|Year : 2018 | Volume
| Issue : 2 | Page : 45-50
Discrepancies between DNA index by flow cytometry and cytogenetic studies in childhood B-Lymphoblastic leukemia
Nour Almozain1, Ayman Mashi2, Suleimman Al-Sweedan3, Asim Belgaumi4, Faisal Rawas5, Randa Alnounou5
1 Division of Hematology, Department of Pathology, King Saud University Medical City, Riyadh, Saudi Arabia
2 Hematology Section, Pathology Department, King Fahad Central Hospital, Ministry of Health, Jazan, Saudi Arabia
3 Pediatric Hematology/Oncology, King Faisal Specialist Hospital & Research Centre, Riyadh, Saudi Arabia
4 Division of Hematology Oncology, Sidra Medical and Research Center, Doha, Qatar
5 Department of Pathology and Laboratory Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
|Date of Web Publication||18-Jun-2018|
Dr. Randa Alnounou
Department of Pathology and Laboratory Medicine, King Faisal Specialist Hospital, Riyadh
Source of Support: None, Conflict of Interest: None
BACKGROUND: DNA index by flow cytometry (DNAI-FCM) is a rapid technique used in classification of acute B-lymphoblastic leukemia (B-ALL). The objective of this study is to estimate the reliability of FCM in the early classification of childhood B-ALL and to analyze the causes of discrepancies between the DNAI-FCM and the cytogenetic studies (CG) (Karyotype and Fluorescent in situ Hybridization [FISH]).
MATERIALS AND METHODS: DNAI-FCM and CG (Karyotype and FISH) were analyzed in 69 consecutive children, newly diagnosed with B-ALL in King Faisal Specialist Hospital and Research Centre between January 2013 and June 2014.
RESULTS: A statistically significant correlation existed between DNAI-FCM and CG (P = 0.001). DNAI-FCM was proportional to CG in 82.6% (57/69) of the cases. There was a discrepancy between the DNAI-FCM and the CG in 17.4% (12/69) of the cases.
CONCLUSION: DNAI-FCM shows 82.6% concordance with CG in childhood B-ALL with a predictive value of 81%. Discrepancies occur due to either the small size of the chromosome or due to insufficient genetic material representing the abnormality.
Keywords: Acute lymphoblastic leukemia, cytogenetic, discrepancy, DNA index, flow cytometry, lymphoblastic leukemia
|How to cite this article:|
Almozain N, Mashi A, Al-Sweedan S, Belgaumi A, Rawas F, Alnounou R. Discrepancies between DNA index by flow cytometry and cytogenetic studies in childhood B-Lymphoblastic leukemia. J Appl Hematol 2018;9:45-50
|How to cite this URL:|
Almozain N, Mashi A, Al-Sweedan S, Belgaumi A, Rawas F, Alnounou R. Discrepancies between DNA index by flow cytometry and cytogenetic studies in childhood B-Lymphoblastic leukemia. J Appl Hematol [serial online] 2018 [cited 2018 Dec 16];9:45-50. Available from: http://www.jahjournal.org/text.asp?2018/9/2/45/234551
| Introduction|| |
A cute lymphoblastic leukemia is the most common single malignant disease in childhood and also the neoplasm with the most significant therapeutic progress during the last three decades. The incidence of cytogenetic (CG) abnormalities in pediatric acute lymphoblastic leukemia (ALL) is 87.7%. Age <1 year and a white blood cell count >100 at diagnosis are strong predictors of treatment failure,, due to certain translocations such as t (4;11) and t (9;22) which predict unresponsiveness to conventional, intense cytostatic treatment , In contrast, age between 1 and 10 years and hyperdiploid leukemia are recognized as independent indicators of good treatment outcome using standard protocols., Therefore, when stratifying patients into future treatment protocols, it will be important to reliably and rapidly determine the ploidy of the leukemic cells at diagnosis. The traditional way is karyotyping of cultured bone marrow cells with light microscopic counting of Giemsa-banded metaphase chromosomes. However, CG techniques are notoriously cumbersome, time-consuming, and technician dependent, as ideally, 20 metaphases should be studied and in order to call a numerical change clonal, at least two cells showing the same abnormality are obligatory, and the demand is three cells in the case of whole chromosome losses. However, in real practice, <20 cells are usually studied, and the low number of metaphases studied makes this technique fairly insensitive. The second approach is DNA content measurement by flow cytometry (FCM), which is more rapid and reproducible technique.
The aim of this study is to correlate the CG techniques (karyotype and fluorescent in situ hybridization [FISH]) with the DNA index measured by the FCM (DNAI-FCM). The clinical significance of this study relies on the conceivable idea that numerical chromosomal aberrations by CG would logically show correspondent differences in cellular DNA content by FCM. Validation of this concept will make the FCM a reliable and acceptable rmethod for a rapid quantitative detection of chromosomal abnormalities of leukemic cells in patients with childhood acute lymphoblastic leukemia B–ALL, which will help in their early classification and enrollment into the appropriate therapeutic regimen. In this study, we will calculate the concordance between the two techniques and we will try to analyze the causes of discrepancies.
| Materials and Methods|| |
This is a retrospective study which analyzed DNAI-FCM and CG (Karyotype and FISH) in 69 consecutive children, newly diagnosed with acute B-lymphoblastic lymphoblastic leukemia (B-ALL) in King Faisal Specialist Hospital and Research Centre between January 2013 and June 2014.
Bone marrow aspirate and/or peripheral blood of newly diagnosed leukemia were stained using whole blood method 8-color leukemia panel. The panel was run on BD FACSCanto II equipped with three lasers using BD FACSDiva software (Becton Deckinson and company, BD Biosciences, san Jose, CA 95131 USA). The pre-B-cell blasts were identified using CD45 versus side scatter (SSC). The blasts were positive for CD19, CD10, and CD34 (±) and negative for surface immunoglobulin light chain, T-cell, and myeloid markers.
DNA measurement by flow cytometry
Determination of DNA content of the newly diagnosed B-ALL cases was performed by using whole blood method and were ran on BD FACSCanto II and analyzed using the Modfit software. A DNA QC kit by Becton Dickinson and a normal control from blood bank donor were ran on the same day the patients were tested. The patient's cells were stained using DNA-Prep Coulter Reagents kit that contained RNase, and the concentration of propidium iodide is sufficient to saturate the entire DNA. DNAI was determined by using Modfit software where aggregates and cellular debris were excluded. DNA QC kit was used to determine and check the linearity of the instrument using the CTN and CEN beads. A normal blood bank control was used to place the G0/G1 population on the 50 channel mark on which the instrument setting of the FL2A is not changed. The patient(s) were run after that using the same setting of the FL2A of the control. This helped determine the diploid population in the patient's sample.
A DNAI of 1.0 was considered normal. Near-diploid was determined to be a DNA Index of 1.05–1.1. Hyperdiploid was determined to be with a DNAI >1.1. Hypodiploid was determined to be a DNAI from 0.8 to 0.95.
Bone marrow cells were processed for karyotype analysis according to standard procedures. The chromosomes were G-banded with trypsin, and analysis was performed using the Applied Spectral Imaging GENASIS software platform. Chromosomal abnormalities were identified and described according to the International System of Human CG Nomenclature (ISCN).
Fluorescent in situ hybridization
18 mm circle slides were prepared from fixed cell suspensions obtained from standard harvest procedures. Slides are merged in 2xSSC solution with Pepsin A solution, and dehydrated in a 70%, 85%, and 100% ethanol series. Slides and the fluorescently labeled DNA probe are codenatured on a Hybrite for 3 min at 73°C and hybridized overnight at 37°C. The next morning, the slides were washed in 0.4% SSC/0.3% NP40 solution at 72°C, counterstained with DAPI (4',6-diamidino-2-phenylindole) to visualize the nuclei and analyzed by fluorescent microscopy. The current pediatric B-ALL FISH panel consists of Vysis (Abbott) BCR/ABL1 (t [9;22]), MLL (11q23), ETV6/RUNX1 (t [12;21]) probes plus CEP 4, CEP 10, and CEP 17 centromere probes.
Data were collected through the ICES in excel 2013 and analyzed in SPSS 20 (IBM, Armonk, NY, United States of America). Means and standard deviation were used to describe continuous variables. The main outcome was binary (Match, Not match). Receiver operating characteristic curve was used to assess the ability of every variable to predict the outcome; area under the curve was compared at significance level of 0.05. Classification tables were used to assess the percentage of correctly predicted cases when applying logistic regression models.
| Results|| |
There were 41 males and 28 females. Their ages ranged from 3 months to 14 years with a mean age of 4 years. The diagnosis of B-ALL was established by morphology and FCM according to the WHO classification of hematological tumors 2008. DNAI-FCM ranged between 0.8 and 1.85 with a mean of 1.09. Karyotype was successful in the metaphases of 56 cases; it was diploid in 40 patients, hypodiploid in two, and hyperdiploid in 14 cases [Table 1]. Chromosomal rearrangements (translocations) were found in 15% of the diploid, 57.14% of the hyperdiploid, and all the hypodiploid cases. Karyotype has failed in 13 cases due to insufficient quantity of the samples submitted [Table 1]. The DNAI-FCM was matching the CG studies in 82.60% of the cases. The results of the B-ALL FISH panel are shown in [Table 2].
|Table 2: Fluorescent in situ hybridization results applying acute B-lymphoblastic leukemia fluorescent in situ hybridization panel|
Click here to view
The DNA histograms of normal and abnormal bone marrow cells have the general appearance shown in [Graph 1]. The chart in [Graph 2] demonstrates a linear correlation between DNAI-FCM and CG. To study these cases thoroughly, we divided them based on karyotype, using ISCN, into four groups: diploid (6/57 – 10.53%), pseudodiploid (21/57 – 36.84%), hyperdiploid (13/57 – 22.81%), and high hyperdiploid (17/57 – 36.84%). In 47–48 hyperdiploid (near diploid) cases which were successfully identified by FCM, the genetic abnormalities were either tetrasomy 21, and/or +4, +10,+17 [Table 3].
|Table 3: Fluorescent in situ hybridization panel in near-diploid cases that resulted in abnormal DNA index by flow cytometry|
Click here to view
There was a mismatch between DNAI-FCM and CG in 12 cases. As demonstrated in [Table 4], four cases showed an insufficient genetic material submitted for Karyotype and FISH. Five cases showed trisomy/tetrasomy 21 as an exclusive genetic abnormality. The explanation for discrepancy in the latter five cases is the small genetic material represented by chromosome 21, which was previously demonstrated by Morton  [Table 5]. In the remaining 3 cases, the cause of discrepancies was not clear and could not be explained. However, it could be due to technical or human error.
|Table 4: Cases showing mismatch between DNA index by flow cytometry and cytogenetic studies|
Click here to view
|Table 5: Diploid genome percentage of chromosomal copies according to sex|
Click here to view
| Discussion|| |
It has been repeatedly proven that hyperdiploid ALL has a better prognosis than pseudodiploid and diploid ALL., There is also evidence that not only hypodiploid but also triploid and tetraploid ALL cases have a worse prognosis., New therapeutic regimes seem to decrease the impact of tri-and tetraploidy on prognosis but hypodiploidy still remains a bad prognostic factor.,
The standard technique to evaluate ploidy is metaphase karyotyping. DNA content measurement by FCM can be used with high accuracy as demonstrated in this study and previous studies. Successful karyotyping needs living cells spontaneously entering mitosis, and analysis of metaphases is performed by light microscopy, with a usual turn-around time of 21–28 days. Flow cytometric DNA analysis is easy to perform on a large number of cells and is not dependent on the proliferation state of the tumor;, living cells are not essential for the analysis so the cytoplasm can be lysed, allowing for easy cell dispersion, and the turn-around time is only 2 h. The ability of flow cytometric method to scan ten thousands of cells in a short time makes it very sensitive to discover small aneuploidy clones constituting a low percentage of the total cell population.
The major question concerning the clinical applications of FCM is how reliable is it? In the literature, there are only few studies that have tried to identify the reliability of FCM in relation to the standard CG techniques. Application of DNAI-FCM as a primary technique for risk stratification will help in early prediction of prognosis and accordingly will guide in assigning the patients into appropriate treatment protocols.
Aneuploidy has been detected by FCM in a variety of hematological and nonhematological tumors. Compared to 46.4% in our study, it was 23% in patients with leukemia, 53% with lymphoma, 76% with myeloma, 45% with prostate cancer, 51% with bladder cancer, and 91% with a variety of solid tumors., In the solid tumors, all poorly differentiated tumors are aneuploid, whereas well differentiated tumors may be diploid or aneuploid ,
A similar study on childhood lymphoblastic leukemia, has approved DNAI FCM as a sensitive and reliable method to identify hyperdiploid leukemia (>51 chromosomes). In our study, DNAI-FCM was able to detect some of the near-diploid cases in which the affected chromosomes were large in size (+4, +10, +17) and was able to detect ploidy in all cases with (>51 chromosomes). Our data have no patients with true hypodiploid karyotype, as it is not common in pediatric age group. Patients with normal diploid or near-diploid karyotypes exhibiting marked DNA deviations may be due to the insufficient material submitted for CG studies and may also reflect the lack of proliferation of some leukemic clones which is a prerequisite for CG identification.,
The discrepancies between FCM and CGs in solid tumors were much higher, reaching 70%, compared to 17.4% in our study. Most of the observed discrepancies occurred in hypodiploid cases by CGs. For instance, in human breast cancer, diploid DNAI by FCM was reported in cases with abnormal hypodiploid karyotype. While in colorectal tumors, hyperdiploid population showed a good correlation between DNAI FCM and CG. A linear correlation between the two methods was reported in 66.4% of cases with different malignancies, which is much less than we have reported in our study, i.e., 82.6%.
| Conclusion|| |
DNAI-FCM shows 82.6% concordance with CG in childhood B-ALL with a predictive value of 81%. Discrepancies do occur in 17.4%. In 66.66%, this mismatch refers to either the small size of the chromosome or to an insufficient genetic material representing the abnormality. Further studies are required to validate DNAI-FCM on B-ALL with a hypodiploid karyotype.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Pui CH. Childhood leukemias. N
Engl J Med 1995;332:1618-30.
Guo XH, Zhai XW, Qian XW, Wang HS, Fan CQ. Cytogenetic characteristics of 163 children with acute lymphoblastic leukemia. Zhongguo Shi Yan Xue Ye Xue Za Zhi 2015;23:312-7.
Lampert F, Harbott J, Ritterbach J, Schellong G, Ritter J, Creutzig U, et al.
Karyotypes in acute childhood leukemias may lose prognostic significance with more intensive and specific chemotherapy. Cancer Genet Cytogenet 1991;54:277-9.
Forestier E, Gustafsson G, von Heideman A, Heim S, Hernell O, Mitelman F, et al.
Prognostic impact of bone marrow karyotype in childhood acute lymphoblastic leukaemia: Swedish experiences 1986-91. Acta Paediatr 1997;86:819-25.
Crist W, Carroll A, Shuster J, Jackson J, Head D, Borowitz M, et al.
Philadelphia chromosome positive childhood acute lymphoblastic leukemia: Clinical and cytogenetic characteristics and treatment outcome. A pediatric oncology group study. Blood 1990;76:489-94.
Arthur DC, Bloomfield CD, Lindquist LL, Nesbit ME Jr. Translocation 4; 11 in acute lymphoblastic leukemia: Clinical characteristics and prognostic significance. Blood 1982;59:96-9.
Raimondi SC, Pui CH, Hancock ML, Behm FG, Filatov L, Rivera GK, et al.
Heterogeneity of hyperdiploid (51-67) childhood acute lymphoblastic leukemia. Leukemia 1996;10:213-24.
Harris MB, Shuster JJ, Carroll A, Look AT, Borowitz MJ, Crist WM, et al.
Trisomy of leukemic cell chromosomes 4 and 10 identifies children with B-progenitor cell acute lymphoblastic leukemia with a very low risk of treatment failure: A pediatric oncology group study. Blood 1992;79:3316-24.
Secker-Walker LM, Lawler SD, Hardisty RM. Prognostic implications of chromosomal findings in acute lymphoblastic leukaemia at diagnosis. Br Med J 1978;2:1529-30.
Forestier E, Holmgren G, Roos G. Flow cytometric DNA index and karyotype in childhood lymphoblastic leukemia. Anal Cell Pathol 1998;17:145-56.
Smets LA, Slater R, van Wering ER, van der Does-van den Berg A, Hart AA, Veerman AJ, et al.
DNA index and %S-phase cells determined in acute lymphoblastic leukemia of children: A report from studies ALL V, ALL VI, and ALL VII (1979-1991) of the Dutch Childhood Leukemia Study Group and The Netherlands Workgroup on Cancer Genetics and Cytogenetics. Med Pediatr Oncol 1995;25:437-44.
Look AT, Melvin SL, Williams DL, Brodeur GM, Dahl GV, Kalwinsky DK, et al.
Aneuploidy and percentage of S-phase cells determined by flow cytometry correlate with cell phenotype in childhood acute leukemia. Blood 1982;60:959-67.
Shaffer L, editor. International System for Human Cytogenetic Nomenclature. Karger, Basel, Switzerland: Published in Collaboration with Cytogenetic Cell Genet; 2013.
Morton N. Parameters of the Human Genome. Proceedings of the National Academy of Sciences of the United States of America; 1991. p. 7474-6.
Pui CH, Carroll AJ, Head D, Raimondi SC, Shuster JJ, Crist WM, et al.
Near-triploid and near-tetraploid acute lymphoblastic leukemia of childhood. Blood 1990;76:590-6.
Pui CH, Carroll AJ, Raimondi SC, Land VJ, Crist WM, Shuster JJ, et al.
Clinical presentation, karyotypic characterization, and treatment outcome of childhood acute lymphoblastic leukemia with a near-haploid or hypodiploid less than 45 line. Blood 1990;75:1170-7.
Crissman HA, Mullaney PF, Steinkamp JA. Methods and applications of flow systems for analysis and sorting of mammalian cells. Methods Cell Biol 1975;9:179-246.
Crissman HA, Steinkamp JA. Rapid, simultaneous measurement of DNA, protein, and cell volume in single cells from large mammalian cell populations. J Cell Biol 1973;59:766-71.
Krishan A. Rapid flow cytofluorometric analysis of mammalian cell cycle by propidium iodide staining. J Cell Biol 1975;66:188-93.
Koss LG, Czerniak B, Herz F, Wersto RP. Flow cytometric measurements of DNA and other cell components in human tumors: A critical appraisal. Hum Pathol 1989;20:528-48.
Barlogie B, Raber MN, Schumann J, Johnson TS, Drewinko B, Swartzendruber DE, et al.
Flow cytometry in clinical cancer research. Cancer Res 1983;43:3982-97.
Bichel P. Flow microfluorometry and transrectal fineneedle biopsy in the classification of human prostatic carcinoma. Cancer 1977;40:1206-11.
Tribukait B, Gustafson H, Esposti P. Ploidy and proliferation in human bladder tumors as measured by flow-cytofluorometric DNA-analysis and its relations to histopathology and cytology. Cancer 1979;43:1742-51.
Barlogie B, Göhde W, Johnston DA, Smallwood L, Schumann J, Drewinko B, et al.
Determination of ploidy and proliferative characteristics of human solid tumors by pulse cytophotometry. Cancer Res 1978;38:3333-9.
Heerema NA, Nachman JB, Sather HN, Sensel MG, Lee MK, Hutchinson R, et al.
Hypodiploidy with less than 45 chromosomes confers adverse risk in childhood acute lymphoblastic leukemia: A report from the children's cancer group. Blood 1999;94:4036-45.
Barlogie B, Hittelman W, Spitzer G, Trujilo JM, Hart JS, Smallwood L, et al.
Correlation of DNA distribution abnormalities with cytogenetic findings in human adult leukemia and lymphoma. Cancer Res 1977;37:4400-7.
Kamihira S, Matutes E, Marco J, Hoda S, Morilla R, Owusuankomah K, et al.
Flow-cytometry detection of minimal DNA aneuploidy in mature lymphoid leukemias-comparison with metaphase and interphase cytogenetics. Int J Oncol 1994;5:211-4.
Shackney SE, Burholt DR, Pollice AA, Smith CA, Pugh RP, Hartsock RJ, et al.
Discrepancies between flow cytometric and cytogenetic studies in the detection of aneuploidy in human solid tumors. Cytometry 1990;11:94-104.
Remvikos Y, Gerbault-Seurreau M, Vielh P, Zafrani B, Magdelénat H, Dutrillaux B, et al.
Relevance of DNA ploidy as a measure of genetic deviation: A comparison of flow cytometry and cytogenetics in 25 cases of human breast cancer. Cytometry 1988;9:612-8.
Petersen SE, Friedrich U. A comparison between flow cytometric ploidy investigation and chromosome analysis of 32 human colorectal tumors. Cytometry 1986;7:307-12.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]