Cancer progression involves changes in extracellular proteolysis, but the contribution of stromal cell secretomes to the cancer degradome remains uncertain. We have now defined the secretome of a specific stromal cell type, the myofibroblast, in gastric cancer and its modification by proteolysis. SILAC labeling and COFRADIC isolation of methionine containing peptides allowed us to quantify differences in gastric cancer-derived myofibroblasts compared with myofibroblasts from adjacent tissue, revealing increased abundance of several proteases in cancer myofibroblasts including matrix metalloproteinases (MMP)-1 and -3. Moreover, N-terminal COFRADIC analysis identified cancer-restricted proteolytic cleavages, including liberation of the active forms of MMP-1, -2, and -3 from their inactive precursors. In vivo imaging confirmed increased MMP activity when gastric cancer cells were xenografted in mice together with gastric cancer myofibroblasts. Western blot and enzyme activity assays confirmed increased MMP-1, -2, and -3 activity in cancer myofibroblasts, and cancer cell migration assays indicated stimulation by MMP-1, -2, and -3 in cancer-associated myofibroblast media. Thus, cancer-derived myofibroblasts differ from their normal counterparts by increased production and activation of MMP-1, -2, and -3, and this may contribute to the remodelling of the cancer cell microenvironment.
Cancer progression involves changes in extracellular proteolysis, but the contribution of stromal cell secretomes to the cancer degradome remains uncertain. We have now defined the secretome of a specific stromal cell type, the myofibroblast, in gastric cancer and its modification by proteolysis. SILAC labeling and COFRADIC isolation of methionine containing peptides allowed us to quantify differences in gastric cancer-derived myofibroblasts compared with myofibroblasts from adjacent tissue, revealing increased abundance of several proteases in cancer myofibroblasts including matrix metalloproteinases (MMP)-1 and -3. Moreover, N-terminal COFRADIC analysis identified cancer-restricted proteolytic cleavages, including liberation of the active forms of MMP-1, -2, and -3 from their inactive precursors. In vivo imaging confirmed increased MMP activity when gastric cancer cells were xenografted in mice together with gastric cancer myofibroblasts. Western blot and enzyme activity assays confirmed increased MMP-1, -2, and -3 activity in cancer myofibroblasts, and cancer cell migration assays indicated stimulation by MMP-1, -2, and -3 in cancer-associated myofibroblast media. Thus, cancer-derived myofibroblasts differ from their normal counterparts by increased production and activation of MMP-1, -2, and -3, and this may contribute to the remodelling of the cancer cell microenvironment.
Elucidation of the
dynamic changes in secretomes, i.e., the secreted
subset of the proteome, underlies a systems approach to understanding
the mechanisms controlling cell–cell and cell–matrix
interactions in health and disease. In cancer it is now clear that
changes in the cellular microenvironment determine disease progression,
and that these include two-way interactions between cancer cells and
surrounding stromal cells.[1−3]Several recent studies have
employed proteomic techniques to define
the secretomes of cancer cells.[4−10] Recent studies have also defined the secretome in breast and colon
cancer fibroblasts,[11,12] but in general the interrogation
of stromal cell secretomes by proteomic methods has been limited.
Changes in secretomes may reflect alterations in secretory protein
abundance due to variations in gene expression, rates of exocytosis
or presecretory post-translational processing. But in addition, there
may also be extensive postsecretory proteolysis that defines the extracellular
tumor degradome. In cancer, alterations in extracellular proteolysis
through differential secretion of proteases or their inhibitors is
important, not least because it underlies disease progression and
sensitivity to protease targeted therapies.[13−15]Cancer-associated
fibroblasts, of which myofibroblasts are a subset,
are important stromal cells that exhibit an altered phenotype in many
cancers.[16−19] Myofibroblasts play important roles in defining the tissue microenvironment
through secretion of extracellular matrix components, growth factors,
proteases and their inhibitors.[20,21] Differences between
normal and cancer-associated myofibroblasts (CAMs) have been linked
to tumor progression by mechanisms including recruitment from circulating
mesenchymal stromal cells, global DNA hypomethylation and changes
in gene expression profiles.[22−24] Since myofibroblasts stimulate
cancer cell invasion, in the present study we sought to define the
differences between gastric CAMs compared with adjacent tissue-derived
myofibroblasts (ATMs) with respect to proteolytic processing of their
secretomes. The data indicate both upregulation and activation of
matrix metalloproteinases (MMPs)-1, -2, and -3 are characteristic
of the CAM secretome.
Materials and Methods
Human Primary Myofibroblasts
Myofibroblasts from gastric
cancers (CAMs) and adjacent tissue (ATMs) from two patients have been
described previously (Supporting Information).[19] The work was approved by the Ethics
Committee of the University of Szeged, Hungary, and subjects provided
informed consent.
SILAC Labeling
Myofibroblasts were
cultured in DMEM
SILAC media (Pierce, Thermo Scientific, Rockford, IL, USA) for 6 population
doublings in the presence of either natural (light) or heavy 13C6-labeled l-arginine (0.94 mM) and 13C6l-lysine (0.46 mM) (Invitrogen, Paisley,
Renfrew, U.K.). Media were further supplemented with 10% dialyzed
fetal bovine serum (Pierce), 2% antibiotic/antimycotic (Sigma-Aldrich,
Poole, U.K.) and 1% penicillin/streptomycin (Sigma).
Sample Preparation
Media (10 mL, serum-free) obtained
from 1 × 106 myofibroblasts plated in 10 cm diameter
dishes (80–90% confluency) were collected after 24 h. Samples
were concentrated to approximately 0.5 mL using Amicon Ultra-15 3
kDa centrifugal filter devices (Millipore, Watford, U.K.), precipitated
with 20% TCA and resuspended in 50 mM HEPES, pH 7.4, 100 mM NaCl,
0.8% w/v CHAPS, 1% v/v Protease Inhibitor Cocktail Set III, EDTA-Free
(Calbiochem, Merck Biosciences, Beeston, U.K.). Equal amounts (35
μg each) of light and heavy SILAC-labeled secretome samples
from CAMs and ATMs were mixed following determination of protein concentration
by the Bradford assay (Bio-Rad Lab, Inc., Hemel Hempstead, U.K.).
COFRADIC Isolation of Methionine Containing Peptides
Methionyl-COFRADIC
was performed as described previously[25] (see Supporting Information Methods).
Samples were reduced and S-alkylated, and following trypsinization
(trypsin:protein 1:100), peptides were fractionated by reversed-phase
HPLC (RP-HPLC) using an Agilent 1100 HPLC system with a Zorbax 300SB-C18 column (2.1 mm (internal diameter) × 150 mm, Agilent
Technologies, Wokingham, U.K.). The resulting HPLC fractions were
further processed by incubating for 30 min with 0.1% w/v hydrogen
peroxide at 30 °C. Following oxidation of methionines, reaction
mixtures were immediately reinjected onto the RP-HPLC column for secondary
RP-HPLC separations under identical conditions. Fractions with methionine
containing peptides displayed a hydrophilic shift and were collected
(n = 90) and analyzed by LC–MS/MS.
COFRADIC
Isolation of N-Terminal Peptides
N-terminal
COFRADIC was performed as described previously[26,27] (see Supporting Information Methods).
Proteins were reduced and alkylated, and primary α- and ε-amines
were blocked by trideutero-acetylation. Samples were then trypsinized,
and N-terminal peptides were pre-enriched by strong cation exchange
chromatography at low pH. Following a pyro-glutamate removal step,
peptides were separated by RP-HPLC as described above. Primary fractions
were incubated with 2,4,6-trinitrobenzenesulphonic acid (TNBS) to
modify internal tryptic peptides with free α-N-termini. A series
of secondary RP-HPLC runs was then performed on each individual primary
fraction, and N-terminal peptides (which did not display a hydrophobic
shift) were collected (n = 36) for LC–MS/MS
analysis.
Non-COFRADIC Experiments
Samples prepared for “shotgun”
analysis of the secretomes were processed following the same method
as for Met-COFRADIC up to the stage immediately before the first RP-HPLC
run. At this point the sample was processed for LC–MS/MS analysis
(see Supporting Information Methods).For neo-N-terminal enrichment, the non-COFRADIC method employed a
SCX-only enrichment of N-terminal peptides. Samples were prepared
as for N-terminal COFRADIC up to the first RP-HPLC run. At this stage
60 fractions of 1 min interval were collected, pooled to give a total
of 20 fractions, dried and prepared for LC–MS/MS analysis.
LC–MS/MS Analysis and Peptide Identification by Mascot
Peptides were analyzed using a LTQ Orbitrap XL mass spectrometer
(Thermo Electron, Bremen, Germany) as described previously.[28] Mascot generic files (mgf) were created using
the Mascot Distiller software (version 2.2.1.0, Matrix Science, Ltd.,
London, U.K.). When generating peak lists, grouping of spectra was
performed with a maximum intermediate retention time of 30 s and maximum
intermediate scan count of 5. Grouping was further done with 0.1 Da
precursor ion tolerance. A peak list was only generated when the spectrum
contained more than 10 peaks. There was no deisotoping, and the relative
signal-to-noise limit for both precursor and fragment ions was set
to 2. The peak lists were then searched with Mascot using the Mascot
Daemon interface (version 2.2.0, Matrix Science, Ltd.) against human
proteins in the Swiss-Prot database (Uniprot release 15.0, containing
20 333 human protein sequences). Spectra were searched with
semiArgC/P enzyme settings, allowing no missed cleavages for the N-terminal
peptide experiments, and with trypsin/P settings allowing no missed
cleavages for the Met-COFRADIC/shotgun experiments. Mass tolerance
of the precursor ions was set to 10 ppm (with Mascot’s C13
option set to 1) and of fragment ions to 0.5 Da. The instrument setting
was ESI-TRAP. Variable modifications were acetylation of alpha-N-termini
and pyroglutamate formation of N-terminal glutamine residues; fixed
modification was oxidation of methionine (sulfoxide). Additionally,
for N-terminal peptide experiments, trideutero-acetylation of the
N-terminus was set as variable peptide modification, and trideutero-acetylation
of lysine side chains was included as fixed modification. Only peptides
that were ranked one and scored above the identity threshold score
set at 99% confidence were withheld. The FDR was calculated for every
search as described previously (see Supporting
Information Methods, Table SM3).[28] Identified peptides were quantified using the Mascot Distiller Quantitation
Toolbox (www.matrixscience.com) in the “precursor”
mode as described previously.[29] Ratios
for all peptides of interest were validated by manual inspection of
spectra. For processing of all MS data, the ms_lims software platform
was used.[30] Protein ratios were inferred
using the mean of the peptide group ratios for each protein. A peptide
group represents all quantifications of a single peptide sequence
in an experiment. The distribution of protein ratios as determined
by the Met-COFRADIC and shotgun experiments was plotted using Rover.[31] This was used to define thresholds to give the
5% of proteins with the largest fold changes in CAMs relative to ATMs.
All spectra have been stored in the PRIDE database (http://www.ebi.ac.uk/pride/, accession numbers 27157–27161) using PRIDE converter.[32] Protein subcellular localizations and functional
classifications were manually curated, using the UniProt and HPRD
online databases.
In Vivo Imaging
Immunocompromised
mice (6 weeks old,
BALB/c nu/nu, Charles River, Wilmington, MA) with xenogafts of MKN45
cells with or without CAMs (Supporting Information Methods) were used for imaging MMP-activity using MMPSense 750 FAST.
These experiments were approved by the University of Liverpool Animal
Welfare Committee and were conducted in compliance with the U.K. Animals
(Scientific Procedures) Act 1986.
Western Blot
Myofibroblast
cell extracts were prepared
in RIPA buffer containing protease and phosphatase inhibitors. Cell
extracts or media were resolved by SDS-PAGE and processed for Western
blotting as previously described.[33] Blots
were probed with antibodies against MMP-1 (BAF901, R&D Systems,
Minneapolis, MN, USA), MMP-2 (BAF902, R&D Systems) and MMP-3 (BAF513,
R&D Systems). Membranes were reprobed with anti-GAPDH antibody
(Biodesign, Saco, Maine, USA) for assessing equal loading where appropriate.
Enzyme Assays
Fluorogenic assays for MMP enzyme activity
were performed using selective substrates: DNP-Pro-Leu-Ala-Leu-Trp-Ala-Arg-OH
(MMP-1; Calbiochem, Bedfont Cross, U.K.), DNP-Pro-Leu-Gly-Met-Trp-Ser-Arg-OH
(MMP-2/9; Calbiochem), MCA-Pro-Leu-Ala-Nva-Dpa-Ala-Arg-NH2 (MMP-2; Calbiochem), DNP-Pro-Tyr-Ala-Ty-Trp-Met-Arg-OH (MMP-3; AnaSpec,
Fremont, CA, USA) and 5-FAM-Arg-Pro-Lys-Pro-Val-Glu-Nva-Trp-Arg-Lys(TQ2W)-NH2 (MMP-3; Enzo Life Sciences, Exeter, U.K.) as previously described.[33,34] Briefly, equal volumes of assay buffer and media from 105 myofibroblasts were incubated with 12 μM substrate as appropriate.
Migration Assays
Gastric cancer cell (AGS) migration
(105 cells per 8 μm pore filter insert) (BD Biosciences,
Oxford, U.K.) was studied as previously described.[35,36] Conditioned media were collected as described above and treated
with MMP-1 neutralizing antibody (MAB901, R&D Systems), or selective
MMP-2 (inhibitor I, Calbiochem) and MMP-3 (inhibitor IV, Calbiochem)
inhibitors as appropriate.
Statistics
Results are expressed
as mean ± standard
error of the mean (SEM), unless otherwise stated. Student’s t-test or ANOVA (Systat Software, Inc., Hounslow, London,
U.K.) as appropriate were used to determine statistical significance
of results and considered significant at p < 0.05,
unless otherwise stated.
Results
Different Secretomes in
Cancer-Derived and Adjacent Tissue Myofibroblasts
When myofibroblasts
derived from two gastric cancers and corresponding
ATMs were SILAC labeled and the secretomes analyzed by LC–MS/MS,
approximately 350 unique proteins (310 and 392) were identified in
each pair on the basis of one or more peptide unique assignments with
validated quantification (Supporting Information Tables S1, S2). Of these, 42 and 48% were characterized as extracellular
proteins on the basis of annotations in the UniProt and HPRD databases.
One of the paired samples was further analyzed using the COFRADIC
technology that enriches for methionine-containing peptides in an
attempt to increase overall proteome coverage by reducing sample complexity.
This approach more than doubled the number of unique peptides and
proteins identified in the secretome, although a comparable proportion
(31%) of the identifications were attributable to extracellular proteins
(Figure 1A; Supporting
Information Table S3). The Met-COFRADIC analysis identified
the majority (72%) of proteins identified in the initial experiments
(Figure 1A). In total across the three experiments,
1460 unique proteins were identified, of which 364 were annotated
to be extracellular proteins.
Figure 1
Myofibroblast secretomes. (A) Venn diagram showing,
left, identification
of unique proteins, on the basis of one or more unique peptides with
a validated quantification, in media from pairs of CAMs/ATMs from
two patients, and overlap with Met-COFRADIC identifications in patient
1 based on the same criteria; right, extracellular proteins in this
data set. (B) Functional classification of extracellular proteins
identified by Met-COFRADIC and classical “shotgun” proteomics,
alongside cleaved proteins and total cleavage products in myofibroblast
secretomes by N-terminal peptide enrichment (restricted to identifications
with successful quantification).
Myofibroblast secretomes. (A) Venn diagram showing,
left, identification
of unique proteins, on the basis of one or more unique peptides with
a validated quantification, in media from pairs of CAMs/ATMs from
two patients, and overlap with Met-COFRADIC identifications in patient
1 based on the same criteria; right, extracellular proteins in this
data set. (B) Functional classification of extracellular proteins
identified by Met-COFRADIC and classical “shotgun” proteomics,
alongside cleaved proteins and total cleavage products in myofibroblast
secretomes by N-terminal peptide enrichment (restricted to identifications
with successful quantification).Extracellular proteins making up the secretome were grouped
into
11 functional classifications (Figure 1B).
There was a broadly similar distribution across these groups in both
pairs of CAMs and ATMs, with binding proteins and extracellular matrix
proteins the two largest groups (Figure 1B).
When 95% confidence limits were determined and applied to individual
experiments, 9–47 proteins were identified that were above
or below these limits (Supporting Information Figure S1; Supporting Information Table
S4). Interestingly, MMP-1, MMP-3, MMP-10 and uPA were identified as
upregulated in CAMs in both patients (Supporting
Information Table S4). The largest groups showing differential
abundance were “binding” proteins, e.g., the insulin-like
growth factor binding proteins (IGFBPs), “receptor”
proteins, e.g., epidermal growth factor receptor, and proteases, e.g.,
MMP-1 (Supporting Information Table S4).
Proteolytic Processing of the Secretome
We then extended
the analysis to the identification of neo-N-termini generated as a
consequence of proteolytic cleavage. Thus, SILAC-labeled media samples
were enriched for N-terminal peptides using a strong cation exchange
(SCX) step to remove nonterminal peptides. As part of this procedure,
neo-N-terminal peptides had been trideutero-acetylated prior to trypsinisation
to facilitate discrimination from other peptides by mass spectrometry,
and the results were filtered so that only peptides that were trideutero-acetylated
and had a valid Mascot identification were used in subsequent analyses.
Of unique quantified peptides, 20–42% were trideutero-acetylated
(Supporting Information Table S5). This
process identified peptides starting at residues 1 or 2 of the protein
or immediately after removal of the signal sequence, which were excluded
from further analysis as they were considered uninformative for present
purposes. For each of the remaining peptides, the ratio of relative
abundance between the CAM and ATM samples was manually validated by
inspecting the spectra and calculating the area under the peaks of
the heavy and light isotopes.One of the paired samples was
further analyzed using N-terminal COFRADIC in addition to the SCX
enrichment step in an attempt to increase coverage of N-terminal peptides
by reducing sample complexity. Similar numbers of peptides were identified
by N-terminal COFRADIC and SCX-only enrichment, but over 2-fold more
of these identifications corresponded to neo-N-termini in the COFRADIC
data set (Supporting Information Table
S5). Approximately 50% of all unique proteins identified corresponded
to putative secreted proteins (Supporting Information Table S6). In the functional classification, “binding proteins”
and “ECM” proteins again predominated (Figure 1B). Furthermore, 41 proteins were identified that
were not seen in the first set of SILAC experiments, of which 24 were
known extracellular proteins.
CAM-Restricted Proteolytic
Events
In the data set as
a whole, neo-N-termini corresponding to putative proteolytic cleavage
sites were identified in a total of 94 unique proteins, of which collagens
alpha1(I) and alpha-2(I) and IGFBP-5 had the most cleavage sites (Supporting Information Table S7). In order to
refine cancer-related changes, we then sought those proteins for which
unique neo-N-termini were identified in CAM secretomes relative to
their ATM counterparts. Applying this criterion, we identified 13
proteins that exhibited CAM-restricted proteolytic cleavage (Table 1): strikingly, these included cleavages in the propeptide
domains of MMP-1 (interstitial collagenase) and MMP-3 (stromelysin-1)
(Table 1 and Supporting
Information Figure S2); moreover, N-terminal COFRADIC also
identified increased prodomain cleavage in MMP-2 (72 kDa type IV collagenase)
(Supporting Information Table S7).
Table 1
Neo-N-terminal Peptides of Extracellular
Proteins Unique to CAMs (i.e., Singletons), Excluding Those Representing
Removal of a Signal Sequencea
Uniprot
functional
classification
description
cleavage
site
start
end
peptide
patient 1
patient 2
patient 1
(N-terminal COFRADIC)
P07858
protease
Cathepsin B
Cathepsin B heavy chain
321
331
IESEVVAGIPR
CAM
singleton
P14209
binding protein
CD99 antigen
Extracelular
domain
89
115
SFSDADLADGVSGGEGKGGSDGGGSHR
CAM singleton
P12110
ECM
Collagen alpha-2(VI) chain
Nonhelical region
772
784
LYSIACDKPQQVR
CAM
singleton
P30443
receptor
HLA class I histocompatibility
antigen, A-1 alpha chain
Alpha-1 region
60
72
FDSDAASQKMEPR
CAM singleton
P01889
receptor
HLA class I histocompatibility
antigen, B-7 alpha chain
Alpha-1 region
51
59
YVDDTQFVR
CAM singleton
P10321
receptor
HLA class I histocompatibility
antigen, Cw-7 alpha chain
Tumor necrosis factor receptor
superfamily member 10D
TBFR-Cys 1 repeat
77
89
SLKEEECPAGSHR
CAM
singleton
Functional
classification and
cleavage sites were manually annotated using Uniprot database. Start
and end position number of the N-terminally labeled peptide are relative
to unprocessed forms of the protein.
Functional
classification and
cleavage sites were manually annotated using Uniprot database. Start
and end position number of the N-terminally labeled peptide are relative
to unprocessed forms of the protein.
In Vivo MMP Activity
To determine the in vivo relevance
of myofibroblasts for MMP activity in tumors, we made use of FMT imaging
of a MMP fluorescent substrate in a xenograft model consisting of
MKN45 gastric cancer cells alone or with humanCAMs. In matched tumors
of similar size generated with and without coadministration of CAMs,
the MMPSense substrate revealed significantly increased activity when
humanCAMs were present (Figure 2) .
Figure 2
Increased MMP
activity in vivo in xenografts containing CAMs. (A)
In BALB/c nu/nu mice, MMP activity revealed by FMT imaging of MMPSense
750 FAST is increased in xenografts of gastric cancer MKN45 cells
containing two different CAMs compared with MKN45 cells alone. (B)
Representative FMT images of mice with xenografts of MKN45 cells alone
(top row), MKN45 cells + CAM2 (middle row), and MKN45 cells + CAM1
(bottom row).
Increased MMP
activity in vivo in xenografts containing CAMs. (A)
In BALB/c nu/nu mice, MMP activity revealed by FMT imaging of MMPSense
750 FAST is increased in xenografts of gastric cancer MKN45 cells
containing two different CAMs compared with MKN45 cells alone. (B)
Representative FMT images of mice with xenografts of MKN45 cells alone
(top row), MKN45 cells + CAM2 (middle row), and MKN45 cells + CAM1
(bottom row).
Activation of MMP-1, -2,
and -3 in CAM Media
The substrate
used for in vivo imaging does not distinguish individual MMPs, and
subsequent studies therefore made use of in vitro techniques to assess
the relative contribution of MMPs1–3 in CAM media. Western
blots of MMP-1 revealed increased abundance of a 42 kDa form corresponding
to the active enzyme in CAM compared with ATM media; in contrast,
in cell extracts of the two cell types there was similar abundance
of the precursor proteins of 57 and 52 kDa (Figure 3A). For MMP-2, we identified a precursor form of 72 kD in
cells and media of both CAMs and ATMs, again in similar abundance
in the two cell types. When blots of media were overexposed it was
possible to identify a minor band of 63 kDa corresponding to the active
enzyme in CAM but not ATM media (Figure 3B).
Finally, for MMP-3 we identified precursor proteins of 59 and 54 kDa
in cells and media of both CAMs and ATMs; a band of 45 kDa corresponding
to the active enzyme was found in media, and the abundance was greater
in CAMs compared with ATMs (Figure 3C).
Figure 3
Western blots show the active forms of MMP-1, MMP-2, and
MMP-3
in CAM media. (A) Representative Western blots of MMP-1 in CAM and
ATM media (left) and cell extracts (right). (B) Representative Western
blots of MMP-2 in CAM and ATM media (left) and cell extracts (right).
(C) Representative Western blots of MMP-3 in CAM and ATM media at
two different exposures (left, center) and cell extracts (right).
Western blots show the active forms of MMP-1, MMP-2, and
MMP-3
in CAM media. (A) Representative Western blots of MMP-1 in CAM and
ATM media (left) and cell extracts (right). (B) Representative Western
blots of MMP-2 in CAM and ATM media (left) and cell extracts (right).
(C) Representative Western blots of MMP-3 in CAM and ATM media at
two different exposures (left, center) and cell extracts (right).To establish the functional significance
of these results, we then
studied MMP enzyme activity in CAM and ATM media. Using a fluorogenic
substrate for MMP-1, we found significantly greater activity in CAM
compared with the corresponding ATM media (Figure 4A). Similarly, substrates selective for MMP-2, or for MMP-2/MMP-9
(Figure 4A), revealed greater activity in CAM
than ATM media, and the same pattern was observed with two different
MMP-3 substrates (Figure 4A).
Figure 4
Increased MMP-1, MMP-2,
and MMP-3 activity in CAM media. (A) MMP-1,
MMP-2, and MMP-3 enzyme activities (using the selective substrates
indicated in brackets) are increased in CAM compared with ATM media;
left, assays based on Trp fluorescence and right on FRET. (B) CAM-CM
media stimulates AGS cell migration and is inhibited by neutralizing
antibody to MMP-1 (2.5 μg mL–1) or inhibitors
(see text) of MMP-2 (6 μM) and MMP-3 (3 μM). Horizontal
bars, p < 0.05.
Increased MMP-1, MMP-2,
and MMP-3 activity in CAM media. (A) MMP-1,
MMP-2, and MMP-3 enzyme activities (using the selective substrates
indicated in brackets) are increased in CAM compared with ATM media;
left, assays based on Trp fluorescence and right on FRET. (B) CAM-CM
media stimulates AGS cell migration and is inhibited by neutralizing
antibody to MMP-1 (2.5 μg mL–1) or inhibitors
(see text) of MMP-2 (6 μM) and MMP-3 (3 μM). Horizontal
bars, p < 0.05.
Myofibroblast MMPs and Cancer Cell Migration
There
is MMP-stimulation of migration of AGS gastric cancer cells in Boyden
chambers,[33] and this was then used to test
the functional significance of the changes in MMP abundance and activity
in CAM media. Conditioned media (CM) from both CAMs and ATMs stimulated
AGS cell migration, but the response to the former was significantly
greater than to the latter (CAM-CM: 207 ± 11 cells per field;
ATM-CM: 145 ± 11, p < 0.05; control media:
15 ± 2). Neutralizing antibody to MMP-1 (2.5 μg mL–1) significantly suppressed AGS cell migration in response
to CAM-CM (Figure 4B); similarly, previously
characterized selective inhibitors of MMP-2 or MMP-3 at concentrations
approximately 3-fold above their reported K in each case (6 and 3 μM, respectively)[37,38] also inhibited AGS cell migration in response to CAM-CM, indicating
that active MMP-2 and MMP-3 released from myobfibroblasts play a role
in cancer cell migration (Figure 4B).
Discussion
The tumor microenvironment reflects the secretomes of both cancer
and stromal cells including myofibroblasts, fibroblasts, pericytes,
endothelial cells, inflammatory and immune cells. Crucially, interactions
between different secretomes influence cancer cell migration, invasion
and metastasis by multiple mechanisms including the activation or
inhibition of proteases with consequences for the proteolytic cleavage
of ECM proteins, growth factors, cytokines and chemokines.[15] The secretomes of cancer cells have attracted
increasing attention in recent years,[4−9] but little is yet known of stromal cell secretomes. Differences
in the secretomes of myofibroblasts recovered from gastric cancers
and those recovered from adjacent tissue have been reported recently
using iTRAQ.[19] We have now used SILAC and
COFRADIC to determine the extent to which proteolysis influenced myofibroblast
secretomes in gastric cancer. Our study identified neo-N-termini derived
from 94 proteins in CAM secretomes including evidence of cleavage
of the prodomains of MMP-1, -2, and -3 leading to increased extracellular
proteolytic activity. The data indicate that a distinguishing feature
of cancer myofibroblasts is increased expression and increased activation
of these MMPs in an autonomous manner in gastric cancer with the potential
for promoting cancer progression.The identification of secreted
biomarkers by cancer cells has been
a focus of interest for several generations and has been stimulated
more recently by the development and refinement of proteomic methods
and the prospect of rigorously defining the cancer secretome.[39] Extracellular proteolysis presents additional
challenges in defining the relevant secretomes; it is important not
least because it underlies multiple mechanisms implicated in cancer
progression including angiogenesis, tumor cell migration and invasion.
A number of proteomic methods have recently been used to identify
neo-N-termini generated in complex samples including COFRADIC[26] and terminal amine isotopic labeling of substrates
(TAILS),[40] which has been applied to the
identification of substrates of MMP-2 and MMP-9 in fibroblast secretomes.[41,42] Since SILAC has previously been used successfully for secretome
studies in a range of cell types including stromal cells from other
tissues,[43,44] and since COFRADIC coupled with SILAC labeling
is considered to offer a rigorous approach to N-terminomics,[26,42] these methods were selected for the present studies.The present
study identified proteins in media released by the
endoplasmic reticulum–Golgi secretory pathway; however, as
commonly found in secretome studies, there were also proteins likely
to be released by other mechanisms including cytoplasmic proteins
liberated through cell death, shedding of membrane proteins and release
of exosomes. Previous studies have identified similar rates of apoptosis
in CAMs and ATMs[19] suggesting that differential
cell death is unlikely to account for differences in the CAM and ATM
secretomes. For proteins released through classical secretory mechanisms,
we were able to identify many previously reported in the secretomes
of fibroblasts and of the stem cells that may give rise to them, including
extracellular matrix proteins, IGFBPs, MMPs and TIMPs.[12,44] The differences between CAM and ATM secretomes may reflect alterations
in gene expression, post-translational processing, relative rates
of secretion and in proteolysis following release. We have now defined
the latter though identification of neo-N-termini in CAMs compared
with their corresponding ATMs. For example, we found multiple neo-N-termini
in collagens alpha-2 (I) and alpha-1(I), and IGFBP5, as well as at
limited sites in 91 other proteins. In a small subset of proteins
we identified neo-N-termini that were unique to CAMs, and these included
six neo-N-termini in the prodomains of MMP-1 and MMP-3, suggesting
that activation of these MMPs might be functionally important in CAMs.It is well established that MMP activity is increased in tumors
and promotes cancer cell migration and invasion;[13] the present in vivo imaging data indicate that CAMs contribute
to this increased activity in an animal model. It is likely that MMPs
have multiple roles in different tumor functions accounting for the
fact that MMP inhibitors have not yet led to successful anticancer
therapies.[15] The present demonstration
of increased expression and activation of MMP-1, MMP-2 and MMP-3 in
CAM secretomes nevertheless suggests a novel dimension to the role
of these enzymes. In vivo there may be activation of myofibroblast
MMPs by epithelial or cancer-derived proteases, e.g., MMP-7.[33] Importantly, however, the present data indicate
that increased MMP activity in CAM media occurs independently of a
cancer or epithelial cell stimulus. This is nevertheless relevant
to cancer cell function not least because MMP-1, MMP-2, and MMP-3
stimulate cancer cell migration and make a substantial contribution
to the chemotactic properties of CAM conditioned media. The prodomain
cleavages of MMP-1, -2, and -3 identified here are all on the N-terminal
side of the conserved cysteine switch sequence, and we think it is
possible that these facilitate activation by exposing the site for
autolysis much in the same way that trypsin activates MMPs.[45] However, the precise protease(s) responsible
for CAM-autonomous prodomain cleavages is presently unclear and should
now be investigated. In this context it is worth noting that there
was decreased abundance of protease inhibitors, including TIMPs-1,
-2, and -3 in one patient (Supporting Information Table S4), which may contribute to increased protease activity.The present study using SILAC–COFRADIC has provided the
most detailed analysis of gastric cancer myofibroblast secretomes
to date. It extends previous studies,[19] but in addition, it defines differences in the extracellular degradomes
of CAMs and ATMs. At least some of the differences between CAFs or
CAMs and their normal tissue counterparts are thought to reflect interactions
that occur in the presence of cancer cells.[3] The present data indicate that selective MMP-activation occurs in
the CAM secretome even when these cells are cultured in the absence
of cancer cells. This property reflects a cell-autonomous mechanism
by which CAMs might contribute to a cancer-promoting microenvironment.
The possibility of targeting anticancer therapies to stromal cells
has emerged recently,[46] and the present
data indicate how these could be refined to include the stromal degradome.
Authors: Kris Gevaert; Jozef Van Damme; Marc Goethals; Grégoire R Thomas; Bart Hoorelbeke; Hans Demol; Lennart Martens; Magda Puype; An Staes; Joël Vandekerckhove Journal: Mol Cell Proteomics Date: 2002-11 Impact factor: 5.911
Authors: An Staes; Francis Impens; Petra Van Damme; Bart Ruttens; Marc Goethals; Hans Demol; Evy Timmerman; Joël Vandekerckhove; Kris Gevaert Journal: Nat Protoc Date: 2011-07-14 Impact factor: 13.491
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Authors: Astrid De Boeck; An Hendrix; Dawn Maynard; Mieke Van Bockstal; Annick Daniëls; Patrick Pauwels; Christian Gespach; Marc Bracke; Olivier De Wever Journal: Proteomics Date: 2013-01-06 Impact factor: 3.984
Authors: J Dinesh Kumar; Islay Steele; Andrew R Moore; Senthil V Murugesan; Zoltan Rakonczay; Viktoria Venglovecz; D Mark Pritchard; Rodney Dimaline; Laszlo Tiszlavicz; Andrea Varro; Graham J Dockray Journal: Am J Physiol Gastrointest Liver Physiol Date: 2015-05-14 Impact factor: 4.052
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