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Hermann
Lage
Priv.-Doz. Dr. Hermann Lage
Charite Campus Mitte
Institute of Pathology
Schumannstr. 20/21
D-10117 Berlin
Germany
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The global analysis of expressed cellular proteins is commonly
designated as �proteomics�. Proteomics techniques provide powerful
tools for the detailed comparison of proteins from normal and
neoplastic tissue. In particular, cancer cell lines are suited for
applying proteomics techniques, such as two-dimensional gel
electrophoresis (2D-PAGE) and mass spectrometry (MS), to identify
specific protein expression profiles and/or proteins that may be
associated with a defined phenotype of the cancer cells. As an
instance of such an application of proteomics techniques, the
detailed proteome analyses of different drug-resistant and
thermo-resistant cancer cell lines will be discussed. Following
proteome analyses, the potential roles of newly identified factors
have to be proven by functional studies. This experimental
validation strategy will be discussed for the �transporter
associated with antigen presentation� (TAP), a factor identified by
2D-PAGE analyzes of drug-resistant carcinoma-derived cell culture
models.
15.1 Introduction
Following the completion of the human genome sequence,
experimental endeavours have been more focused on a global analysis
of the proteins. This approach has been commonly designated as
�proteomics�. The term �proteome� is defined as the total protein
complement of a genome. The process of studying the proteome became
known as proteomics. However, traditionally proteomics has been
associated with displaying a large number of different proteins
from a given origin by two-dimensional polyacrylamide gel
electrophoresis (2D-PAGE). In this sense, proteomics already dates
back to the late 1960s when 2D-PAGE was introduced into biomedical
research for determination of the protein composition in the
ribosomal subunits ofEscherichia coli. During the following years,
the technique of 2D-PAGE was improved continuously.
There are several reasons for the intensified focus on the
analysis of protein expression profiles: the mRNA expression level
of a given gene frequently does not directly correspond to the
cellular amount of biological active protein; although the amino
acid sequence predicts potential modification sites within a given
protein, the real post-translational modifications, that may be
essential for biological function and activity, are not obvious;
and reclusive genomic data do not reflect dynamic cellular
processes. Moreover, proteomics includes the differential display
of proteins for comparison of e.g. different physiological or
disease states; it includes the characterization of protein
localization; it includes the analysis of protein-protein and
protein-nucleic acids interactions as well as the biochemical
analysis of protein function. Although 2D-PAGE and mass
spectrometry (MS) are currently the two most important proteomics
technologies, several other techniques have been developed and are
still under further development. These proteomics technologies
include the yeast two-hybrid system (Y2H), protein microarrays,
surface-enhanced laser desorption/ionisation (SELDI), tissue
microarray (TMA) technology, phage display method, and fluorescence
resonance energy transfer (FRET) technique. Thus, the proteomic
approach may have a major impact on the improved understanding of
biological problems associated with clinical questions.
15. 2 Proteomics in
cancer cell research
Various comparative 2D-PAGE experiments for analyzing
differences in the protein expression pattern of human cancer cell
lines have been performed. Cancer cell line-related investigations
included pure protein expression studies, e.g. protein expression
profiling in hepatocellular carcinoma (HCC) cells, gastric
carcinoma cells, ovarian carcinoma cells, or mammary carcinoma
cells. However, most of the cancer cell studies were performed on
account of functional investigations, e.g. analyzes of invasion and
metastasis, or proliferation and differentiation. Moreover, many of
these functional studies concerned the cellular response of cancer
cells against stress factors, including heat and drugs.
Furthermore, proteomics appears as a promising strategy to compare
the protein expression profiles in drug-resistant or other
therapy-resistant cancer cell lines with those of non-resistant
counterparts.
15.2.1
Therapy-resistant cancer cell lines
Therapy resistance, e.g. drug resistance, radiation resistance,
or thermo-resistance, is the main cause of therapeutic failure and
death in patients suffering from malignancies. Tumour cells can be
naturally resistant to anti-cancer treatment, and they are able to
develop acquired therapy-resistant phenotypes, which include the
multi-drug resistance (MDR) phenomenon. The MDR phenotype is
characterized by simultaneous resistance of tumour cells to various
anti-neoplastic agents that are structurally and functionally
unrelated. Besides the classical MDR phenotype, mediated by the
enhanced expression of the adenosine triphosphate-binding cassette
(ABC) transporter MDR1/P-glycoprotein (P-gp), alternative forms of
multidrug-resistant tumour cells have been described. Commonly used
terms to designate this phenomenon are atypical MDR or
non-P-gp-mediated MDR.
In recent years, some of the mechanisms leading to atypical MDR
have been identified. These mechanisms include enhanced expression
of alternative ABC-transporters, such as MRP1-MRP8 or BCRP, or
alterations in apoptotic pathways. However, since all these
mechanisms could not explain the MDR phenotype of all
drug-resistant cells, other additional resistance mechanism must be
operating in cancer cells. Furthermore, the current concept of MDR
is based on the hypothesis that MDR is multifactorial and
heterogenous.
To improve response rates of cancer patients to chemotherapeutic
treatment, in recent years chemotherapy has been combined with
experimental treatment regimens, e.g. hyperthermia. Good responses
have been reported with combined thermo-chemotherapy in several
experimental tumour models as well as in advanced cancer patients
including tumour cells exhibiting a MDR phenotype. Thus, it turned
out that chemotherapy combined with hyperthermia might be
considered as a promising approach. The clinical success of this
combined anti-cancer treatment may be limited by the induction of
MDR phenotypes and additionally by the development of
thermoresistance. Consequently, the elucidation of the biological
mechanisms involved in drug resistance and thermo-resistance is of
urgent importance to develop new treatment modalities and improve
response rates in advanced tumours.
In order to gain further understanding of therapy resistance in
human neoplasms, various in vitro model systems derived from many
tumour entities were established in recent years. For this
approach, commonly cancer cell lines were exposed to
stepwise-increased concentrations of different antineoplastic
agents for several months resulting in the selection of
drug-resistant sublines, respectively. In analogy, thermo-resistant
cell lines were established by exposure to increasing temperatures.
In various biochemical studies using these in vitro systems,
distinct differences between the therapy-sensitive parental cells
and the corresponding therapy-resistant sublines have been
described. However, since these studies could not explain all
therapy-resistant phenotypes of cancer cells in detail, other
additional mechanisms must contribute to drug resistance as well to
thermoresistance. A powerful strategy to identify new factors that
could play a role in therapy resistance of neoplastic cells is the
proteomic approach. Applying 2D-PAGE or alternative proteomics
techniques provide ideal tools to compare the protein expression
patterns in parental sensitive cancer cells with those in different
drug-resistant, thermoresistant, or radiation-resistant cancer cell
lines.
15.2.2 Proteomic
analyzes of therapy-resistant cancer cell lines
The first 2D-PAGE studies using cancer cell lines and
corresponding drug-resistant sublines were already performed in the
mid 1980s. In these experiments, expression patterns of
[35S]-methionine-labeled proteins prepared from parental KB cells
and multidrug-resistant variants selected for resistance against
colchicine, doxorubicin, or vinblastine, were analyzed. Protein
alterations in the multidrug-resistant lines included the decreased
prevalence of members of a family of proteins of molecular mass in
the rage of 70-80 kDa, pI 4.8-5.0, and the increased expression of
a 170 kDa protein in membrane preparations of these cell lines.
Moreover, in the colchicine-selected multidrug-resistant KB cell
variant KB-Ch, the increased synthesis of a protein of molecular
mass 21 kDa, pI 5.0, could be observed. Although, Western blot
experiments indicated that the increase in the expressed 170 kDa
protein is probably identical to P-gp, the identity of the
differential expressed proteins was not determined.
In the last years, systematic proteomics studies were performed
for identifying potential proteins involved in drug resistance
and/or thermoresistance by using cell culture models derived from
breast cancer, cervix carcinoma, colon carcinoma, fibrosarcoma,
gastric carcinoma, hepatoma, lung cancer, melanoma, and pancreatic
carcinoma. The sensitive parental cell lines and their
therapy-resistant sublines were analyzed for differences in the
protein expression patterns by 2D-PAGE. For this approach, several
independent 2D-PAGEs were regularly performed. Using PDQUEST
software the different gels were scanned. Commonly, the scanned
gels were used for calculation of cell line-specific master gel
images. Decreased or increased protein levels were determined by
comparing differences in the optical density of corresponding
protein spots in cell line-specific gel images. Proteins showing
differences in expression level were identified by MALDI-TOF MS, or
microsequencing after enzymatic hydrolysis in the gel. Subsequent
to this procedure, for some of the proteins the differential
protein expression level was confirmed by alternative, more
specific techniques.
Figure 1 illustrates an example of this strategy: the protein
expression patterns of the parental human pancreatic carcinoma cell
line EPP85-181P and its thermoresistant derivative EPP85-181P-RT
were analyzed by 2D-PAGE. The over expressed protein spot indicated
in Figure 1A, was hydrolyzed with trypsin and the MALDT-TOF MS
(Figure 1B) identified the spot as the endoplasmic reticulum (ER)
protein reticulocalbin.
Figure 1. Enhanced expression level of reticulocalbin in
thermoresistant pancreatic carcinoma EPP85-181P-TR cells. (A)
2D-PAGE analysis of silver stained protein expression patterns in
parental EPP85-181P cells and the thermoresistant counterpart
EPP85-181P-TR. (B) Mass spectrum (MS) of reticulocalbin following
in-gel digestion with trypsin. (Data are from Lage (2004) Pathol.
Res. Pract. 200: 105-117; the 2D-PAGE images were kindly provided
by Pranav Sinha, Klagenfurt, Austria; the reticulocalbin-specific
MS image was kindly provided by Martina Schn�lzer, DKFZ,
Heidelberg, Germany).
Figure 2 Analysis of protein expression by the proteomic approach
in the thermosensitive, parental gastric carcinoma cell line
EPG85-257P and in its thermoresistant variant EPG85-257P-TR. (A)
2D-PAGE analysis of silver stained protein expression patterns in
both cell lines. (B) Detail magnification of 2D-PAGE images. In the
thermoresistant cell line EPG85-257P-TR additional protein spots
could be observed. MALDI-TOF MS identified one of them as Hsp27 and
another spot as variant of Hsp27. (C) Confirmation of differential
Hsp27 expression by Western blot. (Data are from Lage (2004)
Pathol. Res. Pract. 200: 105-117; the 2D-PAGE images were kindly
provided by Pranav Sinha, Klagenfurt, Austria).
A further example is shown in Figure 2: the protein expression
profiles of parental human gastric carcinoma EPG85-257P cells and
the thermoresistant counterpart EPG85-257P-RT were analyzed by
2D-PAGE. Evaluation of the silver-stained gels using the PDQUEST
software revealed at least 19 MALDI-TOF MS-identified proteins
exhibiting alterations in the expression level. Figure 2B shows
increased expression of the small heat shock factor Hsp27 and of a
variant of Hsp27 in the thermoresistant variant EPG85-257P-TR. As
shown in Figure 2C, the increased expression of Hsp27 was confirmed
by Western blot analysis. Since expression of Hsp27 may be the
result of increased temperature, the data are conclusive.
Hsp27 may act in signal transduction pathways and is an
ATP-independent powerful molecular chaperone, its main chaperone
function being protection against protein aggregation. Its activity
contributes to mechanisms that enable tumour cells as well as
normal cells to survive and recover from stressful conditions by as
yet uncompletely understood mechanisms. Hsp27 is of special
clinical interest because of data suggesting its role in
thermoresistance by acting as an antiapototic protein. Thus, it is
not astonishing that the expression of Hsp27 is differentially
regulated in the thermoresistant cell variant. However, the exact
molecular mechanism of Hsp27, e.g. modulation of apoptotic signals
or correct refolding of drug-damaged proteins, by that Hsp27
contributes to thermoresistance, is not yet clear.
A large number of differentially expressed proteins could be
identified by comparing the 2D-PAGE protein expression patterns of
sensitive and therapy-resistant cancer cell variants. Only a few of
the factors identified in these 2D-PAGE studies have been
previously linked to drug resistance or thermoresistance. So far it
is not known how these proteins might be involved in therapy
resistance, or whether they are merely co-regulated, or the
alterations in expression may be the result of unspecific events.
Thus, it is absolutely essential to evaluate the data to find out
whether the potential new factor is functionally involved in
therapy resistance, or, e.g. in the case of a specific
co-regulation, is useful as diagnostic or prognostic marker.
15.2.3 Validation of
the biological relevance of the potential new factor �TAP�
2D-PAGE analyzes of a gastric carcinoma-derived drug resistance
model demonstrated various alterations in protein expression
profiles in the drug-resistant cell lines. Microsequencing of a
protein spot found to be overexpressed in the mitoxantrone-selected
atypical multidrug-resistant gastric carcinoma cell line
EPG85-257RNOV revealed amino acids sequences exhibiting similarity
to the �transporter associated with antigen processing� (TAP) 1.
Northern and Western blot analyzes confirmed that the expression
levels of TAP1 as well as of TAP2 are indeed increased in the
atypical multidrug-resistant gastric carcinoma cell line. TAP
represents an additional member of the ABC-transporter superfamily.
TAP, a heterodimer formed by TAP1 and TAP2 subunits,
physiologically plays a major role in major histocompatibility
complex (MHC) class I�restricted antigen presentation by mediating
peptide translocation over the endoplasmic reticulum (ER) membrane.
TAP1 and TAP2 are homologous polypeptides, each possessing a
hydrophobic N-terminal domain and a C-terminal nucleotide-binding
domain. Both monomers are required for peptide binding and
translocation, preferentially peptides of 8-15 amino acid residues.
It has been reported previously that over-expression of TAP could
be detected in MDR cell lines by using a TAP1-specific antiserum.
This study demonstrated that expression of rat cDNAs encoding TAP1
and TAP2 subunits in the TAP-deficient lymphoblastoid cell line T2
could lead to a slightly elevated tolerance to etoposide.
Consistent with these data, a cDNA microarray study analyzing the
mRNA expression profiles in different drug-resistant human hepatoma
cell lines, likewise identified TAP1 as associated with resistance
against mitoxantrone.
For functional validation of the potential role of TAP in the
mitoxantrone-selected atypical MDR phenotype of the gastric
carcinoma cell line EPG85-257RNOV, both TAP subunits encoding cDNA
molecules, TAP1 and TAP2, were transfected into the drug-sensitive
parental counterpart EPG85-257P. This experimental design conferred
a 3.3-fold resistance to mitoxantrone but no cross-resistance to
other antineoplastic agents. Furthermore, cell clones transfected
with both, but not singularly expressing TAP1 or TAP2, reduced
cellular mitoxantrone accumulation. The data indicate that the
heterodimeric TAP complex possesses characteristics of a xenobiotic
transporter and that the TAP dimer is functionally involved in
atypical MDR of human cancer cells. However, whether TAP is
possibly useful as a diagnostic or prognostic marker for drug
resistance, has to be evaluated in further studies using clinical
specimens.
15.3 Conclusions
Proteomics provides powerful tools to study pathological
processes or clinically important problems at the molecular level
and will have a major impact in the future. Since cell culture
models are widely used and characterized to a large extent, cell
lines, especially cancer cell lines, represent the ideal object to
evaluate and improve proteomics techniques. A specific and highly
reproducible manipulation of these models, e.g. an acquired
drug-resistant phenotype, can be analyzed in detail by methods such
as 2D-PAGE. Although functional studies could confirm that
potential factors that were identified by proteomics techniques are
indeed involved in the phenotype of interest, other investigations,
analyzing the role of a potential new factor, failed. Thus,
expression data obtained by proteomics studies should be considered
as preliminary. It is absolute necessary to perform
hypothesis-driven biochemical experiments to evaluate the potential
role of a protein of interest. Moreover, considerable technological
innovations are necessary to improve the repertoire of proteomics
technologies for applying them for better diagnostics and
introduction into clinical practice.
ACKNOWLEDGEMENTS
Own work in this field has been supported by the �Deutsche
Krebshilfe� (grant no. 10-1628-La 4). Many thanks to Pranav Sinha
and Julia Poland (Klagenfurt, Austria) and Martina Schn�lzer (DKFZ,
Heidelberg, Germany) for collaboration in the field of
proteomics.
References
- Hanash S: Disease proteomics. Nature (2003); 422, 226-232
- H�tter G, Sinha P: Proteomics for studying cancer cells and the
development of chemoresistance. Proteomics (2001); 1,
1233-1248
- Lage H: Proteomics in cancer cell research: an analysis of
therapy resistance. Pathol. Res. Pract. (2004); 200, 105-117
- Lawrie LC, Fothergill JE, Murray GI: Spot the differences:
proteomics in cancer research. Lancet Oncol. (2001); 2,
270-277
- Petricoin EF, Zoon KC, Kohn EC, Barret JC, Liotta LA: Clinical
proteomics: translating benchside promise into bedside reality.
Nat. Rev. Drug Dis. (2002); 1, 683-695
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