The extracellular matrix (ECM) is a complex assembly of hundreds of proteins forming the architectural scaffold of multicellular organisms. In addition to its structural role, the ECM conveys signals orchestrating cellular phenotypes. Alterations of ECM composition, abundance, structure, or mechanics have been linked to diseases and disorders affecting all physiological systems, including fibrosis and cancer. Deciphering the protein composition of the ECM and how it changes in pathophysiological contexts is thus the first step toward understanding the roles of the ECM in health and disease and toward the development of therapeutic strategies to correct disease-causing ECM alterations. Potentially, the ECM also represents a vast, yet untapped reservoir of disease biomarkers. ECM proteins are characterized by unique biochemical properties that have hindered their study: they are large, heavily and uniquely posttranslationally modified, and highly insoluble. Overcoming these challenges, we and others have devised mass-spectrometry–based proteomic approaches to define the ECM composition, or "matrisome," of tissues. This first part of this review provides a historical overview of ECM proteomics research and presents the latest advances that now allow the profiling of the ECM of healthy and diseased tissues. The second part highlights recent examples illustrating how ECM proteomics has emerged as a powerful discovery pipeline to identify prognostic cancer biomarkers. The third part discusses remaining challenges limiting our ability to translate findings to clinical application and proposes approaches to overcome them. Lastly, the review introduces readers to resources available to facilitate the interpretation of ECM proteomics datasets. The ECM was once thought to be impenetrable. Mass spectrometry–based proteomics has proven to be a powerful tool to decode the ECM. In light of the progress made over the past decade, there are reasons to believe that the in-depth exploration of the matrisome is within reach and that we may soon witness the first translational application of ECM proteomics. 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Yet, while some proteins (e.g., fibronectin, elastin) or families of proteins (e.g., collagens, tenascins) of the ECM have been extensively studied, the ECM as a whole, remained, until recently, largely underexplored (43Wilson R. The extracellular matrix: an underexplored but important proteome.Expert Rev. Proteomics. 2010; 7: 803-806Crossref PubMed Scopus (14) Google Scholar) and uncharted (44Filipe E.C. Chitty J.L. Cox T.R. Charting the unexplored extracellular matrix in cancer.Int. J. Exp. Pathol. 2018; 99: 58-76Crossref PubMed Scopus (0) Google Scholar). The very biochemical properties allowing ECM proteins to assemble into an architectural scaffold capable of withstanding significant mechanical stress and deformations have hindered our ability to study the global composition of the ECM. The core, structural proteins of the ECM tend to be very large, on average 1045 amino acids long. ECM proteins undergo extensive intracellular and extracellular posttranslational modifications (PTMs), including glycosylation, lysine and proline hydroxylation for collagens and collagen-domain-containing proteins that contribute to the stabilization of the triple-helical structure of collagens (45Rappu P. Salo A.M. Myllyharju J. Heino J. Role of prolyl hydroxylation in the molecular interactions of collagens.Essays Biochem. 2019; 63: 325-335Crossref PubMed Scopus (52) Google Scholar), and glycation. ECM proteins also assemble into higher-order molecular structures established via hydrogen bonds (e.g., collagen triple-helical structures (46Buehler M.J. Nature designs tough collagen: explaining the nanostructure of collagen fibrils.Proc. Natl. Acad. Sci. U. S. A. 2006; 103: 12285-12290Crossref PubMed Scopus (593) Google Scholar, 47Shoulders M.D. Raines R.T. Collagen structure and stability.Annu. Rev. 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Because of their high insolubility, ECM proteins are underrepresented in global proteomic datasets. Further contributing to this underrepresentation is the fact that, apart from a few exceptions, the ECM represents a small fraction of healthy organ and tissue mass. The second challenge limiting the comprehensive characterization of the ECM is its broad dynamic range in terms of protein abundance. The ECM is comprised of very large and highly abundant structural ECM components, which can generate many peptides (for example, there are 121 trypsin cleavage sites in the alpha 1 chain of collagen I), and also smaller secreted factors, such as ECM-remodeling enzymes, growth factors, or morphogens, present in much lower abundance. This limitation is not unique to the ECM, and advances in instrumentations and methods to fractionate protein and peptide samples, that will not be discussed here, have been key to capture the complexity of different subproteomes and are now being applied to ECM proteomics (see below). The first attempts at profiling the protein composition of the ECM of ECM-rich tissues, like the cartilage, or following ECM enrichment for other tissues, employed SDS-PAGE or 2D gel electrophoresis to separate the subsets of ECM proteins that could be solubilized, followed by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). These studies reported the detection of up to a few dozen structural ECM proteins. At the time, this was no small feat and these early studies have been instrumental in helping shape the field of ECM proteomics (51Wilson R. Bateman J.F. Cartilage proteomics: challenges, solutions and recent advances.Proteomics Clin. 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Conversely, proteins for which no prior knowledge existed would fail to be annotated as belonging to the ECM. This represented a significant limitation to any attempt aiming to identify biomarkers of diseased states. It thus became obvious that tailored experimental and analytical approaches would be needed to decipher the complexity of the ECM. This review will discuss the latest developments in ECM proteomics, from enhancement in sample preparation and analytical methods to the application of ECM proteomics for the purpose of biomarker and therapeutic target discovery with a focus on cancer. As part of the Special Issue on Clinical Proteomics, this article will highlight selected studies performed on clinical samples or rodent models of human diseases that show translational promise. Of note, ECM proteomics is also applied to study the ECM of many multicellular organisms, for example, zebrafish (59Chen W.C.W. Wang Z. Missinato M.A. Park D.W. Long D.W. 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While prior studies had attempted to overcome some of the limitations described above (for example, by decellularizing samples or extracting ECM proteins in guanidine hydrochloride), we set up to tackle them all. In brief, we first took advantage of the differential solubility of intracellular and ECM proteins to deplete non-ECM proteins by sequential incubations in extraction, or decellularization, buffers concomitantly enriching for ECM proteins. Observing that incubation in 8 M urea and 100 mM DTT did not fully solubilize ECM-enriched samples and suspecting that many ECM components would be found in the insoluble material, we processed "crude" 8 M-urea-resuspended samples. We then hypothesized that deglycosylating ECM proteins would enhance trypsin accessibility and thus treated samples with Peptide-N-glycosidase F (PNGaseF). We further preincubated deglycosylated ECM-enriched protein suspension with LysC, a smaller protease capable of digesting tightly folded proteins, prior to tryptic digestion. To capture a broad range of ECM components, we fractionated peptide samples using off-gel electrophoresis. Last, to ensure the correct identification and quantification of all ECM proteins, we stipulated the ECM-specific PTMs lysine and proline hydroxylations as variable modifications for database search. Indeed, proline represents 19% of the amino acid sequence of the alpha 1 chain of collagen I and is found in positions X and Y of X-Y-Gly repeats and is often hydroxylated (45Rappu P. Salo A.M. Myllyharju J. Heino J. Role of prolyl hydroxylation in the molecular interactions of collagens.Essays Biochem. 2019; 63: 325-335Crossref PubMed Scopus (52) Google Scholar). In parallel, we developed a robust nomenclature to annotate and classify ECM proteins. In brief, we used sequence analysis and the characteristic domain-based organization of ECM proteins (72Hohenester E. Eng