1. © Journal of Medicine and Biomedical Sciences, ISSN: 2078-0273, Vol. 4. No. 2, 2013
49
Mohadese H. Boroojerdi, N. Daneshvar, P. Ghoraishizadeh, S. Md Noor, Z. Seman, R. Ramasamy.
Descriptive analysis of antigen expression pattern in refractory anemia, refractory anemia with ringed
sideroblasts and refractory anemia with excess blast cases using flow cytometry. Journal of Medicine and
Biomedical Sciences 2013; 4(2), 49-56. DOI: 10.7813/jmbs.2013/4-2/8
DESCRIPTIVE ANALYSIS OF ANTIGEN EXPRESSION PATTERN IN
REFRACTORY ANEMIA, REFRACTORY ANEMIA WITH RINGED
SIDEROBLASTS AND REFRACTORY ANEMIA WITH EXCESS
BLAST CASES USING FLOW CYTOMETRY
Mohadese Hashem Boroojerdi
1
, Nasibeh Daneshvar
2
, Peyman Ghoraishizadeh
1
,
Dr. Sabariah Md Noor
1
, Dr. Zainina Seman
1
, Dr. Rajesh Ramasamy
1
1
Pathology Department, Faculty of Medical and Health Science, University Putra Malaysia,
2
Institute of Bioscience, Universiti Putra Malaysia, 43400 Serdang, Selangor (MALAYSIA)
E-mails: Mohadese_b84@yahoo.com, Nasibe.daneshvar@yahoo.com, peyman.innovate@gmail.com
DOI: 10.7813/jmbs.2013/4-2/8
ABSTRACT
Myelodysplastic Syndromes (MDSs) are a slow progressing group of disease that causes
peripheral cytopaenia of all cell lineages, with high capabilities to transform into acute myeloid
leaukaemia (AML). Establishing a frame of reference for antigen expression pattern in different MDS
subtypes, may help to classify the patients for choosing more appropriate therapeutic approaches. In
this study, thirty bone marrow (BM) samples from newly-diagnosed MDS patients were analyzed by 4-
colour FACS Canto flow cytometer. In this research, the quantitative analysis of antigen expression
patterns of granulocytic, monocytic, erythroid and lymphoid lineages also myeloid precursors were
performed. The one-way ANOVA was used to test the differences between mean percentages of
antigens in MDS subtypes. In this study, we showed the mean percentages of CD71/CD235a/
CD45/CD117, HLA-DR/CD13/CD45/CD11b, CD14/CD33/CD45/CD34, and CD19/ CD20/CD45/CD10
antibody combinations on erythroid, granulocytic, monocytic, and lymphoid lineages, respectively, in
different MDS subtypes. The most important finding of this study was the significant difference of
CD71 mean percentage in erythroid cells between MDS subtypes. Erythroid lineage in Refractory
Anemia with Excess Blast (RAEB) cases was found by lower mean percentage of CD71 (54.74%), as
compared to Refractory Anemia (RA) (74.65%) and Refractory Anemia with Ringed Sideroblasts
(RARS) cases (74.60%). In this study, the difference of CD71
+
erythroid cells was statistically
significant only between RARS and RAEB subtypes (p=0.011). Our study, showed the expression
range of different CD markers on different lineages of MDS subtypes. These findings can improve
understanding the prognosis of various subtypes, and explaining the laboratory and clinical results.
Key words: Myelodysplastic Syndromes (MDSs), bone marrow (BM), Flow cytometer
1. INTRODUCTION
Myelodysplastic syndromes (MDSs) are a various group of hematological diseases that present
production of the blood cells in an ineffective way (1, 2). Several MDS classification and prognostic
scoring systems have been proposed (3) (4-6). There are two MDS staging systems such as;
International Prognostic Scoring System (IPSS) and World Health Organization (WHO) Prognostic
Scoring System (WPSS) (7-9). Percentage of blasts in bone marrow (BM), chromosome abnormalities
and, blood counts were three factors that were established by IPSS to stage MDS. In this
classification, each patient was taken a score for each of three factors, and lower score was shown
better prognosis. As mentioned before, based on IPSS score, MDS patients divided to four groups
(low risk, intermediate-1 risk, intermediate-2 risk, high risk). According to this system, cases with
higher risk had the lower median survival and higher risk for progressing to Acute Myeloid Leukemia
(AML) and cases with lower risk had the higher median survival and lower risk for progressing to AML.
MDS cases were classified to five groups based on IPSS scoring. These five groups are: Refractory
anemia with ringed sideroblasts (RARS), Refractory anemia (RA), chronic myelomonocytic leukemia

2. © Journal of Medicine and Biomedical Sciences, ISSN: 2078-0273, Vol. 4. No. 2, 2013
50
(CMML), and Refractory anemia with excess blasts (RAEB), Refractory anemia with excess blasts in
transformation (RAEB-t). In general, those with more chromosomal damage, higher number of blasts
in the BM, have more chance for progressing to AML (7-9). Chromosome abnormalities and, patient
requirement for transfusions were three factors that were established by WPSS to stage MDS. Based
on this system, MDS patients divided to five groups (very low risk, low risk, intermediate risk, high risk,
very high risk). According to this categorization, cases with lower risk had the higher median survival
and lower risk for progressing to AML and vice versa. In this staging system, MDS cases were
classified to five groups (Refractory anemia, Refractory anemia with ringed sideroblasts, Refractory
cytopenia with multilineage dysplasia, Refractory cytopenia with multilineage dysplasia and ringed
sideroblasts, Refractory anemia with excess blasts-1, Refractory anemia with excess blasts-2,
Myelodysplastic syndrome, unclassified, Myelodysplastic syndrome associated with isolated del(5q)).
In fact, MDS subclassification makes managing and controlling of this disease more possible.
Unfortunately, subclassification of MDS remains difficult and imprecise. A single marker that reliably
distinguishes MDS from non-MDS would greatly facilitate diagnosis and might aid MDS
subclassification. Diagnosis and subclassification of MDS remain difficult by the absence of definitive
testing for these purposes(10). In recent decades, immunophenotyping by flow cytometry plays an
important role in diagnosis and sub classification of haematological malignancies (11-13). On the other
hand, knowing about the prognosis of individual patients will provide useful information that lead to
more trustable diagnosis also, better controlling and treatment of the disease. In fact, knowledge about
the pattern of antigen expression on various cell lineages in different MDS subtypes can give us a
prognostic value of each subtype. Knowing the prognosis of each subtype by immunophenotyping,
cause more accurate diagnosis of this malignancy (14) also, might help to choose more appropriate
therapeutic approaches (15).
2. MATERIALS AND METHODS
In this study, 30 MDS cases with newly diagnosed MDS based on French-American-British
(FAB) criteria were investigated (16). Flow cytometric analysis of the samples was performed in the
flow cytometry laboratory, Haematology Unit, Pathology Department, Faculty of Medicine and Health
Science, University Putra Malaysia (UPM). Sample collection was done from February 2009 to
November 2010 at Hospital Kuala Lumpur (HKL) after written informed consent from patients and
ethical clearance from the Faculty of Medicine and Health Sciences (UPM) (no: UPM/FPSK/PADS/T7-
MJKEtikaPer/F01(LECT(JPAT)_MAC(10)02), and approval letter from HKL (no: HKL /PAT/180/1). The
pattern recognition approach that we adopted in this study was the method suggested by Van Lochem
et al. (Van Lochem et al 2004). In this study, CD71/CD235a/CD45/CD117, HLA-DR/CD13/CD45/
CD11b, CD14/CD33/CD45/CD34, and CD19/CD20/CD45/CD10 antibody combinations were used to
analyze erythroid, granulocytic, monocytic, and lymphoid lineages respectively. The method for
labeling the cells was carried out according to Li et al. with some modifications according to the
recommendation of the manufacturer to optimize the technique. The process has been described in
our published manuscript. A descriptive analysis was done for all variables studied (17).
3. STATISTICAL ANALYSIS
The one-way ANOVA was used to test of differences between mean percentages of antigens in
MDS subtypes. Tukey test was done in the cases that showed significant differences in one-way
ANOVA test. A p-value of ≤0.05 was considered as statistically significant
4. RESULTS
The mean percentages of CD13, CD34, CD10, HLA-DR, CD33 and CD11b expression of the
granulocyte lineage were 82.85%, 34.72%, 51.15%, 11.05%, 96.35%, and 83.60%, respectively, in RA
patients. In addition, patients with RARS showed mean percentages of 86.70%, 32.50%, 39.30%,
16.75%, 93.34%, and 84%, respectively, while patients with RAEB showed mean percentages of
84.28%, 35.41%, 38.22%, 13.96%, 87.85%, and 70.49%, respectively. There was no significant
difference in granulocytic antigen expression among MDS subtypes. Table 1 shows the percentages
of different antigens on granulocytic lineage in MDS subtypes.

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Table 1. Percentages of different antigens on granulocytic lineage in MDS subtypes
Variable Group Mean percentage SD F/Welch P values
CD13 RA 82.85 13.10 0.237 0.790
RARS 86.70 7.76
RAEB 84.28 12.51
CD34 RA 34.72 7.07 0.582 0.566
RARS 32.50 5.38
RAEB 35.41 7.71
CD10 RA 51.15 10.88 1.046 0.365
RARS 39.30 17.53
RAEB 38.22 16.09
HLA-DR RA 11.05 6.23 0.911 0.414
RARS 16.75 10.23
RAEB 13.96 5.54
CD33* RA 96.35 3.53 2.36 0.155
RARS 93.34 2.15
RAEB 87.85 13.93
CD11b* RA 83.60 10.09 2.39 0.157
RARS 84 4.69
RAEB 70.49 22.29
* For cases (CD33 and CD11b) that homogeneity of variance was not assumed Welch statistic has been
reported.
4.1.2. ERYTHROID LINEAGE
The mean percentages of CD71, CD235a and CD71/CD235a-positive erythroid lineages were
74.65%, 39.27% and 9.02% in RA. Analysis of these antigens’ expressions on RARS and RAEB
subtypes showed mean percentages of 74.60%, 38.57%, 7.57% and 54.74%, 33.16%, 5.26%,
respectively. The mean percentages of CD71-positive, CD235a-positive and CD71/CD235a-positive
nucleated red cells were lower in RAEB as compared to RA and RARS. Only the difference of CD71-
positive erythroid cells was statistically significant. Based on Tukey test the difference of CD71-
positive erythroid cells was statistically significant only between RARS and RAEB subtypes (p≤0.05).
Table 2 shows the mean percentages of different antigen expression on erythroid lineage in MDS
subtypes. Table 3 shows the significant differences in one-way ANOVA test by Tukey test.
Table 2. Percentages of different antigens on erythroid lineage in MDS subtypes
Variable Group Mea percentage SD F/Welch P values
CD71 RA 74.65 5.83 5.80 0.008
RARS 74.60 13.22
RAEB 54.74 19.33
CD235a RA 39.27 12.98 0.68 0.515
RARS 38.57 14.02
RAEB 33.16 12.57
CD71/CD235a-positive* RA 9.02 5.486 1.86 0.224
RARS 7.57 4.15
RAEB 5.26 2.45
*For cases (CD71/CD235a) that homogeneity of variance was not assumed (p value was less than 0.05)
Welch statistic has been reported.
Table 3. Analysis of CD markers that showed significant
differences in one-way ANOVA test by Tukey test
The mean percentages of monocytic lineage expressed HLA-DR, CD19, HLA-DR/CD11b-
positive, CD14, CD33, CD14/CD34-positive and CD13 were 33.05%, 32.40%, 28.50%, 83.47%,
87.77%, 30.72%, and 73.92% in RA. Patients with PARS and RAEB showed mean percentages of
36.89%, 29.70%, 31.50%, 66.65%, 83.22%, 35.84%, 70.92% and 35.90%, 32.85%, 34.29%, 60.63%,
75.40%, 37.48%, 78.16%, respectively. There was no significant difference in monocytic antigen
expression among MDS subtypes. Table 4 shows the percentages of different antigens on monocytic
lineage in MDS subtypes.
Variable Group Group P value
CD71 RA RARS 1.00
RAEB 0.087
RARS RA 1.00
RAEB 0.011
RAEB RA 0.087
RARS 0.011

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Table 4. Percentages of different antigens on monocytic lineage in MDS subtypes
Variable Group Mean
percentage
SD F/Welch P values
HLA-DR RA 33.05 7.25 0.25 0.781
RARS 36.89 11.49
RAEB 35.90 13.17
CD19 RA 32.40 11.29 0.30 0.739
RARS 29.70 9.63
RAEB 32.85 10.67
HLA-DR/CD11b-positive RA 28.50 7.30 0.95 0.397
RARS 31.50 8.79
RAEB 34.29 7.57
CD14* RA 83.47 3.84 1.89 0.169
RARS 66.65 19.52
RAEB 60.63 23.81
CD33 RA 87.77 11.04 1.20 0.315
RARS 83.22 9.29
RAEB 75.40 21.19
CD14
/
CD34-positive RA 30.72 10.42 0.27 0.763
RARS 35.84 15.02
RAEB 37.48 18.06
CD13 RA 73.92 23.36 0.29 0.748
RARS 70.92 16.88
RAEB 78.16 28.017
*For cases (CD14) that homogeneity of variance was not assumed (p value was less than 0.05)) Welch
statistic has been reported.
4.1.4. MYELOID PRECURSORS
The mean percentages of CD33, CD34, CD13, HLA-DR, HLA-DR/CD11b-positive, CD117 and
CD11b expressed by myeloid precursors were 82.07%, 72.97%, 58.77%, 67.05%, 18.67%, 20.40%,
and 29.37%, respectively, in RA. Patients with RARS and RAEB showed mean percentages of
69.36%, 52.70%, 57.21%, 46.49%, 21.97%, 18.61%, 17.79% and 65.72%, 60.95%, 63.64%, 56.54%,
24.38%, 20.68%, 25.98%, respectively. There was no significant difference in myeloid precursor’s
antigen expression among MDS subtypes. Table 5 shows the percentages of antigens on myeloid
precursors in MDS subtypes.
Table 5. Percentages of antigens on myeloid precursors in MDS subtypes
Variable Group Mean percentage SD F/Welch P values
CD33 RA 82.07 3.10 0.84 0.440
RARS 69.36 25.94
RAEB 65.72 21.88
CD34 RA 72.97 6.37 1.78 0.187
RARS 52.70 20.06
RAEB 60.95 19.68
CD13 RA 58.77 21.31 0.32 0.729
RARS 57.21 21.47
RAEB 63.64 20.27
HLA-DR RA 67.05 18.85 1.77 0.188
RARS 46.49 20.50
RAEB 56.54 19.50
HLA-DR/CD11b-poisitive RA 18.67 13.81 0.29 0.749
RARS 21.97 13.32
RAEB 24.38 14.36
CD117 RA 20.40 9.36 0.14 0.869
RARS 18.61 9.45
RAEB 20.68 10.51
CD11b* RA 29.37 19.23 1.97 0.243
RARS 17.79 5.40
RAEB 25.98 16.73
*For cases (CD11b) that homogeneity of variance was not assumed (p value was less than 0.05) Welch
statistic has been reported.

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The mean range for CD19, CD19/CD10-positive, CD19/CD20-positive and CD20/CD10-positive
were 15.47%, 6.84%, 12.43%, and 3.32%, respectively, in RA. The expression of these antigens were
14.35%, 3.75%, 12.97%, and 2.90%, respectively, in RARS and 14.73%, 3.68%, 11.59%, and 3.13%,
respectively, in RAEB cases. Table 6 shows the percentages of different antigens on lymphoid lineage
in MDS subtypes. Table 7 shows the significant differences in one-way ANOVA test by Tukey test.
Table 6. Percentages of different antigens on lymphoid lineage in MDS subtypes
Variable Group Mean
Percentage
SD F/Welch* P values
CD19 RA 15.47 7.81 0.061 0.941
RARS 14.35 4.81
RAEB 14.73 5.39
CD19/CD10-positive RA 6.84 2.17 4.108 0.028
RARS 3.75 1.92
RAEB 3.68 2.11
CD19/CD20-positive RA 12.43 2.40 0.401 0.674
RARS 12.97 3.37
RAEB 11.59 4.52
CD20/CD10-positive RA 3.32 2.38 0.105 0.901
RARS 2.90 2.05
RAEB 3.13 1.94
Table 7. Analysis of CD markers that showed significant differences
in one-way ANOVA test by Tukey test
5. DISCUSSION
MDS has a broad distribution of clinical and pathologic features, and patients vary markedly in
their prognosis and response to treatment. Differences in clinical features and treatment response are
likely due to molecular heterogeneity that underlies the disease process(18). In this study, we did the
quantitative flow cytometric analysis of the most important maturation-associated antigens in BM cells
of erythroid, granulocytic, monocytic, lymphoid lineages and myeloid precursors. Thirty newly-
diagnosed MDS patients were analysed in this study(19). The aim of this study was quantitative
analysis of antigen expression, also, showing some abnormal antigen expression pattern in different
MDS subtypes.
Several studies have reported the phenotypic changes occurring in the different cell populations
in MDS subtypes. In mentioned studies, different antibody panel has been used, and various cell
lineages has been analyzed(20, 21) (22, 23). We showed some abnormal expression pattern; in
addition, the mean percentage of different antigen in various cell lineages in our study.
This study, though the analysis of granulocytic lineage we found that the mean percentage of
CD10, CD11b and CD33 was lower in RAEB but the difference was not statistically significant. As
mentioned previously, CD13 and CD33 are markers which decrease during maturation. In addition,
CD34 that relates to the immature cells was higher in RAEB cases as compared to other MDS
subtypes although, the difference was not statistically significant. These results are the same as what
has been found by other researchers(20, 21). same as other studies, our findings showed the mean
percentage of CD10 on granulocytes was lower in RAEB, while granulocytes in RA cases showed a
higher mean percentage of CD10 but the difference was not statistically significant (20, 23).
CD 14 is normally expressed on mature monocytes. Decreased of mean percentage of CD14
on monocytic lineage is more prominent in RAEB subtypes (21). In this study, the mean proportion of
different CD markers on monocyte lineage was compared among MDS subtypes. The mean
proportion of HLA-DR/CD11b combination and CD13 on monocytes was higher in RAEB in comparison
to other MDS subtypes. In addition, the mean percentage of CD33 and CD14 on monocytes was lower
in RAEB than RA and RARS. But there was no significant difference in monocytic antigen expression
Variable Group Group P value
CD19/CD10-positive RA RARS 0.038
RAEB 0.027
RARS RA 0.038
RAEB 0.996
RAEB RA 0.027
RARS 0.996

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54
among MDS subtypes. We also showed the mean percentages of erythroid precursors CD markers in
different subtypes of MDS. The mean percentage of CD71, CD235a and combination of
CD71/CD235a on erythroid precursors was lower in RAEB in comparison to RA and RARS. Analysis
of erythroid antigens showed that, only the difference of CD71 on erythroid cells was statistically
significant between MDS subtypes. This difference was statistically significant only between RARS
and RAEB subtypes (p<0.011).Our results also, supported previous studies(23).
Changes in antigen expression pattern of the myeloid precursors in MDS cases have been
shown several times by different researchers (12, 13, 24-26). These characteristics have been shown
with a great frequency in MDS cases that are in a high grade such as RAEB cases (27). Some studies
showed enhance of CD34 density on the myeloid precursors in RAEB cases(28) (18). Samuel et al.
showed the CD13 expression on myeloid precursors was higher in RAEB cases, as compared to RA
and RARS cases (22). Kussick et al, used 4-color flow cytometric analysis, conducted the most
extensive evaluation of myeloid precursor’s phenotypic changes in MDS. They found that, the
abnormal expression of HLA-DR, CD13, CD33, CD38, and CD117 on myeloid precursor was occurred
in 50% or more of cases. In addition, they showed a declined mean percentage of CD33 and HLA-DR
and raised mean proportion of CD13 on myeloid precursors in RAEB subtypes(12).Samuel et al.
demonstrated similar phenotypic abnormalities with frequencies that were subtype related. These
abnormalities were included increased expression of CD13 and CD34 on myeloid precursors. They
found that, the most frequent changes in RA, RARS, and RAEB subgroups were increased density of
CD34 and CD117 or combination of CD34/CD117. They also indicated abnormal expression of CD34
and CD117 were presented in 50% of RARS, and 100% of RAEB cases (22). In fact, increased
density of CD34 and CD117 on myeloid precursors was common findings in AML and has been
proposed as valuable aids for detecting minimal residual disease (29, 30). In this study, the mean
percentage of CD33 on myeloid precursors was lower in RAEB in comparison to other MDS subtypes.
In addition, the mean percentage of CD13 on myeloid precursors was higher in RAEB than RA and
RARS. In MDS subtypes, there was an increase in percentage of HLA-DR/CD11b
,
combination and
CD117 on myeloid precursors in RAEB subtypes, as compared to RARS and RA groups. But there
was no significant difference in monocytic antigen expression among MDS subtypes. These results
support the idea that the maturity of cells in RAEB subtype is lower than in RA and RARS subtypes, as
well, may show that RAEB cases have higher risk for progressing to AML, as compared to RA and
RARS subtypes. These findings, also, indicates the association of these disorders with AML. In fact,
these abnormalities have been detected in high frequency. As a result, it can show the efficacy and
importance of these measurements in flow cytometric diagnosis of MDS, as well, may show that
phenotypic abnormalities can be subtype related. Indeed, MDS patient’s prognosis is really varied.
Although, recent prognostic classifications for example IPSS and WPSS are really useful they are not
practical to be used in all subgroups of patients. As a result, more research in the area of the
molecular pathogenesis of each subgroups also biomarkers those are responsible for pathogenesis
are needed. On the other hand, being familiar with these biomarkers can lead to find the more suitable
therapeutic approaches(31). Different studies showed RA and RARS cases higher median survival
also lower risk of progressing to AML in compared to RAEB cases. This shows that RA and RARS
cases have a better prognosis than RAEB cases (9, 31-34).
As mentioned above, different studies also our results about antigen expression pattern of MDS
subtypes showed more abnormality and lower maturity in RAEB subtypes, as compared to RA and
RARS subtypes. On the other hand, RAEB cases showed the lower median survival and higher risk
for progressing to AML as compared to RA and RARS subtypes. These results combined together can
support the idea that cases with higher abnormality in antigen expression pattern have higher risk for
progression to AML and less median survival. As a result, these cases have worse prognosis. This
shows the importance of immunophenotyping and knowing about the antigen expression pattern of
MDS subtypes.
This study, showed the range of different CD markers on myeloid, erythroid and lymphoid
lineages of MDS subtypes. Also, abnormalities in antigen expression pattern of MDS subtypes were
shown. In fact, our results can be useful for understanding the prognosis of each subtypes and
interpretation of laboratory and clinical findings, also, can help to find more appropriate therapeutic
approaches for each patient. Although, the project was successfully completed some limitations were
observed. In the end, our study was limited by its small sample size and the lack of samples
throughout Malaysia. Having a reference of antigen expression pattern can be useful for estimating
disease grade in MDS and can help to predict clinical outcomes of these patients.

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ACKNOWLEDGMENTS
We would like to thank Dr Raudhawati Osman as the head of the haematology unit in Hospital
Kuala Lumpur for allowing us to collect and conduct this study and Madam Lee Siew Moi, for the
assistance in sample collection.
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