Analysis of bone marrow lymphocyte subsets in patients with acute myeloid leukemia and its clinical significance

doi:10.16150/j.1671-2870.2020.04.016

Abstract

Abstract:

Objective: To investigate the distribution of bone marrow lymphocyte subsets in patients with acute myeloid leukemia (AML),and comparing the bone marrow immune function between patients at different stage of disease and with different prognostic risk, and exploring their related clinical significance. Methods: The bone marrow samples from 131 patients with AML before treatment were collected, and the lymphocyte subsets CD4⁺ T cells, CD8⁺ T cells and CD19⁺ B cells were identified by multi-color flow cytometry for determining the percentages of lymphocyte subsets and CD4⁺/CD8⁺ ratio. The results were compared with that of healthy bone marrow samples obtained from the public data platforms. The AML patients included de novo cases (94 cases), secondary cases （18 cases）, and relapsing cases after chemotherapy （19 cases）. The de novo AML were categorized into low risk, intermediate risk and high risk groups according to the cytogenetic abnormality. Differences in lymphocyte subsets between the three groups and between the three different risk levels were compared. In relapsing patients, the percentages of lymphocyte subsets at onset were compared with that at relapse. Results: Compared with healthy subjects, AML patients had a higher percentage of CD8⁺ T cells (31.73%±12.38% vs 21.40±7.33%, P<0.001) and lower percentage of CD19⁺ B cells ( 9.62% vs 14.03%, P<0.01) and lower ratio of CD4⁺/CD8⁺ (1.04 vs 1.48, P<0.05). When compared with de novo patients, relapsing patients had higher CD8⁺ T cells (41.56%±11.64% vs 29.86%±12.20%, P<0.001), but lower CD19⁺ B cells ( 4.18% vs 11.82%, P<0.05) and CD4⁺/CD8⁺ ratio (0.59 vs 1.12, P<0.05). Paired comparison showed that relapsing patients had significant lower percentage of CD19⁺ B cells than that at onset(2.40% vs 12.41%, P<0.05). There were no significant differences in distribution of lymphocyte subsets between different risk level groups of de novo AML. The percentages of NK cells between the three groups were not different significantly. Conclusions: The bone marrow of AML patients showes obvious suppression of humoral immunity and cellular immunity. The suppression of bone marrow immune function is obviously more severe in patients with relapsing AML than in de novo. It is suggested that the distribution of bone marrow lymphatic subsets may be an effective indicator for detecting and assessing the prognosis of the disease.

Key words: Acute myeloid leukemia, Lymphocyte subsets, Relapse, B lymphocyte, T lymphocyte

CLC Number:

R733.7

GAO Yanting, ZHAO Jinyan, WANG Juan, LI Jia, XU Wen, LI Li, LIN Lihui. Analysis of bone marrow lymphocyte subsets in patients with acute myeloid leukemia and its clinical significance[J]. Journal of Diagnostics Concepts & Practice, 2020, 19(04): 407-413.

Figures/Tables 5

References 27

[1]	Döhner H, Weisdorf DJ, Bloomfield CD. Acute myeloid leukemia[J]. N Engl J Med, 2015, 373(12):1136-1152. doi: 10.1056/NEJMra1406184 URL
[2]	Global Burden of Disease Cancer Collaboration, Fitzmaurice C, Dicker D, et al. The global burden of cancer 2013[J]. JAMA Oncol, 2015, 1(4):505-527. doi: 10.1001/jamaoncol.2015.0735 pmid: 26181261
[3]	Song X, Peng Y, Wang X, et al. Incidence, survival, and risk factors for adults with acute myeloid leukemia not otherwise specified and acute myeloid leukemia with recurrent genetic abnormalities: analysis of the surveillance, epidemiology, and end results (SEER) database, 2001-2013[J]. Acta Haematol, 2018, 139(2):115-127. doi: 10.1159/000486228 URL
[4]	Deschler B, Lübbert M. Acute myeloid leukemia: epidemiology and etiology[J]. Cancer, 2006, 107(9):2099-2107. pmid: 17019734
[5]	Institute NC. Cancer Stat Facts: Leukemia-Acute Myeloid Leukemia(AML)[DB/OL]. 2017 [2020-04-22]. https://seer.cancer.gov/statfacts/html/alyl.html.
[6]	Le Dieu R, Taussig DC, Ramsay AG, et al. Peripheral blood T cells in acute myeloid leukemia (AML) patients at diagnosis have abnormal phenotype and genotype and form defective immune synapses with AML blasts[J]. Blood, 2009, 114(18):3909-3916.
[7]	Paczulla AM, Rothfelder K, Raffel S, et al. Absence of NKG2D ligands defines leukaemia stem cells and media-tes their immune evasion[J]. Nature, 2019, 572(7768):254-259. doi: 10.1038/s41586-019-1410-1 URL
[8]	Raulet DH, Gasser S, Gowen BG, et al. Regulation of li-gands for the NKG2D activating receptor[J]. Annu Rev Immunol, 2013, 31:413-441. doi: 10.1146/annurev-immunol-032712-095951 pmid: 23298206
[9]	Goswami M, Prince G, Biancotto A, et al. Impaired B cell immunity in acute myeloid leukemia patients after chemotherapy[J]. J Transl Med, 2017, 15(1):155. doi: 10.1186/s12967-017-1252-2 URL
[10]	Gabert J, Beillard E, van der Velden VH, et al. Standardization and quality control studies of 'real-time' quantitative reverse transcriptase polymerase chain reaction of fusion gene transcripts for residual disease detection in leukemia-a Europe Against Cancer program[J]. Leukemia, 2003, 17(12):2318-2357. doi: 10.1038/sj.leu.2403135 pmid: 14562125
[11]	Beillard E, Pallisgaard N, van der Velden VH, et al. Evaluation of candidate control genes for diagnosis and residual disease detection in leukemic patients using 'real-time' quantitative reverse-transcriptase polymerase chain reaction (RQ-PCR)-a Europe against cancer program[J]. Leukemia, 2003, 17(12):2474-2486. pmid: 14562124
[12]	Duncavage EJ, Abel HJ, Szankasi P, et al. Targeted next generation sequencing of clinically significant gene mutations and translocations in leukemia[J]. Mod Pathol, 2012, 25(6):795-804. doi: 10.1038/modpathol.2012.29 URL
[13]	Luthra R, Patel KP, Reddy NG, et al. Next-generation sequencing-based multigene mutational screening for acute myeloid leukemia using MiSeq: applicability for diagnostics and disease monitoring[J]. Haematologica, 2014, 99(3):465-473. doi: 10.3324/haematol.2013.093765 URL
[14]	Arber DA, Orazi A, Hasserjian R, et al. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia[J]. Blood, 2016, 127(20):2391-2405. doi: 10.1182/blood-2016-03-643544 URL
[15]	Döhner H, Estey E, Grimwade D, et al. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel[J]. Blood, 2017, 129(4):424-447. doi: 10.1182/blood-2016-08-733196 URL
[16]	Oetjen KA, Lindblad KE, Goswami M, et al. Human bone marrow assessment by single-cell RNA sequencing, mass cytometry, and flow cytometry[J]. JCI Insight, 2018, 3(23):e124928. doi: 10.1172/jci.insight.124928 URL
[17]	黄方, 郝思国. 急性髓系白血病患者外周血T淋巴细胞亚群的水平变化及临床意义[J]. 第二军医大学学报, 2020, 41(5):546-550.
[18]	杨莉, 何浩明. 急性髓细胞白血病患者外周血淋巴细胞亚群的检验分析[J]. 国际检验医学杂志, 2016, 37(6):817-819.
[19]	晁丹阳. 68例急性髓细胞白血病患者淋巴细胞亚群的变化分析[J]. 临床医学, 2017, 37(10):66-68.
[20]	Austin R, Smyth MJ, Lane SW. Harnessing the immune system in acute myeloid leukaemia[J]. Crit Rev Oncol Hematol, 2016, 103:62-77. doi: 10.1016/j.critrevonc.2016.04.020 URL
[21]	Williams P, Basu S, Garcia-Manero G, et al. The distribution of T-cell subsets and the expression of immune checkpoint receptors and ligands in patients with newly diagnosed and relapsed acute myeloid leukemia[J]. Cancer, 2019, 125(9):1470-1481. doi: 10.1002/cncr.31896 pmid: 30500073
[22]	Bozzano F, Perrone C, Moretta L, et al. NK cell precursors in human bone marrow in health and inflammation[J]. Front Immunol, 2019, 10:2045. doi: 10.3389/fimmu.2019.02045 URL
[23]	Ribeiro VS, Hasan M, Wilson A, et al. Cutting edge: Thymic NK cells develop independently from T cell precursors[J]. J Immunol, 2010, 185(9):4993-4997. doi: 10.4049/jimmunol.1002273 pmid: 20889548
[24]	Vargas CL, Poursine-Laurent J, Yang L, et al. Development of thymic NK cells from double negative 1 thymocyte precursors[J]. Blood, 2011, 118(13):3570-3578.
[25]	Freud AG, Yu J, Caligiuri MA. Human natural killer cell development in secondary lymphoid tissues[J]. Semin Immunol, 2014, 26(2):132-137. doi: 10.1016/j.smim.2014.02.008 URL
[26]	Jia B, Wang L, Claxton DF, et al. Bone marrow CD8 T cells express high frequency of PD-1 and exhibit reduced anti-leukemia response in newly diagnosed AML patients[J]. Blood Cancer J, 2018, 8(3):34. doi: 10.1038/s41408-018-0069-4 URL
[27]	Knaus HA, Berglund S, Hackl H, et al. Signatures of CD8⁺ T cell dysfunction in AML patients and their reversibility with response to chemotherapy[J]. JCI Insight, 2018, 3(21):e120974. doi: 10.1172/jci.insight.120974 URL

分组	初诊AML			继发AML（n=18）	复发AML（n=19）
分组	低危组（n=36）	中危组（n=27）	高危组（n=31）	继发AML（n=18）	复发AML（n=19）
性别(女/男)	14/22	11/16	12/19	8/10	4/15
中位年龄(岁）	53(18~77)	38(26~68)	54(25~72)	53(33~78)	48(17~70)
融合基因
RUNX1-RUNX1T1	6(16.67%)				1(5.26%)
KMT2A重排			2(6.45%)		3(15.79%)
CBFB-MYH11	7(19.44%)				3(15.79%)
突变基因
NPM1	14(38.89%)	1(3.70%)	2(6.45%)		1(5.26%)
NPM1突变伴低水平FLT3-ITD	2(5.56%)		1(3.23%)
NPM突变伴高水平FLT3-ITD		1(3.70%)	1(3.23%)
野生型NPM1伴低水平FLT3-ITD		4(14.81%)	4(12.90%)		2(10.53%)
野生型NPM1伴高水平FLT3-ITD			1(3.23%)
CEBPA双突变	9(25.00%)
RUNX1	2(5.56%)		7(22.58%)	1(5.56%)	2(10.53%)
ASXL1	9(25.00%)		21(67.74%)	10(55.56%)	2(10.53%)
TP53			5(16.13%)	5(27.78%)	2(10.53%)