FLOW CYTOMETRY IN THE CLINICAL LABORATORY

Transcription

eJIFCC Vol 23 n° 4. 2012
Editor-in-Chief: Gábor L. Kovács,
e-mail:gabor.l.kovacs@aok.pte.hu
Publisher: IFCC
The JOURNAL OF THE INTERNATIONAL FEDERATION OF CLINICAL CHEMISTRY (eJIFCC) is an electronic journal with frequent updates on its home page. Our articles, debates, reviews and editorials are addressed to clinical laboratorians.
Besides offering original scientific thought in our featured columns, we provide pointers to quality resources on the
World Wide Web. The journal will publish general news articles, IFCC publicity/news, educational material and have a
letters section.
Aims and Scope
The Journal of the International
Federation of Clinical Chemistry and
Laboratory Medicine (eJIFCC) is an
online journal, published four times a
year, on the web site of the IFCC.
The peer-reviewed original articles,
posters, case studies and reviews,
are focused on the needs of clinical
laboratorians worldwide. In addition to
the peer-reviewed content, there are
also occasional editorials with pointers to quality resources on the Web.
Also the journal publishes some IFCC
news,letters, reviews of books, debates and educational material to
assist the development of the field
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medicine worldwide
FLOW CYTOMETRY IN THE CLINICAL LABORATORY,
János Kappelmayer
FOREWORD OF THE EDITOR,
Gábor L. Kovács
Pages
2-3
Page
4
FLOW CYTOMETRY IN THE DIAGNOSIS OF MYELODYSPLASTIC SYNDROMES,
Bettina Kárai, Eszter Szánthó, János Kappelmayer, Zsuzsa Hevessy
Pages
5-11
PREDICTION OF THERAPY RESPONSE AND PROGNOSIS IN LEUKEMIAS BY FLOW CYTOMETRIC MDR ASSAYS,
János Kappelmayer, Zsuzsa Hevessy, András Apjok, Katalin Tauberné Jakab
Pages
12-18
FLOW CYTOMETRIC INVESTIGATION OF CLASSICAL AND ALTERNATIVE PLATELET ACTIVATION MARKERS,
Béla Nagy Jr, Ildikó Beke Debreceni, János Kappelmayer
Pages
19-29
MEASUREMENT OF SOLUBLE BIOMARKERS BY FLOW CYTOMETRY,
Péter Antal-Szalmás, Béla Nagy Jr, Ildikó Beke Debreceni, János Kappelmayer
Pages
30-37
CALCIUM INFLUX CHARACTERISTICS DURING T LYMPHOCYTE ACTIVATION MEASURED
WITH FLOW CYTOMETRY,
Enikő Biró, Barna Vásárhelyi, Gergely Toldi
Pages
38-44
ADVANCES IN ORAL COAGULANTS,
Eleanor S. Pollak
Pages
45-48
1Janos
JÁNOS KAPPELMAYER
In this issue: FLOW CYTOMETRY IN THE CLINICAL LABORATORY
The Journal of the International Federation of Clinical Chemistry
and Laboratory Medicine
Guest editor
János Kappelmayer MD. PhD. DSc. head
Department of Laboratory Medicine, University of Debrecen, Hungary
This issue of the eJIFCC is dedicated to highlight some aspects of clinical flow cytometry. In the past 50 years several techniques
have revolutionized laboratory medicine. Undoubtedly flow cytometry is one of those, with a substantial impact on diagnosing
and monitoring diseases in laboratory hematology, hemostasis and immunology. The development in flow technology also
exerted a considerable effect on the accuracy of testing, as well as on turnaround times and on the objectivity of the reported
data. Although morphological investigation of peripheral blood and bone marrow smears has remained a gold-standard in
diagnosing malignant hematological disorders, recently flow cytometric studies are an absolute requirement in finalizing the
diagnosis of de novo leukemias, while in other areas, like minimal residual disease detection it completely replaced morphology
and has become a technique that can reliably identify 1 leukemic cell in 10,000 normal cells. Platelet glycoprotein abnormalities,
reticulated platelets, as well as activated platelets are all diagnosed today by flow cytometric techniques. For certain red blood
cell disorders like paroxysmal nocturnal hemoglobinuria and hereditary spherocytosis, flow cytometry is a key technique. This
method is required also in the diagnosis of immunodeficencies, autoimmune disorders, antigen specific T-cell responses,
allergy-testing and is utilized in transplantation immunology.
The wide repertoire of these diagnostic applications was made possible partly by the large arsenal of probes – e.g. directly
conjugated monoclonal antibodies, fluorescent probes for cell function and viability – as well as by the constant improvement
of the flow cytometers. Today, CE labeled benchtop analysers are routinely equipped with
2-3 lasers and can provide 8-10 color labelings with a high event rate per second, thus enables the acquisition of 0.5-1 million
cells in a reasonable time frame. Along with these developments in hardware and reagent supply, new softwares have been
developed. Thus, cytometrists can analyse and provide interpretative report for a large number of clinical samples in a relatively
short time, not mechanically reporting percent positivities for individual CD markers, but by describing only key phenotypic
findings and corrrelating staining patterns to diseases.
Clinical research and laboratory diagnostics can not always be sharply separated in flow cytometry. What is regarded today
as a research tool can soon turn to a diagnostic assay.
This issue of eJIFCC provides some examples for the versatility of this technology. The first paper describes the state of the art
multicolor flow analysis of myelodysplasia. The second publication is on a functional assay to identify the multidrug resistant
phenotype in hematological malignancies. Cardiovascular disorders like myocardial infarction and stroke are exemplified by
the presence of activated platelets. The third article depicts the possibilities to identify activated platelets by flow cytometry.
The fourth paper deals with a different approach, where we are analysing soluble plasma proteins by a flow technology that
uses either beads or cells as a reagent. Finally the analysis of intracellular calcium as a cell signalling event as well as a potential
disease marker is described by flow cytometric methods.
I am fascinated how, this ever-growing technology influenced our daily work in the past decades and I am sure that at least
two different directions of future developments will prevail. Most likely many assays will be applied to smaller scale
equipments, that will be affordable by more and more laboratories while on the other hand, frontline applied research will
generate diagnostic tests in many areas of cell biology – apoptosis studies, phosphoprotein and cell cycle analysis - that today
are carried out mostly only in research applications.
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21KOvacs
KOVÁCS L. GÁBOR
FOREWORD OF THE EDITOR
FOREWORD OF THE EDITOR
Janos Kappelmayer was born in Debrecen, Hungary in 1960. In 1985 he received his medical degree from the University of
Debrecen with "summa cum laude". After his residency program in clinical pathology, he obtained his board certification in
1989. He received a second board certification in laboratory hematology and immunology in 2003. He defended the PhD thesis
in 1994 and D.Sc. degree in 2008. His scientific interest is in laboratory diagnostics, hematology, and thrombosis research. Since
2004, he is the director of the Institute of Laboratory Medicine at the University of Debrecen. He spent two postdoctoral years
at The Sol Sherry Thrombosis Research Center, Temple University School of Medicine, Philadelphia (1990-92) and one year at
the Cardiovascular Biology Program, Oklahoma Medical Research Foundation as a Greenberg Scholar (2001). Dr. Kappelmayer
has several ongoing international research collaborations, e.g. with the Department of Medicine and Biochemistry at the
Oklahoma Health Sciences Center and the Cytometry Services Department of Hematology, University of Salamanca, Spain. He
was the tutor of 4 graduated PhD students in the areas of flow cytometry, leukemia diagnostics and thrombosis research. He
was invited speaker at several international meetings, e.g. Thrombosis research (ISTH, SSC meetings): Venice 2004, Oslo 2006;
Flow cytometry: Odense 1999, Antalya 2010; Laboratory medicine: Belgrade 2003, Berlin 2011, Istanbul 2014. He published 143
original papers, 93 of them in highly ranked international journals. His cumulative impact factor is 290, with 1540 independent
citations in the literature. In 2009-2011 he was the president of the Hungarian Society of Laboratory Medicine and a board
member of the European Society of Clinical Cell Analysis (ESCCA). Since 2003, he is the treasurer of the Hungarian Society of
Thrombosis and Hemostasis.
Kovács L. Gábor MD, PhD, DSc.
eJournal IFCC Editor-in-chief
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3karai
B. KÁRAI, E. SZÁNTHÓ, J. KAPPELMAYER, Z. HEVESSY
FLOW CYTOMETRY IN THE DIAGNOSIS OF
MYELODYSPLASTIC SYNDROMES
FLOW CYTOMETRY IN THE DIAGNOSIS OF MYELODYSPLASTIC SYNDROMES
Bettina Kárai, Eszter Szánthó, János Kappelmayer, Zsuzsa Hevessy
Department of Laboratory Medicine, University of Debrecen, Debrecen H-4032, Hungary
Corresponding Author:
Bettina Kárai
Department of Laboratory Medicine, University of Debrecen, Nagyerdei krt. 98,
Debrecen H-4032, Hungary
Tel: +36 30 386 2672
Fax: +36 52 417 631
e-mail: bettina.karai@gmail.com
Key words: myelodysplastic syndromes, flow cytometry, classification system, prognostic scoring system
ABSTRACT
Myelodysplastic syndromes are clonal hematopoietic stem cell disorders. Their exact etiology is unknown. Myelodysplastic
syndromes cause progressive bone marrow failure resulting in pancytopenia and refractory, transfusion-dependent anemia.
One can observe typical morphological alterations in the erythroid, myeloid and/or megakaryocytic cell lineage. Blast counts
may also be increased. The pathologic cells are genetically unstable, and a myelodysplastic syndrome might transform into acute
myeloid leukemia. The overall survival of these diseases range between few months to around ten years. Correct diagnosis and
accurate prognostic classification is essential. In the past decades several scoring systems were established beginning with the
French-American-British classification to the most recent Revised International Prognostic Scoring System. In all of these
classifications bone marrow morphology is still the most important factor, though nowadays the genetic aberrations and flow
cytometry findings are also included. The diagnosis and prognostic classification of myelodysplastic syndromes remain a great
challenge for hematologists.
INTRODUCTION
Myelodysplastic syndromes (MDS) are clonal hematopoietic stem-cell disorders. The incidence of MDS is 3.4 per 100,000/per
year in the United States, which increases with age. The median age at diagnosis is 76 years in the U.S. and 74 years in Europe.
The incidence is slightly higher in men than in women [1, 2].
The exact etiology of MDS is unknown. MDS have two subtypes according to their etiology, a primary (de novo) and a secondary
one. The development of the second type of MDS occurs more frequently after some environmental mutagenic event, such as
the effect of toxic chemicals, e.g. benzene, or treatment of malignant tumor with radiation and/or chemotherapy. Several studies
have examined the causes of MDS, which include environmental exposures, cytogenetic and epigenetic changes in stem cells
and progenitors, altered bone marrow microenvironment, immune dysregulation, and abnormal cell cycle regulation and
differentiation (Figure 1). Thus it has become commonly accepted that MDS is the result of a complex process [3].
Although MDS are a heterogeneous diseases group, there are some common characteristics to these pathological conditions.
One of these is the progressive bone marrow failure, which manifests in peripheral cytopenia due to ineffective hematopoesis.
In patient histories we often encounter anemia resistant to treatment (refractory anemia), while the bone marrow is hypercellular
and erythroid hyperplasia can be detected. When examining these peripheral and bone marrow samples, typical morphological
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Figure 1
Theories of pathophysiology involved in MDS development.
alterations – dysplastic features – can be observed, which might affect the erythroid, myeloid and megakaryocytic cell lineages.
In addition, blast counts might also be increased in severe cases. Another common characteristic is the genetic instability of the
pathological cells, which results in an enhanced risk of MDS transforming into acute myeloid leukemia (AML). This transformation
occurs in approximately 30 percent of the cases, and it is one of the most important causes of mortality of MDS. Further causes
of mortality may include consequences of ineffective haematopiesis and the complications of cytopenia (e.g. infections,
bleeding).
Overall survival time in MDS has a large interval from some months up to more than ten years, therefore correct diagnosis and
accurate prognostic classification are essential for the
optimal treatment [4, 5].
CLASSIFICATION SYSTEM, PROGNOSTIC SCORING SYSTEM
In the past 30 years, several classification and prognostic scoring systems have been developed. The first widespread
classification system was the French-American-British (FAB), which assigned patients to five categories: refractory anemia
(RA), refractory anemia with ringed sideroblasts (RARS), refractory anemia with excess blasts (RAEB), refractory anemia with
excess blasts in transformation (RAEB-T), and chronic myelomonocytic leukemia (CMML) [6]. This classification system is
based on the histopathological examination of peripheral and bone marrow specimens (Table 1), where the percentage of
sideroblasts and blasts are taken into consideration along with the morphologic features.
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Table 1
Typical morphologic alteration in MDS
dyserythropoiesis
dysgranulopoiesis
dysmegakaryocytopoiesis
anisocytosis
nuclear/cytoplasmic asynchrony
large megakaryocytes with unsegmented nuclei
poikilocytosis
hypogranulation
micromegakaryocytes
macrocytosis
nuclear hyposegmentation pseudo Pelger- Huet cells
megakaryocytes with two or more small, unconnected nuclei
increased dacryocytes
giant hypogranular platelets
basophil stippling
increased
nucleated red blood cell
nuclear fragmentation (karyiorrhexis)
nuclear budding (bridging)
ring sideroblasts
The International Prognostic Scoring System (IPSS), published in 1997, was based on at least seven previous risk assessments,
including the FAB classification as the most dominant source. In this study 816 primary MDS patients were examined in terms
of survival and AML evolution, respectively. Patients who had previously received intensive chemotherapy and those with CMML
(proliferative subtype) who had a higher white blood cell count (WBC) than 12000/µL were excluded from the analysis. All
variables (blast percentage, peripheral cytopenia, cytogenetic abnormalities, age and gender) were weighed according to their
statistical power. Finally three prognostic parameters – percentage of blasts, cytogenetic alteration, and the degree of peripheral
cytopenia – were selected to develop a new prognostic scoring system that assigned patients into one of four risk groups: low,
intermediate-1, intermediate-2, high (Table 2). There is significant difference between these groups in overall survival and in
the probability of AML evolution. Patients older than 60 and assigned to the low and intermediate-1 groups exhibited significantly
reduced overall survival [7].
Based on the results of IPSS the World Health Organization (WHO) made several changes to the FAB classification and
introduced a new system. One of the major alterations concerned the criteria of AML. While the FAB classification established
the diagnosis of AML when the blast percentage reached 30% in peripheral blood or bone marrow, the WHO reduced this
threshold to 20%; furthermore, it established a new category within AML, namely, AML transformed from MDS.
Consequently the former RAEB-T group is absent from the WHO classification. On the other hand, new groups were also created,
such as MDS with isolated 5q deletion – MDS del(5q); refractory cytopenia with multiple cell lineage dysplasia (RCMD), and
unclassified MDS – the RAEB group was also split on the basis of blast percentage (RAEB-1 and RAEB-2). The creation of the
MDS del(5q) group is justified by the different therapy requirements, especially good prognosis and idiosyncratic clinical
symptoms (anemia, normal or increased platelet count in the peripheral bloody, and increased count of hypolobulated
megakaryocytes in the bone marrow) of these patients. According to the most recent (2008) WHO recommendations, the
unclassified MDS group consists of patients with cytopenia and blast count under 1% in the peripheral blood and under 5% in
the bone marrow, while upon analyzing the latter, no cell lineage can be declared dysplastic, yet characteristic cytogenetic
alterations of MDS can be detected (Table 2). A cell lineage is dysplastic if clear dysplastic features are observed in at least 10%
of its cells. Beyond these morphological criteria, factors causing secondary dysplasia must also be excluded (iron-, B12-, folic
acid-, or copper-deficiency; infection (HIV), autoimmune disorders. [3,8,9,10,11].
The WHO Classification-Based Prognostic Scoring System (WPSS) was published in 2007, the advantage of which over IPSS is
the exclusion of FAB RAEB-T- and CMML patients . These patients are currently classified in the AML and MDS/MPN (MPN:
Myelo- Proliferative Neoplasm) category. Another advantage of WPSS is that it is a dynamic system that can be applied
throughout the course of the illness. This is because while in the IPSS study patients were examined only at diagnosis, participants
of the WPSS monitoring were repeatedly checked and re-classified if necessary. Furthermore, in addition to the WHO
classification and the karyotype, the WPSS incorporated a new, independent prognostic factor that is transfusion dependency
(Table 2) [12].
The above data demonstrate that morphology remains the basis for both diagnosis and prognostic classification but the current
WHO recommendations (2008) and the WPSS also considers the cytogenetic and clinical features. Even if the quality of the
sample is appropriate the examiners face a difficult task when looking for the minimum morphological criteria determined by
the WHO and the International Working Group on Morphology of Myelodysplastic Syndrome (IWGM-MDS) (Figure 2) [13]. In
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Table 2
Prognostic scoring systems in MDS
IPSS
BM blast(% )
point
WHO category
• <5
0
• 5…10
0,5
• 11…20
R…IPSS
point
BM blast %
point
• RA, RARS, 5q
0
• ≤2
0
• RCMD, RCMD…RS
1
• >2…<5
1
1,5
• RAEB…1
2
• 5…10
2
• 21 30
2
• RAEB 2
3
• >10
3
karyotype*
point
karyotype*
point
karyotype*
point
• good
0
• good
0
• very good
0
• intermediate
0,5
• intermediate
1
• good
1
• poor
1
• poor
2
• intermediate
2
cytopenias
point
transfusion requirement point
• poor
3
• 0/1
0
• no
0
• very poor
4
• 2/3
0,5
• regular
1
hemoglobin (g/dl) point
…
prognostic
variable
WPSS
…
…
• ≥10
0
• 8 <10
1
• <8
1,5
platelets (G/L)
point
• ≥100
0
• 50--<100
0,5
• <50
1
ANC (G/L)
point
• ≥0,8
0
• <8
0,5
…
risk score
risk groups
risk score
risk score
low
0
very low
0
very low
≤1,5
intermediate-1
0,5-1
low
1
low
>1,5-3
intermediate-2
1,5-2
intermediate
2
intermediate
>3-4,5
high
≥2
high
3-4
high
>4,5-6
very high
5-6
very high
>6
very good
• -Y alone
• del(11q)
karyotype*
good
• normal
• -Y alone
• del(5q) alone
• del(20q)alone
good
• normal
• -Y alone
• del(5q) alone
• del(20q) alone
good
• normal
• del(5q)
• del(20q)
• del(12p)
• double including del(5q)
intermediate
• +8
intermediate
• single miscellaneous
• double
abnormalities
• +8
intermediate
• single miscellaneous
• double
abnormalities
• del(7q)
• +8
• +19
• i(17q)
• any other single/double
independent clones
poor
• ≥3 abnormalities
poor
• chrom. 7 anomalies
• ≥3 abnormalities
• chrom. 7 anomalies
poor
• -7
• inv(3)/t(3q)/del(3q)
• double including-7/del(7q)
• complex 3 abnormalities
very poor
• complex >3 abnormalities
Based on
• Greenberg P. et al. International scoring system for evaluating prognosis in myelodysplastic syndromes. Blood 1997;89:2079-2088.
• Malcovati L. et al. Time-dependent prognostic scoring system for predicting survival and leukemic evolution in myelodysplastic syndromes. Journal of Clicinical
Oncology 2007; 25:3503-3510.
• Greenberg PL et al. Revised international prognostic scoring system for myelodysplastic syndromes. Blood 2012; 120:2454-2465.
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Figure 2
Minimal diagnostic criteria in MDS.
an attempt to provide an objective diagnosis and prognostic classification of MDS, in the last two decades several working groups
have been trying to introduce new technologies and to establish a new system of criteria.
One of the most documented methods is the application of flow cytometry [14] (Figure 3). comparing the antigen-expression
patterns of normal hematopoietic cells and of those taken from MDS patients reveals several characteristic distinctions on the
blasts [15,16] as well as on cells of the myeloid [17,18], erythroid [19], and megakaryocytic lineage [20,21]. The most important
are the followings: abnormal CD45 expression on the granulocytes and blast cells, decreased CD11b, HLA-DR, CD13, CD33,
CD14 expression on the monocytes; attenuation or complete loss of CD11b, CD13, CD16, CD33 on the granulocytes; appearance
of lymphoid markers (CD7, CD56) on granulocytes (Figure 4).
On this basis a flow-cytometric scoring system was created in 2003 (Flow Cytometric Scoring System, FCSS). The bone marrow
patterns of 115 MDS and 104 other patients along with 25 healthy individuals were examined with three-color flow cytometric
analysis. According to the pathological differences in the antigen-expression of the cells of the myeloid line, the intensity of the
side-scatter, the myeloid-lymphoid ratio, and the blast percentage MDS patients were classified in three groups (mild, moderate,
severe). Significant differences were found between the groups in terms of mean overall survival and relapse potential following
allogeneic bone marrow transplantation (111 patients). Comparing the FCSS and IPSS results of MDS patients, the two systems
showed good correlation, and the FCSS can offer extra information in the case of the IPSS intermedier-1 group, which facilitates
prognostic stratification [17].
In the minimum diagnostic criteria system based on the agreements of the 2006 MDS conference, flow cytometry figures as a
co-criterion. This way flow cytometry is indicated as a useful tool in cases where an unequivocal MDS diagnosis cannot be
established on the basis of clinical data, morphology, and cytogenetics. Two such conditions are known today, namely,
idiopathic cytopenia of undetermined significance (ICUS) and idiopathic dysplasia of uncertain significance (IDUS). In both
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Figure 3
Normal granulocyte, monocyte maturation. The arrows indicate the maturation process.
cases, diseases causing chronic cytopenia and dysplasia can be ruled out, yet only some of the minimum criteria of MDS are
met, therefore an MDS diagnosis cannot be established. In the case of ICUS, refractory cytopenia can be observed, accompanied
by mildly or unmodified morphology and normal karyotype, while patients classified as having IDUS exhibit the reverse, that is,
unequivocal dysplastic morphological features without the cytopenia necessary for diagnosis of MDS [13,22,23].
SUMMARY
In summary, the diagnosis and prognostic classification of MDS seems to be the greatest challenge among all myeloid neoplasms.
The uncertainty is sustained by several factors. On one hand, MDS is a rather heterogeneous group of diseases; on the other
hand, the correct evaluation of morphology—which serves as the basis for diagnosis and prognosis—is a difficult task even for
experienced examiners. Therefore in the past decades, to facilitate the more precise classification of patients with a number of
objective studies, such as well-defined anamnestic data (e.g., number of transfusions), laboratory parameters (WBC, absolute
neutrophil count, platelet count, lactate dehydrogenase value (LDH), ferritin, β2 microglobulin, etc.), cytogenetic, flow cytometric,
and molecular genetic research were int he center of interest. The most recent prognostic scoring systems reflect these efforts.
In case of the Revised International Prognostic Scoring System (R-IPSS), the prognostic power of several parameters (cytogenetic
alterations, degree of cytopenia, LDH, ferritin, β2 microglobulin, myelofibrosis, age, sex, FAB, WHO classifications) was tested
on numerous patients (IPSS n=816, R-IPSS n=7012). The analysis of such a large sample allowed the demonstration of the
prognostic effect of less frequent cytogenetic alterations, thus, instead of the three cytogenetic groups of IPSS, here five groups
facilitate the more precise anticipation of clinical outcome. Beside cytogenetics, the percentage of blasts, the hemoglobin
concentration, platelet and absolute neutrophil count proved to be the most determining parameters. On the basis of these
factors, patients are assigned to five risk groups, making the assessment of low-risk patients more precise [24,25] (Table 2).
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Figure 4
Characteristic distinctions of antigen-expression patterns in MDS. Histograms show one of the most important antigen expression on dysplastic
(red frame) and normal (yellow frame) granulocytes or monocytes.
The most up-to-date flow-cytometric scoring scales – such as the one prepared by European LeukemiaNET – also aid in the
diagnosis and prognostic classification of low-risk as well as ICUS and IDUS patients. In that study, 797 patient samples (417 lowrisk MDS, 380 pathologic control samples) were analyzed by flow cytometry. According to the results, merely four cytometric
parameters facilitate effectively the diagnosis of low-risk patients. These are the followings: the percentage of bone marrow
blasts, the percentage of progenitor B cells within CD34 positive cells, the mean fluorescence intensity of CD45 expression in
lymphocytes as compared to myeloblasts, and the granulocyte to lymphocyte side scatter ratio [18].
The results of these new studies contributed to the more objective and more precise diagnosis and clinical follow-up of MDS
throughout a wider institutional spectrum.
ACKNOWLEDGEMENTS
This work was supported by a TAMOP-4.2.2.B-11/1/KONV of the Medical and Health Science Center, University of Debrecen (B.K:).
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References
1. Ma X, Does M, Raza A, Mayne ST. Myelodysplastic syndromes: incidence and survival in the United States. Cancer 2007; 109:15361542.
2. EU MDS Registry http://www.leukemianet.org/content/leukemias/mds/eu_mds_registry/index_eng.html (download 2012. november 21.)
3. Warlick ED, Smith BD. Myelodysplastic Syndromes: Review of Pathophysiology and Current Novel Treatment Approaches. Current Cancer
Drug Targets 2007; 7:541-558.
4. Greenberg PL; Attar E; Bennett JM; Bloomfield CD; De Castro CM; Deeg HJ; Foran JM; Gaensler K; Garcia-Manero G; Gore SD; Head D; Komrokji
R; Maness LJ; Millenson M; Nimer SD; O’Donnell MR; Schroeder MA; Shami PJ; Stone RM; Thompson JE; Westervelt P. NCCN clinical practice
guidelines in oncology: myelodysplastic syndromes. Journal of the National Comprehensive Cancer Network 2011; 9:30-56.
5. Mufti GJ; Bennett JM; Goasguen J; Bain BJ; Baumann I; Brunning R; Cazzola M; Fenaux P; Germing U; Hellström-Lindberg E; Jinnai I; Manabe
A; Matsuda A; Niemeyer CM; Sanz G;Tomonaga M; Vallespi T; Yoshimi A. Diagnosis and classification of myelodysplastic syndrome:
International Working Group on Morphology of myelodysplastic syndrome (IWGM-MDS) consensus proposals for the definition and
enumeration of myeloblasts and ring sideroblasts. Haematologica 2008;93:1712-1717.
6. Bennett JM; Catovsky D; Daniel MT; Flandrin G; Galton DA; Gralnick HR; Sultan C. Proposals for the classification of the myelodysplastic
syndromes. Br J Haematol. 1982; 51:189-199.
7. Greenberg P; Cox C; LeBeau MM; Fenaux P; Morel P; Sanz G; Sanz M; Vallespi T; Hamblin T; Oscier D; Ohyashiki K; Toyama K; Aul C; Mufti
G; Bennett J. International scoring system for evaluating prognosis in myelodysplastic syndromes. Blood 1997; 89:2079-2088.
8. Vardiman JW, Harris NL, Brunning RD. The World Health Organization (WHO) classification of the myeloid neoplasms. Blood 2002 100:22922302.
9. Vardiman JW; Thiele J; Arber DA; Brunning RD; Borowitz MJ; Porwit A; Harris NL; LeBeau MM; Hellström-Lindberg E; Tefferi A; Bloomfield
CD. The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and
important changes. Blood 2009; 114:937-951.
10. Van den Berghe H; Cassiman JJ; David G; Fryns JP; Michaux JL; Sokal G. Distinct haematological disorder with deletion of the long arm of
no. 5 chromosome. Nature 1974; 251:437-441.
11. Dunlap WM, James GW, Hume DM. Anemia and neutropenia caused by copper deficiency. Ann Intern Med. 1974; 80:470-476.
12. Malcovati L; Germing U; Kuendgen A; Della Porta MG; Pascutto C; Invernizzi R; Giagounidis A; Hildebrandt B; Bernasconi P; Knipp S; Strupp
C; Lazzarino M; Aul C; Cazzola M. Time-dependent prognostic scoring system for predicting survival and leukemic evolution in
myelodysplastic syndromes. Journal of Clicinical Oncology 2007; 25:3503-3510.
13. Valent P; Horny HP; Bennett JM; Fonatsch C; Germing U; Greenberg P; Haferlach T; Haase D; Kolb HJ; Krieger O; Loken M; van de Loosdrecht
A; Ogata K; Orfao A; Pfeilstöcker M; Rüter B; Sperr WR; Stauder R; Wells DA. Definitions and standards in the diagnosis and treatment
of the myelodysplastic syndromes: Consensus statements and report from a working conference. Leukemia Research 2007; 31:727-736.
14. Wood B. Multicolor immunophenotyping: human immune system hematopoiesis. Methods in Cell Biology 2004; 75:559-576.
15. Satoh C; Tamura H; Yamashita T; Tsuji T; Dan K; Ogata K. Aggressive characteristics of myeloblasts expressing CD7 in myelodysplastic
syndromes. Leukemia Research 2009; 33:326-331.
16. Ogata K; Satoh C; Hyodo H; Tamura H; Dan K; Yoshida Y. Association between phenotypic features of blasts and the blast percentage in
bone marrow of patients with myelodysplastic syndromes. Leukemia Research 2004; 28:1171-1175.
17. Wells DA; Benesch M; Loken MR; Vallejo C; Myerson D; Leisenring WM; Deeg HJ: Myeloid and monocytic dyspoiesis as determined by
flow cytometric scoring in myelodysplastic syndrome correlates with the IPSS and with outcome after hematopoietic stem cell
transplantation. Blood 2003; 102:394-403.
18. Westers TM; Ireland R; Kern W; Alhan C; Balleisen JS; Bettelheim P; Burbury K; Cullen M; Cutler JA; Della Porta MG; Dräger AM; Feuillard
J; Font P; Germing U; Haase D; Johansson U; Kordasti S; Loken MR; Malcovati L; te Marvelde JG; Matarraz S; Milne T; Moshaver B;
Mufti GJ; Ogata K; Orfao A; Porwit A; Psarra K; Richards SJ; Subirá D; Tindell V; Vallespi T; Valent P; van der Velden VH; de Witte TM; Wells
DA; Zettl F; Béné MC; van de Loosdrecht AA. Standardization of flow cytometry in myelodysplastic syndromes: a report from an international
consortium and the European LeukemiaNet Working Group. Leukemia 2012; 26:1730-1741.
19. Kuiper-Kramer PA; Huisman CM; Van der Molen-Sinke J; Abbes A; Van Eijk HG. The expression of transferrin receptors on erythroblasts in
anaemia of chronic disease, myelodysplastic syndromes and iron deficiency. Acta Haematol 1997; 97:127-131.
20. Tomer A. Human marrow megakaryocyte differentiation: multiparameter correlative analysis identifies von Willebrand factor as a sensitive
and distinctive marker for early (2N and 4N) megakaryocytes. Blood 2004; 104:2722-2727.
21. Sandes AF; Yamamoto M; Matarraz S; Chauffaille Mde L; Quijano S; López A; Oguro T; Kimura EY; Orfao A: Altered immunophenotypic
features of peripheral blood platelets in myelodysplastic syndromes. Haematologica 2012; 97:895-902.
22. Valent P; Jäger E; Mitterbauer-Hohendanner G; Müllauer L; Schwarzinger I; Sperr WR; Thalhammer R; Wimazal F. Idiopathic bone marrow
dysplasia of unknown significance (IDUS): definition, pathogenesis, follow up, and prognosis. Am J Cancer Res 2011; 1:531-541.
23. Valent P; Bain BJ; Bennett JM; Wimazal F; Sperr WR; Mufti G; Horny HP. Idiopathic cytopenia of undetermined significance (ICUS)
and idiopathic dysplasia of uncertain significance (IDUS), and their distinction from low risk MDS; Leukemia Research 2012; 36:1-5.
24. Greenberg PL; Tuechler H; Schanz J; Sanz G; Garcia-Manero G; Solé F; Bennett JM; Bowen D; Fenaux P; Dreyfus F; Kantarjian H; Kuendgen
A; Levis A; Malcovati L; Cazzola M; Cermak J; Fonatsch C; LeBeau MM; Slovak ML; Krieger O; Luebbert M; Maciejewski J; Magalhaes SM;
Miyazaki Y; Pfeilstöcker M; Sekeres M; Sperr WR; Stauder R; Tauro S; Valent P; Vallespi T; van de Loosdrecht AA; Germing U; Haase D.
Revised international prognostic scoring system for myelodysplastic syndromes. Blood 2012; 120:2454-2465.
25. Schanz J; Tüchler H; Solé F; Mallo M; Luño E; Cervera J; Granada I; Hildebrandt B; Slovak ML; Ohyashiki K; Steidl C; Fonatsch C; Pfeilstöcker
M; Nösslinger T; Valent P; Giagounidis A; Aul C; Lübbert M; Stauder R; Krieger O; Garcia-Manero G; Faderl S; Pierce S; LeBeau MM; Bennett
JM; Greenberg P; Germing U; Haase D. New comprehensive cytogenetic scoring system for primary myelodysplastic syndromes and
oligoblastic AML following MDS derived from an international database merge. J Clin Oncol 2012; 30:820-829.
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4kappelmayer
J. KAPPELMAYER, Z. HEVESSY, A. APJOK,
K. TAUBERNÉ JAKAB
PREDICTION OF THERAPY RESPONSE AND PROGNOSIS IN
LEUKEMIAS BY FLOW CYTOMETRIC MDR ASSAYS
PREDICTION OF THERAPY RESPONSE AND PROGNOSIS IN LEUKEMIAS BY FLOW CYTOMETRIC
MDR ASSAYS
János Kappelmayer1, Zsuzsa Hevessy1, András Apjok2, Katalin Tauberné Jakab2
Department of Laboratory Medicine, Medical and Health Science Center, University of Debrecen, Hungary, 2Solvo Biotechnology,
Szeged, Hungary
1
János Kappelmayer, Department of Laboratory Medicine, Medical and Health
Science Center, University of Debrecen, Hungary
Tel: +36 52-340-006
Fax: +36 52-417-631
e-mail: kappelmayer@med.unideb.hu
Key words: flow cytometry, leukemia, drug-resistance
ABSTRACT
Multidrug resistance (MDR) is an unwanted phenomenon, that may cause therapy failure in several neoplasms including
hematological malignancies. The purpose of any type of laboratory MDR assay is to reliably identify such patients and to provide
useful data to clinicians with a relatively short turnaround time. MDR can be multicausal and several previous data identified a
group of transmembrane proteins - the ATP-binding casette (ABC) proteins - that may be involved in MDR in various
hematological malignancies. The prototype of these proteins is the P-glycoprotein (Pgp, MDR1, ABCB1) that is a seven-membrane
spanning transmembrane protein capable of extruding several cytotoxic drugs that are of key importance in the treatment
of hematological disorders. Similarly other ABC proteins – Multidrug resistance associated protein 1 (ABCC1) and breast
cancer resistance protein (ABCG2) are both capable of pumping out cytotoxic drugs. Here, we present flow cytometric methods
to identify MDR proteins by antigen and activity assays. The advantage of flow technology is the short turnaround time and its
relative easiness compared to nucleic acid based technologies. However, for the activity assays, it should be noted, that these
functional tests require live cells, thus adequate results can only be provided if the specimen transport can be completed within
6 hours of sample collection. Identification of MDR proteins provides prognostic information and may modulate therapy, thus
signifies a clinically useful information in the evaluation of patients with leukemias.
INTRODUCTION
Drug resistance may be intrinsic or acquired and it severely impairs the progress in cancer chemotherapy [1,2]. The importance
of this phenomenon is underlined by the fact that its presence is not limited to malignancies but may hamper the success of
therapy in several other diseases like rheumatoid arthritis and epilepsy. In MDR, resistance occurs to several chemically unrelated
drugs, lipid-soluble drugs like anthracyclines, vinca alkaloids, epipodophyllotoxins, antibiotics and the resistance can be caused
by one or more of several mechanisms. A frequently observed phenomenon is when the drug is quickly extruded from the cell
by transporters before any cytotoxic action can be elicited. These efflux proteins are localized in the cell membrane, however
further intracellular sites were also described and these are thought to contribute to resistance by accumulating the drug in
intracellular compartments and preventing it from reaching its nuclear targets [3].
The best studied efflux pump is a permeability glycoprotein (P-glycoprotein, Pgp) which is a 170 kDa protein that cleaves ATP to
cover the energy needed for expelling many xenobiotics. Pgp consists of two homologous halves, each consisting of six
transmembrane segments and one ATP-binding domain. The most accepted model is based on the presence of a catalytic
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K. TAUBERNÉ JAKAB
intermediate where both catalytic sites of Pgp are active and ATP is hydrolysed alternatively alternatively (Figure 1.). ATP
hydrolysis at one site triggers conformational changes within the protein resulting in drug transport, while hydrolysis of a second
ATP at the other site is required for resetting the original high- affinity binding conformation [4-7]. The transmembrane
segments containing the drug-binding site are quite mobile so drug binding occurs through a substrate-induced fit mechanism.
This mechanism explains how Pgp can accommodate a broad range of compounds [7]. Pgp was designated as MDR1 and it was
shown 25 years ago, that the expression of a full-length cDNA for the human "MDR1" gene confers resistance to colchicine,
doxorubicin, and vinblastine [8]. The human Pgp belongs to a large group of transport proteins, known as ATP-binding casette
(ABC) superfamily, that share common structural and functional properties. To date, about 50 human ABC transporter genes
have been identified. Their protein products are classified into seven groups entitled: ABCA-ABCG.
In addition to MDR proteins other membrane pumps extrude somewhat different substrates than Pgp. A 190 kDa protein called
MRP (multidrug resistance related protein) is a group of transporters that can contribute to clinical resistance. In contrast to
Pgp, MRP1 expression is predominant in the basolateral plasma membrane. MRP protein functions as a multispecific organic
anion transporter, with oxidized glutathione, cysteinyl leukotrienes, and activated aflatoxin B1 as substrates. This protein also
transports glucuronides, sulphate conjugates of steroid hormones, bile salts and other hydrophobic compounds in the presence
of glutathione [9-12]. MRP proteins play an important physiological role in the protection of the body against xenobiotics
occurring in the environment. MRP2 and MRP3 seem to play a role in organic conjugate transport while MRP4 and MRP5
may have a nucleotide transporter function.
The third most studied efflux protein is the breast cancer resistance protein (BCRP, ABCG2). Its mRNA encodes this 663 amino
acid member of the ATP-binding cassette superfamily of transporters. Enforced expression of the full-length BCRP cDNA in
MCF-7 breast cancer cells confers resistance to mitoxantrone, doxorubicin, and daunorubicin, reduces daunorubicin accumulation
and retention, and causes an ATP-dependent enhancement of the efflux of rhodamine 123 in the cloned transfected cells [13].
Furthermore its over-expression was identified as a negative prognostic marker in acute myeloid leukemia patients and it was
described that the survival significantly worsened in case of BCRP over-expression concomitant with Pgp and other unfavourable
prognostic markers. [14, 15].
IMPORTANCE OF DRUG RESISTANCE IN HEMATOLOGICAL MALIGNANCIES
The importance of MDR in hematological malignancies seem to be well-established, since from the historic paper of Ueda et al.
in 1987 over 1400 hits can be found in Medline about MDR and leukemias. The mechanisms that may contribute to the enhanced
Pgp expression are the activity of its transcription factor [16], gene rearrangement [17], or hypomethylation of the mdr-1
promoter region [18]. In addition, Pgp has been investigated in lymphoid malignancies and it has been demonstrated that
patients with increased level of Pgp, either at diagnosis or upon relapse have poorer prognosis than those patients who do not
express Pgp [19-21]. Undoubtedly however, the majority of literature deals with MDR in AML patients, where drug resistance is
primarily determined by Pgp [22-24] although other transporters were also found to have significance [25-27].
Figure 1
Function of MDR proteins. Drug-efflux proteins like Pgp expel xenobiotics already from the cell membrane, thus most of these molecules can
not enter the cell.
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Aside from de novo resistance, MDR can develop during chemotherapy as sensitive cells are killed off and genetic resistance is
induced either by the chemotherapy itself or emerges spontaneously during treatment. Although normal tissues possess
constitutive Pgp activity, acquired resistance never develops in noncancerous cells. Pgp may not only influence disease outcome
as a pump protein, but because of its involvement as an intramembranal substrate transport, it may have anti-apoptotic effect
as well.
In addition to the analysis of MDR pump function at the protein level, several studies have lead the way to delineate the role of
MDR-1 genetic polymorphisms in disease outcome. MDR-1 single nucleotide polymorphisms were found to be associated with
an achievement of complete remission and event-free survival in AML patients, however they were not found to be associated
with overall survival [28].
METHODS TO DETECT DRUG RESISTANCE
A few considerations are important when MDR diagnostic assays are discussed. One is that in hematological malignancies more
than one mechanism of drug resistance may be present that may impose a special diagnostic problem. The other is that most
of the data on MDR assays are derived from measurements on cell lines. However in clinical samples the efflux proteins like Pgp
is present in several orders of magnitude lower copy numbers. There are three different approaches to identify MDR.
(i) RNA measurement for different MDR proteins
(ii) determination of protein expression by flow cytometry or immunohistochemistry
(iii) functional tests that measure the transport activity of MDR proteins.
The 3-4,5 dimethylthiazol-2-yl-2,5-diphenyltetrazolium-bromide (MTT) assay or that is more simply referred to as cell survival
assays is used in some laboratories. It reports results in quantitative terms, however it is laborious and requires 4 days and thus
is unsuitable for routine analysis of clinical samples. According to a consensus paper published in 1996 [29] two methods have
to be executed in order to obtain reliable results for MDR testing. The problem with RNA measurement is that mRNA level does
not necessarily correlate with the expression of the relevant proteins and the mRNA results are often provided only in
semi-quantitative terms.
MDR ANTIGEN AND ACTIVITY MEASUREMENTS
Antigenic assays are easy to execute and thus can easily fit into the general routine of a flow cytometry laboratory as all CD
markers are detected by using directly conjugated antibodies. However, the major drawback of antigenic detection of MDR is
that the different clones of antibodies have variable sensitivity and thus the results obtained are often highly variable.
Furthermore, reporting of MDR antigenic data is not straightforward as in many cases the conventional percent positivity is not
very meaningful due to the low expression rate in clinical samples. Thus, authors report the results in terms of fluorescence
units or mean fluorescence intensities. Here, the ratio of the sample mean fluorescence channel and the isotypic control
fluorescence channel was calculated and MFI ratios exceeding values found on normal blood cells were reported as positive.
Thus, relative fluorescence intensity values (RFI) are usually provided for various MDR proteins when measured by antibodies
[30]. Some papers, however points to the possibility that certain antibodies detecting MDR1 have been shown to be sensitive
to conformational changes [31,32], thus an increase in antibody binding capacity may be exploited in the investigation of clinical
samples. Functional assays definitely offer an advantage over antigen measurements since they measure the clinically relevant
property, the transport activity of MDR proteins. The most widely used functional assay to detect MDR activity is based
on the measurement of a fluorescent substrate. These are mainly accumulation type assays where the fluorescent dye is
continuously accumulated in the cell either due to its binding to intracellular structures like doxorubicin or due to its intracellular
enzymatic modification like in case of calcein-acetoxymethyl ester. The fluorescence tracers in the majority of these assays are
the rhodamine 123 [33], calcein-AM, [34] or JC1 [35]. The tracer JC1 has proven to be useful for the simultaneous detection of
Pgp activity and apoptosis in leukemic cells [36]. These functional assays are evaluated by flow cytometry and the principle of
the measurement is to measure fluorescence of cells in the presence and absence of efflux pump inhibitors. An advantage
of functional assays is, that they can be combined with surface staining of the leukemic cells, thus the cell population of interest
can be gated out [37] by labelling the sample by the appropriate antibody and the efflux activity of the desired cells population
is analysed with and without the efflux pump inhibitor (Figure 2). It should be noted that in this assay the positive population is
represented with the lower fluorescence values– since the indicator dye is removed from the cells – while in an antigen assay
the positive cells are always displayed with higher fluorescence values as observed with any other flow cytometric antigen assay
(Figure 3.).
The quantitative results of the functional assay can be expressed in multidrug resistance activity factor (MAF) units by using
selective inhibitors. The difference in fluorescence is proportional to the activity of the efflux pump. In a typical flow activity
assay, MDR1 and MRP1 are inhibited separately and thus total MDR activity can more appropriately be dissected. A definite
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Figure 2
Functional MDR assay in an AML sample. The cells are identified on the FS-SS dot plots (panel A) than subsequently the CD45-dim myeloid
blasts are gated out (panel B). Calcein is measured on the blasts in the presence (panel C) or absence (Panel D) of an MDR inhibitor. Note that
the fluorescence values are lower in the absence of the inhibitor.
disadvantage of the functional assays, however that they require living cells, thus prolonged storage of samples is not possible.
This is probably one reason why the detection of MDR in flow cytometry laboratories is relatively rare.
In our previous work the functional assay was correlated to an antigenic assay carried out by quantitative flow cytometry [38].
We performed the determination of the antibody binding capacity by incubating cells with the anti-Pgp antibody MRK16 and
subsequently with a FITC labeled anti-mouse IgG. Results were expressed as ABC by using a calibration curve obtained by
measuring the fluorescence intensity of precalibrated beads. The multidrug resistance activity factor (MAF) values were
determined with the MDR inhibitor Verapamil (Vp). In triplicate samples by the preincubation of samples with (Vp+) or without
(Vp-) the MDR blocker and subsequently loading them with calcein-AM. The calcein fluorescence was measured and the values
MFI (Vp+) – MFI (Vp-)/MFI (Vp+) x100 were reported as the MAF value corresponding to MDR activity. This quantitative
measurement of MDR activity is characteristic for the cumulative activity of Pgp and MRP1 as verapamil inhibits both
transporters. When MAF was determined in the presence of the MRP1 inhibitor MK571 the MAFVp-MAFMK571 value referred to
the Pgp specific resistance.
We found that in the high Pgp expressor KB-V1 cell line an extremely high MDR activity was detectable along with high number
of Pgp molecules/cell while in the low expressor KB-8-5 cell line the functional assay resulted only in a 20% decrease while the
number of Pgp molecules decreased by over 90%. This also refers to the better sensitivity of the functional assay.
A commercially available kit is available that measures the activity of multiple transporters. Preliminary results with this
MultiDrugQuant assay kit were published and the authors were able to show a significant correlation between the expression
of the multidrug resistant proteins (P-gp and MRP1) and their functional activity in adult AML and pediatric ALL samples [39].
This test was also suitable to identify drug resistance in solid tumors as collagenase disintegration preserved the MDR activity
and the antigenicity of tumor cells. The extended calcein assay provided sufficient viable and functionally active tumor cells
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Figure 3
Comparison of the functional an antigen assays in cell lines. In the functional MDR assays (panel A) positive cells display reduced
fluorescence values since they expel the fluorescent dye. In the antigen assays (panel B) the positive cell line displays higher fluorescence due
to binding the fluorescent antibody.
from surgical biopsies to determine the functional MDR activity [40].
In 2011 the SOLVO-MDQ kit received a CE/IVD qualification. It provides all necessary ingredients to execute functional MDR
assays for Pgp, MRP1 and BCRP by using selective inhibitors and two different fluorescence dyes and as a minimum requirement
a 4-color flow cytometer is required.
CONCLUSIONS
Flow cytometry is increasingly been used in clinical laboratories and today already small benchtop cytometers can provide the
advantage of using multiple colors. We anticipate that in hematology, as many novel probes emerge functional assays may
become more popular and one such application is likely to be the detection of MDR protein activities, that is easier with a CEmarked diagnostic kit.
ACKNOWLEDGEMENT
The author would like to thank Valéria Sziráki Kiss for technical assistance. This study was supported by the IVDMDQ08 NKTH
project.
References:
1. Fojo T, Bates S. Strategies for reversing drug resistance. Oncogene. 2003; 2:7512-7523.
2. Tsuruo T, Naito M, Tomida A, Fujita N, Mahima T, Sakamoto H, Haga N. Molecular targeting therapy of cancer; drug resistance, apoptosis
and survival signal. Cancer Sci. 2003; 94: 15-21.
4
P a g5 e 1 6
K. TAUBERNÉ JAKAB
3. Munteanu, Verdier M, Grandjean-Forestier F, Stenger C, Jayat-Vignoles C, Huet S, Robert J, Ratinaud MH. Mitochondrial localization and
activity of P- glycoprotein in doxorubicin-resistant K562 cells. Biochem Pharmacol. 2006;71: 1162-1174.
4. Ramachandra, M, Ambudkar, SV, Chen D, Hrycyna CA, Dey S, Gottesman MM, Pastan I. Biochemistry, Human P-glycoprotein exhibits
reduced affinity for substrates during a catalytic transition state. 1998; 37, 5010-5019
5. Hrycyna CA, Ramachandra M, Ambudkar SV, Ko YH, Pedersen PL, Pastan I, Gottesman MM. Mechanism of action of human P-glycoprotein
ATPase activity. Photochemical cleavage during a catalytic transition state using orthovanadate reveals cross-talk between the two ATP
sites J Biol Chem 1998; 273, 16631- 16634
6. Loo TW, Clarke DM. Vanadate trapping of nucleotide at the ATP-binding sites of human multidrug resistance P-glycoprotein exposes different
residues to the drug-binding site. Proc Natl Acad Sci USA, 2002; 99, 3511-3516
7. Loo TW, Bartlett MC, Clarke DM. Substrate-induced conformational changes in the transmembrane segments of human P-glycoprotein.
Direct evidence for the substrate-induced fit mechanism for drug binding. J Biol Chem 2003; 278, 13603- 13606
8. Ueda K, Cardarelli C, Gottesman MM, Pastan I. Expression of a full-length cDNA for the human "MDR1" gene confers resistance to colchicine,
doxorubicin, and vinblastine. Proc Natl Acad Sci U S A. 1987; 84: 3004-3008.
9. Borst P, Evers R, Kool M, Wijnholds J. The multidrug resistance protein family. Biochim Biophys Acta. 1999; 1461:347-357.
10. Hipfner DR, Deeley RG, Cole SP. Structural, mechanistic and clinical aspects of MRP1.Biochim Biophys Acta. 1999;1461:359-376.
11. Manciu L, Chang XB, Buyse F, Hou YX, Gustot A, Riordan JR, Ruysscahert JM. Intermediate structural states involved in MRP1-mediated
drug transport. Role of glutathione. J Biol Chem 2003; 278 :3347-3356.
12. Bodo, A.; Bakos, E.; Szeri, F.; Varadi, A.; Sarkadi, B. The role of multidrug transporters in drug availability, metabolism and toxicity. Toxicol
Lett. 2003;140-141:133-143.
13. Doyle LA, Yang W, Abruzzo LV, Krogmann T, Gao Y, Rishi AK, Ross DD. A multidrug resistance transporter from human MCF-7 breast cancer
cells. Proc Natl Acad Sci U S A. 1998;95(26):15665-15670.
14. Damiani D, Tiribelli M, Michelutti A, Geromin A, Cavallin M, Fabbro D, Pianta A, Malagola M, Damante G, Russo D, Fanin R. Fludarabinebased induction therapy does not overcome the negative effect of ABCG2 (BCRP) over-expression in adult acute myeloid leukemia patients.
Leuk Res. 2010;34(7):942-945.
15. Tiribelli M, Geromin A, Michelutti A, Cavallin M, Pianta A, Fabbro D, Russo D, Damante G, Fanin R, Damiani D. Cancer. Concomitant ABCG2
overexpression and FLT3-ITD mutation identify a subset of acute myeloid leukemia patients at high risk of relapse. Cancer. 2011;117: 21562162.
16. Lutterbach B, Sun D, Schuetz J, Hiebert SW. The MYND motif is required for repression of basal transcription from the multidrug resistance
1 promoter by the t(8;21) fusion protein. Mol Cell Biol. 1998 Jun;18(6):3604-3611.
17. Mickley LA, Spengler BA, Knutsen TA, Biedler JL, Fojo T. Gene rearrangement: a novel mechanism for MDR-1 gene activation. J Clin Invest.
1997;99(8):1947-1957.
18. Nakayama M, Wada M, Harada T, Nagayama J, Kusaba H, Ohshima K, Kozuru M, Komatsu H, Ueda R, Kuwano M. Hypomethylation
status of CpG sites at the promoter region and overexpression of the human MDR1 gene in acute myeloid leukemias. Blood.
1998;92(11):4296-4307.
19. Kourti M, Vavatsi N, Gombakis N, Sidi V, Tzimagiorgis G, Papageorgiou T, Koliouskas D, Athanassiadou F.Expression of multidrug resistance
1 (MDR1), multidrug resistance-related protein 1 (MRP1), lung resistance protein (LRP), and breast cancer resistance protein (BCRP) genes
and clinical outcome in childhood acute lymphoblastic leukemia. Int J Hematol. 2007;86(2):166-173.1
20. Guillaume N, Gouilleux-Gruart V, Claisse JF, Troussard X, Lepelley P, Damaj G, Royer B, Garidi R, Lefrere JJ. Multi-drug resistance
mediated by P- glycoprotein overexpression is not correlated with ZAP-70/CD38 expression in B-cell chronic lymphocytic leukemia. Leuk
Lymphoma. 2007;48(8):1556-1560.
21. Nuessler V, Gieseler F, Gullis E, Pelka-Fleischer R, Stötzer O, Zwierzina H, Wilmanns W. Functional P-gp expression in multiple myeloma
patients at primary diagnosis and relapse or progressive disease. Leukemia. 1997;11 Suppl 5:S10-4.
22. Karászi E, Jakab K, Homolya L, Szakács G, Holló Z, Telek B, Kiss A, Rejtô L, Nahajevszky S, Sarkadi B, Kappelmayer J.Calcein assay for multidrug
resistance reliably predicts therapy response and survival rate in acute myeloid leukaemia. Br J Haematol. 2001;112(2):308-314.
23. Schaich M, Soucek S, Thiede C, Ehninger G, Illmer T on behalf of the SHG AML96 Study Group. MDR1 and MRP1 gene expression are
independent predictors for treatment outcome in adult acute myeloid leukemia. Br J Haematol. 2004;128(2):324-332.
24. Marie JP, Legrand O. MDR1/P-GP expression as a prognostic factor in acute leukemias. Adv Exp Med Biol. 1999;457:1-9.
25. Sargent JM, Williamson CJ, Maliepaard M, Elgie AW, Scheper RJ, Taylor CG. Breast cancer resistance protein expression and resistance to
daunorubicin in blast cells from patients with acute myeloid leukaemia. Br J Haematol. 2001;115(2):257-62.
26. van den Heuvel-Eibrink MM, Wiemer EA, Prins A, Meijerink JP, Vossebeld PJ, van der Holt B, Pieters R, Sonneveld P. Increased expression
of the breast cancer resistance protein (BCRP) in relapsed or refractory acute myeloid leukemia (AML). Leukemia. 2002;16(5):833-9.
27. van den Heuvel-Eibrink MM, van der Holt B, Burnett AK, Knauf WU, Fey MF, Verhoef GE, Vellenga E, Ossenkoppele GJ, Löwenberg B,
Sonneveld P.CD34-related coexpression of MDR1 and BCRP indicates a clinically resistant phenotype in patients with acute myeloid leukemia
(AML) of older age. Ann Hematol. 2007;86(5):329-37
28. Kim DH, Park JY, Sohn SK, Lee NY, Baek JH, Jeon SB, Kim JG, Suh JS, Do YR, Lee KB. Multidrug resistance-1 gene polymorphisms associated
with treatment outcomes in de novo acute myeloid leukemia. Int J Cancer. 2006 May 1;118(9):2195-201.
29. Broxterman HJ, Sonneveld P, Feller N, Ossenkoppele GJ, Währer DC, Eekman CA, Schoester M, Lankelma J, Pinedo HM, Löwenberg B,
Schuurhuis GJ. Quality control of multidrug resistance assays in adult acute leukemia: correlation between assays for P-glycoprotein
expression and activity. Blood. 1996;87(11):4809-16.
30. Suárez L, Vidriales MB, Moreno MJ, López A, García-Laraña J, Pérez-López C, Tormo M, Lavilla E, López-Berges MC, de Santiago M, San
Miguel JF, Orfao A; PETHEMA Cooperative Group. Differences in anti-apoptotic and multidrug resistance phenotypes in elderly and young
acute myeloid leukemia patients are related to the maturation of blast cells. Haematologica. 2005;90(1):54-59.
4
Pag
6 e 17
K. TAUBERNÉ JAKAB
31. Mechetner EB, Schott B, Morse BS, Stein WD, Druley T, Davis KA, Tsuruo T, Roninson IB. P-glycoprotein function involves conformational
transitions detectable by differential immunoreactivity. Proc Natl Acad Sci U S A. 1997;94(24):12908-13.
32. Nagy H, Goda K, Arceci R, Cianfriglia M, Mechetner E, Szabó G Jr. P- Glycoprotein conformational changes detected by antibody competition.
Eur J Biochem. 2001;268(8):2416-2420.
33. Lamy T, Drenou B, Grulois I, Fardel O, Jacquelinet C, Goasguen J, Dauriac C, Amiot L, Bernard M, Fauchet R, et al. Multi-drug resistance
(MDR) activity in acute leukemia determined by rhodamine 123 efflux assay. Leukemia. 1995;9(9):1549-55.
34. Holló Z, Homolya L, Davis CW, Sarkadi B. Calcein accumulation as a fluorometric functional assay of the multidrug transporter.
Biochim Biophys Acta. 1994;1191(2):384-388.
35. Legrand O, Perrot JY, Simonin G, Baudard M, Marie JP. JC-1: a very sensitive fluorescent probe to test Pgp activity in adult acute
myeloid leukemia. Blood. 2001;97(2):502-8.
36. Chaoui D, Faussat AM, Majdak P, Tang R, Perrot JY, Pasco S, Klein C, Marie JP, Legrand O. JC-1, a sensitive probe for a simultaneous detection
of P- glycoprotein activity and apoptosis in leukemic cells. Cytometry B Clin Cytom. 2006;70(3):189-96.
37. Kappelmayer J, Karászi E, Telek B, Jakab K. "Pros and cons" on how to measure multidrug resistance in leukemias. Leuk Lymphoma.
2002;43(4):711-717.
38. Kappelmayer J, Simon A, Kiss F, Hevessy Z. Progress in defining multidrug resistance in leukemia. Expert Rev Mol Diagn. 2004;4(2):209-17.
39. Fazlina N, Maha A, Zarina AL, Hamidah A, Zulkifli SZ, Cheong SK, Ainoon O, Jamal R, Hamidah NH.Assessment of P-gp and MRP1 activities
using MultiDrugQuant Assay Kit: a preliminary study of correlation between protein expressions and its functional activities in newly
diagnosed acute leukaemia patients. Malays J Pathol. 2008;30(2):87-93.
40. Schwab R, Micsik T, Szokolóczi O, Schafer E, Tihanyi B, Tihanyi T, Kupcsulik P, Diófalvi K, Mersich T, Besznyak I Jr, Zarand A, Mihalik R,
Sarkadi B, Kéri G, Pap A, Jakab F, Kopper L, Petak I. Functional evaluation of multidrug resistance transporter activity in surgical samples of
solid tumors. Assay Drug Dev Technol. 2007;5(4):541-550.
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5BNagyJr
B.NAGY JR, I. BEKE DEBRECENI, J. KAPPELMAYER
FLOW CYTOMETRIC INVESTIGATION OF CLASSICAL AND
ALTERNATIVE PLATELET ACTIVATION MARKERS
FLOW CYTOMETRIC INVESTIGATION OF CLASSICAL AND ALTERNATIVE PLATELET ACTIVATION
MARKERS
Béla Nagy Jr, Ildikó Beke Debreceni, János Kappelmayer
Department of Laboratory Medicine, Medical and Health Science Center, University of Debrecen, Debrecen, Hungary
Béla Nagy Jr, MD, PhD
Department of Laboratory Medicine, Medical and Health Science Center, University of
Debrecen, Debrecen, Hungary
Tel: +36 52 340 006
Fax: +36 52 417 631
e-mail: nagyb80@gmail.com
Keywords: P-selectin, heterotypic aggregates, microparticle, coated-platelets, flow cytometry, heparin-induced thrombocytopenia
ABSTRACT
Platelets show a substantial role in the maintenance of vascular integrity when these cells after a rapid activation adhere to the
vessel wall lesion, aggregate with other platelets and leukocytes resulting in an arterial thrombosis. Analysis of in vivo platelet
activation at an early time point is crucial in the detection of developing thrombotic events. In addition, the forecast of future
complications as well as the evaluation of the efficacy of anti- platelet medication are also essential in a large group of patients.
Changes in the levels of platelet receptors or alteration in other surface properties due to intra- and extracellular responses to
a stimulus can be measurable primarily by flow cytometry with specific antibodies via the assessment of classical and alternative
platelet activation markers. Some of these biomarkers have been already used in routine laboratory settings in many cases,
while others still stand in the phase of research applications. Deficiency in platelet receptors is also accessible with this technique
for the diagnosis of certain bleeding disorders. We here describe the most important types of platelet activation markers, and
give an overview how the levels of these markers are altered in different diseases.
INTRODUCTION
Platelets are involved in the regulation of hemostasis, as activated platelets normally adhere to the injured vessel wall.
Thrombocytes form aggregates with each other, but also interact with leukocytes to avoid a substantial blood loss from the
circulation. These cellular complexes also contribute to the development of local inflammatory events. In contrast, abnormal
platelet function may result in thrombotic or bleeding complications.
In arterial thrombosis, the level of platelet reactivity increases, and the expression of several platelet activation proteins (markers)
can be measured on the cell surface. In addition, distinct platelet subpopulations (e.g. coated-platelets) may be also investigated
using such experiments. Discovery of novel biomarkers is still of interest to predict emergency thrombotic states, and to monitor
the effects of anti-platelet therapy. The deficiency or lack of platelet receptors may generate a dysfunction in platelet aggregation
and cause hemorrhage. Early detection of all these anomalies is demanding, and flow cytometry is a reliable laboratory method
to analyze platelet function in ex vivo clinical samples. This tool is now getting available in more and more laboratories, and a
combination of two or three antibodies against platelet receptors allows a sensitive and specific analysis of platelets. However,
there are several preanalytical and methodological pitfalls, which may influence the measurement and the interpretation of
these results. In this review, the classic and alternative platelet activation markers on flow cytometry are summarized, which
have been assessed in a large number of studies to evaluate altered platelet function.
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I. CLASSICAL PLATELET ACTIVATION MARKERS
I/1. CD62P
P-selectin (CD62P) is one of the most abundant proteins in the α-granules of platelets, which is exposed on the cell surface
within seconds after platelet activation [1]. Flow cytometric analysis of surface-bound CD62P alone or in a combination
with other markers (see below) has been used as the ‘gold standard’ marker for the assessment of platelet activation in ex vivo
patient samples in the last 3 decades reviewed in [2].
Detection of elevated surface P-selectin was the subject of numerous clinical studies in acute coronary syndrome (ACS) [3-5], in
type 1 and 2 diabetes mellitus (DM) [6-8], untreated hypertension [9], obesity with or without DM [10-11], peripheral artery
disease (PAD) [12], acute ischemic stroke [13-16], essential thrombocythemia (ET) [17], and in those clinical conditions where
platelet activation is one part of the disease pathomechanism such as in primary Raynaud’s disease [18]. Platelet-bound Pselectin values are typically determined in percent positivity (%), however, even a small change in mean fluorescence intensity
(MFI) values may demonstrate a larger alteration in surface P-selectin measured on a logarithmic scale. P-selectin analysis
in non-activated samples is for ‘baseline’ CD62P positivity in the current in vivo platelet activation status, while platelet reactivity
can be evaluated with CD62P levels on stimulated platelets by using submaximal concentrations of classic agonists adenosinediphosphate (ADP) (0.5-5 µM), collagen (1-2 µg/mL), or thrombin-receptor activating peptide (TRAP) (1-8 µM) [7,10,19,20].
Significantly higher P-selectin levels were independently correlated with the body mass index (BMI) [10], the atherosclerosis
indicator carotid intima-media thickness (IMT), and the inflammation marker C-reactive protein (CRP) [11]. Stellos et al. further
investigated surface-bound P-selectin as a prognostic marker in myocardial infarction (MI), and they found a positive association
between the extent of myocardial injury measured with the levels of troponin-I plus creatine kinase-MB and CD62P
positivity independently of age, gender, and baseline medication [5]. CD62P values were significantly increased in ST-segment
elevation MI (STEMI) patients that reflected a greater degree of occlusive thrombus formation in these patients versus others
with non- ST-segment elevation MI (NSTEMI) or Troponin-I-positive unstable angina (UA). On the other hand, P-selectin positivity
showed a limited sensitivity (57.5%) and specificity (69%) for detection of ACS and discrimination of chest pain of different
origins [5]. In monitoring of anti-platelet medication, CD62P had a minor sensitivity to the effects of ADP-receptor blocker
clopidogrel and acetylsalicylic acid (ASA) therapy in stroke [21]. Surprisingly, opposite findings were also reported when less
CD62P positive platelets were measured in MI [20,22] and (convalescent) cerebral infarction as baseline values and in response
to agonist stimulation compared to clinical control cohorts [19,23,24]. Likewise, CD62P expression rapidly declined after the
onset of acute ischemic stroke [25]. These phenomena were explained to be due to the rapid shedding of P-selectin from
circulating platelets, and the sequestration of these activated cells into heterotypic aggregates [26,27]. In fact, the plasma
concentration of released/shed receptors (i.e. soluble P-selectin) was measured in parallel with immunoassays as an additional
platelet marker in these studies [11,19,20,24]. It was also suggested that platelets were exhausted and failed to respond to
thrombin in vitro after a substantial cellular activation during stroke [28]. Therefore, detection of CD62P by flow cytometry
seems to be a more reliable tool for monitoring platelet function at acute but not chronic stimulus of platelets.
I/2. CD40L
CD40L expression was first described on activated T-cells [29], and was later shown to be liberated to the platelet surface from
α-granules, similarly to P-selectin [30]. It is now considered as an emerging platelet activation marker, and its level (CD154) was
also increased when platelet activation was associated with endothelial dysfunction and inflammation in MI and UA [31]. Patients
with UA who needed coronary angioplasty or had recurrent angina showed even higher CD40L expression on platelets compared
with those without such complications [32]. Moreover, significant increase in CD40L on platelets was already detected in transient
ischemic attack (TIA), not only complete stroke [33]. Especially in atherosclerotic ischemic stroke, CD40L positivity was enlarged
compared to that in asymptomatic carotid stenosis [14]. Consequently, upregulated CD40L level was thought to initiate
ischemic stroke from large artery atherosclerosis, and the concentration of this marker was correlated with worse clinical
outcome after cerebral infarction [16,34].
I/3. CD63
CD63 (granulophysin, LAMP-3) is translocated from dense-granules and lysosomes to the plasma membrane after platelet
activation [35]. CD63 expression was higher on day 1 in the stroke group versus control group, which remained significantly
elevated until day 90 [25]. Similarly, Cha et al. found significantly higher CD63 platelet positivity in patients with
atherosclerotic ischemic stroke than in normal subjects; however, no significant differences were seen between atherosclerotic
ischemic stroke and asymptomatic carotid stenosis [14]. Additionally, increased CD63 level was predominantly detected in the
acute stage of ischemic stroke compared with its convalescent stage and the control group [16,36]. In contrast, others found no
elevation in CD63 positivity in either acute or convalescent stroke patients versus subjects without vascular disease [15]. Similarly
to P-selectin, CD63 had an inferior role to detect the effects of clopidogrel and ASA in stroke patients [21].
Immunofluorescence analysis of CD63 by flow cytometry was a suitable method for the diagnosis of Hermansky-Pudlak syndrome
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accompanied with bruise and bleeding complications, where the significantly lower number of dense-granules and lysosomes
in platelets was recognized by using anti-CD63 antibody versus a normal sample [35].
I/4. GPIIb/IIIa receptor (PAC-1 binding)
Fibrinogen receptors undergo a conformational change during platelet activation [37]. PAC-1 antibody was formerly developed
by Shattil and his coworkers [37], and nowadays it is a commercially available monoclonal antibody, which specifically binds
to the activated form of GPIIb/IIIa receptor complex induced by shear stress upon platelet aggregation. Increasing level of
activated GPIIb/IIIa receptors was studied from clinically stable to unstable coronary artery diseases [38]. Also, constantly elevated
PAC-1 binding at 3-month follow-up was associated with an increased incidence of recurrent stroke [36]. On the contrary, McCabe
et al. did not find any difference in PAC-1 percent positivity between those with acute or convalescent cerebrovascular disease
[15]. In manifest metabolic syndrome, higher expression of PAC-1 with augmented fibrinogen binding was observed compared
to subjects with vascular disease [39]. PAC-1 was also found as a sensitive parameter in following clopidogrel effect along with
decreased level of the intracellular vasodilator-stimulated phosphoprotein (VASP) [40].
II. ALTERNATIVE BIOMARKERS OF PLATELET ACTIVATION
II/1. PMPs
Platelet-derived microparticles (PMPs) has been employed as an alternative evaluation of platelet activation in recent years.
These vesicles are formed during platelet ‘budding’, and thus contain several components from platelet cytoplasm and outer
membrane. Consequently, PMPs were positive for CD62P and CD63 [41]. Moreover, those PMPs shed from phosphatidylserine
(PS)-positive platelets were also positive for PS, and had 50- to 100-fold higher procoagulant activity than activated platelets
[42]. Definition and analysis of PMPs are still a debated area of clinical flow cytometry. Due to the variable storage and
preparation of samples, isolation of PMPs as well as differences in the settings of measurement, PMP numbers fairly varied even
in the same disease causing potential inappropriate interpretations [43]. Yet, the need for standardized protocols is still
demanding. The analysis of PMPs was first set by using fluorescent beads with standard size and amount for enumerating PMPs
below 1 µm [44]. Beads were initially processed, and then clinical samples were measured within a standard collection time of
30 seconds. The numbers of PMPs were calculated based on the event count from the bead tube collected for the same time
period. PMPs were gated into a restricted area by FSC and SSC parameters, and then identified by the presence of PS with
Annexin V- FITC and their CD41 positivity. In addition, CD62P expression was also measured on these vesicles [44] (Figure 1).
Previous studies described elevated number of PMPs in MI, atrial fibrillation, and ischemic stroke with severe carotid
atherosclerosis compared to healthy controls [23,41,45,46]. Others recently claimed that PMPs act as an independent marker
of cardiovascular events in high-risk ACS patients, because atherosclerotic burden did not affect PMP number in stable angina
subjects [47]. Furthermore, in ACS patients who underwent coronary stenting had even higher PMP numbers at 15 minutes
after the intervention induced by the procedure-mediated trauma compared to those with diagnostic catheterization alone
[44] (Figure 1). In terms of abnormal metabolic and inflammatory conditions, Csongrádi and her colleagues demonstrated
Figure 1
Representative dot plots of PMP analysis. PMPs were collected in patients after diagnostic catheterization without stenting (A) and clinical
subjects after coronary stenting (B). PMPs were identified in R1 gate according to FSC and SSC parameters, and then by their Annexin V
(PS) positivity (PMP number: 881 events [A] vs. 1117 events [B] in R2). During further analysis, PMPs were stained by anti-CD41-PECy5 and
anti-CD62-PE antibodies to measure the activation status of PMPs (20.5% vs. 33.7%) (adapted after some minor modifications with permission
from [44]).
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significantly higher PMP concentrations in obese subjects and type 2 DM patients versus healthy individuals, where PMP levels
were strongly associated with carotid IMT, BMI values, and CRP concentrations [11]. In agreement with this study, PMP levels
were positively and independently correlated with carotid IMT in the convalescent phase of ischemic stroke as well [19]. Finally,
PMPs could be also measured in the flow cytometric detection of heparin-induced thrombocytopenia (HIT) (see below). In
summary, although increased PMP levels were documented even in the early phase of vascular diseases, it is still questionable
whether flow cytometric analysis of PMPs is ready to be used as a biomarker for routine laboratory purposes due to
relatively lower sensitivity and specificity, and the rather variable conditions of measurement [47].
II/2. Heterotypic aggregates
Platelet-leukocyte aggregates are generated in the blood stream when activated leukocytes and platelets rapidly produce
cellular complexes with each other via exposed receptors, notably with CD62P through an interaction with P-selectin Glycoprotein
Ligand-1 (PSGL-1) [48]. These heterotypic aggregates accumulate in the site of thrombus formation facilitating the development
of variable vascular infarctions. Thus, therapeutic interference of these interactions may be a potential target of anti-platelet
medication reviewed in [49]. The half-life of circulating interactions (platelet-monocytes) is much longer (about 30 minutes)
compared to P-selectin expression [26]. Thus, the analysis of platelet-leukocyte aggregates may be a more consistent indicator
of platelet activation than measuring the amount of P-selectin positive single platelets.
Patients with UA showed a significant increase in the level of neutrophil-platelet aggregates compared with patients with stable
angina [50]. In ACS, not only the total level of platelet-monocyte complexes was augmented, but such tissue factor (TF)positive population as well in contrast to stable angina or controls [51]. Significantly elevated levels of platelet-monocyte
aggregates were published in the acute stage of cerebral infarction compared to control groups [15,16,33] that showed a good
predictive value in early outcome and long-term prognosis after stroke in a recent study [34]. Yet, there were some contradictory
data on the presence of platelet-leukocyte interactions in atrial fibrillation showing decreased levels versus control healthy
individuals [20]. In terms of metabolic diseases, neutrophil-platelet aggregates were higher in type 1 DM patients with
nephropathy compared to DM patients with normal renal function as well as non-diabetic persons [7]. There was a significant
difference in the percentage of monocyte-platelet aggregates but not platelet-neutrophil or platelet-lymphocyte interactions
between the diabetic especially with proliferative retinopathy and nephropathy and control groups [52]. Similarly to these data,
enhanced leukocyte-platelet adhesion was correlated to platelet hyperreactivity among DM patients especially those with
microangiopathy [53]. In chronic myeloproliferative diseases, the increased level of platelet-monocyte aggregates may also
contribute to the vascular complications [54].
II/3. FXIII
Coagulation factor XIII (FXIII) is a protransglutaminase that is essential for maintaining hemostasis as a key regulator of fibrinolysis,
and accelerates the fibrin cross-linking process [55]. FXIII is targeted and concentrated at the site where platelet-rich thrombi
are formed. FXIII binds to activated platelets (Figure 2), and this interaction occurs via GPIIb/IIIa and αVβ3 receptors [56,57],
and the surface-bound form was suggested to cross-link secreted α-granule proteins when coated-platelets are generated [58].
In a clinical study [59] in patients with PAD, platelet-associated FXIII was found significantly higher than in healthy controls, and
the detection of FXIII on platelets was proposed as an alternative marker of platelet activation [59,60].
II/4. Phosphatidylserine
Phosphatidylserine (PS), a negatively charged lipid in the inner-leaflet of phospholipid membranes, is exposed to cell surface
upon platelet activation to propagate coagulation events. Via cleaving FX and prothrombin into their active form, PS facilitates
the assembly and activation of tenase and prothrombinase complexes. As a result, fibrin fibers are formed in the early phase of
clot formation reviewed in [61]. PS exposure can be detected by the binding of Annexin V to platelets, which requires extracellular
Ca2+, so it should be supported during such experiments [62]. Interestingly, this marker did not become a conventional platelet
activation marker for ex vivo clinical samples, but was an available tool for studying in vitro procoagulant platelet responses,
and identifying PMPs by flow cytometry.
Apart from these processes, PS expression also occurs during platelet apoptosis via caspase and calpain activation, when
platelets undergo a cellular death pathway resulting in their clearance from the circulation by scavenger cells [63,64]. These
events could be also induced in vitro by the classic platelet agonist, thrombin [65]. Aging, and stored platelets after several days
were also positive for PS [66,67]. Overall, analysis of other biomarkers is necessary with PS to distinguish platelet activation and
apoptosis-mediated changes from each other.
III. DEFICIENCY IN PLATELET GLYCOPROTEINS
Inherited platelet disorders are characterized by abnormalities of platelet function and production causing mucocutaneous
bleeding symptoms with distinct intensity reviewed in [68]. When platelets show defects with an absence or malfunction of
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Figure 2
Representative dots plot series on TRAP- activated (20 µM) platelets (R1) in a normal whole blood sample analyzed by flow cytometry in
three-color labeling experiments with anti-FXIIIA-FITC, anti- CD62-PE and anti-CD42a-PerCP antibodies. FXIII-A showed a co-expression with
CD62P (23%). CD62% was 94% due to full platelet activation.
receptor(s) in adhesion receptors (GPIb/V/IX complex; Bernard-Soulier syndrome [BS]), or aggregation receptors (GPIIb/GPIIIa
complex; Glanzmann-thrombasthenia [GT]), platelets fail to bind to the main ligands von Willebrand factor (vWF) and fibrinogen,
respectively. BS was characterized with lacking ristocetin-induced aggregation, prolonged bleeding time, large platelets and
thrombocytopenia resulting in epistaxis, gingival and cutaneous bleeding in an adult female patient [69]. GT platelets showed
impaired aggregation to natural agonists (ADP, collagen, arachidonic acid) causing mucosal bleeding or epistaxis in a young male
subject [70]. In both diseases, flow cytometric analysis of surface glycoprotein expression was essential for the final
diagnosis when surface properties of patient platelets were compared to those from a healthy age-matched sample. In the type
II GT patient, platelets were identified by anti- CD42a (GPIX) with no difference between patient and control in this term, while
GPIIb receptors (CD41) were hardly detectable (Figure 3A). In addition, GPIIIa receptors were also absent by using anti-CD61
antibody (data not shown) [70]. In case of the BS person, GPIX by anti-CD42a showed a significantly lower expression, and GPIb
receptors with anti-CD42b antibodies demonstrated a null level versus those of a healthy individual. Platelets were identified
by their CD41 positivity [69] (Figure 3B).
IV. Reticulated platelets
Percent of reticulated/immature platelets was suggested as a useful marker of augmented production or turnover of platelets
in subjects with increased platelet activation long ago [71]. These platelets have large size with higher density compared to
normal platelets. They also demonstrate an enhanced reactivity as they secrete more granule contents upon activation than
smaller platelets [72]. Elevated level of reticulated platelets was measured in increased thrombopoiesis such as in ET, or when
a compensatory mechanism occurs due to a large platelet loss (e.g. immune thrombocytopenic purpura) [73]. Flow
cytometric analysis of reticulated platelets was formerly set using thiazole orange staining to detect their mRNA content
and a platelet-specific (e.g. anti-GPIb) antibody for platelet gating [71]. ACS patients had significantly higher level of reticulated
platelets versus healthy individuals [74]. Moreover, reticulated platelet percent was increased in both early and late phase of
ischemic stroke/TIA after adjustment for age [75]. In terms of monitoring of anti-platelet drugs, larger immature platelet fraction
was observed in aspirin treatment in those after stent thrombosis showing an increased platelet turnover [76]; however, it was
not confirmed in subjects with stroke [75].
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Figure 3
Representative dot plots of a complex flow cytometry analysis of platelet glycoproteins in a GT (A) and a BS (B) patient. Platelets were identified
by anti-CD42a (GPIX), and GPIIb receptors (CD41; 1.5%) were hardly detectable in GT (A). In contrast, in a BS individual, markedly less GPIX
(CD42a) receptors could be detected (67%), and there was no GPIb receptors (2%; CD42b) compared to a healthy person (CD42a: 99%;
CD42b: 91%). Results from these patients were depicted with “P”, while data of healthy controls were marked with “C”. These dot plots
were adapted with permission after some minor modifications from [69,70].
V. HEPARIN-INDUCED THROMBOCYTOPENIA (HIT)
HIT is one of the most common immune-mediated reactions caused by platelet activating IgG antibodies, which usually bind to
heparin/PF4 complexes after heparin administration. Heparin/PF4/IgG complexes may induce platelet aggregation with increased
thrombin generation resulting in a prothrombotic state [77]. Three types of HIT can be distinguished according to the onset of
thrombocytopenia. Typically, thrombocytopenia begins between 4 and 15 days after the start of heparin therapy. Sometimes HIT
develops within the first 24 hours of heparin administration (rapid- onset), or several days after the discontinuation of heparin
(delayed-onset) [77]. Functional test for HIT laboratory diagnosis is available on flow cytometers as well [78,79]. Oláh and co-workers
recently analyzed a patient sample from a rapid-onset HIT with the following methodology [80]. Normal platelets were incubated
with the serum of a HIT patient and the therapeutic concentration of heparin (0.3 IU/mL). Annexin V binding on the surface of
platelets and microparticle release were measured, and platelets were identified by CD41 positivity. For instance, in a negative control,
PRP were incubated with heparin alone, while Ca-ionophore-stimulated sample (10 µM) was used as a positive control. Then, PRP
with the patient plasma was studied, and finally PRP with plasma plus heparin (0.3 IU/ml). Due to the presence of HIT, a significantly
increased Annexin V positivity could be measured compared to samples with heparin or plasma alone (Figure 4).
VI. COATED-PLATELETS
Coated-platelets are produced by a simultaneous activation of collagen and α-thrombin, and represent a subpopulation of
activated platelets with high PS exposure and a substantial prothombinase activity [58]. In addition, coated-platelets are
characterized by the retention of several α-granule-derived coagulation factors e.g. factor V, vWF, thrombospondin, and
fibrinogen on their surface [58], which are covalently bound together via serotonin creating a potentially procoagulant
surface matrix [81]. Elevated levels of coated-platelets were measured in patients with TIA and ischemic stroke compared to
healthy subjects [82,83]. In contrast, significantly lower levels of coated- platelets were also shown in spontaneous cerebral
bleeding, severe hemophilia A, and asymptomatic ET versus healthy cohorts [17,84,85]. Dale and his coworkers previously set
a standardized methodology [58]. Accordingly, subsequent immunostaining and platelet activation were assessed in gel-filtered
platelets by biotinylated-fibrinogen and anti-CD41 antibody with convulxin and α-thrombin. Coated-platelets were then indirectly
labeled with streptavidin-PE to detect enhanced fibrinogen binding compared to the rest of platelets. Detection of P-selectin
percent positivity was simultaneously performed (Figure 5).
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Figure 4
Representative dot plots of HIT investigation by flow cytometry. Normal platelets were incubated with the serum of a HIT patient and heparin
(0.3 IU/mL).
Platelets were identified by their CD41 positivity. In a negative control, PRP were incubated with heparin alone (2%; A), and Ca-ionophorestimulated sample (99%; 10 µM) was used as a positive control (B). PRP with the patient plasma was studied (12%; C), and PRP with plasma
plus heparin (0.3 IU/ml) (25%; D). Due to the presence of HIT, a significantly increased Annexin V positivity could be measured compared to
samples with heparin or plasma alone.
Figure 5
Representative dot plots of coated-platelet measurement in a normal sample on flow cytometer. Platelets were gated (P1) based on FSC-SSC
parameters, and then these events were further analyzed in P2 gate where only CD41-positive cells were counted (92%). Finally, coatedplatelets were separated from the rest of platelets according to their increased fibrinogen binding detected by biotinylated- fibrinogen and
streptavidin-PE (38%; P3).
CONCLUSIONS
Investigation of platelet biomarkers has not been only an approach to study platelet reactivity in variable diseases, but also
provided new insights for a better understanding of the complexity of platelet physiology. For instance, modulating the activity
of intracellular proteins (e.g. protein phosphatases) via activation signaling with potential anti-platelet drugs could be easily
tested through platelet biomarkers by flow cytometry [86]. Novel aspects can be also studied, i.e. two distinct subpopulations
of procoagulant platelets have been recently described after high concentrations of thrombin or collagen- related peptide based
on the quantification of PS positivity, PAC-1 binding, and intracellular Ca2+ concentration [87,88]. The relative function of these
platelet subpopulations needs further analysis.
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In summary, platelet activation markers generally show good sensitivity and specificity even in the detection of lower degree of
change in platelet reactivity, and except for PMP analysis, these biomarkers provide a good reproducibility as well.
ACKNOWLEDGEMENTS
This work was supported by a Mecenatura grant (Mec-10/2011) of the Medical and Health Science Center, University of Debrecen
(B.N.Jr).
References:
1. McEver RP. Selectins. Curr Opin Immunol 1994; 6:75-84.
2. Kappelmayer J, Nagy B Jr, Miszti-Blasius K, Hevessy Z, Setiadi H. The emerging value of P-selectin as a disease marker. Clin Chem Lab Med
2004; 42:475-486.
3. Gurbel PA, O’Connor CM, Dalesandro MR, Serebruany VL. Relation of soluble and platelet P-selectin to early outcome in patients with
acute myocardial infarction after thrombolytic therapy. Am J Cardiol 2001; 87:774-777.
4. Blann AD, Nadar SK, Lip GY. The adhesion molecule P-selectin and cardiovascular disease. Eur Heart J 2003; 24:2166-2179.
5. Stellos K, Bigalke B, Stakos D, Henkelmann N, Gawaz M. Platelet-bound P- selectin expression in patients with coronary artery disease:
impact on clinical presentation and myocardial necrosis, and effect of diabetes mellitus and anti- platelet medication. J Thromb Haemost
2010; 8:205-207.
6. Tschoepe D, Driesch E, Schwippert B, Nieuwenhuis HK, Gries FA. Exposure of adhesion molecules on activated platelets in patients with
newly diagnosed IDDM is not normalized by near-normoglycemia. Diabetes 1995; 44:890-894.
7. Tarnow I, Michelson AD, Barnard MR, Frelinger AL 3rd, Aasted B, Jensen BR, Parving HH, Rossing P, Tarnow L. Nephropathy in type 1
diabetes is associated with increased circulating activated platelets and platelet hyperreactivity. Platelets 2009; 20:513-519.
8. Nagy B Jr, Csongrádi É, Bhattoa HP, Balogh I, Blaskó G, Paragh G, Kappelmayer J, Káplár M. Investigation of Thr715Pro P-selectin gene
polymorphism and soluble P-selectin levels in type 2 diabetes mellitus. Thromb Haemost 2007; 98:186-191.
9. Preston RA, Coffey JO, Materson BJ, Ledford M, Alonso AB. Elevated platelet P-selectin expression and platelet activation in high risk patients
with uncontrolled severe hypertension. Atherosclerosis 2007; 192:148-154.
10. Schneider DJ, Hardison RM, Lopes N, Sobel BE, Brooks MM; Pro-Thrombosis Ancillary Study Group. Association between increased platelet
P-selectin expression and obesity in patients with type 2 diabetes: a BARI 2D (Bypass Angioplasty Revascularization Investigation 2 Diabetes)
substudy. Diabetes Care 2009; 32:944-949.
11. Csongrádi É, Nagy B Jr, Fülöp T, Varga Z, Karányi Z, Magyar MT, Oláh L, Papp M, Facskó A, Kappelmayer J, Paragh G, Káplár M. Increased
levels of platelet activation markers are positively associated with carotid wall thickness and other atherosclerotic risk factors in obese
patients. Thromb Haemost 2011; 106:683-692.
12. Zeiger F, Stephan S, Hoheisel G, Pfeiffer D, Ruehlmann C, Koksch M. P-selectin expression, platelet aggregates, and platelet-derived
microparticle formation are increased in peripheral arterial disease. Blood Coagul Fibrinolysis 2000; 11:723–728.
13. Zeller JA, Tschoepe D, Kessler C. Circulating platelets show increased activation in patients with acute cerebral ischemia. Thromb Haemost
1999; 81:373-377.
14. Cha JK, Jeong MH, Jang JY, Bae HR, Lim YJ, Kim JS, Kim SH, Kim JW. Serial measurement of surface expressions of CD63, P-selectin and
CD40 ligand on platelets in atherosclerotic ischemic stroke. A possible role of CD40 ligand on platelets in atherosclerotic ischemic stroke.
Cerebrovasc Dis 2003; 16:376-382.
15. McCabe DJ, Harrison P, Mackie IJ, Sidhu PS, Purdy G, Lawrie AS, Watt H, Brown MM, Machin SJ. Platelet degranulation and monocyteplatelet complex formation are increased in the acute and convalescent phases after ischaemic stroke or transient ischaemic attack. Br J
Haematol 2004; 125:777-787.
16. Tsai NW, Chang WN, Shaw CF, Jan CR, Chang HW, Huang CR, Chen SD, Chuang YC, Lee LH, Wang HC, Lee TH, Lu CH. Levels and value of
platelet activation markers in different subtypes of acute non-cardio-embolic ischemic stroke. Thromb Res 2009; 124:213-218.
17. Reményi G, Szász R, Debreceni IB, Szarvas M, Batár P, Nagy B Jr, Kappelmayer J, Udvardy M. Comparison of coated-platelet levels in patients
with essential thrombocythemia with and without hydroxyurea treatment. Platelets 2012, DOI:10.3109/09537104.2012.731112.
18. Shemirani AH, Nagy B Jr, Takáts AT, Zsóri KS, András C, Kappelmayer J, Csiki Z. Increased mean platelet volume in primary Raynaud's
phenomenon. Platelets 2012; 23:312-316.
19. Lukasik M, Dworacki G, Michalak S, Kufel-Grabowska J, Watala C, Kozubski W. Chronic hyper-reactivity of platelets resulting in enhanced
monocyte recruitment in patients after ischaemic stroke. Platelets 2012; 23:132-142.
20. Alberti S, Angeloni G, Tamburrelli C, Pampuch A, Izzi B, Messano L, Parisi Q, Santamaria M, Donati MB, de Gaetano G, Cerletti C. Plateletleukocyte mixed conjugates in patients with atrial fibrillation. Platelets 2009; 20:235-241.
21. Grau AJ, Reiners S, Lichy C, Buggle F, Ruf A. Platelet function under aspirin, clopidogrel, and both after ischemic stroke: a case-crossover
study. Stroke 2003;34:849-854.
22. Serebruany VL, Gurbel PA, Shustov AR, Ohman EM, Topol EJ. Heterogeneity of platelet aggregation and major surface receptor expression
in patients with acute myocardial infarction. Am Heart J 1998;136:398-405.
23. Lukasik M, Rozalski M, Luzak B, Michalak S, Kozubski W, Watala C. Platelet activation and reactivity in the convalescent phase of ischaemic
stroke. Thromb Haemost 2010; 103:644-650.
24. Järemo P, Eriksson M, Lindahl TL, Nilsson S, Milovanovic M. Platelets and acute cerebral infarction. Platelets 2012; DOI:
10.3109/09537104.2012.712168.
4
P a g8 e 2 6
25. Marquardt L, Ruf A, Mansmann U, Winter R, Schuler M, Buggle F, Mayer H, Grau AJ. Course of platelet activation markers after ischemic
stroke. Stroke 2002;33:2570-2574.
26. Michelson AD, Barnard MR, Hechtman HB, MacGregor H, Connolly RJ, Loscalzo J, Valeri CR. In vivo tracking of platelets: circulating
degranulated platelets rapidly lose surface P-selectin but continue to circulate and function. Proc Natl Acad Sci USA, 1996; 93:1187711882.
27. Michelson AD, Barnard MR, Krueger LA, Valeri CR, Furman MI. Circulating monocyte-platelet aggregates are a more sensitive marker of in
vivo platelet activation than platelet surface P-selectin: studies in baboons, human coronary intervention, and human acute myocardial
infarction. Circulation 2001; 104:1533-1537.
28. Jurk K, Jahn UR, Van Aken H, Schriek C, Droste DW, Ritter MA, Bernd Ringelstein E, Kehrel BE. Platelets in patients with acute
ischemic stroke are exhausted and refractory to thrombin, due to cleavage of the seven- transmembrane thrombin receptor (PAR-1).
Thromb Haemost 2004; 91:334-344.
29. Lederman S, Yellin MJ, Krichevsky A, Belko J, Lee JJ, Chess L. Identification of a novel surface protein on activated CD4+ T cells that induces
contact-dependent B cell differentiation (help). J Exp Med 1992; 175:1091-1101.
30. Henn V, Slupsky JR, Gräfe M, Anagnostopoulos I, Förster R, Müller-Berghaus G, Kroczek RA. CD40 ligand on activated platelets triggers
an inflammatory reaction of endothelial cells. Nature 1998; 391:591-594.
31. Abu el-Makrem MA, Mahmoud YZ, Sayed D, Nassef NM, Abd el-Kader SS, Zakhary M, Ghazaly T, Matta R. The role of platelets CD40 ligand
(CD154) in acute coronary syndromes. Thromb Res 2009; 124:683-688.
32. Garlichs CD, Eskafi S, Raaz D, Schmidt A, Ludwig J, Herrmann M, Klinghammer L, Daniel WG, Schmeisser A. Patients with acute coronary
syndromes express enhanced CD40 ligand/CD154 on platelets. Heart 2001;86:649-655.
33. Garlichs CD, Kozina S, Fateh-Moghadam S, Handschu R, Tomandl B, Stumpf C, Eskafi S, Raaz D, Schmeisser A, Yilmaz A, Ludwig J, Neundörfer
B, Daniel WG. Upregulation of CD40-CD40 ligand (CD154) in patients with acute cerebral ischemia. Stroke 2003; 34:1412-1418.
34. Lukasik M, Dworacki G, Kufel-Grabowska J, Watala C, Kozubski W. Upregulation of CD40 ligand and enhanced monocyte-platelet aggregate
formation are associated with worse clinical outcome after ischaemic stroke. Thromb Haemost 2012; 107:346-355.
35. Nishibori M, Cham B, McNicol A, Shalev A, Jain N, Gerrard JM. The protein CD63 is in platelet dense granules, is deficient in a patient with
Hermansky- Pudlak syndrome, and appears identical to granulophysin. J Clin Invest 1993;91:1775-1782.
36. Fateh-Moghadam S, Htun P, Tomandl B, Sander D, Stellos K, Geisler T, Langer H, Walton K, Handschu R, Garlichs C, Daniel WG, Gawaz M.
Hyperresponsiveness of platelets in ischemic stroke. Thromb Haemost 2007;97:974-978.
37. Shattil SJ, Hoxie JA, Cunningham M, Brass LF. Changes in the platelet membrane glycoprotein IIb.IIIa complex during platelet activation.
J Biol Chem 1985; 260:11107-11114.
38. Tantry US, Bliden KP, Suarez TA, Kreutz RP, Dichiara J, Gurbel PA. Hypercoagulability, platelet function, inflammation and coronary
artery disease acuity: results of the Thrombotic RIsk Progression (TRIP) study. Platelets 2010;21:360-367.
39. Serebruany VL, Malinin A, Ong S, Atar D. Patients with metabolic syndrome exhibit higher platelet activity than those with conventional
risk factors for vascular disease. J Thromb Thrombolysis 2008; 25:207-213.
40. Schwarz UR, Geiger J, Walter U, Eigenthaler M. Flow cytometry analysis of intracellular VASP phosphorylation for the assessment of
activating and inhibitory signal transduction pathways in human platelets--definition and detection of ticlopidine/clopidogrel effects.
Thromb Haemost 1999; 82:1145-1152.
41. van der Zee PM, Bíró É, Ko Y, de Winter RJ, Hack CE, Sturk A, Nieuwland R. P- selectin- and CD63-exposing platelet microparticles reflect
platelet activation in peripheral arterial disease and myocardial infarction. Clin Chem 2006; 52:657-664.
42. Sinauridze EI, Kireev DA, Popenko NY, Pichugin AV, Panteleev MA, Krymskaya OV, Ataullakhanov FI. Platelet microparticle membranes have
50- to 100-fold higher specific procoagulant activity than activated platelets. Thromb Haemost 2007; 97:425-434.
43. Shah MD, Bergeron AL, Dong JF, López JA. Flow cytometric measurement of microparticles: pitfalls and protocol modifications. Platelets
2008; 19:365-372.
44. Nagy B Jr, Szük T, Debreceni IB, Kappelmayer J. Platelet-derived microparticle levels are significantly elevated in patients treated by elective
stenting compared to subjects with diagnostic catheterization alone. Platelets 2010, 21:147-151.
45. Katopodis JN, Kolodny L, Jy W, Horstman LL, De Marchena EJ, Tao JG, Haynes DH, Ahn YS. Platelet microparticles and calcium homeostasis
in acute coronary ischemias. Am J Hematol 1997; 54:95-101.
46. Choudhury A, Chung I, Blann AD, Lip GY. Elevated platelet microparticle levels in nonvalvular atrial fibrillation: relationship to p-selectin
and antithrombotic therapy. Chest 2007; 131:809-815.
47. Biasucci LM, Porto I, Di Vito L, De Maria GL, Leone AM, Tinelli G, Tritarelli A, Di Rocco G, Snider F, Capogrossi MC, Crea F. Differences in
microparticle release in patients with acute coronary syndrome and stable angina. Circ J 2012;76:2174-2182.
48. Li N, Hu H, Lindqvist M, Wikström-Jonsson E, Goodall AH, Hjemdahl P. Platelet-leukocyte cross talk in whole blood. Arterioscler
Thromb Vasc Biol 2000; 20:2702-2708.
49. Nagy B Jr, Miszti-Blasius K, Kerényi A, Clemetson KJ, Kappelmayer J. Potential therapeutic targeting of platelet-mediated cellular interactions
in atherosclerosis and inflammation. Curr Med Chem 2012; 19:518-531.
50. Ott I, Neumann FJ, Gawaz M, Schmitt M, Schömig A. Increased neutrophil- platelet adhesion in patients with unstable angina. Circulation
1996; 94:1239-1246.
51. Brambilla M, Camera M, Colnago D, Marenzi G, De Metrio M, Giesen PL, Balduini A, Veglia F, Gertow K, Biglioli P, Tremoli E. Tissue factor
in patients with acute coronary syndromes: expression in platelets, leukocytes, and platelet- leukocyte aggregates. Arterioscler Thromb
Vasc Biol 2008; 28:947-953.
52. Káplár M, Kappelmayer J, Veszprémi A, Szabó K, Udvardy M. The possible association of in vivo leukocyte-platelet heterophilic aggregate
formation and the development of diabetic angiopathy. Platelets 2001; 12:419-422.
4
Pag
9e 27
53. Hu H, Li N, Yngen M, Ostenson CG, Wallén NH, Hjemdahl P. Enhanced leukocyte-platelet cross-talk in Type 1 diabetes mellitus:
relationship to microangiopathy. J Thromb Haemost 2004; 2:58-64.
54. Káplár M, Kappelmayer J, Kiss A, Szabó K, Udvardy M. Increased leukocyte- platelet adhesion in chronic myeloproliferative disorders with
high platelet counts. Platelets 2000; 11:183-184.
55. Muszbek L, Bereczky Z, Bagoly Z, Komáromi I, Katona É. Factor XIII: a coagulation factor with multiple plasmatic and cellular functions.
Physiol Rev 2011; 91:931-972.
56. Nagy B Jr, Simon Z, Bagoly Z, Muszbek L, Kappelmayer J. Binding of plasma factor XIII to thrombin-receptor activated human platelets.
Thromb Haemost 2009; 102:83-89.
57. Magwenzi SG, Ajjan RA, Standeven KF, Parapia LA, Naseem KM. Factor XIII supports platelet activation and enhances thrombus formation
by matrix proteins under flow conditions. J Thromb Haemost 2011; 9:820-833.
58. Dale GL, Friese P, Batár P, Hamilton SF, Reed GL, Jackson KW, Clemetson KJ, Alberio L. Stimulated platelets use serotonin to enhance their
retention of procoagulant proteins on the cell surface. Nature 2002; 415:175-179.
59. Devine DV, Andestad G, Nugent D, Carter CJ. Platelet-associated factor XIII as a marker of platelet activation in patients with peripheral
vascular disease. Arterioscler Thromb Vasc Biol 1993; 13:857-862.
60. Devine DV, Bishop PD. Platelet-associated factor XIII in platelet activation, adhesion, and clot stabilization. Semin Thromb Haemost
1996; 22:409-413.
61. Heemskerk JW, Bevers EM, Lindhout T. Platelet activation and blood coagulation. Thromb Haemost 2002; 88:186-193.
62. Vermes I, Haanen C, Steffens-Nakken H, Reutelingsperger C. A novel assay for apoptosis. Flow cytometric detection of phosphatidylserine
expression on early apoptotic cells using fluorescein labelled Annexin V. J Immunol Methods 1995;184:39-51.
63. Maugeri N, Rovere-Querini P, Evangelista V, Covino C, Capobianco A, Bertilaccio MT, Piccoli A, Totani L, Cianflone D, Maseri A,
Manfredi AA. Neutrophils phagocytose activated platelets in vivo: a phosphatidylserine, P- selectin, and {beta}2 integrin-dependent
cell clearance program. Blood 2009;113:5254-5265.
64. Jackson SP, Schoenwaelder SM. Procoagulant platelets: are they necrotic? Blood 2010; 116:2011-2018.
65. Leytin V, Allen DJ, Mykhaylov S, Lyubimov E, Freedman J. Thrombin-triggered platelet apoptosis. J Thromb Haemost 2006; 4:2656-2663.
66. Mason KD, Carpinelli MR, Fletcher JI, Collinge JE, Hilton AA, Ellis S, Kelly PN, Ekert PG, Metcalf D, Roberts AW, Huang DC, Kile BT.
Programmed anuclear cell death delimits platelet life span. Cell 2007; 128:1173-1186.
67. Albanyan AM, Harrison P, Murphy MF. Markers of platelet activation and apoptosis during storage of apheresis- and buffy coatderived platelet concentrates for 7 days. Transfusion 2009; 49:108-117.
68. Nurden AT, Freson K, Seligsohn U. Inherited platelet disorders. Haemophilia 2012; 18 Suppl 4:154-160.
69. Schlammadinger A, Tóth J, Nagy B Jr, Fazakas F, Hársfalvi J, Kappelmayer J, Muszbek L, Radványi G, Boda Z. Bernard-Soulier szindróma: a
herediter thrombocytopéniák ritka oka. Hemat Transzf 2007; 40:40-46.
70. Kerényi A, Szegedi I, Sarudi S, Kappelmayer J, Kiss C, Muszbek L. Glanzmann thrombasthenia II. típusa. Esetleírás. Klin Kisérl Lab Med 1999;
25:162-168.
71. Ault KA, Rinder HM, Mitchell J, Carmody MB, Vary CP, Hillman RS. The significance of platelets with increased RNA content (reticulated
platelets). A measure of the rate of thrombopoiesis. Am J Clin Pathol 1992; 98:637-646.
72. Matic GB, Chapman ES, Zaiss M, Rothe G, Schmitz G. Whole blood analysis of reticulated platelets: improvements of detection and assay
stability. Cytometry 1998; 34:229-234.
73. Harrison P, Robinson MS, Mackie IJ, Machin SJ. Reticulated platelets. Platelets 1997; 8:379-383.
74. Lakkis N, Dokainish H, Abuzahra M, Tsyboulev V, Jorgensen J, De Leon AP, Saleem A. Reticulated platelets in acute coronary syndrome: a
marker of platelet activity. J Am Coll Cardiol 2004; 44:2091-2093.
75. McCabe DJ, Harrison P, Sidhu PS, Brown MM, Machin SJ. Circulating reticulated platelets in the early and late phases after
ischaemic stroke and transient ischaemic attack. Br J Haematol 2004; 126:861-869.
76. Würtz M, Grove EL, Wulff LN, Kaltoft AK, Tilsted HH, Jensen LO, Hvas AM, Kristensen SD. Patients with previous definite stent thrombosis
have a reduced antiplatelet effect of aspirin and a larger fraction of immature platelets. JACC Cardiovasc Interv 2010; 3:828-835.
77. Haas S, Walenga JM, Jeske WP, Fareed J. Heparin-induced thrombocytopenia: the role of platelet activation and therapeutic implications.
Semin Thromb Hemost 1999; 25 Suppl 1:67-75.
78. Lee DH, Warkentin TE, Denomme GA, Hayward CP, Kelton JG. A diagnostic test for heparin-induced thrombocytopenia: detection of platelet
microparticles using flow cytometry. Br J Haematol 1996; 95:724-731.
79. Tomer A, Masalunga C, Abshire TC. Determination of heparin-induced thrombocytopenia: a rapid flow cytometric assay for direct
demonstration of antibody-mediated platelet activation. Am J Hematol 1999; 61:53-61.
80. Oláh Z, Kerényi A, Kappelmayer J, Schlammadinger A, Rázsó K, Boda Z. Rapid- onset heparin-induced thrombocytopenia without previous
heparin exposure. Platelets 2012; 23:495-498.
81. Szász R, Dale GL. Thrombospondin and fibrinogen bind serotonin-derivatized proteins on COAT-platelets. Blood 2002; 100:2827-2831.
82. Prodan CI, Joseph PM, Vincent AS, Dale GL. Coated-platelets in ischemic stroke: Differences between lacunar and cortical stroke. J Thromb
Haemost 2008; 6:609-614.
83. Prodan CI, Vincent AS, Dale GL. Coated-platelet levels are elevated in patients with transient ischemic attack. Transl Res 2011; 158:71-75.
84. Prodan CI, Vincent As, Dale GL. Coated platelet levels correlate with bleed volume in patients with spontaneous intracerebral
hemorrhage. Stroke 2010;41:1301-1303.
85. Saxena K, Pethe K, Dale GL. Coated-platelet levels may explain some variability in clinical phenotypes observed with severe hemophilia. J
Thromb Haemost 2010;8:1140-1142.
86. Simon Z, Kiss A, Erdödi F, Setiadi H, Debreceni IB, Nagy B Jr, Kappelmayer J.Protein phosphatase inhibitor calyculin-A modulates activation
markers in TRAP- stimulated human platelets. Platelets 2010; 21:555-562.
4
P a10
g e 28
87. Topalov NN, Yakimenko AO, Canault M, Artemenko EO, Zakharova NV, Abaeva AA, Loosveld M, Ataullakhanov FI, Nurden AT, Alessi
MC, Panteleev MA. Two types of procoagulant platelets are formed upon physiological activation and are controlled by integrin
α(IIb)β(3). Arterioscler Thromb Vasc Biol 2012; 32:2475-2483.
88. Heemskerk JW, Mattheij NJ, Cosemans JM. Platelet-based coagulation: different populations, different functions. J Thromb Haemost
2012; DOI:10.1111/jth.12045.
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6Antal-Szalmas
P. ANTAL-SZALMÁS, B. NAGY JR, I. BEKE DEBRECENI,
J. KAPPELMAYER
MEASUREMENT OF SOLUBLE BIOMARKERS
BY FLOW CYTOMETRY
MEASUREMENT OF SOLUBLE BIOMARKERS BY FLOW CYTOMETRY
Péter Antal-Szalmás, Béla Nagy Jr, Ildikó Beke Debreceni, János Kappelmayer
Department of Laboratory Medicine, Medical and Health Science Center, University of Debrecen, Debrecen, Hungary
Péter Antal-Szalmás
Department of Laboratory Medicine, Medical and Health Science Center, University of Debrecen, Hungary
Tel: +36 52-340-006
Fax: +36 52-417-631
e-mail: alumni@med.unideb.hu
Key words: bead technology, soluble markers, flow cytometry
ABSTRACT
Microparticle based flow cytometric assays for determination of the level of soluble biomarkers are widely used in several
research applications and in some diagnostic setups. The major advantages of these multiplex systems are that they can measure
a large number of analytes (up to 500) at the same time reducing assay time, costs and sample volume. Most of these assays
are based on antigen-antibody interactions and work as traditional immunoassays, but nucleic acid alterations – by using special
hybridization probes –, enzyme- substrate or receptor-ligand interactions can be also studied with them. The applied beads are
nowadays provided by the manufacturers, but cheaper biological microbeads can be prepared by any user. One part of the
systems can be used on any research or clinical cytometers, but some companies provide dedicated analyzers for their multiplex
bead arrays. Due to the high standardization of the bead production and the preparation of the assay components the analytical
properties of these assays are quite reliable with a wide range of available applications. Cytokines, intracellular fusion proteins,
activated/phosphorylated components of different signaling pathways, transcription factors and nuclear receptors can be
identified and quantitated. The assays may serve the diagnostics of autoimmune disorders, different viral and bacterial infections,
as well as genetic alterations such as single nucleotide polymorphisms, small deletions/insertions or even nucleotide triplet
expansions can be also identified. The most important principles, technical details and applications of these systems are
discussed in this short review.
INTRODUCTION
Changes in the concentration of different proteins in human serum or plasma may indicate the presence of several normal or
pathological processes and show the progression of different disorders. The measurement of total serum protein and its
subfractions or quantitation of individual proteins have been applied in routine laboratory diagnostics for several decades. The
first assays determined the total protein content of serum using mainly protein-specific dyes and spectrophotometry, while the
subfractions were analyzed by electrophoresis. Later, serum proteins were studied based on their enzymatic activity as these
molecules were easily measured by the conversion of their substrate to a colored product measured by photometry. A major
step was the introduction of antibody-antigen based immunoassays that could considerably enhance the number of tested
individual proteins. Several different types of immunoassays were then developed for measuring the light scatter alteration
caused by the immunocomplexes formed due to the antibody-antigen interactions (turbidimetry, nephelometry). Furthermore,
a variety of methods was introduced that used antigens or antibodies labeled with radioactive, enzyme, fluorescence or
luminescence components in competitive or sandwich immunoassays. Several of these tests were applied on automated
immunoanalyzers enhancing the efficacy and the precision of these assays. In spite of all advantages the major drawback of
these methods is the measurement of only one single analyte at one time that increases the time period and sample volume
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required for analysis. Multiplex immunoassays can solve these problems. One possibility is the development of antibody-based
protein chips – like the RANDOX QuantiPlasma 69 system – where antibodies are coated to small carriers (chips) and can measure
large number of proteins – 69 plasma proteins in that case – simultaneously in a “sandwhich” or competitive way. The other
option is the application of multicolor flow cytometric bead arrays.
The introduction of microparticles into flow cytometry opened a brand new field for determination of the level of soluble
biomarkers in different human body fluids. The method is very robust, and the standardized production of the microbeads
provides a very reproducible and accurate technique. The introduction of multicolor beads further enhanced its applicability,
since each type (color) of microparticles supports an individual test, and thus a large number of assays can be run at the same
time. Besides high-throughput, the flexibility of the systems is also excellent as different vendors offer high freedom for the
customers in choosing the proper bead mixes for the proper clinical/research solutions. Another advantage of the technique is
the versatility of the system, since several biomolecules and markers can be tested on the same platform from proteins to nucleic
acids and from enzyme-substrate interactions to receptor-ligand binding [1-4].
BASIC PRINCIPLES OF THE MICROPARTICLE BASED FLOW CYTOMETRIC ASSAYS
Protein determination - immunoassays
The most widely used application of the system is based on antigen-antibody interaction and works as most of the classical
immunoassays. The solid base is provided by the fluorescently labeled microparticles, and in the “two-site” or “sandwich” type
of this assay a capture antibody is coated on them. This antibody recognizes the serum protein of interest and the detection of
the captured protein is managed by a fluorescently labeled second antibody (Figure 1A). The second type of the immunoassays
based on the competition of different assay components (competitive immunoassays). One option is when a capture antibody
is coated on the beads and a fluorescently labeled antigen is competing with the appropriate “cold” antigens of the tested
sample. The higher the amount of the protein in the serum the lower the signal we can detect. In case of another type the
tested antigen is immobilized on the surface of the beads, and their soluble analogues in the tested sample compete for binding
to a fluorescently labeled antigen-specific antibody (Figure 1B). The microparticles make also possible the detection of
autoantibodies when autoantigens are present on the surface of the beads. The bound autoantibodies are identified by a
secondary anti-human immunoglobulin specific antibody labeled by a second/third fluorescent dye. Similarly, microbe-specific
antibodies can be identified supporting the rapid diagnostics of different bacterial/viral/fungal infections (Figure 1C) [1-4].
Nucleic acid detection – hybridization
Another possible application of the system is the detection of certain nucleic acid sequences based on the hybridization to
oligonucleotide probes coated on the microparticles. Such an assay makes possible for instance the identification of single
nucleotide polymorphisms (SNPs) or point mutations in the tested sample. The target region of the genomic DNA is amplified
in a specific PCR reaction using fluorescently labeled primers and then the single stranded PCR products are hybridized to the
probes present on the beads. In this case two types of beads capture the labeled DNA; one carries an oligonucleotide containing
the wild type nucleotide of the SNP, while the other bead carries the mutant one. The positivity/negativity and the fluorescent
intensity of the two beads measured will define the proper genotype. The system can also support gene-expression studies.
The RNA extracted from e.g. two differently treated cell populations can be transcribed into cDNA, and one of the cDNA samples
can be simultaneously labeled fluorescently. The beads of the multiplex system contain special probes for special genes, and
the competition between the two cDNA samples for binding to these probes will provide information about the relative
expression of these genes in the two differently treated samples (Figure 1D) [4-5].
Enzyme-substrate and receptor-ligand assays
A more research and development orientated application of the system is the search for proper substrates or ligands for certain
enzymes or receptors. These assays can work simply using fluorescently labeled test ligands and receptor coated particles, or a
competitive assay is also applicable, when known ligand(s) of the receptor labeled fluorescently compete with the new test
molecules for binding to receptors coated onto the microparticles (Figure 1E, F) [6,7].
TYPES OF THE MICROPARTICLES
The most widely used microparticles are plastic beads that can be easily manufactured with a high throughput and a large
precision. The latest technologies also allow the color-coding up to 500 different bead entities; furthermore, the size of the
beads can be also a usable variable in creating more-and-more complex arrays. Certain companies also incorporate the possibility
for magnetic separation of the beads in their systems [1-3].
Concerning the utility of these beads one part of the assays produced by different companies are predefined, because welldefined capture antibodies are coated on the surface of the microparticles. Thus, these beads are suitable for measuring only
one type of an analyte. Another option is the purchase of “multifunctional” beads coated by free carboxyl or amino groups
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suitable for covalent adhesion of certain proteins according to the design of the user. Avidin/streptavidin or goat anti-mouse
immunoglobulin label can also support the labeling of the beads by user defined molecules and antibodies [2].
Historically, other easily accessible bioparticles were also applied in similar microparticle assays. More than a decade ago a
simple flow cytometric test was developed by our group that could measure the serum soluble CD14 (sCD14) concentration
in an easy way. The membrane bound CD14 of isolated human monocytes competed with sCD14 in the serum of the tested
patients for the binding to a fluorescently labeled anti-CD14 monoclonal antibody. The fluorescence intensity of the monocytes
was measured by flow cytometry and the lower the fluorescence we observed the higher the sCD14 concentration was in the
serum. A serial dilution of a serum sample with known concentration of sCD14 served as calibrator for the assay (Figures 1B
and 2) [8].
The application of normal human cells as target microparticle itself might also supply the detection of different autoantibodies
(such as anti-neutrophil cytoplasmic antibodies). Moreover, certain microbes can help the identification of specific antimicrobial
antibodies thought to be important in the diagnostics of special immune-mediated disorders (e.g. in colitis ulcerosa or Crohn’s
disease). A typical example is the evaluation anti-Saccharomyces cerevisiae antibodies (ASCA) using bakers’ yeast suspension as
a substrate particle of the detection. In these cases the gates are set around the target bioparticles based on their scatter
properties and the fluorescence of the secondary anti-human immunoglobulin antibody is measured (Figure 1C) [2].
A rather novel approach is to create low cost and easily reproducible bioparticles (mainly bacteria and fungi) coated by
avidin/streptavidin for capture of biotin-labeled antibodies, antigens or even special nucleotide probes. The fluorescent labeling
of these microbes is easy handled and even multiplex labeling is achievable that makes this type of particles a real alternative
especially in research applications [4].
SINGLE VERSUS MULTIPLEX SYSTEMS
The prototype of these systems was developed using only single beads that did not differ much from single ELISA-s in terms of
their throughput and efficacy. A large breakthrough was the introduction of multiple beads with different sizes and then with
different labeling color. In the recent systems the microparticles have a certain color that identifies the assay (and the protein
detected by the beads) and in the case of multiplex systems each type of bead (recognizing different soluble markers) has a
Figure 1
Basic principles of the microparticle based flow cytometric assays. Green circles: fluorescently labeled microparticles; red circles: fluorophore
used for detection; Ag: antigen; Ab: antibody; GaHu-Ig: Goat anti-human immunoglobulin specific antibody.
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Figure 2
Determination of sCD14 in human serum by a simple flow cytometry based competitive immunoassay. Isolated monocytes were incubated
with the appropriate dilution of the tested serum and a FITC-labeled anti-CD14 monoclonal antibody. The cells were washed and the
fluorescence intensity of the monocytes – gated based on their scatter properties – was analyzed by a Coulter EPICS XL flow cytometer (A). As
the sCD14 in the serum competes with the mCD14 of the monocytes for binding to the labeled anti-CD14 antibody, the higher the concentration
of sCD14 in the sample the lower the fluorescence intensity we detected on monocytes. A serial 2-fold dilution of a serum sample containing
known amount of sCD14 served as standard. The representative FL1 histograms of the standard samples and the standard curve created from
these data is presented on Figure 2B.
separate color. The detection antibody is labeled by another fluorophore that helps the detection and quantitation of the
captured protein. In multiplex systems the color of the beads – measured in one or two fluorescence channels of the flow
cytometer – identifies the measured protein, while the fluorescence intensity, provided by the dye of the detection antibody
on a separate fluorescence channel, clarifies the amount of protein bound to a certain bead. In each assay of the multiplex
system where we gate on a single bead population the fluorophore of the detection antibody can be the same in the case of all
detected proteins. The amount of protein in the tested sample can be accurately quantitated using standard samples containing
known amounts of the tested protein. Obviously, in case of multiplex systems one standard curve is required for each measured
analyte [1-3].
One possible limitation of the multiplex system is the different dynamic range of tested analytes. In the case of a certain
experimental setup such as in the stimulation of isolated cells the amount of one analyte released from cells can be very high,
that require the dilution of the sample, while the others have to be measured in the undiluted supernatant. As nowadays the
flexibility of the assays is very high – with proper pilot experiments the over- or under- expressed analytes can be identified and
– the matching tests can be freely selected. Another important issue is the optimization of the assay conditions (washing
buffer, pH, ionic strength) that is suitable for each antigen-antibody pair. Moreover, the multiplexing of the assays always results
in the elevation of the background noise and the decrease in the sensitivity of the tests that has to be kept in mind. Finally, the
possible interactions of certain antibodies or the so called “matrix effect” can alter the properties of individual tests. Because
of these effects, an assay that is running properly on its own will not be automatically reliable in a multiplex system [1,2].
DETECTION PLATFORMS
One part of the multiplex flow cytometric bead assays can be used with everyday clinical or research flow cytometers. The
Becton-Dickinson BD™ Cytometric Bead Array (CBA) system supports the majority of Coulter, DAKO, Partec and BectonDickinson flow cytometers. The kit includes the appropriate data for the setup of the equipment, reagents, calibrators and even
an analysis software that can evaluate the list mode data of the measurement in an Excel-base format. Another approach is
offered by the Luminex’s xMAP Technology. In that case the company developed special flow cytometers designed for multiplex
bead analysis. The Luminex 100/200™ and FLEXMAP 3D® systems have similar components like any flow cytometers but they
can be used only for measurement and evaluation of the xMAP multiplex bead arrays. A very similar approach is offered by BioRad’s Bio-Plex MAGPIX, Bio-Plex 200, and Bio-Plex 3D systems. In contrast to these instruments that identify the beads based
on their fluorescent labels the Copalis (Coupled Particle Light Scattering) system of Diasorin discriminates between single
beads with different diameters and aggregated beads based on their scatter properties [1-3].
POSSIBLE APPLICATIONS
The number of possible tests available in the form of multiplex bead assay is radically increasing. Several companies provide
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Figure 3
Possible applications of the flow cytometric multiplex bead assays.
a long range of tests covering different areas of research and diagnostic use. These possible applications are listed in Figure
3. One of the first areas that is still the most widely used application of the cytometric bead array systems is the measurement
of different cytokines in body fluid of patients and controls or in the supernatant of differently stimulated cells. The “cytometric
bead array cytokines” search in the PubMed database provides 300 hits and the first publication was prepared in 2001, describing
the simultaneous measurement of 6 cytokines in tear samples [9]. Nowadays assays are available for IL-1 to IL-18, TNFα
and β, INFα, β and γ, more than 10 chemokines and soluble cytokine receptors. In addition, complex kits are available for
Th1/Th2/Th17 (IL-2, IL-4, IL-6, IL-10, IFNγ, TNFα, IL-17α) or inflammatory (IL-6, IL-10, IL-12, IFNγ, TNFα, MCP-1) cytokines [1-3].
Figure 4 illustrates one of our experiments aiming the multiplex determination of cytokines in LPS stimulated whole blood and
platelet rich plasma (PRP).
The detection of intracellular proteins in cell lysates is also a valuable technique that can serve diagnostic and research purposes,
too. The recently developed assay for measuring the bcr/abl fusion protein in the lysate of white blood cells is a unique method
for the rapid diagnosis of chronic myeloid or acut lymphoblastic leukaemia. The assay is based on fluorescent beads coated with
monoclonal antibodies that can recognize the bcr part of the bcr/abl fusion proteins independently of the type of the fusion
(the minor or the major breakpoint cluster region of the bcr gene is involved in the translocation). The lysate of the white blood
cells is mixed with the beads and then a fluorescently-labeled anti-abl antibody detects the bound proteins [10]. In a recent
work, we evaluated the analytical properties of this assay. The intra- assay CV% of positive controls was respectable as 3.7%
was in the normal and 10% was found in the pathological range. The cut-off for mean fluorescence intensity was 112 that
provided 100% sensitivity and 100% specificity for the assay. The results of the cytometric bead assay showed 100% agreement
with the molecular biological tests used for bcr/abl transcript detection [11]. Recently, a similar assay was introduced for the
detection of the PML/RARA fusion protein [12].
Another broad field within the detection of intracellular proteins is the identification of activated/phosphorylated components
of different signaling pathways. Dozens of signaling molecules can be tested including the MAPK-family, Wnt/GSK/Akt or the
JAK/STAT pathway in addition to the activation of several growth factor receptors (like EGFR, IGFR, VEGFR, c-kit, c-Met) [1,3].
Several publications are also available in the international literature. Koeper and colleagues described a skin implant model to
test the toxic/irritating effect of different skin sensitizers by simultaneous testing the phosphorylation of the MAP- kinases, STAT1
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Figure 4
Multiplex detection of human cytokines in LPS-stimulated whole blood and PRP.
Citrated whole blood or PRP samples were stimulated by Re-LPS (10 µg mL-1) for 1 hour at 37°C and G-CSF, IL-1ra, IL-6, TNFα, IL-4, IL-10 and
IFNγ levels were determined simultaneously. Briefly, microparticles with pre-coated antigen-specific antibodies on their surface were added
to the samples and pipetted into wells on a microplate. For the analysis of the levels of microparticle-bound antigen, a biotinylated
secondary antibody and a streptavidin-PE conjugate were applied. After microparticles were suspended in buffer, results were determined by
a Luminex 100TM analyzer (Luminex, Austin, TX, USA). One laser was microparticle-specific to show which antigen level was under investigation,
and another laser determined the fluorescent signal, which was directly proportional to the concentration of antigen bound. On Figure 3A-G
we can see the standard curves of each cytokine measured. Figure 3H presents the concentration of each cytokines in the plasma of
LPS stimulated whole blood. There was a significant increase (P<0.01) in the level of two cytokines due to the Re-LPS stimulation versus the
control sample (IL-1ra: 4.98±0.42 pg mL-1 vs. 1.42±0.39 pg mL-1) (TNF-α: 1.0±0.12 pg mL-1 vs. 0.1±0.06 pg mL-1). The cytokine concentrations
in the PRP were below the detection levels independently of LPS stimulation.
and Phospholipase C γ [13]. Dawes et al. studied the activation of the pERK, pP38, and pJNK upon TGFβ2 stimulation in lens
epithelial cells during the differentiation to myofibroblasts [14], while Wong and colleagues investigated the MAPK and NF-κB
activity in IL-25 stimulated T helper lymphocytes [15]. Similarly, intracellular nuclear receptors can be also detected using the
multiplex bead arrays like in the work of Schneiderhan-Marra, where 56 proteins – including oestrogen receptor – were tested
in breast cancer needle biopsy samples [16].
A very dynamically developing field is the use of the multiplex bead arrays for identification of valuable biomarkers in the early
diagnostics or follow-up of malignant disorders [1]. Opstal-van Winden et al. tested simultaneously 10 biomarkers in the serum
of breast cancer patients but they could not identify a panel that could help the early diagnosis of this disorder [17]. Kim and
coworkers analyzed 3 markers (CA-125, transthyretin, and apolipoprotein A1) of ovarian cancer in a multiplex system and could
show that the combination of these markers was superior to the analytical performance of the individual ones [18]. In a very
recent elegant study, 30 biomarkers were tested in the serum of non-small cell lung cancer patients using a multiplex bead array.
Twenty-three parameters differed between the controls and the patients, and the combined application of the 5 highest-ranked
biomarkers (α1-antitrypsin, CYFRA 21-1, IGF-1, RANTES, AFP) could discriminate between controls and NSCLC patients with high
accuracy [19].
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For the diagnostics of autoimmune disorders a relatively large number of multiplex assays are already available. The complex
evaluation of antinuclear antibodies (ANA), extractable nuclear antigens (ENA) or anti-neutrophil cytoplasmic antibodies
(ANCA) can be performed using these systems. Furthermore, disease specific panels are also available for celiac disease, systemic
lupus erythematosus, autoimmune thyroid disorders and vasculitis (1,20,21). An import application of the technique is the HLAtyping of donors and recipients of kidney transplantation and the identification of donor-specific serum antibodies [1,22].
The application of multiplex bead assays can support diagnostic microbiology, too [1]. Yu et al. developed an inhibitory multiplex
bead assay to determine 26 serotypes of pathogenic Streptococcus pneumoniae strains [23], while Wagner and colleagues
described an assay that can simultaneously identify antibodies specific for the outer surface protein A, C and F of Borrelia
burgdorferi serving the diagnostics of Lyme disease in both humans and animals [24]. Furthermore, food poisoning caused by
Escherichia coli O157:H7 can be identified easily and rapidly using this multiplex bead system [25]. Commercially available arrays
are ready to use for Epstein-Barr and Herpes virus identification, and for respiratory tract viruses and
measles/mumps/rubeola/varicella detection [1].
A promising new are of this field is the combination of multiplex bead arrays with the DNA/RNA based molecular biologic
techniques. The system is suitable to analyze the presence of SNPs like the IL-6 SNP distribution in different ethnic groups [26]
or the 22 SNPs of the ABC transporter genes in healthy individuals [27]. It can also detect small insertions or deletions in the
BRCA1 gene [5] or even the number of nucleotide triplet expansions in Huntington disease [5]. Furthermore, the cytometric
array can be used for gene expression studies [28].
DISCUSSION
The development of microbeads based flow cytometric assays for measuring soluble biomarkers started more than 10 years
ago. At that time we thought that this system would make a revolution in laboratory diagnostics as covering even several
hundreds of analytes in one run could replace the currently available laboratory techniques. The system is indeed a robust one,
the number of the available assays is enormous and there are certain areas – especially in research – where this technique really
became a number one choice. On the other hand, the still high costs of the systems and also the evolution of laboratory
automation and the development of the classical laboratory tests did not let the change occur. Nevertheless, these microparticle
based assays are very much useful, and will support our research and certain diagnostic activities in the future.
ACKNOWLEDGEMENTS
This work was supported by the TÁMOP-4.2.2.A-11/1/KONV-2012-0025 project. This project was co-supported with the
involvement of the European Union and the European Social Foundation. This work was also supported by the National Office
for Research and Technology of Hungary (TECH-09-A1-2009-0113; mAB-CHIC).
References
1. Elshal MF, McCoy JP. Multiplex bead array assays: performance evaluation and comparison of sensitivity to ELISA. Methods 2006; 38:317323.
2. Hsu HY, Joos TO, Koga H. Multiplex microsphere-based flow cytometric platforms for protein analysis and their application in clinical
proteomics - from assays to results. Electrophoresis 2009; 30:4008-4019.
3. Morgan E, Varro R, Sepulveda H, Ember JA, Apgar J, Wilson J, Lowe L, Chen R, Shivraj L, Agadir A, Campos R, Ernst D, Gaur A. Cytometric
bead array: a multiplexed assay platform with applications in various areas of biology. Clin Immunol 2004; 110:252-266.
4. Pataki J, Szabó M, Lantos E, Székvölgyi L, Molnár M, Hegedüs E, Bacsó Z, Kappelmayer J, Lustyik G, Szabó G. Biological microbeads for flowcytometric immunoassays, enzyme titrations, and quantitative PCR. Cytometry A 2005; 68:45-52.
5. Imre L, Balogh I, Kappelmayer J, Szabó M, Melegh B, Wanker E, Szabó G. Detection of mutations by flow cytometric melting point analysis
of PCR products. Cytometry A 2011; 79:720-726.
6. Breuer S, Sepulveda H, Chen Y, Trotter J, Torbett BE. A cleavage enzyme-cytometric bead array provides biochemical profiling of resistance
mutations in HIV-1 Gag and protease. Biochemistry 2011; 50:4371-4381.
7. Curpan RF, Simons PC, Zhai D, Young SM, Carter MB, Bologa CG, Oprea TI, Satterthwait AC, Reed JC, Edwards BS, Sklar LA. High-throughput
screen for the chemical inhibitors of antiapoptotic bcl-2 family proteins by multiplex flow cytometry. Assay Drug Dev Technol 2011; 9:465474.
8. Antal-Szalmás P, Szöllősi I, Lakos G, Kiss E, Csípő I, Sümegi A, Sipka S, van Strijp JA, van Kessel KP, Szegedi G. A novel flow cytometric assay
to quantify soluble CD14 concentration in human serum. Cytometry 2001; 45:115-123.
9. Cook EB, Stahl JL, Lowe L, Chen R, Morgan E, Wilson J, Varro R, Chan A, Graziano FM, Barney NP. Simultaneous measurement of six cytokines
in a single sample of human tears using microparticle-based flow cytometry: allergics vs. non-allergics. J Immunol Methods 2001; 254:109118.
10. Weerkamp F, Dekking E, Ng YY, van der Velden VH, Wai H, Böttcher S, Brüggemann M, van der Sluijs AJ, Koning A, Boeckx N, Van
Poecke N, Lucio P, Mendonça A, Sedek L, Szczepański T, Kalina T, Kovac M, Hoogeveen PG, Flores- Montero J, Orfao A, Macintyre E, Lhermitte
4
P a g7 e 3 6
J. KAPPELMAYER
BY FLOW CYTOMETRY
L, Chen R, Brouwer-De Cock KA, van der Linden A, Noordijk AL, Comans-Bitter WM, Staal FJ, van Dongen JJ; EuroFlow Consortium. Flow
cytometric immunobead assay for the detection of BCR-ABL fusion proteins in leukemia patients. Leukemia 2009; 23:1106-1117.
11. Hevessy Z, Hudák R, Kiss-Sziráki V, Antal-Szalmás P, Udvardy M, Rejtő L, Szerafin L, Kappelmayer J. Laboratory evaluation of a flow
cytometric BCR-ABL immunobead assay. Clin Chem Lab Med 2011; 50:689-692.
12. Dekking EH, van der Velden VH, Varro R, Wai H, Böttcher S, Kneba M, Sonneveld E, Koning A, Boeckx N, Van Poecke N, Lucio P, Mendonça
A, Sedek L, Szczepański T, Kalina T, Kanderová V, Hoogeveen P, Flores-Montero J, Chillón MC, Orfao A, Almeida J, Evans P, Cullen M, Noordijk
AL, Vermeulen PM, de Man MT, Dixon EP, Comans- Bitter WM, van Dongen JJ; EuroFlow Consortium (EU-FP6, LSHB-CT-2006-018708). Flow
cytometric immunobead assay for fast and easy detection of PML-RARA fusion proteins for the diagnosis of acute promyelocytic leukemia.
Leukemia 2012; 26:1976-1985.
13. Koeper LM, Schulz A, Ahr HJ, Vohr HW. In vitro differentiation of skin sensitizers by cell signaling pathways. Toxicology 2007; 242:144-152.
14. Dawes LJ, Sleeman MA, Anderson IK, Reddan JR, Wormstone IM. TGFbeta/Smad4- dependent and -independent regulation of human lens
epithelial cells. Invest Ophthalmol Vis Sci 2009; 50:5318-5327.
15. Wong CK, Li PW, Lam CW. Intracellular JNK, p38 MAPK and NF-kappaB regulate IL-25 induced release of cytokines and chemokines from
costimulated T helper lymphocytes. Immunol Lett 2007; 112:82-91.
16. Schneiderhan-Marra N, Sauer G, Kazmaier C, Hsu HY, Koretz K, Deissler H, Joos TO. Multiplexed immunoassays for the analysis of breast
cancer biopsies. Anal Bioanal Chem 2010; 397:3329-3338.
17. Opstal-van Winden AW, Rodenburg W, Pennings JL, van Oostrom CT, Beijnen JH, Peeters PH, van Gils CH, de Vries A. A bead-based
multiplexed immunoassay to evaluate breast cancer biomarkers for early detection in pre-diagnostic serum. Int J Mol Sci 2012; 13:1358713604.
18. Kim YW, Bae SM, Lim H, Kim YJ, Ahn WS. Development of multiplexed beadbased immunoassays for the detection of early stage ovarian
cancer using a combination of serum biomarkers. PLoS One 2012; 7(9):e44960.
19. Lee HJ, Kim YT, Park PJ, Shin YS, Kang KN, Kim Y, Kim CW. A novel detection method of non-small cell lung cancer using multiplexed beadbased serum biomarker profiling. J Thorac Cardiovasc Surg 2012; 143:421-427.
20. González-Buitrago JM. Multiplexed testing in the autoimmunity laboratory. Clin Chem Lab Med 2006; 44:1169-1174.
21. Maecker HT, Nolan GP, Fathman CG. New technologies for autoimmune disease monitoring. Curr Opin Endocrinol Diabetes Obes 2010;
17:322-328.
22. Ziemann M, Schönemann C, Bern C, Lachmann N, Nitschke M, Fricke L, Görg S. Prognostic value and cost-effectiveness of different
screening strategies for HLA antibodies prior to kidney transplantation. Clin Transplant 2012; 26:644-656.
23. Jigui Yu, Jisheng Lin, Kyung-Hyo Kim, William H. Benjamin, Jr., and Moon H. Nahm. Development of an Automated and Multiplexed
Serotyping Assay for Streptococcus pneumoniae Clin Vaccine Immunol 2011; 18:1900–1907.
24. Wagner B, Freer H, Rollins A, Erb HN. A fluorescent bead-based multiplex assay for the simultaneous detection of antibodies to B.
burgdorferi outer surface proteins in canine serum. Vet Immunol Immunopathol 2011; 140:190-198.
25. Kelly M. Leach, Joyce M. Stroot, and Daniel V. Lim Same-Day Detection of Escherichia coli O157:H7 from Spinach by Using
Electrochemiluminescent and Cytometric Bead Array Biosensors Appl Enviroment Microbiol 2010; 76:8044–8052.
26. Ivanova M, Ruiqing J, Kawai S, Matsushita M, Ochiai N, Maruya E, Saji H. IL-6 SNP diversity among four ethnic groups as revealed by beadbased liquid array profiling. Int J Immunogenet 2011; 38:17-20.
27. Koo SH, Ong TC, Chong KT, Lee CG, Chew FT, Lee EJ. Multiplexed genotyping of ABC transporter polymorphisms with the Bioplex
suspension array. Biol Proced Online 2007; 9:27-42.
28. Wedemeyer N, Göhde W, Pötter T. Flow cytometric analysis of reverse transcription- PCR products: quantification of p21(WAF1/CIP1)
and proliferating cell nuclear antigen mRNA. Clin Chem 2000; 46:1057-1064.
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7Biro
E. BIRÓ, B. VÁSÁRHELYI, G. TOLDI
CALCIUM INFLUX CHARACTERISTICS DURING T LYMPHOCYTE
ACTIVATION MEASURED WITH FLOW CYTOMETRY
CALCIUM INFLUX CHARACTERISTICS DURING T LYMPHOCYTE ACTIVATION MEASURED WITH
FLOW CYTOMETRY
Enikő Biró1, Barna Vásárhelyi2,3, Gergely Toldi1
First Department of Pediatrics, Semmelweis University, Budapest H‐1083, Hungary
2Department of Laboratory Medicine, Semmelweis University, Budapest H‐1083, Hungary
3Research Group of Pediatrics and Nephrology, Hungarian Academy of Sciences, Budapest H‐1083, Hungary
1
Enikő Biró
First Department of Pediatrics, Semmelweis University, Bókay u. 53, Budapest H‐1083, Hungary
Tel: +36 30 997 6217
Fax: +36 1 3138212
e‐mail: biroeniko92@gmail.com
Key words: Ca2+ influx, flow cytometry, autoimmune disease, T lymphocyte activation
ABSTRACT
T lymphocytes are of paramount importance in many intercellular reactions, such as the regulation of the inflammatory response
and immune reactivity. Until the recent past, single‐cell techniques were used for the investigation of calcium influx during T
lymphocyte activation. Therefore, over the recent years we have created a novel approach that allows simultaneous recording
of calcium influx in several lymphocyte subsets using flow cytometry. Our research group developed a robust algorithm (FacsKin)
for the evaluation of the acquired data that fits functions to median values of the fluorescent marker of interest and calculates
relevant parameters describing each function.
Over the recent years, we have investigated calcium influx characteristics applying this method in a number of autoimmune
disorders and under different physiological conditions (such as the neonatal period and pregnancy). In this review, we aim to
give a brief summary of our findings and of the common characteristics of calcium influx in the investigated disorders, namely:
multiple sclerosis (MS), rheumatoid arthritis (RA), type 1 diabetes mellitus (T1DM), ankylosing spondylitis (AS), and preeclampsia
(PE). Based on our results, a number of dominant features were identified that were present in most of the investigated
autoimmune diseases.
INTRODUCTION
T lymphocytes are of paramount importance in many intercellular reactions, such as the regulation of the inflammatory response
and immune reactivity. Upon the engagement of the T cell receptor (TCR), a number of signal transduction pathways culminate
in the transient elevation of the cytoplasmic calcium concentration ([Ca2+]cyt). First, Ca2+ is released from intracellular stores
that is followed by further Ca2+ entry from the extracellular space through the store‐operated calcium release activated calcium
(CRAC) channels. In the course of lymphocyte activation, K+ channels maintain the driving force for sustained Ca2+ influx as
they grant the efflux of K+ from the cytoplasm, thus conserving an electrochemical potential gradient between the intra‐ and
extracellular spaces. There are two major types of K+ channels in T cells: the voltage‐gated Kv1.3 and the Ca2+‐activated IKCa1
channels. The relation between the Ca2+ currents through CRAC channels and the efflux of K+ makes the proliferation and
activation of lymphocytes sensitive to pharmacological modulation of Kv1.3 and IKCa1 channels, and provides an opportunity
for targeted intervention. Specific inhibition of these channels results in a diminished Ca2+ influx in lymphocytes and a lower
level of lymphocyte activation.
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Previous data suggest that selective modulation of lymphocyte activation through specific inhibition of K+ channels may be a
possible therapeutic approach for the treatment of autoimmune disease [1‐6]. Beeton et al. showed that terminally differentiated
effector memory T (TEM) cells play a pivotal role in the pathogenesis of autoimmunity [1]. For instance, Wulff et al. suggest that
disease causing TEM cells are able to home to inflamed tissues in the CNS and exhibit immediate effector function in autoimmune
disease. They described that the characteristic K+ channel phenotype of TEM cells in MS is Kv1.3high IKCa1low, contrasting naïve
and central memory T (TCM) cells, which exhibit a Kv1.3low IKCa1high channel phenotype [3]. Therefore the therapeutic
relevance of specific Kv1.3 channel inhibitors is of outstanding interest, as they may offer the possibility for selective modulation
of pathogenic TEM cells, while naïve and TCM cells (needed for physiological immune responses) would escape the inhibition
through upregulation of IKCa1 channel expression. Beeton et al. demonstrated that the symptoms of experimental autoimmune
encephalitis, a murine model of MS, significantly improved after treatment with selective Kv1.3 inhibitors [1, 4]. Besides naive
and memory cells, helper (CD4) and effector (CD8) T lymphocytes modulate the autoimmune response in different ways. CD4
cells influence the immune system by producing cytokines, while CD8 cells are capable of causing immediate cell destruction.
The two main arms of CD4 lymphocytes are Th1 and Th2 cells. Th1 cells mainly produce pro‐inflammatory cytokines, thus
sustaining autoimmune reactions. However, Th2 cells reduce the inflammatory response by producing anti‐inflammatory cytokines.
Until the recent past, single‐cell techniques were used for the investigation of Ca2+ influx during lymphocyte activation. There
has been no high‐throughput method available to study the kinetics of lymphocyte activation in more subsets simultaneously.
Single‐cell techniques are restricted by not being capable of characterizing this process in complex cellular systems, therefore
ignoring the interaction between the different lymphocyte subsets that may modulate the course of their activation. Therefore,
over the recent years we have created a novel approach that allows simultaneous recording of Ca2+ influx in several lymphocyte
subsets. Our research group developed a robust algorithm (FacsKin) that fits functions to median values of the data of interest
and calculates relevant parameters describing each function. By selecting the best fitting function, this approach provides an
opportunity for the mathematical analysis and statistical comparison of kinetic flow cytometry measurements of distinct samples.
For example, in case of Ca2+ influx measurements, the software fits a double‐logistic function on each recording. This function is
used to describe measurements that have an increasing and a decreasing intensity as time passes. The software also calculates
parameter values describing each function, such as the Maximum value, the Time to reach maximum value or the Area Under
the Curve (AUC). These parameters represent different characteristics of lymphocyte Ca2+ influx kinetics (Figure 1).
Details of the method of measurements were described earlier [7, 8]. Briefly, peripheral blood mononuclear cells (PBMCs) were
separated from freshly drawn peripheral venous blood of the investigated subjects. Cell surface markers were applied to separate
the lymphocyte subsets of interest. Cells were loaded with Ca2+ sensitive dyes and activated with aspecific stimuli. Cell
fluorescence data were measured and recorded for 10 minutes in a kinetic manner on flow cytometer. Our studies were adhered
to the tenets of the most recent revision of the Declaration of Helsinki.
Over the recent years, we have investigated Ca2+ influx characteristics in a number of autoimmune disorders and under different
physiological conditions. In this review, we aim to give a brief summary of our findings and of the common characteristics of
Ca2+ influx in autoimmune disease.
MULTIPLE SCLEROSIS
Multiple sclerosis (MS) is an autoimmune disease affecting the central nervous system. The autoimmune reaction primarily
destroys the myelin sheath covering the nerve cells. T lymphocytes play a key role in the pathogenesis of MS. They regulate the
ongoing inflammatory process of the central nervous system (CNS) which leads to the damage of the myelin sheath and axons.
However, only a small part of T lymphocytes are myelin‐specific autoreactive cells. Besides the demyelinating action of these
cells of the CNS, the activation of peripheral lymphocytes also contributes to the pathogenesis and disease progression [9]. In
our investigations we measured samples of healthy individuals and MS patients with no immunomodulatory therapy, as well as
MS patients treated with interferon beta (IFN‐b), currently regarded as the most effective therapy of MS.
In our study we discovered increased sensitivity of CD8 cells to Kv1.3 channel inhibition in MS. Therefore, from the CD4‐CD8
point of view, we demonstrated specific immunomodulation that may be beneficial in the therapy of MS via the selective
suppression of CD8 effector lymphocytes over CD4 helper cells. However, this specificity is not present within the CD4 subset,
since our results suggest that Th1 and Th2 cells are similarly suppressed upon the inhibition of Kv1.3 channels. Since the cytokine
balance is of utmost importance in the regulation of the autoimmune reaction, the inhibition of the Th2 subset would probably
result in a setback of therapeutic efforts in MS. Our findings are relevant in the light of observations regarding the contribution
of TEM cells to the development of MS, as described above. Although the Kv1.3high IKCa1low pattern is found in both CD4+
and CD8+ TEM cells, we can assume that the majority of TEM cells are CD8+, since TEM cells express immediate effector function.
This provides an explanation for the increased sensitivity of CD8 cells to Kv1.3 channel inhibition in MS in our study.
We have also demonstrated important differences in Ca2+ influx kinetics and lymphocyte K+ channel function in MS patients
without IFN‐b compared with healthy individuals. The selective blocker of the lymphocytes Kv1.3 channel might be a promising
drug in combination therapy, supplementing the presently used IFN‐b treatment. Our results indicate that IFN‐b therapy causes
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Figure 1
A: Dot‐plot of a kinetic flow cytometry recording, where each dot represents one cell of the measured sample. Horizontal axis: Time (in
seconds), Vertical axis: Fluorescent intensity of Ca2+ sensitive dyes (relative parameter value). Green line: median value of the fluorescent
parameter of interest.
B: FacsKin software fits a double‐logistic function (red line) on each recording. Horizontal axis: Time (in seconds), Vertical axis: Fluorescent
intensity of Ca2+ sensitive dyes (relative parameter value). The calculated parameters: Max: the peak value of Ca2+ influx, tmax: time to reach
Max value, AUC: Area Under the Curve.
compensatory changes only in the Th1 subset in MS regarding Ca2+ influx kinetics and the function of K+ channels. However,
the increased function of the Th2 subset, and therefore the production of anti‐inflammatory cytokines is less affected. This
might contribute to a more effective treatment of the autoimmune process in this disorder [10].
RHEUMATOID ARTHRITIS
The short‐term activation of peripheral blood and synovial fluid T lymphocytes, especially that of autoreactive T cells plays a
crucial role in initiating and maintaining the chronic inflammation in the joints of patients suffering from rheumatoid arthritis
(RA). These cells regulate the inflammatory process resulting in the destruction of the articular cartilage and also play a role in
extra‐articular damage. We investigated T lymphocyte Ca2+ influx kinetics following activation in peripheral blood of recently
diagnosed RA patients compared to healthy individuals.
Our results indicate that margatoxin (MGTX), a specific blocker of the Kv1.3 channel acts differentially on Ca2+ influx kinetics in
major peripheral blood lymphocyte subsets of RA patients:
Th2 and CD8 cells are inhibited more dominantly than Th1 and CD4 cells. Kv1.3 channel expression in RA patients and healthy
subjects Based on our results, the immunomodulatory effect of Kv1.3 channel inhibition is predominantly seen in cytotoxic (CD8)
T cells in RA. However, this effect does not seem to be as specific as reported before by Beeton and colleagues in case of TEM
cells [13], since anti‐inflammatory Th2 cells are also affected to a noteworthy extent. This subset has an important role in
counterbalancing the peripheral lymphocytes might be the differential distribution of disease‐associated autoreactive T cells in
RA patients on local and systemic levels. In the synovial fluid (locally), autoreactive TEM cells, expressing high numbers of Kv1.3
channels are abundantly present. However, this Kv1.3 pattern was not detected in peripheral blood T cells, because autoreactive
TEM cells are infrequent in the circulation. Peripheral blood T cells were predominantly found to be naive and TCM cells [13]. A
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reason for limited specificity of Kv1.3 inhibition in peripheral lymphocytes might be the differential distribution of disease‐
associated autoreactive T cells in RA patients in the synovial fluid and the circulation [11].
TYPE 1 DIABETES
Type 1 diabetes mellitus (T1DM) is an autoimmune disease affecting the pancreas by destroying the insulin‐producing beta cells.
Due to the lack of insulin glucose levels increase in blood and in urine. Without insulin treatment T1DM is a fatal disease.
In lymphocytes of healthy subjects both Kv1.3 and IKCa1 channels contribute to the maintenance of Ca2+ influx upon activation.
On the contrary, the sensitivity of T1DM lymphocytes to the inhibition of Kv1.3 channels is increased. Our data indicate that by
specific inhibition of Kv1.3 channels, lymphocyte activation can be modulated in T1DM. It has been hypothesized that beneficial
effects of Kv1.3 channel inhibition by MGTX are due to the dominance of Kv1.3 channels on activated TEM cells [12, 13]. It was
also presumed that MGTX would inhibit the activation of CD8 lymphocytes responsible for cytotoxic destruction of pancreatic
beta cells. Nevertheless, our findings obtained with a functional method (i.e. kinetic flow cytometry measurements) provide
clear evidence for Kv1.3 channels to have an important role in each lymphocyte subset in T1DM, including Th2 lymphocytes
acting as counterbalancing factors in the development of T1DM through the production of antiinflammatory cytokines [14].
Therefore, administration of Kv1.3 channel inhibitors would not have an exclusive effect on cells responsible for the autoimmune
response in T1DM, but may have an impact on the activation characteristics of immune cells in general, leading to unpredictable
alterations. For this reason, further studies are needed to describe the effects of the application of specific Kv1.3 inhibition and
the extent of beneficial consequences in T1DM [8].
ANKYLOSING SPONDYLITIS
Ankylosing spondylitis (AS) is a chronic inflammatory rheumatic disease, the best characterized of the diseases belonging to the
concept of spondylarthritides. The pathogenesis of AS is still unclear, but it is considered to be a systemic autoimmune disease
[15]. This is supported by the number of alterations found in lymphocyte subgroups in peripheral blood. Specifically, increased
numbers of circulating Th2 helper lymphocytes [16] were reported in AS. Along with the alterations observed in cell prevalence
one can assume that T cell activation properties may also be altered in AS. We investigated the short‐term T cell activation
characteristics in AS before and during infliximab (IFX) therapy [17].
CD4 and CD8 cells presented with a delayed increase in cytoplasmic Ca2+ levels after activation in AS compared to controls.
With IFX, therapy the delay in CD4+ cytoplasmic Ca2+ levels did not normalize in AS. For CD8+ cells, cytoplasmic and
mitochondrial Ca2+ kinetics during activation normalized by week 6 on IFX (but not on week 2).
Of note, the increase of cytoplasmic Ca2+ levels in CD4 and CD8cells from AS is delayed compared to controls. The delayed
Ca2+ response of AS fits well into the observations done in in vitro tests with T cells exposed to TNF‐α. Church et al. reported
that TNF‐α suppressed the Ca2+ peak after PHA stimulation; they have suggested that either signalling pathways upstream of
Ca2+ mobilisation or the Ca2+ signalling itself were impaired by prolonged TNF‐α exposure [18]. In AS, only one study has been
performed with a more robust analytical approach: Lee et al. did not observe a significant difference in intracellular Ca2+ between
AS patients and normal controls in activated peripheral blood mononuclear cells [19]. The inconsistency between their and our
results is probably due to different methodology and cell types investigated [17].
HEALTHY PREGNANCY AND PREECLAMPSIA
In healthy pregnancy (HP), the maternal immune system needs to acquire tolerance to protect the developing fetus from harmful
immunological reactions. If this tolerance is impaired, a general maternal immune response may arise, resulting in systemic
inflammation. This has been suggested to be a major factor in the pathogenesis of preeclampsia (PE) [20, 21]. This disorder is
characterized by hypertension, proteinuria, edema and endothelial dysfunction usually evolving in the third trimester of
pregnancy. We compared the activation‐elicited Ca2+ influx in major peripheral T lymphocyte subsets of HP and PE women to
that in non pregnant women and tested the alteration of Ca2+ influx upon treatment with specific inhibitors of the Kv1.3 and
IKCa1 K+ channels.
Our findings suggest that the Ca2+ influx kinetics in activated T lymphocytes markedly differs in HP compared to non pregnant
women: the decreased activation of the Th1 subset may partly be responsible for the well‐established Th2/Th1 skewness in HP
[22, 24]. Indeed, the maintained activation properties of Th1 lymphocytes in patients with PE may contribute to the lack of Th2
dominance associated with normal pregnancy. Similarly, CD8 cells in PE do not acquire suppressed activation kinetics either.
[23] Thus, the decrease in their cytotoxic activity characteristic for HP is not present in PE. It is of particular interest that Ca2+
influx of Th2 lymphocytes in HP was insensitive to K+ channel inhibition, while Ca2+ influx decreased significantly in non pregnant
upon treatment with specific channel blockers. Of note, Th2 lymphocytes in PE presented with non pregnant‐like characteristics
and were sensitive to K+ channel inhibition as well. While it is unclear whether the resistance or sensitivity of Th2 lymphocytes
4
Pag
4e 41
to K+ channel inhibition is reflected in
Th2 function, it is tempting to speculate that this may be an element contributing to the Th2 shift present in HP, but absent in
PE. This hypothesis may be supported by reports suggesting that the shape of Ca2+ influx influenced by K+ channel functions
may determine the cytokine production profile of helper T lymphocytes. Interestingly, other differences were also observed
between HP and PE. While Ca2+ influx in CD8 and Th1 lymphocytes was resistant to K+ channel inhibition in PE, that of HP
lymphocytes was sensitive. Again, while it is unclear whether the resistance of Th1 lymphocytes to K+ channel inhibition is
reflected in their function, the insensitivity of the Th1 subset in PE may be linked to the Th1 skewness. Comparing the inhibitory
properties of lymphocyte K+ channels in non pregnant women and PE, we found that – similarly to the Ca2+ influx kinetics –
they are comparable in all investigated subsets, except for the CD8 lymphocytes. Our results indicate marked differences of Ca2+
influx kinetics and sensitivity to lymphocyte K+ channel inhibition in major lymphocyte subsets between non pregnant, HP and
PE lymphocytes. It is of interest that these properties in PE are more comparable to non pregnant than to HP.
These results suggest that there is a characteristic pattern for Ca2+ influx and its sensitivity to K+ channel inhibition in HP that
is missing in PE. This raises the notion that lymphocyte Ca2+ handling upon activation may have a role in the characteristic
immune status of healthy pregnancy [24].
NEONATES
Decreased functionality of neonatal T cells is a widely recognized experimental and clinical phenomenon. Reduced functioning
is well characterized by a lower level of cytokine production compared with adult T cells [25, 26]. Several factors might be
responsible for the decreased cytokine expression compared with that of adult lymphocytes. Among many others, propositions
include naivity of neonatal lymphocytes. The majority of these cells is naive (CD45RA) lymphocytes in contrast to adults, where
effector (CD45RO) cells dominate [26].
Another possible factor might be the impairment of mechanisms regulating short‐term activation of lymphocytes compared
with adults. Kv1.3 and IKCa1 lymphocyte K+ channels are essential components of these mechanisms. We hypothesized that
short‐term T lymphocyte activation properties are different in neonates compared with adults. The aim of our study was to
characterize the Ca2+ influx kinetics upon activation in major T lymphocyte subsets in the neonate and its sensitivity to the
specific inhibition of Kv1.3 and IKCa1 lymphocyte K+ channels, important regulators of Ca2+ influx.
Ca2+ influx following PHA activation of T lymphocytes markedly differs in the neonate from tha in the adult. Upon treatment of
lymphocytes with selective inhibitors of the Kv1.3 and IKCa1 channels (MGTX and TRAM, respectively), Ca2+ influx reduction
was not demonstrated in neonatal lymphocytes only in CD8 subsets. The finding that neonatal lymphocytes are less sensitive
to the specific inhibition of K+ channels compared with adults may be due to altered functionality or a lower expression of these
channels. Therefore, we measured the expression of Kv1.3 K+ channels on the investigated lymphocytes. Instead of lower values,
we found increased expression of Kv1.3 channels on neonatal CD4, CD8 and Th2 lymphocytes compared with adults. Thus, the
option that the decreased sensitivity of lymphocytes to K+ channel inhibition is due to lower channel expression should be
excluded. Based on the lower sensitivity of lymphocyte Ca2+ influx to inhibition at higher channel expression values, it is
reasonable to postulate that neonatal Kv1.3 channels are functionally altered. Signs of altered sensitivity to K+ channel inhibition
were present in all major lymphocyte subsets investigated (i.e. Th1, Th2, CD4 and CD8 cells). The only subset in which the short‐
term activation was inhibited significantly by specific blockers of both Kv1.3 and IKCa1 channels was CD8 lymphocytes. However,
even in this case, the level of inhibition did not reach the extent described in adults in spite of high Kv1.3 expression values. This
suggests that our observations are generally characteristic of all lymphocyte subpopulations studied. Furthermore, an interesting
observation is that the decreased Ca2+ influx found in the CD8 subset in neonates after MGTX and TRAM treatment is coupled
with a massive elevation in the expression of Kv1.3 channels by this subset. However, no correlation was detected between
Ca2+ influx parameters and channel expression data; thus, a causative relation between the two findings is unlikely.
Our results may partly explain why neonatal lymphocytes are less responsive to activating stimuli and, hence, exert a lower
intensity of immune response. We demonstrated that short‐term activation and associated intracellular Ca2+ influx kinetics are
lower in neonatal lymphocytes compared with adults. This phenomenon is associated with the altered function of lymphocyte
K+ channels. Our results improve the understanding of the mechanisms that prevent neonatal T lymphocytes from adequate
activation upon activating stimuli. They show that the functional impairment of lymphocyte K+ channels may be of importance
in those mechanisms [27].
SUMMARY
Based on our results, a number of dominant features were identified that were present in most of the investigated autoimmune
diseases. First, the time when the peak of Ca2+ influx was reached decreased in autoimmune patients compared to healthy
4
P a g5 e 4 2
individuals, indicating that these cells are in a state of sustained reactivity due to the ongoing autoimmune reaction.
Earlier studies were limited to the investigation of K+ channels in naive and memory lymphocytes. As an extension of these
findings to other significant T lymphocyte subsets, in Th1 cells in patients suffering from an autoimmune disease we detected
a different pattern of sensitivity to the inhibition of lymphocyte K+ channels compared to healthy individuals: a greater decrease
of Ca2+ influx upon the inhibition of the Kv1.3 channel than that of the IKCa1 channel was observed. On the contrary, in healthy
individuals the IKCa1 channels had a more effective inhibition profile compared to the Kv1.3 channels. This finding is of special
interest, since Th1 cells are regarded as key players in the mediation of pro‐infalmmatory responses.
However, the selectivity of the investigated inhibitors (MGTX and TRAM) was limited in our experiments, as they did not only
affect a single subset, as previously suggested. Although in earlier observations the inhibition of Kv1.3 channels specifically
blocked the function of TEM cells, our investigations extending to other significant T lymphocyte subsets demonstrated that the
inhibitory effect is present not only in disease‐associated CD8 and Th1 cells, but also in the anti‐inflammatory Th2 subset. The
induced decrease in their function could lead to unexpected potential side‐effects in vivo and also in a setback of therapy, since
Th2 cells are responsible for anti‐inflammatory responses.
The advantage of our newly developed method compared with the single‐cell techniques is that it enables characterizing the
progress of lymhocyte activation in complex cellular systems, since the interaction between the different cell subsets is also
taken into account. Substances produced during lymphocyte activation (e.g. cytokines, chemokines) modulate the function of
other cell subsets. Thus cell activation does not only affect one cell type but indirectly takes an effect on other cells in the sample.
Accordingly, different lymphocyte subsets might be regarded as a network, where cells are in connection with the ones
surrounding them. Furthermore, not only K+ channel blockers, but other molecules and drugs might be screened. Investigating
other lymphocyte subsets of interest is also possible with our method depending on the type of surface markers used for
discriminating the cell types. Furthermore, our method may play a key role in several other fields of basic and clinical research
where the characterization of different intracellular kinetic processes are needed that can be identified with fluorescent reagents
(e.g. the generation of reactive oxygen radicals, alterations of membrane potential, etc). Further details of our algorithm and its
application can be found at www.facskin.com.
ACKNOWLEDGEMENT
The preparation of this manuscript was supported by grant OTKA 101661.
References:
1. Beeton C, Wulff H, Standifer NE, Azam P, Mullen KM, Pennington MW, Kolski‐Andreaco A, Wei E, Grino A, Counts DR, Wang PH, LeeHealey
CJ, Andrews BS, Sankaranarayanan A, Homerick D, Roeck WW, Tehranzadeh J, Stanhope KL, Zimin P, Havel PJ, Griffey S, Knaus HG, Nepom
GT, Gutman GA, Calabresi PA, Chandy KG. Kv1.3 channels are a therapeutic target for T cellmediated autoimmune diseases. Proc Natl Acad
Sci USA 2006; 103:17414‐17419.
2. Chandy KG, Wulff H, Beeton C, Pennington M, Gutman GA, Cahalan MD. K+ channels as targets for specific immunomodulation. Trends
Pharmacol Sci 2004; 25:280‐289.
3. Wulff H, Calabresi PA, Allie R, Yun S, Pennington M, Beeton C, Chandy KG. The voltage‐ gated Kv1.3 K+ channel in effector memory T cells
as new target for MS. J Clin Invest 2003; 111:1703‐1713.
4. Rangaraju S, Chi V, Pennington MW, Chandy KG. Kv1.3 potassium channels as a therapeutic target in multiple sclerosis. Expert Opin
Ther Targets 2009; 13:909‐924.
5. Rus H, Pardo CA, Hu L, Darrah E, Cudrici C, Niculescu T, Niculescu F, Mullen KM, Allie R, Guo L, Wulff H, Beeton C, Judge SI, Kerr DA, Knaus
HG, Chandy KG, Calabresi PA. The voltage‐gated potassium channel Kv1.3 is highly expressed on inflammatory infiltrates in multiple sclerosis
brain. Proc Natl Acad Sci USA 2005; 102:11094‐11099.
6. Varga Z, Csepany T, Papp F, Fabian A, Gogolak P, Toth A, Panyi G. Potassium channel expression in human CD4+ regulatory and naïve T cells
from healthy subjects and multiple sclerosis patients. Immunol Lett 2009; 124:95‐101.
7. Kaposi AS, Veress G, Vásárhelyi B, Macardle P, Bailey S, Tulassay T, Treszl A. Cytometry‐acquired calcium‐flux data analysis in activated
lymphocytes. Cytometry A 2008; 73:246‐253.
8. Toldi G, Vásárhelyi B, Kaposi A, Mészáros G, Pánczél P, Hosszufalusi N, Tulassay T, Treszl A. Lymphocyte activation in type 1 diabetes mellitus:
the increased significance of Kv1.3 potassium channels. Immunol Lett 2010; 133:35‐41.
9. Martino G, Furlan R, Brambilla E, Bergami A, Ruffini F, Gironi M, Poliani PL, Grimaldi LM, Comi G. Cytokines and immunity in multiple
sclerosis: the dual signal hypothesis. J Neuroimmunol. 2000; 109:3‐9.
10. Toldi G, Folyovich A, Simon Z, Zsiga K, Kaposi A, Mészáros G, Tulassay T, Vásárhelyi B. Lymphocyte calcium influx kinetics in multiple sclerosis
treated without or with interferon β. J Neuroimmunol 2011; 237:80‐86.
11. Toldi G, Bajnok A, Dobi D, Kaposi A, Kovács L, Vásárhelyi B, Balog A. The effects of Kv1.3 and IKCa1 potassium channel inhibition on calcium
influx of human peripheral T lymphocytes in rheumatoid arthritis. Immunobiology 2012 May 23 [Epub ahead of print]
12. Wulff H, Calabresi PA, Allie R, Yun S, Pennington M, Beeton C, Chandy KG. The voltage‐gated Kv1.3 K+ channel in effector memory T cells
as new target for MS. J Clin Invest 2003; 111:1703‐1713.
4
P a g6 e 4 3
13. Chandy KG, Wulff H, Beeton C, Pennington M, Gutman GA, Cahalan MD. K+ channels as targets for specific immunomodulation. Trends
Pharmacol Sci 2004; 25:280‐289.
14. Yoon JW, Jun HS. Cellular and molecular pathogenic mechanisms of insulin‐dependent diabetes mellitus. Ann NY Acad Sci 2001; 928:200‐
211.
15. Colbert RA, Delay ML, Klenk EI, Layh‐Schmitt G. From HLA‐B27 to spondyloarthritis: a journey through the ER. Immunol Rev 2010; 233:181‐
202.
16. Yang PT, Kasai H, Zhao LJ, Xiao WG, Tanabe F, Ito M. Increased CCR4 expression on circulating CD4+ T cells in ankylosing spondylitis,
rheumatoid arthritis and systemic lupus erythematosus. Clin Exp Immunol 2004; 138:342‐347.
17. Szalay B, Mészáros G, Cseh Á, Ács L, Deák M, Kovács L, Vásárhelyi B, Balog A. Adaptive immunity in ankylosing spondylitis: phenotype and
functional alterations of T‐cells before and during infliximab therapy. Clin Dev Immunol 2012; 2012:808724.
18. Church LD, Goodall JE, Rider DA, Bacon PA, Young SP. Persistent TNF‐α exposure impairs store operated calcium influx in CD4+ T
lymphocytes. FEBS Letters 2005;579:1539‐1544.
19. Lee HT, Chen WS, Chen MH, Tsai CY, Chou CT. The expression of proinflammatory cytokines and intracellular minerals in patients with
ankylosing spondylitis. Formosan J Rheumatol 2009; 23:40‐46.
20. Saito S, Shiozaki A, Nakashima A, Sakai M, Sasaki Y. The role of the immune system in preeclampsia. Mol Aspects Med 2007; 28:192‐209.
21. Redman CW, Sargent IL. Immunology of pre‐eclampsia. Am J Reprod Immunol 2010;63:534‐543.
22. Darmochwal‐Kolarz D, Leszczynska‐Gorzelak B, Rolinski J, Oleszczuk J. T helper 1‐ and T helper 2‐type cytokine imbalance in pregnant
women with pre‐eclampsia. Eur J Obstet Gynecol Reprod Biol 1999; 86:165‐170.
23. Darmochwal‐Kolarz D, Saito S, Rolinski J, Tabarkiewicz J, Kolarz B, Leszczynska‐ Gorzelak B, Oleszczuk J. Activated T lymphocytes in
preeclampsia. Am J Reprod Immunol 2007; 58:39‐45.
24. Toldi G, Stenczer B, Treszl A, Kollár S, Molvarec A, Tulassay T, Rigó J, Vásárhelyi B. Lymphocyte calcium influx characteristics and their
modulation by Kv1.3 and IKCa1 channel inhibitors in healthy pregnancy and preeclampsia. Am J Reprod Immunol 2011;65:154‐63.
25. Cohen SB, Perez‐Cruz I, Fallen P, Gluckman E, Madrigal JA. Analysis of the cytokine production by cord and adult blood. Hum Immunol
1999; 60:331‐336.
26. García Vela JA, Delgado I, Bornstein, Alvarez B, Auray MC, Martin I, Oña F, Gilsanz F. Comparative intracellular cytokine production by in
vitro stimulated T lymphocytes from human umbilical cord blood (HUCB) and adult peripheral blood (APB). Anal Cell Pathol 2000; 20:93‐
98.
27. Toldi G, Treszl A, Pongor V, Gyarmati B, Tulassay T, Vásárhelyi B. T‐lymphocyte calcium influx characteristics and their modulation by Kv1.3
and IKCa1 channel inhibitors in the neonate. Int Immunol 2010; 22:769‐774.
4
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8ESPolak
E.S. POLLAK
ADVANCES IN ORAL COAGULANTS
Eleanor S. Pollak
Department of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, and Children's Hospital of
Philadelphia and the Philadelphia VA Medical Center
Eleanor S. Pollak, MD, FCAP
Associate Professor
Department of Pathology and Laboratory Medicine
Hospital of the University of Pennsylvania, and
Children's Hospital of Philadelphia and
the Philadelphia VA Medical Center
310B Abramson Research Center
3615 Civic Center Blvd.
Philadelphia, PA 19104
Office: (215)590-6117; Fax: (215)590-2320
e-mail: Pollak@mail.med.upenn.edu
Key words: oral anticoagulants, warfarin, pharmacogenetics, dabigatran, rivaroxaban, apixaban
ABSTRACT
This article reviews current and future treatment practices concerning oral anticoagulants. In the second decade of the 21st
millennium clinicians can finally treat thrombotic disease with long-awaited new oral anticoagulant medications. In addition,
improvements have been made in managing warfarin, the traditional but far from obsolete medication. The first part of this
review will cover current advances with warfarin treatment. The second portion will discuss specific active coagulation factor
inhibitors, the new oral anticoagulants.
Warfarin
The drug warfarin has remained the principal oral anticoagulant medication used to hinder the coagulation waterfall cascade of
proteolytic enzymes.[1] Although warfarin was patented back in the 1940s and was followed by an onslaught of correlated
scientific activity, the actual gene for the warfarin target, Vitamin K epoxide reductase (VKOR), was not identified until 2004.[2,
3] This discovery of VKOR has also allowed the medical field to focus on decreasing warfarin‘s dangerous safety profile by
generating new complementary genetic tests.[4]
The warfarin preparation: Technically, the warfarin compound (C19H16O4), [C19H15NaO4 -- commonly known by the brand name:
Coumadin ®], is a racemic mixture of the R- and S-enantiomers of 3-(α-acetonylbenzyl)-4-hydroxycoumarin. It is a crystallized
form of warfarin sodium, an isopropanol clathrate, which essentially lacks any of the impurities of its amorphous form. In some
countries, different coumarins with either shorter (acenocoumarol) or longer (phenprocoumon) half-lives are used in place of
warfarin. Despite worldwide use, tremendous disadvantages still accompany warfarin. Notably, the prescribed drug dosage has
a dangerously narrow therapeutic index. Vast variability exists for warfarin dosage needs depending in part on common patient
genotypes. The frequent genotypes influencing this variability have focused on two principal genetic variant groups. These
variants belong to vitamin K-epoxide reductase complex (VKORC1) enzymes as well as cytochrome P450-2C9 (CYP2C9) molecules
and influence drug concentration and metabolism, respectively.[4]
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E.S. POLLAK
Warfarin is contraindicated when the risk hazard is greater for hemorrhage than for the benefit provided by anticoagulation.
The Prothrombin Time (PT) response due to warfarin may be influenced by a multitude of endogenous and exogenous factors.
These not only include therapeutically prescribed medications, but herbal compounds as well as food consumed. In the United
States, at the request of the FDA (United States Food and Drug Administration) in 2006, the company Bristol-Myers Squibb
inserted a “black-box warning” label for Coumadin on the risk of major or fatal bleeding.
It is essential that a patient’s PT/INR (Internationally Normalized Ratio) be determined on a frequent basis. Thus, warfarin use
must be carefully watched when insufficient laboratory facilities would complicate monitoring. Care should be taken to avoid or
prudently consider use with pregnancy [5], blood dyscrasias, and imminent surgery of the CNS, eye or large exposed surfaces.
Additionally, unsupervised patients at risk for mishaps pose significant dangers. A non-profit website provides a validated
calculation tool to assist with warfarin dosing decisions: http://www.warfarindosing.org.[6]
In the mid 1980s, the recognition of problems of non-uniform testing of the PT ultimately led to an international method to
standardize and calibrate warfarin-like anticoagulant compounds. This resulted in the assignment of the World Health
Organization (WHO) thromboplastin preparation with an International Sensitivity Index (ISI) of 1.1. A comparison ratio to this
ISI is measured and reported for each laboratory’s thromboplastin using the unit of the International Normalised Ratios (INR).[7]
Overall, the use of warfarin has improved for compliant, regularly monitored patients. However, many of the extant difficulties
have been greatly decreased with the introduction of new drugs.
New Oral Anticoagulant Medications
In this decade new oral anticoagulants are becoming the preferred therapy for indications when warfarin had been the only
available oral anticoagulant therapy for over the previous half a century. The medications, dabigatran, rivaroxaban, abixaban,
betrixaban, and edoxaban are small-molecule, selective inhibitors that bind to the active site of coagulation vitamin K dependent
factors IIa or Xa. These recently developed new oral anticoagulants possess general similarities to the chemical structure of
warfarin. Molecular weights of these new oral anticoagulants are approximately 1.5 to 2 times that of warfarin. (see Table 1).
The new oral anti-coagulants are attractive to patients, many healthcare providers, and healthcare system suppliers in part
because laboratory monitoring is not routinely required; standard fixed doses are prescribed to patients with normal weights
and renal function. This saves time and energy for those patients who would have normally been required to travel to a testing
site for frequent warfarin monitoring. The new anticoagulants also reduce other drawbacks of warfarin including multiple drug
interactions and problematic pharmacogenetics. Three of the novel new oral anticoagulants, dabigatran, rivaroxaban, apixaban
have each been tested head-to-head against warfarin in large clinical trials for the indication of treatment of atrial fibrillation
(AF).[8-10] Although no trial has prospectively tested these agents against each other, several meta-analyses provide added
perspective regarding the utility and benefits that may be provided by these medications.[11] A semisystematic review and
meta-analysis of 44,563 patients showed the new oral anticoagulants to be superior to warfarin in patients without heart failure
regardless of gender or the presence of diabetes. However, additional benefits were not seen alongside the concurrent conditions
of heart failure nor nonparoxysmal atrial fibrillation.[12]
Table 2 provides the specifics of the targeted enzyme, the drug half-life, the bioavailability, the % renal excretion, the doses /day
of medication, possible method of testing if needed, the year of FDA approval for human use, the name of trial and safety risks
of bleeding. All of these new drugs reach peak plasma levels between 1 and 4 hours after administration.
However, there remain patient characteristics that commonly influence the safety, efficacy and pharmacokinetics of the new
oral anticoagulants. These include obesity, reduced hepatic, gastrointestinal and renal organ function, and contemporaneous
prescriptions of interfering medications. It should be noted that factor Xa inhibitors are not devoid of problems and still do have
potential interactions with other compounds including inhibitors and inducers of cytochrome P450 and the P-glycoprotein (Pgp) transporter-mediated drug interactions. Drugs that may be contra-indicated include: NSAIDs, ASA, anti-platelet drugs, proton
pump inhibitors, and inhibitors or inducers of P-gp transport or CYP3A4.[13] [14] [15] The following populations were not
included in most of the major new oral anticoagulant trials: pediatric, pregnant, elderly, and chronically ill patients. In addition,
to the cited comparisons with warfarin (see Table 2), new oral anticoagulant apixaban was also shown to be more effective than
aspirin in stroke risk reduction in the AVERROES trial. [15]
Despite the overall attraction of the new anticoagulants, other advantages must be carefully balanced. The major benefit in the
use of warfarin remains the large ratio of its efficacy to its cost and availability. Besides the difficult issue with the new
anticoagulants compliance due to the lack of regular monitoring the current high cost of the medications may result in patients
saving money by not filling their prescriptions or reducing the number of pills the patient takes.
The most dangerous aspect of the new anticoagulants is the lack specific antidotes to reverse the medication should there be
4
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E.S. POLLAK
Table 1
New Oral Anticoagulants
Anti-coagulant Drug
Chemical Formula and Molecular Weight
Tradename & Company
C19H16O4
308 g/mol
COUMADIN®
Bristol-Myers
Squibb
C34H41N7O5
628 g/mol
PRADAXA®
Boehringer
Ingelheim
C19H18ClN3O5S
436 g/mol
XARELTO®
Bayer/
Janssen
Pharmaceutical
Apixaban
C25H25N5O4
459/mol
ELIQUIS®
Pfizer and
Bristol-Myers
Squibb
Edoxaban
C24H30ClN7O4S
548 g/mol
LIXIANA®
Daiichi Sankyo
Warfarin
Dabigatran
etexilate
Rivaroxaban
Chemical Structure
Table 2
Oral Anticoagulant Characteristics
Anti-coagulant
Drug
Targeted
Enzyme
Half-Life
(hrs)
Warfarin
Vitamin K
dependent Enzymes
40
Dabigatran
Thrombin
12 to 17
Rivaro-xaban
Factor Xa
Apixaban
Factor Xa
% Bio-availability
FDA
approval
Name
of Trial
Safety risks
for major
bleeding vs.
warfarin
1
1954* in
humans
----
----
Thrombin Time
(TT) or Dilute TT
2
2010
RE-LY
Comparable
65
anti-Xa
1
2011
ROCKET AF
Comparable
25
anti-Xa
2
2012
ARIS-TOTLE
Superior
Renal
Excretion
Method of
testing if needed
92
Prothrombin
Time (PT)
6
80
9
80
9 to 14
50
Dose/ day
a problem with bleeding. This is particularly relevant in the case of catastrophic bleeding due to excess medication. Guidance
on treatment includes quickly providing routine supportive care. Because the new anticoagulants have short durations of
effectiveness discontinuing the anticoagulant most commonly resolves the problem of excess
medication.[13] However, if necessary, activated charcoal may be an option if the ingestion is within several hours of the
treatment. As dabigatran is only 1/3 bound by albumin, hemodialysis is a possibility reversal of dabigatran, particularly in cases
when poor renal function delays natural drug elimination.[16]. Vitamin K has no indication in the scenario of reversing action of
the new anticoagulants. However, another major benefit of warfarin includes the effectiveness of administering Vitamin K as an
antidote in the event of over-anticoagulation.
Specific drug-directed neutralizing antibodies are under development for oral anticoagulants dabigatran and apixaban against
Factors IIa and Xa, respectively.[17, 18]
The challenge to physicians is clear. Warfarin's use since the 1950s provides practioners with expertise not yet available when
4
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E.S. POLLAK
using the newer oral anticoagulants. Cost considerations are an extra burden that new medications add to decision-making.
The solution to the age-old cost/benefit conundrum and the necessary substantial familiarity with the new drugs are issues to
be solved by experience and time. The end result will be better outcomes for our patients, our guiding mission.
References
1. Davie, E.W., Fujikawa K., Kurachi, K., Kisiel, W., The role of serine proteases in the blood coagulation cascade. Adv Enzymol Relat Areas Mol
Biol. , 1979. 48: p. 277-318.
2. Link, K.P. The discovery of dicumarol and its sequels. Circulation, 1959. 19(1): p. 97-107.
3. Li, T., Chang, C. Y., Jin, D. Y., Lin, P. J., Khvorova, A., Stafford, D. W, Identification of the gene for vitamin K epoxide reductase. Nature, 2004.
427(6974): p. 541-4.
4. Johnson, J. A., Gong, L., Whirl-Carrillo, M., Gage, B. F., Scott, S. A., Stein, C. M., Anderson, J. L., Kimmel, S. E., Lee, M. T., Pirmohamed, M.,
Wadelius, M., Klein, T. E., Altman, R. B., Clinical Pharmacogenetics Implementation Consortium Guidelines for CYP2C9 and VKORC1
genotypes and warfarin dosing. Clin Pharmacol Ther, 2011. 90(4): p. 625-9.
5. Blickstein, D. and I. Blickstein, The risk of fetal loss associated with Warfarin anticoagulation. Int J Gynaecol Obstet, 2002. 78(3): p. 221-5.
6. Gage, B.F., Eby, C., Johnson, J.A., Deych, E., Rieder, M.J., Ridker, P.M., et al., Use of pharmacogenetic and clinical factors to predict the
therapeutic dose of warfarin. Clin Pharmacol Ther., 2008. 84(3): p. 326-31.
7. Thomson, J.M., Tomenson, J.A., Poller, L., The calibration of the second primary international reference preparation for thromboplastin
(thromboplastin, human, plain, coded BCT/253). Thromb Haemost. 1984. 52(3): p. 336-42.
8. Connolly, S.J., Ezekowitz, M.D., Yusuf, S. et al, Dabigatran versus warfarin in patients with atrial fibrillation. N Engl J Med, 2009. 361: p.
1139-51.
9. Patel, M.R., Mahaffey, K.W., Garg, J., et al., Rivaroxaban versus warfarin in nonvalvular atrial fibrillation. N Engl J Med 2011;365:883-91. N
Engl J Med 2011;365:883-91., 2011. N Engl J Med 2011;365:883-91.: p. 883-91.
10. Connolly, SJ, Eikelboom, J., Joyner, C., et al., Apixaban in patients with atrial fibrillation. N Engl J Med 2011. 363: p. 806-17.
11. Mantha, S. and J. Ansell, An indirect comparison of dabigatran, rivaroxaban and apixaban for atrial fibrillation. Thromb Haemost, 2012.
108(3): p. 476-84.
12. Ahmad Y, L.G., Apostolakis S., New oral anticoagulants for stroke prevention in atrial fibrillation: impact of gender, heart failure, diabetes
mellitus and paroxysmal atrial fibrillation. Expert Rev Cardiovasc Ther., 2012. 10(12): p. 1471-80.
13. Kaatz, S., Kouides, P. A., Garcia, D. A., Spyropolous, A. C., Crowther, M., Douketis, J. D., Chan, A. K., James, A., Moll, S., Ortel, T. L., Van Cott,
E. M., Ansell, J. Guidance on the emergent reversal of oral thrombin and factor Xa inhibitors. Am J Hematol, 2012. 87 Suppl 1: p. S141-5.
14. Cabral, K.P. and J. Ansell, Oral direct factor Xa inhibitors for stroke prevention in atrial fibrillation. Nat Rev Cardiol, 2012. 9(7): p. 385-91.
15. Littrell, R. and Flaker, G. Apixaban for the prevention of stroke in atrial fibrillation. Expert Rev Cardiovasc Ther, 2012. 10(2): p. 143-9.
16. van Ryn, J., Stangier, J., Haertter, S., Liesenfeld, K. H., Wienen, W., Feuring, M., Clemens, A., Dabigatran etexilate--a novel, reversible, oral
direct thrombin inhibitor: interpretation of coagulation assays and reversal of anticoagulant activity. Thromb Haemost, 2010. 103(6): p.
1116-27.
17. Portola Pharmaceuticals, Portola initiates phase 2 study of PRT4445, universal antidote for factor Xa inhibitor anticoagulants [press release].
2012.
18. van Ryn, J., Litzenburger, T., Gan, G., Coble, K. and Schurer, J., In vitro Chacterization, Pharmacokinetics and Reversal of supratherapeutic
doses of dabigatran-induced bleeding in rats by a specific antibody fragment antidote to dabigatran., in American Heart Association:
Scientific Sessions. 2012.
19. Horton, J.D., and Bushwick, B.M., Warfarin Therapy: Evolving Strategies in Anticoagulation, Am Fam Physician., 1999 59(3):635-646.
20. Potpara, T. S., Polovina, M. M., Licina, M. M., Stojanovic, R. M., Prostran, M. S., Lip, G. Y., Novel oral anticoagulants for stroke prevention
in atrial fibrillation: focus on apixaban. Adv Ther., 2012. 29(6): p. 491-507.
21. Doggrell, S.A., More light at the end of the tunnel - apixaban in atrial fibrillation. Expert Opin Investig Drugs, 2012. 21(8): p. 1235-9.
22. Hochtl, T. and Huber, K., New anticoagulants for the prevention of stroke in atrial fibrillation. Fundam Clin Pharmacol, 2012. 26(1): p. 4753.
23. Pollack, C.V., Jr., New oral anticoagulants in the ED setting: a review. Am J Emerg Med, 2012.
24. Carter, K. L., Streiff, M. B., Ross, P. A., Wellman, J. C., Thomas, M. L., Kraus, P. S., Shermock, K. M. Analysis of the projected utility of
dabigatran, rivaroxaban, and apixaban and their future impact on existing Hematology and Cardiology Anticoagulation Clinics at The Johns
Hopkins Hospital. J Thromb Thrombolysis, 2012. 34(4): p. 437-45.
25. Esmon, C.T., What did we learn from new oral anticoagulant treatment? Thromb Res., 2012. 130(Suppl 1): p. S41-3.
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