blood1244correspondencecombined 654..661

658
BLOOD, 24 JULY 2014 x VOLUME 124, NUMBER 4
CORRESPONDENCE
expression and miR-processing enzymes are described for several
types of cancer. Dicer1, as one of the main components of the miR
processing ensemble, has been implicated in the context of cancer
initiation and evolution, especially in myeloma cells.4 The induction
of miR-128 by mutant (Mut) p53 has also been observed in tumor
cells, suggesting its role in the generation of chemoresistance.5
Here, the human myeloma cancer cell lines p53-Mut (L363) and
p53 wild-type (p53-WT) (MMS1) were used as a model system to
investigate the effects of bortezomib on MM cell growth. As shown in
Figure 1A, we detected a dose-dependent decrease in the growth
of both WT and p53-Mut myeloma cell lines with 50% inhibitory
concentration values of 11.6 nM (against L363) and 7.4 nM (against
MMS1) 24 hours after exposure to bortezomib. Having obtained this
information, we next asked whether bortezomib modulates Dicer1
expression levels. As depicted in Figure 1B, we found bortezomib to
decrease Dicer1 protein levels in MMS1 cells. In contrast, no change
in Dicer1 expression levels was observed in p53-Mut L363 cells.
In MM cells, the cell cycle inhibitor p21WAF1 is reduced by
increased proteasome activity, which fosters progression through the
cell cycle. In addition, miR-106a, miR-106b, miR-17-5p, and miR-20b
have been shown to critically participate in the regulation of cell cycle
progression by downregulating p21WAF1.6-8 We next evaluated the
p21 expression pattern that is associated with Dicer1 in response to
bortezomib. Dicer1 reduction was found to inversely correlate with
p21 protein accumulation in p53-WT MMS1 cells (Figure 1B).
Notably, p53-Mut L363 cells failed to accumulate p21WAF1 protein.
p21WAF1 stabilization was detected only with bortezomib at higher
concentrations in a p53-independent manner in the p53-Mut cell line.
Consistent with these ﬁndings, bortezomib effectively inhibited cell
growth and induced cell death in MMS1 cells with p53-WT but was
less effective in inhibiting cell growth and inducing cell death for L363
cells with p53-Mut (Figure 1C). This indicates that p53 status–
associated Dicer1 expression is an essential parameter for predicting
bortezomib sensitivity. The data presented here illustrate that cells with
p53-WT show a low level of Dicer1 and are sensitive to bortezomib,
and myeloma cells with p53-Mut show a constant high level of Dicer1
and are less sensitive to bortezomib-mediated apoptosis induction.
Suzuki et al9 reported a role for p53 in promoting the maturation
of miRs via interaction with the miR processing complex, DDR8Drosha. Both p53-WT and p53-Mut have prominent but opposing
roles at various levels in the process of miR maturation. Impaired
processing of miR was associated with MM disease progression. The
ﬁndings of Zhou et al8 clearly suggest that depletion of AGO2 or
Dicer1, 2 key regulators for miR maturation and functionality,
signiﬁcantly decreased viability of myeloma cells. Knockdown of
Dicer1 by siRNA increased sensitivity to bortezomib in p53-WT
MMS1 cells. When Dicer1 expression was antagonized in the p53Mut L363 cell line, a greater cytotoxic response was seen in treatment
with bortezomib (Figure 1B-C). In conclusion, this study identiﬁed
that Dicer1 knockdown can be exploited to sensitize myeloma for
chemotherapy, even in p53-Mut cells.
Gernot Stuhler
Department of Internal Medicine II, Julius-Maximilian’s University,
Wuerzburg, Germany
Tatyana S. Nekova
Department of Internal Medicine II, Julius-Maximilian’s University,
Wuerzburg, Germany
Acknowledgments: This work was supported by the Deutsche Jose Carreras
Leukamie
¨
Stiftung (DJCLS R07/10) (G.S.).
Contribution: T.S.N. performed the laboratory work for this study and wrote the
paper; G.S. made a contribution to conception and design.
Conflict-of-interest disclosure: The authors declare no competing financial
interests.
Correspondence: Tatyana S. Nekova, Department of Internal Medicine II,
Julius-Maximilian’s University of Wuerzburg, Josef-Schneider Strasse 2, 97080
Wuerzburg, Germany; e-mail: [email protected].
References
1. McConkey DJ, Zhu K. Mechanisms of proteasome inhibitor action and resistance
in cancer. Drug Resist Updat. 2008;11(4-5):164-179.
2. Ling X, Calinski D, Chanan-Khan AA, Zhou M, Li F. Cancer cell sensitivity to
bortezomib is associated with survivin expression and p53 status but not cancer
cell types. J Exp Clin Cancer Res. 2010;29(1):8.
3. Mendell JT, Olson EN. MicroRNAs in stress signaling and human disease. Cell.
2012;148(6):1172-1187.
4. Benetatos L, Vartholomatos G. Deregulated microRNAs in multiple myeloma.
Cancer. 2012;118(4):878-887.
5. Donzelli S, Fontemaggi G, Fazi F, et al. MicroRNA-128-2 targets the
transcriptional repressor E2F5 enhancing mutant p53 gain of function. Cell Death
Differ. 2012;19(6):1038-1048.
6. Ivanovska I, Ball AS, Diaz RL, et al. MicroRNAs in the miR-106b family regulate
p21/CDKN1A and promote cell cycle progression. Mol Cell Biol. 2008;28(7):
2167-2174.
7. Gibcus JH, Kroesen B-J, Koster R, et al. MiR-17/106b seed family regulates p21
in Hodgkin’s lymphoma. J Pathol. 2011;225(4):609-617.
8. Zhou Y, Chen L, Barlogie B, et al. High-risk myeloma is associated with global
elevation of miRNAs and overexpression of EIF2C2/AGO2. Proc Natl Acad Sci
USA. 2010;107(17):7904-7909.
9. Suzuki HI, Yamagata K, Sugimoto K, Iwamoto T, Kato S, Miyazono K.
Modulation of microRNA processing by p53. Nature. 2009;460(7254):529-533.
© 2014 by The American Society of Hematology
To the editor:
Imaging flow cytometry documents incomplete resistance of human sickle F-cells to ex vivo
hypoxia-induced sickling
We have read with great interest the “Perspectives” article by
Steinberg et al in the January 23, 2014, edition of Blood.1 The authors
present a mathematical model that implies that the critical content of
fetal hemoglobin (HbF) required to prevent polymerization of sickle
hemoglobin is higher than the threshold HbF content that renders an
erythrocyte detectable as an “F-cell” on immunoﬂuorescent staining
by ﬂow cytometry. This would lead to a hypothesis that only a subset of
F-cells are resistant to hypoxia-induced sickling. We obtained data from
a new imaging ﬂow cytometry assay that can qualitatively support this
general principle, although with clear assay limitations that don’t permit
us to address quantitatively the predictions of Steinberg et al in detail.
These new results show that intracellular HbF is a major factor
inﬂuencing sickling, but it is clearly not the only factor.
We investigated the inﬂuence of HbF content on sickling at the
individual cell level through our recently developed Sickle Imaging
Flow Cytometry Assay (SIFCA), a robust, reproducible sickling assay.2
We developed an enhanced version of SIFCA that allows simultaneous
analysis of both intracellular expression of HbF and morphological
BLOOD, 24 JULY 2014 x VOLUME 124, NUMBER 4
CORRESPONDENCE
659
Figure 1. Imaging flow cytometry documents incomplete
resistance of human sickle F-cells to ex vivo hypoxiainduced sickling. (A) HbF in the hemolysate correlates
positively with the percentage of F-cells detected by SIFCA.
HbF protective effect against sickling is shown by a positive
correlation with the percent of cells that remain in normal
shape after deoxygenation (B), and an opposite correlation
with the percent of cells that become sickled (C). Sample
images acquired by the imaging flow cytometer show simultaneous brightfield images (left column) and fluorescence of an
anti-HbF-PE antibody (right column) in a normal non-F-cell
(Di), sickled non-F-cell (Dii), normal F-cell (Diii), and a sickled
F-cell (Div). (E) Transmission electron microscopy of RBCs
enriched by fluorescence-activated cell sorting was performed
to confirm that sickled cells contained similar fibers corresponding to hemoglobin S polymers regardless of whether
they were non-F-cells (top) or F-cells (bottom). Bar 5 100 nm.
Images acquired with a JEM1400 electron microscope (JEOL)
equipped with an AMT XR-111 digital camera (Advanced
Microscopy Techniques Corporation). Image Adjust-Levels
and Image Adjust Brightness functions in Photoshop Creative
Suite 6 software (Adobe Systems Corporation) were used to
equalize the densities in both images. (F) Non-F-cells sickled
more than F-cells in both patients off hydroxyurea (left side,
*P 5 .0014, paired Student t test) and on HU (right side,
*P 5 .0057, paired Student t test), but cells from treated
patients sickle less than from untreated patients (Mann-Whitney
test, #P 5 .0197 for F-cells from patients off HU compared with
on HU, P 5 .0501 for comparison between non-F-cells).
features of each red blood cell (RBC). Peripheral venous blood samples
were collected with written consent from 22 adult sickle cell anemia
(SCA) patients (8 off and 14 on hydroxyurea, median HbF 10.7% and
18.3%, respectively) with a wide HbF range (1.5% to 33.0%). We
subjected 1% RBC suspensions to deoxygenation for 2 hours at
2% oxygen followed by ﬂuorescent labeling against HbF. Images
from 20 000 cells were obtained by imaging ﬂow cytometry
(ImageStreamX Mk II; Amnis Corporation), allowing combined
analysis of shape change and HbF expression for each RBC. We
conﬁrmed previous observations3 using conventional ﬂow cytometry
that F-cell count signiﬁcantly correlates with percent HbF determined by HPLC (Figure 1A). F-cell count by SIFCA correlated
highly with conventional F-cell ﬂow cytometry by an independent
Clinical Laboratory Improvement Amendments–certiﬁed facility
(r2 5 0.9976, 95% CI 0.9861-0.9996, P , .0001, data not shown).
SIFCA yields automated determination of the percentage of
“normal cells,” which remain biconcave discs, and of “abnormal
cells,” which change their shape on hypoxic incubation, including
660
BLOOD, 24 JULY 2014 x VOLUME 124, NUMBER 4
CORRESPONDENCE
the majority of sickled cells. As expected, the HbF percentage
correlated positively and negatively with the percentage of normal
and abnormal cells, respectively (Figure 1B-C).
Fluorescent labeling of HbF allowed us to discriminate nonF-cells (Figure 1Di-ii) from F-cells (Figure 1Diii-iv), and analyze their
shape as captured in the brightﬁeld images. The images conﬁrmed the
prediction that some RBCs with detectable HbF content still sickle
(Figure 1Div), and also identiﬁed RBCs that are resistant to sickling
despite no detectable HbF (Figure 1Dii). The percentage of non-Fcells sickling on deoxygenation was signiﬁcantly higher than among
F-cells (20.08% [95% CI 15.56-24.60] vs 13.44% [95% CI 10.2116.68], P , .0001). This difference was statistically signiﬁcant both
in patients not taking HU and in treated patients (Figure 1F). F-cells
from patients on HU sickled signiﬁcantly less than F-cells from
patients off HU, and the same difference was borderline signiﬁcant
when comparing non-F-cells from patients on HU with those off HU.
Our observations support that the threshold used for detection of
F-cells is not the same threshold that deﬁnes protection against
sickling. Similar to previous investigators, we also have found that
the very high concentration of intraerythrocytic hemoglobin poses a
difﬁcult challenge in achieving the antigen saturation with antig-globin antibody that is necessary to measure accurately the amount
of HbF per F-cell,4 which will be needed ultimately to test fully the
mathematical modeling predictions of Steinberg et al. Differential
RBC susceptibility of non-F-cells to sickling between patients on or off
HU also supports the existence of additional beneﬁcial mechanisms of
HU other than HbF induction.4 The identiﬁcation of factors besides
HbF that modulate sickle hemoglobin polymerization may help in the
design of novel therapies for HU-resistant SCA patients.
Kleber Yotsumoto Fertrin
Sickle Cell Vascular Disease Section, Hematology Branch,
National Heart, Lung, and Blood Institute,
Bethesda, MD
Eduard J. van Beers
Sickle Cell Vascular Disease Section, Hematology Branch,
National Heart, Lung, and Blood Institute,
Bethesda, MD
Leigh Samsel
Flow Cytometry Core Facility,
National Heart, Lung, and Blood Institute,
Bethesda, MD
Laurel G. Mendelsohn
Sickle Cell Vascular Disease Section, Hematology Branch,
National Heart, Lung, and Blood Institute,
Bethesda, MD
Rehan Saiyed
Sickle Cell Vascular Disease Section, Hematology Branch,
National Heart, Lung, and Blood Institute,
Bethesda, MD
James S. Nichols
Sickle Cell Vascular Disease Section, Hematology Branch,
National Heart, Lung, and Blood Institute,
Bethesda, MD
David A. Hepp
Electron Microscopy Core Facility,
National Heart, Lung, and Blood Institute,
Bethesda, MD
Christine A. Brantner
Electron Microscopy Core Facility,
National Heart, Lung, and Blood Institute,
Bethesda, MD
Mathew P. Daniels
Electron Microscopy Core Facility,
National Heart, Lung, and Blood Institute,
Bethesda, MD
J. Philip McCoy
Flow Cytometry Core Facility,
National Heart, Lung, and Blood Institute,
Bethesda, MD
Gregory J. Kato
Department of Medicine, Division of Hematology-Oncology,
Heart, Lung, Blood and Vascular Medicine Institute,
University of Pittsburgh,
Pittsburgh, PA
Contribution: K.Y.F., E.J.v.B., L.S., L.G.M., and R.S. performed sample
processing and flow cytometry experiments with supervision of J.P.M. and
G.J.K.; J.S.N. enrolled patients and procured samples; D.A.H. and C.A.B.
performed electron microscopy processing, imaging and developed related
figures with supervision of M.P.D.; K.Y.F., J.P.M., and G.J.K. designed the
study; K.Y.F. and G.J.K. performed data analysis and drafted the manuscript;
and all authors reviewed and edited the final manuscript.
Conflict-of-interest disclosure: The authors declare no competing financial
interests.
Correspondence: Gregory J. Kato, Department of Medicine, Division of
Hematology-Oncology, and the Heart, Lung, Blood and Vascular Medicine
Institute, University of Pittsburgh, 200 Lothrop St, BST E1240, Pittsburgh,
PA 15261; e-mail: [email protected].
References
1. Steinberg MH, Chui DHK, Dover GJ, Sebastiani P, Alsultan A. Fetal
hemoglobin in sickle cell anemia: a glass half full? Blood. 2014;123(4):
481-485.
2. van Beers EJ, Samsel L, Mendelsohn LG, et al. Imaging flow cytometry for
fully automated quantification of percentage of sickled cells in sickle cell
anemia. Am J Hematol. 2014;89(6):598-603.
3. Steinberg MH, Lu ZH, Barton FB, Terrin ML, Charache S, Dover GJ;
Multicenter Study of Hydroxyurea. Fetal hemoglobin in sickle cell anemia:
determinants of response to hydroxyurea. Blood. 1997;89(3):1078-1088.
4. Segel GB, Simon W, Lichtman MA. Should we still be focused on red cell
hemoglobin F as the principal explanation for the salutary effect of
hydroxyurea in sickle cell disease? Pediatr Blood Cancer. 2011;57(1):8-9.
To the editor:
Misleading results from saliva samples of patients post-BMT in exome analyses
We routinely perform clinical exome sequencing on blood samples
from patients without bone marrow transplants (BMTs). Moreover, we accept saliva samples due to the acceptable DNA quality,
noninvasiveness, and improved percentage of participants.1 We
assess the quality at the wet laboratory as well as the bioinformatics
process which includes monitoring the number of variants after
inheritance model ﬁltering. Recently, a 4-member family (mother,
father, female proband, and affected sister) was referred for exome
analysis due to combined immune deﬁciency of undetermined genetic
etiology in the proband. The samples that were submitted for analysis
were blood for both parents and saliva for both affected sisters. All of
the quality controls passed the set thresholds except for the inheritance

Download Report