Flow Cytometric DNA Ploidy Analysis in Haemato-Lymphoid Neoplasms: An Analysis of 132 Cases
Abstract
Background: FxCycleTM Violet (FCV) based flow cytometric (FCM) DNA ploidy analysis is a rapid and simple tool that can substantiate in characterizing the biological behaviour across the spectrum of haematological malignancies and correlates with cytogenetic studies.
Materials and Methods: In this prospective study, we performed simultaneous immunophenotyping with FCV based on ploidy analysis in n=132 consecutive new samples, comprising n=110 samples of haemato-lymphoid neoplasms, including acute leukemias (n=67, 60.9%), CML with myeloid blast crisis (n=1, 0.9%), MDS with excess blasts (n=2, 1.8%), mature B cell/ T cell neoplasms (n=37, 33.7%), multiple myeloma (n=3, 2.7%) along with n=22 normal samples. The FCM DNA data was compared with corresponding conventional karyotyping results, wherever available.
Results: In FCM ploidy analysis (n=110), the overall DNA index (DI) ranged from 0.81 to 2.17 and S-Phase fraction (SPF) from 0.1-31.6%. Diploidy was seen in n = 90 (81.8%), low-hyperdiploidy in n = 10 (9.1%), high-hyperdiploidy in n = 7 (6.4%) with one case each (0.9% each) having near-tetraploidy, high-hypodiploidy and low-hypodiploidy. The DI of all viable cell populations in normal samples ranged from 0.96-1.05. Conventional karyotyping was performed in n=76/110 cases (70%) with n= 11/76 (15%) culture failures. The modal chromosome number ranged from 45 to 63. A concordance of 95.4% (n=62/65) was noted with corresponding FCM DI.
Conclusion: FCV-based ploidy is a sensitive technique that provides complementary information and ascertains a strong correlation with conventional cytogenetics across all haemato-lymphoid neoplasms. It can detect aneuploidy in all B-ALL and myeloma cases, even in hemodiluted samples with cytogenetic culture failure; supplement the diagnoses of erythroleukemia, and provide a useful screen for a higher grade lymph node disease in lymphoma cases with SPF > 3%.
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6. Krishan A. Rapid DNA content analysis by the propidium iodidehypotonic citrate method. Methods Cell Biol. 1990;33:121–5.
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15. Charrin C, Thomas X, Ffrench M, et al. A report from the LALA-94 and LALA-SA groups on hypodiploidy with 30 to 39 chromosomes and near-triploidy: 2 possible expressions of a sole entity conferring poor prognosis in adult acute lymphoblastic leukemia (ALL). Blood. 2004;104(8):2444-51.
16. Irving JAE, Enshaei A, Parker CA, et al. Integration of genetic and clinical risk factors improves prognostication in relapsed childhood B-cell precursor acute lymphoblastic leukemia. Blood. 2016; 128(7):911–22.
17. Dastugue N, Suciu S, Plat G, et al. Hyperdiploidy with 58-66 chromosomes in childhood B-acute lymphoblastic leukemia is highly curable: 58951 CLG-EORTC results. Blood. 2013; 121(13):2415–23.
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24. Chng WJ, Winkler JM, Greipp PR, et al. Ploidy status rarely changes in myeloma patients at disease progression. Leuk Res. 2006;30(3):266-71.
25. Paiva B, Vídriales MB, Montalbán MÁ, et al. Multiparameter flow cytometry evaluation of plasma cell DNA content and proliferation in 595 transplant-eligible patients with myeloma included in the Spanish GEM2000 and GEM2005< 65y trials. Am J Pathol. 2012;181(5):1870-8.
26. Rajkumar SV. Multiple myeloma: 2018 update on diagnosis, risk‐stratification, and management. Am J Hematol. 2018;93(8):981-1114.
27. García‐Sanz R, González‐Fraile MI, Mateo G, et al. Proliferative activity of plasma cells is the most relevant prognostic factor in elderly multiple myeloma patients. Int J Cancer. 2004;112(5):884-9.
28. Quijano S, López A, Rasillo A, et al. Association between the proliferative rate of neoplastic B cells, their maturation stage, and underlying cytogenetic abnormalities in B-cell chronic lymphoproliferative disorders: analysis of a series of 432 patients. Blood. 2008;111(10):5130-41.
29. Holte H, Suo Z, Smeland EB, et al. Prognostic value of lymphoma-specific S-phase fraction compared with that of other cell proliferation markers. Acta Oncol. 1999;38(4):495-503.
30. Juneja SK, Cooper IA, Hodgson GS, et al. DNA ploidy patterns and cytokinetics of non-Hodgkin's lymphoma. J Clin Pathol. 1986;39(9):987-92.
31. Pinto AE, Cabeçadas J, Nóbrega SD, et al. Flow cytometric S‐phase fraction as a complementary biological parameter for the cytological grading of non‐Hodgkin's lymphoma. Diagn Cytopathol. 2003;29(4):194-9.
32. Estey EH. Acute myeloid leukemia: 2019 update on risk‐stratification and management. Am J Hematol. 2018;93(10):1267-91.
33. Döhner H, Estey E, Grimwade D, et al. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. Blood. 2017;129(4):424-47.
34. Sandahl JD, Kjeldsen E, Abrahamsson J, et al. Ploidy and clinical characteristics of childhood acute myeloid leukemia: A NOPHO‐AML study. Genes Chromosomes Cancer. 2014;53(8):667-75.
35. Pawar RN, Banerjee S, Bramha S, et al. Mixed-phenotypic acute leukemia series from tertiary care center. Indian J Pathol Microbiol. 2017;60(1):43-49.
36. Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA, Stein H, Thiele J (Eds): WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues (Revised 4th edition). IARC: Lyon 2017.
37. Gupta N, Parihar M, Banerjee S, et al. FxCycle™ Based Ploidy Correlates with Cytogenetic Ploidy in B‐Cell Acute Lymphoblastic Leukemia and Is Able to Detect the Aneuploid Minimal Residual Disease Clone. Cytometry B Clin Cytom. 2019;96(5):359-367.
38. Antonenko VG, Shilova NV. About an International System for Human Cytogenomic Nomenclature-ISCN 2016. Med Genet. 2018;17(6):11-7.
39. Gupta N, Dadu T, Mittal A, Choudhary D, et al. Utility of Flow Cytometric DNA Ploidy Analysis in the Diagnosis of Pure Erythroid Leukemia: An Illustrative Case Report. AHRJ. 2019;2(3):1-9.
1. Yuan CM. A bright and colorful future for DNA cell cycle analysis. Cytometry A. 2016;89(3):236-8.
2. Duque RE, Andreeff M, Braylan RC, et al. Consensus review of the clinical utility of DNA flow cytometry in neoplastic hematopathology. Cytometry. 1993;14(5):492-6.
3. Wang XM. Advances and issues in flow cytometric detection of immunophenotypic changes and genomic rearrangements in acute pediatric leukemia. Transl Pediatr. 2014; 3(2):149–155.
4. Darzynkiewicz Z. Critical aspects in analysis of cellular DNA content. Curr Protoc Cytom. 2011; Chapter 7:Unit 7.2.
5. Tembhare P, Badrinath Y, Ghogale S, et al. A novel and easy FxCycle™ violet based flow cytometric method for simultaneous assessment of DNA ploidy and six-color immunophenotyping. Cytometry A. 2016;89(3):281–91.
6. Krishan A. Rapid DNA content analysis by the propidium iodidehypotonic citrate method. Methods Cell Biol. 1990;33:121–5.
7. Trueworthy R, Shuster J, Look T, et al. Ploidy of lymphoblasts is the strongest predictor of treatment outcome in B progenitor cell acute lymphoblastic leukemia of childhood: A pediatric oncology group study. J Clin Oncol. 1992; 10(4):606–13.
8. Smets LA, Slater R, van Wering ER, 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(6):437–44.
9. Raimondi SC, Zhou Y, Shurtleff SA, et al. Near-triploidy and near-tetraploidy in childhood acute lymphoblastic leukemia: Association with B-lineage blast cells carrying the ETV6-RUNX1 fusion, T-lineage immunophenotype, and favourable outcome. Cancer Genet Cytogenet. 2006;169(1):50–7.
10. Tembhare P, Badrinath Y, Ghogale S, et al. Method for DNA Ploidy analysis along with Immunophenotyping for rare populations in a sample using FxCycle violet. Curr Protoc Cytom. 2017;80:6.38.1–6.38.15.
11. Zwick D, Cooley L, Hetherington M. Minimal residual disease testing of acute leukemia by flow cytometry immunophenotyping: A retrospective comparison of detection rates with flow cytometry DNA ploidy or FISH-based methods. Lab Hematol. 2006;12(2):75–81.
12. Kenney B, Zieske A, Rinder H, et al. DNA ploidy analysis as an adjunct for the detection of relapse in B-lineage acute lymphoblastic leukemia. Leuk Lymphoma. 2008;49(1):42–8.
13. Kim KH, Sederstrom JM. Assaying cell cycle status using flow cytometry. Curr Protoc Mol Biol. 2015;111:28.6.1-28.6.11.
14. Rachieru-Sourisseau P, Baranger L, Dastugue N, et al. DNA index in childhood acute lymphoblastic leukaemia: A karyotypic method to validate the flow cytometric measurement. Int J Lab Hematol. 2010;32(3): 288–298.
15. Charrin C, Thomas X, Ffrench M, et al. A report from the LALA-94 and LALA-SA groups on hypodiploidy with 30 to 39 chromosomes and near-triploidy: 2 possible expressions of a sole entity conferring poor prognosis in adult acute lymphoblastic leukemia (ALL). Blood. 2004;104(8):2444-51.
16. Irving JAE, Enshaei A, Parker CA, et al. Integration of genetic and clinical risk factors improves prognostication in relapsed childhood B-cell precursor acute lymphoblastic leukemia. Blood. 2016; 128(7):911–22.
17. Dastugue N, Suciu S, Plat G, et al. Hyperdiploidy with 58-66 chromosomes in childhood B-acute lymphoblastic leukemia is highly curable: 58951 CLG-EORTC results. Blood. 2013; 121(13):2415–23.
18. Zaliova M, Hovorkova L, Vaskova M, et al. Slower early response to treatment and distinct expression profile of childhood high hyperdiploid acute lymphoblastic leukaemia with DNA index < 1.16. Genes Chromosomes Cancer. 2016;55(9):727–37.
19. Kumar BK, Bhatia P, Trehan A, et al. DNA Ploidy and S-phase Fraction Analysis in Paediatric B-cell Acute Lymphoblastic Leukemia Cases: A Tertiary Care Centre Experience. Asian Pac J Cancer Prev. 2015;16(17):7917–22.
20. Stark B, Jeison M, Gobuzov R, et al. Near haploid childhood acute lymphoblastic leukemia masked by hyperdiploid line: Detection by fluorescence in situ hybridization. Cancer Genet Cytogenet. 2001;128(2):108–13.
21. Hoelzer D, Bassan R, Dombret H, et al. Acute lymphoblastic leukaemia in adult patients: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2016; 27(suppl 5):v69-v82
22. Rajan AM, Rajkumar SV. Interpretation of cytogenetic results in multiple myeloma for clinical practice. Blood Cancer J. 2015;5(10):e365.
23. Wuilleme S, Robillard N, Lode L, et al. Ploidy, as detected by fluorescence in situ hybridization, defines different subgroups in multiple myeloma. Leukemia. 2005;19(2):275-8.
24. Chng WJ, Winkler JM, Greipp PR, et al. Ploidy status rarely changes in myeloma patients at disease progression. Leuk Res. 2006;30(3):266-71.
25. Paiva B, Vídriales MB, Montalbán MÁ, et al. Multiparameter flow cytometry evaluation of plasma cell DNA content and proliferation in 595 transplant-eligible patients with myeloma included in the Spanish GEM2000 and GEM2005< 65y trials. Am J Pathol. 2012;181(5):1870-8.
26. Rajkumar SV. Multiple myeloma: 2018 update on diagnosis, risk‐stratification, and management. Am J Hematol. 2018;93(8):981-1114.
27. García‐Sanz R, González‐Fraile MI, Mateo G, et al. Proliferative activity of plasma cells is the most relevant prognostic factor in elderly multiple myeloma patients. Int J Cancer. 2004;112(5):884-9.
28. Quijano S, López A, Rasillo A, et al. Association between the proliferative rate of neoplastic B cells, their maturation stage, and underlying cytogenetic abnormalities in B-cell chronic lymphoproliferative disorders: analysis of a series of 432 patients. Blood. 2008;111(10):5130-41.
29. Holte H, Suo Z, Smeland EB, et al. Prognostic value of lymphoma-specific S-phase fraction compared with that of other cell proliferation markers. Acta Oncol. 1999;38(4):495-503.
30. Juneja SK, Cooper IA, Hodgson GS, et al. DNA ploidy patterns and cytokinetics of non-Hodgkin's lymphoma. J Clin Pathol. 1986;39(9):987-92.
31. Pinto AE, Cabeçadas J, Nóbrega SD, et al. Flow cytometric S‐phase fraction as a complementary biological parameter for the cytological grading of non‐Hodgkin's lymphoma. Diagn Cytopathol. 2003;29(4):194-9.
32. Estey EH. Acute myeloid leukemia: 2019 update on risk‐stratification and management. Am J Hematol. 2018;93(10):1267-91.
33. Döhner H, Estey E, Grimwade D, et al. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. Blood. 2017;129(4):424-47.
34. Sandahl JD, Kjeldsen E, Abrahamsson J, et al. Ploidy and clinical characteristics of childhood acute myeloid leukemia: A NOPHO‐AML study. Genes Chromosomes Cancer. 2014;53(8):667-75.
35. Pawar RN, Banerjee S, Bramha S, et al. Mixed-phenotypic acute leukemia series from tertiary care center. Indian J Pathol Microbiol. 2017;60(1):43-49.
36. Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA, Stein H, Thiele J (Eds): WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues (Revised 4th edition). IARC: Lyon 2017.
37. Gupta N, Parihar M, Banerjee S, et al. FxCycle™ Based Ploidy Correlates with Cytogenetic Ploidy in B‐Cell Acute Lymphoblastic Leukemia and Is Able to Detect the Aneuploid Minimal Residual Disease Clone. Cytometry B Clin Cytom. 2019;96(5):359-367.
38. Antonenko VG, Shilova NV. About an International System for Human Cytogenomic Nomenclature-ISCN 2016. Med Genet. 2018;17(6):11-7.
39. Gupta N, Dadu T, Mittal A, Choudhary D, et al. Utility of Flow Cytometric DNA Ploidy Analysis in the Diagnosis of Pure Erythroid Leukemia: An Illustrative Case Report. AHRJ. 2019;2(3):1-9.
| Files | ||
| Issue | Vol 16, No 1 (2022) | |
| Section | Original Article(s) | |
| DOI | https://doi.org/10.18502/ijhoscr.v16i1.8440 | |
| Keywords | ||
| DNA ploidy; FxCycle™ violet; S-phase fraction; Cytogenetics; Karyotyping | ||
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How to Cite
1.
Gupta N, Mittal A, Dadu T, Choudhary D, Handoo A. Flow Cytometric DNA Ploidy Analysis in Haemato-Lymphoid Neoplasms: An Analysis of 132 Cases. Int J Hematol Oncol Stem Cell Res. 2022;16(1):34-46.
