Skip to main content
The Journal of Biological Chemistry logoLink to The Journal of Biological Chemistry
. 2009 Jun 19;284(33):22041–22047. doi: 10.1074/jbc.M109.002964

The First Draft of the Endostatin Interaction Network*

Clément Faye ‡,1, Emilie Chautard ‡,1, Bjorn R Olsen §, Sylvie Ricard-Blum ‡,2
PMCID: PMC2755928  PMID: 19542224

Abstract

Endostatin is a C-terminal proteolytic fragment of collagen XVIII that is localized in vascular basement membrane zones in various organs. It binds to heparin/heparan sulfate and to a number of proteins, but its molecular mechanisms of action are not fully elucidated. We have used surface plasmon resonance (SPR) arrays to identify new partners of endostatin, and to give further insights on its molecular mechanism of action. New partners of endostatin include glycosaminoglycans (chondroitin and dermatan sulfate), matricellular proteins (thrombospondin-1 and SPARC), collagens (I, IV, and VI), the amyloid peptide Aβ-(1–42), and transglutaminase-2. The biological functions of the endostatin network involve a number of extracellular proteins containing epidermal growth factor and epidermal growth factor-like domains, and able to bind calcium. Depending on the trigger event, and on the availability of its members in a given tissue at a given time, the endostatin network might be involved either in the control of angiogenesis, and tumor growth, or in neurogenesis and neurodegenerative diseases.


Endostatin is a C-terminal proteolytic fragment of collagen XVIII that is localized in vascular basement membrane zones in various organs. It inhibits angiogenesis and tumor growth (13). The effect of endostatin depends on its concentration (4, 5), on the length of exposure (6), on the type of endothelial cells (7), and on the growth factor inducing cell proliferation (fibroblast growth factor 2 or VEGF)3 (8, 9).

Endostatin binds to several membrane proteins including α5β1 and αvβ3 integrins (10, 11), heparan sulfate proteoglycans (glypican-1 and -4) (12), and KDR/Flk1/VEGFR2 (13). We have previously characterized the binding of endostatin to heparan sulfate chains (9), and of endostatin to integrins (11). Furthermore, we have shown that α5β1, αvβ3, and αvβ5 integrins bind to heparin/heparan sulfate (11).

The broad molecular targets of endostatin suggest that multiple signaling systems are involved in mediation of its antiangiogenic action. Endostatin is a broad spectrum angiogenesis inhibitor that suppresses angiogenesis by blocking general mechanisms that govern endothelial cell growth (14), and initiates a complex network of signaling at the gene level (15). However, its molecular mechanism of action is still a matter of debate.

An integrative view of the endostatin interaction network, including interactions between endostatin partners, is necessary to provide a clear understanding of how all these molecules work together to regulate angiogenesis, and tumor growth. This global approach places individual proteins into a functional context, and takes into account the fact that a single molecule such as endostatin can affect a wide range of other cell components. Indeed, most proteins and other components carry out their functions within a complex network of interactions and this approach based on protein-protein interaction networks has been developed for several years to give new clues on biological processes (16).

This study was thus designed to identify additional extracellular partners of endostatin in an attempt to obtain new insights into its mechanisms of action, and the biological processes in which it participates. For this purpose, we have developed protein and glycosaminoglycan arrays using an automated surface plasmon resonance (SPR) platform. Proteins and glycosaminoglycans selected for SPR analysis were present in the same tissues or structures, such as basement membranes (17), brain (18), cartilage (19), or they were involved in the same physio-pathological processes (angiogenesis, neuro-degenerative diseases) as endostatin, and they were available as full-length molecules. Collagens I and VI, for example, have been selected because the α1 and α2 chains of collagen VI were determined to be potential pan-endothelial markers as was the α1 chain of collagen XVIII containing endostatin (20), and because the genes coding for the α1 and α2 chains of collagen I, and the α3 chain of collagen VI are up-regulated in angiogenic vessels and elevated in tumor endothelium (20). Some proteins and glycosaminoglycans were also included to serve as positive controls for well known interactions with the potential partners of endostatin. We report that endostatin binds to other endogenous angiogenesis inhibitor, the matricellular proteins thrombospondin-1 and SPARC, and to several collagens (I, IV, and VI). Other interacting partners of endostatin are transglutaminase-2, the amyloid peptide Aβ-(1–42), chondroitin, and dermatan sulfate.

EXPERIMENTAL PROCEDURES

Source of Proteins and Glycosaminoglycans

Recombinant human endostatin, the trimeric C-terminal domain of collagen XVIII called NC1 and several mutants were produced by human embryonic kidney cells expressing Epstein-Barr virus nuclear antigen (293-EBNA cells) according to established protocols (8, 9, 11). Amino acid residues were numbered starting from the first amino acid residue of endostatin (His1, also referred to as His132 when numbering starts from the first amino acid of the entire C-terminal domain NC1 of collagen XVIII). Laminin (L2020) isolated from basement membrane of Engelbreth-Holm-Swarm mouse sarcoma, human collagen I (C5483), human amyloid β protein fragment 1–42 (A9810), chondroitin sulfate from bovine trachea (C8529), heparin (H3393), and dermatan sulfate (C3788) from porcine intestinal mucosa, murine SPARC (S5174), guinea pig transglutaminase (T5398), bovine biglycan (B8041), and human fibronectin (F2006) were purchased from Sigma. Sodium hyaluronate was from Acros Organics (Geel, Belgium). Heparan sulfate from porcine intestinal mucosa was from Celsus (OH). Full-length human α5β1, αvβ3, and αvβ5 integrins were from Chemicon (Millipore, France), and recombinant human thrombospondin-1 was from R&D Systems (Minneapolis, MN). Pepsinized collagens IV and VI from human placenta were a generous gift from Dr. Florence Ruggiero (UMR 5086, CNRS, University Lyon 1, France). Bovine collagen XI was a generous gift from Dr. Marie-Claire Ronzière (UMR 5086, CNRS, University Lyon 1, France).

SPR Arrays

SPR arrays were handled in a Biacore Flexchip system (GE Healthcare), a commercially available high-density array platform that is capable of analyzing one analyte against 400 target spots at a time. Proteins or glycosaminoglycans were printed directly in triplicate at two different concentrations onto the gold surface of a Gold Affinity chip (GE Healthcare) using a non-contact PiezoArray spotter (PerkinElmer Life Sciences). The spotted matrix (15 × 15) comprised 225 spots. Proteins were spotted at concentrations varying from 50 to 200 μg/ml and glycosaminoglycans at 0.5 and 1 mg/ml. Six drops of 330 pl each were delivered to the surface of the chip (total spotted volume, 2.2 nl; spot diameter, 250–300 μm; spotted amount, 100–400 pg/spot). The chips were then dried at room temperature and stored under vacuum at 4 °C until their insertion into the Biacore Flexchip. The regions of interest of the chip were defined when the chip was dry. Each region of interest had four associated reference spots that were used to correct bulk refractive index changes as well as nonspecific binding of the analyte to the chip. The chip was blocked with a buffer containing mammalian proteins (Superblock, Pierce) for 5 times for 5 min. The blocked chip was then equilibrated with phosphate-buffered saline, 0.05% Tween 20 at 500 μl/min for 90 min. The analyte was flowed over the chip surface at 25 °C at a concentration ranging from 50 nm to 5 μm for 25 min at the same flow rate. The dissociation was monitored during injection of phosphate-buffered saline, 0.05% Tween for 40 min. Injected proteins were diluted in phosphate-buffered saline, 0.05% Tween, except full-length integrins, which were diluted in 10 mm Hepes buffer, pH 7.4, containing 150 mm NaCl, 2 mm CaCl2, 2 mm MnCl2, and 50 mm octyl β-d-glucopyranoside. Data collected from reference spots (gold surface) and buffer spots were subtracted from those collected on spotted proteins or glycosaminoglycans to obtain specific binding curves.

Building and Visualization of the Endostatin Interaction Network

Cytoscape, a software environment for integrated models of biomolecular interaction networks (21), was used to visualize the endostatin interaction network built with the tools provided on the website of MatrixDB (22).

In Silico Analysis of Endostatin Network

UniProtKB entries (Universal Protein Resource) (23) were tagged with 10 categories of keywords (biological process, cellular component, coding sequence diversity, developmental stage, disease, domain, ligand, molecular function, post-translational modification, and technical term). The keywords associated to the 26 protein partners of endostatin were ranked according to their occurrence. The percentage of keyword use in the endostatin network was compared with the keyword use in the 19,398 annotated human protein entries of UniProtKB (January 20, 2009). UniProt data were stored into a data base based on AceDB (24) to ease the counting of UniProt keywords and InterPro annotations.

InterPro (Integrated Resource of Protein Domains and Functional Sites) is a data base of protein families, domains, regions, repeats, and sites (25). UniProtKB cross-references to InterPro were used to identify the domains present in the protein partners of endostatin. The percentage of occurrence of a particular domain was calculated as described above for UniProtKB keywords, except that cross-references were available for 16,774 annotated human protein entries.

RESULTS

We looked for additional partners of endostatin using SPR arrays. This approach was selected because the yeast two-hybrid assay, which is widely used for high throughput discovery of protein interactions, is not the method of choice for studying extracellular interactions. Extracellular proteins are not optimally expressed in the nucleus, they are sticky and this may lead to false positive results. Furthermore, two-hybrid assays are not adapted to identify protein-polysaccharide interactions, which are of major importance for cell-matrix interactions and for the organization of the extracellular matrix. Known interactions were analyzed to validate SPR arrays and the Biacore Flexchip as reliable tools for the investigation of interactions established by endostatin. We confirmed by this technique previously described interactions between heparin/heparan sulfate and several extracellular proteins including endostatin (8, 9, 26), collagens I and V (27, 28), fibronectin, and transglutaminase-2. Protein-protein interactions between endostatin and laminin (29), endostatin and α5β1 integrin (10, 11), or between tissue transglutaminase and α5β1 integrin (30) were also confirmed, as were interactions between proteins and proteoglycans such as the collagen VI-biglycan interaction (31) (Table 1).

TABLE 1.

Interactions identified using surface plasmon resonance arrays

Molecule injected in buffer flow (analyte) Molecule spotted on the array (ligand)
Interactions identified using SPR arrays
    Heparin Endostatin
    Heparin Collagen XI
    Heparan sulfate Endostatin
    Laminin-1 Endostatin
    Laminin-1 NC1(XVIII)
    Laminin-1 Heparin
    Laminin-1 Heparan sulfate
    Laminin-1 Dermatan sulfate
    Laminin-1 Transglutaminase-2
    Integrin α5β1 Endostatin
    Integrin α5β1 NC1(XVIII)
    Integrin α5β1 Heparan sulfate
    Integrin α5β1 Transglutaminase-2
    Integrin α5β1 Heparin
    Integrin α5β1 Hyaluronan
    Integrin αvβ3 Endostatin
    Integrin αvβ3 NC1(XVIII)
    Integrin αvβ3 Heparin
    Integrin αvβ3 Collagen XI
    Integrin αvβ3 Collagen VI
    Integrin αvβ3 Transglutaminase-2
    Collagen I Biglycan
    Collagen I Transglutaminase-2
    Collagen I Endostatin
    Collagen I Heparan sulfate
    Collagen I Dermatan sulfate
    Collagen I Heparin
    Collagen I Chondroitin sulfate
    Collagen IV Transglutaminase-2
    Collagen IV Endostatin
    Collagen IV NC1(XVIII)
    Collagen IV Heparin
    Collagen IV Heparan sulfate
    Collagen IV Dermatan sulfate
    Collagen IV Biglycan
    Collagen IV Chondroitin sulfate
    Collagen VI Transglutaminase-2
    Collagen VI Endostatin
    Collagen VI NC1(XVIII)
    Collagen VI Heparin
    Collagen VI Heparan sulfate
    Collagen VI Dermatan sulfate
    Collagen VI Biglycan
    Collagen VI Chondroitin sulfate
    Fibronectin Heparin
    SPARC Endostatin
    SPARC NC1(XVIII)
    SPARC Heparin
    SPARC Dermatan sulfate
    SPARC Collagen I
    SPARC Collagen XI
    Transglutaminase-2 Heparin
    Transglutaminase-2 Collagen XI
    Transglutaminase-2 Endostatin
    Transglutaminase-2 NC1(XVIII)
    Transglutaminase-2 Heparan sulfate
    Endostatin Collagen I
    Endostatin Chondroitin sulfate
    Endostatin Collagen VI
    Endostatin Heparin
    Endostatin Heparan sulfate
    Endostatin Amyloid peptide β-(1–42)
    Endostatin Dermatan sulfate
    Endostatin Transglutaminase-2
    Endostatin Biglycan
    Amyloid peptide β-(1–42) NC1(XVIII)
    Amyloid peptide β-(1–42) Biglycan
    Amyloid peptide β-(1–42) Collagen XI
    Amyloid peptide β-(1–42) Endostatin
    Amyloid peptide β-(1–42) Transglutaminase-2
    Amyloid peptide β-(1–42) Hyaluronan
    Amyloid peptide β-(1–42) Heparan sulfate
    Amyloid peptide β-(1–42) Heparin
    Amyloid peptide β-(1–42) Chondroitin sulfate
    Amyloid peptide β-(1–42) Dermatan sulfate
    Thrombospondin-1 Collagen I
    Thrombospondin-1 Collagen VI
    Thrombospondin-1 Collagen XI
    Thrombospondin-1 Chondroitin sulfate
    Thrombospondin-1 Dermatan sulfate
    Thrombospondin-1 Heparin
    Thrombospondin-1 Heparan sulfate
    Thrombospondin-1 Endostatin
    Thrombospondin-1 NC1(XVIII)
    Thrombospondin-1 Transglutaminase-2
    Thrombospondin-1 Fibronectin
    Thrombospondin-1 Biglycan
    Thrombospondin-1 Amyloid peptide β-(1–42)

No interaction detected using SPR arrays
    Endostatin Collagen XI
    Endostatin Fibronectin
    Endostatin Hyaluronan

Identification by SPR Arrays of New Partners to Build the Interaction Network of Endostatin

New partners of endostatin, either as a monomer or as a trimer within the NC1 domain of collagen XVIII, were identified (Figs. 1 and 2). They include the amyloid peptide Aβ-(1–42), thrombospondin-1, SPARC, transglutaminase-2, chondroitin sulfate, dermatan sulfate, and collagens I, IV, and VI. Because collagen IV and VI preparations used in this study were solubilized by pepsin treatment, it is likely that endostatin bind to the triple-helical part of these collagen molecules. Endostatin did not bind to fibronectin, collagen XI, or hyaluronan (Table 1).

FIGURE 1.

FIGURE 1.

SPR arrays. Injection of collagens I (50 nm), IV (250 nm), and VI (250 nm), thrombospondin-1 (70 nm), heparan sulfate proteoglycan-2 (155 nm), and amyloid peptide (5 μm) over immobilized endostatin spotted onto a Gold Affinity chip.

FIGURE 2.

FIGURE 2.

The interaction network of endostatin. New partners identified by SPR arrays are in red.

Direct interactions were also found between transglutaminase-2 and the β-amyloid peptide or transglutaminase-2 and αvβ3 integrin. Furthermore, collagen XI was identified as a new ligand of αvβ3 integrin, and was shown to bind the amyloid peptide Aβ-(1–42) (Table 1).

SPR assays were performed with mutants of the NC1 domain to determine the influence of well characterized mutations on the binding of these new partners to the trimeric NC1 domain. Mutations of two arginine residues Arg27 and Arg139 of the NC1 domain abolish the binding to heparin (32), whereas individuals homozygous for the D104N polymorphism might have a high risk of occurrence of sporadic breast cancer (33). Mutations of Arg27 and Arg139 decreased binding of the NC1 domain to collagen IV, collagen VI, and the amyloid peptide, suggesting that these two residues participate in these interactions. The D104N mutation, whether in monomeric endostatin or within the NC1 domain, did not significantly alter the ability to bind to heparin, collagens IV and VI, α5β1 integrin, and heparan sulfate proteoglycan 2.

Analysis of Endostatin Network

To determine the major structural and functional features of the endostatin interaction network, the network was analyzed using the annotations provided by UniProtKB and InterPro. Annotations were available for the 26 protein partners of endostatin. Endostatin partners lacking annotations (endorepellin, zinc, glycosaminoglycans, and multimolecular complexes) were excluded from the analysis because they are not annotated in UniProtKB.

UniProtKB keywords were found to be present four times on average in the protein partners of endostatin. Only keywords used more than four times in the network were thus taken into account for further analysis. We checked that the over-representation of a keyword within the network was not due to an over-representation in UniProtKB human entries. Protein partners of endostatin were frequently and significantly associated to the following keywords “basement membrane,” “extracellular matrix,” and “secreted” for the “cellular component category,” to “calcium” for the “ligand category,” to “cell adhesion” for the “biological process category,” and to “EGF-like domain” for the “domain” category (Table 2).

TABLE 2.

Use of keywords from UniProtKB in the protein partners of endostatin

Keyword category (UniProtKB) Keyword Number of annotations in endostatin partners (26) Number of annotations in human proteins(19,398) Use in endostatin partners Use in human proteins Ratio between endostatin partners and human proteins
%
Technical term Three-dimensional structure 13 3,471 50.00 17.89 2.79
Direct protein sequencing 17 2,608 65.38 13.44 4.86
Coding sequence diversity Alternative splicing 10 7,307 38.46 37.67 1.02
Polymorphism 21 10,670 80.77 55.01 1.47
Cellular component Basement membrane 6 35 23.08 0.18 127.90
Extracellular matrix 13 221 50.00 1.14 43.89
Membrane 7 6,427 26.92 33.13 0.81
Secreted 20 1,722 76.92 8.88 8.67
Ligand Calcium 14 800 53.85 4.12 13.06
Biological process Cell adhesion 9 425 34.62 2.19 15.80
Disease Disease mutation 12 1,526 46.15 7.87 5.87
Domain EGF-like domain 9 233 34.62 1.20 28.82
Signal 23 3,459 88.46 17.83 4.96
Post-translation modification Glycoprotein 24 4,425 92.31 22.81 4.05
Phosphoprotein 8 6,540 30.77 33.71 0.91

The procedure described above was applied to InterPro to analyze the domain structure of the protein partners of endostatin (Table 3). InterPro domains were found to be present two times on average in the endostatin network. Only keywords used more than twice in the network were taken into account for further analysis. The most represented domains in the endostatin network were the EGF domain and its variants (EGF calcium-binding, EGF-like, EGF-like calcium-binding, EGF-like region conserved site, EGF-like type 3, and EGF-type aspartate/asparagine hydroxylation conserved site). They were present in 12 proteins over 26 (46%). Although numerous extracellular matrix proteins comprise EGF or EGF-like modules, the number of these modules was increased by at least a factor of 2 in the endostatin network. The network was also enriched in the concanavalin A-like lectin/glucanase domain (found in laminin-1, thrombospondin-1, and perlecan), in collagen triple helix repeats, and in the von Willebrand factor A domain.

TABLE 3.

Use of InterPro keywords of the protein partners of endostatin

Term Number of occurrence in endostatin partners (26) Number of occurrence in human proteins (16,774) Use in endostatin partners Use in human proteins Ratio between endostatin partners and human proteins
%
Collagen triple helix repeat 3 82 11.54 0.49 23.60
Concanavalin A-like lectin/glucanase, subgroup 3 76 11.54 0.45 25.47
EGF 7 206 26.92 1.23 21.92
EGF calcium binding 7 74 26.92 0.44 61.03
EGF-like 4 146 15.38 0.87 17.68
EGF-like calcium binding 7 101 26.92 0.60 44.71
EGF-like region, conserved site 12 276 46.15 1.65 28.05
EGF-like, type 3 9 232 34.62 1.38 25.03
EGF-type aspartate/asparagine hydroxylation conserved site 7 99 26.92 0.59 45.62
Immunoglobulin I-set 3 136 11.54 0.81 14.23
Immunoglobulin subtype 2 3 211 11.54 1.26 9.17
Immunoglobulin-like 3 709 11.54 4.23 2.73
Immunoglobulin-like fold 4 706 15.38 4.21 3.66
von Willebrand factor, type A 3 90 11.54 0.54 21.51

DISCUSSION

A number of new endostatin partners have been identified by SPR arrays. Of course we cannot rule out the existence of further partners of endostatin as discussed below, but the coverage of interactomes (interaction networks) remains difficult to assess, and is a general concern for existing data sets (34).

Endostatin is a component of basement membrane, and it interacts with collagen IV, a major component of basement membrane, and with collagen VI. Endostatin may link elastic fibers to collagen VI microfibrils in elastic tissues such as the aortic wall where endostatin is present (35). The binding of endostatin to collagen VI is in agreement with the fact that collagen VI is in contact with endothelial basement membranes. Collagen VI might anchor endothelial basement membranes not only by interacting with collagen IV (36), but also by interacting with endostatin.

Endostatin binds to several molecules participating in the control of angiogenesis. Besides integrins and heparan sulfate, it binds to an endogenous inhibitor of angiogenesis, endorepellin, a C-terminal domain of perlecan (37). Heparan sulfate proteoglycan-2 or perlecan, which plays a dual role in angiogenesis (38), also interacts with endostatin. Transglutaminase-2 is a new interacting partner of endostatin that is also involved in angiogenesis. The formation of a complex between this enzyme and VEGFR-2 has been proposed as a mechanism for modulation of endothelial cell response to VEGF (39). We have identified another endogenous inhibitor of angiogenesis, thrombospondin-1, as an interacting partner of endostatin. Thrombospondin-1 and endostatin share several properties. Both are found in platelets, bind to heparin, and are endogenous inhibitors of angiogenesis. Furthermore, the expression of thrombospondin-1 is up-regulated by endostatin (15), and thrombospondin-1 may act as a mediator of anti-angiogenic therapy (40). Endostatin also binds to SPARC, which blocks angiogenesis (41, 42) and is found as well as endostatin in platelets and basement membranes.

Interestingly, SPARC and thrombospondin-1 belong to the matricellular protein family. The term “matricellular” refers to a group of modular, extracellular proteins whose functions are achieved by binding to matrix proteins as well as to cell surface receptors, or to other molecules such as cytokines and proteases that interact, in turn, with the cell surface (43). Members of this protein class serve as biological mediators of cell function by interacting directly with cells or by modulating the activity of growth factors, proteases, and other extracellular matrix proteins (44). Endostatin might regulate cell adhesion not only via integrin signaling, but also in association with thrombospondin-1 and SPARC. Other matricellular proteins, such as members of the tenascin protein family and osteopontin, might also be able to interact with endostatin to control cell adhesion. The participation of the endostatin network to the control of cell adhesion is further supported by the fact that 46% of the protein partners of endostatin are annotated with a Gene Ontology term (45) referring to cell adhesion (data not shown).

We demonstrated that endostatin binds to the amyloid Aβ peptide, which has been previously shown to be co-localized with endostatin in amyloid plaques of patients with Alzheimer disease (18). Several other partners of endostatin are involved in neurodegenerative diseases. They include transglutaminase-2, which catalyzes the cross-linking of the amyloid peptide β (46), fibulin-1 (47), laminin-1 (48), thrombospondin-1 (49), heparan sulfate and heparan sulfate proteoglycans (50), perlecan (51), α5β1 integrin (52), collagen IV (53), and collagen VI, an important component of the neuronal injury response (54). The binding of endostatin to the amyloid peptide could have a protective effect, as suggested for transthyretin (55), and for other extracellular components such as collagens VI (54) and XXV (56). Depending on the trigger event (e.g. increase in VEGF expression), and on the availability of its members in a given tissue at a given time, the endostatin network might be involved either in the control of angiogenesis, and tumor growth, or in neurogenesis and neurodegenerative diseases.

At the molecular level, the major features of the endostatin interaction network are the presence of EGF modules (e.g. in fibulins, nidogens, laminin-1, perlecan, thrombospondin-1, and integrins), and the ability of several partners to bind calcium (e.g. transglutaminase-2). This finding is supported by the fact that 50% of the protein partners of endostatin are annotated with the Gene Ontology term “calcium ion binding” (data not shown). Other extracellular proteins containing EGF modules might be potential partners of endostatin. We are currently studying the structure of EGF domains found in endostatin partners to identify possible common features, which will be helpful to select EGF domains of multidomain proteins for further interaction studies.

The interaction network will be useful for mimicking gene silencing studies and suppression in silico of glycosaminoglycans. This will be of special interest for glycosaminoglycans, which can be “suppressed” in vivo only by silencing several genes involved in their biosynthesis. It will also be of interest for the set-up of combination therapies, in which drugs targeting different pathways are simultaneously administered. The multifaceted nature of the angiogenic process suggests that the combination of antiangiogenic drugs might be more effective than single-agent therapies (57).

We combined extracellular protein-protein and protein-glycosaminoglycan interactions involving endostatin without discriminating their spatio-temporal expression. The next step will be to switch from a static to a dynamic extracellular interaction network by (i) putting weight on the interactions using kinetic and affinity constants to define the hierarchy of interactions according to their rate of formation and their stability, (ii) determining mutually exclusive interactions from three-dimensional structures and/or docking experiments, and (iii) integrating expression data. The building of a dynamic extracellular interaction network will be of interest to understand how information/signaling is conveyed through the network and to predict the consequences of perturbations due to changes in the expression of pro- and anti-angiogenic factors. The integrated network will be used as a framework to build a mathematical model of endostatin mechanism of action in various physio-pathological processes such as basement membrane assembly, angiogenesis, neurogenesis, and neurodegenerative diseases.

Acknowledgments

We thank C. Marquette and L. Blum (ICBMS, UMR 5246 CNRS, University Lyon 1, France) for providing access to the spotter. The support of the GE Healthcare staff (C. Quétard, P. Linden, T. Salomon, X. Rousselot, and A. Sylvan), who provided access to the Biacore Flexchip for the first experiments is gratefully acknowledged. We thank F. Ruggiero and M. C. Ronzière (UMR 5086, CNRS, University Lyon 1, France) for their generous gift of collagens IV, VI, and XI.

*

This work was supported, in whole or in part, by National Institutes of Health Grant 36820 (to B. O.). This work was also supported by Association pour la Recherche contre le Cancer Grant 3652 (to S. R. B.), GIS Maladies Rares INSERM Grant A04115SP (to S. R. B.), grants from the CPER Rhône-Alpes (to C. F., E. C., and S. R. B.), Institut Rhône-Alpin des Systèmes Complexes (to C. F., E. C., and S. R. B.), the Emergence Research Program Région Rhône-Alpes (to S. R. B.), and a Bonus Qualité Recherche grant from the University Lyon-1 (to S. R. B.).

3
The abbreviations used are:
VEGF
vascular endothelial growth factor
EGF
epidermal growth factor
NC1
non-collagenous 1
SPARC
secreted protein acidic and rich in cysteine
SPR
surface plasmon resonance.

REFERENCES

  • 1.Nyberg P., Xie L., Kalluri R. (2005) Cancer Res. 65, 3967–3979 [DOI] [PubMed] [Google Scholar]
  • 2.Folkman J. (2006) Exp. Cell Res. 312, 594–607 [DOI] [PubMed] [Google Scholar]
  • 3.Digtyar A. V., Pozdnyakova N. V., Feldman N. B., Lutsenko S. V., Severin S. E. (2007) Biochemistry 72, 235–246 [DOI] [PubMed] [Google Scholar]
  • 4.Celik I., Sürücü O., Dietz C., Heymach J. V., Force J., Höschele I., Becker C. M., Folkman J., Kisker O. (2005) Cancer Res. 65, 11044–11050 [DOI] [PubMed] [Google Scholar]
  • 5.Tjin Tham Sjin R. M., Naspinski J., Birsner A. E., Li C., Chan R., Lo K. M., Gillies S., Zurakowski D., Folkman J., Samulski J., Javaherian K. (2006) Cancer Gene Ther. 13, 619–627 [DOI] [PubMed] [Google Scholar]
  • 6.Li C., Harris M. B., Venema V. J., Venema R. C. (2005) Biochem. Biophys. Res. Commun. 329, 873–878 [DOI] [PubMed] [Google Scholar]
  • 7.Schmidt A., Wenzel D., Ferring I., Kazemi S., Sasaki T., Hescheler J., Timpl R., Addicks K., Fleischmann B. K., Bloch W. (2004) Dev. Dyn. 230, 468–480 [DOI] [PubMed] [Google Scholar]
  • 8.Yamaguchi N., Anand-Apte B., Lee M., Sasaki T., Fukai N., Shapiro R., Que I., Lowik C., Timpl R., Olsen B. R. (1999) EMBO J. 18, 4414–4423 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Ricard-Blum S., Féraud O., Lortat-Jacob H., Rencurosi A., Fukai N., Dkhissi F., Vittet D., Imberty A., Olsen B. R., van der Rest M. (2004) J. Biol. Chem. 279, 2927–2936 [DOI] [PubMed] [Google Scholar]
  • 10.Rehn M., Veikkola T., Kukk-Valdre E., Nakamura H., Ilmonen M., Lombardo C., Pihlajaniemi T., Alitalo K., Vuori K. (2001) Proc. Natl. Acad. Sci. U.S.A. 98, 1024–1029 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Faye C., Moreau C., Chautard E., Jetne R., Fukai N., Ruggiero F., Humphries M. J., Olsen B. R., Ricard-Blum S. (2009) J. Biol. Chem. in press [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Karumanchi S. A., Jha V., Ramchandran R., Karihaloo A., Tsiokas L., Chan B., Dhanabal M., Hanai J. I., Venkataraman G., Shriver Z., Keiser N., Kalluri R., Zeng H., Mukhopadhyay D., Chen R. L., Lander A. D., Hagihara K., Yamaguchi Y., Sasisekharan R., Cantley L., Sukhatme V. P. (2001) Mol. Cell 7, 811–822 [DOI] [PubMed] [Google Scholar]
  • 13.Kim Y. M., Hwang S., Kim Y. M., Pyun B. J., Kim T. Y., Lee S. T., Gho Y. S., Kwon Y. G. (2002) J. Biol. Chem. 277, 27872–27879 [DOI] [PubMed] [Google Scholar]
  • 14.Cao Y. (2008) Adv. Cancer Res. 100, 113–131 [DOI] [PubMed] [Google Scholar]
  • 15.Abdollahi A., Hahnfeldt P., Maercker C., Gröne H. J., Debus J., Ansorge W., Folkman J., Hlatky L., Huber P. E. (2004) Mol. Cell 13, 649–663 [DOI] [PubMed] [Google Scholar]
  • 16.Chautard E., Thierry-Mieg N., Ricard-Blum S. (2009) Pathol. Biol. 57, 324–333 [DOI] [PubMed] [Google Scholar]
  • 17.Marneros A. G., Olsen B. R. (2005) FASEB J. 19, 716–728 [DOI] [PubMed] [Google Scholar]
  • 18.Deininger M. H., Fimmen B. A., Thal D. R., Schluesener H. J., Meyermann R. (2002) J. Neurosci. 22, 10621–10626 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Pufe T., Petersen W. J., Miosge N., Goldring M. B., Mentlein R., Varoga D. J., Tillmann B. N. (2004) Matrix Biol. 2, 267–276 [DOI] [PubMed] [Google Scholar]
  • 20.St. Croix B., Rago C., Velculescu V., Traverso G., Romans K. E., Montgomery E., Lal A., Riggins G. J., Lengauer C., Vogelstein B., Kinzler K. W. (2000) Science 289, 1197–1202 [DOI] [PubMed] [Google Scholar]
  • 21.Shannon P., Markiel A., Ozier O., Baliga N. S., Wang J. T., Ramage D., Amin N., Schwikowski B., Ideker T. (2003) Genome Res. 13, 2498–2504 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Chautard E., Ballut L., Thierry-Mieg N., Ricard-Blum S. (2009) Bioinformatics 25, 690–691 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.UniProt Consortium ( 2009) Nucleic Acids Res. 37, D169–D174 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Durbin R., Thierry-Mieg J. (1994) in Computational Methods in Genome Research (Suhai S. ed) pp. 45–55, Plenum Press, New York [Google Scholar]
  • 25.Hunter S., Apweiler R., Attwood T. K., Bairoch A., Bateman A., Binns D., Bork P., Das U., Daugherty L., Duquenne L., Finn R. D., Gough J., Haft D., Hulo N., Kahn D., Kelly E., Laugraud A., Letunic I., Lonsdale D., Lopez R., Madera M., Maslen J., McAnulla C., McDowall J., Mistry J., Mitchell A., Mulder N., Natale D., Orengo C., Quinn A. F., Selengut J. D., Sigrist C. J., Thimma M., Thomas P. D., Valentin F., Wilson D., Wu C. H., Yeats C. (2009) Nucleic Acids Res. 37, D211–D215 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Sasaki T., Fukai N., Mann K., Göhring W., Olsen B. R., Timpl R. (1998) EMBO J. 17, 4249–4256 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Ricard-Blum S., Peel L. L., Ruggiero F., Freeman N. J. (2006) Anal. Biochem. 352, 252–259 [DOI] [PubMed] [Google Scholar]
  • 28.Ricard-Blum S., Beraud M., Raynal N., Farndale R. W., Ruggiero F. (2006) J. Biol. Chem. 281, 25195–25204 [DOI] [PubMed] [Google Scholar]
  • 29.Javaherian K., Park S. Y., Pickl W. F., LaMontagne K. R., Sjin R. T., Gillies S., Lo K. M. (2002) J. Biol. Chem. 277, 45211–45218 [DOI] [PubMed] [Google Scholar]
  • 30.Akimov S. S., Krylov D., Fleischman L. F., Belkin A. M. (2000) J. Cell Biol. 148, 825–838 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Wiberg C., Heinegård D., Wenglén C., Timpl R., Mörgelin M. (2002) J. Biol. Chem. 277, 49120–49126 [DOI] [PubMed] [Google Scholar]
  • 32.Sasaki T., Larsson H., Kreuger J., Salmivirta M., Claesson-Welsh L., Lindahl U., Hohenester E., Timpl R. (1999) EMBO J. 18, 6240–6428 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Lourenço G. J., Cardoso-Filho C., Gonçales N. S., Shinzato J. Y., Zeferino L. C., Nascimento H., Costa F. F., Gurgel M. S., Lima C. S. (2006) Breast Cancer Res. Treat. 100, 335–338 [DOI] [PubMed] [Google Scholar]
  • 34.Venkatesan K., Rual J. F., Vazquez A., Stelzl U., Lemmens I., Hirozane-Kishikawa T., Hao T., Zenkner M., Xin X., Goh K. I., Yildirim M. A., Simonis N., Heinzmann K., Gebreab F., Sahalie J. M., Cevik S., Simon C., de Smet A. S., Dann E., Smolyar A., Vinayagam A., Yu H., Szeto D., Borick H., Dricot A., Klitgord N., Murray R. R., Lin C., Lalowski M., Timm J., Rau K., Boone C., Braun P., Cusick M. E., Roth F. P., Hill D. E., Tavernier J., Wanker E. E., Barabási A. L., Vidal M. (2009) Nat. Methods 6, 83–90 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Miosge N., Sasaki T., Timpl R. (1999) FASEB J. 13, 1743–1750 [DOI] [PubMed] [Google Scholar]
  • 36.Kuo H. J., Maslen C. L., Keene D. R., Glanville R. W. (1997) J. Biol. Chem. 272, 26522–26529 [DOI] [PubMed] [Google Scholar]
  • 37.Mongiat M., Sweeney S. M., San Antonio J. D., Fu J., Iozzo R. V. (2003) J. Biol. Chem. 278, 4238–4249 [DOI] [PubMed] [Google Scholar]
  • 38.Bix G., Iozzo R. V. (2008) Microsc. Res. Tech. 71, 339–348 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Dardik R., Inbal A. (2006) Exp. Cell Res. 312, 2973–2982 [DOI] [PubMed] [Google Scholar]
  • 40.Bocci G., Francia G., Man S., Lawler J., Kerbel R. S. (2003) Proc. Natl. Acad. Sci. U.S.A. 100, 12917–12922 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Chlenski A., Liu S., Crawford S. E., Volpert O. V., DeVries G. H., Evangelista A., Yang Q., Salwen H. R., Farrer R., Bray J., Cohn S. L. (2002) Cancer Res. 62, 7357–7363 [PubMed] [Google Scholar]
  • 42.Chlenski A., Liu S., Guerrero L. J., Yang Q., Tian Y., Salwen H. R., Zage P., Cohn S. L. (2006) Int. J. Cancer 118, 310–316 [DOI] [PubMed] [Google Scholar]
  • 43.Bornstein P. (1995) J. Cell Biol. 130, 503–506 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Alford A. I., Hankenson K. D. (2006) Bone 38, 749–757 [DOI] [PubMed] [Google Scholar]
  • 45.Ashburner M., Ball C. A., Blake J. A., Botsein D., Butler H., Cherry J. M., Davis A. P., Dolinski K., Dwight S. S., Eppig J. T., Harris M. A., Hill D. P., Issel-Tarver L., Kasarskis A., Lewis S., Matese J. C., Richardson J. E., Ringwald M., Rubin G. M., Sherlock G. (2000) Nat. Genet. 25, 25–29 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Wang D. S., Dickson D. W., Malter J. S. (2008) Int. J. Clin. Exp. Pathol. 1, 5–18 [PMC free article] [PubMed] [Google Scholar]
  • 47.Timpl R., Sasaki T., Kostka G., Chu M. L. (2003) Nat. Rev. Mol. Cell Biol. 4, 479–489 [DOI] [PubMed] [Google Scholar]
  • 48.Morgan C., Bugueño M. P., Garrido J., Inestrosa N. C. (2002) Peptides 23, 1229–1240 [DOI] [PubMed] [Google Scholar]
  • 49.Buée L., Hof P. R., Roberts D. D., Delacourte A., Morrison J. H., Fillit H. M. (1992) Am. J. Pathol. 141, 783–788 [PMC free article] [PubMed] [Google Scholar]
  • 50.van Horssen J., Wesseling P., van den Heuvel L. P., de Waal R. M., Verbeek M. M. (2003) Lancet Neurol. 2, 482–492 [DOI] [PubMed] [Google Scholar]
  • 51.Castillo G. M., Ngo C., Cummings J., Wight T. N., Snow A. D. (1997) J. Neurochem. 69, 2452–2465 [DOI] [PubMed] [Google Scholar]
  • 52.Matter M. L., Zhang Z., Nordstedt C., Ruoslahti E. (1998) J. Cell Biol. 141, 1019–1030 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Kiuchi Y., Isobe Y., Fukushima K. (2002) Life Sci. 70, 1555–1564 [DOI] [PubMed] [Google Scholar]
  • 54.Cheng J. S., Dubal D. B., Kim D. H., Legleiter J., Cheng I. H., Yu G. Q., Tesseur I., Wyss-Coray T., Bonaldo P., Mucke L. (2009) Nat. Neurosci. 12, 119–121 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Buxbaum J. N., Ye Z., Reixach N., Friske L., Levy C., Das P., Golde T., Masliah E., Roberts A. R., Bartfai T. (2008) Proc. Natl. Acad. Sci. U.S.A. 105, 2681–2686 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Osada Y., Hashimoto T., Nishimura A., Matsuo Y., Wakabayashi T., Iwatsubo T. (2005) J. Biol. Chem. 280, 8596–8605 [DOI] [PubMed] [Google Scholar]
  • 57.Abdollahi A., Lipson K. E., Sckell A., Zieher H., Klenke F., Poerschke D., Roth A., Han X., Krix M., Bischof M., Hahnfeldt P., Grone H. J., Debus J., Hlatky L., Huber P. E. (2003) Cancer Res. 63, 8890–8898 [PubMed] [Google Scholar]

Articles from The Journal of Biological Chemistry are provided here courtesy of American Society for Biochemistry and Molecular Biology

RESOURCES