The use of proteomic technologies in breast cancer research
The main findings in the field of breast cancer proteomic research as well as modern strategies, technologies and methods of validation are reviewed. A special attention is focused on validated proteomic biomarkers of breast cancer. The data on proteomic profiling of stroma, tumor microenvironment,...
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nasplib_isofts_kiev_ua-123456789-1377482025-02-09T12:51:56Z The use of proteomic technologies in breast cancer research Mazur, M.G. Pyatchanina, T.V. Reviews The main findings in the field of breast cancer proteomic research as well as modern strategies, technologies and methods of validation are reviewed. A special attention is focused on validated proteomic biomarkers of breast cancer. The data on proteomic profiling of stroma, tumor microenvironment, involvement of proteins in tumor progression, invasion and metastasis, and mechanisms of action of new generation drugs, are analyzed. The results of proteomic analysis are of high clinical importance and significantly improve tumor molecular profiling, stratification of patients, screening, diagnostics, and therapy of breast cancer. 2016 Article The use of proteomic technologies in breast cancer research / M.G. Mazur, T.V. Pyatchanina // Experimental Oncology. — 2016 — Т. 38, № 3. — С. 146–157. — Бібліогр.: 79 назв. — англ. 1812-9269 https://nasplib.isofts.kiev.ua/handle/123456789/137748 en Experimental Oncology application/pdf Інститут експериментальної патології, онкології і радіобіології ім. Р.Є. Кавецького НАН України |
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Reviews Reviews Mazur, M.G. Pyatchanina, T.V. The use of proteomic technologies in breast cancer research Experimental Oncology |
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The main findings in the field of breast cancer proteomic research as well as modern strategies, technologies and methods of validation are reviewed. A special attention is focused on validated proteomic biomarkers of breast cancer. The data on proteomic profiling of stroma, tumor microenvironment, involvement of proteins in tumor progression, invasion and metastasis, and mechanisms of action of new generation drugs, are analyzed. The results of proteomic analysis are of high clinical importance and significantly improve tumor molecular profiling, stratification of patients, screening, diagnostics, and therapy of breast cancer. |
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Mazur, M.G. Pyatchanina, T.V. |
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Mazur, M.G. Pyatchanina, T.V. |
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Mazur, M.G. |
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The use of proteomic technologies in breast cancer research |
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The use of proteomic technologies in breast cancer research |
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The use of proteomic technologies in breast cancer research |
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The use of proteomic technologies in breast cancer research |
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The use of proteomic technologies in breast cancer research |
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use of proteomic technologies in breast cancer research |
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Інститут експериментальної патології, онкології і радіобіології ім. Р.Є. Кавецького НАН України |
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The use of proteomic technologies in breast cancer research / M.G. Mazur, T.V. Pyatchanina // Experimental Oncology. — 2016 — Т. 38, № 3. — С. 146–157. — Бібліогр.: 79 назв. — англ. |
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Experimental Oncology |
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AT mazurmg theuseofproteomictechnologiesinbreastcancerresearch AT pyatchaninatv theuseofproteomictechnologiesinbreastcancerresearch AT mazurmg useofproteomictechnologiesinbreastcancerresearch AT pyatchaninatv useofproteomictechnologiesinbreastcancerresearch |
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146 Experimental Oncology 38, 146–157, 2016 (September)
The use of proTeomic Technologies
in breasT cancer research
M.G. Mazur*, T.V. Pyatchanina
R.E. Kavetsky Institute of Experimental Pathology, Oncology and Radiobiology, NAS of Ukraine, Kyiv 03022, Ukraine
The main findings in the field of breast cancer proteomic research as well as modern strategies, technologies and methods of validation
are reviewed. A special attention is focused on validated proteomic biomarkers of breast cancer. The data on proteomic profiling
of stroma, tumor microenvironment, involvement of proteins in tumor progression, invasion and metastasis, and mechanisms of action
of new generation drugs, are analyzed. The results of proteomic analysis are of high clinical importance and significantly improve
tumor molecular profiling, stratification of patients, screening, diagnostics, and therapy of breast cancer.
Key Words: breast cancer, proteomic biomarkers of breast cancer, proteomic technologies, strategy and methods for identification
of proteins, MS-based methods.
Breast cancer (BC) is a highly complex systemic
disease with different histological forms and molecular
subtypes. The biologic complexity of BC is determined
by significant intratumoral heterogeneity that is char-
acterized by physiologic, morphologic, molecular, ge-
netic and epigenetic features. The development of the
strategy for personalized approach for diagnostics and
therapy of BC patients requires advanced knowledge
on molecular markers of malignant transformation and
treatment response for improvement of diagnostic tests,
survival indexes and quality of life of the patients, and
the de ve lopment of new generation anticancer thera-
peutics [1–3].
The studies of BC proteome are driven foremost
by the necessity for an analysis of information accu-
mulated within the frameworks of “Human Genome”
project at the levels of trascriptome, proteome, and
metabolome. The relation between proteome with other
areas of functional genomics is presented in Fig. 1 [4].
When immunohistochemical analysis (IHC) has been
introduced into clinical practice as a diagnostic method,
it became possible to study the state of specific protein
receptors in BC patients, and, consequently, to identify
the molecular subtypes of BC such as luminal А and В,
basal, Her2-expressing subtype, and subtype histologi-
cally similar to normal phenotype [5, 6]. In turn, pro-
teome and interactome of the molecular BC subtypes
are highly heterogeneous, therefore the clinical use
of personalized therapy presupposes an identification
of protein markers for diagnostics of BC and the disease
prognosis. Despite the newest achievements in the field
of genetic and histological assays, the deficit of molecu-
lar diagnostic me thods for determination of BC features
is still evident [6].
The present review is devoted to an analysis
of modern strategies, technologies and scientific find-
ings in proteomic research of BC.
Proteomic strategies, technologies and study
subject. In recent years, a number of studies were di-
rected on the determination of relevant panel of protein
markers of BC molecular subtypes matching the criteria
for standard clinical study of patient’s biologic material
for diagnostics, prognosis and therapy. Along with this,
the development of protein profile and identification
of protein biomarkers of BC in body tissues and fluids
(classification of biomarkers [7], Fig. 2) should meet
the requirements, in particular, for high level of repro-
ducibility in different laboratories during an analysis
of monotypic material. In parallel with increasing bulk
of experimental findings potentially important for clinical
practice, there has been performed an improvement
Submitted: August 05, 2016.
*Correspondence: E-mail: mariamazur17@gmail.com
Phone: +38 (098) 994-70-39
Abbreviations used: 2D-DIGE – two-dimensional differential in-gel
electrophoresis; 2D-PAGE – 2D-polyacrylamide gel electrophoresis;
APE1 – apurinic/apyrimidinic endonuclease 1; BC – breast cancer;
CAFs – cancer-associated fibroblasts; EPR – endoplasmic reticu-
lum; ER – estrogen receptor; ESI – electrospray ionization source;
FFPA – forward phase protein array; FFPE – formalin-fixed, paraffin-
embedded; FT-ICR MS – fourier transform ion cyclotron resonance
analyzer of mass spectrometry; HER2 – human epidermal growth
factor receptor 2; ICAT – isotope-coded affinity tags; IHC – immuno-
histochemical analysis; iTRAQ – isobaric tags for relative and absolute
quantification; KIFAP3 – kinesin associated protein 3; LC – liquid
chromatography; LCM – laser capture microdissection; LTQ-Orbitrap
MS – hybrid linear ion trap analyzer of mass spectrometry; MALDI –
matrix-assisted laser desorption-ionization; MD-LC – multidimensional
liquid chromatography; MRM-MS – multiple reaction monitoring mass
spectrometry; MS – mass spectrometry; MS/MS – tandem mass
spectro metry; mTRAQ – mass differential tags for relative and abso-
lute quantification; MudPIT – multidimensional protein identification
technology; Nanospray MS – ionization source of mass spectrometry;
nLC-MS/MS – nanoscale liquid chromatography-tandem mass spec-
trometry; PR – progesterone receptor; Q MS – quadrupoles analyzer
of mass spectrometry; Q-Orbitrap MS – hybrid analyzer of mass
spectrometry; Q-TOF MS – hybrid quadrupoles–time-of-flight analyzer
of mass spectrometry; RP-LC – reverse phase liquid chromatography;
RPPA – reversed phase protein array; RRBP1 – ribosome binding
protein 1; SAX – strong anionic exchange; SCX – strong cationic ex-
change; SDS – sodium dodecyl sulphate; SELDI – surface enhanced
laser desorption/ionization source; SILAC – stable isotope labeling
by amino acids in cell culture; SRM-MS – selective reaction monitoring
mass spectrometry; SW – software; TMA – tissue microarrays; TNBC –
triple-negative breast cancer subtype; TOF – time-of-flight analyzer;
TripleTOF MS – hybrid time-of-flight analyzer of mass spectrometry;
XCT II MS (TripleQ MS) – hybrid quadrupoles analyzer of mass spec-
trometry.
Exp Oncol 2016
38, 3, 146–157
reviews
Experimental Oncology 38, 146–157, 2016 (September) 147
of existing approaches and analytic methods for pro-
tein research and technical capabilities of equipment,
in particular, via combination of a few simple methods
and devices.
Biomarkers
Prognostic Diagnostic Predictive
Prognostic of clinical
outcome Type of cancer
Prediction
of response
to treatment
Normal cell In situ Invasive cancer
Transformed cell Invasive cancer Metastasis
Proliferation Metastasis Diagnosis
Treatment
Atypia Early detection
Diagnosis
TreatmentIn situ
Prevention
Early detection
Diagnosis
Treatment
fig. 2. Classification of biomarkers by their assignment and
relation to tumor progression
Strategies. Advantages and limitations of the
strategies for detection of cancer biomarkers are
reviewed in detail in [8] (Fig. 3).
Biomarkers
Approach Technology Equipment
Gene-expression
profiling Peptidomics MS-based profiling
Serum proteomics Auto-antibodies MS-imaging
of tissues
Secreted protein Gene fusions/
translocations Protein arrays
Strategies for discovering biomarkers
fig. 3. Classification of strategies for discovering BC biomarkers
The known strategies of preparing the samples
for protein profiling, so called “bottom-up analysis”
and “top-down analysis” are principally different
at an initial stage of a sample treatment and are
used in the methods based on gel-electrophoresis,
liquid chromatography (LC) and mass spectrometry
(MS) [9]. Bottom-up analysis requires initial enzymatic
digestion of protein molecules into peptides with the
use of proteases. The strategy is used in a few cases:
firstly, for identification of proteins through peptide
analysis with their following search in databases;
secondly, for chemical modification of the peptides
for quantification of peptides and proteins. Top-down
analysis deals with intact preparations where protein
molecules remain undamaged and undigested, and
is used for an analysis of separate proteins or simple
protein mixes, an analysis of protein-protein com-
plexes and target proteins, or for multiple identification
of proteins with post-translational modifications. The
main advantages and disadvantages of these strate-
gies are as follows [9]:
• bottom-up analysis allows one to analyze the
samples of high complexity, provides a set of large
data bases, is more sensitive; however, it requires
repeated analysis of the samples with large peptide
variability, is limited by protein sequence coverage
by identified peptides, is ambiguitous regarding the
origin for redundant peptide sequences;
• top-down analysis allows one to identify isoforms
of proteins and study labile proteins with post-
translational modifications, improves quantification
but has the limitations associated with precur-
sor ion charge state resulting in some problems
in analy zing proteins with charge-state ambiguity
and front-end separation (as far as the range of me-
thods for protein separation is limited).
Methodological instruments for the use of men-
tioned strategies are various: in proteomic studies per-
formed by bottom-up strategy, such methods as gel
electrophoresis, affine chromatography (inclu ding
isotope-coded affinity tags — ICAT), ion-exchange
chromatography, reverse phase liquid chromatogra-
phy (RP-LC), Q-TOF MS, LTQ-Orbitrap MS are used,
while top-down analysis studies exploit the methods
of ion-exchange chromatography, RP-LC, 2D-LC,
ESI MS, LTQ-Orbitrap MS [9]. Some methods, for
example, RP-LC та LTQ-Orbitrap MS, could be used
for both strategies.
Technologies. Different classifications of technolo-
gies for proteomic studies that are used for an analysis
of tumor tissues and body fluids are known [10]. The
methods of proteomic studies are based on the use
of antibodies, in particular, Western blot, enzyme-linked
ToolsTools DataData
Genomics
Non Gel-based Proteomics
Structural Proteomics
Animal models
Transcriptomics
Antibody probes Antibodies Tissue arrays
Tissue bank Fluid bank
Functional Analysis
Mass Spectrometry Analysis
Interactomics
Bioinformatics Metabolomics
ResourcesResources Post-Genomic Era
Gel-based Proteomics
fig. 1. Interrelation of sources, technologies, and “omics” data in proteomic studies of BC
148 Experimental Oncology 38, 146–157, 2016 (September)
immunosorbent assay (ELISA), IHC, tissue microarray
(TMA), forward phase protein array (FFPA) and reverse
phase protein array (RPPA), or these methods are not
exploiting antibodies and are based on MS. The first
group of methods is used for verification and validation
of the obtained data for further use of the results in clini-
cal practice and requires an established knowledge
of the proteins under study, while the second group
of methods is represents the experimental platforms for
generation of databases for identified proteins.
By the type of equipment used in the research, one
may classify the proteomic technologies as follows:
methods of gel electrophoresis (2D-PAGE, 2D-DIGE),
peptide-oriented proteomics (LC combined with
MS/MS: LC-MS/MS), the methods based on the use
of arrays (RPPA) [7].
MS-based proteomic platforms for cancer stu-
dies and their principles of use are discussed in detail
in [11]. To these platforms belong such methods as gel
electrophoresis (1D-PAGE, 2D-PAGE (SDS-PAGE),
2D-DIGE), liquid chromatography (LC/MALDI or LC/MS
(LC-MS/MS)), 2D-LC or multidimensional protein
identification technology (MudPIT), LC-ESI-MS,
mass spectrometry (ion sources (ESI MS, MALDI MS,
SELDI MS) combined with mass analyzers (Q MS,
TOF MS, FT-ICR MS): MALDI-TOF MS, SELDI-TOF MS,
ESI-MS/MS). By the data [11], LC-MS/MS is used
mostly with bottom-up strategy, along with this some
methodologies based on top-down strategy are al-
ready developed, too [12]. Also, for identification
of new cancer biomar kers and potential therapeutic
targets LC-MS/MS could be combined with quantita-
tive methods: ICAT-LC-MS/MS, iTRAQ-LC-MS/MS,
SILAC-LC-MS/MS [11].
In general, modern proteomic studies often use
gel electrophoresis and chromatography combined
with MS. Mostly, gel electrophoresis and chromatog-
raphy are used for separation of protein mixture into
specific fractions containing few proteins with similar
physical and chemical characteristics. The fractions
could be further analyzed by MS, allowing identifi-
cation of thousands of proteins per sample. During
MS double scanning is used when information ob-
tained after first scanning is selectively used during the
second scanning. Apart from this, complex methods
based on combination of few sequential separations
of the proteins with the use of elementary LC meth-
ods (for example SCX-RP-LC [13], SCX-SCX-LC [14]
or RP-RP-LC [15]) and their identification with the se-
quential use of elementary MS methods (for example,
LC-MS/MS [16–19]) have been applied.
Analysis of the use of strategies and technolo-
gies. An analysis of proteomic studies of BC shows
several major directions in this field.
Firstly, it is the development of the strategies
of preparation of protein/peptide samples top-down
or bottom-up with or without their proteolytic digestion
(for example, trypsinization/pepsinization) prior to the
use of proteomic technologies. An analysis of experi-
mental studies of BC proteome at tissue level published
in 2011–2016 has revealed that bottom-up strategy
combined with modern technologies has been used
more often (Table 1) due to its higher informativenes
for identification of BC biomarkers [20]: on the one
side, there has been revealed a trend for the use of uni-
fied bottom-up strategy, on the other side, for the use
of both bottom-up and top-down strategies in one
research but for different technological approaches.
Also, there has been found a trend for minimal number
of studies where top-down strategy was used along
with narrow spectrum of methods (see Table 1). The
authors [9] have listed wider spectrum of methods
with which top-down strategy could be used for protein
identification, but by our consideration, methodological
variability of top-down in proteomic BC research is some
what depleted (see Table 1). This fact opens possibili-
ties for analyzing the limitations of methods and equip-
ment to overcome them for the proper use of top-down
strategy for the analysis of complex protein mixtures and
for the development of the optimal protocols on the use
of this strategy with other methods and/or new technical
solutions. An example of such optimization for the use
of top-down is the work [20], reporting on successful
usage of 2D-LC-MS/MS for identification of BC proteins
in tumor tissue (see Table 1).
The second direction is the development of tech-
nologies via combination of several methods (chroma-
tography and tandem MS). An analysis of experimental
studies on BC proteomics from the point of applied
technologies has revealed a trend for the widest use
of combined LC-MS/MS with different modifications
(see Table 1), where among elementary methods most
commonly RP-LC, ESI MS (ion source) and LTQ-Orbitrap
MS (tandem hybrid mass analyzer) were being used. For
analysis of BC proteome triple mass analyzer XCT II MS
(Triple Q MS) is used as well [21] (see Table 1). In the
proteomic studies of different biologic material there ap-
pears a trend for the combined use of different elemen-
tary LC methods (SCX-RP-LC [13]), while in the studies
of total BC proteome such trend is not observed — similar
LC methods are used in tandem (SCX-SCX-LC [14] and
RP-RP-LC [15]) (see Table 1). There is also a trend for
prevalent use of label-free combined LC-MS/MS me-
thods (label-free analysis, Table 1), that opens the pos-
sibilities for active use of methods utilizing affine labels
(label analysis, Table 1) to achieve better quality of the
results. In general, in proteomic studies employing MS,
a wide spectrum of ion sources and mass analyzers has
been used combination of which depended on the aim
of the research. The use of one or another elementary
methods was analyzed only for the studies where the
methodological components were described in detail
(see Table 1).
It is necessary to note that there have been repor-
ted methodologies, in particular, combination of both
strategies to obtain maximally informative protein profile
of the tumors [20], modification of the stage of peptide
preparation for LC-MS/MS with analytical instruments
in silico [19], development of new proteomic approach
on the use of affine chromatography with top-down
Experimental Oncology 38, 146–157, 2016 (September) 149
strategy [22], development of protocol for the use
of LC-MS/MS with isotope dilution [23]. One should be-
lieve that along with the development of new proteomic
analytical technologies for protein identification and
achievement of the data on protein post-translational
modifications there will be a drastic increase of the
number of identified cancer biomarkers, including bio-
markers of BC progression. For their further implication
into clinical practice, an additional validation of identified
proteins using the antibody-based methods is required,
that, in turn, will stimulate the study of properties and
functions of these proteins.
At present time proteomic-based search of BC bio-
markers has a number of limitations at different levels:
• Biologic material. Molecular heterogeneity of BC,
complex composition of biologic fluids used as ex-
perimental samples, multiplicity of proteome com-
position and its dynamical variability create sig-
nificant methodological challenge in proteomic
research [24].
• Isolation, storage and preparation of experimental
samples. Requirements for conditions of sample
collection, their primary treatment, high quality
storage conditions of biologic materials are being
solved by standardization that is determined in part
by special conditions preventing degradation of the
particular proteins. There are some achievements
in the standardization of plasma samples collection
for obtaining plasma proteomic profile [21].
Disadvantages of bottom-up and top-down strat-
egies could be referred to such limitations as well.
Presently they are counter-balanced by technical
solution for combination of the strategies in a joint
method for proteomic profiling [20]. Apart from this,
for tumor peptidome analysis an improved protocol
of peptide preparation has been proposed that, being
combined with the methods in silico, completes the
results of bottom-up strategy [19].
There are still none technical means allowing si-
multaneous isolation and analysis of DNA, RNA and
proteins from cryomaterials [24].
• Devices and instruments. In the samples low
quantities of proteins that hypothetically could
be tumor-specific, require perfect analytical
sensitivity of the equipment. The methods of gel-
electrophoresis are of the lowest sensitivity while
the MS-based methods are of the highest sensi-
tivity. MS possess own limitations as well at the
levels of ion sources and mass analyzers, making
impact into general disadvantages of combined
elementary methods (for example, if ion sources
MALDI MS or SELDI MS are combined with analyzers
TOF MS — MALDI-TOF MS, SELDI-TOF MS [4]).
• Limitations in silico. The software (SW) used for as-
sessment of experimental data at the stages of their
analysis, visualization, storage, and interpretation
should be up-graded or developed de novo [24].
Presently SW is used more and more often for
verification and validation of the data [19, 20, 25].
The progress in silico will allow reaching higher
levels of BC research [24], meta-analysis [24] and
assessment of the obtained data.
Objects of study. The wide spectrum of human
biologic material used for proteomic study of BC, al-
lows one to perform systemic analysis of tumor-host
interactions. For sampling tumor tissue, invasive me-
thods are used. Body fluids could be taken by noninva-
sive methods that is much more preferable for clinical
application of experimental results.
In proteomic study of BC, a large number of mono-
typic samples are being used. Protein fractions are
isolated from tumor or normal cells, tissues and
body fluids [5, 7, 11, 26–33]. Biopsy, postoperative
material, tissue obtained by laser capture microdis-
section (LCM) method [34, 35], BC cell lines in vitro,
experimental tumors in vivo are studied in tumor tissue
Table 1. Methods for modern proteomic strategies applied
in the proteome research of BC
Bottom-up Top-down Bottom-up +
top-down
Label-free analysis
LC-MS/MS:
LC-MS/MS [16, 17, 21, 25, 29,
33, 36, 43–45, 79],
LC-MS/MS with isotope
dilution [23],
nLC-MS/MS [18, 28, 41],
2D-LC-MS/MS [15, 22];
basic methods of liquid
chromatography for LC-MS/MS:
RP-LC [21, 29, 36],
2D-LC (RP-RP-LC) [15];
basic methods of mass spectrom-
etry for LC-MS/MS (ion sources):
ESI MS [21, 22, 29, 25],
SELDI MS [44];
basic methods of mass
spectro metry for LC-MS/MS
(mass analyzers):
Q MS [17],
Q-TOF MS [28],
LTQ MS [16, 45, 79],
hybrid Q-Orbitrap MS [33, 43],
LTQ-Orbitrap MS [15, 18, 22, 29,
33, 36, 41],
XCT II MS (TripleQ MS) [21];
reaction monitoring mass
spectrometry:
SRM-MS [23],
MRM-MS [14, 21].
Label analysis
label-LC-MS/MS:
SILAC-LC-MS/MS [25],
iTRAQ-2D-LC-MS/MS [37],
iTRAQ-MD-LC-MS/MS [14];
basic methods of LC
for label-LC-MS/MS:
SAX-LC [25],
MD-LC (SCX-SCX-LC) [14];
basic methods of mass
spectrometry for label-LC-MS/MS
(ion sources):
MALDI MS [14];
basic methods of mass
spectrometry for label-LC-MS/MS
(mass analyzers):
TOF-TOF MS [14];
label-reaction monitoring mass
spectrometry:
mTRAQ-SRM MS [37]
1D-PAGE
(SDS-PAGE) [18],
2D-PAGE
(SDS-PAGE)
[14, 22, 28, 37, 46],
2D-DIGE [14, 36],
affinity chroma-
tography [22]
Label-free
ana lysis
2D-LC-MS/MS
[20];
basic methods
of 2D-LC-MS/MS:
Bottom-up
Proteomics:
Nanospray MS,
TripleTOF MS
[20];
Top-Down
Proteomics:
RP-LC,
Nanospray MS,
Orbitrap MS
[20]
150 Experimental Oncology 38, 146–157, 2016 (September)
proteomics. In the research of body fluids, postopera-
tive serum, tumor extracellular fluid, blood serum and
blood plasma, mononuclear cells, cerebrospinal fluid,
urine, saliva, milk, nipple aspirate, fluids from organs
and body cavities are used. A typical scheme of mo-
dern proteomic studies of BC is reviewed in details
in [7], and illustrated in Fig. 4.
LCM Blood plasma
Serum
Milk
Urine
Saliva
Serial sectioning
FFPE
Frozen blocks
Tissue dissection
Biopsy material
Fluids
Tissue and fluid analysis
+
sample preparation
Proteomic technologies
Discovery driven Knowlege based
FPPA
RPPA
MS imaging
1D gel/2D gel LC-MS/MS
SELDI-TOF MS
MALDI-TOF MS
ESI-LTQ-Orbitrap MS
MALDI-TOF/TOF MS
lCAT-LC-MS/MS
iTRAQ-LC-MS/MS
SILAC-LC-MS/MS
Data verification
IHC
Western blotting
mTRAQ-SRM SRM
MRM
TMA
ICH/TMA
Prototype
ELISA
RPPA
Large scale validation
fig. 4. Schematic representation of proteomic BC studies
Clinical importance of the results of proteomic
studies of BC. Proteomic profiling of biologic ma-
terial from BC patients with the use of MS-based
methods allows detecting simultaneously much more
individual proteins than antibody-based methods (in-
cluding IHC [33]) applied for verification and validation
of the results. Information obtained from proteomic
analysis is useful for studying the role of extracellular
matrix [15]; post-translational modification of pro-
teins [31, 36]; proteins involved in DNA repair [33];
tumor micronvironment [33]; microenvironment
of tumor cell [22]; proteins of tumor stroma [37, 38];
cytoplasmic proteins [39]; proteins of endoplasmic re-
ticulum (EPR) [40]; the role of proteins of mechanistic
pathways, components of protein biosynthesis, cyclins
in progression, invasion and metastasis of BC [38].
The proteomic profiling based search for BC bio-
markers showed following trends: BC progression
(BC with different lymph nods status [37, 41, 42] and
metastatic BC [29, 31, 35]), profiling of BC subtypes
(triple negative breast cancer (TNBC) [25, 37, 38, 41,
43, 44], HER2+ [14, 25, 37, 38, 44, 45], ER/PR [25,
37, 38], basal and luminal [19, 20, 45]) and the study
of tumors of different histopathological grade [22, 27].
In [46], the top-down strategy for 2D-PAGE
(SDS-PAGE) and Bradford technique have been used
for determination of expression levels of proteins in tu-
mor and normal tissues of mammary gland. In total,
454 proteins have been found, 138 of which showed
an altered expression in tumor tissue (expression
of 61 proteins was suppressed, 3 — up-regulated, and
74 — down-regulated). So, compared to normal tissue,
expression of a large number of proteins is changed,
and many of them are down-regulated, sometimes
completely suppressed [46]. In our view, these data
should have been verified by MS and LC-MS, because
of low separating capacity of 2D-PAGE (SDS-PAGE).
Generation of large databases for proteomic
profiles of biologic materials has limitations caused
by variability of both the sample collection and pro-
teomic technologies used for analysis. In [21], the
collection of plasma samples from healthy individuals
and BC patients has been standardized that allowed
one to create database of proteomic profiles of plasma
with the use of bottom-up strategy and combined
LC-MS/MS method. This database will be useful for
the search of BC biomarkers for diagnostic, prog-
nosis, monitoring of the disease progression and
therapy [21]. The data on three proteins — potential
BC biomarkers, have been already verified (Table 2).
The recent findings in BC proteomic analysis
pertaining to screening, diagnostics, therapy and
prognosis are reviewed in detail in separate sections
presented below.
Screening. Screening tests require high sensi-
tivity, specificity, accuracy, non-invasiveness, ease
of process, low cost and reliability of false-positive/
false-negative result, therefore proteomic analysis
of biologic body fluids for identification of markers
for preclinical changes could be the best choice for
screening purposes.
Using combined LC-MS/MS and bottom-up strategy,
protein biomarkers were identified in urine of BC patients
with different disease stage and tumor material was stud-
ied in parallel as well [29]. Expression levels of 59 proteins
was found to be different from that in control samples,
in particular, 13 novel up-regulated proteins associated
with BC of diagnostic value have been revealed. The
relation between BC progression and a panel of specific
protein markers has been ascertained: preinvasive ductal
carcinoma in-situ — leucine LRC36, protein MAST4 and
uncharacterized protein CI131, early invasive BC —
DYH8, HBA, PEPA, MMRN2 proteins, filaggrin, and un-
characterized protein C4orf14 (CD014), and metastatic
BC — AGRIN, NEGR1, FIBA proteins and KIC10 keratin.
The proteins that have been already validated are listed
in Table 2. These data will be used for the development
of screening programs.
Diagnostics. Early diagnosis and monitoring
of BC progression are of great importance for better
prognosis of the disease.
TNBC is a heterogeneous pathology with unfavor-
able prognosis due to insufficient targeted treatment
effectiveness. For the first time proteomic analysis
of 12 000 proteins and molecular profile of this BC sub-
type in tumor samples and cell cultures in vitro was
provided using combined LC-MS/MS and bottom-
up strategy [43]. In this research proteins of signal
pathways were quantified and proteins markers of drug
resistance were identified. These data could be useful
for understanding the mechanisms of drug resistance,
as well as for diagnosis and therapy of TNBC.
Experimental Oncology 38, 146–157, 2016 (September) 151
Table 2. The results of modern proteomic studies of BC
Biological samples Research methods Methods of validation Protein(s) Field of use Ref.
Invasive
object
Tumor tissue of invasive duc-
tal carcinoma
Subtypes:
Luminal B HER2+ve
HER2 enriched
2D-PAGE (SDS-PAGE),
2D-DIGE,
iTRAQ-MD-LC-MS/MS
(MD-LC (SCX-LC),
MALDI-TOF/TOF MS)
Western blotting
MRM-MS
Apolipoprotein A1 (APOA1)
Gelsolin (GELS);
Heat shock protein HSP 90-beta
(hs90b);
Eukaryotic elongation factor
1 alpha (EF1A1); Peroxiredoxin
3 (PRDX3); NHRF1.
Peroxiredoxin 1 (PRDX1); Oxidore-
ductase (catD); Calreticulin (CALR)
ATPase beta chain (atpB);
SOX14 (CH60) SRY-box 14.
Protein biomarkers of BC
Tumor subtyping, diagnosis
of early and late stages
Prediction of treatment out-
come
[14]
Tumor tissue of invasive duc-
tal carcinoma
Stages:
Early stages
Late stages
2D-PAGE (SDS-PAGE),
2D-DIGE,
iTRAQ-MD-LC-MS/MS
(MD-LC (SCX-LC),
MALDI-TOF/TOF MS)
Western blotting
MRM-MS
Tropomyosin 4 (TPM4); Oxido-
reductase (catD); Peroxiredoxin
3 (PRDX3); Annexin A3 (ANXA3);
Heat shock protein family B (small)
member 1 (HSPB1).
Calreticulin (CALR); Ovotransferrin-
like (TRFE); Gelsolin (GELS);
SOX14 (CH60) SRY-box 14;
Capping actin protein, gelsolin like
(CAPG);
Ywhag (1433G) tyrosine 3-mono-
oxygenase/tryptophan 5-monooxy-
genase activation protein gamma;
Glucose regulated protein
78 (grp78);
NHRF1.
Protein biomarkers of BC
Tumor subtyping,
diagnosis of early and late
stages
Prediction of treatment out-
come
[14]
Lymph node positive vs.
negative, low grade primary
BC tissues
Primary breast carcinoma tis-
sues from patients with dif-
ferent lymph node status
2D-PAGE (SDS-PAGE)
iTRAQ-2D-LC-MS/MS
qPCR (transcript level),
iTRAQ-2D-LC-MS/MS,
mTRAQ-SRM MS,
IHC/TMA;
mTRAQ-SRM MS,
IHC/TMA
Transgelin (TAGLN)
Transgelin (TAGLN);
Transgelin-2 (TAGLN2)
Cancer-associated biomark-
ers of lymph node metasta-
sis of BC
Cancer-associated biomarkers
of lymph node metastasis of BC
[37]
[37]
Breast ductal carcinoma tis-
sues
Published data and data-
base (mRNA level)
IHC/TMA Kinesin associated protein 3
(KIFAP3)
Biomarker of BC [39]
Metastatic BC (tumor tissue) Published data and data-
base (mRNA level)
IHC/TMA Ribosome binding protein
1 (RRBP1)
Biomarker of invasive breast
carcinomas
[40]
Breast tumor tissues HER2+
TNBC
LC-MS/MS (SELDI MS) IHC KRT19 (CK19) keratin 19.
RNA-binding Ras-GAP SH3 bind-
ing protein (G3BP)
Biomarker of HER2+ tumors;
Predictive biomarker of TNBC;
Biomarker correlating with tu-
mor progression, and me-
tastasis
[44]
Human disease-free breast
tissues and malignant breast
tumors
LC-MS/MS with isotope
dilution
SRM-MS Apurinic/apyrimidinic endonucle-
ase 1(APE1)
Development of APE1 inhibi-
tors as anticancer drugs;
may have prognostic and pre-
dictive significance in cancer
treatment
[23]
BC tissues with different ER,
PR and HER2 status (meta-
analysis)
Published data on pro-
teins as important tar-
gets and proteomic pro-
cesses in BC
RPPA ER; PR; Apoptosis regula-
tor (BCL2); GATA binding pro-
tein 3 (GATA3);
KIAA1324 (EIG121); Epidermal
growth factor receptor (EGFR);
Erb–b2 receptor tyrosine ki-
nase 2 (HER2); HER2p1248;
Cyclin B1 (CCNB1);
Cyclin E1 (CCNE1).
10-protein biomarker panel
for BC classification and out-
comes prediction
[38]
Non-in-
vasive
object
Serum (patients with recurrent
BC and patients with no sign
of recurrence 5 years after di-
agnosis)
Lectin affinity chroma-
tography, 2D-DIGE,
LC-MS/MS (RP-LC)
ELISA CDH5 (CADHERIN5) cadherin 5,
type 2 (vascular endothelium)
Predictive and diagnostic bio-
marker
[36]
Plasma (healthy donors and
BC patients)
LC-MS/MS
(RP-LC, ESI MS,
XCT II MS (TripleQ MS)
MRM-MS Apolipoprotein A1 (APOA1);
Hemopexin hemopexin-like;
Angiotensin preprotein.
Candidate biomarkers of BC [21]
Com-
bined
object
Urine and tumor tissue (iden-
tification)
Cell lines (validation)
Tumor tissue (validation)
LC-MS/MS (RP-LC)
Western blotting
IHC, Western blotting
Extracellular matrix pro-
tein 1 (ECM1);
FLG2 (FILAGGRIN) filaggrin fami-
ly member 2; Microtubule associ-
ated serine/threonine kinase family
member 4 (MAST4);
Microtubule associated serine/
threonine kinase family mem-
ber 4 (MAST4).
Screening, monitoring of tumor
progression
[29]
152 Experimental Oncology 38, 146–157, 2016 (September)
Variability of HER2/Neu overexpression is typical
for molecular subtypes of invasive ductal carcinoma,
luminal B HER2+ (ER+/PR+/HER2+) and HER2 enriched
(ER−/PR−/HER2+), which are poorly studied yet in re-
gard to prognostic markers. A comparative proteomic
profiling of luminal B HER2+ve and HER2 enriched sub-
types of invasive ductal carcinoma and healthy tissues
of mammary gland was provided [14]. Tumor material
obtained during modified radical mastectomy has been
used for the search of protein biomarkers of early and
late stages of these molecular BC subtypes with the use
of proteomic analysis methods (see Table 2). Top-down
strategy was used for gel-electrophoresis, and bottom-
up strategy — for MS-based methods. In total, in the
studied BC subtypes 67 proteins expressed in tumor
material were found, and expression of 68 proteins
depended on BC stages; there have been validated
(see Table 2) 6 proteins for luminal В HER2+ subtype,
5 proteins for HER2+ subtype, 5 and 8 proteins for early
and late stages of these BC subtypes, respectively. The
authors believe that these panels of protein biomark-
ers could be used for molecular classification of the
tumors in diagnostics of early and late BC stages and
for prognosis of treatment outcome.
Several studies analyzed expression of protein
isoforms and proteins which composition and func-
tions were altered via post-translational modifica-
tions (phosphorylation, acetylation, glycosylation,
methylation and ubiquitination) [11, 31, 36]. The
results obtained are proposed for the use as sensitive
diagnostic markers of BC clinical course. In studies
mentioned above, the samples of blood serum and
urine of BC patients and paraffin blocks of primary
tumors (FFPE), were analyzed by lectin microarray
[31] or gel-electrophoresis as top-down strategy com-
bined with MS-based methods as bottom-up strategy
[36] (see Table 2). As it has been concluded [31,
36], the altered glycosylation of proteins in cancer
patients could be associated with particular cancer
types, however, total spectrum of glycane structures
is still unknown. An analysis of glycosylated proteins
of blood serum and urine of patients with metastatic
BC has revealed diagnostic and predictive potential
of cadherin-5 and lectin-binding patterns, including
N- and O-bound glycanes [31, 36]. This is supported
by validation of the results [36] establishing 90% speci-
ficity of cadherin-5 as diagnostic marker of metastasis
(see Table 2).
Therapy. Proteomic profiling of BC specimens
could be also useful for analyzing mechanism
of action of anticancer agents such as identification
of targets [25, 44], search for protein-targets or their
inhibitors for adjuvant chemotherapy [23, 41] and
controlling invasive properties of tumors via influence
on proteins of the cells surrounding tumors [33].
In regard to the recent results of integrated “ge-
nome-transcriptome” studies in the absence of uni-
versal panel of BC biomarkers and optimal medicinal
remedies the proteomic analysis of tumor tissues
of different BC subtypes is of special importance.
Using bottom-up strategy, quantification technology
SILAC-LC-MS/MS and LC-MS/MS on FFPE BC tissue
blocks (ER+/PR+, HER2+, TNBC) and BC cell lines
(HCC1599, MCF7, HCC1937) the study of functional
networks between multifunctional proteins and cell
processes in the tumors of different molecular sub-
types has been conducted [25]. Up to 410,000 pro-
teins have been analyzed, and it has been shown
that BC subtypes differ in the functions of proteins
involved in translation of mRNA, cell growth, intercel-
lular interaction, and energetic metabolism. In total,
19 protein signatures were found, just 3 from which
were related to gene copy number, and 11 — to mRNA
levels. Possibly, these data could support an absence
of regular relations between the protein product level
and gene copy number, and protein product content
and mRNA profile. The special SW was applied for
a cross-validation procedure of the obtained data
on proteomic profiling of the tumors. These results
embody the novel ideas that are practically valid for
the development of specific therapeutic agents.
Predictive protein markers of different BC sub-
types will allow us to determine therapeutic response
to particular treatment, to optimize and personalize
cancer therapy.
In a pilot study [44], protein signatures of two
BC subtypes potentially useful for prediction of treat-
ment results were identified. Specific predictive protein
markers of response to neoadjuvant chemotherapy
were studied using bottom-up strategy and combined
LC-MS/MS method in tumors of HER2+ and TNBC
subtypes. There were identified 20 protein signatures
typical for tumors of both subtypes, 20 signatures
with different expression levels allowing to classify
these subtypes, 20 predictive markers of response
to neoadjuvant chemotherapy for HER2+ subtype
and 30 predictive markers of response to neoadjuvant
chemotherapy for TNBC subtype. TNBC subtype was
characterized by overexpression of ALDH1A1 and
galectin-3-binding protein, while in HER2+ subtype
the following proteins were found to be overexpressed:
transketolase, transferrin, CK19, thymosin β4, and thy-
mosin β10. The number of proteins, namely, enolase,
peroxiredoxin 5, periostin precursor, cathepsin
D preproprotein, vimentin, Hsp 70, annexin 1, RhoA
were related to the tumor response to neoadjuvant
chemotherapy. Also, two proteins for classification
of these subtypes were validated (see Table 2).
In spite of constantly increasing number of clinical
trials of anticancer agents there is a necessity for the
correction of modern treatment schemes from the
point of benefit/risk ratio. As far as TNBC is highly
aggressive and there are still none sensitive spe-
cific prognostic markers, up-to-date an optimal target
therapy of this subtype isn’t developed. As a rule, the
patients with negative lymph node status are cured with
adjuvant chemotherapy, but in 30% of cases distant
metastasis develops [47, 48]. With the use of bottom-
up strategy and technology nLC-MS/MS [41] in tumor
material of patients with TNBC and negative lymph
Experimental Oncology 38, 146–157, 2016 (September) 153
node status not treated with adjuvant chemotherapy,
11 prognostic protein signatures, protein products
of the CMPK1, AIFM1, FTH1, MTHFD1, EML4, GANAB,
CTNNA1, AP1G1, STX12, AP1M1, CAPZB genes were
identified and verified. The obtained results could
be useful in clinical practice and address an expedi-
ency of adjuvant systemic therapy in patients with
TNBC and negative lymph node status.
The search for a candidate for proteomic biomarker
for prognosis and therapy of BC patients has been re-
cently attempted [23]. Overexpression of APE1З (the
main protein of DNA excision repair pathway apurinic/
apyrimidinic endonuclease) was detected in clinical
material with the use of bottom-up strategy and the
deve loped analytical approach based on MS [23] (see
Table 2). Hyper-/hypoexpression of APE1 could be pos-
sibly related to decreased/increased tumor cell survival
rate, therefore in future its inhibitors could be used
in clinical practice [23]. It is supposed that APE1 expres-
sion levels could be related to life expectancy of BC pa-
tients, and clinical assessment of APE1 expression
levels in intact and tumor tissues of mammary gland
could be of prognostic and predictive value [23].
Cancer-associated fibroblasts (CAFs) are known
to stimulate angiogenesis and metastasis [49, 50] and
an inflammatory and wound healing related activation
of fibroblasts are the main mechanisms of CAF activation
[33]. The functional state of CAFs was assessed in bi-
opsy specimens of breast adenocarcinoma using com-
bined method LC-MS/MS and bottom-up strategy [33].
In total, 2074 proteins from biopsy material fibroblasts
and 5212 proteins from cultured ZR-75-1 cells were
identified. Comparative analysis of proteins of untreated
fibroblasts, fibroblasts incubated with IL-1β (in vitro
modeling of inflammatory way of fibroblast activation)
or TGF-β (in vitro modeling of wound healing-induced
activation of fibroblasts) has shown that proteomic pro-
file of BC biopsy could be useful for assessment of cell
types at quiescent state, inflammation, wound healing.
Proteomic profile of CAFs was found to be close to that
of fibroblasts at the state of wound healing (common
proteins, including fibulin-5, SLC2A1 and MUC18).
The authors supposed [33] model CAFs systems could
be advantageous for testing the agents which inhibit
or reverse the proinvasive activity of the components
of tumor microenvironment.
Prognosis. At present time the existing clini-
cal criteria of pathologic process based on tumor
aggressiveness grading don’t reflect a real state
of cancer process for assessment of its progression
and prognosis [22]. With the use of top-down strat-
egy (me thods: affinity chromatography, 2D-PAGE
(SDS-PAGE)) and bottom-up strategy (combined
method LC-MS/MS) [22] protein signatures associ-
ated with histopathological grading (G1, G2, G3)
of breast tumors were indentified, 49 of which were
validated using the data of meta-analysis of transcrip-
tion profiling of tumors of independent group of pa-
tients. The special SW permitted to determine that the
validated proteins are localized in intercellular space,
plasma membrane, cytoplasm, and nuclei. The ob-
tained results could be important for the revision of the
microenvironment model during tumor progression
and be useful for classification and prognosis of BC.
Two proteins, transgelin and transgelin-2 could
be of clinical importance serving as prognostic pro-
teomic markers of metastasis of different tumor types
(pancreatic, colorectal, gastric, lung, BC) [37, 51–54].
Transgelin is a differentiation marker of smooth mus-
cles [55], and is expressed in myofibroblasts and CAFs
of gastric and lung tumors [54, 56]. Its up-regulation
in fibroblasts in gastric tumor tissue supports tumor
cell migration and invasion via increased production
of matrix metalloproteinase-2 [52], and this protein
is oncosuppressor, expression of which is down-
regulated by Ras oncoprotein in BC samples [57].
Hypermethylatioin of its promoter is related to down-
regulation of its expression in cell lines and tumor
tissues of mammary gland [58]. In regard to transge-
lin-2, its overexpression in breast tumor vasculature
has been reported [59]. Using proteomics methods,
a comparative analysis of expression of transgelin and
transgelin-2 in lymph nodes of BC patients has been
provided [37]. Using top-down strategy and 2D-PAGE
(SDS-PAGE) up-regulation of transgelin in positive
lymph nodes of BC patients with primary low grade
tumors and different lymph node status has been re-
vealed (see Table 2). These results were clinically vali-
dated on the larger group of BC patients with different
lymph node status (see Table 2). In this research [37],
a comparative proteomic analysis of transgelin and
transgelin-2 in tumor tissue of BC patients with the
use of bottom-up strategy demonstrated a specific
relation between transgelin and lymph node metas-
tasis in BC patients and tumor differentiation grade,
nevertheless no association of transgelin expression
with molecular markers ER, PR, HER2 has been found.
Since both presence [60] and absence [37] of specific
expression of transgelin have been reported, its speci-
ficity as a marker is under question. Down-regulation
of transgelin in high grade tumors and overexpres-
sion of transgelin-2 in metastatic and low differenti-
ated tumors were considered as a consequence
of stromal cells dedifferentiation [37]. It has been
shown (IHC/TMA) that transgelin is mostly expressed
in stromal cells (fibroblasts and endothelial cells),
while transgelin-2 is expressed in epithelial cells of the
tumors [37, 56]. The authors [37, 56] supposed that
tumor stroma is capable to express relevant proteomic
biomarkers of potential clinical importance.
The studies on gene expression profiling have
created large databases for genes, RNA and proteins
expressed in BC. In particular, in tumor samples
of BC patients and cell lines [61] overexpression
of KIFAP3 gene (located in 1q24 chromosome loci,
and coding for kinesin associated protein 3 (KIFAP3)
has been revealed [39]. Protein KIFAP3 is localized
in nucleus, cytoplasm and EPR [62, 63] and interacts
with the proteins involved in carcinogenesis: interac-
tion of KIFAP3 with APC affects cell migration [64,
154 Experimental Oncology 38, 146–157, 2016 (September)
65], KIFAP3 is phosphorylated with BRK or PTK6 ki-
nases in BC cell line BT20 [66], KIFAP3 is required for
BRK-induced cell migration [66] and may play a role
of a key effector of BRK signal pathway [66]. Experi-
mental study on validation of KIFAP3 protein [39] (see
Table 2) has shown its overexpression in the cells
of breast ductal carcinoma, mostly in cytoplasm.
Expression of one more protein considered as BC-
associated markers, namely RRBP1 (ribosome binding
protein), was studied [40]. RRBP1 is a multifunctional
membrane protein localized in rough EPR [67–69],
cytoplasm and nucleus [70], participating in trans-
location of nascent proteins through the membrane
of rough EPR [71]. RRBP1 interacts with KIF5B [72]
and is involved in ribosome binding [71], biosynthesis
of procollagen and terminal differentiation of secretory
tissues [67, 73]. High level of its expression was found
in some cancer cell lines [74], and its overexpression
was registered in colorectal cancer [75]. Overexpres-
sion of RRBP1 in the perinuclear region of cytoplasma
was documented in 84% (177/219) cases of breast
carcinoma [40] (see Table 2). These two examples
demonstrate an integrated interaction between the
data and sources of “omics” and systemic assessment
of functions of BC-associated proteins.
Systemic neoadjuvant therapy may increase the
risk of recurrence after organ-sparing operations and
promote the development of drug resistance [76–78].
Modern functional proteomics could be helpful for
prognosis of pathologic response to systemic neoad-
juvant therapy. Proteomic meta-analysis utilizing RPPA
method covering tumor specimens from 712 BC pa-
tients who received taxane and anthracycline-taxane
systemic therapy, has validated a panel from 10 pre-
dictive biomarkers (see Table 2) [38]. Based on these
findings, the patients may be stratified into 6 prognos-
tic groups: HER2+; ER–/PR– and ER–/PR–/HER2 with
unfavorable prognosis; ER+/PR+ with favorable
prognosis; and three intermediate groups that mostly
were characterized by overexpression of tumor cell
proteins involved in various cell processes (cyclines,
components of protein biosynthesis system, stromal
markers, proteins of mechanistic pathways).
For better stratification of the patients at the stage
of prescription of adjuvant chemotherapy and for prog-
nosis of the disease course in the study [42] the blood
serum samples of patients with primary BC and lymph
node metastases have been analyzed postoperatively.
With the use of ion-exchange and affine chromato-
graphy (immobilized metal affinity chromatography —
IMAC) combined with SELDI-TOF MS protein profil-
ing and MALDI-TOF/TOF MS for peptide profiling
4 mass peaks were revealed (m/z 3073, m/z 3274,
m/z 4405 and m/z 7973) believed typical of proteins
associated with recurrence-free survival of the pa-
tients. Among these potential biomarkers, a protein
with m/z 3274 was identified as an inter-alpha-trypsin
inhibitor heavy chain 4 fragment. These data should
be further validated with enrollment of an independent
group of patients, however, the authors consider the
use of anion-exchange fractionation combined with
SELDI-TOF MS as a promising tool for identification
of new prognostic markers of BC [42].
Improvement of quality of prteomic BC stu dies.
The studies of BC proteome and peptidome aimed
at the search of diagnostic and prognostic markers
develop dynamically, especially in regard to vali-
dated clinical results. Such aim requires perfection
of methodological and technical approaches for the
analysis and identification of various BC biomarkers.
As an example of the newest approaches one could
mention combining existing strategies and developing
new analytical platforms.
Combined strategies. A large number of works re-
viewed in [9] addressed advantages and disadvantages
of bottom-up and top-down strategies for different
tasks, and also expediency of their use for proteomic
analysis and quantification of protein molecules.
In the study [20], the complementarity of these
strategies was assessed with the use of combined
method LC-MS/MS and material of two BC models,
namely, patient-derived xenografts established from
a basal-like and luminal B BC subtypes. The study
has been designed as follows: testing of label-free
top-down quantitative proteomics platform (as far
as LC-MS/MS is used mostly with bottom-up strat-
egy); comparative analysis of differential expression
of proteins and their proteoforms with low molecular
weight (< 30 kDa) in the samples of basal and luminal
B molecular BC subtypes. The comparative analysis
of the efficacy of using bottom-up and top-down
strategies supported the 10-fold superiority of bottom-
up: identification of 49,185 groups of peptides and
quantification of 3519 proteins derived from them
versus 982 proteoforms and 358 proteins in the case
of top-down use. However, quantitative effective-
ness of the strategies had a ratio of 60:40, and the
use of top-down allowed to gain a unique informa-
tion complementing the data obtained with the use
of bottom-up. In turn, bottom-up was by 8 times more
accurate for identification of proteins with molecular
weight of 0–30 kDa. With the use of special SW, the
obtained data were validated. This work demonstrated
the priority of combination of these strategies in the
study of BC proteome and BC biology involving ge-
nome data, and also confirmed that bottom-up strat-
egy does not allow identifying the differences between
some post-translational modifications (for example,
phosphorylation).
New analytic platform. Tumor peptidome (intra-
cellular and intercellular products of protein degrada-
tion) could represent a potential source of biomark-
ers for tumor-related proteolytic properties. Using
combined method LC-MS/MS, an analytic platform
in silico has been developed which along with im-
proved protocol of peptides isolation complemented
the results of conventional bottom-up strategy. This
platform has been used for a complex analysis of pep-
tidome of ovarian cancer and xenografts of basal and
luminal BC subtypes [19]. The developed platform
Experimental Oncology 38, 146–157, 2016 (September) 155
represents the novel technological stage for further
determination of molecular features and functional
significance of peptidomic/degradomic activities
in tumor tissues. It is characterized by reproducibility
of the results and high capacity of studies on quantifi-
cation of identified peptides. The use of the platform
allowed one to identify peptidome profiles reflecting
the types of action of tumor-associated proteases;
the results were validated with the use of special
SW. The developed analytic platform and the obtained
data are of practical significance not only for tumor
tissue profiling in BC, but also in other cancer types
as far as aberrant degradation of proteins is inherent
to many of tumor types.
Methods for verification and validation of the
results of proteomic analysis. Verification and
validation of the results of experimental studies are
the mandatory stages is analyzing the bulk of findings
based on the generally accepted methods. Validation
means that from the pool of identified proteins only
relevant oncological markers of clinical significance
should be selected. Three groups of methods each
with its advantages and disadvantages, are being
used for this purpose: IHC based, TMA based, and
MS based (SRM/MRM-MS) [7]. Combined IHC/TMA
group of validation methods is becoming more and
more popular [37, 39, 40], because it allows to ana-
lyze the samples of tissues of larger size compared
to convenient TMA [7]. Common methods are
Western blot [14, 29] and MRM-MS [14, 21] while
SRM-MS [23], mTRAQ-SRM MS [37], IHC [44],
RPPA [38] and ELISA are less commonly used [36].
There is a trend for the use of several validation meth-
ods in one study for more effective assessment of the
significance of the obtained results (Western blot +
MRM-MS [14], mTRAQ-SRM MS + IHC/TMA [37],
Western blot + IHC [29], Table 2). It’s necessary
to note that RPPA has been used as the validation
method in proteomic meta-analysis of BC tissue
(n = 712) aimed at determination of predictive bio-
markers panel ([38], Table 2). The use of SW for verifi-
cation and validation of experimental results becomes
more common [19, 20, 25]. The results of proteomic
studies which were successfully validated are used
as clinically valid biomarkers for diagnostics, prog-
nosis and therapy of BC [29, 36–40, 44].
In conclusion, an analysis of literature sources
on BC proteomics indicated an important role of top-
down and bottom-up strategies as the major ones
in the search of proteomic BC biomarkers with the use
of LC-MS/MS. The technological progress is focused
on more wide use of a spectrum of elementary LC and
MS methods in a frame of combined LC-MS/MS. The
study of BC proteome is directed on profiling of various
biologic materials and is aimed at the improvement
of prophylaxis, screening, diagnostics, prognosis, and
therapy. A large pool of proteins of mammary gland
tumors and BC-associated proteins from body fluids
have been already identified, and in part they were
validated. The progress of validation methods is helpful
in more efficient application of BC biomarkers in clini-
cal practice. Taken together, the results of proteomics
studies demonstrate an integrated interaction of the
data and “omics” sources with the systemic approach
for assessment of functions of biomolecules in various
pathologies and BC in particular.
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