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Larson RA, Druker BJ, Guilhot FA, O’Brien SG, Riviere GJ, Krahnke T, Gathmann I, Wang YImatinib pharmacokinetics and its correlation with response and safety in chronic phase chronic myeloid leukemia: a subanalysis of the IRIS study. Blood 111(8): 4022-4028

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Imatinib at 400 mg daily is standard treatment for chronic myeloid leukemia in chronic phase. We here describe the correlation of imatinib trough plasma concentrations (C(mins)) with clinical responses, event-free survival (EFS), and adverse events (AEs). Trough level plasma samples were obtained on day 29 (steady state, n = 351). Plasma concentrations of imatinib and its metabolite CGP74588 were determined by liquid chromatography/mass spectrometry. The overall mean (+/- SD, CV%) steady-state C(min) for imatinib and CGP74588 were 979 ng/mL (+/- 530 ng/mL, 54.1%) and 242 ng/mL (+/- 106 ng/mL, 43.6%), respectively. Cumulative estimated complete cytogenetic response (CCyR) and major molecular response (MMR) rates differed among the quartiles of imatinib trough levels (P = .01 for CCyR, P = .02 for MMR). C(min) of imatinib was significantly higher in patients who achieved CCyR (1009 +/- 544 ng/mL vs 812 +/- 409 ng/mL, P = .01). Patients with high imatinib exposure had better rates of CCyR and MMR and EFS. An exploratory analysis demonstrated that imatinib trough levels were predictive of higher CCyR independently of Sokal risk group. AE rates were similar among the imatinib quartile categories except fluid retention, rash, myalgia, and anemia, which were more common at higher imatinib concentrations. These results suggest that an adequate plasma concentration of imatinib is important for a good clinical response. This study is registered at http://clinicaltrials.gov as NCT00333840.
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doi:10.1182/blood-2007-10-117531
Prepublished online January 24, 2008;
Andrey S Shaw, Tony Petrella, Harald Stein, Peter G Isaacson, Fabio Facchetti and David Y Mason
Michael Dictor, Martin-Leo Hansmann, Stefano A Pileri, Martin J Dyer, Silvano Sozzani, Ivan Dikic,
Teresa Marafioti, Jennifer C Paterson, Erica Ballabio, Kaaren K Reichard, Sara Tedoldi, Kevin Hollowood,
cells
Novel markers of normal and neoplastic human plasmacytoid dendritic
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20036.
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Novel markers of normal and neoplastic human plasmacytoid dendritic cells
Running Head: Immunoprofile of normal and neoplastic pDC
Teresa Marafioti
1
, Jennifer C. Paterson
1,*
, Erica Ballabio
1,*
, Kaaren K. Reichard
2,*
,
Sara Tedoldi
1
, Kevin Hollowood
3
, Michael Dictor
4
, Martin-Leo Hansmann
5
, Stefano A.
Pileri
6
, Martin J. Dyer
7
, Silvano Sozzani
8
, Ivan Dikic
9
, Andrey S. Shaw
10
, Tony
Petrella
11
, Harald Stein
12
, Peter G. Isaacson
13
, Fabio Facchetti
8
, and David Y.
Mason
1
1
Leukaemia Research Fund Immunodiagnostics Unit, Nuffield Department of Clinical
Laboratory Sciences, John Radcliffe Hospital, Oxford, United Kingdom;
2
Department
of Pathology, University of New Mexico, Albuquerque, NM;
3
Department of Cellular
Pathology, John Radcliffe Hospital, Oxford, United Kingdom;
4
Department of
Pathology, Lund University Hospital, Lund, Sweden;
5
Senckenberg Pathology
Institute, Johann Wolfgang Goethe-University Clinic Frankfurt am Main, Germany;
6
Haematopathology Unit, "L&A Seragnoli" Institute of Haematology, University of
Bologna, Italy;
7
MRC Toxicology Unit, University of Leicester, United Kingdom;
8
Department of Pathology and General Pathology, University of Brescia, Italy;
9
Institute of Biochemistry II, Goethe University School of Medicine, University Clinic
Frankfurt am Main, Germany;
10
Department of Pathology, Washington University
School of Medicine, St. Louis, MO;
11
Department of Pathology and Centre of
Pathology, Hospital-University Centre, Dijon, France;
12
Institute for Pathology,
Campus Benjamin Franklin, Charité University Medicine Berlin, Germany;
13
Department of Pathology, University College London, London, United Kingdom
Corresponding author’s address: Dr. Teresa Marafioti, Leukaemia Research Fund
Immunodiagnostics Unit, Nuffield Department of Clinical Laboratory Sciences, John
Radcliffe Hospital, Oxford, OX3 9DU, United Kingdom.
* J.C.P., E.B. and K.R. contributed equally to this work.
The work was carried out in the Leukaemia Research Fund Immunodiagnostics Unit,
Nuffield Department of Clinical Laboratory Sciences, John Radcliffe Hospital, Oxford,
United Kingdom.
Blood First Edition Paper, prepublished online January 24, 2008; DOI 10.1182/blood-2007-10-117531
Copyright © 2008 American Society of Hematology
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Abstract
Plasmacytoid dendritic cells (pDC) are involved in innate immunity (eg by secreting
interferons) and also give rise to "CD4+CD56+ hematodermic neoplasms". We report
extensive characterization of human pDC in routine tissue samples, documenting the
expression of 19 immunohistologic markers, including signaling molecules (eg
BLNK), transcription factors (eg ICSBP/IRF8 and PU.1) and Toll-like receptors (TLR7
and TLR9). Many of these molecules are expressed in other cell types (principally B
cells), but the adaptor protein CD2AP was essentially restricted to pDC, and is
therefore a novel immunohistologic marker for use in tissue biopsies. We found little
evidence for activation-associated morphologic or phenotypic changes in conditions
where pDC are greatly increased (eg Kikuchi’s disease). Most of the molecules were
retained in the majority of pDC neoplasms, and three (BCL11A, CD2AP and
ICSBP/IRF8) were also commonly negative in "leukemia cutis" (acute myeloid
leukemia in the skin), a tumor that may mimic pDC neoplasia. In summary, we have
documented a range of molecules (notably those associated with B cells) expressed
by pDC in tissues and peripheral blood (where pDC were detectable in cytospins at a
frequency of <1% of mononuclear cells) and also defined potential new markers (in
particular CD2AP) for the diagnosis of pDC tumors.
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Introduction
Hematologists are familiar with the major cell lineages generated in the bone marrow
and with the neoplastic disorders to which they give rise. However, less attention has
been focussed on minor hematopoietic subpopulations that, despite their low
numbers have important functional roles and are of clinical relevance because of
their capacity to undergo neoplastic transformation.
One such lineage comprises the cell type known as “plasmacytoid dendritic
cells” (pDC), a population that is typically found in cell clusters (or as isolated cells) in
T cell-rich interfollicular areas in peripheral lymphoid tissue.
1,2
Their “plasmacytoid”
morphology reflects a rich content of rough endoplasmic reticulum whose major
product comprises type I interferons (mainly interferon-
α
). They respond to a variety
of stimuli (including viruses, and hypo- and non-methylated bacterial DNA
sequences
3-6
) and carry receptors, including a number of Toll-like receptors, capable
of binding a spectrum of pathogen-associated molecules.
7
They therefore represent a
strategically positioned first line defence against viral and other pathogens entering
lymphoid tissue from the circulation.
A number of studies have documented the molecules expressed at the RNA
and/or protein level by pDC, although more data are available for the mouse than for
man.
8
Knowledge of the phenotype of pDC is not only of relevance to an
understanding of their origin and function but is also of potential clinical importance in
the field of hemato-oncology since it has been recognized for a number of years that
pDC can undergo neoplastic transformation. In early reports it was noted that such
neoplasms were associated with a myeloproliferative disorder (principally acute or
chronic myelomonocytic or monocytic leukemia),
9
but more recently a distinctive
tumor type, “CD4+C56+ hematodermic neoplasm” involving both the skin and
peripheral blood/bone marrow, has been documented.
10
The diagnosis of these tumors in biopsy samples is based principally on
markers such as CD4, CD56, CD123 and TCL1,
10-12
but most of these are present on
other cell types. Furthermore, difficulties in diagnosis can also arise when a molecule
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is absent or is aberrantly expressed. There is therefore a need for robust additional
markers of pDC detectable in routine biopsies that are expressed on their neoplastic
counterparts but are not found on tumors with which they may be confused.
In this paper we report an extensive immunophenotypic characterization of
human pDC and document a range of molecules (eg involved in cell signaling and
gene transcription) that have not previously been demonstrated in pDC in routine
biopsy material. Many of these are also expressed on neoplastic pDC, and one
molecule, the adaptor protein CD2AP, is not expressed to a comparable degree by
other peripheral white cells, making it a valuable new marker for detecting normal
and neoplastic pDC in tissue biopsies and in peripheral blood.
Materials and methods
Tissue samples
Paraffin-embedded tissue sections of reactive human tonsils, lymph nodes with
histologic features of Castleman’s disease (no. 4), of Kikuchi’s disease (no. 4), skin
biopsies of cutaneous lupus erythematosus (no. 6), lichen planus (no. 5) and normal
bone marrow trephines (no. 2) were obtained from the authors’ institutions. Cryostat
sections of human tonsils from the same source were also used for this study.
Tissue sections from 47 pDC-derived neoplasms were obtained from the
author’s institutions (M.D., F.F., P.G.I., P.T., T.M., K.R. and H.S.) and comprised:
a) Cutaneous, bone marrow or splenic tumors, which had been diagnosed as "blastic
NK-cell lymphoma",
13
"CD4+CD56+ hematodermic neoplasm"
10
or simply (in the
case of two cutaneous neoplasms) as "pDC tumors" (41 cases).
b) Neoplasms diagnosed as "pDC proliferations associated with myeloproliferative
disorders"
9
(6 cases).
Table 1 summarises the available phenotype and clinical data for each case of
pDC neoplasia. The study also included tissue sections of: a) 24 acute myeloid
leukemia in the skin (“leukemia cutis”), with and without CD56 expression, b) bone
marrow trephines from seven chronic myeloid and five chronic myelomonocytic
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leukemias, and c) tissue sections from B- and T-lymphoblastic leukemia/lymphomas
(seven and six cases respectively). This material was retrieved from the files of six
authors (F.F., K.H., M.-L.H., T.M., D.Y.M. and S.P.). The diagnosis of all lymphoid
and myeloid neoplasms was based on the criteria of the WHO classification.
13
Approval from the Oxford Research Ethics Committee B was obtained for this study
(Ref: C02.162).
Peripheral blood samples
Peripheral blood mononuclear cells (PBMCs) were isolated from human EDTA-
anticoagulated peripheral blood from healthy donors after informed consent by a
conventional gradient centrifugation technique using Histopaque (Sigma-Aldrich,
Gillingham, UK). The isolated PBMCs at 1.25x10
6
/ml were used to prepare cytospins
according to a protocol described elsewhere.
14
PDC purification
Peripheral blood mononuclear cells were isolated from buffy coats by Ficoll gradient
(Amersham Biosciences) and pDC were magnetically sorted with blood DC Ag
BDCA-4 cell isolation kits (Miltenyi Biotec), as described previously.
15
More than 90%
of the purified cells expressed CD123 (assessed by flow cytometry – data not
shown), confirming the plasmacytoid DC nature of the great majority of the isolated
cells. Blood pDC isolated in this way (10
6
cells/ml) were cultured in medium
containing 1,000 U/ml recombinant human GM-CSF (Myelogen; Schering-Plough,
Dardilly, France) and 20 ng/ml IL-3 (ProSpec). PDC were finally collected as cytospin
and fixed in 95% ethanol for 5 minutes before immunostaining.
Antibodies
The antibodies used in this study for immunohistologic staining are detailed in Table
2.
Immunostaining
Single immunostaining, double immunoenzymatic and immunofluorescent labeling
was performed on tissue sections and on cytospin preparations of peripheral blood
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mononuclear cells, as described previously.
14,16
In some experiments cytospin
preparations were subjected to “antigen retrieval” in a microwave oven in EDTA-
buffer prior to immunostaining.
Results
Detection of novel markers associated with normal pDC
Paraffin-embedded tissue sections of reactive human tonsils containing abundant
pDC were screened with antibodies against a range of leucocyte-associated
molecules in order to identify markers strongly and selectively expressed in these
cells. Some of the molecules evaluated were chosen because they had been
documented in pDC in the literature (but usually only at the level of mRNA
expression, often in mice) and none had been studied previously in human tissue by
immunohistologic techniques (with the exception of BCL11A, reported recently in
pDC in a single publication
17
). The other molecules evaluated were randomly
selected known leucocyte-associated markers.
The adaptor protein CD2AP emerged from this immunohistologic screening as
a selective marker of pDC, being expressed uniformly throughout the cytoplasm of
these cells (Figure 1). It was not found in other cells in peripheral lymphoid tissue
(with the exception of very weak labeling of mantle zone B cells in some samples and
rare cells in germinal centers). CD2AP was originally cloned from T cells,
18-20
but in
the present study peripheral T cells were consistently CD2AP negative (using three
different antibodies) regardless of antibody dilution or whether the tissue section
came from a paraffin embedded or a cryostat sample. Endothelial cells and tonsillar
squamous epithelium were weakly to moderately positive. In addition, 18 other
molecules were expressed by cells with the typical features of pDC, as summarized
in Table 3. These markers differed greatly in the degree to which they were
expressed in cell types other than pDC but many molecules were also present in B
cells (see Table 3).
Double immunolabeling was performed to explore the relationship between the
new cytoplasmic pDC marker CD2AP and the known pDC-associated transcription
factor BCL11A. This revealed that BCL11A and CD2AP were expressed in the same
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cells (Figure 1), and in double immunoenzymatic labeling studies of the phenotype of
pDC (see Figures 1-4) these two markers were therefore used interchangeably to
reveal pDC (eg CD2AP was used in combination with nuclear markers and BCL11A
in combination with cytoplasmic molecules).
A number of B cell-associated transcription factors, namely ICSBP/IRF8, the
products of the E2A gene (E12 and E47) and FOXP1 (Figure 1) were found in pDC,
and PU.1 was very weakly expressed in a minority of these cells. In contrast, eleven
other transcription factors (eg BCL-6, BOB.1 and PAX-5 - see Table 4), all but three
of which are associated with the B cell lineage, were absent (Figure 1). The
expression of leucocyte-associated molecules involved in intracellular signaling was
also explored and this revealed the presence of five B cell-associated molecules (the
adaptor protein BLNK, the kinases BTK, Lyn and Syk, and the PLC
γ
2 phospholipase)
and also the transmembrane adaptor protein LIME (which is found in T cells and
plasma cells) (Figure 2, Table 3). However, other T cell-associated signaling
molecules (eg TRIM, SLP76) were absent (Figure 2, Table 4). In addition, three
signaling molecules that have not been studied previously in human tissues by
immunocytochemistry were detected in pDC, namely DAP12, IRAK1 and TCB1D4
(Figure 2, Table 3). Furthermore, the Toll-like receptors TLR7 and TLR9 were clearly
present in human pDC (Figure 3, Table 3), in keeping with data from studies of
murine cells.
21,22
Two other cell types present in interfollicular areas in human tonsil, namely
classical interdigitating dendritic cells (expressing DC-SIGN) and presumptive
immature lymphoid cells (expressing TdT), were investigated by double labeling
(immunofluorescence for DC-SIGN and immunoenzymatic for TdT) in combination
with CD2AP (Figure 3). There was no overlap in expression of these markers,
providing further evidence that CD2AP is confined to pDC.
pDC have been extensively evaluated in the past for classical surface/"CD"
molecules associated with lymphoid and myeloid lineages and they are known to
express only a small number, eg CD4, CD68. Such lineage markers were therefore
not explored in detail in this study but we confirmed the expression of CD4 and CD68
in CD2AP-positive cells and also noted that CD79b (but not its partner CD79a) was
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weakly expressed. Furthermore, we studied CD123 (a well recognized marker of
pDC) in relation to the transcription factor BCL11A by double labeling and showed
the latter molecule in all CD123-positive cells (Figure 3) further confirming its
selectivity for pDC. CD33, which has been reported in some pDC-derived
neoplasms,
23,24
was also studied and it was found on occasional pDC (as defined by
expression of BCL11A).
pDC in biopsies from reactive conditions
The pDC that are known to accumulate in non-neoplastic conditions (Kikuchi's
lymphadenitis,
25,26
Castleman’s disease,
27,28
lupus erythematosus
29,30
and lichen
planus
31
) were all sharply delineated (mainly in the form of nodular aggregates but
also as scattered cells) by immunostaining for CD2AP (Figure 3). In biopsies of
cutaneous lupus lesions the pDC appeared identical to those seen in the tonsil,
whereas some of the pDC in Kikuchi's disease were a little larger, with more
voluminous cytoplasm. The phenotypic profile of pDC in the latter disease was
investigated with the full panel of markers to see if it differed from that of tonsillar
pDC, but no differences were observed (Figure 3). It was also noted that CD2AP-
positive cells in Kikuchi’s lymphadenitis were myeloperoxidase-negative (observed
by using double immunofluorescence), showing they were not immature monocytes
(usually present in this disease and positive for myeloperoxidase).
pDC in blood and bone marrow
Cytospin preparations of normal peripheral blood mononuclear cells contained rare
CD2AP-positive cells, accounting for less than 0.5% of all cells (in two healthy
donors) (Figure 4). Their morphology was relatively constant, ie medium-sized cells,
often with slightly eccentrically placed nuclei some of which were indented. These
CD2AP-positive cells all co-expressed the pDC-associated transcription factor
BCL11A and they lacked CD3 and CD20 (Figure 4). Furthermore, pDC isolated from
peripheral blood using anti-BDCA-4 all showed strong staining for CD2AP (Figure 4)
and CD123. BDCA-4 is a well-accepted marker for purification of pDC,
32,33
and it was
used previously by two authors of this paper (FF and SS) to purify pDC, achieving a
purity of 90-98%.
34
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Bone marrow trephine biopsies also contained scattered CD2AP-positive cells,
very similar in morphology to those seen in peripheral lymphoid tissue, and all co-
expressed the transcription factor BCL11A (Figure 4).
pDC neoplasms
A total of 47 pDC-derived neoplasms (detailed in Table 1) were investigated for the
expression of the pDC-associated molecules listed in Table 3 (with the exception of
IRF7, LIME and PLCγ2). However, because of the limited material available, it was
not possible to test each case with all markers. In addition, biopsies from cases of
acute myeloid leukemia in the skin ("leukemia cutis") were studied, since these can
cause diagnostic confusion, together with samples of chronic myeloproliferative
disorders and acute lymphoblastic leukemia (see Table 5).
Most of the pDC markers we evaluated were expressed on the great majority of
cases of pDC neoplasia (Figure 5, Table 5). One of the 16 pDC-associated
molecules, CD2AP, appeared to have particular potential diagnostic value since it
was present in neoplastic pDC in the great majority of cases (41/43), but absent in all
but one of the 24 "leukemia cutis" cases analyzed (and in all other myeloid
neoplasms studied). The B cell-associated transcription factors BCL11A and
ICSBP/IRF8 were also commonly found in neoplastic pDC (42/44 and 34/36 cases
respectively), but they were also found in a minority of cases of "leukemia cutis" (six
and five out of 24 cases respectively). Many of the other pDC-associated molecules
studied (eg BTK, DAP12, Lyn) were found in all cases of pDC neoplasia, but were
also expressed in the majority of “leukemia cutis” samples. Furthermore, markers
expressed in normal B cells (eg BLNK, BTK, Lyn) were commonly found in B cell
acute lymphoblastic leukemia (Table 5).
Discussion
Plasmacytoid dendritic cells were first identified fifty years ago by Lennert and his
associates in human lymph nodes as a population of cells with morphologic features
of plasma cells lying in interfollicular T cell-rich areas.
35
It was subsequently shown
that they express CD36 and CD68, suggesting a monocyte/macrophage origin and
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they came to be known by many authors as "plasmacytoid monocytes".
36
This was
supported by reports that neoplastic proliferations involving these cells (eg in lymph
node, spleen, bone marrow) are always associated with a myeloproliferative disorder
(principally acute or chronic myelomonocytic or monocytic leukemia).
37-41
This
suggested that both proliferative processes share a common origin, and this has
been supported more recently by reports of identical cytogenetic abnormalities in the
two cell populations in cases of myelodysplasia,
42,43
and in a case of acute myeloid
leukemia.
44
"Plasmacytoid monocytes/T cells" were studied by many pathologists in the
following years, and prominent clusters of these cells were recognized as a feature of
Kikuchi's disease,
25,26
and the hyaline vascular subtype of Castleman's disease.
27,28
However, they received relatively little attention until it was shown that they secrete
large amounts of type I interferons (principally interferon-
α
),
1,45
a function that
accounts for their extensive rough endoplasmic reticulum.
29
It was also reported that
similar cells could be generated in vitro from mononuclear or CD34-positive cells in
the peripheral blood and that activation by factors such as IL3 or CD40L generates
cells of dendritic morphology with antigen-presenting capability.
4,46,47
For this reason
they have come to be widely known as "plasmacytoid dendritic cells".
3,4
At the same
time a murine counterpart was identified with similar properties,
48-51
and many
published studies are based on pDC from this species.
It has been reported in recent years that pDC can give rise to a second tumor
type that appears distinct from the rare neoplasms associated with myeloproliferative
disorders referred to above.
23,52-58
This tumor entity was initially believed to arise from
natural killer (NK) cells (because of its expression of CD56
59-61
and categorized as
“blastic NK cell lymphoma” in the WHO classification, but it was subsequently re-
named "CD4+/CD56+ hematodermic neoplasm" in the WHO/EORTC classification
scheme for cutaneous lymphomas.
10,62
These tumors have many phenotypic features
of pDC,
54,63,64
and are characterized by skin lesions, frequent involvement of other
tissues (marrow, spleen and/or lymph nodes), either initially or later in the course of
the disease, and circulating neoplastic cells. The disease often responds initially to
therapy but overall it has a poor prognosis.
23,55-57,61,63-67
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In leukemic cases, the diagnosis is made principally by flow cytometry.
66,68
However, cases are commonly first diagnosed in a skin biopsy, requiring markers
that can be detected in paraffin-embedded tissue.
63
The first markers to be used
(CD4, CD56, HLA-DR, CD123 and CD45RA
54,63
) have more recently been
supplemented by TCL1 and CLA (HECA-452),
10-12,57
but all these markers are also
present on neoplasms of non-pDC origin. A type II C-type lectin BDCA-2 has also
been reported as a specific marker of pDC,
69
and evaluated on pDC tumors.
64,70-72
However, there is little information on its expression in non-pDC neoplasms and it is
only expressed in a proportion of pDC tumors. Siglec-H has also been reported as a
surface constituent on pDC,
73,74
but not exploited as a diagnostic marker.
In this paper we report a number of new immunohistologic markers that can be
used to detect normal and neoplastic pDC in human tissue samples. The adaptor
protein CD2AP (CD2-associated protein) is of particular interest because it was
essentially restricted to pDC. CD2AP is a 80 kDa molecule first identified through its
binding to the terminal 20 amino acids in the cytoplasmic domain of the T cell-
associated molecule CD2.
18,19
CD2AP has also been shown to play a role in
podocyte homeostasis in the kidney (CD2AP-deficient mice develop nephrotic
syndrome and glomerulosclerosis
75,76
). CD2AP is described in the literature as a
component of normal T cells (and we expected to see expression in these cells when
assessing its immunohistologic reactivity in peripheral lymphoid tissues). However,
the only staining observed in T cells was in cortical thymocytes (data not shown) and
three different antibodies (all of which react with cells transfected with the CD2AP
gene - manuscript in preparation) gave identical immunohistologic labeling.
Furthermore, we confirmed by double staining for BCL11A and CD2 (data not shown)
reports from the literature that CD2 (the partner for CD2AP) is not detectable in pDC
in tissue sections
2
(although it has been reported in a minority of cases of pDC
neoplasia).
2,53,57,63,64,66,77
In consequence, CD2AP may associate with a hitherto
unidentified partner other than CD2 in normal pDC. It may be added that, while
CD2AP expression has been documented in mouse T cells, its expression pattern in
human T cells is unclear having only been demonstrated to be expressed in the T
cell leukemia cell line,
Jurkat cells.
18,19,78,79
It is therefore possible that there are
species-specific differences in the pattern of CD2AP expression. It may be added
that Northern blotting studies have suggested that CD2AP is widely expressed in
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human tissues (with the exception of brain),
18,80
but Dustin et al 1998 reported a
more restricted range of protein expression (assessed by Western blotting).
80
Whatever the explanation of the unexpected absence of immunostaining for CD2AP
in peripheral T cells in human tissue samples, it clearly emerged in this empirical
study as a selective and reproducible marker of pDC.
Nine other signaling molecules were also shown for the first time in this study to
be detectable at the protein level in normal and neoplastic human pDC (see Table 3).
Some had been implicated previously at least as possible components of pDC,
usually in murine studies, ie BLNK, Btk, DAP12 (DNAX-activation protein 12, known
also as KARAP), IRAK1 and Syk. However, others have not been associated with
this cell type, eg the GTPase-activating protein TBC1D4 (also known as AS160).
Also the strong expression of TLR7 and TLR9 we found in human pDC (Figure 3) is
in keeping with reports of their transcripts in human and murine pDC.
22,81
82
There is evidence that pDC can arise from both lymphoid and myeloid
precursors,
83-88
and it has also been reported that they show features associated with
several lineages, ie T cells, B cells and myeloid cells.
58,77,85,89,90
Furthermore, the
lymphoid precursor-associated marker TdT is expressed at the mRNA level in murine
pDC and as protein in neoplastic human pDC.
8,56,63,65,91-93
In consequence, the
cellular origin of pDC has been the subject of controversy, to which the present study
might be expected to bring some new insight. It was striking that many markers
detected in normal and neoplastic pDC are expressed in B lymphoid cells (see Table
3), including four transcription factors (BCL11A, the products of the E2A gene,
ICSBP/IRF8 and PU.1) and five signaling molecules (BLNK, BTK, Lyn, PLCγ2 and
Syk). In addition, LIME and TBC1D4 are found in B cells at the plasma cell
94
and
germinal center maturation stage respectively (Figure 2). This suggestion that pDC
are related to B cells is in keeping with reports that signaling initiated from BDCA-2
(CD303) resembles the effect of B cell receptor ligation (eg both involve Syk and
BLNK phosphorylation).
95,96
Interestingly, the consequence of this stimulation is to
inhibit rather than to stimulate IFN production.
69,97,98
However, five classical B cell-
associated transcription factors we studied (eg OCT2, PAX5) were not expressed by
pDC (Table 4). Furthermore, three other B cell-associated molecules we identified
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(Lyn, PU.1 and Syk) are also found in myeloid cells, and another novel marker,
DAP12, is expressed in macrophages but not in B cells (Figure 2, Table 3).
Thus, the phenotypic studies in this paper shed only limited light on the
controversial question of the cellular origin of pDC. We also found no evidence to
support the report by Pelayo et al
8
that different populations of plasmacytoid dendritic
cells ("pDC1" and "pDC2") can be distinguished on the basis of phenotypic
differences. They reported that BCL11A, ICSBP/IRF8, PAX5 are all positive in pDC1
and negative in pDC2, but in the present study we found that these markers (and
indeed other markers evaluated) were either present (BCL11A, ICSBP/IRF8) or
absent (PAX5, mb1/CD79a) in all pDC. The homogeneity of pDC marker expression
in the present paper therefore argues against the existence of subsets of human
pDC1 comparable to those reported by Pelayo et al in mice. It has also been
suggested that the expression of cell markers (eg BDCA-4 and CD7) changes during
pDC maturation, and that the clinical behaviour of pDC-derived tumors is related to
the maturation stage from which they arise.
71
However, the markers documented in
the present study did not show variability suggestive of major phenotypic alteration
during differentiation.
The other controversial topic concerns the degree to which circulating pDC
become cells with classical dendritic morphology, possessing the ability to present
antigen, when they enter peripheral lymphoid tissue. This is a widely held belief, and
accounts for the use of the term "dendritic" and for the fact that on occasion
circulating pDC are referred to as "precursors", implying that their morphology
changes when they emigrate into tissues. In the present study the morphology of
cells in peripheral lymphoid tissue carrying pDC markers appeared very similar to
that of the cells seen in the bone marrow and in the circulation. Furthermore,
although some of the numerous pDC present in Kikuchi’s disease showed slightly
more voluminous cytoplasm for the most part they lacked dendritic surface processes
(Figure 3) and we detected no acquired novel phenotypic features. It is therefore
possible that the ability of pDC to transform into cells with the morphology and
function of classical dendritic cells is an in vitro phenomenon rather than a common
physiologic event in vivo.
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A major aim of the present paper was to identify new markers present on
neoplastic pDC. We therefore analyzed a total of 43 cases of hematodermic
neoplasia and also six cases of pDC proliferation associated with a myeloproliferative
disorder (Tables 1 and 5). The phenotype of these two types of pDC neoplasia
matched published data, including the fact that in the latter disorder TdT was not
expressed and CD56 and TCL1 were less commonly expressed than in
hematodermic neoplasia (Table 1). A significant diagnostic problem is posed by
cutaneous deposits of diseases such myeloid leukemia (“leukemia cutis”) since these
are morphologically similar to hematodermic neoplasms and some express CD4 and
CD56. We therefore evaluated the most selective pDC markers on 24 cases of this
sort.
This analysis showed that many of the markers we documented on normal pDC
were expressed on their neoplastic equivalents. Most of these markers were also
expressed on neoplasms of B cell and/or myeloid lineage. However only a minority of
leukemia cutis samples (the neoplasms most likely to be confused with the
CD4+CD56+ hematodermic neoplasm) expressed BCL11A and BLNK, while CD2AP
and ICSBP/IRF8 were even less commonly expressed (Table 5), indicating their
potential value for the diagnosis of hematodermic neoplasms. It should be added that
the frequency of CD2AP and ICSBP/IRF8 expression on myeloid neoplasms was
comparable to, or lower than, that of the two recently proposed diagnostic markers
TCL1 and HECA452/CLA.
11,12,57
The number of cases associated with a myeloproliferative disorder was small
but it may be of significance that some cases in this category lacked the transcription
factors BCL11A (2/5), E47 (1/3) and ICSBP (2/3), whereas these molecules were
present without exception in cases of hematodermic neoplasia. Conversely, PU.1 (a
transcription factor found not only in B cells but also in macrophages) was present in
each of three cases associated with a myeloproliferative disorders but absent in
11/16 hematodermic tumors.
In conclusion, we have documented a range of phenotypic markers of normal
and neoplastic human pDC in tissues and peripheral blood. Our observations do not
resolve the controversy surrounding the cellular origin of these cells (beyond
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reinforcing reports that they share many molecular features with B cells), but they
present a picture of the plasmacytoid dendritic cell as a cell that changes little in
morphology or phenotype between the bone marrow and peripheral tissue, even
when it accumulates in large numbers in diseases such as Kikuchi’s lymphadenitis,
or following neoplastic transformation. These new markers include molecules (in
particular the adaptor protein CD2AP and the transcription factor ICSBP/IRF8) that
may be of value for the diagnosis of pDC tumors.
Acknowledgments
The authors thank Mr. Ralf Lieberz for his technical assistance, and Mrs. Bridget
Watson for her expertise in the preparation of the manuscript. This work was
supported by Project Grant (No. 0382) and Programme Grant (No. 04061) from the
Leukaemia Research Fund and by the Julian Starmer-Smith Lymphoma Fund. The
authors thank all the members of the French Study Group on Cutaneous Lymphomas
for their collaboration.
Conflict of interest disclosure
The authors confirm that there is no conflict of interest and that there are no
competing financial interests.
Author contribution statement
T.M. designed the project, analyzed and interpreted the data, and wrote the paper.
J.C.P., E.B. and S.T. were responsible for cell and tissue preparations as well as
performing all the immunohistologic experiments. K.K.R., K.H., M.D., M-L.H., S.A.P.
and T.P. provided tissue samples. M.J.D., I.D. and A.S.S. provided novel reagents.
S.S. performed part of the experiments. H.S. and P.G.I. provided tissue samples and
also reviewed the results. F.F. provided tissue samples, reviewed the results and
contributed to writing the paper. D.Y.M. contributed to the design of the study,
interpreted the data and wrote the paper.
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Table 1. Clinical and phenotypic data in 47 cases of pDC neoplasms
CD4+CD56+ Hematodermic neoplasm
Case
No.
Age/Sex Site of
involvement
CD4 CD45RA CD43 CD56 CD123 TCL1 TdT
1 77/F Skin + + + + Scat’rd+ nd Scat’rd+
2 73/F Skin + nd nd - nd nd +
3 61/M Skin and
bone marrow
+ + + + (30%) + + -
4 67/M Skin + nd + + + + -
5 60/M Skin + + + + + + +
6 80/M Bone
marrow
+ + + + + + --
7 51/M Bone
marrow
+ + + + + nd --
8 75/M Skin + + + + -- + --
9 78/F Spleen + + + + + + --
10 80/M Skin + + + -- + + --
11 78/M Bone
marrow
+ + + + + + --
12 45/F n.a. + + + + + + --
13 58/M Bone
marrow
+ + + + + + --
14 71/M
Skin + + + + + + +
15 72/M Skin + + + + + nd --
16 30/M Skin + + + +/- + + -/+
17 n.a. n.a. + + + +/- + + +/-
18 31/M Skin + + + + + + -/+
19 57 M Skin, lymph
node and
bone marrow
+ nd + + nd nd +
20 68 F Skin + nd + + nd nd +
21 12 F Skin + nd + + nd nd +
22 25/F Skin + nd + + + + nd
23 77/M Skin +
+
+ + + + -
24 35/F Skin + nd + + + + -
25 80/M Skin + nd
nd
+ nd
nd
nd
26 96/F Skin + nd +
+
+ + + (30%)
27 73/M Skin + nd + + + + -
28 76/M Skin + nd + + + + + (50%)
29 54/F Skin + nd - + + + + (80%)
30 71/M Skin + nd + + + + -
31 63/M Skin + nd nd + + + + (10%)
32 8/M Skin + + + + + + -
33 64/M Lymph node + nd + + nd + +
34 84/M Skin + + + + + + -
35 60/F Skin + nd nd + nd nd nd
36 83/M Skin + nd nd + + + -
37 75/M Skin + nd + + + + -
38 25/M Skin + nd nd + + + -
39 70/F Skin + nd + + nd + -
40 88/F Skin + + + + + + + (10%)
41 72/M Skin + + + + + + -
PDC proliferations associated with a myeloproliferative disorder
42 52/M Lymph node + + + (+) + + -
43 63/F Lymph node + + + (+) + (+) -
44 24/M Lymph node
and skin
+ + + - + (+) -
45 62/F Lymph node + + + - + (+) -
46 65/M Lymph node + nd + (+) + + -
47 71/M Bone
marrow
+ + + - + nd -
+ : All tumor cells are positive; (+) : Almost all tumor cells are weakly positive; +/- : Most of the tumor cells are positive; Scat’rd+ :
Scattered tumor cells are positive; -/+ : Most of the tumor cells are negative; – : All tumor cells are negative; nd : Not done;
n.a. : Data not available
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Table 2
. Antibodies used in present study
Molecule Antibody type
Clone name/
product ref.
Source
BCL11A
17
Mouse monoclonal BCL11A/123c
LRF Monoclonal Antibody Facility, John Radcliffe
Hospital, Oxford, UK.
BCL-6
99
Mouse monoclonal GI191E/A8 Dr Giovanna Roncador, CNIO, Madrid, Spain.
BLIMP-1
100
Mouse monoclonal ROS Dr Giovanna Roncador, CNIO, Madrid, Spain.
BLNK Mouse monoclonal 2B11 Santa Cruz Biotechnology, Santa Cruz, CA.
BTK Rabbit polyclonal Contact the corresponding author for details.
BOB.1
(OCAB-1)
a) Mouse monoclonal
b) Rabbit polyclonal
a) TG14 a) Leica Biosystems, Newcastle upon Tyne, UK.
b) Santa Cruz Biotechnology, Santa Cruz, CA.
CD2 Mouse monoclonal AB75 Leica Biosystems, Newcastle upon Tyne, UK.
CD2AP a) Mouse monoclonal
b) Rabbit polyclonal
Contact the corresponding author for details.
CD3 a) Mouse monoclonal
b) Mouse monoclonal
c) Rabbit polyclonal
a) LN10
b) F7.2.38
a) Leica Biosystems, Newcastle upon Tyne, UK.
b) and c) DAKO, Glostrup, Denmark.
CD4 Mouse monoclonal 4B12 Leica Biosystems, Newcastle upon Tyne, UK.
CD19 Rabbit polyclonal 3574 Cell Signaling Technology, Danvers, MA.
CD20 Mouse monoclonal L26 DAKO, Glostrup, Denmark.
CD25 Mouse monoclonal AC9 Leica Biosystems, Newcastle upon Tyne, UK.
CD33 Mouse monoclonal PWS44 Leica Biosystems, Newcastle upon Tyne, UK.
CD34 Mouse monoclonal QBEND-10 DAKO, Glostrup, Denmark.
CD56 Mouse monoclonal BC56C04 Biocare Medical, Concord, CA.
CD79a
101,102
Mouse monoclonal JCB117,
HM57
LRF Immunodiagnostics Unit, John Radcliffe Hospital,
Oxford, UK.
CD79b
103
Mouse monoclonal B29/123
LRF Immunodiagnostics Unit, John Radcliffe Hospital,
Oxford, UK.
CD123 Mouse monoclonal 7G3 BD Biosciences Pharmingen, San Jose, CA.
DAP12 Goat polyclonal Contact the corresponding author for details.
DC-SIGN Mouse monoclonal DC28 R&D Systems, Abingdon, Oxford, UK.
E2A gene
products
(E12/E47)
a) Mouse monoclonal
(E47)
b) Mouse monoclonal
(E12/47)
a) G127-32
b) G98-271
BD Biosciences Pharmingen, San Jose, CA.
ETS.1 Mouse monoclonal 1G11 Leica Biosystems, Newcastle upon Tyne, UK.
FOXP1
104
Mouse monoclonal JC12 AbD Serotec, Kidlington, Oxford, UK.
FOXP3
105
a) Mouse monoclonal
b) Goat polyclonal
a) 236A/E7
b) EB5294
a) Dr Giovanna Roncador, CNIO, Madrid, Spain.
b) Everest Biotech Ltd, Upper Heyford, UK.
GATA-3 a) Mouse monoclonal
b) Mouse monoclonal
a) HG3-31
b) HG3-35
Santa Cruz Biotechnology, Santa Cruz, CA.
Glycophorin A
Mouse monoclonal JC159 DAKO, Glostrup, Denmark.
Glycophorin C Mouse monoclonal Ret40F DAKO, Glostrup, Denmark.
IRAK1 Mouse monoclonal F-4 Santa Cruz Biotechnology, Santa Cruz, CA.
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IRF4/MUM-1
106
Mouse monoclonal MUM1p Prof. Brunangelo Falini, Perugia, Italy.
IRF5 Mouse monoclonal Contact the corresponding author for details.
IRF7 Rabbit polyclonal Contact the corresponding author for details.
IRF8/ICSBP Rabbit polyclonal Contact the corresponding author for details.
LAT
94
Mouse monoclonal LAT01 Prof. Vaclav Horejsí, Prague, Czech Republic.
LIME
94
Mouse monoclonal LIME10 Prof. Vaclav Horejsí, Prague, Czech Republic.
Lyn Mouse monoclonal H-6 Santa Cruz Biotechnology, Santa Cruz, CA.
Myelo-
peroxidase
Rabbit polyclonal A0398 DAKO, Glostrup, Denmark.
NFATc1 Mouse monoclonal 7A6 Santa Cruz Biotechnology, Santa Cruz, CA.
OCT-2 Mouse monoclonal Oct-207 Leica Biosystems, Newcastle upon Tyne, UK.
PAX-5
(BSAP)
a) Mouse monoclonal
b) Mouse monoclonal
a) 24
b) 1EW
a) BD Biosciences, San Jose, CA, USA.
b) Leica Biosystems, Newcastle upon Tyne, UK.
PLC 1 Rabbit polyclonal sc-81 Santa Cruz Biotechnology, Santa Cruz, CA.
PLC 2 Mouse monoclonal B-10 Santa Cruz Biotechnology, Santa Cruz, CA.
PU.1 (Spi.1) Mouse monoclonal G148-74 BD Biosciences, Franklin Lakes, NJ, USA.
SLP-76 Rabbit polyclonal sc-9062 Santa Cruz Biotechnology, Santa Cruz, CA..
Syk Rabbit polyclonal sc-1077 Santa Cruz Biotechnology, Santa Cruz, CA.
TBC1D4/AS1
60
Rabbit polyclonal Contact the corresponding author for details.
T-bet Mouse monoclonal 4B10 Santa Cruz Biotechnology, Santa Cruz, CA.
TdT Mouse monoclonal SEN28 Leica Biosystems, Newcastle upon Tyne, UK.
TLR-7 a) Mouse monoclonal
b) Rabbit polyclonal
Contact the corresponding author for details.
TLR-9 a) Mouse monoclonal
b) Rabbit polyclonal
Contact the corresponding author for details.
TRIM
94
Mouse monoclonal TRIM10 Prof. Vaclav Horejsí, Prague, Czech Republic.
Zap-70 Mouse monoclonal 2F3.2 Millipore, Watford, UK.
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Table 3. Novel markers of plasmacytoid dendritic cells
Molecule Nature Labeling in
plasmacytoid
dendritic cells
Expression in
other white
cell types
Comments
Transcription regulators
BCL11A Zinc finger
protein
Nuclear
(stronger than
B cells)
B cells. Detected previously at the RNA and
protein level in murine and human
pDC
8,17
and shown to be overexpressed
by gene expression profiling in human
pDC neoplasms.
107
E47/E12
(E2A
gene
products)
Basic helix-
loop-helix
(bHLH)
protein
Nuclear Most B cells. E47 expression detected at the mRNA
level in murine pDC.
8
Not previously
studied as an immunocytochemical
marker of human pDC.
FOXP1 Forkhead
protein
Nuclear Mantle zone B
cells. Minority
of germinal
center B cells.
Plays a role in transcriptional regulation
of B cell development.
108
Not previously
studied in the context of human pDC.
ICSBP
(IRF8)
Interferon
regulatory
factor
Nuclear Most B cells.
Macrophages.
Detected at the RNA level in murine
pDC.
8,85
ICSBP-deficient mice display
loss of PDCs which can be restored by
enforced ICSBP expression.
109-111
Shown to be overexpressed by gene
expression profiling in human pDC
neoplasms.
107
Not previously studied as
an immunocytochemical marker of
human pDC.
IRF7 Interferon
regulatory
factor
Cytoplasmic Absent. Detected in human pDC at RNA and
protein level (flow cytometry).
112-114
Plays an essential role in mice in
induction of type 1 IFN production upon
virus infection.
115
Stimulation of human
pDC with CpG DNA induces activation
of NF-κB and p38 MAPK via TLR9
signaling and leads to the de novo
expression of IRF7.
116
PU.1
(Spi.1)
Member of
the ETS
family
Weak nuclear
staining in
minority of
cells
Most B cells.
Macrophages.
Detected at mRNA level in murine pDC.
8
The closely related factor Spi.B is
detectable at mRNA level in human and
murine pDC and is required for murine
pDC development.
8,117
Not previously
studied as an immunocytochemical
marker of human pDC.
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Signaling molecules
BLNK
(SLP65)
Adapter
protein
Cytoplasmic Most B cells. Phosphorylated in the course of
signaling initiated by CD303 (BDCA-2).
96
Not previously studied in the context of
normal pDC but shown to be
overexpressed by gene expression
profiling in human pDC neoplasms.
107
Btk Kinase Cytoplasmic Most B cells. Has a negative regulatory effect on
murine dendritic cells.
118
BTK-deficient
dendritic cells in humans show an
impaired response to TLR8 signaling.
119
Normal numbers of pDC reported in
children lacking the BTK gene.
120
Not
previously studied as an
immunocytochemical marker in human
pDC.
CD2AP
(CMS)
Adaptor
protein
Cytoplasmic Mantle zone B
cells in some
samples (very
weak).
Not previously studied in the context of
pDC.
DAP12
(KARAP)
Adaptor
protein
Cytoplasmic Germinal
center
macrophages,
scattered cells
in interfollicular
areas.
Involved in signaling in pDC initiated via
TLR9 and Siglec-H.
121-123
Not previously
studied as an immunocytochemical
marker in human pDC.
IRAK1 Kinase Membrane
and
cytoplasmic
Scattered cells
in germinal
center and
interfollicular
areas.
Probable
plasma cells.
Involved in signaling induced by
interleukin-1, Toll-like receptors and
tumor necrosis factor receptor (TNFR)
superfamily molecules linking to the
IRF7 transcription factor.
124
Not
previously studied as an
immunocytochemical marker in human
pDC.
LIME Trans-
membrane
adaptor
molecule
Cytoplasmic Most T cells.
Plasma cells.
94
Not previously studied in the context of
pDC.
Lyn Kinase Cytoplasmic Most B cells.
Myeloid
cells.
125
Plays a role in the generation and
maturation of murine dendritic cells
(pDC not specifically studied).
126
Not
previously studied as an
immunocytochemical marker in human
pDC.
PLC
γ
2
Phospho-
lipase
Weak
cytoplasmic
staining
(compared to
B cells)
Most B
cells.
125
Not previously studied as an
immunocytochemical marker in human
pDC.
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Toll-like receptors
TLR7 and
TLR9
Endosome-
associated
Cytoplasmic Some cells in
germinal
centers, in
interfollicular
areas and in
plasma cells.
These intracellular receptors have been
extensively studied as initiators of
signaling in murine pDC.
21,81,131,132
Highly expressed in human pDC.
133
Viral
binding may initially be mediated by
antibodies recognized by Fc receptors
before sensing by TLR7.
134
Detected at
the mRNA level in murine pDC.
8
Not
previously studied as
immunocytochemical markers in human
pDC.
Cell surface molecules
CD79b Associated
with
surface Ig
Cytoplasmic
(weak)
Most B cells,
but mantle
zone cells
stronger than
germinal
center cells.
Detected at the mRNA level in murine
pDC.
8
Not previously studied in the
context of human pDC.
Syk Kinase Cytoplasmic Most B cells.
Myeloid
cells.
125
Cross linking of ILT7/Fc
ε
RI complexes
or CD303 (BDCA-2) on pDC causes
phosphorylation of Syk.
95,96,127
Not
previously studied as an
immunocytochemical marker in human
pDC.
TBC1D4/
AS160
GTPase-
activating
protein
Cytoplasmic
Many cells in
germinal
centers
Key regulator of intracellular vescicular
trafficking.
128
Involved in insulin induced
signaling and phosphorylated by Akt
kinase.
129
High mRNA levels reported in
T cells of patients with atopic
dermatitis.
130
Not previously studied as
an immunocytochemical marker of
human pDC.
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Table 4. Transcription factors and signaling molecules not detected in pDC
Molecule Normal expression
Transcription factors
BCL6 Germinal center B cells
BLIMP1 Terminally differentiated B cells
BOB1 B cells
Ets.1 Majority of white cells
FOXP3 Regulatory T cells
GATA3 T cells
IRF5 Subpopulation of B cells
MUM1 Plasma cells
OCT2 B cells
PAX5 B cells
T-BET T cells
Signaling molecules
LAT T cells. Megakaryocytes
NFATc1 Most white cells
PLC
γ
1
T cells
SLP76 T cells. Macrophages
TRIM T cells
Zap70 T cells
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Table 5. Expression of pDC-associated molecules in pDC neoplasms and in myeloid and
lymphoid leukemias.
Transcription factors
pDC
neoplasms
Hemato-
dermic
Myelopro-
liferative
associated
Leukemia
cutis
CML CMML B-ALL T-ALL
BCL11A 39/39
(100%)
3/5
(60%)
6
i
/24
(25%)
1/7
(14%)
3/5
(60%)
7
w
/7
(100%)
4/5
(80%)
E47 16
a
/16
(100%)
2
h
/3
(67%)
20
j
/24
(83%)
5/6
(83%)
5/5
(100%)
7/7
(100%)
6/6
(100%)
FOXP1 6/6
(100%)
2/2
(100%)
7/7
(100%)
1/5
(20%)
1/4
(25%)
n.d. n.d.
ICSBP/IRF8 33
b
/33
(100%)
1/3
(33%)
5
k
/24
l
(21%)
0/5
(0%)
0/5
(0%)
0/6
(0%)
0/6
(0%)
PU.1 5
c
/16
(31%)
3/3
(100%)
19
m
/24
(79%)
5/5
(100%)
5/5
(100%)
2/7
(28%)
0/6
(0%)
Signaling molecules
BLNK 21/21
(100%)
4/4
(100%)
8
n
/24
o
(33%)
0/6
(0%)
0/5
(0%)
7/7
(100%)
1/6
(17%)
BTK 16/16
(100%)
3/3
(100%)
24/24
(100%)
1/6
(17%)
2/4
(50%)
7/7
(100%)
0/6
(0%)
CD2AP 35/37
(95%)
6/6
(100%)
1/24
(4%)
0/7
(0%)
0/5
(0%)
0/7
(0%)
0/5
x
(0%)
DAP12 13/13
(100%)
2/2
(100%)
20/22
p
(91%)
5/5
(100%)
3/4
(75%)
0/7
(0%)
0/5
(0%)
IRAK1 6
d
/6
(100%)
1/1
(100%)
6
q
/7
(86%)
1/5
t
(20%)
3
u
/4
(75%)
n.d. n.d.
Lyn 16/16
(100%)
2/2
(100%)
23
r
/24
(96%)
5/5
(100%)
2/5
v
(40%)
6/7
(86%)
0/6
(0%)
Syk 16
e
/16
(100%)
1/1
(100%)
24/24
(100%)
5/5
(100%)
5/5
(100%)
7/7
(100%)
3/6
(50%)
TCB1D4 2/4
(50%)
1/1
(100%)
3/7
(43%)
0/5
(0%)
0/4
(0%)
n.d. n.d.
Receptor molecules
CD79b 9
f
/15
(60%)
0/2
(0%)
3/24
(12.5%)
0/5
(0%)
0/5
(0%)
6/7
(86%)
1/6
(17%)
TLR7 16/16
(100%)
3/3
(100%)
22/24
(92%)
1/6
(17%)
0/4
(0%)
2/7
(28%)
0/6
(0%)
TLR9 10
g
/14
(71%)
1/2
(50%)
24
s
/24
(100%)
0/5
(0%)
4/4
(100%)
0/7
(0%)
2/5
(40%)
Cases are scored as positive if at least 90% of neoplastic cells were stained. In the footnotes below
“weak and/or weakly positive” indicates a low level of staining by all neoplastic cells.
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a
4 out of 16 were weakly positive;
b
2 out of 33 were weakly positive;
c
1 out of 5 was very weak positive;
d
2 out of 6 were weakly positive;
e
2 out of 16 were weakly positive;
f
3 out of 9 were weakly positive;
g
2
out of 10 were very weakly positive;
h
1 out of 2 was weak positive;
i
3 out of 6 were weakly positive;
j
6
out of 20 were weakly positive;
k
2 out of 5 were weakly positive;
l
In 3 out of 24 cases (scored as
negative) a small proportion of atypical cells were positive;
m
1 out of 19 was weak positive;
n
3 out of 8
were very weakly positive;
o
In 2 out of 24 cases (scored as negative) a small proportion of atypical cells
were positive;
p
In 2 out of 22 cases (scored as negative) a small proportion of tumor cells were positive;
q
2 out of 6 cases were weakly positive;
r
1 out of 23 was weak positive;
s
3 out of 24 were weakly
positive;
t
In 1
out of 5 cases (scored as negative) a small proportion of cells was weak positive;
u
All 3
cases were weak positive;
v
In 3 out of 5 cases (scored as negative) 5% to 20% of cells were positive;
w
1 out of 7 was very weak positive;
x
1 out of 5 cases showed focal and weak positivity.
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25
Figure legends
Figure 1:
Immunostaining of pDC in human tonsil. Top row: Left: Clusters of pDC (arrowed and
at higher magnification in the inset) lying close to vessels outside a lymphoid follicle
(Foll.) in the T cell-rich region are strongly stained for the adaptor protein CD2AP.
(Immunoperoxidase technique, hematoxylin counterstain). Right: Double
immunoenzymatic labeling for CD2AP (brown) and the B cell-associated transcription
factor BCL11A (blue) confirms that both molecules are present in the same cells. (No
counterstain). Middle row: Co-expression of three B cell-associated transcription
factors, namely ICSBP (brown), E47 (red) and FOXP1 (brown), in pDC expressing
CD2AP (blue or brown). Note that FOXP1 is also expressed in B cells and in
endothelial cells in a vessel (Vess.). (Double immunoenzymatic staining, hematoxylin
counterstain for E47+CD2AP staining). Third row: The B cell-associated transcription
factors BCL6 (brown) and PAX5 (blue) are expressed in B cell follicles (Foll.), but are
absent from extrafollicular pDC (identified by immunostaining for the cytoplasmic
marker CD2AP in blue or brown). Scattered BCL6- and PAX5-positive B cell nuclei
among the pDC are arrowed. (No counterstain). (Images were acquired on a Nikon
Eclipse E800 microscope [Nikon, Tokyo, Japan] equipped with 10x/0.45 Plan Apo or
20x/0.7, 40x/0.95 and 60x/1.4 Plan Fluor objective lenses [Zeiss]), using a Zeiss
Axiocam digital camera [Zeiss, Oberkochen, Germany], Axiovision 3 image
acquisition software [Zeiss] and Adobe Photoshop 7 image processing and
manipulation software (Adobe, San Jose, CA).
Figure 2:
Immunostaining of human tonsil for signaling molecules in pDC. Top row: BLNK is
clearly present in a cluster of pDC (circled and at higher magnification in the inset)
lying close to a lymphoid follicle (Foll.). (Immunoperoxidase staining, hematoxylin
counterstain). Double immunofluorescent labeling (with CD2AP) shows that pDC also
express the signaling molecules Syk and Btk. (DAPI counterstain for Syk). Middle
row: pDC, identified by double staining for the transcription factor BCL11A (blue),
express the transmembrane adaptor protein LIME (brown) but are negative for two
other T cell-associated signaling molecules (TRIM and SLP76 – both brown). The
arrows indicate LIME-positive BCL11A-negative T cells. (No counterstain). Third row:
For personal use only. by guest on September 19, 2011. bloodjournal.hematologylibrary.orgFrom
26
Left: A cluster of pDC (circled and at higher magnification, center) lying adjacent to a
lymphoid follicle (Foll.) co-express DAP12 (brown) and the transcription factor
BCL11A (blue). Macrophages in the follicle (arrowed) express DAP12 alone. (No
counterstain). Right: TCB1B4 (a GTPase activating protein) is also strongly
expressed by clusters of pDC (circled in low power view). Note expression of
TCB1B4 in a B cell follicle (Foll.). (Immunoperoxidase staining, hematoxylin
counterstain). (Images were acquired on a Nikon Eclipse E800 microscope [Nikon,
Tokyo, Japan] equipped with 20x/0.7, 40x/0.95 and 60x/1.4 Plan Fluor objective
lenses [Zeiss]), using a Zeiss Axiocam digital camera [Zeiss, Oberkochen, Germany],
Axiovision 3 image acquisition software [Zeiss] and Adobe Photoshop 7 image
processing and manipulation software (Adobe, San Jose, CA).
Figure 3:
Immunostaining of human tonsil and in disorders characterized by reactive pDC. Top
two rows: pDC express the Toll-like receptors TLR7 and TLR9. (Immunoperoxidase
staining, hematoxylin counterstain). Vess: vessel. Double immunofluorescent labeling
shows co-expression in pDC of TLR7 and CD2AP. Third row: Left: The interfollicular
area contains cells stained for the pDC marker CD2AP (brown) and also TdT-positive
cells (red), but it is evident (see high magnification inset) that these two populations
do not overlap. (Hematoxylin counterstain). Right: Double immunoenzymatic staining
for CD123 (brown) and BCL11A (blue) shows co-expression in pDC. The nuclei in
the background with weak staining for BCL11A are B cells. (No counterstain). Fourth
row: The clusters of pDC that accumulate in cutaneous lupus (revealed by
immunostaining for CD2AP) are morphologically identical to those seen in tonsil and
blood, and show no evidence of dendritic processes. (Immunoperoxidase staining,
hematoxylin counterstain). In Kikuchi’s disease, large clusters of pDC are seen,
some of which have increased cytoplasm, and they show the same pattern of marker
expression as normal pDC, eg positive for the cytoplasmic marker CD2AP (brown or
red), and for the transcription factors BCL11A (red) and ICSBP/IRF8 (brown).
(Immunoperoxidase and double immunoenzymatic staining, hematoxylin
counterstain). (Images were acquired on a Nikon Eclipse E800 microscope [Nikon,
Tokyo, Japan] equipped with 20x/0.7, 40x/0.95 and 60x/1.4 Plan Fluor objective
lenses [Zeiss]), using a Zeiss Axiocam digital camera [Zeiss, Oberkochen, Germany],
For personal use only. by guest on September 19, 2011. bloodjournal.hematologylibrary.orgFrom
27
Axiovision 3 image acquisition software [Zeiss] and Adobe Photoshop 7 image
processing and manipulation software (Adobe, San Jose, CA).
Figure 4:
Immunostaining of pDC in blood and bone marrow. Upper panel: Immunoperoxidase
staining of normal peripheral blood mononuclear cells (cytospin preparation) shows
rare cells expressing the pDC marker CD2AP. Double labeling (right) shows that
these cells do not express CD3 or CD20 (double immunofluorescence) but they co-
express (as in tissue) CD2AP (brown) and BCL11A (red) (double staining).
Immunostaining of cytospin preparations of pDC isolated from peripheral blood using
anti-BDCA-4 shows that the great majority of cells express CD2AP and also the pDC
marker CD123 (and no staining is seen in a negative control). CD2AP is also
expressed by pDC isolated from peripheral blood using anti-BDCA-4 (Cytospin
preparation). (DAPI counterstain for the immunofluorescence preparations,
hematoxylin counterstain for the immunoenzymatic preparations). Lower panel:
Scattered pDC (arrowed) are seen in a bone marrow trephine (upper row)
immunostained for CD2AP and glycophorin (in brown and red respectively). In the
lower row, examples are shown at high magnification of bone marrow pDC co-
expressing CD2AP (brown) and BCL11A (red). (Hematoxylin counterstain). (Images
were acquired on a Nikon Eclipse E800 microscope [Nikon, Tokyo, Japan] equipped
with 60x/1.4 and 100/1.3 Plan Fluor objective lenses [Zeiss]), using a Zeiss Axiocam
digital camera [Zeiss, Oberkochen, Germany], Axiovision 3 image acquisition
software [Zeiss] and Adobe Photoshop 7 image processing and manipulation
software (Adobe, San Jose, CA).
Figure 5:
Immunostaining of pDC-associated markers in tumors derived from these cells (left),
and in cutaneous deposits of acute myeloid leukemia ("leukemia cutis") (right), a
neoplasm that can show similar histopathologic features. The markers shown were
expressed by essentially all cases of pDC-derived neoplasms, and the first four were
expressed only in a minority of leukemia cutis biopsies (BCL11A: 6/24 cases; BLNK:
8/24 cases; CD2AP: 1/24 cases and ICSBP: 5/24 cases). In contrast, BTK was
expressed in all samples of leukemia cutis tested (24/24 cases). (Immunoperoxidase
For personal use only. by guest on September 19, 2011. bloodjournal.hematologylibrary.orgFrom
28
staining, hematoxylin counterstain). (Images were acquired on a Nikon Eclipse E800
microscope [Nikon, Tokyo, Japan] equipped with 20x/0.7, 40x/0.95 and 60x/1.4 Plan
Fluor objective lenses [Zeiss]), using a Zeiss Axiocam digital camera [Zeiss,
Oberkochen, Germany], Axiovision 3 image acquisition software [Zeiss] and Adobe
Photoshop 7 image processing and manipulation software (Adobe, San Jose, CA).
For personal use only. by guest on September 19, 2011. bloodjournal.hematologylibrary.orgFrom
29
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... Since imatinib was suggested by the NCCN guidelines as the first-line therapy for CML, the management of the disease has undergone a significant change [4]. The majority of circulating imatinib binds to plasma proteins, namely albumin and alpha1 acid glycoprotein (AGP), and the elimination half-life is around 18 h [15]. Imatinib is efficiently absorbed when taken orally. ...
... Some investigations have shown that imatinib resistance was depending on plasma drug concentration and was brought on by inadequate dosages, reduced drug influx via the hOCT1 transporter, or enhanced drug efflux brought on by greater P-gp expression [16]. In a trial by Larson et al., patients experienced a full haematological response when plasma imatinib levels were>1000 ng/ml, and a poor haematological response was associated with low plasma levels of imatinib [15]. Previous reports also suggested that the patients with higher mean plasma imatinib levels of>1000ng/ml experienced cytogenetic response [17]. ...
... The results of our investigation are consistent with those of the aforementioned studies and suggest that a poor response to treatment may be caused by lower imatinib plasma trough levels [15,17,18]. ...
Article
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Objective: To measure and compare P-glycoprotein (P-gp) expressions in imatinib responders and non-responders with chronic myeloid leukemia-chronic phase (CML-CP) and correlate with plasma imatinib levels. Methods: Patients were classified into two groups based on their haematological and cytogenetic responses to imatinib: responders and non-responders. Liquid chromatography-mass spectrometry was used to measure plasma imatinib levels, while flow cytometry was used to evaluate leucocyte P-gp expression. Results: The median plasma imatinib trough levels in non-responders were 496 (217-3150) ng/ml compared to 2245 (454-4270) ng/ml in the responders, which was statistically significant (p=0.0003). The proportion of patients expressing P-gp in granulocytes was higher in the non-responder group than in the responder group (75% vs. 62.5%). The ratio of mean fluorescence intensity (RFI) revealed that non-responders had higher median P-gp expression than did respondents MFI (1.16(1.06-1.50) and 1.12(1.01-1.38), respectively; p = 0. 2307). In both groups, there was a negative correlation between P-gp expression and plasma imatinib trough levels (-0.4384 vs.-0.2848). Conclusion: Imatinib median plasma trough levels in non-responders were considerably lower. This was highly supported by P-gp expression in granulocytes, which is inversely related to imatinib plasma trough levels; however, the difference was not statistically significant, which could be attributed to the small number of patients. This could be the cause of imatinib resistance in non-responder CML-CP patients, and P-gp levels should be evaluated to optimize treatment in patients who do not achieve hematologic or cytogenetic response.
... Also, previous studies suggest that patients are more likely to have good treatment responses or improved response rates when administered imatinib at the appropriate trough concentration. Plasma levels of imatinib are shown to be higher in patients who obtain a complete cytogenetic response (CCR) compared to those who do not, and this trend is also seen in individuals with a major molecular response (MMR) [18,19]. In addition, higher imatinib plasma levels may contribute to the swift and effective management of illness observed in patients with elevated CK possibly reflecting higher drug levels [12], but it is uncertain whether individuals with elevated CK experience improved clinical outcomes due to these heightened responses [20]. ...
... High CK levels were also linked to the steady-state concentration and volume of distribution of Imatinib. Higher CK levels in patients on Imatinib may be the cause of the increased frequency of myalgia [18], which was found to occur after 1 month of treatment at the normal 400 mg/day dose. The pharmacokinetic (PK) variability, which has been reported to be around 60% in the steady-state trough concentrations of Imatinib in patients with GISTs and 71% in CML, is a potential cause of interpatient heterogeneity in treatment response [43,44]. ...
Article
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Background Imatinib treatment for certain cancers can lead to elevated creatine kinase (CK) levels, potentially indicating muscle injury, and ongoing research aims to understand the correlation between imatinib levels and creatine kinase to assess its impact on treatment response. Methods This single-center observational study involved 76 chronic myeloid leukemia (CML) patients receiving imatinib treatment, focusing on evaluating drug and metabolite levels using liquid chromatography–mass spectrometry (LC–MS-MS) instrumentation. Serum CK and creatine kinase-MB (CK-MB) levels were assessed using Colorimetric kits. Results CK and CK-MB levels were measured, CK showed a median value of 211.5 IU/l and CK-MB showed a median value of 4.4 IU/l. Comparing low and high CK groups, significant differences were found in peak and trough plasma concentrations of imatinib and its metabolites. Correlations between CK levels and pharmacokinetic parameters were explored, with notable associations identified. Binary logistic regression revealed predictors influencing the therapeutic response to imatinib and categorized expected CK levels into high or low, with peak levels of imatinib emerging as a significant predictor for CK level categorization. Conclusion The study highlights the link between imatinib’s pharmacokinetics and elevated CK levels, indicating a possible correlation between specific metabolites and improved treatment response. Individualized monitoring of CK levels and imatinib pharmacokinetics could enhance care for CML patients.
... Physical functioning was worse in the Genike group than in the Glivec group, while the economic burden and symptoms of insomnia in Glivec patients were worse. Population pharmacokinetic studies have suggested that the plasma concentration of imatinib may be influenced by white blood cell, granulocyte, hemoglobin, and α1-acid glycoprotein levels, age, body weight, body-surface area and chronic exposure to imatinib [15][16][17][18][19]. In our previous study, we investigated whether the factors affecting imatinib C min in Chinese populations were the same as those in Western populations [7]. ...
Article
Full-text available
Genike, the imatinib (IM)-alpha form is widely used in the treatment of gastrointestinal stromal tumor (GIST) patients in China. We wanted to investigate whether there are differences in IM plasma concentrations, adverse events, health-related quality of life (QOL) and outcomes between patients treated with Genike and Glivec. Thirty included GIST patients receiving IM treatment were matched to either Genike or Glivec according to gastrectomy, body weight, body surface area and sex. There was no statistically significant difference in IM trough plasma levels between the two groups. There were no significant differences in very common adverse events of IM between the Genike and Glivec groups. IM was well tolerated, although it was associated with a significant change in cognitive function (P < 0.001), fatigue (P = 0.015), pain (P = 0.015), nausea/vomiting (P = 0.029), insomnia (P = 0.019), diarrhea (P = 0.003) and financial difficulties (P < 0.001). Physical functioning, financial burden and insomnia were significantly different between the two groups (P = 0.026). Until Aug. 2022, there was no significant difference in time to imatinib treatment failure (TTF) between the two groups. In conclusion, there was no difference in IM plasma concentration and adverse events between Genike and Glivec. Both Genike and Glivec could partially decrease the QOL of GIST patients. Physical functioning was worse in Genike group than in Glivec group, while the economic burden and symptoms of insomnia in Glivec patients were worse. There was no significant difference in TTF between the two groups.
... This difference may lead to the exclusion of laboratory indicators related to liver function examination in the final selection of variables. IM C min was shown to be higher in females than in males in several studies, and researchers believed the difference could be attributable to differences in body weight or medication adherence between genders [31,32]. The existence of liver metastases may result in more changes and increased exposure to IM, which may cause higher in IM C min [33]. ...
Article
Full-text available
Aim Patients with advanced gastrointestinal stromal tumors (GISTs) exhibiting an imatinib plasma trough concentration (IM C min ) under 1100 ng/ml may show a reduced drug response rate, leading to the suggestion of monitoring for IM C min . Consequently, the objective of this research was to create a customized IM C min classification model for patients with advanced GISTs from China. Methods Initial data and laboratory indicators from patients with advanced GISTs were gathered, and the above information was segmented into a training set, validation set, and testing set in a 6:2:2 ratio. Key variables associated with IM C min were identified to construct the classification model using the least absolute shrinkage and selection operator (LASSO) regression and forward stepwise binary logistic regression. Within the training and validation sets, nine ML classification models were constructed via the resampling method and underwent comparison through the Brier scores, the areas under the receiver-operating characteristic curve (AUROC), the decision curve, and the precision-recall (AUPR) curve to determine the most suitable model for this dataset. Two methods of internal validation were used to assess the most suitable model's classification performance: tenfold cross-validation and random split-sample validation (test set), and the value of the test set AUROC was used to evaluate the model's classification performance. Results Six key variables (gender, daily IM dose, metastatic site, red blood cell count, platelet count, and percentage of neutrophils) were ultimately selected to construct the classification model. In the validation set, it is found by comparison that the Extreme Gradient Boosting (XGBoost) model has the largest AUROC, the lowest Brier score, the largest area under the decision curve, and the largest AUPR value. Furthermore, as evaluated via internal verification, it also performed well in the test set (AUROC = 0.725). Conclusion For patients with advanced GISTs who receive IM, initial data and laboratory indicators could be used to accurately estimate whether the IM C min is below 1100 ng/ml. The XGBoost model may stand a chance to assist clinicians in directing the administration of IM.
... At the same time, with few exceptions, nonradioactive oncologic therapies are administered as fixed or calculated doses based on patient weight or body surface area. Although personalized dosing schemes based on tumor burden, pharmacokinetics, and pharmacodynamics can potentially improve the therapeutic index of cancer treatments, very few such regimens have been adopted in clinical practice (1)(2)(3). Large, randomized clinical trials are required to validate personalized treatment regimens compared with conventional ones, and few such trials have been conducted. ...
... HUVECs were chosen based on prior studies demonstrating that toxicity of BCR-ABL TKIs in HUVECs correlates with and predicts arterial thrombotic events in humans [23]. For all experiments, HUVECs were treated with vehicle (dimethyl sulfoxide, DMSO) or each TKI at the steady-state peak plasma concentrations reported in CML patients: imatinib (4.0 μM) [31], dasatinib (0.2 μM) [32], ponatinib (0.1 nM) [8], nilotinib (3 μM) [33], asciminib (1.1 μM) [9], radotinib (0.38 μM) [34], and bafetinib (1.0 μM) [12]. Viability assays were also performed at 0.5 Cmax and 0.25 Cmax to assess the dose-response relationship of EC toxicity. ...
Article
Full-text available
BCR-ABL tyrosine kinase inhibitors (TKIs) have dramatically improved survival in Philadelphia chromosome-positive leukemias. Newer BCR-ABL TKIs provide superior cancer outcomes but with increased risk of acute arterial thrombosis, which further increases in patients with cardiovascular comorbidities and mitigates survival benefits compared to imatinib. Recent studies implicate endothelial cell (EC) damage in this toxicity by unknown mechanisms with few side-by-side comparisons of multiple TKIs and with no available data on endothelial impact of recently approved TKIs or novels TKIs being tested in clinical trials. To characterize BCR-ABL TKI induced EC dysfunction we exposed primary human umbilical vein ECs in 2D and 3D culture to clinically relevant concentrations of seven BCR-ABL TKIs and quantified their impact on EC scratch-wound healing, viability, inflammation, and permeability mechanisms. Dasatinib, ponatinib, and nilotinib, the TKIs associated with thrombosis in patients, all significantly impaired EC wound healing, survival, and proliferation compared to imatinib, but only dasatinib and ponatinib impaired cell migration and only nilotinib enhanced EC necrosis. Dasatinib and ponatinib increased leukocyte adhesion to ECs with upregulation of adhesion molecule expression in ECs (ICAM1, VCAM1, and P-selectin) and leukocytes (PSGL1). Dasatinib increased permeability and impaired cell junctional integrity in human engineered microvessels, consistent with its unique association with pleural effusions. Of the new agents, bafetinib decreased EC viability and increased microvessel permeability while asciminib and radotinib did not impact any EC function tested. In summary, the vasculotoxic TKIs (dasatinib, ponatinib, nilotinib) cause EC toxicity but with mechanistic differences, supporting the potential need for drug-specific vasculoprotective strategies. Asciminib and radotinib do not induce EC toxicity at clinically relevant concentrations suggesting a better safety profile.
Article
Introduction Imatinib mesylate (IM) is the drug of choice for the treatment of chronic myeloid leukemia (CML). However, despite most of the results obtained with this therapy being positive, some patients still present a suboptimal therapeutic response or still develop some type of resistance. Therefore, the aim of this study was to evaluate IM plasma levels in CML patients treated at a referral unit in Manaus and correlate them with variables that might interfere with these levels. Methods Data from 52 patients were obtained through a standardized questionnaire containing clinical, sociodemographic, lifestyle, and use of other medication information, as well as an estimate of therapeutic adherence. Additionally, blood collection was performed to measure the plasma concentration of the drug using the HPLC-UV technique. Molecular studies were done to identify the presence of polymorphism in the ABCG2 C421A membrane transporter. Results Most patients were male with a mean age of 52 ± 12.3 years (95% CI 49.0–55.9). There was a high variation in drug concentrations in the range from 0 to 4694 ng/mL, with a mean of 1558.59 ± 989.79 ng/mL (95% CI 1283.0–1834.1). Conclusion Approximately two-thirds of patients were classified in the drug-level range considered therapeutic, and there was a correlation between plasma concentration and higher molecular response. Additionally, most individuals had the normal genotype for the ABCG2 C421A polymorphism but further studies should be performed to reveal the role of this variable in the outcome of the disease in this population.
Introduction: Tyrosine kinase inhibitors (TKIs) have revolutionized survival rates of chronic myeloid leukemia (CML) and Philadelphia chromosome positive (Ph+) acute lymphoblastic leukemia (ALL) and replaced hematopoietic stem cell transplantation (hSCT) as the key treatment option for these patients. More recently, the so-called Philadelphia chromosome-like (Ph-like) ALL has similarly benefitted from TKIs. However, many patients shift from the first generation TKI, imatinib, due to treatment-related toxicities or lack of treatment efficacy. A more personalized approach to TKI treatment could counteract these challenges and potentially be more cost-effective. Therapeutic drug monitoring (TDM) has led to higher response rates and less treatment-related toxicity in adult CML but is rarely used in ALL or in childhood CML. Areas covered: This review summarizes different antileukemic treatment indications for TKIs with focus on imatinib and its pharmacokinetic/-dynamic properties as well as opportunities and pitfalls of TDM for imatinib treatment in relation to pharmacogenetics and co-medication for pediatric and adult Ph+/Ph-like leukemias. Expert opinion: TDM of imatinib adds value to standard monitoring of ABL-class leukemia by uncovering non-adherence and potentially mitigating adverse effects. Clinically implementable pharmacokinetic/-dynamic models adjusted for relevant pharmacogenetics could improve individual dosing. Prospective trials of TDM-based treatments, including both children and adults, are needed.
Article
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Imatinib (IMA) is a common chemotherapy drug for the treatment of leukemia and can potentially lead to drug resistance and toxicity during the course of treatment. Monitoring IMA concentrations in body fluids is necessary to optimize therapeutic schedules and avoid overdosage. In this paper, a novel ultrasensitive electrochemical sensor based on CuMOF and SWCNTs@AuNPs was developed to determine this antileukemic drug. Herein, AuNPs were supported on carboxylic single-walled carbon nanotubes (SWCNT-COOH), and then poly(diallyldimethylammonium chloride) (PDDA) was used as a dispersant to overcome the internal van der Waals interactions among the CNTs, further increasing the AuNP loading. Moreover, the morphology, structure, composition, and electrochemical properties of the CuMOF-SWCNTs@AuNPs composite film were characterized using SEM, TEM, FT-IR, UV–vis, XRD, XPS, CV, and EIS. Due to the advantage of the superior electrocatalytic and conductive properties of SWCNTs@AuNPs and their preferable adsorptivity and affinity to IMA of CuMOF, the fabricated glassy carbon electrode significantly improved the determination performance via their synergetic amplified effect. Under optimal conditions, a wide linear response was exhibited in the range from 0.05 to 20.0 μM and the low detection limit of 5.2 nM. In addition, our prepared sensor has been applied to the analysis of IMA in blood serum samples with acceptable results. Therefore, our CuMOF-SWCNTs@AuNPs-based electrochemical sensor possessed prominent sensing responses for IMA, which could be used as a prospective approach in clinical application.
Article
Imatinib is a tyrosine kinase inhibitor used in the treatment of chronic myeloid leukemia (CML). The area under the concentration–time curve (AUC) is a pharmacokinetic parameter that symbolizes overall exposure to a drug, which is correlated with complete cytogenetic and treatment responses to imatinib, as well as its side effects in patients with CML. The limited sampling strategy (LSS) is considered a sufficiently precise and practical method that can be used to estimate pharmacokinetic parameters such as AUC, without the need for frequent, costly, and inconvenient blood sampling. This study aims to investigate the pharmacokinetic parameters of imatinib, develop and validate a reliable and practical LSS for estimating imatinib AUC0–24, and determine the optimum sampling points for predicting the imatinib AUC after the administration of once-daily imatinib in Palestinian patients with CML. Pharmacokinetic profiles, involving six blood samples collected during a 24-h dosing interval, were obtained from 25 Palestinian patients diagnosed with CML who had been receiving imatinib for at least 7 days and had reached a steady-state level. Imatinib AUC0–24 was calculated using the trapezoidal rule, and linear regression analysis was performed to assess the relationship between measured AUC0–24 and concentrations at each sampling time. All developed models were analyzed to determine their effectiveness in predicting AUC0–24 and to identify the optimal sampling time. To evaluate predictive performance, two error indices were employed: the percentage of root mean squared error (% RMSE) and the mean predictive error (% MPE). Bland and Altman plots, along with mountain plots, were utilized to assess the agreement between measured and predicted AUC. Among the one-timepoint estimations, predicted AUC0–24 based on concentration of imatinib at the eighth hour after administration (C8-predicted AUC0–24) demonstrated the highest correlation with the measured AUC (r2 = 0.97, % RMSE = 6.3). In two-timepoint estimations, the model consisting of C0 and C8 yielded the highest correlation between predicted and measured imatinib AUC (r2 = 0.993 and % RMSE = 3.0). In three-timepoint estimations, the combination of C0, C1, and C8 provided the most robust multilinear regression for predicting imatinib AUC0–24 (r2 = 0.996, % RMSE = 2.2). This combination also outperformed all other models in predicting AUC. The use of a two-timepoint limited sampling strategy (LSS) for predicting AUC was found to be reliable and practical. While C0/C8 exhibited the highest correlation, the use of C0/C4 could be a more practical and equally accurate choice. Therapeutic drug monitoring of imatinib based on C0 can also be employed in routine clinical practice owing to its reliability and practicality. The LSS using one timepoint, especially C0, can effectively predict imatinib AUC. This approach offers practical benefits in optimizing dose regimens and improving adherence. However, for more precise estimation of imatinib AUC, utilizing two- or three-timepoint concentrations is recommended over relying on a single point.
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9528 Background: Imatinib achieves tumor control in most pts with advanced GIST, but the durability of remissions has not been well described. We now present an updated long-term analysis of a randomized phase II trial first presented in 2001, with a median follow-up of 52 months. Methods: 147 pts with unresectable or metastatic malignant GIST were randomized to treatment with daily dosing of imatinib, 400 or 600 mg po. Results: Two pts (1%) achieved a complete response, 98 (67%) achieved a partial response (PR), and 23 (16%) exhibited stable disease (SD) as their best response. Median time-to-response was 13 weeks (95% CI; 12–23 weeks), but one quarter of pts responded after 23 weeks. No significant response differences were seen between the two dose levels tested. The median duration of response was 27 months, and median overall survival was 58 months. Pts with SD or PR had similar 4-year survival rates (64% versus 62%). KIT and/or PDGFRA mutational analyses were obtained in 87% of patients, and the mutational status was highly significant in predicting outcome. GISTs harboring KIT mutations in exon 11, exon 9, and with no detectable mutations in KIT or PDGFRA demonstrated PR rates of 87%, 48%, and 0%, respectively. The median survival for pts with exon 11 KIT mutations has not yet been reached, and it was 45 months for those with exon 9 mutations. Conclusions: While late progression can be seen in GIST pts treated with imatinib, the majority of pts derive benefit. Survival in those achieving SD parallels those with PRs. Late responses are often seen in pts with initial SD, and responses in general are of lasting duration. In particular, pts with KIT mutations in exon 11 (the most common exon affected) have very high response rates and favorable long term survival. [Table: see text]
Article
CD303 is a calcium dependent type II lectin also known as Blood-Dendritic-Cell-Antigen-2 (BDCA-2) specifically expressed by human plasmacytoid dendritic cells (PDC). We have previously shown that monoclonal antibody (mAb) ligation of CD303 induces mAb endocytosis, calcium mobilization, protein tyrosine phosphorylation and inhibition of type I interferon (IFN I) production in stimulated PDC. Here we show that CD303 signaling and internalization in many aspects resembles B cell receptor (BCR) signaling and internalization. Instead of CD79a and CD79b, CD303 appears to use the Fc-receptor-common-gamma-chain as transmembrane adaptor protein. Like BCR signaling, CD303 triggering leads to SYK and BLNK phosphorylation. Signal transduction most likely involves activation of the phospholipase C-gamma 2, the phosphoinositide-3 kinase and the protein kinase C delta. Therefore, inhibition of IFN I production in stimulated PDC can be mimicked by PMA. Western blotting and peptide mass fingerprinting show that tyrosine phosphorylation occurs at cytoskeletal proteins (actin, alpha/beta-tubulin, profilin, alpha-actinin), proteasome activator subunit and the clathrin heavy chain, indicating clathrin-mediated endocytosis and vesicle trafficking. Finally, CD303 triggering inhibits TNF-alpha and CpG ODN-induced NF-kappa B activation in PDC.
Article
BDCA2 is a C-type lectin uniquely expressed by human plasmacytoid dendritic cells (pDCs). Ligation of this receptor by mAb inhibits Toll-like receptor (TLR)-mediated type I IFN responses by pDCs. However, it remains unclear how BDCA2 signals. We demonstrate here that BDCA2 forms a receptor complex with the transmembrane adapter FcεRIγ. Furthermore, pDCs express a comprehensive signaling machinery similar to that of the B cell receptor (BCR), which is distinct from that involved in T cell receptor (TCR) signaling. BDCA2 crosslinking resulted in the activation of BCR-like signal cascade in pDCs including phosphorylation of Syk and Src family kinases, as well as adapter molecule BLNK, leading to NFAT activation and calcium flux. This potently suppressed the ability of pDCs to produce IFN and other cytokines in response to both TLR7 and TLR9 ligands. Therefore, BDCA2 negatively regulates pDCs’ innate immune functions by associating with FcεRIγ and activating a BCR-like signaling pathway.
Article
6038 Background: Imatinib is an oral therapy with efficacy in chronic myelogenous leukemia (CML) and gastrointestinal stromal tumors (GIST). Optimal dosing and adherence to treatment is critical to achieve the best clinical outcomes. This study examined compliance and persistency with imatinib and identified the clinical and patient characteristics related to compliance. Methods: Claims data from a US health plan were used to identify imatinib-treated patients from 6/1/01–3/31/04 who had continuous pharmacy and medical benefits in the 3 months prior and 12 months following initiation of imatinib therapy, and a diagnosis of CML or GIST (ICD-9-CM 205.1, 205.10, or 205.11 for CML; 159.0, 159.8, or 159.9 for GIST). Compliance was defined by medication possession ratio (MPR = total days supply of imatinib in the first year divided by 365). Persistency was defined as failure to refill imatinib within 30 days from the run-out date of the prior prescription. Multivariate analyses were used to identify key factors associated with compliance. Results: Total 878 imatinib-treated patients were identified of whom 413 had at least 15 months’ continuous eligibility. Sixty-nine percent (n = 286) were diagnosed with CML, 8% (n = 34) with GIST, and 23% (n = 93) with neither. Results are presented for CML and GIST patients. The average age was 51 and 58% were males. The average starting daily dose was 424 mg, with 80% (n = 255) initiating on 400 mg daily. The mean MPR was 76%. Overall, 28% patients discontinued imatinib for at least 30 consecutive days during the 1-year follow up period. Multivariate analyses indicated MPR improved with age until age 51 and then deteriorated (p < 0.001) but at a diminishing rate, decreased as the number of medications increased (p < 0.001), and was lower in women (p = 0.005) and patients with more cancer complications (p < 0.001). In addition, women were more likely to discontinue than men (OR = 2.08; p = 0.003). Conclusions: Compliance to imatinib was about 75% with 30% of patients interrupting therapy for at least 30 consecutive days in the first year. It has been found that interruption of imatinib therapy may lead to rapid tumor progression in GIST (PASCO05 Le Cesne #9031). Not having patients take the correct doses on a regular basis may lead to sub therapeutical clinical outcomes. [Table: see text]
Article
CpG DNA induces plasmacytoid dendritic cells (pDC) to produce type I IFN and chemokines. However, it has not been fully elucidated how the TLR9 signaling pathway is linked to these gene expressions. We examined the mechanisms involving the TLR9 and type I IFN signaling pathways, in relation to CpG DNA-induced IFN-alpha, IFN regulatory factor (IRF)-7, and chemokines. p CXCL10 and CCL3 in human pDC. In pDC, NF-kappa B subunits p65 and p50 were constitutively activated. pDC also constitutively expressed IRF-7 and CCL3, and the gene expressions seemed to be regulated by NF-kappa B. CpG DNA enhanced the NF-kappa B p65/p50 activity, which collaborated with p38 MAPK to up-regulate the expressions of IRF-7, CXCL10, and CCL3 in a manner independent of type I IFN signaling. We then examined the pathway through which IFN-alpha is expressed. Type I IFN induced the. p expression of IRF-7, but not of IFN-alpha, in a NF-kappa B-independent way. CpG DNA enabled the type I IFN-treated pDC to express IFN-alpha in the presence of NF-kappa B/p38 MAPK inhibitor, and chloroquine abrogated this effect. With CpG DNA, IRF-7, both constitutively and newly expressed, moved to the nuclei independently of NF-kappa B/p38 MAPK. These findings suggest that, in CpG DNA-stimulated human pDC, the induction of IRF-7, CXCL10, and CCL3 is mediated by the NF-kappa B/p38 MAPK pathway, and that IRF-7 is activated upstream of the activation of NF-kappa B/p38 MAPK in chloroquine-sensitive regulatory machinery, thereby leading to the expression of IFN-alpha.
Article
6119 Background: IM (Glivec, Gleevec) is an oral targeted therapy with unprecedented efficacy in CML and GIST. Prescription compliance and persistency of pts receiving IM were measured by analysis of pt-level pharmacy claims data. Methods: Compliance and persistency were determined by analyzing the prescription-filling activity of pts (N=4043) compared with the prescribing activity of their physicians (N=3316) using pt pharmacy records accrued over 24 months (1/03–12/04). Observed average daily consumption (DACON) and average prescribed days of therapy were calculated and compared. Also, compliance and persistency were examined by pt demographics and initial IM dose prescribed. Results: Overall compliance (defined as medication possession ratio = apparent mg taken/mg prescribed) was 75%, with CML pts showing slightly greater compliance (78%) than GIST pts (73%). Fifty percent of pts were 100% compliant, the greatest compliance being found in pts initially treated with IM 300 or 400 mg/day (77%). Persistency (time on therapy without significant gaps in refills) averaged 255 days over 24 months. The most persistent pts were those initially given 300 or 400 mg/day (13.0 and 12.9 months, respectively). DACON was 400 mg/day for 65% of patients, but fluctuated above and below 400 mg/day in 18% and 17% of pts, respectively. Conclusions: This is the first assessment of pt compliance and persistency with prescribed IM therapy. Although less pronounced than with most other non-oncology products, suboptimal compliance and persistency with IM are a concern as doses <300–400 mg may result in plasma levels lower than needed to eliminate cancer cells. Patient support programs and improved communication on the importance of adhering to recommended dosing could potentially optimize outcome and further reduce risk of relapse and progression. [Table: see text]
Article
NCCN's Sarcoma Clinical Practice Guidelines in Oncology include a subsection regarding treatment recommendations on gastrointestinal stromal tumors (GISTs). GIST is one area of medicine where the standard of practice has been affected rapidly and dramatically by the introduction of effective molecularly targeted therapy for this disease. There are few examples in modern medicine in which the implementation of new technologies into practice has so radically and rapidly affected clinical diagnostic strategies and treatments with significant implications for the care of patients. Because of these recent changes, NCCN organized a broad multidisciplinary panel composed of experts in the fields of diagnostic radiology, pathology, molecular diagnostics, surgery, medical oncology, and radiation oncology to discuss the optimal approach for the care of patients with GIST at all stages of the disease. The GIST task force is composed of NCCN faculty and other key experts from North America, comprising the United States and Canada. The purpose of this meeting was to expand on the existing NCCN clinical practice guidelines for gastrointestinal sarcomas and to identify areas of future research to optimize our understanding and treatment of this disease.