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ORIGINAL ARTICLE |
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Year : 2022 | Volume
: 21
| Issue : 2 | Page : 171-177 |
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Assessment of soluble natural killer group 2d ligand (MHC Class I A and UL16 Binding Protein 1) in Iraqi patients with acute myeloid leukemia
Baan Abdulatif Mtashar1, Zainab Fadhel Ashoor2, Zeyad Ahmed Shabeeb3, Bassam Francis Matti4
1 The National Center of Hematology, Al.Mustansiriyah University; Department of Microbiology, College of Medicine, Al-Mustansiriyah University, Baghdad, Iraq 2 Department of Microbiology, College of Medicine, Al-Mustansiriyah University, Baghdad, Iraq 3 The National Center of Hematology, Al-Mustansiriyah University, Baghdad, Iraq 4 Department of Clinical Hematology, Baghdad Teaching Hospital, Medical City; Bone Marrow Transplant Center, Medical City, Baghdad, Iraq
Date of Submission | 02-Aug-2022 |
Date of Decision | 19-Aug-2022 |
Date of Acceptance | 21-Aug-2022 |
Date of Web Publication | 2-Jan-2023 |
Correspondence Address: Dr. Baan Abdulatif Mtashar PH.D Studient, Microbilogy Department, College of Medicine, Mustansiriyah University, Baghdad Iraq
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/mj.mj_29_22
Background: Acute myeloid leukemia (AML) is “a heterogeneous disease,” defined by a wide range of genetic alterations and molecular mutations that have an effect on clinical outcomes and could be used to develop new drugs. In AML, the immune system is tricked and actively suppressed by leukemia itself and by mechanisms that leukemia picked up through further mutations under suppression of selection. Myeloblasts in Acute myeloid leukemia can evasion the naturak killer cell killing by many ways , one of the these way ,the myelocblast cells shed NKG2D soluble ligand (MIC A/B and or ULPB 1-6 ) in blood and bound to NKG2D activation receptor which lead to inhibit activation of NK cells. The Aim of Study: The aim of this study assessment of Soluble ligand (MICA and ULPB-1) in patients with AML. Patients and Methods: Thirty patients newly diagnosed as AML were enrolled in this study, 24 patients out of 30 were follow up after 14 days of tratment. after 30 days of treatment we get result of therapy. twenty healthy looking persons were considered as control subjects. We used ELISA technique to detection the level of soluble legand ( MICA and ULPB-1). Results: The study showed that in order level of sMICA, there were significant differences in AML patients at diagnosis and after 14 days of treatment in comparison to control subjects while there were no significant differences in the level of sULPB1 between AML patients at diagnosis and after 14 days of treatment in comparison to control subjects. Conclusion: This study showed that there was an elevated level of sMICA in AML patients at diagnosis and 14 days to treatment while there was no elevated level of sULPB1 in comparison to the control group. Keywords: Acute myeloid leukemia, natural killer, soluble MHC class I A, soluble natural killer group 2D ligand, soluble UL16 binding protein 1
How to cite this article: Mtashar BA, Ashoor ZF, Shabeeb ZA, Matti BF. Assessment of soluble natural killer group 2d ligand (MHC Class I A and UL16 Binding Protein 1) in Iraqi patients with acute myeloid leukemia. Mustansiriya Med J 2022;21:171-7 |
How to cite this URL: Mtashar BA, Ashoor ZF, Shabeeb ZA, Matti BF. Assessment of soluble natural killer group 2d ligand (MHC Class I A and UL16 Binding Protein 1) in Iraqi patients with acute myeloid leukemia. Mustansiriya Med J [serial online] 2022 [cited 2023 Jun 4];21:171-7. Available from: https://www.mmjonweb.org/text.asp?2022/21/2/171/366626 |
Introduction | |  |
Acute myeloid leukemia (AML) is a kind of leukemia in which aberrant, proliferative myeloid precursors infiltrate the bone marrow, blood, and other tissues.[1] The French-American-British Cooperative Leukemia Working Group established the most important diagnostic criteria for AML, there are at least 20% blasts in the aspirate, or CD34 or CD117 immunostains show that immature precursors are in an unusual place on the biopsy section.[2]
AML is a very variable illness that can manifest as a de novo or secondary disease “therapy-related or postantecedent hematologic condition.” The incidence of onset rises with age, and age is also linked to a larger frequency of high-risk cytogenetic and molecular abnormalities.[3] Although AML accounts for only about 1% of all cancers with an incidence of 4 per 100,000 a year, it is the most common acute leukemia in adults.[4],[5],[6] AML is often associated with elderly persons and is uncommon before the age of 45, while it can occur at any age. The typical age upon diagnosis is 68 years, with most individuals diagnosed between the ages of 65 and 74[7] and predominant in males more than females.[8],[9]
The idea of using the immune system to fight cancer comes from cellular immunology, but until recently, it was thought that cancer cells were not very immunogenic and that the immune system did not tumor cells.[10]
It has been observed that adaptive and innate immune system features, such as the number of various kinds of immune cells in tumor tissue, have a significant impact on the clinical prognosis of AML.[11] Immune surveillance mechanisms comprising adaptive and innate immune systems are naturally designed to eliminate AML development. However, leukemic cells apply various immune evasion mechanisms to deviate host immune responses resulting in tumor progression. One of the recently well-known immune escape mechanisms is the overexpression of immune checkpoint receptors and their ligands. The introduction of blocking antibodies targeting co-inhibitory molecules achieved invaluable success in tumor-targeted therapy. Moreover, several new co-inhibitory pathways are currently studying for their potential impacts on improving anti-tumor immune responses.[12]
The equilibrium between the expression of activating and inhibiting receptors mediates and controls nature killer (NK) cell functioning.[13] Natural cytotoxic receptors “(NKp30, NKp46, NKp44), natural killer group 2D (NKG2D), and DNAX accessory molecule-1 (DNAM-1)” are the primary activating receptors, while the killer inhibitory receptor (KIR) family and natural killer group 2A are inhibitory receptors. In a process known as “licensing” or “education” of NK cells, inhibitory receptors (mostly KIRs) engage with self-molecules (self-MHC class I [MICA]) to prevent the detection of self-cells.[14] The uneven expression of these receptors and their ligands impedes the identification of malignant cells and facilitates the growth of tumors. In a large proportion of AML patients, the expression levels of several activating receptors “(NKG2D, NKp30, NKp46, and DNAM-1)” are either null or very low.[15] The negative association between DNAM-1 expression levels and one of its ligands (CD112) in AML patients implies that activating receptor expression is dependent on the presence of their ligands on the surface of AML cells.[16] AML also modifies the expression of the activating receptors' ligands. NKG2D ligands “(NKG2DL, MICA/MICB, and ULBPs1-3)” are missing or expressed at extremely low levels on the cell surface of myeloid blasts, as shown by many research groups.[17] Expression of these ligands is dependent on the cellular subtype, with little or no expression in myeloblastic cells and a high level of expression in monoblastic cells, indicating that NKG2DL is acquired during the last phases of maturation.[18] The release of these ligands in a soluble form from the cell surface by metalloprotease cleavage or into exosomes is an essential technique evolved by AML cells to elude immune identification. Two investigations have shown that these ligands are often found in the serum of AML patients, resulting in the downregulation of NKG2D and the loss of NKs' cytotoxic potential.[19] Therefore, AML patients with decreased levels of soluble MICA (sMICA), MICB, and ULBP1 had a greater chance of achieving complete remission (CR) and surviving more than a year.[19]
Aim of study
Assessment of NKG2D ligand ( MICA and ULPB-1 ) in patients with AML.
Patients and Methods | |  |
Study design
A cohort study designed 30 patients who were diagnosed with AML and follow-up on day 14 and day 30 at treatment collected from Baghdad Medical City, National Center of Hematology, from February 2021 to November 2021.
Patients
Thirty persons were diagnosed as AML, 19 male and 11 female. 24 ppatient out of 30 were follow up after 14 days of tratment. The patients collected from Baghdad medical city, Hematology center from February 2021 to November 2021. Twenty healthy-looking persons were considered control subjects.
Inclusion criteria
New diagnosed AML patients with all types of AML (M0 - M7), axcept AML-M3 all patients before starting tratment collected from them Bone maroow asperate and diagnosed by immunophynotyping study with multicolor Flowcytometry, of any sex, age 18–65 years. The treatment is a 7 + 3 drug regimen.
Exclusion criteria
The Age under 18 years , AML patients wit M3 type and the patients did not trated with 7+3 drug regimen.
Methods
In this study detected level of MICA and ULPB-1 using Sandwich ELISA techniques ( Sunlong Biotech, china). After prepered serial diluted standared, 50 microliter of standered dilutiens were added to the microtitter wells. First, micro-ELISA stripplets leave a well empty as blank control. In sample wells, 40 μl sample dilution buffer and 10 μl sample were added (dilution factor is 5) the microtitter plate were mixed and cover by plate membrane. Micro-ELISA stripplets were incubated for 30 min at 37°C. the micro-ELISA plate were washed by washing buffer 5 times by asperated and refilled the plate with washing buffer and hold for 30 sec. HRP conjugate were added to each wells accepted blank conjugate) reagent to each accept the blank control well. Incubation was described previously. Microplate was washed as described. 50 microliter of chromogen reagent A and 50 microleter of Chromogen B were added to each well, then gently shacked and incubated for 15 min in 37 C in dark place. Termination: 50 μl of stop reagent was added to each well to terminate the reaction. The color in the well changed from blue to yellow. The microplate was read absorbance OD 450 nm using a microtiter plate reader. The OD value of the blank control well is set as 0.
Calculation of the results
The results of sMICA and sULPB-1 detection level used logaretmic Standered curve. the serial dilution of standered with known concentration were plotted on X - axis and the Optecal dencity of standared dilution plotted on Y - axis ULPB1 (pg/ml) and sMICA (ng/L) in samples were determined by plotting. By plotting the sampple's OD on the y-axes. Then, the original concentration was calculated by multiplying the dilution factor.
Statistical analysis
Statistical analysis was performed using the “Statistical Package for the Social Sciences SPSS software version 23.0.0. Analytic statistics were carried out using a t-test, with P < 0.05 which was considered statistically significant. Descriptive statistics were presented in tables, bar charts, stem and leaf plots, scatter plots, and trend line mainly in the form of a range, mean, and standard deviation.
Results | |  |
30 patients were diagnosed as AML, 24 patients ourt of 30 were followed up after 14 days of tratment. 19 AML patients were male while 11 was female with ratio male: female (1.72: 1) [Table 1] and [Figure 1]. 6 patients out of 30 were died. Twenty age- and gender-matched healthy-looking subjects were considered a control group.
The mean age of patients with AML was 40.2 ± 15.2 years and ranged from 18 to 65 years, while the mean for the healthy-looking subjects was 41.1 ± 13.3 years and ranged from 24 to 64 years [Table 2] and [Figure 2]. | Figure 2: Age distribution of patients with acute myeloid leukemia at diagnosis and 14 days after treatment
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Hematological remission with a patient of acute myeloid leukemia
Hematological remission is defined as an absence of clinical evidence of leukemia with bone marrow blast cells <5%, absence of Auer rods, neutrophil count ≥1 × 109/l, and platelet count ≥100 × 109/l.[20] Fifteen (62.5%) out of 24 patients with AML at day 30 after treatment were in remission, and 9 (37.5%) out of 24 patients were not in remission [Table 3] and [Figure 3]. | Table 3: Hematological remission of patients with acute myeloid leukemia at day 30 after treatment (n=24)
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 | Figure 3: Hematological remission of patients with acute myeloid leukemia at day 30 after treatment
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According to the data represented in [Table 4], there are no statistical differences between AML at diagnosis and AML 14 days after treatment in the serum level of sULPB1 and sMICA [P = 0.593 and 0.128, respectively; [Figure 4] and [Figure 5]. | Table 4: Serum level of soluble UL16 binding protein 1 and soluble MHC class I A in patients with acute myeloidleukemia
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 | Figure 4: Concentration of soluble MHC class I A (ng/L) in patients with acute myeloid leukemia at diagnosis and 14 days after treatment in comparison to control subjects
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 | Figure 5: Concentration of soluble UL16 binding protein 1 (pg/mL) in patients with acute myeloid leukemia at diagnosis and 14 days after treatment in comparison to control subjects
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With P = 0.001, there are significant statistical differences between AML at diagnosis and control subjects' serum levels of sMICA. On the contrary, there were no statistically significant differences in the sULPB1, P = 0.942.
In the comparison between AML at 14 days after treatment and control subjects, there were no statistically significant differences in serum levels of sULPB1 with P = 0.079 while there were statistically significant differences in serum levels (sMICA) with P = 0.001.
According to mortality, there were no significant differences between alive patients with AML and deceased in serum levels of sULPB1 and sMICA [P = 0.421 and 0.27, respectively; [Table 5]]. | Table 5: Serum level of soluble UL16 binding protein 1 and soluble MHC class I A in patients with acute myeloidleukemia at diagnosis in relation to mortality
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Concerning remission after 30 days of treatment, there are statistically significant differences in serum level of sMICA, P = 0.041, while there are no statistically significant differences between remission and no remission in serum level of sULPB1, P = 0.767 [Table 6]. | Table 6: Serum level of soluble UL16 binding protein 1 and soluble MHC class I A in patients with acute myeloid leukemia at diagnosis, concerning remission at 30 days after a treatment
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Concerning remission after 14 days of treatment, there was no statistically significant difference between remission and no remission in serum level of sULPB1 and sMICA [P = 0.218 and 0.114, respectively; [Table 7]]. | Table 7: Serum level of soluble UL16 binding protein 1 and soluble MHC class I A in patients with acute myeloid leukemia at diagnosis, concerning remission at 14 days after a treatment
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Discussion | |  |
AML is a cancer of the bone marrow that is caused by myeloid progenitor cells that grow in clones and stop differentiating. Age-adjusted rates of AML in the US are 4.3 per 100,000 people/year.[21] In Iraq, Abdulridha et al. studied 3102 leukemia patients in the Iraqi Center for Hematology in the City of Medicine in Baghdad between January 2018 and December 2019, AML was 37% of total leukemia in 2018, while in 2019, AML was 40.8% of total leukemia.[22] In Iraq, sperated studies in Baghdad , Karbala and Sulaymaniyah demonstrated that the incidence of AML among other type of leukemia was 24.85%, in Baghdad between 2018 and 2019,[22] in Karbala the incidence of AML in 2019 out of 402 leukemic patients 19.2%.[23] In research conducted at the Hiwa Hospital in Sulaymaniyah between 2009 and 2013, 17% of 570 leukemia patients had AML.[24]
AML may affect people of all ages, from infants to the elderly.[25],[26] AML is thought to be a disease of the elderly. In the United States, the median age of AML diagnosis ranged from 62 to 68 years.[27] Similar variations were seen in Europe and Canada.[28],[29] In Saudi Arabia, the median age at AML diagnosis seems to be lower than that reported for the United States and Europe, even though there are minimal data to support this notion. The current research, which included 30 patients with AML at the time of diagnosis and followed up 24 of those patients after 14 days of treatment, found that the mean age of patients with AML was 40.2 ± 15.2 years, ranging from 18 to 65 years according to the exclusion criteria.
The AML patients in the current study were 19 males and 11 females with a male: female ratio of 1.72:1. This result agrees with Juliusson et al., as with most leukemia, AML is a hematological malignancy which is more common in males than in females.[25]
According to the data represented in [Table 5], there were no statistically significant differences between AML at diagnosis and AML 14 days after treatment in the serum levels of sULPB1 and sMICA (P = 0.593 and 0.128, respectively). There were significant statistical differences in serum level sMICA between AML at diagnosis and control subjects, with P = 0.001. On the contrary, there were no statistically significant differences in the ULPB1, P = 0.942. Compared to a control subject, AML patients after 14 days of treatment showed no statistically significant differences in serum levels of ULPB1 (P = 0.079), but there were statistically significant differences in serum levels of sMICA (P = 0.001) ligands (MICA and ULPB1). MICA/B and ULBP ligands interact with the activating receptors NKG2D to facilitate their capacity to remove altered or virally infected cells. The NK cells considered effective cells to kill tumor cells and viruses thus these cells developed a varaity of protection mechanisms to avoied natural killer lysis by production different typpes of NKG2D ligands. Targeted cells may degrade ligand transcripts through microRNAs or alter them at the protein level to prevent their appearance at the cell surface via shedding, with the added benefit that shed ligands desensitize NKG2D receptors and prevent destruction by NK cells.[18],[30] The present study demonstrates an increase in soluble ligand MICA in AML patients at diagnosis and after 14 days of therapy, which is consistent with previous research versus ULPB1, whose level decreased; this may be due to the rise in another form of soluble legends, such as ULPB2, ULPB3, ULPB4, ULPB5, and ULPB6.[31],[32] Consistent with the hypothesis that NKG2DL releasing is a tumor escape mechanism, higher levels of soluble NKG2DL have been found in the serum of malignancies patients, and associations between soluble NKG2DL and tumor stage and/or progression have been reported.[32] The soluble NKG2D-L may bind to NKG2D, induce the downregulation of NKG2D expression on NK cells and CD8 + T-cells, and decrease the concentration of NKG2D-L on the surface of tumor cells, therefore inhibiting NKG2D-mediated immune recognition and elimination.[33] It has been hypothesized that adsorption apheresis may be used to remove soluble NKG2D-L from patients' plasma.[34] Accumulating data indicate that soluble NKG2D-L, as a biomarker, may restrict immune checkpoint blockage.[35],[36] Some clinically used chemotherapeutic medicines (e.g., Epirubicin) block sMICA shedding by downregulation of A disintegrin and Metalloprotinase 10 (ADAM10), resulting in decreased sMICA levels in vivo. In some circumstances, soluble NKG2DL in the serum of cancer patients is functionally active and able to downregulate NKG2D expression and suppress NKG2D-dependent cytotoxicity[37] and also low level of NKG2D soluble ligand in CR gives chance for survival more than 1 year.[38]
Conclusion | |  |
The level of sMICA was elevated in AML patients practically increasing in no remission patients and decreasing in remission patients, while sULPB1 is not significantly different among AML patients at diagnosis, patients at 14 days of treatment, and controls. Therefore, sMICA could be a prognostic biomarker for AML.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
References | |  |
1. | Kitamura T, Inoue D, Okochi-Watanabe N, Kato N, Komeno Y, Lu Y, et al. The molecular basis of myeloid malignancies. Proc Jpn Acad Ser B Phys Biol Sci 2014;90:389-404. |
2. | Bennett JM, Orazi A. Diagnostic criteria to distinguish hypocellular acute myeloid leukemia from hypocellular myelodysplastic syndromes and aplastic anemia: Recommendations for a standardized approach. Haematologica 2009;94:264-8. |
3. | Wiese M, Daver N. Unmet clinical needs and economic burden of disease in the treatment landscape of acute myeloid leukemia. Am J Manag Care 2018;24:S347-55. |
4. | Miller KD, Goding Sauer A, Ortiz AP, Fedewa SA, Pinheiro PS, Tortolero-Luna G, et al. Cancer statistics for Hispanics/Latinos, 2018. CA Cancer J Clin 2018;68:425-45. |
5. | Li K, Chen L, Zhang H, Wang L, Sha K, Du X, et al. High expression of COMMD7 is an adverse prognostic factor in acute myeloid leukemia. Aging (Albany NY) 2021;13:11988-2006. |
6. | Döhner H, Weisdorf DJ. [Acute myeloid leukemia]. New England Journal of Medicine, 2015;373 (Supp12):1136-52. |
7. | Solomon SR, Solh M, Jackson KC, Zhang X, Kent Holland H, Bashey A, et al. Real-world outcomes of unselected elderly acute myeloid leukemia patients referred to a leukemia/hematopoietic cell transplant program. Bone Marrow Transplant 2020;55:189-98. |
8. | Maleki Behzad M, Abbasi M, Oliaei I, Ghorbani Gholiabad S, Rafieemehr H. Effects of lifestyle and environmental factors on the risk of acute myeloid leukemia: Result of a hospital-based case-control study. J Res Health Sci 2021;21:e00525. |
9. | De-Morgan A, Meggendorfer M, Haferlach C, Shlush L. Male predominance in AML is associated with specific preleukemic mutations. Leukemia 2021;35:867-70. |
10. | Barrett AJ. Acute myeloid leukaemia and the immune system: Implications for immunotherapy. Br J Haematol 2020;188:147-58. |
11. | Velcheti V, Schalper K. Basic overview of current immunotherapy approaches in cancer. Am Soc Clin Oncol Educ Book 2016;35:298-308. |
12. | Taghiloo S, Asgarian-Omran H. Immune evasion mechanisms in acute myeloid leukemia: A focus on immune checkpoint pathways. Crit Rev Oncol Hematol 2021;157:103164. |
13. | Pegram HJ, Andrews DM, Smyth MJ, Darcy PK, Kershaw MH. Activating and inhibitory receptors of natural killer cells. Immunol Cell Biol 2011;89:216-24. |
14. | Orr MT, Lanier LL. Natural killer cell education and tolerance. Cell 2010;142:847-56. |
15. | Sandoval-Borrego D, Moreno-Lafont MC, Vazquez-Sanchez EA, Gutierrez-Hoya A, López-Santiago R, Montiel-Cervantes LA, et al. Overexpression of CD158 and NKG2A inhibitory receptors and underexpression of NKG2D and NKp46 activating receptors on NK cells in acute myeloid leukemia. Arch Med Res 2016;47:55-64. |
16. | Sanchez-Correa B, Gayoso I, Bergua JM, Casado JG, Morgado S, Solana R, et al. Decreased expression of DNAM-1 on NK cells from acute myeloid leukemia patients. Immunol Cell Biol 2012;90:109-15. |
17. | Pende D, Spaggiari GM, Marcenaro S, Martini S, Rivera P, Capobianco A, et al. Analysis of the receptor-ligand interactions in the natural killer-mediated lysis of freshly isolated myeloid or lymphoblastic leukemias: Evidence for the involvement of the poliovirus receptor (CD155) and nectin-2 (CD112). Blood 2005;105:2066-73. |
18. | Diermayr S, Himmelreich H, Durovic B, Mathys-Schneeberger A, Siegler U, Langenkamp U, et al. NKG2D ligand expression in AML increases in response to HDAC inhibitor valproic acid and contributes to allorecognition by NK-cell lines with single KIR-HLA class I specificities. Blood 2008;111:1428-36. |
19. | Hilpert J, Grosse-Hovest L, Grünebach F, Buechele C, Nuebling T, Raum T, et al. Comprehensive analysis of NKG2D ligand expression and release in leukemia: Implications for NKG2D-mediated NK cell responses. J Immunol 2012;189:1360-71. |
20. | Bain BJ. Leukaemia diagnosis. John Wiley & Sons. 2010. |
21. | Shallis RM, Wang R, Davidoff A, Ma X, Zeidan AM. Epidemiology of acute myeloid leukemia: Recent progress and enduring challenges. Blood Rev 2019;36:70-87. |
22. | Abdulridha RH, Jawad NK, Numan AT. Prevalence and risk of leukemia reported cases, observational descriptive statistic from Iraqi center for hematology in Baghdad province. Indian J Forensic Med Toxicol 2021;15:2428-33. |
23. | Mjali A, Al-Shammari HH, Abbas NT, Azeez ZD, Abbas SK. Leukemia epidemiology in Karbala province of Iraq. Asian Pac J Cancer Care 2019;4:135-9. |
24. | Karim ZA, Khidhir KG, Ahmed RA, Hassan HA, Karim DO. Leukemia study in sulaymaniyah province, Kurdistan, Iraq. Chin Med J (Engl) 2016;129:244-5. |
25. | Juliusson G, Lehmann S, Lazarevic V. Epidemiology and Etiology of AML. In Acute Myeloid Leukemia. Springer, Cham. 2021. p. 1-22. |
26. | Abelson S, Collord G, Ng SW, Weissbrod O, Mendelson Cohen N, Niemeyer E, et al. Prediction of acute myeloid leukaemia risk in healthy individuals. Nature 2018;559:400-4. |
27. | Song X, Peng Y, Wang X, Chen Y, Jin L, Yang T, 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. Acta Haematol 2018;139:115-27. |
28. | Shysh AC, Nguyen LT, Guo M, Vaska M, Naugler C, Rashid-Kolvear F. The incidence of acute myeloid leukemia in Calgary, Alberta, Canada: A retrospective cohort study. BMC Public Health 2017;18:94. |
29. | Smith A, Howell D, Patmore R, Jack A, Roman E. Incidence of haematological malignancy by sub-type: A report from the haematological malignancy research network. Br J Cancer 2011;105:1684-92. |
30. | Machuldova A, Holubova M, Caputo VS, Cedikova M, Jindra P, Houdova L, et al. Role of polymorphisms of NKG2D receptor and its ligands in acute myeloid leukemia and human stem cell transplantation. Front Immunol 2021;12:651751. |
31. | Li Y, Sun R. Tumor immunotherapy: New aspects of natural killer cells. Chin J Cancer Res 2018;30:173-96. |
32. | Chitadze G, Bhat J, Lettau M, Janssen O, Kabelitz D. Generation of soluble NKG2D ligands: Proteolytic cleavage, exosome secretion and functional implications. Scand J Immunol 2013;78:120-9. |
33. | Zwirner NW, Fuertes MB, Girart MV, Domaica CI, Rossi LE. Cytokine-driven regulation of NK cell functions in tumor immunity: Role of the MICA-NKG2D system. Cytokine Growth Factor Rev 2007;18:159-70. |
34. | Döhner H, Estey E, Grimwade D, Amadori S, Appelbaum FR, Büchner T, et al. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. Blood 2017;129:424-47. |
35. | Weil S, Memmer S, Lechner A, Huppert V, Giannattasio A, Becker T, et al. Natural killer group 2D ligand depletion reconstitutes natural killer cell immunosurveillance of head and neck squamous cell carcinoma. Front Immunol 2017;8:387. |
36. | Nakamura Y. Biomarkers for immune checkpoint inhibitor-mediated tumor response and adverse events. Front Med (Lausanne) 2019;6:119. |
37. | Kohga K, Takehara T, Tatsumi T, Miyagi T, Ishida H, Ohkawa K, et al. Anticancer chemotherapy inhibits MHC class I-related chain a ectodomain shedding by downregulating ADAM10 expression in hepatocellular carcinoma. Cancer Res 2009;69:8050-7. |
38. | Chitadze G, Kabelitz D. Immune surveillance in glioblastoma: Role of the NKG2D system and novel cell-based therapeutic approaches. Scand J Immunol 2022;96:e13201. |
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7]
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