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Research Article
Lymphocyte Transformation Test Based on Lymphocyte Changes
Observed by a Hematology Analyzer before and after
Phytohemagglutinin Stimulation
Lulu Zhang , Tinghua Feng , and Hui Liu
College of Medical Laboratory, Dalian Medical University, Dalian, China
Correspondence should be addressed to Hui Liu; immunology@dmu.edu.cn
Received 3 July 2022; Revised 6 October 2022; Accepted 19 October 2022; Published 7 November 2022
Academic Editor: Benoit Dugue
Copyright © 2022 Lulu Zhang et al. This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Objective. The lymphocyte transformation test is a classical test for the detection of cellular immune function and is based on
subjective judgment. In this study, we have established an objective novel lymphocyte transformation test using the
hematology analyzer to observe lymphocyte transformation. Methods. Whole blood cells were cultured using a whole blood
method with a lymphocyte culture medium; phytohemagglutinin was used to stimulate the experimental samples, and control
was set up at the same time. After the whole blood cells were cultured, the number of lymphocytes in the two groups was
observed using a hematology analyzer, and the conversion rate was calculated. The new method was used to observe
differences in lymphocyte conversion in the peripheral blood of patients with hematopathy and healthy persons. Results. There
were significant differences between the stimulated peripheral blood group and the blank group. The transformation rate of
peripheral blood lymphocytes in patients with hematopathy was significantly lower than that in healthy persons; the difference
was statistically significant (P<0:05). Conclusion. Lymphocyte transformation can be observed using a hematology analyzer.
The lymphocyte transformation test that is based on the determination of lymphocyte count by a hematology analyzer has
important clinical value.
1. Introduction
There are two types of immune response in humans [1]. One
arm is the humoral immune response, involving B cells that
recognize circulating antigens or pathogens in the lymph or
blood, and the second arm is the cell-mediated immune
response that mainly involves T cells and responds to viral
cells, tumor cells, or transplants [2].
Cellular immunity is an important type of adaptive
immune response [3]. The biological significance of this type
of immunity is that immune cells can effectively eliminate
antigenic foreign bodies in the body by recognizing “self”
and “non-self”to maintain the relative stability of the internal
environment of the body [4]. The evaluation of cellular
immune function mainly includes assessing the lymphocyte
count and lymphocyte function test [5]. Counting the number
of lymphocytes includes the detection of CD antigen and
classification and counting of lymphocyte subsets. Such
methods only reflect the number of lymphocytes, but not their
function; the detection of which is more important.
In vitro measurement of cellular immune function
requires firstly obtaining lymphocytes from peripheral blood
of humans or animals, followed by subsequent experiments,
including the T lymphocyte proliferation test. The lympho-
cyte transformation test is a method to determine the func-
tion and state of immune cells in a certain organism by
stimulating the proliferation of lymphocytes [6]. The princi-
ple of this test is that the metabolism and morphology of T
cells change after being stimulated by antigens or mitogens
in vitro, which is mainly manifested as increases in protein
and nucleic acid synthesis, a series of proliferation reactions,
and transformation into lymphoblasts [7]. The T lympho-
cyte transformation rate reflects the cellular immune status
of the body [8].
Hindawi
Disease Markers
Volume 2022, Article ID 5967429, 7 pages
https://doi.org/10.1155/2022/5967429
The lymphocyte transformation test technique mainly
involves morphological examination, the
3
H-TdR method
and methyl thiazolyl tetrazolium colorimetric analysis
(MTT assay) [9, 10]. The
3
H-TdR approach works on the
principle that DNA synthesis involves
3
H-TdR absorption
during transformation of T cells into lymphoblastic cells,
and the degree of transformation is proportional to uptake
of
3
H-TdR [11]. Although the
3
H-TdR is objective and accu-
rate, there is a potential danger of radioactive contamina-
tion; it also requires certain equipment conditions. The
MTT has a strong nonspecific reaction and high background
[12]. The results of the morphological examination are
greatly influenced by subjective factors, and its reproducibil-
ity is poor; hence, low efficiency of determination is inevita-
ble. Therefore, none of the mentioned methods is ideal,
which impedes the evaluation of cellular immune function.
In this study, we attempt to conduct lymphocyte transfor-
mation tests based on morphology using a hematology ana-
lyzer so as to make the findings more objective, trustworthy,
and stable.
2. Methods
The study was conducted in accordance with the principles
and guidelines laid down in the Declaration of Helsinki.
The Dalian Medical University Ethics Committee approved
the study and waived the requirements for written informed
consent, since the samples were remnants following clinical
use and therefore not specifically collected for this study
and no risk to patients was involved.
Lymphocyte function was assessed by measuring lympho-
cyte proliferation in response to mitogen phytohemagglutinin
(PHA) [13]. T cells were stimulated in vitro using a T
lymphocyte-sensitive stimulant, such as phytohemagglutinin-
P (PHA-P) [14, 15]. T cells undergo morphological and bio-
chemical alterations when activated. Some small lymphocytes
are transformed into immature lymphocytes or blast cells,
which undergo mitosis and proliferation. The percentage of
lymphocytes was found to increase when the automated hema-
tology analyzer calculated the proportion of lymphocytes. As a
result, the rate of lymphocyte transformation can be measured
(Figure 1).
2.1. Morphological Method. Using the whole blood method,
1.8 mL of 10% bovine serum was added to the RPMI 1640 cul-
ture medium, and then, 0.2 mL of EDTA anticoagulated whole
blood (sample to be tested) along with 0.1 mL PHA-P (Solar-
bio origin: Beijing article number: p8090 specification: 5 mg)
(1 mg/mL) was added to the culture dish. After 72 hours of
culture in a 5% CO
2
incubator, some of the cells were centri-
fuged and the supernatant was removed. A smear was made
and stained with Giemsa stain, the morphological changes in
lymphocytes were observed under a microscope, and the per-
centage of lymphoblasts in 200 lymphocytes was calculated.
2.2. Hematology Analyzer Method. We added 160 μLof1640
culture med ium (10% bovin e serum), 40 μL of EDTA anticoa-
gulated whole blood (sample to be tested), and 20μL of PHA-
P (1 mg/mL) into a 96-well clear flat bottom TC-treated
microculture plate; each sample (220 μL) was tested three
times in three wells of the microculture plate at the same time
(Table 1). At the same time, in the blank or control sample,
PHA was replaced with normal saline. Subsequently, culture
in a 5% CO
2
incubator for 72 hours was performed, mixed,
and blood cells were tested with an automated hematology
analyzer (Mindray, Shenzhen, China).
Thelymphocytetransformationrateiscalculatedasfollows:
lym%PHA group
ðÞ
−lym%blank group
ðÞ
lym%PHA group
ðÞ× 100%:ð1Þ
2.3. Hematology Analyzer and Morphological Comparison. A
total of 55 healthy individuals were randomly selected from
the Lushun People’s Hospital in Dalian, China. Individuals
in this random sample were aged between 20 and 40 years
PHA
Aer
72 h
Normal saline
Figure 1: The lymphocyte transformation using a hematology analyzer.
Table 1: The trial dose added to each hole in the lymphocyte
transformation test.
Group 10% 1640 (μL) Blood (μL) PHA-P (μL) Saline (μL)
Blank 160 40 0 20
Test 160 40 20 0
2 Disease Markers
(27 males and 28 females). For the lymphocyte transformation
test, whole blood collected in EDTA-coated tubes was used to
obtain a complete blood count using a hematology analyzer.
All experiments were carried out using the same procedure
(Table 1). The results were compared to those produced using
the morphological counting approach and analyzed.
2.4. Stability Test. A healthy volunteer was chosen from whom
peripheral blood was collected for five consecutive days in
EDTA-coated tubes, and complete blood counts were deter-
mined using a hematology analyzer. All experiments were car-
ried out using the same protocol (Table 1). The volunteer
followed the same routine so as to maintain the same physio-
logical condition for five consecutive days. Toassess the stabil-
ity of the hematology analyzer measurements, the coefficient
of variation (CV) was computed.
2.5. Gender Comparison Testing. A random sample of 22
healthy men and 25 healthy women was obtained from the
Lushun People’s Hospital in Dalian, China. Individuals in this
study’s random sample were aged between 20 and 40 years.
Venous blood samples were collected in EDTA-anticoagulated
tubes. The experimental procedure was the same as described
in Table 1. The results of lymphocyte transformation in males
and females were compared.
2.6. Age Group Comparison. The study involved 20 healthy sub-
jects, aged >60 years (mean age, 84 years), 30 healthy subjects,
aged 20 through 40 years, with equal distribution of men and
women. The random samples were provided by the Lushun
People’s Hospital in Dalian, China. The experimental procedure
was the same as described in Table 1. The results of lymphocyte
transformation in different age groups were compared.
2.7. Clinical Specimen Test. The hematological disease group,
which included leukemia and malignant lymphoma, was
classified according to the World Health Organization clas-
sification of hematological malignancies. The inclusion cri-
teria for leukemia were as follows: hospitalized patients
with ≥20% blasts in blood or bone marrow smear and age
>18 years [16]. A total of 28 participants (20 males and 8
females; age range, 29–74 years; mean age, 51 years) in the
leukemia group were included. The inclusion criteria for
malignant lymphoma were as follows: hospitalized patients
who on lymph node biopsy were diagnosed lymphoma
(Hodgkin’s or non-Hodgkin’s) and age>18 years [16]. A
total of 16 participants (9 males and 7 females; age range,
25–77 years; mean age, 60 years) in the malignant lym-
phoma group were included.
The normal blood samples were obtained from healthy
individuals subjected to routine physical exams. The inclusion
criteria were routine blood tests and blood biochemical tests
were within the normal range and age > 18 years. A total of
30 participants (14 males and 16 females; age range, 25–84
years; mean age, 60 years) in the healthy group were included.
The samples were collected from the second department of the
First Affiliated Hospital of Dalian Medical University. The
experimental procedure was the same as mentioned.
2.8. Statistical Analysis. Analysis of variance was used to
compare the means of multiple groups; an independent sam-
ple t-test was used to compare the mean of the single group;
K-S analysis and Q-Q chart were used to test the normal dis-
tribution. Statistical significance was set at P<0:05. SPSS
17.0 (IBM, Armonk, New York, USA) statistical software
was used for the mentioned analysis.
3. Results
3.1. Morphological Count and Hematology Analyzer. Lympho-
cyte morphological alterations were observed by
Figure 2: Whole blood was stimulated using PHA-P and cultured
for 72 h (morphological counting method).
Table 2: The result of lymphocyte transformation in a healthy
person.
Group N
Lympercent
(%) Lymphocyte transformation
rate (%)
Mean SD P
Blank 55 15.65 9.46 <0.001 57
PHA 55 37.04 12.65
Table 3: Test results for five consecutive days.
Date Rate (%) Mean (%) SD CV (%)
First 77
74 4.8 6
Second 80
Third 70
Fourth 69
Fifth 72
Table 4: Analysis of results of lymphocyte transformation test in
male and female.
Group NTransformation rate (%) SD tP
Males
Females
22
25
48
56
0.32
0.28 0.878 0.385
Table 5: Analysis of results of lymphocyte transformation tests in
various age groups.
Group NTransformation rate (%) SD tP
Young adults
Aged adults
30
20
56
48
0.28
0.36 0.825 0.413
3Disease Markers
morphological counting under a microscope (Figure 2). The
lymphocyte transformation rate was found to be 60%–80%
after counting.
The lymphocyte ratios were detected using the hematol-
ogy analyzer (Table 2). The lymphocyte ratios of 55 healthy
persons in the experimental group were significantly higher
than those in the control group (P<0:001). Table 2 presents
the lymphocyte conversion rates of 55 healthy individuals as
measured by the hematology analyzer. The results obtained
by the hematology analyzer method were essentially similar
to the lymphocyte transformation rate as determined by
the morphological counting method.
3.2. Stability Results. For the same volunteer, the lymphocyte
transformation rate in the peripheral blood was measured
for five consecutive days (Table 3). The lymphocyte transfor-
mation rate was found to be between 60% and 80% and the
coefficient of variation (CV) was 6%.
3.3. Lymphocyte Transformation Tests according to Gender.
In the gender comparison experiment, the mean percentages
of lymphocytes in the male blank and experimental groups
were 14.848 and 37.276, respectively. The mean percentages
of lymphocytes in the female blank and experimental groups
were 20.409 and 34.605, respectively. The lymphocyte con-
version rates of males and females are shown in Table 4.
The transformation rates of the two groups were similar,
with no significant differences (P=0:385).
3.4. Lymphocyte Transformation Tests according to Age. In the
comparison experiment for different age groups, the average
percentage of lymphocytes in the blank group of the younger
age group was 15.300 and in the experimental group was
0
0
0.2
The expected normal value
0.4
0.6
0.8
1
1.2
Leukemia group
0.2 0.4 0.6
Observed value
0.8 1 1.2
Figure 3: Normal distribution test Q-Q chart of the leukemia group.
0
0
0.2
The expected normal value
0.4
0.6
0.8
1
1.2
Malignant lymphoma group
0.2 0.4 0.6
Observed value
0.8 1
Figure 4: Normal distribution test Q-Q chart of the malignant lymphoma group.
4 Disease Markers
36.973. The average percentage of lymphocytes in the blank
group of the elderly group was 17.840 and in the experimental
group was 35.455. The lymphocyte conversion rates of the
younger and elderly groups are shown in Table 5. The conver-
sion rates of the two groups were similar with no significant
differences (P=0:413).
3.5. Normal Distribution Test of Blood Samples in Patients and
Healthy Persons. Forty-four patients’(28, leukemia; 16, malig-
nant lymphoma) and 30 healthy persons’data were analyzed
by normal distribution Q-Q chart (Figures 3–5). Pvalues of
the normal distribution K-S test in the leukemia, lymphoma,
and healthy groups were 0.305, 0.272, and 0.641, respectively;
Pvalues were greater than 0.05, indicating that the three
groups were all in normal distribution.
3.6. Differences between Hematopathy Patients and Healthy
Persons. We compared the hematopathy group with the
healthy group (Table 6). There was a significant difference
in the mean lymphocyte transformation rate between
patients with hematopathy and healthy people (∗∗ P<0:01).
3.7. Patients with Different Hematopathies and Healthy
Persons. We compared the leukemia group and the lym-
phoma group with the healthy group (Table 7). The differ-
ences between the average lymphocyte transformation rate
of the leukemia and healthy groups (∗P<0:05) and those
between the lymphoma group and the healthy group
(∗∗P<0:01) were statistically significant.
4. Discussion
The hematological analyzer is one of the most commonly
used instruments for the detection and analysis of blood
abnormalities in medical laboratories at present [17, 18]. It
is easy to operate, fast to detect blood anomalies, and reports
many parameters. The results are accurate and reliable,
which greatly improves the efficiency and quality of hemato-
logical analysis [19]. In this experiment, the lymphocyte
transformation test was based on the analysis of blood cells.
The results were more accurate. Because morphology is
greatly influenced by subjective factors, poor repeatability,
and low detection efficiency when observing and counting
lymphoblasts, the correlation between the morphological
method and the hematology analyzer was not performed.
However, all transformed lymphocytes observed under the
microscope could be measured by the hematology analyzer.
The results obtained by the automated hematology analyzer
are largely similar to the morphological method, thereby
implying that the automated hematology analyzer can accu-
rately reflect lymphocyte transformation rate. The results of
the stability test obtained by the automated hematology ana-
lyzer revealed CV < 10%, indicating that the test is
repeatable.
We studied the lymphocyte transformation test data
from many healthy men and women to assess if the experi-
ment is modified by sex and age. Lymphocyte
0.10 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
0
−0.2
−0.4
0.2
The expected normal value
0.4
0.6
0.8
1
1.2
Observed value
Healthy group
Figure 5: Normal distribution test Q-Q chart of the healthy group.
Table 6: Transformation rate of hematopathy patients and healthy
persons (
X±S).
Group NTransformation rate (%) SD tP
Hematopathy
Healthy
44
30
42
60
0.36
0.18 2.870 0.005
Table 7: Transformation rate of different hematopathy patients
and healthy persons (
X±S).
Group NTransformation rate
(%) SD tP
Leukemia group 28 45 0.35 2.048 0.045
Lymphoma
group 16 36 0.38 2.936 0.005
Healthy group 30 60 0.18 ——
5Disease Markers
transformation rates in males and females were comparable,
with no significant variation (P>0:05). Next, we examined
the lymphocyte transformation test findings of people aged
between 20 and 60 years. The young and old groups’lym-
phocyte transformation rates were similar, with no signifi-
cant differences (P>0:05). These results show that gender
and age do not affect lymphocyte transformation rates.
Currently, phytohemagglutinin (PHA) and concanavalin
A (ConA) are some of the most often employed mitotic
stimulators in lymphocyte transformation experiments [20,
21]. PHA outperformed all other mitogens in inducing
mitosis in human peripheral blood cultures in experiments
where each mitogen was tested individually. Furthermore,
in the combined use of two mitogens, there was no reliable
combination to enhance mitotic stimulation [22]. PHA, a
mitotic lectin that binds to the TCR on T cell surfaces, is
identical to the receptor that recognizes APC surface ligand
[23]. The signaling cascade it initiates in lymphocytes can
activate particular molecules, such as p38-MAPK or the
transcription factor family and signal transducer and activa-
tor of transcription (STAT) pathway [24], resulting in cell
cycle entry and DNA replication [25].
This experiment provides good evidence of T cell abnor-
mality. Traditionally, RPMI 1640 culture medium (10% calf
serum should be prepared before use) and PHA-P stimulant
(1000 μg/mL was prepared with RPMI 1640 culture
medium) were commonly used for lymphocyte transforma-
tion test, which involves culturing the test sample under
the CO
2
cell culture shelves for 72 hours and observing
and counting the results under a microscope. We observed
that the hematology analyzer could check lymphocyte trans-
formation through the change in lymphocyte count, to make
the lymphocyte transformation experiment more stable and
objective, evaluate the cellular immune function of the body
more accurately, and provide reliable indicators for disease
diagnosis and related research.
Hematological diseases originate primarily in the hema-
topoietic system [26]. There are various kinds of blood dis-
orders that can be broadly divided into three categories:
red cell diseases, white cell diseases, and hemorrhagic and
thrombotic disorders. Common hematological diseases
include leukemia [27], multiple myeloma, and lymphoma
[28]; in blood diseases, changes in lymphocytes and immune
function are seen. Malignant cloning of hematopoietic stem
cells in patients with leukemia will lead to an increase in the
number of primitive blood cells and thereby decreased cellu-
lar immune function [29, 30]. In malignant lymphomas,
large numbers of proliferating abnormal lymphocytes lack
proliferative activity after antigen and mitogen stimulation,
which will lead to decreased cellular immunity [31, 32].
Therefore, the lymphocytes from leukemia and malignant
lymphoma patients may have a lower transformation rate
compared to healthy people. The lymphocyte transforma-
tion test is a routine test to detect cellular immune function.
If the lymphocyte transformation rate is taken as the evalu-
ation standard, the lymphocyte transformation rate of
patients with hematopathy would be lower than that of
healthy persons on analysis with a hematology analyzer,
which indicates that there is a significant difference in the
lymphocyte transformation rate between the patients with
hematopathy and healthy persons; the cellular immune
function of patients with hematopathy is obviously
decreased. This implies that the method of detecting lym-
phocyte transformation by a hematology analyzer is correct;
this has clinical significance for the observation, diagnosis,
and treatment of blood diseases.
Although this study has numerous strengths, it also has
some limitations. First, tritium is strictly controlled in China
because it is highly radioactive. Therefore, the
3
H-TdR
incorporation method could not be carried out in this exper-
iment, and the experimental results were not compared with
the
3
H-TdR incorporation method. Second, because the
experimental samples could not be preserved for a long time,
we could not continuously measure the lot-to-lot variability
of the samples. However, we measured the same volunteer
for five consecutive days, and the coefficient of variation of
the measured value for five consecutive days was 6%, which
shows that our experiment has a relatively good stability.
In conclusion, it is feasible to use a hematology analyzer
for the lymphocyte transformation test. The observation is
more accurate and convenient, and the experimental data
are more accurate as compared with conventional methods.
This novel method can be used in the diagnosis and treat-
ment of clinical diseases and related research. Therefore,
the determination of lymphocyte transformation by a hema-
tology analyzer has important clinical value.
Data Availability
The datasets generated and/or analyzed during the current
study are not publicly available but are available from the
corresponding author on reasonable request.
Conflicts of Interest
The authors declare that they have no conflicts of interest.
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7Disease Markers
