JO U R N A L OF PR O TE O MI CS 85 ( 20 1 3 ) 4 4 –52
Available online at www.sciencedirect.com
www.elsevier.com/locate/jprot
Complement C3f serum levels may predict breast cancer risk in
women with gross cystic disease of the breast
Aldo Profumoa, 1 , Rosa Mangerinib, 1 , Alessandra Rubagottib, c , Paolo Romanoa ,
Gianluca Damonted , Pamela Guglielminic , Angelo Facchianoe , Fabio Ferri f , Francesco Riccic ,
Mattia Roccoa , Francesco Boccardob, c,⁎
a
Biopolymers and Proteomics Unit, IRCCS AOU San Martino-IST (San Martino University Hospital and National Cancer Research Institute), Genoa, Italy
Academic Unit of Medical Oncology (Medical Oncology B), IRCCS AOU San Martino—IST (San Martino University Hospital and National
Cancer Research Institute), Genoa, Italy
c
Department of Internal Medicine, School of Medicine, University of Genoa, Genoa, Italy
d
Department of Experimental Medicine and Center of Excellence for Biomedical Research (CEBR), School of Medicine, University of Genoa, Genoa, Italy
e
Bioinformatics, Institute of Food Sciences, National Research Council, Avellino, Italy
f
Department of Science and High Technology, Insubria University, Como, Italy
b
AR TIC LE I N FO
ABS TR ACT
Article history:
Gross cystic disease (GCDB) is a breast benign condition predisposing to breast cancer.
Received 30 January 2013
Cryopreserved sera from GCDB patients, some of whom later developed a cancer (cases), were
Accepted 13 April 2013
studied to identify potential risk markers. A MALDI-TOF mass spectrometry analysis found
several complement C3f fragments having a significant increased abundance in cases
compared to controls. After multivariate analysis, the full-length form of C3f maintained a
Keywords:
predictive value of breast cancer risk. Higher levels of C3f in the serum of women affected by a
Complement C3f
benign condition like GCDB thus appears to be correlated to the development of breast cancer
Serum
even 20 years later.
Peptidome profile
MALDI-TOF
Biological significance
Breast cancer risk
Increased complement system activation has been found in the sera of women affected by GCDB
who developed a breast cancer, even twenty or more years later. C3f may predict an increased
breast cancer risk in the healthy population and in women affected by predisposing conditions.
© 2013 Elsevier B.V. All rights reserved.
1.
Introduction
One of the most relevant problems in breast cancer prevention
is how to identify the women who might be at higher risk of
developing this disease and, therefore, who might gain the
greatest benefit from periodic surveillance with new imaging
technologies or from chemoprevention measures. Gross cystic
disease of the breast (GCDB) is a common benign disease of
the mammary gland, affecting some 7% of women in Western
countries [1]. It is associated with a 2–4 fold increased risk of
developing breast cancer, probably as a consequence of the
evolution of the proliferative epithelial changes which are
commonly associated with this benign condition [2]. Though
breast cancer risk appears to be associated with cyst type and
the intracystic level of steroids or growth factors [3–5], so far no
specific serum risk marker has been reported yet in the women
affected by GCDB. To this end, proteomic studies could be quite
informative, especially when nanotechnologies are applied.
⁎ Corresponding author at: Academic Unit of Medical Oncology (Medical Oncology B), IRCCS AOU San Martino—IST, Largo Rosanna Benzi
10, Genoa, 16132, Italy. Tel.: + 39 010 5600 560.
E-mail address: fboccardo@unige.it (F. Boccardo).
1
These authors contributed equally to this work.
1874-3919/$ – see front matter © 2013 Elsevier B.V. All rights reserved.
http://dx.doi.org/10.1016/j.jprot.2013.04.029
JO U R N A L OF P ROTE O MI CS 8 5 ( 20 1 3 ) 4 4–5 2
In particular, mass spectrometry (MS) is well suited for the
detection of low molecular weight proteins or peptides that
might not be detectable with traditional techniques, and that
might well represent a dynamic reflection of tissue function.
A few studies have addressed the possibility of applying a
proteomic approach to the analysis of cyst fluid or nipple
aspirates in the diagnosis of breast cancer [6–8]; more encouraging results have been achieved by applying these techniques to
the study of the serum peptidome of women diagnosed with
breast cancer or to follow disease outcome of patients after
breast surgery [9–11]. In particular, Villanueva et al. [12] identified
specific degradation patterns associated with breast cancer and
able to generate proteomic signatures potentially useful to
diagnose this disease. However, so far just a few studies used
biological fluids, collected before breast cancer diagnosis, in
proteomic profiling approaches to this disease. Namely, Opstalvan Winden et al. [13] performed a serum surface-enhanced
laser desorption/ionization (SELDI)-time of flight (TOF) analysis
at the peptidome level and identified two signals, of m/z 3323 and
m/z 8938 respectively, able to identify the women subsequently
developing a breast cancer up to three years before cancer was
diagnosed. These findings, though preliminary, prompted us to
investigate the possible association of serum peptidome profiles
with breast cancer risk in a group of women diagnosed with
GCDB but followed for a much longer period of time (up to 20 or
more years since blood collection). On the basis of preliminary
work on the matrix assisted laser desorption/ionization (MALDI)TOF MS analysis of cryopreserved sera of a group of healthy
donors [14], we have begun by analyzing the sera of a group of
women diagnosed with GCDB even twenty or more years before
developing breast cancer and those of an appropriately matched
group of comparable women who were still breast cancer-free by
the same date limit. The results of this analysis form the object of
the present article.
2.
Materials and methods
2.1.
Study design and ethical aspects
Serum samples were obtained from 600 patients affected by
GCDB at the time of first cyst aspiration. Samples were collected
between 1985 and 1993, and stored at −80 °C. A proportion of
these women were followed up at our institution and a few of
them have been found to have developed a breast cancer. Many
more were lost to follow-up and were diagnosed with breast
cancer at other hospitals. Information about the destiny of
these women in relation to the development of a breast cancer
was obtained by consulting the Genoa Tumor registry.
At the date limit of December 31th 2010, fifty out of 600
women were found to have developed a breast cancer but
for only thirty women a number of serum aliquots adequate
to be processed for the purposes of the present research were
available. In fact a large subgroup of the original cohort
had been enrolled in previous sera-epidemiological studies
and no residual serum aliquots were available any longer for
them. Data concerning women reproductive history and family
history of breast cancer had been recorded at the time of clinical
examination. The thirty women developing a breast cancer
following first cyst aspiration and for whom an adequate
45
number of serum aliquots was actually available served as
cases. These women were individually matched (according to a
1:2 ratio) with 60 women who, by the same date limit, were still
breast cancer free and who served as controls. Matching was
done on the basis of age at first cyst aspiration (cases: median
age 43.5 years, range 34–54; controls: median age 44 years,
range 35–54) and family history of breast cancer (positive in
24% of both cases and controls). Moreover, as the duration of
cryopreservation could potentially affect the protein profile, as
it was previously evidenced by us [14], cases and controls were
also rigorously matched for the length of cryopreservation
period (cases: median length 22.5 years, range 19–24; controls:
median length 22.5 years, range 20–24). All the women had
provided their consent to blood drawing and cryopreservation;
moreover the present study project was approved by the Ethics
Committee of the IRCCS AOU San Martino Hospital and
National Cancer Research Institute of Genoa, Italy. The permission from the Italian Data Protection Authority has been also
obtained to get the information relative to the women health
condition for the women lost to follow up.
2.2.
Analytical procedures
Acetonitrile, methanol and water were LiChroSolv from Merck
(Darmstadt, Germany), trifluoroacetic acid (TFA) and α-cyano-4hydroxycinnamic acid (CHCA) were from Fluka (St. Louis, MO).
Serum samples preparation, MALDI-TOF/MS and MS/MS analysis
procedures were described in a previous paper [14]. In order
to avoid procedural bias, both case and control samples were
randomly distributed during processing and analysis. All spectra
were acquired in quadruplicate in a mass range from 800 to
3000 m/z.
2.2.1.
Solid phase extraction
As functionalized superparamagnetic beads appear to be
best suited in preparation of low molecular weight (LMW)
fraction from complex matrices, samples were processed
using Dynabeads® RPC 18 (Invitrogen Dynal, Irvine, CA) with
C18 alkyl-modified surface, which are intended for peptide
concentration in samples.
Some modifications were made to the Dynabeads® RPC 18
manufacturer's protocol. Briefly, 40 μl of beads suspension
were washed one time with water and three times with 100 μl
of 200 mM NaCl, 0.1 % TFA. The beads were re-suspended in
20 μl of water, mixed with 50 μl of serum and left at room
temperature for 5 min. After incubation, the tube was placed
in the manual magnetic particle concentrator (Dynal MPC®,
Invitrogen Dynal) and the supernatant was discarded. The
peptides-enriched beads were washed three times with 300 μl
of 0.1 % TFA in water and the bound fraction was eluted
by incubation, at room temperature for 2 min, with 12 μl of a
1:1 acetonitrile:water solution, to which 3.5 pmoles/μl of an
internal standard peptide (MW 1419.76) were added. The
standard peptide, used to normalize the data, was directly
spiked in the eluting solution to avoid any interference during
the binding reaction between analytes and the magnetic beads.
In Supplementary Fig. S1 we report the analysis by Tricine–SDS–
urea–PAGE of the fraction obtained by solid phase extraction
using Dynabeads® RPC 18 with C18 alkyl-modified surface. As
can be seen, the extracted serum sample (lane1) appears to
46
JO U R N A L OF PR O TE O MI CS 85 ( 20 1 3 ) 4 4 –52
contain some residual LMW proteins and a not well defined
fraction at MW lower than 3.5 kDa (box). This fraction, which is
very difficult to visualize by SDS–PAGE, represents the subject of
our MALDI/TOF analysis. Unfortunately, the mass range covered by our mass spectrometer did not allow us to extend the
analysis to species with a higher molecular weight.
2.2.2.
API–MALDI/TOF MS analysis
For API–MALDI/TOF analysis, several parameters (matrix composition, sample/matrix ratio, spotted volume, laser power)
have been tested in the previous work [14] to find the best
experimental conditions. Based on the results obtained, a
standard procedure was established: one volume of the eluted
sample was manually mixed with two volumes of premade
matrix solution (6.2 mg of CHCA in 1 ml of 36% methanol, 56%
acetonitrile and 8% water), 0.5 μl of this mixture was spotted
onto the MALDI target plate, and allowed to dry at room
temperature. API–MALDI/TOF analysis was performed in reflectron positive mode on a 6210 Time of Flight LC/MS (Agilent,
Santa Clara, CA) coupled with an atmospheric pressure PDFMALDI Ion Source (Agilent) equipped with a 337 nm nitrogen
laser. The following voltages were applied: fragmentor, 300 V;
skimmer, 60 V; OCT RF, 300 V. The acquisition laser power was
set at 35% of maximum (Peak Power 75 kW, Pulse Energy
300 mJ). Data acquisition was automated through the software
Mass Hunter (Agilent), and programmed to accumulate 600
shots per spectrum. The irradiation program was automated
using the spiral motion control of the PDF-MALDI Ion Source.
The instrument was externally calibrated using Tuning Mix
(Agilent). The nominal resolution of the instrument was 20,000
(17,000, observed) and the nominal mass accuracy (with
internal calibration) was <2 ppm.
2.2.3.
API–MALDI/ion trap MS/MS analysis
The MS/MS analysis of selected peptides was performed
coupling the API–MALDI ion source to an 1100 MSD ion trap
instrument (Agilent). The value set for the focalization lenses
was: skim1: 85 V; octapole: 3.5 V; trap drive: 65. The spectra
were collected in the ICC mode and the maximum accutime
was 300 ms. The acquisition laser power was set at 35% of
maximum (Peak Power 75 kW, Pulse Energy 300 mJ). Other
API–MALDI parameters were the same as the MS analysis.
2.3.
Data processing
For each spectrum, raw data generated by the mass spectrometer analysis software were exported as an Excel spreadsheet, filtered by using the LabView-based MS-BASELINER tool
(see below), and finally processed by using Geena [15] (http://
bioinformatics.istge.it/geena/), a recently developed software
tool that aims at automating some of the fundamental
elaboration steps involved in the analysis of m/z and abundance
data from MALDI/TOF MS experiments. Geena processing
methods are based on original algorithms and include the
following steps: a) preprocessing of spectra replicates, which
consists in a series of optional elaborations including isotopic
peaks joining, normalization of the abundance of each m/z
signal against that of a peptide used as an internal standard,
and peak selection; b) computing average spectra for replicated
analysis of samples; and c) alignment of average spectra. While
the peak selection method currently implemented in Geena is
sufficient for many applications, some noisy datasets may
require a special treatment. For this reason, we have adopted an
alternative method, which is currently implemented into a
stand-alone LabView program, MS-BASELINER, that can be
freely downloaded from the Geena website. Geena results
were exported as a matrix of m/z values and relative abundances, and after a visual inspection to resolve a few spectral
ambiguities, 96 candidate signals were obtained. Sporadic
signals, presumably due to specific patient related variables
such as diet, menopausal status, and drug assumption, have
not been considered.
2.4.
Statistical analysis
The data spread sheet elaborated by Geena was imported into
the TMeV program and analyzed using various statistical
algorithms such as hierarchical clustering and significance
analysis of microarray (SAM). Then, we analyzed the odds
associated with each individual peptide. All continuous
values are presented as the mean ± standard deviation. The
statistical analysis was conducted using the χ2 test for
categorical variables and a t test for continuous variables
when appropriate. Univariate and multivariate logistic regression were used to compute odds ratio (OR), P value, and 95%
confidence interval (95% CI) comparing cases and controls.
All ORs were adjusted for the potential confounders, namely:
age, family history and cryopreservation time. The regression
models were constructed using the backward elimination
procedure. The model's goodness of fit was evaluated using
the R2 index and the level of statistical significance was set at
P ≤ 0.05. All P values were two-tailed. For data analysis we used
the IBM software Statistical Package for Social Sciences (SPSS)
version 19.0 for Windows (SPSS Inc., Chicago, Illinois, USA).
2.5.
Data validation
The validation of the SAM analysis was carried out by implementing a bootstrap resampling of original data and by
evaluating the frequency of occurrence of peptide signals. The
bootstrap method works by constructing a large number of new
random data sets by resampling from the original data set
[16,17]. Bootstrap may actually be implemented with or without
replacement. In the former case, the random data sets may
include the same sample twice of even more times (hypothetically, the same sample could randomly be resampled all times
and the whole resulting data set could be constituted only
by replications of the same sample). In the latter case, this
replication is avoided. Due to the relatively small number of
samples involved in our analysis, we preferred to avoid the risk
of bias that would have been introduced by replicated samples
in the validation data sets and we therefore applied bootstrap
without replacement.
3.
Results
The good quality of our MS spectra can be appreciated in
Fig. 1. After data processing and statistical analysis, 9 out of 96
signals showed an increased intensity in cases as compared to
JO U R N A L OF P ROTE O MI CS 8 5 ( 20 1 3 ) 4 4–5 2
47
Fig. 1 – A typical spectrum of a GCDB case serum sample generated by API–MALDI/TOF analysis.
controls. The peak list with the abundance means is shown
in Table 1. Fig. 2A shows the distribution of normalized
abundances of the 9 peptides in cases (n = 30) and controls
(n = 60) Fig. 2B shows a heat map of the intensities of the
discriminating peaks.
The identities of the selected signals were assigned by
comparing their experimental masses with literature values.
Most of them have been found to be C3f complement fragments
differing from each other for the removal of a single amino acid.
One of the two remaining peaks is a fragment of high molecular
weight (HMW) kininogen (m/z 2209.08) while the signal having
m/z 964.43 has not been identified yet. The analysis carried out
using the bioinformatics tool FindPept (http://expasy.org)
allowed verifying the consistency of our high-resolution experimental masses with the assigned sequences. In addition, the
sequence of the C3f peptides was also confirmed by MS/MS
experiments performed coupling the API–MALDI ion source to
an ion trap analyzer (see Supplementary Fig. S2).
To confirm the reliability of our MALDI TOF data we
performed an additional experimental validation. Briefly, we
Table 1 – The mean abundance of the selected peaks.
Signals
(m/z)
964.43
1211.63
1348.67
1449.72
1690.88
1777.89
1864.96
2021.04
2209.08
Controls (n = 60)
mean (SE)
2.83
3.81
1.28
5.46
0.50
0.69
2.93
0.44
1.10
(1.27)
(1.23)
(0.52)
(1.99)
(0.24)
(0.30)
(0.78)
(0.26)
(0.39)
Cases (n = 30)
mean (SE)
P<
10.18 (2.54)
19.12 (4.56)
6.58 (1.65)
23.34 (5.08)
2.71 (0.79)
4.06 (1.26)
10.40 (2.12)
4.79 (1.71)
5.02 (1.37)
0.013
0.003
0.004
0.002
0.01
0.014
0.002
0.018
0.009
selected two aliquots of a single serum sample showing high
levels of C3f fragments and performed two independent solid
phase extractions. Then, the eluted peptides were analyzed,
in quadruplicate, by MALDI/TOF mass spectrometry, and
results were normalized against the internal standard (see
Ref. [14]). The normalized abundances of C3f fragments,
reported as mean and standard deviation in Fig. 3A, show
the good reproducibility of the analytical procedures.
Our results were further validated by implementing a
bootstrap resampling of original data without replacement,
then evaluating the frequency of occurrence of significant
peptide signals. We therefore choose to build 100 random data
sets constituted each by 75 out of the 90 samples of the
original data set, keeping the same 2:1 ratio between controls
and cases. In each random data set, the 75 samples included
50 controls and 25 cases. A SAM analysis was then performed
for each of the 100 random data sets. Signals that significantly
differ between cases and controls were then selected and a
summary analysis was performed. Results of this analysis are
shown in Fig. 3B where the number of signals that were found
to be significantly different in the two groups at least in one of
the SAM runs is reported against the number of times they
were found to be significant. The figure confirms in a very
effective way the results of the SAM analysis that was carried
out on the original data set. All the signals (mainly C3f
fragments) that were identified by this analysis appear to be
largely the most selected by the SAM analysis performed on
the 100 random data sets.
To evaluate the breast cancer risk related with the panel of
identified signals, we estimated the odds ratio(s) (OR), adjusted
for age at first cyst aspiration, family history of breast cancer,
and cryopreservation duration time. Table 2 puts in evidence a
higher presence of the signals in cases than in controls,
resulting in a significant increase in breast cancer odds for
each of them.
48
JO U R N A L OF PR O TE O MI CS 85 ( 20 1 3 ) 4 4 –52
Fig. 2 – Panel A: Distribution of normalized abundances of cases and controls. Black horizontal lines represent the median for
each group. Panel B: Supervised hierarchical clustering of serum peptide data, using average-linkage and Euclidean Distance
as a distance metric, expressed as normalized ion intensities, derived from the two groups of samples (cases in cyan and
controls in blue). Columns represent samples (per group), and rows represent m/z peaks. The heat map scale, ranging from
bright green (lowest) to bright red (highest), of normalized peptide intensities is shown below it.
Logistic regression analysis was then performed to assess
which of the investigated signals would maintain a significant
predictive value of the risk of developing a breast cancer. As it
is shown in Table 3, only the full-length form of C3f (m/z
2021.04) maintained a statistically significant predictive value
(OR = 7.1; P = 0.04) after multivariate analysis. Noteworthy, in
JO U R N A L OF P ROTE O MI CS 8 5 ( 20 1 3 ) 4 4–5 2
49
Fig. 3 – (A) Histogram showing the good reproducibility of the analytical procedures. Two aliquots (black and grey columns) of a
single serum sample showing high levels of various C3f fragments. The columns represent the normalized abundances
evaluated by API–MALDI/TOF analysis, in quadruplicate. Data are reported as mean and standard deviation. (B) Histogram
showing the distribution of signals identified by the SAM analysis carried out on the 100 random data sets built by bootstrap
resampling. Only the signals that were identified at least by one SAM analysis are shown. On the left are the signals that were
rarely identified, the first column referring to the two signals that were identified by one analysis only. On the right are the
signals that were identified more often, the last column referring to the two signals (1211.63 and 1449.72) that were identified
by all 100 SAM analyses. In the labels on the rightmost columns, the identity of signals is reported. All the signals that were
identified at least by 92 out of 100 analyses refer to the C3f fragment of complement. The signal that was identified by 89
analyses refers to the HMW kininogen.
this analysis the HMW kininogen (m/z 2209.08) and the
unknown peak (m/z 964.43) lost their predictive value.
Finally, we have also investigated the qualitative changes
that may occur in the C3f degradation pattern between cases
and controls. For this purpose, we evaluated the ratio between
the remaining most abundant degraded forms of C3f. Briefly,
for each sample, in which the signals having m/z 1211.63, m/z
1348.67, m/z 1449.72, and m/z 1864.96 were simultaneously
represented, we calculated the percentage of the abundance
of any individual peptide in respect to their total amount.
Then, an average value, with its standard deviation, was
calculated for the whole sample set. As is shown in Fig. 4, no
significant differences were found.
4.
Discussion
Most proteomic profiling studies on breast cancer so far
available have looked for novel diagnostic markers, while the
search for new predictive biomarkers is limited to few studies
investigating the possibility to predict for tumor outcome
following surgery and treatment monitoring. The major aim of
our study was to identify a serum peptidome signal predictive
of the risk of developing a breast cancer in women affected by
GCDB constituting a subgroup of otherwise healthy women,
though they bear a higher breast cancer risk. Several hypotheses have been proposed to explain the origin of the serum
50
JO U R N A L OF PR O TE O MI CS 85 ( 20 1 3 ) 4 4 –52
Table 2 – Odds ratio (OR) associated to the presence/
absence of each signal.
Signals
(m/z)
Controls
(n = 60) +/−
Cases
(n = 30) +/−
OR a
(95% CI)
P<
964.43
1211.63
1348.67
1449.72
1690.88
1777.89
1864.96
2021.04
2209.08
8/52
11/49
8/52
13/47
5/55
6/54
14/46
3/57
9/51
12/18
18/12
13/17
18/12
10/20
10/20
18/12
11/19
15/15
4.52 (1.56–13.10)
7.59 (2.71–21.20)
5.45 (1.87–15.89)
6.98 (2.45–19.94)
5.50 (1.67–18.7)
5.74 (1.68–19.56)
6.18 (2.21–17.33)
13.36 (3.02–59.03)
6.41 (2.22–18.50)
0.005
0.000
0.002
0.000
0.005
0.005
0.001
0.001
0.001
+: Presence of signal; −: absence of signal.
a
Adjusted for age, family history of breast cancer and time of
cryopreservation.
LMW proteome/peptidome. Some authors suggest that a combination of endopeptidase and exopeptidase activities [12,18]
could be responsible for peptide fragments generation from
specific precursor proteins. Recently, Yi et al. [19] reported
experimental evidence that stable isotopically labeled peptides
spiked into serum samples are subjected to degradation by
intrinsic aminopeptidase and carboxypeptidase activities as a
function of time. Other authors suggested thrombin as responsible for a broad spectrum proteolysis in human serum samples
[20]. Furthermore, plasma kallikrein is able to cleave HMW
kininogen, and subsequently cleavage products are rapidly
degraded by plasma proteases [21,22]. Villanueva et al. [12]
proposed that the serum peptidome profile could be not only
cancer-specific but also cancer type-specific, although in some
cancers an overlapping of peptide signatures was observed.
In the present study, statistical analysis of data obtained by
API–MALDI/TOF MS of cryopreserved serum samples has
singled out several signals differing between cases and controls;
these signals are related to C3f complement fragments, a
fragment of HMW kininogen, and an unidentified signal having
m/z 964.43 respectively. All these signals were individually
associated with an increased breast cancer risk; however
only the m/z 2021.04 C3f fragment maintained a statistically
significant predictive value after multivariate analysis, thus
Table 3 – Logistic Regression Model including the seven
signals of C3f, the HMW kininogen (m/z 2209.08) and the
unknown peak (m/z 964.43).
m/z
964.43
1211.63
1449.72
1864.96
1348.67
1690.88
1777.89
2021.04
2209.08
a
OR a (95% CI)
2.09
5.11
1.81
0.59
0.55
1.99
0.41
7.10
1.11
(0.50–8.70)
(0.50–52.33)
(0.21–15.80)
(0.05–7.08)
(0.05–6.55)
(0.25–15.71)
(0.04–4.69)
(1.04–48.38)
(0.19–6.44)
Adjusted for age, family history of breast cancer and time of
cryopreservation.
P<
0.3
0.5
0.6
0.7
0.6
0.5
0.5
0.04
0.9
Fig. 4 – Histogram showing the percentage of the most
abundant degraded forms of C3f in respect to their total
amount in cases and controls. The percentage of each
individual peptide (m/z 1211.63, m/z 1348.67, m/z 1449.72,
m/z 1864.96) was calculated by comparing the single
abundance with the sum of their abundances.
proposing itself as a “cancer marker” able to identify the women
with the highest risk of developing a breast cancer.
The full length form of C3f is a 17 amino acids peptide having
a mass of 2020.1 Da (monoisotopic), and derives from the
cleavage of C3b into iC3b by factors I and H [23]. Since the C3f
peptide is an internal sequence of the complement C3 protein,
its presence in serum can be related exclusively to a specific
enzymatic action. Subsequently, it may be degraded by intrinsic
peptidase activities, to form the typical degradation pattern
observed in the MS spectrum of cryopreserved sera. The level
of the C3f-derived peptides has been previously reported to
increase in the serum of patients diagnosed with several neoplasms, including breast, bladder, thyroid and prostate cancer
[12,24]. Our findings put in evidence, for the first time, that a
higher level of C3f peptides can be found in the serum of women
affected by a benign condition like GCDB, who developed a
breast cancer even 20 or more years later.
The complement system is involved in the innate immunity and plays an important role in the surveillance against
tumors [25]. Indeed, since the early nineties, immunohistochemistry studies, performed on the tissue samples of breast
carcinomas, have demonstrated the deposition of C5b-9
complexes on tumor cell surface, indicating persistent complement activation [26]. Cancer cells are able to activate the
complement cascade, and the increased serum concentration
of C3f in patients with GCDB, who developed a breast cancer
during follow-up, may give rise to two opposing interpretations. On one hand, it could suggest an activation of the
complement system by “dormant” breast cancer micro-foci
hypothetically associated with breast cysts [5]. It is known
that, even at early stages of tumorigenesis, transformed cells
may express cancer-specific markers able to initiate the so
called “Cancer Immunoediting Process”, composed of three
phases: elimination, equilibrium, and escape [27]. In the first
phase, the developing tumor may be eradicated by innate and
adaptive immunity and represents the classical concept of
cancer immunosurveillance which protects the host from
JO U R N A L OF P ROTE O MI CS 8 5 ( 20 1 3 ) 4 4–5 2
tumor formation. The equilibrium phase is the period of
immuno-mediated latency after incomplete cancer cells
removal in the elimination phase, where tumor cells may be
either maintained chronically or modified to generate new
tumor variants. During the third phase, these variants may
eventually escape the immunological control and tumor
growth may proceed unrestrained by immune pressure.
These concepts may explain the sometimes very late onset
of overt tumors in the GCDB patients with high serum levels
of C3f. On the other hand, the complement system might be
activated in all cases of GCDB, as a consequence of an altered
micro-environment generated by the presence of macrocysts,
in particular the type I cysts, that are associated to a constant
inflammatory condition of the mammary gland. According to
this assumption, only the women with massive C3b inactivation, mediated by factor I and H, would present increased level
of C3f [28]. C3b inactivation would result in a lower surveillance against transformed cells, which would take advantage
of an immune evasion mechanism mediated by factors I and
H. This interpretation is in accord with the data reported by
other authors [29] who showed a lower expression of C3c
complement fragment in tissues from infiltrating ductal
breast carcinomas. In fact C3c is generated from iC3b by the
action of factor I, during the complement inactivation process
that leads to the removal of cell-bound complement components from tumor cell membrane. A down regulation of
complement C3c component in tumor tissues may, therefore,
suggest the putative involvement in breast tumors of complement inhibitory mechanisms.
In our study, solely the presence of the full-length C3f
peptide appears to be associated with a significantly increased breast cancer risk after multivariate analysis. We
have also investigated the putative qualitative changes in the
C3f degradation pattern between cases and controls, and,
apart from the 2021.04 peptide, we failed to find any significant difference in the ratio between the remaining most
abundant degraded forms of C3f (Fig. 4). This suggests that, in
the specific subgroup of patients with GCDB enrolled in our
study, the higher concentration of C3f derived peptides in the
sera of women who subsequently developed a breast cancer,
is likely to be the result of a different concentration of the C3b
precursor protein rather than of a different peptidase activity.
This assumption could also explain the higher concentration
of full length C3f in the cases group. Indeed, under hypothetical equivalent condition of intrinsic aminopeptidase and
carboxypeptidase activities, the persistence of undigested
C3f could result from higher baseline levels of full length
substrate. In the cases group we correlated the variability of
C3f serum levels with age at first cyst aspiration, time to
breast cancer diagnosis and family history of breast cancer
through the Pearson's test but no correlation was found. To
correctly interpret this finding it is necessary to take into
account that cancer is a multifactorial disease, believed to
result from the interaction of genetic factors with environmental factors. In this context, the increase in the level of
C3f in serum, indicative of an activation/inactivation of the
complement system, may be considered just one of these
factors. With regard to the remaining peaks, namely the HMW
kininogen, it is worthy to note that our findings are in accord
with previous studies in patients with early as well as
51
advanced cancer reported by Villanueva et al. [12] and
Umemura et al. [30]. Although these authors suggested
that this peptide could be a product of the tissue microenvironment contributing to mammary carcinogenesis, this
hypothesis needs to be clarified.
Though preliminary and obtained through a small retrospective case–control study, our findings appear to suggest
that the study of peptidome degradation might be a useful
tool to identify the women who might be at higher risk of
developing breast cancer and who, therefore, might gain the
greatest benefit from periodic surveillance with new imaging
technologies or from chemoprevention treatments. In order
to improve these findings, we are now proceeding by
investigating the degradation profile of breast cyst fluid
peptidome of the same women selected for the present
study, which might well be more representative of mammary
micro-environment.
Supplementary data to this article can be found online at
http://dx.doi.org/10.1016/j.jprot.2013.04.029.
Acknowledgments
We are indebted to Dr. L. Zinoli for the assistance in the
graphic production and to Dr. M. Muselli for helping in data
validation. We gratefully thank Dr. U. Pfeffer and Dr. S. Ferrini
for critical reading of the article. This work was supported by
grants from Italian Ministry of Education, University and
Research (contract 2006063220_002). P. Romano has been
partially supported by the Italian Ministry of Health, project
“Rete Nazionale di Bioinformatica Oncologica”. A. Facchiano
has been partially supported by the “Programma Italia-USA
Farmacogenomica oncologica”, the Flagship Project InterOmics
and the project CNR-Bioinformatics.
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