Oncogene (2006) 25, 7650–7661
& 2006 Nature Publishing Group All rights reserved 0950-9232/06 $30.00
www.nature.com/onc
ONCOGENOMICS
Proteomic identification of the wt-p53-regulated tumor cell secretome
FW Khwaja1,2, P Svoboda3, M Reed3, J Pohl3 , B Pyrzynska1,2 and EG Van Meir1,2
1
ONCOGENOMICS
Laboratory of Molecular Neuro-Oncology, Department of Neurosurgery, Winship Cancer Institute, Emory University School of
Medicine, Atlanta, GA, USA; 2Department of Hematology/Oncology, Winship Cancer Institute, Emory University School of
Medicine, Atlanta, GA, USA and 3Emory University Microchemical and Proteomics Facility, Emory University School of Medicine,
Atlanta, GA, USA
Tumor–stroma interactions play a major role in tumor
development, maintenance and progression. Yet little is
known on how the genetic alterations that underlie cell
transformation elicit cell extrinsic changes modulating
heterotypic cell interactions. We hypothesized that these
events involve a modification in the complement of
secreted proteins by the cell, acting as mediators of
intercellular communication. To test this hypothesis, we
examined the role of wt-p53, a major tumor suppressor, on
the tumor microenvironment through its regulation of
secreted factors. Using a combination of 2-DE and cICAT
proteomic techniques, we found a total of 111 secreted
proteins, 39 of which showed enhanced and 21 inhibited
secretion in response to wt-p53 expression. The majority
of these were not direct targets of p53 transcription factor
activity, suggesting a novel role for wt-p53 in the control
of intracellular protein trafficking and/or secreted protein
stability. Evidence for p53-controlled post-translational
modifications on nine secreted proteins was also found.
These findings will enhance our understanding of wt-p53
modulated interactions of the tumor with its environment.
Oncogene (2006) 25, 7650–7661. doi:10.1038/sj.onc.1209969;
published online 9 October 2006
Keywords: p53; proteomics; secretion; glioma; brain cancer; two-dimensional electrophoresis
Introduction
Traditionally, cancer formation is thought of as a cell
autonomous process driven by mutations in genes that
increase cell proliferation and survival, where a tumor is
primarily composed of transformed cells. Increasing
evidence suggests that the tumor microenvironment also
Correspondence: Dr EG Van Meir, Laboratory of Molecular NeuroOncology, Department of Neurosurgery, Winship Cancer Institute,
Emory University, 1365C Clifton Rd, NE, C5078, Atlanta, GA 30322,
USA.
E-mail: [email protected]
FWK and EGVM designed and interpreted experiments and wrote the
manuscript. FWK performed experiments with the help of PS, MR
and JP for the MS analyses. BP performed the microarrays and
Northern blot. All authors read the manuscript.
Received 10 May 2006; revised 26 July 2006; accepted 27 July 2006;
published online 9 October 2006
contributes to the neoplasm (Hanahan and Weinberg,
2000) and that the tumor–stroma interactions are
an active process initiated by transforming events
(Bhowmick and Moses, 2005; Taieb et al., 2006).
Consequently, we need to understand these tumor–
stroma interactions to develop more effective therapies.
We hypothesized that loss of tumor-suppressor function
during cell transformation may have cell extrinsic effects
through the modulation of secreted factors. We focused
on p53, as it is frequently mutated in cancer and is
a transcription factor that can directly control the
synthesis of a large number of proteins (Harris and
Levine, 2005).
Tumor-suppressive p53 is best known for its role in
maintaining genomic integrity by controlling cell cycle
progression and cell survival in response to DNA
damage (Steele and Lane, 2005). Nevertheless, some
studies have suggested that p53 can influence the
tumor microenvironment through suppression of angiogenesis and tumor invasion (Van Meir et al., 1994;
Zigrino et al., 2005). These processes might be influenced by p53 through two mechanisms; the induced
secretion of inhibitory factors (Van Meir et al., 1994) or
the negative regulation of secreted protumorigenic
proteins (Chiarugi et al., 1998; Sun et al., 2000). While
p53-regulated intracellular proteins are well studied, the
extracellular ones have not been systematically analysed.
Identification of the p53 controlled secreted proteins will
clarify how p53 loss in tumors may lead to the altered
regulation and response of the tumor cells to their
environment.
To examine the regulation of p53 on the cell’s
secretome we identified secreted proteins by p53-null
tumor cells in the presence or absence of reconstituted
wt-p53 expression. This is the first comprehensive study
of how p53 plays a role in the process of transformation
through its manipulation of the tumor microenvironment. Our studies identified 50 new secreted proteins
controlled by p53. These proteins have known roles in
cancer-related processes that are dependent on heterotypic cell–cell communication such as immune response,
angiogenesis, extracellular matrix (ECM) interaction,
and cell survival. Many of these proteins are secreted
through receptor-mediated nonclassical secretory pathways. These results are important to advance our
understanding on how tumor–stroma interactions contribute to cancer progression.
wt-p53-regulated secreted proteins in glioma cells
FW Khwaja et al
7651
expression using two complementary proteomic techniques: two-dimensional gel electrophoresis (2-DE) and
cleavable isotope-coded affinity tag (cICAT).
Results
To identify p53-regulated secreted proteins involved in
the cell–cell communication events important for human
cell transformation, we selected the LN-Z308 cell line as
it was derived from a malignant human glioma that lost
both p53 alleles in vivo by well-characterized genetic
events suggesting selective pressure for their loss
(Albertoni et al., 1998). Reactivating wt-p53 function
in these cells would revert or restore the release of p53regulated secreted proteins and allow their identification
in the conditioned media (CM). To this purpose, we
used isogenic clones of LN-Z308 with tetracyclineinducible (2024 p53 tet-on) (Albertoni et al., 2002) and
repressable (WT11 p53 tet off) (Van Meir et al., 1994)
wt-p53 expression (Figure 1). These cells undergo
growth arrest but not apoptosis in response to p53
(Van Meir et al., 1995) and show induction of the cell
cycle inhibitor p21 upon p53 induction (Figure 1a).
Using this system, we generated differential profiles of
the cell lines’ secretome with and without wt-p53
LNZ308
a
-
2-DE of the tumor cell secretome
The secreted proteins were separated by 2-DE analysis
using nonlinear pH range of 3–10 and linear range of
4–7 in triplicates to ensure reproducibility (Görg et al.,
2004). The proteins were visualized by silver staining
and analysed using ImageMaster software. As a further
precaution against artefacts, we profiled both 2024 and
WT11 clones and only proteins found secreted in both
were retained.
The protein spots were next excised from the gel,
subjected to in-gel digestion with trypsin, and identified using matrix-assisted laser desorption/ionization
time-of-flight (MALDI-TOF/TOF) MS/MS analysis.
We found on average >150 spots on each gel
representing 68 individual proteins (Figure 1b; Tables
1–3). A semiquantitative analysis of this differential
c
2024
- +
- +
WT11
+ - Dox
- + wtp53
2024+wt p53
2024
p53
p21
Actin
b MW
2024 - wt p53
2024 + wt p53
110
X-linked factor
75
MMP-2
α-catenin
Saposin
50
ADAM-10
PG-M
PEDF
PAI-1
SPARC
KIAA0548
BCL6 repressor
KIAA0828MIF
PG-M
NF1
CYR61
33
Gal-1
Gal-1
Transgelin 2
VEGF
OPN
Gal-3
FGF-4
RTVP-1
25
α-2HS
IGFBP6
β -2M
15
TIMP-3
BDNF
14-3-3
10
Thioredoxin
MT2A
TPM4-ALK oncoprotein
pH 4
TGF-β
pH 9 pH 4
NTF1
pH 9
Figure 1 Representative 2-DE gels of secreted proteins from glioma cells with inducible wt-p53 expression. (a) Two p53-null clones (WT11
and 2024) with dox-inducible wt-p53 expression were used (See Materials and methods). Western blot shows wt-p53 induction, and
downstream activation of the p21 cell cycle inhibitor, 48 h postinduction in serum-free media. (b) Secreted proteins found in the CM from
uninduced (left) and wt-p53 induced (right) 2024 cells were analysed by 2-DE analysis using IEF strips pH3-10 NL and 12.5% SDS–Page.
Protein spots circled indicate proteins with enhanced secretion (right) or reduced (left) in response to wt-p53. Samples were run in triplicate
and location of representative proteins is indicated. Black arrow shows p53-induced post-translational modification of Gal-1. White arrow
shows the location of KIAA0828. (c) Enlargement showing acidic shift of Gal 1 in CM from wt p53 expressing cells (arrows).
Oncogene
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Oncogene
Table 1 Secreted proteins with enhanced accumulation in CM upon p53 induction
2024
Access. no.
MW
pI
mRNA
Galectin-3
gi:4504983
26.19
8.58
1.05
Lysyl oxidase-like protein 2
b-Galactosidase binding
lectin
Nm23 protein
gi:4959425
71.10
6.32
1.05
gi:12804557
14.72
5.33
gi:35068
20.41
7.06
2-DE
H:L
s.d.
H:L
s.d.
Functional category
Mode of secretion
Post-translational
requirement
C
1.60
0.12
1.53
0.10
1.65
0.07
1.65
0.00
Vesicle-mediated;
ectocytosis
Classical
Glycosylation/
phosphorylation
Glycosylation
1.36
0.18
1.27
0.12
0.00
Vesicle-mediated;
ectocytosis
Unknown nonclassical pathway
Unknown nonclassical pathway
Vesicle-mediated;
ectocytosis
Glycosylation
2.50
Adhesion and matrix
interactions; apoptosis
Adhesion and matrix
interactions
Cell proliferation regulation
Cell proliferation/differentiation
Cell proliferation/differentiation
DNA binding
C
1.04
X-linked brain specific
factor
BCL6 corepressor
gi:21322252
99.19
6.00
gi:21040336
78.85
8.28
Dickkopf-1*
gi:6049604
28.67
8.80
Growth arrest-specific 6
Collagen type XI alpha1
Proteoglycan PG-M
(V3)
Galectin-1
gi:7512417
gi:6165881
43.14
176.65
5.26
5.24
1.14
1.01
gi:1008913
74.25
7.43
1.34
gi:12804557
14.72
5.33
1.05
Connective tissue
growth factor
CD83 antigen; activated
lymphocytes
KIAA0548
gi:4503123
39.07
8.36
gi:4757946
23.04
gi:3043620
2.08
2.50
0.12
0.00
1.72
2.50
0.11
0.00
ECM component/signaling
ECM component
ECM component
C
2.20
0.00
2.50
0.00
ECM component
C
1.36
0.18
1.27
0.12
1.15
1.87
0.54
1.66
0.14
8.45
1.11
1.94
0.46
1.27
0.00
Cell proliferation regulation
Cell proliferation/differentiation
Immunity and defense
50.08
7.61
1.17
C
2.28
0.04
2.50
0.00
Immunity and defense
gi:179318
gi:187141
13.73
21.34
6.06
9.37
1.12
1.08
C
C
1.25
2.44
0.01
0.00
1.46
2.36
0.19
0.00
Immunity and defense
Immunity and defense
gi:312334
124.76
7.73
1.07
C
1.53
0.04
1.43
0.14
Immunity and defense
Unknown nonclassical pathway
Classical
Classical
Non-classical; receptor-mediated
Vesicle-mediated;
ectocytosis
Classical
Phosphorylation
Phosphorylation
Glycosylation
Phosphorylation
Glycosylation
Glycosylation
Glycosylation
Glycosylation/
phosphorylation
Glycosylation
b-2M
Myeloid leukemia-inhibitory factor
Macrophage migration
inhibitory factor
2-Phosphopyruvate-hydratase-enolase
Saposin precursor
gi:119339
47.17
7.01
1.06
C
1.28
0.06
1.27
0.00
Metabolic enzyme
gi:134218
58.11
5.06
1.18
C
1.43
0.03
1.39
0.00
Metabolism
Autotaxin-t
gi:1160616
99.02
7.14
1.14
1.43
0.05
1.26
0.00
Metabolism
Epididymal secretory E1
precursor
u-Type plasminogen activator
gi:48429027
16.57
7.57
1.71
0.28
2.04
0.10
Protease
Non-classical; receptor-mediated
Unknown nonclassical pathway
Classical
Vesicle-mediated;
ectocytosis
Vesicle-mediated;
ectocytosis
Vesicle-mediated;
ectocytosis
Unknown nonclassical pathway
Non-classical; receptor-mediated
Ectocytosis
gi:137112
48.53
87.80
1.58
0.11
1.40
0.11
Protease
Classical
Glycosylation
PAI-1*
gi:10835159
45.59
6.68
Serine-type protease
Glycosylation
TIMP-3
gi:490094
23.17
8.46
Vesicle-mediated;
exocytosis
Classical
1.09
1.35
2.01
0.16
1.55
0.17
Protease inhibitor
Gycosylation
Glycosylation/
phosphorylation
Glycosylation
Glycosylation
Glycosylation
Unknown
Glycosylation
Glycosylation
Phosphorylation
Glycosylatoin/
phosphorylation
wt-p53-regulated secreted proteins in glioma cells
FW Khwaja et al
Protein name
WT11
Table 1 (continued )
2024
Protein name
Access. no.
MW
pI
mRNA
Glioma pathogenesis-related protein
Palmitoyl-hydrolase
precursor
Mono-ADP-ribosyltransferase
Mitogen-activated protein kinase
a2-HS glycoprotein/Fetuin-A
Cytosolic thyroid hormone-bp
NF1 protein isoform
gi:5803151
30.34
8.80
gi:2135879
34.18
gi:47087626
2-DE
WT11
H:L
s.d.
H:L
s.d.
Functional category
Mode of secretion
Post-translational
requirement
1.32
2.50
0.00
2.50
0.00
Protease inhibitor
Classical
Glycosylation
6.07
1.10
2.75
0.00
2.50
0.00
Protein synthesis
Classical
Glycosylation
5.56
4.34
1.07
1.49
0.04
1.43
0.00
Protein synthesis
Unknown
gi:66932916
41.39
6.50
1.18
4.02
0.67
2.96
0.28
Signaling
gi:7106502
39.32
5.43
1.47
0.10
1.55
0.05
Signaling
Unknown nonclassical pathway
Unknown nonclassical pathway
Classical
gi:338827
58.00
7.95
1.22
2.50
0.00
gi:219940
62.30
8.04
1.09
2.82
0.00
2.58
0.00
Signaling
Importin-7
gi:5453998
119.52
4.70
1.09
1.42
0.05
1.37
0.26
Signaling
Osteopontin*
gi:189405
33.84
4.40
b-5-Tubulin
a-Catenin
gi:21104420
gi:433411
49.67
100.07
4.78
5.95
1.05
1.08
C
C
1.55
4.02
0.25
0.00
1.59
3.55
0.09
0.31
Structure and motility
Structure and motility
BDNF
HP1Hs-g
gi:987872
gi:1773227
27.76
19.72
8.77
5.03
1.01
C
2.02
1.77
0.16
0.24
1.57
1.70
0.00
0.08
Survival
Unknown
KIAA0828
gi:24308043
66.72
7.13
1.12
1.41
0.00
1.54
0.00
Unknown
Unnamed protein product
gi:31873592
35.25
6.51
1.89
0.22
1.65
0.01
Unknown
Signaling
Glycosylation
Phosphorylation
Glycosylation/
phosphorylation
Unknown
Glycosylation/
phosphorylation
Phosphorylation
Glycosylation/
phosphorylation
Glycosylation
Unknown
Glycosylaton
Unknown
Proteins with enhanced levels in the CM in response to wt-p53 are represented with their GenBank accession number (Access. no.), molecular weight (MW; kilodaltons), isoelectric point (pI),
functional category, mode of secretion and post-translational requirements for secretion. Changes in mRNA levels of the corresponding proteins under p53-induction are indicated (mRNA). Listed
ratios are an average of three separate experiments using 2024 cells, after 48 h induction of p53 in serum conditions. Ratios of >1.5 or o0.5 were considered significantly differentially expressed. As
positive controls, wt-p53 and p21 mRNA levels were on average increased 2.81- and 5.02-fold respectively in these microarray studies. The cICAT (H:L) ratio refers to the relative secretion of
proteins under wt-p53 (labeled with heavy (H) reagent) compared to p53-null (labeled with light (L) reagent) conditions, that is, proteins upregulated by wt-p53 have a ratio >1 and those
downregulated a ratio o1. The ratios given are an average of three separate experiments for each cell line (2024 and WT11). Only proteins with ProtScore >1.0 (>85% confidence) were considered.
The average ratios are followed by the standard deviation (s.d.). The 2-DE column indicates whether the proteins were also found by 2-DE analyses (combined results from 2024 and WT11 cells) and
if their secretion levels were found concordant (C) with cICAT. Proteins in bold and with an * are previously known targets of p53. Proteins in italics (13 total) were found upregulated by both
analyses (see Figure 3b). Empty space indicates that proteins were not found in that particular experiment or that the gene was not represented on the microarray chip.
wt-p53-regulated secreted proteins in glioma cells
FW Khwaja et al
Structure and support
Unknown nonclassical pathway
Unknown nonclassical pathway
Unknown nonclassical pathway
Vesicle-mediated;
exocytosis
Classical
Vesicle-mediated;
exocytosis
Classical
Unknown nonclassical pathway
Unknown nonclassical pathway
Undetermined
Unknown
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Oncogene
Table 2
Secreted proteins showing reduced accumulation in the CM upon p53-induction
Protein name
Access. no.
MW
pI
ADAM-10*
gi:4557251
84.14
8.04
PEDF*
CYR61 protein
VEGF*
Transforming growth
factor b*
FGF-4
gi:189778
gi:12584866
gi:181971
gi:339558
46.33
41.99
22.31
12.79
5.84
8.64
7.88
8.59
gi:4503701
22.05
9.73
RTVP-1*
gi:27735198
30.37
8.80
TPM4-ALK fusion
oncoprotein
Granulin
gi:10441386
27.53
4.77
gi:183613
63.57
6.50
1.18
Interleukin 8
gi:33959
10.90
9.10
1.16
Attractin
gi:3676347
175.00
4.71
1.16
ANP32A protein
Aldolase A
MMP-2*
Helicase-MOI
SPARC/Osteonectin*
A Chain A, Bm-40
Insulin-like growth
factor bp6
Metallothionein II D
Transgelin 2
gi:76825059
gi:34577112
gi:11342666
gi:5019620
gi:4507171
gi:2624793
gi:183894
14.79
39.42
73.88
218.81
34.63
27.01
25.19
5.27
8.30
5.26
5.47
4.73
5.53
8.15
1.21
1.37
gi:223529
gi:4507357
6.04
22.39
8.23
8.41
Legend as in Table 1.
mRNA
2-DE
1.13
C
C
1.18
C
1.08
1.12
1.05
H:L
0.38
0.69
s. d.
WT11
H:L
0.00
0.10
0.56
0.65
0.75
0.00
s.d.
0.00
0.00
Functional category
Mode of secretion
Post-translational requirement
Adhesion
Classical
Glycosylation
Angiogenic
Angiogenic
Angiogenic
Cell proliferation/
angiogenic
Cell growth/proliferation/
angiogenic
Cell proliferation/
differntiation
Cell proliferation
Classical
Classical
Classical
Classical
Glycosylation
Unknown
Glycosylation
Glycosylation
Classical
Glycosylation
Classical
Glycosylation/phosphorylation
Non-classical; receptor
mediated
Unknown non-classical
method
Classical
Glycosylation
0.86
0.21
0.80
0.07
Cell proliferation
C
0.63
0.02
0.62
0.00
C
0.39
0.16
0.27
0.09
Immunity and defense/
angiogenic
Immunity and defense
0.44
0.18
0.33
0.18
0.78
0.75
0.01
0.05
0.23
0.79
0.76
0.78
0.00
0.03
0.00
0.05
0.25
0.78
0.73
0.74
0.00
0.06
0.00
0.08
C
C
C
Immunity and defense
Metabolism
Protease
RNA modification
Structure and motility
Structure and motility
Survival
Unknown
Unknown
Unknown non-classical
pathway
Undetermined
Undetermined
Classical
Classical
Classical
Classical
Unknown non-classical
method
Classical
Unknown non-classical
method
Glycosylation
Unknwon
Unknown
Unknown
Unknown
Glycosylation/phosphorylation
Glycosylation/phosphorylation
Glycosylation
None
Unknown
Glycosylation
None
wt-p53-regulated secreted proteins in glioma cells
FW Khwaja et al
2024
wt-p53-regulated secreted proteins in glioma cells
FW Khwaja et al
7655
Table 3
Secreted proteins unchanged by wt-p53 or unclear as found by 2-DE and cICAT analyses
2024
Protein name
Access. no.
Thrombospondin-1*
Endothelin 1
MAC25
GDNF family receptor a 1 isoform
Neurotrophin
Stage-specific S antigen homolog
Hyp. Zinc-finger protein KIAA0296
Ah receptor-interacting protein
Fibulin 1A
Prion protein
Procollagen C-endopeptidase enhancer
Phosphodiesterase I a
Follistatin-like 1
Immunoglobulin heavy chain variable
MAC-2 binding protein precursor
T cell receptor a chain
Immunoglobulin kappa chain variable
Glycosylase I
T-cell receptor delta chain
Isomerase, triosephosphate
HSP 70/71; isoform2
Rnase H
Cathepsin B preproprotein
heterogeneous nuclear ribonucleoprotein
RNA binding protein regulatory subunit
Ribosomal protein S12
CAMKII
Calmodulin related protein-A11
Fibrillin-2 pre
14-3-3 protein tau
Cofilin, non-muscle isoform
Filamin
Vimentin
Myosin light chain 3
Stanniocalcin 2 precursor
Tyrosine 3-monooxygenase
Peptidylprolyl isomerase A
YWHAZ protein
Insulin-like growth factor bp5 precursor
Thioredoxin/ NKEF-B
Amyloid A4 protein
Apolipoprotein-E
Human serum albumin
GDI-a
CDw44 antigen precursor
Unnamed protein product; phosphatase
Similar to HSPC280
Hypothetical FGF-like protein
KIAA0012
MGC:71022
Unnamed protein product; zinc-finger
gi:40317626
gi:556203
gi:307151
gi:20141405
gi:4505469
gi:51466832
gi:40788207
gi:6226814
gi:19743813
gi:220016
gi:4505643
gi:662290
gi:2498390
gi:553428
gi:41150551
gi:416065
gi:185974
gi:62821794
gi:540457
gi:223374
gi:24234686
gi:52000844
gi:22538437
gi:14165439
gi:14198257
gi:14277700
gi:25952118
gi:47458820
gi:66346695
gi:112690
gi:5031635
gi:8100574
gi:62414289
gi:4557777
gi:4507267
gi:136574
gi:10863927
gi:68085909]
gi:184820
gi:50592994
gi:28721
gi:671882
gi:178344
gi:4757768
gi:180197
gi:19701027
gi:6841210
gi:4557679
gi:40789057
gi:38303909
gi:21751981
MW
pI
129.38 4.71
24.43 9.52
28.75 8.40
51.46 8.30
29.35 9.34
68.80 11.82
201.84 7.05
37.66 6.04
138.97 5.41
26.82 9.04
47.95 7.41
99.04 7.49
34.99 5.39
16.16 9.52
52.47 8.91
11.39 6.10
12.50 5.14
66.22 8.31
12.98 5.50
26.63 7.09
53.52 5.62
91.95 9.21
37.82 5.88
51.03 5.19
19.89 6.33
14.51 6.81
54.09 6.61
83.13 6.70
314.77 4.73
27.76 4.68
18.52 8.22
278.20 5.49
53.65 5.06
21.93 5.03
33.25 6.93
58.52 5.90
18.01 7.68
27.75 4.73
30.57 8.58
11.74 4.82
84.82 4.71
11.84 6.57
69.37 5.92
23.21 5.03
39.56 5.13
77.58 5.05
15.80 7.91
133.10 5.71
90.55 6.64
10.83 4.69
82.65 6.78
WT11
mRNA 2-DE H:L s.d. H:L s.d. Functional category
1.13
1.06
1.15
1.05
1.18
1.19
1.23
1.11
1.25
1.06
1.03
C
C
1.05
1.01
1.03
1.63
C
C
U
1.09
1.08
1.46
1.04
1.07
C
U
C
C
C
1.03
1.04
1.11
U
C
C
1.21
1.08
1.08
1.18
C
U
1.06
1.11
1.07
1.15
1.06
1.06
1.21
1.16
1.02
1.18
1.25
1.08
1.28
C
U
C
U
C
U
C
C
U
U
1.22
U
U
0.14
1.18
1.22
1.11
1.45
0.98
0.86
0.94
1.06
1.00
1.00
1.02
0.98
0.75
1.00
1.37
1.01
0.83
0.80
0.93
0.00
0.87
1.06
1.07
1.04
1.24
1.31
1.92
1.64
1.12
0.85
1.15
0.90
1.15
1.31
1.23
1.69
0.04 1.09 0.10 Anti-angiogenic
0.00 0.90 0.11 Angiogenic
0.01 1.02 0.00 Cell proliferation regulation
0.00
Cell differentiation
Differentiation and survival
0.06 1.12 0.03 DNA-binding protein
0.02 0.91 0.03 DNA-binding protein
0.34 1.43 0.07 DNA binding protein
ECM component; cell signaling
0.20 0.96 0.00 ECM protein
0.02 1.45 0.08 Enzyme
0.00 1.09 0.08 Enzyme
0.02 1.03 0.03 Immunity and defense
0.00 1.45 0.09 Immunity and defense
0.16 1.02 0.06 Immunity and defense
0.00 1.10 0.15 Immunity and defense
0.00 0.94 0.05 Immunity and defense
0.02 1.04 0.04 Metabolism
0.00 1.00 0.00 Immunity and defense
0.05 1.09 0.10 Metabolic glycolytic enzyme
0.10 1.04 0.00 Oxidative damage repair enzyme
RNA degradation
0.05 1.00 0.06 Protease
0.14 0.78 0.09 Protein synthesis
0.00
Protein synthesis
0.00
Protein synthesis
Kinase inhibitor
0.06 1.12 0.03 Protein kinase
0.05 0.93 0.07 Structure and motility
0.12 0.87 0.00 Structure and motility
0.02 0.97 0.05 Structure and motility
0.00 2.03 0.16 Structure and motility
0.04 0.96 0.00 Structure and motility
0.08 1.13 0.01 Structure and motility
0.05 1.10 0.11 Signaling
0.13 1.12 0.04 Signaling
0.02 1.21 0.00 Signaling
0.21 1.24 0.00 Signaling
0.10 1.30 0.09 Survival; immunity and defense
0.37 1.63 0.00 Survival/immunity
0.07 1.06 0.08 Transport
Transport
Transport
Vesicle-mediated transport
0.16 0.82 0.05 Adhesion
0.06 1.31 0.02 Unknown
0.09 0.97 0.00 Unknown
0.04 1.33 0.17 Unknown
0.21 1.17 0.00 Unknown
0.00 0.99 0.00 Unknown
0.08 0.98 0.00 Unknown
Legend as in Table 1. Proteins with secretion levels found concordant (C) or unclear (U) between the two methods are indicated.
expression was performed by comparing spot intensity
and volume using ImageMaster (Figure 2). The levels of
34 proteins in the CM were found to be largely
invariable regardless of p53 expression, whereas 32
individual proteins showed differential expression levels
in the CM in response to p53 (Tables 1–3). Among the
differentially expressed proteins, 18 had increased levels
and 16 decreased levels in the CM in response to wt-p53
expression in the cells (Figure 3b). The 68 secreted
proteins identified in the 2-DE screen belonged to 15
functional categories (Figure 3c; Tables 1 and 2).
Secretome analysis by cICAT
Given that the total number of secreted proteins
identified by 2-DE was smaller than we had anticipated,
and to avoid potential bias of using a single identification method, we sought a second complementary
approach. Recently, internally standardized gel-free
quantitative proteomic methods have been developed
to alleviate limitations of 2-DE. One of these methods is
isotope-coded affinity tag (ICAT) reagent labeling and
tandem mass spectrometry (MS/MS) (Gygi et al., 2002).
Secreted proteins from 2024 and WT11 cells were very
Oncogene
wt-p53-regulated secreted proteins in glioma cells
FW Khwaja et al
7656
-
+Wt-p53
-
TSP1
Gal-3
SPARC
Gal-1
FGF-4
β-2M
TGF-β
Pre-alb.
+Wt-p53
Figure 2 Semiquantitative analysis of differentially expressed proteins found by 2-DE and identified by MS/MS analysis. 3D
representation of differential expression for representative proteins found upregulated (Gal-3, Gal-1 and b-2M), downregulated
(SPARC, FGF-4 and TGF-b), and unchanged (TSP-1 and Pre-alb) by 2-DE as analysed by ImageMaster software.
similar in their expression patterns and differed significantly in expression levels for only 10 of the 91
proteins identified by this analysis. Through cICAT
alone, we found 34 proteins with increased levels, and 13
with decreased levels by at least 20% while 44 remained
unchanged in response to wt-p53 expression (Tables 1–3;
Figure 3b). These proteins were found differentially
expressed in CM (Po0.05) in at least two of the three
experiments for both cell lines. The quantification from
cICAT was found to be consistent between experiments
as seen by small standard deviation values for each
tested cell line (Tables 1–3). Similar to 2-DE results, the
91 proteins found secreted in the media by cICAT
experiments belonged to 15 functional groups
(Figure 3c; Tables 1 and 2).
Comparison of 2-DE and cICAT results
Combining both techniques, we were able to identify
111 separate secreted proteins; 68 by 2-DE and 91 by
cICAT analysis (Figure 3a). It is noteworthy that 48 of
the 91 (B50%) secreted proteins identified by cICAT
analysis, were identical to the ones identified by 2-DE
analysis, showing concordant results between the
techniques in identifying the complement of secreted
proteins (Tables 1–3; Figure 3). Thirty-seven of the 48
(77%) proteins commonly identified by the techniques
showed similar responses to p53 activation in the cells.
The majority of the remaining 11 (24%) proteins (listed
Oncogene
as U in Table 3) were either secreted at a very low level
or not differentially expressed to a high degree. When
looking at the concordance between p53-regulated
proteins, we found 13 proteins upregulated, eight
downregulated and 16 unchanged by both 2-DE and
cICAT analysis while the remaining 11 (listed as U) were
found differentially expressed only by one of the two
indicated methods (Figure 3b Tables 1–3).
Verification of proteomic results
Some of the p53-regulated secreted proteins found in
our analysis had been previously reported and validated,
including vascular endothelial growth factor (VEGF),
osteopontin (Opn) (Morimoto et al., 2002), secreted
protein with acidic and cysteine rich domains (SPARC)
and dickkopf (Wang et al., 2000). To confirm our results
we picked three proteins whose levels were increased
(galectin-1 (Gal-1), galectin-3 (Gal-3) and beta 2
microglobulin (b-2M)) and three decreased (SPARC,
fibroblast growth factor-4 (FGF-4) and transforming
growth factor beta (TGF-b)) in the CM in response to
wt-p53 expression for validation by Western analysis.
The levels of Gal-1, Gal-3 and b-2M in the CM were
clearly increased by p53 in 2024 cells (Figure 4, compare
lanes 2 and 4). In contrast, secreted levels of SPARC,
TGF-b and FGF-4 were decreased. The downregulation
of SPARC and TGF-b levels in the CM by p53 was
particularly strong as it was able to antagonize their
wt-p53-regulated secreted proteins in glioma cells
FW Khwaja et al
7657
cICAT (91)
2-DE (68)
48
43
50
45
40
35
30
25
20
15
10
5
0
44
34
18
16
34
13
Up-regulated
Down-regulated
Unchanged/ Unclear
11
13
8 16
2-DE
cICAT
2-DE+cICAT
14
12
2-DE
10
cICAT
8
6
4
2
i
i-a iog on
ng en
e
i
D og sis
iff en
er
e esi
D ntia s
Im NA
tio
m
un bin n
d
e
re ing
sp
M
et on
s
Pr abo e
Pr
ol
lis
ot ife
m
ei
ra
n
t
i
sy on
nt
Pr
h
Pr es
ot
ea ot is
e
se
a
in se
hi
St
ru
Si bito
ct
ur gna r
e
l
& ing
m
ot
il
Su ity
r
Tr vi
an va
sp l
o
U
nk rt
no
w
n
0
A
nt
A
ng
A
dh
es
c
# of proteins identified
20
b
# of proteins identified
a
Figure 3 Comparative analysis of wt-p53-regulated secreted proteins using both proteomic analyses: (a) Ven Diagram showing the
total number (111) of secreted proteins found by 2-DE (white), and cICAT (gray). (b) Number of proteins found unchanged (white),
up- (dark gray) or downregulated (light gray) by wt-p53 expression using 2-DE and c-ICAT analysis alone and those common to both
techniques. (c) Distribution of identified secreted proteins by 2-DE (white) and c-ICAT (gray) analyses according to their general
functional categories. Each protein is seen in a single category only even though some might play multiple functions.
increase by doxycycline (dox) as seen in the LNZ308C16 control cells that lack p53. Thrombospondin-1
(TSP-1) was used as a loading control since its levels are
not found to be increased by wt-p53 in our glioma
system (Tenan et al., 2000). The data show that our
proteomic analysis with 2-DE and cICAT can be used to
reliably identify differential expression of secreted
proteins in the CM (Tables 1–3).
Investigation of the mechanism underlying p53 control
over protein secretion
To examine whether the CM levels of the secreted
proteins identified were regulated by p53 at the gene
expression level, we examined the differential expression
of their mRNAs by microarrays in the 2024 cell line in
three independent experiments. None of the mRNAs
corresponding to the secreted products found in
our analysis appeared to have levels significantly
modulated by p53 (Tables 1–3; column 5). These
findings suggest a role of wt-p53 in the modulation of
the extracellular levels of secreted proteins through
either enhanced stability or secretion. One way that
p53 could potentially affect protein stability and/or
secretion is through regulation of post-translational
modifications, for example, phosphorylation, glycosylation, acetylation and hydroxylation of proteins,
events that may mark certain proteins either for
degradation or for localization (Kamemura and Hart,
2003). Preliminary indications of such post-transcriptional modifications were noted for a subset of
the identified proteins through 2-DE analysis (Table 4),
as seen for example by the horizontal and vertical
shifts of Gal-1 protein spots from their original pI
and MW positions (Figure 1b, c; black arrows). This
suggests a potential novel function of the p53 tumor
suppressor, the modulation of post-transcriptional
modifications. Alternatively, p53 may also be involved
in the regulation of a specific secretory pathway (Yu
et al., 2006). Indeed, most proteins whose levels were
positively regulated by p53 were found secreted through
nonclassical mechanisms including vesicle-mediated
pathways like exocytosis, ectocytosis as well as through
transporter-mediated pathways. In contrast, most proteins released through classical pathways were downregulated (Tables 1 and 2).
Discussion
This is the first comprehensive analysis of the tumor cell
secretome to identify secreted targets of wt-p53. The
term ‘secretome’ refers to proteins released through
classical as well as nonclassical secretion pathways
(Volmer et al., 2005). In addition, it also includes
intracellular proteins and protein fragments that might
be released in exosomes as a result of wt-p53 expression.
Oncogene
wt-p53-regulated secreted proteins in glioma cells
FW Khwaja et al
7658
C16
2024
In our analysis, p53 expression led to increased levels of
39 and decreased levels of 21 proteins in the CM of
glioma cells (Tables 1–3).
The mechanism through which p53 might regulate the
secretion of proteins is currently unknown. A number of
secreted proteins regulated at the transcriptional
level have been reported. However, we did not find
Western
-
+
-
+
Dox
-
-
-
+
p53
Gal-1
Gal-3
β -2M
Pre-alb.
any of the secreted proteins found in our analysis to
be significantly regulated by p53 at the transcriptional
level. Instead, our microarray and Western analyses
showed that most p53-regulated secreted proteins
were not direct p53 targets and may have accumulated
in the CM indirectly through different mechanisms.
One possibility is enhanced stability, which could
result through multiple means including changes in
protein stability and localization or downregulation of
proteases like matrix metalloproteinase (MMPs) thus
leading to the accumulation of the affected proteins in
the media. In fact, MMP-1 and MMP-13 have already
been shown to be downregulated by wt-p53 (Sun et al.,
2000). Alternatively, p53 could alter the secretion rate
of intracellular proteins through either augmented
release of specific proteins or through upregulation
of a particular secretory pathway, thus leading to
enhanced levels of all proteins secreted through that
pathway. There is a precedence in the literature for at
least one p53-regulated protein (TSAP6) that can
facilitate the secretion of another protein (TCTP)
through ectocytosis (Amzallag et al., 2004). Recent
evidence suggests that p53 may act as a general regulator of this nonclassical secretory pathway (Yu et al.,
2006).
Functional implications for tumorigenesis
Wild-type p53 has been shown to inhibit many processes
required for tumor growth including migration, angiogenesis, survival and cell proliferation (Fulci and Van
Meir, 1999). It has also been implicated in eliciting an
immune response against neoplastic cells (Bueter et al.,
2006). The results of our screen found wt-p53 regulating
the secretion of many proteins that are candidate
mediators for the above biological effects.
SPARC
FGF-4
TGF-β
TSP1
Figure 4 Verification of selected 2-DE and cICAT results:
Western blot analysis on TCA-precipitated serum-free CM
collected after 48 h from LNZ308-C16 (control for dox) and 2024
cells with tet-on wt-p53 expression. Differential expression of
SPARC, FGF-4, TGF-b, Gal-1, Gal-3, and b-2M in response to
wt-p53 expression was examined. TSP1 and Pre-alb were loading
controls and remained unchanged.
p53 and metastasis/invasion
Our analysis found several ECM components (growth
arrest-specific 6, collagen type XI a-1, proteoglycan
PG-M) or proteins involved in adhesion and cell–matrix
interactions (galectin-3, lysyl oxidase-like protein 2,
Opn, a-catenin and b-5 tubulin) as well as protease
inhibitors (TIMP-3 and glioma pathogenesis-related
Table 4 Secreted proteins with potential post-translational modifications induced by wt-p53
Protein name
Access. no.
Th. MW
Th. pI
Obs. MW
Obs. pI
Potential post-translational modification
Galectin-3
Galectin-1
b-2 microglobulin
Proteoglycan PG-M (V3)
Cytosolic thyroid hormone-bp
ADAM-10
MMP-2
Thrombospondin-1
14-3-3 protein tau
gi:4504983
gi:12804557
gi:179318
gi:1008913
gi:338827
gi:4557251
gi:11342666
gi:40317626
gi:112690
26.19
14.72
13.73
74.25
58.00
84.14
73.88
129.38
27.76
8.58
5.33
6.06
7.43
7.95
8.04
5.26
4.71
4.68
25–35
17–33
15
1.34
57–62
70
70–75
125
13
7.5–8.7
5.0–5.5
5.0–5.5
7.5–7.75
6.4–6.5
8.7–9.0
4.1
4.5–4.7
4.0–5.0
Phosphorylation and/or glycosylation
Phosphorylation and/or glycosylation
Phosphorylation
Dephosphorylation and/or deglycosylation
Dephosphorylation and/or deglycosylation
Dephosphorylation or proteolysis
Not determined
Phosphorylation
Dephosphorylation and/or proteolysis
Proteins whose spot pattern on 2-DE indicated possible wt-p53 induced post-translational modifications are listed along with their accession
number (Acess. no.), theoretical molecular weight (Th. MW), theoretical isoelectric point (Th. pI), observed molecular weight (Obs. MW), observed
isoelectric point (Obs. pI) and the possible post-translational modification observed. A vertical shift (changes in MW) indicates possible
glycosylations while a horizontal shift towards lower pI indicates possible phosphorylations.
Oncogene
wt-p53-regulated secreted proteins in glioma cells
FW Khwaja et al
7659
protein) upregulated in the CM from the glioma cells
after wt-p53 induction. The induction of these structural
and proadhesion proteins would be expected to improve
cell–cell and cell–matrix interactions, thus resulting in
reduced migratory potential of tumor cells.
In addition to upregulation of antimigratory factors,
other proteins directly involved in induction of migration and invasion in multiple tumor types, were found
downregulated by wt-p53. These included SPARC,
MMP-2, TGF-b, ADAM-10, and Tau (Framson
and Sage, 2004; Mazzocca et al., 2005; Stuelten et al.,
2005). These findings point to a potential new facet of
p53’s multimodal function as a tumor-suppressor
gene, the downregulation of tumor invasion and
metastasis.
p53 and the immune response
In recent years various studies have suggested that
wt-p53 could stimulate immune responses against tumor
cells. For example, secreted Opn found upregulated in
our analysis is one of the key cytokines for type 1
immune responses mediated by macrophages. It has
already been reported as a direct target of wt-p53 and
has been implicated in suppressing tumor growth in vivo
(Morimoto et al., 2002). Our screen identified increased
secretion of immune response-related proteins b-2M and
macrophage migration and myeloid leukemia inhibitory
factors in response to wt-p53. b-2M is a MHC class I
molecule and several studies have shown that tumor
development might be inhibited by immune responses
stimulated by this class of proteins (Bueter et al., 2006).
Other immune-related proteins like interleukin-8 (IL-8),
attractin, and ANP32A were found downregulated by
wt-p53. IL-8 is known to be upregulated in glioma, possibly in response to immune cell infiltration (Desbaillets
et al., 1997). Attractin is upregulated in glioma patient
cerebrospinal fluid (CSF) and can modulate T-cell
motility (Khwaja et al., 2006). These results encourage
further research into how p53 may modulate the tumor
immune response.
p53 and angiogenesis
Our results show repression of at least five proangiogenic proteins, VEGF, IL-8, TGF-b, PEDF, and
CYR61 by wt-p53 in glioma cells. VEGF has been
shown to be downregulated by wt-p53 in many systems
(Qin et al., 2006) while CYR61 has not been reported
as a p53 target before. CYR61 is a secreted ECMassociated signaling molecule that has been shown to
promote the adhesion and proliferation of endothelial
cells (Babic et al., 1998). CYR61 has been shown to be
overexpressed in several cancers including breast and
brain tumors, where it promotes angiogenesis and
increased tumor growth (Tsai et al., 2000; Xie et al.,
2004). Similarly, IL-8 is expressed and secreted at high
levels in human gliomas and involved in glial tumor neovascularity and progression (Brat et al., 2005). Overall
our findings suggest a model in which p53 loss in tumors
activates angiogenesis by an increase in secretion of
proangiogenic factors and decrease of inhibitors.
p53 and tumor proliferation and survival
We found several proteins regulating tumor proliferation and survival to be regulated by wt-p53. Brain
derived neurotrophic factor (BDNF) exhibited enhanced secretion in response to wt-p53. The secreted
form of BDNF mediates apoptosis of cells containing
neurotrophin receptors (Lee et al., 2001). Other proteins, including FGF-4, RTVP1, TPM-ALK fusion
oncoprotein fragment, TGF-b, PEDF, IGFBPs, and
granulin were all found to have inhibited secretion to
varying degrees in response to wt-p53. RTVP1, TGF-b
(Tsuzuki et al., 1998), and PEDF (Pietras et al., 2002)
are previously known targets of wt-p53.
Concluding remarks
In this study we have identified secreted proteins whose
extracellular levels are regulated by p53. We found 39
proteins with enhanced and 21 with inhibited levels in
response to wt-p53 expression out of a total of 111
proteins identified to be secreted by the cells. None of
the tested proteins were found to be transcriptional
targets indicating that wt-p53 may have an indirect role
in their stability or secretion. These secreted targets will
be helpful in better understanding of how wt-p53 may
modulate interactions of tumor cells with their environment and establishes p53 loss in tumors as an originator
of changes in tumor–stroma interactions. They may also
help explain some of the ‘bystander effects’ observed in
p53-mediated cancer gene therapy or with radio- and
chemotherapies that activate p53.
Materials and methods
Cell lines and culturing conditions
LN-Z308 (p53 null) human glioblastoma cell line (Albertoni
et al., 1998), and its isogenic clones LNZ308-C16 (contains a
reverse tetracycline transactivator (rtTA)), 2024 (tet-inducible
wt-p53) (Albertoni et al., 2002) and WT11 (tet-off for wt-p53)
(Van Meir et al., 1994) were grown in Dulbecco’s modified
Eagle’s medium supplemented with 5% tet-tested fetal calf
serum. Cells were grown in serum-free media and wt-p53
expression was induced by modulation with 2 mg/ml of dox.
CM from the cells was collected after 48 h induction and
frozen at 201C after removal of floating cells and cell debris
by centrifugation at 1000 g.
Two-dimensional polyacrylamide gel electrophoresis (2-DE)
Samples were analysed in triplicates using 2-DE as described
(Goldman et al., 1980). The first dimension was performed on
IPGphor system (Amersham Biosciences, NJ, USA). Isoelectric focusing of 200 mg of trichloroacetic acid (TCA)
precipitated protein was performed on 13 cm or 17 cm
Immobiline dry strips (IPG strips) using either pH range of
3–10NL or 4–7L (total run ¼ 130 000 Vh). Strips were then
equilibrated sequentially in equilibration buffer (6 M urea, 2%
sodium dodecyl sulfate (SDS), 0.05 M Tris base pH 8.8, 20%
glycerol) first containing 10 mg/ml dithiothreitol (DTT) and
then 25 mg/ml iodoacetamide followed by separation in the
second dimension on 12.5% polyacrylamide gels with 2% SDS
using the Protean II xi system (BioRad, CA, USA). Silver
Stain Plus kit (BioRad) was used to visualize protein spots and
the gels were analysed using Melanie (http://au.expasy.org/
Oncogene
wt-p53-regulated secreted proteins in glioma cells
FW Khwaja et al
7660
melanie/) and the ImageMaster softwares (Amersham Biosciences, NJ, USA).
In-gel digestion of proteins and MALDI-TOF/TOF-MS analysis
Protein spots of interest were excised from the gel and destained
using SilverOUT kit (GenoTech, MO, USA). The proteins were
digested overnight with 150 ng trypsin (Promega, WI, USA) and
the resulting peptides extracted using Montage In-gel peptide
extraction kit (Millipore, MA, USA), spotted onto target plates
and overlaid with a-cyano-4-hydroxycinnamic acid (Agilent,
DE, USA). The plates were analysed using a 4700 Proteomics
Analyzer (Applied Biosystems, CA, USA). The combined MS
and MS/MS spectra from each spot were processed using GPS
Explorer V2.0 (Applied Biosystems, CA, USA) with MASCOT
(Matrix Science, MA, USA) as the database search engine. Only
proteins that generated multiple peptides with ion scores above
30 were considered positively identified.
cICAT analysis
cICAT technology uses stable isotope tags in combination with
two-dimensional (2D) chromatography of complex peptide
mixtures (Applied Biosystems) (Gygi et al., 2002). Hundred
micrograms each of precipitated secreted protein from the CM
were treated with denaturing (50 mM Tris; 0.1% SDS) and
reducing (50 mM TCEP (Tris(2-carboxyethyl)phosphine hydrochloride)) reagents. Next, the control and wt-p53 induced
samples were respectively labeled with light (9 12C atoms) and
heavy (9 13C atoms) reagents for 2 h at 371C. After trypsin
digestion and purification, the peptides were analysed using an
Ultimate nanoHPLC LC-MS/MS (Dionex/LC Packings, CA,
USA) interfaced to a QSTAR XL mass spectrometer (Applied
Biosystems). The MS/MS data were processed using ProICAT
software for protein identification and quantification. Only
proteins with ProtScore >1.0 (>85% confidence) were considered. Also, the heavy to light ratios were tested for significance using Student t-test and Po0.05 was considered significant.
Western blot analysis
Immunoblots were performed on cell lysates (lysed in 8 M urea,
4% SDS, in 10 mM Tris, pH 7.4). The CM was precipitated by
15% TCA for 2 h at 41C, washed twice with ice-cold acetone,
and then resuspended in lysis buffer (8 M urea, 4% SDS,
100 mM protease inhibitor cocktail (Roche, Germany), in
10 mM Tris, pH 7.4). Antibodies used were: a-TSP1 (Ab-4
NeoMarkers, Freemont, CA, USA; 1:1000), a-FGF-4 (sc16812, Santa Cruz, CA, USA; 1:500), a-SPARC (sc-13324,
Santa Cruz; 1:500), a-VEGF (Santa Cruz; 1:500), a-b-2M
(Clone B2M-01; Abcam, MA, USA; 1:250), a-TGFb
(AE1109.1, Immunodiagnostik, Germany; 1:100), a-galectin-3
(Santa Cruz, CA, USA; sc-14364; 1:500), a-galectin-1 (Santa
Cruz, CA, USA; 1: 500). Pre-albumin (Pre-alb) (sc-13098;
Santa Cruz; 1:1000) and actin (sc-1615; Santa Cruz, CA, USA;
1:1000) were used as a loading controls.
Abbreviations
b-2M, beta-2-microglobulin; 2-DE, two-dimensional gel
electrophoresis; cICAT, cleavable isotope-coded affinity tag
technology; CM, conditioned media; ECM, extracellular
matrix; FGF-4, fibroblast growth factor-4; Gal-1, Galectin-1;
Gal-3, galectin-3; Pre-alb, pre-albumin; SPARC, secreted
protein with acidic and cysteine-rich domains; TGF-b,
transforming growth factor beta; TSP1, thrombospondin-1.
Acknowledgements
We thank Drs JC Lucchesi, D Pallas, I Matsumura and
P Vertino for their support. This work was supported by
National Institutes of Health (NIH) grants CA 86335 (to
EGVM); NCRR 02878, 12878, 13948 (to Microchemical and
Proteomics Facility), the Pediatric Brain Tumor Foundation
of the US (to EGVM) and the American Brain Tumor Association (to BP), the Genetics and Molecular Biology (GMB)
program of the Graduate Division of Biological and
Biomedical Sciences (GDBBS) of Emory University,
and the National Science Foundation (NSF) (PRISM;
DGE0231900).
References
Albertoni MD, Daub M, Arden KC, Viars CS, Powell C,
Van Meir EG. (1998). Genetic instability leads to loss
of both p53 alleles in a human glioblastoma. Oncogene 16:
321–326.
Albertoni M, Shaw PH, Nozaki M, Godard S, Tenan M,
Hamou M-F et al. (2002). Anoxia induces macrophage
inhibitory cytokine-1 (MIC-1) in glioblastoma cells independently of p53 and HIF-1. Oncogene 21: 4212–4219.
Amzallag N, Passer BJ, Allanic D, Segura E, Thery C, Goud B
et al. (2004). TSAP6 facilitates the secretion of translationally controlled tumor protein/histamine-releasing factor via
a nonclassical pathway. J Biol Chem 279: 46104–46112.
Babic AM, Kireeva ML, Kolesnikova TV, Lau LF. (1998).
CYR61, a product of a growth factor-inducible immediate
early gene, promotes angiogenesis and tumor growth. Proc
Natl Acad Sci USA 95: 6355–6360.
Bhowmick NA, Moses HL. (2005). Tumor–stroma interactions. Curr Opin Genet Dev 15: 97–101.
Brat DJ, Bellail AC, Van Meir EG. (2005). The role of
interleukin-8 and its receptors in gliomagenesis and tumoral
angiogenesis. Neuro-oncol 7: 122–133.
Oncogene
Bueter M, Gasser M, Lebedeva T, Benichou G, WaagaGasser AM. (2006). Influence of p53 on anti-tumor
immunity (review). Int J Oncol 28: 519–525.
Chiarugi V, Magnelli L, Gallo O. (1998). Cox-2, iNOS and p53
as play-makers of tumor angiogenesis (review). Int J Mol
Med 2: 715–719.
Desbaillets I, Diserens AC, Tribolet N, Hamou MF,
Van Meir EG. (1997). Upregulation of interleukin 8 by
oxygen-deprived cells in glioblastoma suggests a role in
leukocyte activation, chemotaxis, and angiogenesis. J Exp
Med 186: 1201–1212.
Framson PE, Sage EH. (2004). SPARC and tumor growth:
where the seed meets the soil? J Cell Biochem 92: 679–690.
Fulci G, Van Meir EG. (1999). p53 and the CNS: tumors and
developmental abnormalities. Mol Neurobiol 19: 61–77.
Goldman D, Merril CR, Ebert MH. (1980). Two-dimensional
gel electrophoresis of cerebrospinal fluid proteins. Clin Chem
26: 1317–1322.
Görg A, Weiss W, Dunn MJ. (2004). Current two-dimensional
electrophoresis technology for proteomics. Proteomics 4:
3665–3685.
wt-p53-regulated secreted proteins in glioma cells
FW Khwaja et al
7661
Gygi SP, Rist B, Griffin TJ, Eng J, Aebersold R. (2002).
Proteome analysis of low-abundance proteins using multidimensional chromatography and isotope-coded affinity
tags. J Proteome Res 1: 47–54.
Hanahan D, Weinberg RA. (2000). The hallmarks of cancer.
Cell 100: 57–70.
Harris SL, Levine AJ. (2005). The p53 pathway: positive and
negative feedback loops. Oncogene 24: 2899–2908.
Kamemura K, Hart GW. (2003). Dynamic interplay between
O-glycosylation and O-phosphorylation of nucleocytoplasmic proteins: a new paradigm for metabolic control of signal
transduction and transcription. Prog Nucleic Acid Res Mol
Biol 73: 107–136.
Khwaja FW, Duke-Cohan JS, Brat DJ, Van Meir EG. (2006).
Attractin is elevated in the cerebrospinal fluid (CSF) of
patients with malignant astrocytoma and mediates glioma
cell migration. Clinical Cancer Research, in press.
Lee R, Kermani P, Teng KK, Hempstead BL. (2001).
Regulation of cell survival by secreted proneurotrophins.
Science 294: 1945–1948.
Mazzocca A, Coppari R, De Franco R, Cho JY, Libermann
TA, Pinzani M et al. (2005). A secreted form of ADAM9
promotes carcinoma invasion through tumor–stromal interactions. Cancer Res 65: 4728–4738.
Morimoto I, Sasaki Y, Ishida S, Imai K, Tokino T. (2002).
Identification of the osteopontin gene as a direct target of
TP53. Genes Chromosomes Cancer 33: 270–278.
Pietras K, Rubin K, Sjoblom T, Buchdunger E, Sjoquist M,
Heldin CH et al. (2002). Inhibition of PDGF receptor
signaling in tumor stroma enhances antitumor effect of
chemotherapy. Cancer Res 62: 5476–5484.
Qin G, Kishore R, Dolan CM, Silver M, Wecker A, Luedemann CN et al. (2006). Cell cycle regulator E2F1 modulates angiogenesis via p53-dependent transcriptional control
of VEGF. Proc Natl Acad Sci USA 103: 11015–11020.
Steele RJ, Lane DP. (2005). P53 in cancer: a paradigm for
modern management of cancer. Surgeon 3: 197–205.
Stuelten CH, DaCosta Byfield S, Arany PR, Karpova TS,
Stetler-Stevenson WG, Roberts AB. (2005). Breast cancer
cells induce stromal fibroblasts to express MMP-9 via
secretion of TNF-alpha and TGF-beta. J Cell Sci
118(Part 10): 2143–2153.
Sun Y, Cheung JM, Martel-Pelletier J, Pelletier JP, Wenger L,
Altman RD et al. (2000). Wild type and mutant p53
differentially regulate the gene expression of human collagenase-3 (hMMP-13). J Biol Chem 275: 11327–11332.
Taieb J, Chaput N, Menard C, Apetoh L, Ullrich E, Bonmort
M et al. (2006). A novel dendritic cell subset involved in
tumor immunosurveillance. Nat Med 12: 214–219.
Tenan M, Fulci G, Albertoni M, Diserens AC, Hamou MF,
El Atifi-Borel M et al. (2000). Thrombospondin-1 is
downregulated by anoxia and suppresses tumorigenicity of
human glioblastoma cells. J Exp Med 191: 1789–1798.
Tsai MS, Hornby AE, Lakins J, Lupu R. (2000). Expression
and function of CYR61, an angiogenic factor, in breast
cancer cell lines and tumor biopsies. Cancer Res 60:
5603–5607.
Tsuzuki T, Izumoto S, Ohnishi T, Hiraga S, Arita N, Hayakawa T.
(1998). Neural cell adhesion molecule L1 in gliomas:
correlation with TGF-beta and p53. J Clin Pathol 51:
13–17.
Van Meir EG, Polverini PJ, Chazin VR, Su Huang HJ, de
Tribolet N, Cavenee WK. (1994). Release of an inhibitor of
angiogenesis upon induction of wild type p53 expression in
glioblastoma cells. Nat Genet 8: 171–176.
Van Meir EG, Roemer K, Diserens A-C, Kikuchi T, Rempel
SA, Haas M et al. (1995). Single-cell monitoring of growth
arrest and morphological changes induced by transfer of
wild type p53 alleles to glioblastoma cells. Proc Natl Acad
Sci USA 92: 1008–1012.
Volmer MW, Stuhler K, Zapatka M, Schoneck A, KleinScory S, Schmiegel W et al. (2005). Differential proteome
analysis of conditioned media to detect Smad4 regulated secreted biomarkers in colon cancer. Proteomics 5:
2587–2601.
Wang J, Shou J, Chen X. (2000). Dickkopf-1, an inhibitor of
the Wnt signaling pathway, is induced by p53. Oncogene 19:
1843–1848.
Xie D, Yin D, Wang HJ, Liu GT, Elashoff R, Black K et al.
(2004). Levels of expression of CYR61 and CTGF are
prognostic for tumor progression and survival of individuals
with gliomas. Clin Cancer Res 10: 2072–2081.
Yu X, Harris SL, Levine AJ. (2006). The regulation of
exosome secretion: a novel function of the p53 protein.
Cancer Res 66: 4795–4801.
Zigrino P, Loffek S, Mauch C. (2005). Tumor-stroma
interactions: their role in the control of tumor cell invasion.
Biochimie 87: 321–328.
Oncogene