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1
Decreased serum thrombospondin-1 levels in pancreatic cancer patients up to 24 months prior
to clinical diagnosis: association with diabetes mellitus
Claire Jenkinson
1,2*
, Victoria L. Elliott
1,2*
, Anthony Evans
1,2*
, Lucy Oldfield
1,2
, Rosalind E. Jenkins
3
,
Darragh P. O’Brien
4
, Sophia Apostolidou
4
, Aleksandra Gentry-Maharaj
4
, Evangelia-O Fourkala
4
, Ian
J. Jacobs
4,5
, Usha Menon
4
, Trevor Cox
1
,
Fiona Campbell
6
, Stephen P. Pereira
7
, David A. Tuveson
8
,
B. Kevin Park
3
, William Greenhalf
1,2
, Robert Sutton
1,2
, John F. Timms
4
, John P. Neoptolemos
1,2
and
Eithne Costello
1,2
.
1
Department of Molecular and Clinical Cancer Medicine, University of Liverpool, UK;
2
National
Institute for Health Research Liverpool Pancreas Biomedical Research Unit, Royal Liverpool
University Hospital, UK;
3
MRC Centre for Drug Safety Science, Department of Pharmacology and
Therapeutics, University of Liverpool, UK;
4
Department of Women’s Cancer, Institute for Women’s
Health, University College London, UK;
5
Faculty of Medical & Human Sciences, 1.018 Core
Technology Facility, University of Manchester, UK.
6
Department of Pathology, University of Liverpool,
UK;
7
Institute for Liver and Digestive Health, University College London,
.8
Cold Spring Harbor
Laboratory, Cold Spring Harbor, NY 11724, USA.
*CJ, VE and AE contributed equally to this work.
Running title: Reduced serum TSP-1 prior to clinical diagnosis of PDAC
Keywords – PDAC, Serum, TSP-1, Biomarker, Diabetes
Financial support: This work was supported by Northwest Cancer Research Fund, UK, grant
CR976, The National Institute for Health Research Pancreas Biomedical Research Unit, Cancer
Research UK grant A12790, Pancreatic Cancer UK and the European Community's Seventh
Framework Programme (FP7/2007-2013) under grant agreement no. 256974. UKCTOCS was core-
funded by the Medical Research Council, Cancer Research UK, and the Department of Health with
additional support from the Eve Appeal, Special Trustees of Bart’s and the London, and Special
Trustees of UCLH. UKCTOCS researchers were supported by the National Institute for Health
Research University College London Hospitals Biomedical Research Centre.
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Corresponding author: Eithne Costello, Liverpool Cancer Research-UK Centre, Department of
Molecular and Clinical Cancer Medicine, University of Liverpool, Daulby Street, Liverpool L69 3GA,
UK. Email: ecostell@liverpool.ac.uk; Telephone +441517064178; FAX: +441517065826
Conflict of Interest: IJ and UM have a financial interest through UCL Business and Abcodia Ltd in
the third party exploitation of trials biobanks, developed through their research at UCL. IJ has a
consultancy arrangement with Becton Dickinson in the field of tumour markers and ovarian cancer.
None of the other authors have any conflict of interest or other relationships or activities that could
appear to have influenced the submitted work.
Word count = 4756; Figures & Tables = 6
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Translational Relevance
The majority of patients with pancreatic ductal adenocarcinoma (PDAC) are diagnosed with advanced
stage disease and survive less than 12 months. Biomarkers enabling earlier diagnosis are sorely
needed. Serum biomarker discovery studies tend to use samples from diagnosed patients, meaning
current research efforts are potentially missing critical changes occurring in the months and years
prior to diagnosis. Additionally a high proportion of PDAC patients are either hyperglycaemic or
diabetic. The impact of diabetes on circulating biomarkers is poorly understood. Here we
demonstrate, in serum taken up to 4 years prior to a PDAC diagnosis, that circulating TSP-1 levels
are significantly reduced up to 24 months prior to diagnosis and low serum TSP-1 levels in PDAC
patients are significantly associated with diabetes mellitus. Early detection strategies could benefit
from including TSP-1. Future studies investigating biomarkers for pancreatic cancer detection should
take into account the influence of diabetes mellitus on biomarker behaviour.
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Abstract
Purpose: Identification of serum biomarkers enabling earlier diagnosis of pancreatic ductal
adenocarcinoma (PDAC) could improve outcome. Serum protein profiles in patients with pre-clinical
disease and at diagnosis were investigated.
Experimental Design: Serum from cases up to 4 years prior to PDAC diagnosis and controls
(UKCTOCS,n=174) were studied, alongside samples from patients diagnosed with PDAC, chronic
pancreatitis, benign biliary disease, type 2 diabetes mellitus and healthy subjects (n=298). iTRAQ
enabled comparisons of pooled serum from a test set (n=150). Validation was undertaken using MRM
and/or western blotting in all 472 human samples and samples from a KPC mouse model.
Results: iTRAQ identified thrombospondin-1 (TSP-1) as reduced preclinically and in diagnosed
samples. MRM confirmed significant reduction in levels of TSP-1 up to 24 months prior to diagnosis.
A combination of TSP-1 and CA19-9 gave an AUC of 0.86, significantly outperforming both markers
alone (0.69 & 0.77 respectively; P<0.01). TSP-1 was also decreased in PDAC patients compared to
healthy controls (P<0.05) and patients with benign biliary obstruction (P<0.01). Low levels of TSP-1
correlated with poorer survival, pre-clinically (P<0.05) and at clinical diagnosis (P<0.02). In PDAC
patients, reduced TSP-1 levels were more frequently observed in those with confirmed diabetes
mellitus (P<0.01). Significantly lower levels were also observed in PDAC patients with diabetes
compared to individuals with type 2 DM (P=0.01).
Conclusions: Circulating TSP-1 levels decrease up to 24 months prior to diagnosis of PDAC and
significantly enhance the diagnostic performance of CA19-9. The influence of diabetes mellitus on
biomarker behaviour should be considered in future studies.
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Introduction
For the majority of patients, pancreatic ductal adenocarcinoma (PDAC) goes undetected until it is at
an advanced stage. Symptoms, such as obstructive jaundice, weight loss or pain often manifest late
in the course of the disease when effective treatment options are limited. Consequently, overall
survival is poor (1). CA19-9, the only biomarker in routine use for the management of pancreatic
cancer (2, 3) has a number of limitations including lack of expression in ~5% of the population, and
elevation in related diseases including chronic pancreatitis and obstructive jaundice (2, 4). Alternative
biomarkers that can facilitate earlier diagnosis are actively sought (5, 6).
To date, PDAC serum biomarker discovery work has almost exclusively used samples taken following
diagnosis. Serum protein levels in these samples may not accurately reflect changes occurring in the
months or years prior to diagnosis. To explore alterations in serum proteins that occur pre-clinically,
we performed biomarker discovery using samples collected as part of the prospective cohort ‘United
Kingdom Collaborative Trial of Ovarian Cancer Screening’ (UKCTOCS; www.ukctocs.org.uk/ (7, 8)).
The nested cohort of samples analysed here were from women who were subsequently diagnosed
with pancreatic cancer. We included samples taken up to 48 months prior to diagnosis of pancreatic
cancer, along with control samples, matched for date of donation and the centre at which samples
were donated.
For biomarker discovery we used isobaric tags for relative and absolute quantification (iTRAQ), which
allows for the simultaneous accurate, precise and reproducible quantification of proteins across
several samples (9, 10). For validation we used multiple reaction monitoring (MRM), a mass
spectrometry (MS)-based approach, which provides an alternative to immune-based protein
quantification. MRM enables the detection and precise quantification of predetermined proteins in
complex mixtures (11) and is capable of accurately discriminating between protein isoforms.
We discovered significantly reduced levels of serum Thrombospondin-1 levels pre-clinically, during a
period of 24 months prior to diagnosis with PDAC, and at diagnosis of PDAC. Importantly, we
demonstrated a significant relationship between TSP-1 levels and diabetes mellitus in PDAC patients,
suggesting that TSP-1 merits investigation as a marker for PDAC-associated diabetes.
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METHODS
Patient Groups
Blood was obtained, with ethically approved informed written consent from two independent sources;
UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS; ref.05/Q0505/57) and National
Institute for Health Research Liverpool Pancreas Biomedical Research Unit (PBRU; ref11/NM/0083
and 08/H1005/1). The UKCTOCS study set comprised serum from women recruited to UKCTOCS
between 2001 and 2005(12) who went on to develop pancreatic cancer and time matched controls.
The samples were subcategorised as follows; 0-6 months pre-diagnosis (n=30 cases, 30 controls),
>6-12 months (n=17 cases, 17 controls), >12-24 months (n=17 cases, 17 controls), >24-36 months
(n=11 cases, 11 controls) and >36-48 months (n=12 cases, 12 controls). In total, 174 UKCTOCS case
samples from 76 individuals were used in the study. This included serial samples from 26 individuals.
Two independent PBRU sets were analysed. The first PBRU set (n=199) consisted of 98 patients with
histologically confirmed PDAC, 39 patients with chronic pancreatitis (CP), 20 with jaundice due to gall
stones (benign biliary obstruction, BBO) and 42 healthy control individuals (HC). PDAC patients were
further subcategorised into those with low bilirubin levels (49 patients, <20 µmol/L; upper level of
normal for our Centre) and high bilirubin levels (49 patients, >20 µmol/L). To determine levels of TSP-
1 in individuals with type 2 diabetes mellitus (DM), a second independent PBRU cohort (n=99) was
analysed. This included 54 patients with histologically confirmed PDAC, 18 patients with chronic
pancreatitis (CP), 14 healthy control individuals (HC) and 13 patients with long-term (for 5 or more
years)
type 2 DM. Of the PDAC and CP patients, 26 and 9 respectively had confirmed diabetes. The
clinical characteristics of the study populations are provided in Table 1A & B.
Sample collection
UKCTOCS blood samples were collected and processed throughout the trial according to a
standardised SOP (8, 13). Blood was taken in Greiner gel tubes (8 mL separation tubes; Greiner Bio-
one 455071, Stonehouse UK) at one of 13 trial centres, transported overnight at ambient temperature
to a central laboratory, centrifuged at 4,000 rpm for 10 minutes and serum aliquoted and stored in
liquid nitrogen. All UKCTOCS blood samples used in this study were processed within 20 hours of
venepuncture. PBRU blood samples were collected in Sarstedt Monovette tubes (Sarstedt Ltd,
Leicester, UK), placed at 4 °C for 15 min and centrifuged at 800 ×g for 10 min at 4°C. Serum was
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stored in aliquots at
− 80 °C. Preoperative total serum bilirubin (μmol/L) (Roche Mo
dular SWA) and
CA19−9 levels were measured in hospital Clinical Biochemistry Departments, or by CA19-9 ELISA
(Human Pancreatic & GI Cancer ELISA Kit, Alpha Diagnostics International, San Antonio, Texas,
USA).
Murine sample collection
Animals were treated in accordance with European and institutional guidelines (Legislative Order No.
116/92). 129SvJae/B6 H-2Db mice carrying mutated Kras
G12D
and Trp53
R172H
under the endogenous
promoter, and flanked by Lox-STOP-Lox cassettes (LSL-Kras
G12D/+
and LSL-Trp53
R172H/+
). Serum
samples were collected from 10 LSL-Kras
G12D/+
;LSL-Trp53
R172H/+
;Pdx-1-Cre (KPC) mice and 9 age-
matched control (LSL-Trp53
R172H/+
;Pdx-1-Cre) mice via cardiac bleed under isofluorane gaseous
anaesthesia. Blood was collected at 6 weeks, 2 months and 3-6 months and centrifuged at 1000x g
for 20 minutes at room temperature. Serum was collected, snap frozen (in liquid nitrogen) and stored
at -80°C in 60ul aliquots. Mice were surgically and pathologically examined to confirm the presence of
pancreatic tumours and metastases.
iTRAQ analysis
An iTRAQ 8-plex experiment using pooled, delipidated and high abundance protein-depleted serum
from a discovery subset of pre-diagnosis UKCTOCS samples; 0-6 months cases & controls (n=18 per
group), >6-12 months cases & controls (n=17 per group) and PBRU samples; PDAC non obstructed
(n=20), PDAC obstructed (n=20), CP (n=20) and HC (n=20) (total n= 150), was analysed as
described previously(10, 14) on a QSTAR-Pulsar i Hybrid Mass Spectrometer (AB Sciex,
Framingham, USA). Two replicate analyses were also performed on a Triple TOF-5600 (AB Sciex) as
described(15). Data were analysed using ProteinPilot software (Version 4.0, AB Sciex). The clinical
characteristics of the study subset populations are provided in Supplementary Table S1.
Ingenuity Pathway Analysis
A protein list of significantly altered proteins generated from our iTRAQ data was uploaded into
Ingenuity Pathway Analysis (IPA) software server (http://www.ingenuity.com). The iTRAQ dataset was
converted from iTRAQ ratio to fold change and a significance cut-off of P-value <0.05 was utilised.
Both a Core Analysis and Biomarker Filter were performed.
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MRM analysis
Multiple reaction monitoring was carried out on all 150 samples (UKCTOCS n=70; PBRU n=80) used
in iTRAQ discovery alongside 196 additional validation samples (UKCTOCS n=104; PBRU n=92).
MRM analysis on single serum samples was performed on a 5500 QTRAP mass spectrometer
(ABSciex, Framingham, USA) coupled with an Ultimate 3000 HPLC (Dionex-ThermoScientific, UK).
Two target peptides were chosen for TSP-1 and three optimum transitions for each peptide were
determined empirically using synthetic peptides (Peptide Protein Research Limited, Fareham, UK;
See Supplementary Table S2). Corresponding stable-isotope labelled versions of each peptide (C
13
,
N
15
labelled leucine), were used as internal standards with three transitions selected for each.
Standard curves (7 point) were prepared with each peptide from 0.125 fmol to 10 fmol (on-column) in
a peptide digest from human serum (diluted to ~0.25 µg/mL with 2% acetonitrile + 0.1% formic acid),
with subsequent regression analysis showing acceptable linearity (r
2
≥ 0.95). Serum samples (1 µL),
digested overnight with trypsin, were diluted 1 in 6 with a solution containing 2% acetonitrile, 0.1%
formic acid, spiked with the internal standard peptides (to give a final concentration of 50 fmol) and
ionized using a spray voltage of 5500 V and a source temperature of 475 °C. Analyzer parameters
were optimized for each peptide/transition pair to ensure maximum selectivity, dwell time was 50 ms.
Peptide separation was achieved with a Hypersil Gold 50 x 1 mm, 1.9 µm, 175 Å column, using a 20
min gradient, at a flow rate of 100 µL min
-1
, with buffer A (0.1% formic acid) and Buffer B (95%
acetonitrile + 0.1% formic acid). The LC gradient comprised the following: 2% buffer B for 2 min,
ramped to 10% buffer B in 0.1 min, 40% buffer B in 10 min, 80% buffer B in 0.1 min held for 3 min,
and 2% buffer B in 0.1 min held for 5 min. Prior to analysing each batch of serum samples,
chromatographic performance and mass spectrometric stability were evaluated using a tryptic peptide
mixture of beta-galactosidase (Sigma Aldrich, Dorset, UK). Three aliquots of each serum sample was
analysed, each in duplicate with 2 MRM transitions measured for each of 2 peptides (6 readings for
each of 4 MRM transitions), generating a total of 24 MRM readings per sample. The acquired MRM
.wiff files were analysed using MultiQuant™ software (Version 2.1), where peak-area was determined
for each peptide transition and calculated concentrations determined using the software-generated
standard curves. Percentage coefficients of variance (%CV) for each of the 4 MRM transitions were
calculated and those over 25% were excluded. The average CV for the UKCTOCS samples was
17.7% between the 4 MRM transitions and 11.4% for the PBRU samples.
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Western Blot Analysis
For western blotting, individual serum samples were diluted 1:10 and 4 µL of each sample analysed
using anti-TSP-1 A6.1 mouse monoclonal antibody (1:400; Thermoscientifc, Hemel Hempstead, UK).
A standard comprising 20 pooled HC samples was used at three different dilutions per gel, allowing
comparison and quantification across blots. Protein was separated on Any kD™ Mini-PROTEAN®
TGX™ Precast gels (Biorad, Hemel Hempstead, UK), transferred onto PVDF membranes and
blocked for 1
h in 5% milk/PBS Tween (PBST). Primary antibody was incubated overnight at 4 °C in
5
% milk/PBST. Membranes were washed with PBST and incubated with HRP-conjugated secondary
antibodies diluted in 5
% milk/PBST. Bands were visualised with enhanced chemiluminescence
developed with X-ray film. Densitometry was performed (Kodak MI SE software, Carestream Health),
and protein quantities recorded relative to HC standards. All samples were analysed at least in
triplicate.
Immunohistochemistry
Formalin fixed paraffin embedded (FFPE) tissue from 49 PDAC patients was used to construct a
tissue microarray (TMA). Sections were deparaffinised and antigen retrieval was performed using a
PT Link (Dako) with Target Retrieval Solution, High pH (Dako). Anti-TSP-1 A6.1 mouse monoclonal
antibody (1:100; Thermoscientific) was incubated at room temperature for one hour. Positively stained
tumour cells and tumour-associated stroma were identified by a specialist histopathologist.
Data analysis
Statview V.5.01 (SAS Institute Inc., Cary, North Carolina) and Medcalc software (Version 13,
Mariakerke, Belgium) were used. iTRAQ data were compared using the Mann Whitney U test. MRM
and western data were analyzed using the two-tailed Mann Whitney U test and diagnostic accuracy
compared by Receiver Operating Characteristic (ROC) Analyses. Patient immunohistochemistry data
were compared with clinicopathological parameters using Fisher’s exact, Pearson’s chi-squared and
Mann Whitney U tests as appropriate.
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RESULTS
Study Characteristics
No differences in time to centrifugation were observed between case and control samples in any of
the UKCTOCS time to diagnosis groupings. A significant difference was noted in median age of the
36-48 month groups (P=0.01), however a Spearman's rank correlation for comparison of age and
TSP-1 levels showed no significant correlation (Spearman's rank correlation coefficient rho=0.0.03,
P=0.674). Likewise in the PBRU samples a significant difference was seen in age between cancer
patients and controls (P=0.002) but no significant correlation was seen when Spearman’s rank was
performed (Spearman's rank correlation coefficient rho=-0.07, P=0.328). No gender differences in
TSP-1 were found in the PBRU cohort.
Serum iTRAQ analysis
Pooled sera from pre-diagnosis UKCTOCS samples; 0-6 months cases & controls, >6-12 months
cases & controls and PBRU samples; PDAC non-obstructed, PDAC obstructed, CP and HC, were
compared in an 8-plex iTRAQ experiment. To increase the sensitivity of protein detection, high
abundance proteins were depleted from pooled samples prior to labelling with iTRAQ tags. Since the
presence of jaundice can alter serum protein levels (14, 16), PDAC patients were split into those with
and those without obstructive jaundice. The experiment was performed three times, yielding a total of
225 proteins identified using at least two peptides at 95% confidence. Protein expression differences
between groups were assessed by comparing the relative intensity of reporter ions released from
each labelled peptide and calculating protein ratios. A representative dataset is provided in
Supplementary Table S3.
TSP-1 levels are decreased in pooled pre-diagnosis and diagnosed PDAC samples
We sought markers that were altered in the lead into pancreatic cancer diagnosis and in diagnosed
pancreatic cancer patients irrespective of jaundice. Using IPA-Biomarker we compared iTRAQ data
from pre-diagnostic sample pools versus their respective control pools, along with non-obstructed
PDAC patient pools versus HC pools and CP pools, to generate a shortlist of candidates. The high
abundance proteins targeted in our depletion protocols were excluded, along with proteins previously
characterised by our group (10, 17). TSP-1 emerged as a candidate biomarker as its levels were
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reduced with significant fold change differences in case samples in the 0-6 month and 6-12 month
time groups prior to diagnosis as well as in PDAC versus HC PBRU samples taken at diagnosis
(Table 2).
Validation of TSP-1 in individual pre-diagnosis and diagnosed PDAC samples
For the accurate quantification of serum TSP-1 in individual serum samples (n=346), we used a LC-
MS/MS system, operated in MRM mode with stable isotope labelled internal standards. The two
peptides chosen were unique for TSP-1 (Supplementary Figure S1A) allowing unambiguous
discrimination from other thrombospondin family members. The lower limit of detection of the assay
was 0.1 fmol/µL and where TSP-1 fell below detection, the level was arbitrarily assigned a value of
zero. When all 87 pre-diagnostic cases, covering up to 48 months prior to diagnosis, were compared
with their time-matched controls, TSP-1 levels were significantly lower in cases versus (P<0.001;
Figure 1 A). Separating samples into their individual time to diagnosis groups revealed TSP-1 levels
were significantly reduced compared to time matched controls in the 0-6 month, (P =0.04), 6-12
month (P=0.004) and 12-24 month (P=0.03) cases (Figure 1 B). Significantly lower levels of TSP-1
were observed in PDAC patients in the presence (P=0.02) and in the absence (P=0.03) of jaundice
compared to healthy subjects and compared to patients experiencing biliary obstruction due to
gallstones (BBO: P=0.01 and P=0.05 respectively) (Figure 1 C). By contrast, no significant difference
in TSP-1 level was established between patients with CP (Figure 1 C). Furthermore, we could not
establish any difference between levels of TSP-1 in resectable PDAC cases versus non resectable
cases (Supplementary Figure S2).
Western blotting using a mouse monoclonal (A6.1) antibody for TSP-1 revealed a single band in
human foreskin fibroblast (HFF) cells, which was not detected following treatment with TSP-1-
targeting siRNA (Supplementary Figure S1B). The banding pattern obtained in pre-diagnosis and
diagnosed serum samples with this antibody is shown in Supplementary Figure S1B. Weak, although
significant correlations for TSP-1 in MRM and western measures were observed in pre-diagnosis
samples (n=128; Spearman's rank correlation coefficient rho=0.29, P=0.005) and diagnosed samples
(n=199; Spearman's rank correlation coefficient rho=0.48, P=0.0001). Semi–quantitative western
analysis confirmed a significant decrease in the 6-12 month pre-diagnosis samples (n=17) versus
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controls (n=17, p=0.03) and in diagnosed PDAC patients in the presence (n=48; p=0.001) and
absence (n=49; p=0.0007) of jaundice compared to healthy subjects (n=42).
Corresponding CA19-9 data for the pre-diagnosis and diagnosed PDAC samples are presented in
Supplementary Figures S2 A and B respectively. CA19-9 levels were significantly up-regulated in in
the 0-6 month pre-diagnosis cases compared to controls (p=0.001), in the 6-12 month pre-diagnosis
cases compared to controls (p=0.04), in patients with PDAC in the presence and absence (P=0.0001)
of biliary obstruction compared to HC (P=0.001 and P=0.0001, respectively) and CP (both P=0.0001),
consistent with our previous observations (12).
Validation of TSP-1 in murine samples
Low TSP-1 serum levels were observed in LSL-Kras
G12D/+
;LSL-Trp53
R172H/+
;Pdx-1-Cre (KPC) mice
with cancer, compared to KPC mice with high or low grade PanIN and compared to age-matched
control (LSL-Trp53
R172H/+
;Pdx-1-Cre) mice (Figures 1 D and E).
Low TSP-1 levels correlate with poor outcome
Next we examined the relationship between circulating TSP-1 levels and survival. For this analysis,
TSP-1 levels equal to the 25
th
percentile (0.00 fmol/µL) were classified as low with the remaining
values classified as high. The preclinical levels of TSP-1, up to 24 months prior to diagnosis were
associated with a significantly reduced survival time from diagnosis (Figure 2 A; logrank χ
2
1
=3.7
p=0.05). Only diagnosed patients with resectable disease (n=75) were included and the median
survival of these patients with low circulating TSP-1 was significantly lower than those with high TSP-
1 (Figure 2 B; logrank χ
2
1
=4.27 P=0.04).
Ability to distinguish pre-diagnosis cases from controls
While our work was in progress, Nie et al (18) reported that TSP-1 provided AUCs of 0.78 and 0.83
for the discrimination of clinically diagnosed PDAC from HC and CP respectively. In samples up to 24
months prior to diagnosis (Figure 2 C), we found that TSP-1 distinguished cases from controls with an
AUC of 0.69. During this time period, CA19-9 yielded an AUC of 0.77. The combination of both
markers achieved a significantly higher AUC of 0.85 (p=0.02; Figure 2 C).
TSP-1 levels do not relate to platelet count
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TSP-1 was identified as a molecule released from platelets in response to thrombin treatment (19).
Concerned that fluctuations in circulating TSP-1 may reflect changes in blood platelet levels, we
correlated PDAC patient platelet count (n=96 PDAC patients) with TSP-1 levels. The median platelet
count was 293 x10
9
/L, but was significantly elevated in patients with advanced cancer (n=20; count
344 x10
9
/L), compared to resectable cancer (n=76; count 277 x10
9
/L; p=0.02). No significant
correlation was detected between TSP-1 levels and platelet count in either resectable (Spearman
Rank rho= 0.01, p=0.88) or in advanced patients (rho= -0.13, p=0.57).
TSP-1 serum levels are associated with diabetes mellitus
Although TSP-1 levels were significantly lower in cancer patients than controls (Figure 1 C), not all
cancer patients had reduced levels. We therefore hypothesised that the marker may be regulated in a
sub-set of patients only and examined for associations between circulating TSP-1 levels and
clinicopathologic parameters, separating PDAC patients into low or high for TSP-1 based on
circulating TSP-1 values < or ≥ the median (0.267 fmol/µL). Associations could not be established
between gender, age at surgery, presence of obstructive jaundice, operable versus advanced,
resection margin status, T stage or nodal status (Supplementary Table S4). However, the presence of
diabetes in PDAC patients was significantly associated with TSP-1 (Chi-squared test, P=0.02,
Supplementary Table S4). Examining this further, of 27 patients with confirmed diabetes, 19 (70.3%)
had less than the median level of TSP-1 (14 of those patients had undetectable TSP-1). By contrast,
of the remaining 71 patients without confirmed diabetes, only 30 (42.2%) had less than the median
serum TSP-1 level (Chi-squared test, P=0.01). Upon separating our clinically diagnosed PDAC
patients into those with- and without-diabetes, a significant reduction in TSP-1 levels were observed
for the PDAC patients with diabetes compared to all other control groups (Figure 3A). Finally, given
the correlation between diabetes and TSP-1, we examined whether diabetes was associated with
outcome in this cohort, but no association was observed (Figure 3 B; logrank χ
2
1
=1.53 P=0.22).
PDAC related diabetes often goes undiagnosed (20); it is therefore unsurprising that only 10% of
UKCTOCS cases were recorded as having diabetes. Since a substantial number of UKCTOCS cases
probably had occult diabetes or glucose intolerance, no analysis was undertaken for this cohort.
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TSP-1 serum levels are lower in PDAC patients with diabetes compared to individuals with
long-term type 2 diabetes mellitus
Measurement of TSP-1 levels by western blot in an independent cohort confirmed our previous
observation that significantly lower levels of TSP-1 are present in PDAC patients with diabetes
compared to PDAC patients without diabetes (P=0.002), healthy subjects (P<0.0001) and CP patients
(P=0.05); Figure 4). Significantly lower levels were also observed in PDAC patients with diabetes
compared to individuals with long term type 2 DM (P=0.01).
TSP-1 tumour expression is not associated with diabetes mellitus
To determine whether tumour levels of TSP-1 were associated with diabetes mellitus, a PDAC TMA
was stained for TSP-1 (Figure 3 C). Tumour cell staining was observed in 7/49 cases (14%) while 8
patients (16%) expressed TSP-1 in desmoplastic stroma. Two patients (4%) were positive for both
tumour and stromal staining. Thirty-two (65%) patients lacked detectable tissue TSP-1 expression.
Associations could not be established between TSP-1 expression and other clinicopathological
parameters, including diabetes (Supplementary Table S5). This remained true when expression was
categorised as either tumoural or stromal.
Discussion
Previous serum biomarker studies have carried out discovery work on samples taken from patients
after a diagnosis of PDAC has been made (11, 29, 30, 31, 32), thereby potentially missing critical
changes to the serum disease profile that occur months and years prior to diagnosis. Our study is
virtually unique in that we have simultaneously subjected pre-clinical and clinical samples to a
proteomic biomarker discovery protocol and identified a protein of interest, TSP-1, that appeared
altered before and after diagnosis, highlighting its potential as an early biomarker. We used MRM in
this study to verify these changes in individual serum samples as it afforded unequivocal identification
and accurate quantification of TSP-1 by selecting peptides unique to the TSP-1 protein. We saw
similar trends in reduction of TSP-1 levels using an antibody-based approach. However cross-
reaction between the antibody used in our study and TSP-2 cannot be ruled out (21) and might
explain differences between MRM and western data. TSP-1 is a large secreted multimeric
matricellular protein (22), whose role in cancer is controversial. TSP-1 has been described as anti-
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15
carcinogenic due to its potent anti-angiogenic properties, mediated in large part through binding to
CD36 (fatty acid translocase; FAT) and CD47 (integrin-associated protein; IAP) and its role in
activation of TGF-beta (23). Serum levels of TSP-1 are decreased in patients with prostate cancer
(24) and lung cancer (25)
,
(26), while plasma levels of TSP-1 are elevated in breast cancer patients
(27). In pancreatic cancer, serum TSP-1 levels were found to be significantly increased in patients
with unresectable cancer (28), although we could not establish any difference between levels in
unresectable versus resectable pancreatic cancer patients. Our analysis of TSP-1 expression in
pancreatic cancer tissue did not help explain the reduction in the circulating levels of TSP-1 in PDAC
patients. Currently, we cannot propose a mechanism for our observations.
As we have previously reported, the presence of jaundice, a late symptom in PDAC patients, can
influence biomarker levels (14, 16). Potential markers that are not affected by jaundice are more likely
to be indicative of early disease. We allowed for this here by separately analysing PDAC samples
taken from diagnosed patients in the presence versus absence of jaundice. The reduction of TSP-1
levels in patients’ serum, regardless of the presence of jaundice, distinguished it from previous
candidates evaluated by our group (10) and made it an attractive candidate for early diagnosis.
Consistent with our findings, others have reported lower circulating TSP-1 levels in PDAC patients
compared to healthy controls (18, 28). Here we go further by showing significant reduction of TSP-1
levels in patients up to 24 months prior to diagnosis of pancreatic cancer. We recently showed that
CA19-9 discriminated preclinical PDAC cases from controls (12). Combining TSP-1 and CA19-9
offered a significant improvement over either marker alone. Our analysis of serum from KPC mice
provided evidence for a decrease in circulating TSP-1 in mice with PDAC, but not in mice with PanIN
lesions. This raises the question as to whether the decreases in TSP-1 observed in pre-diagnostic
UKCTOCS cases are occurring in a background of already formed PDAC. Further study is required to
unravel this question.
Upon separating our PDAC patients into those with and without diabetes we found that levels of TSP-
1 were significantly reduced in clinically diagnosed PDAC patients with diabetes compared to all
control groups, including individuals with long-term type 2 DM. Our findings therefore suggest a link
between reduced serum TSP-1 levels and PDAC-associated diabetes (type III C). Pannala et al.
reported that 85% of PDAC patients have hyperglycaemia or diabetes with some 47% having
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16
diabetes (20). In our study, only 27% of diagnosed PDAC patients had confirmed diabetes, which is
likely to be an underestimate. TSP-1 has been shown to be an adipokine, associated with insulin
resistance (29). Moreover, TSP-1-null mice are markedly glucose intolerant and have decreased
glucose-stimulated insulin release and capacity for (pro)insulin biosynthesis, although they possess
an increased beta-cell mass (30). This phenotype was attributed to the lack of activation of islet
TGFβ-1 by endothelial-derived TSP-1. Failure of glucose regulation may occur before a rise in CA19-
9, perhaps explaining why TSP-1 adds to CA19-9 in discriminating early disease. More work is
needed to uncover the true extent of the relationship between TSP-1 and diabetes in PDAC patients,
and to determine whether TSP-1 might serve as a PDAC screening tool in individuals newly
diagnosed with type 2 DM. Aggarwall et al. (31) reported elevated plasma levels of adrenomedullin in
PDAC patients with new-onset DM compared to PDAC patients with normal fasting glucose and
compared to non-cancer subjects with new-onset type DM.
Limitations of this study include using pooled samples for iTRAQ profiling as this is sensitive to
outliers and can lead to false positives. Extensive validation was therefore undertaken using both
individual samples of the iTRAQ set and also independent samples. It is possible that the delay of
processing in UKCTOCS samples may have led to the loss of some proteins. In addition, it was not
possible to evaluate longitudinal preclinical alterations in TSP-1 as the number of UKCTOCS cases
with available longitudinal samples was insufficient to adequately assess this. Finally, as mentioned
above, the number of individuals with diabetes in our PBRU cancer cohort is likely to be
underestimated, and accurate diabetes data were only available for a small number of UKCTOCS
cases, preventing sensible evaluation of TSP-1 levels and diabetes in the preclinical setting.
In conclusion, our study allowed a valuable appraisal of TSP-1 levels during the lead into pancreatic
cancer diagnosis, demonstrating that its inclusion in diagnostic panels could have potential in early
detection strategies. We have also highlighted the effect diabetes can have on the performance of
potential biomarkers and have shown its influence should be controlled for in future biomarker
studies.
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17
TABLE AND FIGURE LEGENDS:
Table 1A). Patients Characteristics of UKCTOCS pre-diagnostic cases and controls for whole study
set and 1B) Patients Characteristics of PBRU diagnosed PDAC samples and controls for whole study
set.
Table 2. IPA Biomarker Filter Analysis from iTRAQ data set.
Figure 1. Detection of thrombospondin 1 (TSP-1) by MRM in (A) all pre-diagnostic samples versus
controls, (B) in individual time to diagnosis groups, (C) in diagnosed samples and controls (PDAC obs
= bilirubin >20µmol/L, presence of jaundice; PDAC non-obs = bilirubin <20µmol/L, absence of
jaundice; CP = chronic pancreatitis, BBO = benign biliary obstruction, HC = healthy control) and (D)
genetically engineered mice (PanIN = pancreatic intraepithelial neoplasia (pre-neoplastic lesion). Low
grade = PanIN I or II, High grade = PanIN III).
Figure 2. Survival curves for TSP-1 in (A) pre-diagnosis and (B) diagnosed patients (low levels =0.00
fmol/µL, (C) Performance of TSP-1, based on MRM measurements, to discriminate 0-24 month pre-
diagnostic patients (n=64) from time matched controls (n=64).
Figure 3. TSP-1 is associated with diabetes in diagnosed samples compared to all other groups (A),
Diabetes mellitus does not relate to outcome (B), TSP-1 staining in PDAC tissue samples (C).
Figure 4. Detection of thrombospondin 1 (TSP-1) by western analysis in an independent cohort of
diagnosed samples and controls (CP = chronic pancreatitis, HC = healthy control).
.
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18
References
1. Siegel R, Naishadham D, Jemal A. Cancer statistics, 2013. CA Cancer J Clin. 2013;63:11-30.
2. Locker GY, Hamilton S, Harris J, Jessup JM, Kemeny N, Macdonald JS, et al. ASCO 2006
Update of Recommendations for the Use of Tumor Markers in Gastrointestinal Cancer. J Clin Oncol.
2006;24:5313-27.
3. Wong D, Ko AH, Hwang J, Venook AP, Bergsland EK, Tempero MA. Serum CA19-9 decline
compared to radiographic response as a surrogate for clinical outcomes in patients with metastatic
pancreatic cancer receiving chemotherapy. Pancreas. 2008;37:269-74.
4. Marrelli D, Caruso S, Pedrazzani C, Neri A, Fernandes E, Marini M, et al. CA19-9 serum levels
in obstructive jaundice: clinical value in benign and malignant conditions. Am J Surg. 2009;198:333-9.
5. Costello E, Greenhalf W, Neoptolemos JP. New biomarkers and targets in pancreatic cancer
and their application to treatment. Nat Rev Gastroenterol Hepatol. 2012.
6. Jenkinson C, Earl J, Ghaneh P, Halloran C, Carrato A, Greenhalf W, et al. Biomarkers for early
diagnosis of pancreatic cancer. Expert Rev Gastroenterol Hepatol. 2014:1-11.
7. Menon R, Zhang Q, Zhang Y, Fermin D, Bardeesy N, DePinho RA, et al. Identification of novel
alternative splice isoforms of circulating proteins in a mouse model of human pancreatic cancer.
Cancer research. 2009;69:300-9.
8. Menon U, Gentry-Maharaj A, Ryan A, Sharma A, Burnell M, Hallett R, et al. Recruitment to
multicentre trials--lessons from UKCTOCS: descriptive study. BMJ. 2008;337:a2079.
9. Ross PL, Huang YN, Marchese JN, Williamson B, Parker K, Hattan S, et al. Multiplexed protein
quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol Cell
Proteomics. 2004;3:1154-69.
10. Tonack S, Jenkinson C, Cox T, Elliott V, Jenkins RE, Kitteringham NR, et al. iTRAQ reveals
candidate pancreatic cancer serum biomarkers: influence of obstructive jaundice on their
performance. British journal of cancer. 2013;108:1846-53.
11. Addona TA, Abbatiello SE, Schilling B, Skates SJ, Mani DR, Bunk DM, et al. Multi-site
assessment of the precision and reproducibility of multiple reaction monitoring-based
measurements of proteins in plasma. Nat Biotechnol. 2009;27:633-41.
12. O'Brien DP, Sandanayake NS, Jenkinson C, Gentry-Maharaj A, Apostolidou S, Fourkala EO, et
al. Serum CA19-9 is significantly up-regulated up to 2 years prior to diagnosis with pancreatic cancer:
implications for early disease detection. Clin Cancer Res. 2014.
13. Menon U, Gentry-Maharaj A, Hallett R, Ryan A, Burnell M, Sharma A, et al. Sensitivity and
specificity of multimodal and ultrasound screening for ovarian cancer, and stage distribution of
detected cancers: results of the prevalence screen of the UK Collaborative Trial of Ovarian Cancer
Screening (UKCTOCS). Lancet Oncol. 2009;10:327-40.
14. Tonack S, Aspinall-O'Dea M, Jenkins RE, Elliot V, Murray S, Lane CS, et al. A technically
detailed and pragmatic protocol for quantitative serum proteomics using iTRAQ. Journal of
proteomics. 2009;73:352-6.
15. Walsh J, Jenkins RE, Wong M, Olayanju A, Powell H, Copple I, et al. Identification and
quantification of the basal and inducible Nrf2-dependent proteomes in mouse liver: Biochemical,
pharmacological and toxicological implications. Journal of proteomics. 2014;108C:171-87.
16. Yan L, Tonack S, Smith R, Dodd S, Jenkins RE, Kitteringham N, et al. Confounding effect of
obstructive jaundice in the interpretation of proteomic plasma profiling data for pancreatic cancer.
Journal of proteome research. 2009;8:142-8.
17. Jenkinson C, Elliott V, Menon U, Apostolidou S, Fourkala OE, Gentry-Maharaj A, et al.
Evaluation in pre-diagnosis samples discounts ICAM-1 and TIMP-1 as biomarkers for earlier diagnosis
of pancreatic cancer. Journal of proteomics. 2014;113C:400-2.
18. Nie S, Lo A, Wu J, Zhu J, Tan Z, Simeone DM, et al. Glycoprotein biomarker panel for
pancreatic cancer discovered by quantitative proteomics analysis. Journal of proteome research.
2014;13:1873-84.
Research.
on December 7, 2015. © 2015 American Association for Cancerclincancerres.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.
Author Manuscript Published OnlineFirst on November 16, 2015; DOI: 10.1158/1078-0432.CCR-15-0879
19
19. Lawler JW, Slayter HS, Coligan JE. Isolation and characterization of a high molecular weight
glycoprotein from human blood platelets. J Biol Chem. 1978;253:8609-16.
20. Pannala R, Leirness JB, Bamlet WR, Basu A, Petersen GM, Chari ST. Prevalence and clinical
profile of pancreatic cancer-associated diabetes mellitus. Gastroenterology. 2008;134:981-7.
21. Annis DS, Murphy-Ullrich JE, Mosher DF. Function-blocking antithrombospondin-1
monoclonal antibodies. J Thromb Haemost. 2006;4:459-68.
22. Henkin J, Volpert OV. Therapies using anti-angiogenic peptide mimetics of thrombospondin-
1. Expert Opin Ther Targets. 2011;15:1369-86.
23. Miyata Y, Sakai H. Thrombospondin-1 in urological cancer: pathological role, clinical
significance, and therapeutic prospects. Int J Mol Sci. 2013;14:12249-72.
24. Lu JC, Ye DW, Li WZ, Du LH, Jin W, Lu XQ, et al. [Supplemental role of thrombospondin-1 in
the diagnosis of prostate cancer]. Zhonghua Yi Xue Za Zhi. 2013;93:252-5.
25. Dudek AZ, Mahaseth H. Circulating angiogenic cytokines in patients with advanced non-small
cell lung cancer: correlation with treatment response and survival. Cancer investigation.
2005;23:193-200.
26. Bigbee WL, Gopalakrishnan V, Weissfeld JL, Wilson DO, Dacic S, Lokshin AE, et al. A
multiplexed serum biomarker immunoassay panel discriminates clinical lung cancer patients from
high-risk individuals found to be cancer-free by CT screening. J Thorac Oncol. 2012;7:698-708.
27. Suh EJ, Kabir MH, Kang UB, Lee JW, Yu J, Noh DY, et al. Comparative profiling of plasma
proteome from breast cancer patients reveals thrombospondin-1 and BRWD3 as serological
biomarkers. Exp Mol Med. 2012;44:36-44.
28. Brand RE, Nolen BM, Zeh HJ, Allen PJ, Eloubeidi MA, Goldberg M, et al. Serum biomarker
panels for the detection of pancreatic cancer. Clin Cancer Res. 2011;17:805-16.
29. Varma V, Yao-Borengasser A, Bodles AM, Rasouli N, Phanavanh B, Nolen GT, et al.
Thrombospondin-1 is an adipokine associated with obesity, adipose inflammation, and insulin
resistance. Diabetes. 2008;57:432-9.
30. Olerud J, Mokhtari D, Johansson M, Christoffersson G, Lawler J, Welsh N, et al.
Thrombospondin-1: an islet endothelial cell signal of importance for beta-cell function. Diabetes.
2011;60:1946-54.
31. Aggarwal G, Ramachandran V, Javeed N, Arumugam T, Dutta S, Klee GG, et al.
Adrenomedullin is Up-regulated in Patients With Pancreatic Cancer and Causes Insulin Resistance in
β Cells and Mice. Gastroenterology. 2012;143:1510-7.e1.
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Figure 1
High
grade
PanIN
n=1
Low
grade
PanIN
n=6
Normal
Pancreas
n=9
PDAC
n=3
PDAC
HC
PDAC
HC
PDAC
HC
PanIN
PanIN
PanIN
PanIN III
HC
HC
HC
TSP-1
TSP-1( relative density)
C. D.
A. B.
Case
(n=87)
Control
(n=87)
p<0.001
E.
Discovery
Validation
case
(n=30)
ctrl
(n=30)
case
(n=17)
ctrl
(n=17)
case
(n=11)
ctrl
(n=11)
case
(n=12)
ctrl
(n=12)
case
(n=17)
ctrl
(n=17)
0-6m 12-24m 24-36m 36-48m 6-12m
p=0.04 p=0.004 p=0.03
0.0
2.0
4.0
6.0
8.0
BBO
(n=20)
CP
(n=29)
HC
(n=25)
PDAC
obs
(n=49)
PDAC
non-obs
(n=49)
p=0.05
p=0.01
p=0.02
p=0.03
TSP-1 (fmol/µl)
0.0
1.0
2.0
3.0
4.0
5.0
Discovery
Validation
TSP-1 (fmol/µl)
TSP-1 (fmol/µl)
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0 200 400 600 800 1000
0
20
40
60
80
100
Time (days)
UKCTOCS Survival probability (%)
High levels of TSP1
Low levels of TSP1
At risk
25 14 9 4 2 0
9 2 0 0 0 0
p=0.05
At risk
46 27 12 6
0
30 8 3 1
0
0 500 1000 1500 2000 2500
0
20
40
60
80
100
Time (days)
PBRU Survival probability (%)
High levels of TSP1
Low levels of TSP1
4
1
p=0.03
Figure 2
A. B.
Pre-diagnosis 0-24 m
100-Specificity
Sensitivity
0 20 40 60 80 100
0
20
40
60
80
100
TSP-1 (0.69)
CA19-9 (0.77)
TSP-1 + CA19-9 (0.86)
C.
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Negative PDAC Positive PDAC Positive stroma
TSP-1
100mm 100mm 100mm
Diabetic
control
(n=8)
HC
non-diabetic
(n=25)
PDAC
non-diabetic
(n=71)
PDAC
diabetic
(n=27)
BBO
(n=17)
CP
(n=24)
p=0.01
p=0.009
p=0.04
p=0.04
p=0.002
PDAC diabetes
PDAC no diabetes
p=0.24
0 500 1000 1500 2000 2500
0
20
40
60
80
100
Time (days)
Survival probability (%)
At risk
22 7 3 1 1 0
54 28 12 6 4 0
Figure 3
TSP-1 (fmol/µl)
A. B.
C.
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Long term
Type 2
diabetic
(n=13)
HC
non-diabetic
(n=14)
PDAC
non-diabetic
(n=26)
PDAC
diabetic
(n=26)
CP
(n=9)
CP
diabetic
(n=9)
TSP-1 (relative density)
p=0.01
p<0.0001
p=0.002
p=0.05
p=0.03
Figure 4
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Table 1a) Patients Characteristics of UKCTOCS pre-diagnostic cases and controls for whole study set
0-6m 6-12m 12-24m 24-36m 36-48m
cases ctrls cases ctrls cases ctrls cases ctrls cases ctrls
n 30 30 17 17 17 17 11 11 12 12
Median Age (y)
(IQR)
66.9
(60.9-70.8)
64.7
(58.2-69.2)
68.3
(59.2-70.6)
67.4
(60.3-71.7)
62.9
(59.1-68.5)
60.8
(55.1-67.1)
62.4
(59-69.9)
60.2
(52.9-67.8)
65.8
(60.5-71)
57.4
(55.6-61.4)
Mean time
f
rom sample collection to
diagnosis (days)
(IQR)
91.5
(49.5-
152.6)
n/a
282.9
(243.5-
314.4)
n/a
535.6
(476.3-
684.5)
n/a
853.4
(814-
944.5)
n/a
1288.9
(1197-
1344)
n/a
Mean time to spin (hours)
(IQR)
21.3
(19.3-23.1)
21.0
(19.2-23.3)
21.0
(19.8-22.5)
20.8
(19.7-23.1)
22.7
(20.5-23.6)
22.7
(20.3-23.6)
22.2
(20.6-24.6)
21.7
(20.4-24.5)
23.6
(20.8-24.9)
22.7
(20.6-24.5)
Abbreviations: ctrls - controls; IQR - interquartile range.
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Table 1b) Patients Characteristics of PBRU diagnosed PDAC samples and controls for whole study set
PBRU cohort 1 PBRU cohort 2
PDAC non-obs PDAC obs HC CP BBO PDAC PDAC
(w/diabetes)
HC Type II
diabetics
CP CP
(w/diabetes)
n 49 49 42 39 20 26 26 14 13 9 9
Median Age
(IQR)
67
(60-73)
66
(62.8-72)
30.5
(25-37.8)
50
(43-60)
65.5
(56.8-75.3)
71
(63-73)
70
(65-74)
56
(53-60)
67
(62-75)
46
(44-59)
54
(46-59)
Gender F/M 28/21 26/23 20/22 20/19 5/15 16/12 9/17 7/7 7/6 3/6 2/7
Diabetes 14 13 n/a 5 3 - 26 - 13 - 9
Resection Margin R0 10 11 - - - 5 6 - - - -
R1 24 26 - - - 16 14 - - - -
U 3 2 - - - 1 - - - - -
I 12 10 4 6
Staging IA 1 - - - - 2 1 - - - -
IB - 1---- - --- -
IIA 6 6 - - - 3 6 - - - -
IIB 28 30 - - - 16 12 - - - -
III/IV 12 10 - - - 4 7 - - - -
U 2 2 - - - 1 - - - - -
Abbreviations: BBO - benign biliary obstruction; CP - chronic pancreatitis; F - female; HC – healthy control; I – Inoperable; IQR -interquartile range; M - male; obs –
obstruction;
PDAC - pancreatic ductal adenocarcinoma; U - unknown
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Table 2. IPA Biomarker Filter Analysis from iTRAQ data set
Data Set Symbol Entrez Gene Name
Fold
Change
p-
value
0-6m
case ‘v’ ctrls
APOE apolipoprotein E -6.54 0.017
HP haptoglobin 1.42 0.000
KRT6B keratin 6B 3.56 0.039
TSP-1 thrombospondin 1 -2.09 0.010
6-12m
case ‘v’ ctrls
FN1 fibronectin 1 -1.08 0.000
ICAM1
intercellular adhesion
molecule 1
-1.51 0.004
KRT6B keratin 6B -5.55 0.038
SERPINA1
serpin peptidase inhibitor,
clade A member 1
-1.21 0.002
TSP-1 thrombospondin 1 -4.49 0.042
PDAC non
obs ‘v’ HC
APOE apolipoprotein E 8.40 0.005
CRP
C-reactive protein, pentraxin-
related
52.96 0.031
FGA fibrinogen alpha chain -10.19 0.042
FN1 fibronectin 1 -1.14 0.000
HP haptoglobin -1.06 0.002
ICAM1
intercellular adhesion
molecule 1
35.65 0.003
KRT6B keratin 6B -2.63 0.004
LGALS3BP
lectin, galactoside-binding,
soluble, 3 binding protein
2.47 0.038
MCAM
melanoma cell adhesion
molecule
-4.29 0.001
NCAM1
neural cell adhesion molecule
1
-2.13 0.030
PLG plasminogen 2.75 0.013
SERPINA1
serpin peptidase inhibitor,
clade A member 1
1.29 0.008
TSP-1 thrombospondin 1 -4.97 0.032
PDAC non
obs ‘v’ CP
APOA1 apolipoprotein A-I 32.21 0.000
APOE apolipoprotein E 32.81 0.000
FGA fibrinogen alpha chain -24.66 0.007
FN1 fibronectin 1 1.03 0.011
HP haptoglobin -1.82 0.000
ICAM1
intercellular adhesion
molecule 1
42.46 0.003
KRT6B keratin 6B -1.91 0.005
MCAM
melanoma cell adhesion
molecule
-4.29 0.001
NCAM1
neural cell adhesion molecule
1
-1.26 0.033
SERPINA1
serpin peptidase inhibitor,
clade A member 1
1.20 0.000
Research.
on December 7, 2015. © 2015 American Association for Cancerclincancerres.aacrjournals.org Downloaded from
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Author Manuscript Published OnlineFirst on November 16, 2015; DOI: 10.1158/1078-0432.CCR-15-0879
Published OnlineFirst November 16, 2015.Clin Cancer Res
Claire Jenkinson, Victoria Elliott, Anthony Evans, et al.
with diabetes mellitus
patients up to 24 months prior to clinical diagnosis: association
Decreased serum thrombospondin-1 levels in pancreatic cancer
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on December 7, 2015. © 2015 American Association for Cancerclincancerres.aacrjournals.org Downloaded from
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