Mononuclears Size-Distribution as Marker of Acute Leukemia

Mononuclears Size-Distribution as Marker of Acute Leukemia G. I. Ruban*1, N. V. Goncharova2, D. V. Marinitch3, V. A. Loiko4 Physical Optics Department, B.I. Stepanov Institute of Physics of the National academy of sciences of Belarus, Nezaleznasti Ave. 68, Minsk, 220072, Belarus First-Third University/Affiliation 1, 4

Center of Transfusiology and biomedicine technologies, Ministry of Health of Belarus, Dolginoyski Tract, 160, Minsk, 220053, Belarus 2, 3

ruban@dragon.bas-net.by; 2ksju2006@gmail.com; 3ddna@mail.com; 4loiko@dragon.bas-net.by

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Abstract Acute leukemias (AL) is a grope of a diseases of particular interest due to rapid onset, the necessity of quick, adequate therapy and prognosis assessment. The latter is based on the biology of blasts cells, primary tumor cell mass, kinetics of treatment response, patient’s age, cytogenetics and molecular prognostic markers. The main goal of such efforts is to detect and monitior minimal residual disease (MRD). Currently morphological, immunological and molecular techniques are being used. However sometimes these facilities are insufficient for correct detection and monitoring of MRD. We have established the significant difference between the size distribution of viable unstained peripheral mononuclears in AL patients, patients with systemic inflammatory response syndrome (SIRS) and healthy individuals. This method can be proposed as an auxillary tool in AL prognosis assessment. The study was approved by the Ethics Committee of the Center of Transfusiology and Biomedicine Technologies, Ministry of Health of Belarus.

Keywords Acute Leukemia; Mononuclears; Size Distributions

Introduction Acute leukemias are clonal malignant hematology neoplasms which are characterized by uncontrolled propagation and accumulation of leukemic blast cells in the bone-marrow and impaired production of normal cells (Jemal A, Thomas A, Murray T., 2002). The most useful classification system of acute leukemias is developed by the World Health Organization (WHO) (Vardiman J.W., Harris N.L., Brunning R.D., 2002; Arber D.A., Brunning R.D., Orazi A., 2008) and includes morphological, immunological and cytogenetic abnormalities. The French-American-British classification (Bennett J., Catovsky D., Daniel M., Flandrin G., Galton D., Gralnick H., Sultan C., 1976; Cui J.W., Wang J., He K., 2004) is mostly superseded by WHO classification but it often used as a preliminary classification for newly diagnosed patients. According the both classification systems, there are two main types of AL: acute lymphoid leukaemia (ALL) and acute myeloid leukaemia (AML). This division is the cornerstone in AL diagnostics. It determines the following choice of treatment.

As it was mentioned above, various techniques are applied to verify the diagnosis of AL, including morphology, immunophenotyping, cytogenetics, in situ hybridization, molecular probing, and others. Morphological approach is the most crucial one in the preliminary stage of the diagnosis. Later, in the remission stage of AL, various methods in combination are used to detect and monitor MRD, because any single test, as a rule, is insufficient to diagnose the latter.

Status of the Problem Molecular probing, immunophenotyping and other modern techniques leave some AL-diagnostics questions open.

Molecular probing is rather sensitive method, but it needs the presence of specific gene rearrangements and thus may provide controversary results (Hsiao A., Hunter M., Greiner C., Gupta S., Georgakoudi I., 2011). Moreover, quantitative-PCR (pomerase chain reaction) results are sometimes (about 4% of cases) non-interpretable for myeloid vs. T- or B- lymphoid lineage evaluation (Saussoy P, 2004). PCR-based techniques need in cell lysis, which International Journal of Advance in Medical Science, Vol. 3, No. 1—May 2015 2327-7238/15/01 001-12 © 2015 DEStech Publications, Inc. doi:10.12783/ams.2015.0301.01

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impedes morphological analysis and tumor cells count (Zhe X., Cher M.L., Bonfil R.D., 2011). Furthermore, the leukemic cells may accumulate in organs and tissues other than blood and bone marrow (Murphy M., 2011, Cronin D.M., 2009). These cells can gain quite different genetic features, because, generally speaking, genetic characteristics of primary tumor and their metastases do not necessarily coincide (Gerlinger M., 2012). So molecular probing for revealing the invaded cells based on genetic characteristics of primary tumor cells can be useless. It should be noted also that the genetic characteristics do not always correlate with disease progression; this requires, in some instances, additional search criteria of diagnostic and prognostic information (Zueva E.E., 2005). It is also noteworthy as well that the panel of marker genes for blood cancers is not yet exhausted and its application for the molecular probing is limited.

Immunophenotyping provides effective multiparametric analysis of cell populations in suspension on a cell-by-cell basis. It is increasingly being used to supplement the routine methods in diagnostic and prognostic information for acute leukemias. However, an interpretation of immunophenotyping results for cell lineage evaluation is complicated by expression of lymphoid-associated markers on myeloid blast cells and coexpression (Al-Mawali A., 2008; Lewis R.E., Cruse J.M., Sanders C.M., 2007) or by expression of myeloid markers on lymphoid cells (Suggs J.L., Cruse J.M., Lewis R.E., 2007). The interpretation is complicated also by the fact that the same combination of antigens can be found, rarely, on leukemic blasts and normal hematopoietic cells (Davis B.H., Foucar K., Szczarkowski W., 1997) as well as by presence of leukemia variants with an aberrant immunophenotype – without some lineage-specific markers (Movchan LV, Belevtsev MV, Savitskiy VP, 2010). For the leukemic cells in AML, the most consistently expressed antigens can be also regularly expressed by normal precursor cells of the hematopoietic lineage (Lewis R.E., Cruse J.M., Webb R.N., Sanders C.M., Beason K., 2007), thus complicating immunophenotypic analysis as well. The interpretation becomes still more complicated in multicolor immunophenotyping (Johansson U, Macey M., 2011; Mittag A, Tarnok A., 2009; Wang L, 2008).

As indicated above, some organs and tissues other than blood and bone marrow can be invaded by leukemic cells (Murphy M., 2011, Cronin D.M., 2009). These cells may have another immunophenotypic and genetic characteristics compared to bone marrow blasts (Cronin D.M., George T.I., Sundram U.N., 2009). Some invaded cells can appear in peripheral blood. All these circumstances further complicate interpretation of leukemic immunophenotype.

Substantial complication of the interpretation of the results, and considerable reducing their reliability can be caused by other factors as well. In particular, elements of immunophenotypic profile are changeable (Hings I., Kay N.E., Ranheim E., Seroogy C., Parson R.E., 1993; Kay N.E., Peterson L., 1991). Moreover, full immunophenotypic profile is changeable (from ALL to AML) (Park M., 2011; Hur M., 2001; Palomero T., 2006; Sakaki H., 2009; Murphy S.B., 1983) or vice versa, from AML to ALL (Ohsaka A.P., Kato K.K., Hikiji K.K., 1998). Leukemic-cell immunophenotype can be changable both in the course of disease progression and disease treatment, which causes false-negative or false-positive results (Hsiao A., 2011; Konrad M., 2003). Furthermore, immunophenotypic lineage switch can be abrupt, in particular, within several days (Murphy S.B., 1983; Hershfield M.S., 1984). Besides, the immunophenotyping method is inconclusive, now and then, in establishing the cell lineage (Saussoy P., 2004); tumor cells that do not express or express a low level of tumor antigens can escape immunophenotyping detection (Guadagni F., Roselli M., Schlom J., Greiner J.W., 1991). Finally, there are rare cases of acute undifferentiated leukemia in which the predominating cell lineage cannot be classified (Van't Veer M.B., 1992; ThalhammerScherrer R., 2002; Gluzman D.F., 2011).

Note also, cell labeling with fluorescence dyes is potentially toxic and it can interfere with normal cell functions (Katoh K., Hammar K., Smith P.J.S., 1999); both flow cytometry immunophenotyping and PCR can result in falsenegative finding due to cell clonal evolution (Neale G.A., 1999); both methods need expensive equipment, complex, and costly cell processing as well as highly trained personnel. Taken together, all abovementioned data suggest that diagnostics and monitoring of acute leukemia need, in some cases, an additional criterion of information.

Having analyzed the problem we hypothesize that mononuclear size distribution can be used as the criterion.

Indeed, size (as well as size control (Fang S-C., Reyes C., Umen J.G., 2006) is the fundamental characteristic defining cell function (Jorgensen P., 2004; Strange K., 2006; Tzur A., 2011). There is an intrinsic cell mechanism that maintains the size of the proliferating mammal cells (Tzur A., 2009). Size parameters of white blood cells have

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some diagnostics, prognostic, and survival-associated value for leukemia (Dubner H.N., 1978; Manocha S., 2003; Bassoe C.F., 1999; Terzakis J.A., 2005; Bittencourt A.L., 2007; Internet, 2013) and some other diseases (CampuzanoZuluaga G., 2010; Terzakis J.A., 2008; Lezvinskaya E.M., 2009; Han S.I., 2011; Perske C., 2011; Benattar L., 2001).

Further, as is well known, normal lymphoid and myeloid cells are different in sizes (some data about sizes and size distributions of normal lymphoid and myeloid cells as applied to flow cytometry conditions are in the papers (Loiko V.A., 2006; Ruban G.I., 2007); blast sizes differ from sizes of mature cells (Manocha S., 2003; Terzakis J.A., 2005; Lezvinskaya E.M., 2009). Therefore, blasts percentage, as well as belonging of the cells to myeloid or lymphoid lineage may influence cell size distribution. In leukemia, blast percentage increased. This increase, as we suppose, can be differently reflected in cell size distribution depending on myeloid, lymphoid or mixed nature of the blasts. It is reasonably to expect that cell size distribution can be, to some extent, an indicator of belonging of the cells to myeloid, lymphoid or mixed lineage. In other words, we expect that for given cell population, for example, for mononuclear cells, size distribution is a generalized indicator of blast percentage and myeloid or lymphoid nature of the cells.

This work is aimed to perform the comparative investigation of size distributions of peripheral blood mononuclears for the healthy individuals, and the patients with AML and ALL, using optical microscopy. Such a systematic study, to our best knowledge, has not been yet carried out. All microscopy measurements were carried out on the cells in suspension.

It is worth noting the fact is that known data on white-blood-cell sizes are basically obtained from blood smears (Pronk-Admiraal C., 2002; Atlas, 1987; Gulati G.L., 2008). The cell sizes, however, can be distorted in smears by the smearing and drying effect, as well as by adhesive interaction of cells with a substrate (Tzur A., 2009; Loiko V.A., 2006; Shaw M., 2013). Consequently, in the context of this study, mononuclears should be measured in suspension.

When cell size is determined in suspension, the known measurements are, however, indirect. Such cases take place for the Coulter counters, dielectrophoretic separators, and flow cytometers and some other devises. Although Coulter counters determine cell volume (and concentration in suspension) (Alexander H., 1992; Coulters, 1997), but the output signal of these counters is not directly related to the cell volume (Chalmers J., Haam S., Zhao Y., 1999).

In the dielectrophoretic separators (Han S.I., 2011), size determination of cells relies on their dielectric properties.

They, however, depend not only on the cell size, but also on cellular composition and cellular organization (Peter R.C., Xiao-Bo Wang G., Ying Huang, 1997) which may vary widely for different WBCs. In flow cytometers, size estimation is based on parameters of cell light scattering, usually forward scattering, FCS. This estimation rests on relations between size of a particle and intensity of light scattering at small angles, basing on the Mie theory for spherical homogeneous particle. But mononuclear cells, which we address in this investigation, have complex shape and constitution. In these cases, correlation between cell size and light scattering may be more complex and ambiguous. For this and some other reasons, there is disagreement as to what kind of parameres of scattering correspond to cell size in the best way: some authors consider the forward scattering (FCS) as an indicator of the cell size while new publications consider side scattering SSC as more adequet one (Tzur A., 2011). Moreover, none of the optical parameters investigated in four cell types provided the best indication of cell volume for all cell types (Tzur A., 2011).

In such a situation, one can anticipate ambiguous results of the MNCs-size estimation (on the base of cell light scattering or other indirect methods of cell size determination).

It would be reasonable, therefore, to assess the size of the mononuclears (i) by a direct method, and (ii) for the cells in suspension. The goal of the work is just the direct microscopy investigation of size distributions of living suspended mononuclears for the healthy individuals and the patients with AML and ALL in the context of detection of the diseases. Important, we focus on the size distributions as features of mononuclear populations rather than on sizes of single cells no matter how large or small they are. Observe, too, morphometric data for MNCs can be of interest in other applications as well, e.g. in relation to (i) segmenting the images of leukemia cells in image cytometry (Prasad B., Badawy W., 2008; Markiewicz T., Osowski S., 2013; Ozaki Y., 2010) and (ii) to the solution of the inverse light-scattering problem for the identification of normal or pathological blood cells in scanning flow cytometry (Ruban G.I., 2007; Maltsev V.P., 2004; Berdnik V., 2004a; Loiko V.A., 2009; Berdnik V.,

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2006a; Berdnik V., 2006b; Berdnik V., 2004b).

Materials and Methods Twenty four blood and bone marrow samples from adult acute myeloid (AML) and acute lymphoid (ALL) leukemia patients (14 AML and 10 ALL) has been undergone investigation (Table 1).

Patients’s mean age was 61±1.7 The diagnosis was confirmed by morphological, cytochemical and immunological (immunophenotyping) methods. The following CD markers were used to distinguish the AL diagnosis (Table 2).

TABLE 1 THE DIAGNOSIS, STATUS, AND NUMBER OF PATIENTS

Diagnosis AML without Maturation AML with Maturation AML with Multilineage Dysplasia AML with Multilineage Dysplasia AML with Maturation AML with Maturation Acute Monoblastic Leukemia Acute Lymphoblastic Leukemia (ALL), L2 (FAB), Pro-B Variant

Status Primary Primary Following Chronic Myelomonocytic Leukemia (MDS/MPD) Following Myelodisplastic Syndrome Relapse I Relapse II Primary

Number 3 3

Primary

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1 2 1 1 3

TABLE 2 THE IMMUNOPHENOTYPING MARKERS USED IN AL DIAGNOSIS

Type of leukemia AML ALL

The CD panel CD 3; CD 7; CD 13; CD 14; CD 33; CD 34; CD 64; CD 117; Cytoplasmic Myeloperoxidase (MPO).

HLA-DR; Tdt; Surface and Cytoplasmic Immunoglobulin M (cyIgM); CD_1a; CD 2; CD 3; CD 5; CD 10; CD 19.

In one case, cytogenetics and molecular analysis were applied. In accordance with immunophenotyping analysis, the blast cells proportion was within range of 38-95%. Twenty six healthy individuals were used as a control group.

In order to emphasize the specifity of the size distribution in acute leukemias we also investigated the distribution in patients with systemic inflammatory response syndrome (SIRS) of bacterial origin. The samples of patients with SIRS were used as a peculiar kind of internal control in order to compare mononuclear size distribution in clonal and no-clonal leucocytosis. Blood samples of five such patients were used. The procalcitonin was used as diagnostic marker of SIRS (the threshold level of the marker was ≥ 0.5 ng/ml).

Only fresh cells of peripheral blood were undergone investigation. 5ml of venous blood was obtained after informed consent of the individuals. The samples were placed in sterile tubes containing preservative-free lithium heparin (20 U/ml), layered on a Ficoll-PaqueTM PLUS (1.077 g/cm3; GE Healthcare Bio-Sciences AB) and centrifuged at 300 g for 30 min at room temperature.

The low-density mononuclear cells (MNCs) were accumulated at the Ficoll-Paque interface, collected and washed twice in phosphate-buffered saline (PBS) containing 0.5% heat-inactivated embryonic calf serum (FCS;HyClone; Logan, Utah) and resuspended in PBS with 1% bovine serum albumin (BSA, Serva, Germany).

The viability of the isolated cells was determined by a standard technique with trypan blue stain (Sigma). The viability tested for 500 to 600 cells for each probe was no less than 98 - 100% in healthy individuals and about 94% in patient samples. Final MNCs concentration in suspension was about 1•106 /ml.

In case of healthy individuals, populations of isolated MNCs were determined by direct immunophenotyping.

5•105 cells were stained with monoclonal antibodies (moAbs) labeled with fluorescence dyes. FITS (Fluorescein Isothiocyanate) and PE (Phycoerythrin) were used as fluorescence dyes for the IgG1 isotypic moAbs against CD14 and CD45 (Beckman Coulter), respectively. MoAbs were used at saturating concentrations. The staining was performed in 100 μl of PBS containing 1% BSA with the moAbs for 30 min at room temperature. To correct nonspecific staining of the cells, the reagents for blocking Fc-receptors were added to, and mixed carefully with,

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the samples. The samples were then washed twice with PBS containing 0.1% azide. For negative (isotypic) control, the cells were incubated with mouse immunoglobulin IgG1 conjugated with FITS (IgG1-FITS, Beckman Coulter) and PE (IgG1-RE, Beckman Coulter) for 30 min at room temperature and then washed twice by PBS with 0.1% azide. Cell fluorescence and autofluorescence intensities were measured by flow cytometry, using a FACScan instrument (Becton Dickinson). To detect cell autofluorescence, the unstained MNCs were used. The intensity of autofluorescence was used as a threshold value to cut off the cells with low intensity fluorescence, i.e. about 10 times smaller than the intensity of autofluorescence. Forward light scattering (FSC) and side light scattering (SSC) intensities were also measured by FACScan. Finally, the flow cytometry data were analyzed using the CellQuest software (Becton Dickinson). Populations of MNCs were determined after software logical gating on the basis of their FSC, and SSC parameters and CD14, and CD45 expression. Purity of MNCs populations isolated for analysis was 94% or more. The number of the cells analyzed per individual was 3•104. The study was approved by the Ethics Committee of the Center of Transfusiology and Biomedicine Technologies, Ministry of Health of Belarus.

For morphometric investigation, mononuclears of healthy individuals or patients were isolated at above mentioned density gradient. The cells size of the isolated living mononuclears was measured in cell suspension.

The measurements were made by methods of light microscopy, using a Leica DMLB2 microscope. A cellular suspension was hermetically sandwiched between the object plate and a slip cover glass as in a microcuvette.

The microscope was used in bright field (BF), differential interference contrast (DIC), and fluorescence (F) modes.

The lens with 100x magnification and numerical aperture of 1.25 was used with an oil immersion.

The cell micrographs were made by microscope-mounted digital camera DC 150 with 5 MPixels matrix. We used Leica image processing software IM 1000 to measure the size of the optical image of the cell. The calibration of the sizes was made by a Leica test object. The two-dimensional images of cells in the BF and F modes, and quasi threedimensional images of cells in the DIC mode were analyzed. Maximal linear size of the cells was measured. The number of cells measured for each patient and healthy individuals were 400 to 1050 and 400 to 3000, respectively.

Note, the approach involved enables one measuring just the cells rather then cell fragments or debris. This is especially important to ensure data validity on left wing of the size distribution, for small cells.

In healthy individuals, the mononuclears were recognized, by CD45-FITS and CD14-PE staining, (taking into account mean fluorescence intensity (MIF) and gating on FSC and SSC) as lymphocytes and monocytes, respectively. Next the identified lymphocytes and monocytes were measured separately. Out of measured lymphocytes and monocytes of healthy individuals, we then selected the 3 populations with different percentage of monocytes and lymphocytes within the normal ranges. The selected populations were used as 3 reference points, for minimal, maximal and middle content of lymphocytes (or monocytes) among normal mononuclears, respectively. The reference points were used for subsequent comparison with the populations of mononuclear cells of the patients.

As mentioned above, the mononuclear cells of healthy individuals were separated into lymphocyte and monocyte populations that are recognized by means of the fluorescent labels. Accordingly, to measure mononuclears of healthy individuals, each field of view of the microscope was displayed twice: first to identify lymphocytes and monocytes (in the F microscope mode) and another time to measure their parameters (in the DIC mode). The patients’ mononuclears were measured one after another, without recognizing their subpopulations. The DIC micrograph for mononuclears of a patient with AML is shown in Figure 1.

Results and Discussion Mononuclear cells' size distributions (MSDs) measured by DIC microscopy for the living cells of the healthy individuals are presented in Figure 2. The distributions are shown for different percentages of monocytes and lymphocytes within the range of their changing in the peripheral WBCs in normal cases. The cell size was detected as a maximal linear one (maximal diameter).

For healthy individuals, one can see the bimodal distribution of MNCs with large and small size modes (Figure 2).

This Figure demonstrates: shifts of the maxima relative to each other are the negligibly small values and the maxima positions for the large size modes practically coincide. The same behavior takes place for shifts of the

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maxima for small size modes relative to each other. So the maxima positions of normal mononuclears on the size axis for both cell modes are rather stable. Importantly, this stability takes place for different percentages of monocytes and lymphocytes within the whole range of their changing in peripheral WBCs in the normal cases.

That means that these mode positions would potentially serve as references for distribution of the cells for patients with leukemia. The above demonstrated stability of the maxima are in accordance with the known data on stable location, in the space of histogram for forward / sideward scattering (FSC / SSC), of the main populations of the non-transformed leukocytes of patients with documented absence of pathology (Zueva E.E., 2005). The positions of both wings of the MSDs are also rather stable.

FIGURE 1. MICROGRAPH OF THE LIVING MONONUCLEAR CELLS FOR A PATIENT WITH AML

FIGURE 2. HISTOGRAMS OF THE MAXIMAL LINEAR SIZES OF THE NORMAL CELLS WITH DIFFERENT MONOCYTES (Mo) AND LYMPHOCYTES (Ly) PERCENTAGE AS VARIANTS OF NORMAL MONONUCLEARS: 11% Mo / 19% Ly (GREY), 7% Mo / 28% Ly (WHITE), 3% Mo / 37% Ly (HATCHED). THE CELLS FOR 26 HEALTHY INDIVIDUALS ARE SHOWN

Some of mononuclear size distributions measured by DIC microscopy for the living cells for the leukemia patients are presented in Figures 3, 4. In contrast to the healthy individuals, MNCs of about 90 % AML samples show one uniform population of the cells without explicit indications of size distribution bimodality; these results are in accordance with the data for AML cells (ML-1) measured with the Coulter counter (Mazur L., Opydo-Chanek M., Wojcieszek K., 2012). The Maxima of the MSDs for AML samples are shifted as compared to the healthy ones. The shifts are vastly larger than the above-mentioned negligibly small values for the healthy individuals. The wings of the MSDs for AML samples are also substantially shifted as compared to the healthy ones. The distribution width increases with appearance very small and very large cell modes. Note, our data guarantee that these “marginal” groups of cells are really the mononuclears, rather than any cell fragments and debris. As for MNCs of ALL samples, some of them show uniform (monomodal) population of the cells as well as size shift of the distribution maxima as compared to the normal. Others MNCs of ALL samples show bimodal cell distribution, but maxima of one or both modes have a size shift as compared to normal.

Thus, there is a significant difference between “normal” and AL distribution of mononuclears.

Normal: The bimodal distribution of MNCs with large and small size modes has stable positions for both modes on the size axis of the cell distribution.

AML: The maximum and the wings of the monomodal MSDs are shifted as compared to healthy ones. The AML distribution width increases with appearance very small and very large cell subpopulations.

ALL: ALL samples show monomodal or bimodal MNCs distributions. Monomodal MNCs demonstrate size shift of the distribution maximum in comparison with the normal cells. For bimodal MNCs, maxima of one or both cells modes also have a size shift as against the normal cells of healthy individuals.

We would like to draw attention also to the non-clonal leucocytosis occurred in septic conditions (SIRS). It should be noted the essential shift of mononuclears’ distribution to the larger cells sizes. The bimodal shape of the histogram is kept almost unchangeable. (Figures 5 and 6).

Figures 2-6 display the significant difference between the size distribution of the viable unstained peripheral mononuclears in AL patients, patients with systemic inflammatory response syndrome (SIRS) and the healthy

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individuals.

FIGURE 3. HISTOGRAMS OF THE MAXIMAL LINEAR SIZES FOR MONONUCLEARS OF PATIENT WITH AML (BLACK COLUMNS) AND HEALTHY INDIVIDUALS (GREY, WHITE AND HATCHED COLUMNS)

FIGURE 4. HISTOGRAMS OF THE MAXIMAL LINEAR SIZES FOR MONONUCLEARS OF PATIENT WITH ALL (BLACK COLUMNS) AND HEALTHY INDIVIDUALS (GREY, WHITE, AND HATCHED COLUMNS)

FIGURE 5. HISTOGRAMS OF THE MAXIMAL LINEAR SIZES FOR MONONUCLEARS OF THE AML PATIENT (BLACK COLUMNS), A SEPSIS PATIENT (WHITE COLUMNS ), AND NORMAL (GREY COLUMNS )

FIGURE 6. HISTOGRAMS OF THE MAXIMAL LINEAR SIZES FOR MONONUCLEARS OF THE ALL PATIENT (BLACK COLUMNS), A SEPSIS PATIENT (WHITE COLUMNS), AND NORMAL (GREY COLUMNS )

Known systematic data on directly measured suspended MSDs in leukemia samples are absent, to our knowledge.

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The comparison of our results for ALL and AML samples with the available data (mean ALL-cell size and known Coulter-counter mean volume data for ALL samples (Chapman E.H., Kurec A.S., Davey F.R., 1981), converted by us into an equivolume sphere diameter) show good correlation. The comparison our results for AML samples with the available data of Coulter counter (Tzur A., 2011) regarding to the size range of the cells.shows good and satisfactory agreements for upper and lower limits of the ranges, respectively. The differences (9% and 24%, respectively) are likely to be owing to the facts that (i) the output signal of the Coulter counters is not directly related to the cell volume and (ii) the Coulter data relate to the cultured cells (HL60). Note also, the size range of the AML-patient mononuclears (Figure 3) can be much broader than that of blood smear mieloblasts, 15-20  m (Atzell J., Perkins S.L., 2011).

AFM data (Rosenbluth M.J., Lam W.A., Fletcher D.A., 2006) on the mean sizes for the myeloid and lymphoid cells are larger than our corresponding values at 19 and 33%, respectively. The differences may be due to the fact that AFM data refer to the cultured cells (HL60, myeloid ones; and Jurcat, lymphoid ones) and the number of the cells measured by AFM is small to represent adequately the population of the cells.

So the distributions, in accordance with the findings, substantially differ in AL patients, patients with systemic inflammatory response syndrome (SIRS), and the healthy individuals. Our DIC-microscopy measurements for living blood cells show that mononuclear size distribution can be used as the provisional criterion to detect individuals with acute lymphoid leukemia and acute myeloid leukemia. MSDs measuring are useful also for leukemia monitoring.

Conclusions Mononuclear size-distributions measurements – available with simple blood analyzers – are proposed as a simple and inexpensive method in assessment of the leukemia status in acute leukemias. The mononuclear sizedistribution data can be useful for leukemia (MRD) monitoring. Our approach gives additional characterization of the mononuclear cell populations and can supplement the known techniques to increase their validity.

The advantage of the method is that it does not need in cell labeling which is potentially toxic or interferes with the normal cell functions. The further investigations will help to determine the usefulness of this approach in experimental work and clinical practice.

ACKNOWLEDGMENT

The study was fulfilled in the frame of Scientific Programs of the Republic of Belarus, “Modern technologies in medicine 4-14”, and “Electronics and photonics 2.1.07”.

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