Abstract
This is a systematic review and meta-analysis evaluating the prognostic significance of epigenetic mutations on the overall survival (OS) in Acute Myeloid Leukemia (AML). We searched for studies evaluating epigenetic mutations in AML (up to November 2018) in PubMed, Trip database and Cochrane library. Hazard ratio (HR) of outcomes were extracted, and random-effects model was used to pool the results. A total of 10,002 citations were retrieved from the search strategy; 42 articles were identified for the meta-analysis (ASXL1 = 7, TET2 = 8, DNMT3A = 12, IDH =15), with fair to good-quality studies. The pooled HR was 1.88 (95% CI: 1.49−2.36) for ASXL1 mutation, 1.39 (95% CI: 1.18−1.63) for TET2 mutation, 1.35 (95% CI 1.16-1.56) for DNMT3a and 1.54 (95% CI: 1.15-2.06) for IDH mutation. However, there was a substantial heterogeneity in the DNMT3a and IDH studies. In conclusion epigenetic mutations in ASXL1, TET2, DNMT3a and IDH adversely impact OS in patients with AML albeit with considerable heterogeneity and possibly publication bias. Further studies are required to address these limitations.
Introduction
Acute myeloid leukemia (AML) is characterized by the uncontrolled proliferation of myeloid blast cells in the bone marrow and peripheral blood (1). Breakthroughs in the past have contributed to our understanding of the genetic failures and the changing biology in the myeloid cells that underlie the initiation and progression of the disease (2). With the application of global DNA sequencing, several recurrent gene mutations have been identified, which has led to improvements in prognostication and molecular characterization within these subsets (3).
It is now recognized that genetic and epigenetic modifications are similarly important in the pathogenesis of AML (2). Epigenetic modification refers to variability in gene expression without underlying genetic changes (4, 5). DNA methylation and histone modifications are the well-known molecular epigenetic mechanisms studied in cancer biology (4). These epigenetics affect gene expression leading to leukemogenesis through silencing tumor suppressors and activation of oncogenes (3). Multiple studies integrating epigenetic modifiers like DNMT3a, IDH1, IDH2, TET2, ASXL1 and EZH2 and clinical outcomes in AML patients identified mutations as markers prognostic stratification (1). In addition to prognostic significance, since these alterations do not change the DNA sequences and are pharmacologically reversible, they have been regarded as optimal targets for what is now known as epigenetic therapy (2).
Several studies and reviews assessed the prognostic significance of these mutations in AML patients; however, the results are widely variable. In a study performed by Ravandi et al. (6) and colleagues, IDH mutation showed no impact on response to therapy nor Overall Survival (OS). However, Shunichiro Yamaguchi and colleagues (7) found IDH mutations are associated with poor prognosis. A meta-analysis performed by Qingyu Xu and colleagues (8) included thirty-three studies and concluded that IDH1 is associated with poor prognosis and IDH2 is associated with good prognosis. Similarly, studies assessing the impact of DNMT3A, TET2, ASXL1 and EZH2 showed conflicting results. Thus, it’s necessary to perform a systematic review and meta-analysis to clarify the prognostic significance of these mutations in AML patients. The rationale of our study is to evaluate the impact of epigenetic mutations in AML patients with the inclusion of recent publications and larger sample size.
Methods
Search strategy
We performed a literature search on several electronic databases, including PubMed (https://pubmed.ncbi.nlm.nih.gov), Trip database (https://www.tripdatabase.com) and Cochrane library (https://www.cochranelibrary.com) up to November 2018. We used various medical subject headings (MeSH terms) and free text search like mutations, epigenetic, acute myeloid leukemia, acute myeloblastic leukemia, acute myelocytic leukemia and AML.
Study selection
We included adult and pediatric AML studies that received any kind of therapy and were tested for epigenetic mutations (DNMT3a, IDH1, IDH2, TET2, ASXL1 and EZH2). In addition, observational and experimental studies were included. We excluded studies not published in the English language or those not reporting outcomes of interest. Two reviewers (RR and FB) independently screened all citations. Unrelated articles and duplicate publications were excluded after the title and abstract screening. Full-text articles were obtained from the remaining articles and were reviewed carefully for eligibility. Any disagreement between the two reviewers was resolved by discussion or involving a third reviewer (MK).
Data abstraction
Data were extracted using a common data collection form which was designed specifically for this study. Two reviewers abstracted the data independently and subsequently compared the results. Any disagreement was resolved by discussion and consensuses. The main variables extracted were patient characteristics, type of therapy, cytogenetics and molecular features, Hazards ratio (HR) and 95% Confidence Interval (CI) for the OS. In all studies that did not report HR or CI, we used Parmar’s methods to estimate the HR from the available data (9). Furthermore, corresponding authors were contacted for missing data.
Risk of bias assessment
The two reviewers assessed the quality of included studies independently using Newcastle-Ottawa-Scale (NOS) for observational studies. The NOS assessment tool included three main elements related to selection, comparability and outcome. A study can be awarded as good, fair or poor quality based on the maximum score. Any discrepancy between the reviewers was resolved by discussion. Cohen kappa coefficient (k) was calculated to assess the agreement.
Analysis and data synthesis
All statistical analyses were performed using R Program version 3.1.2 (R Core Team (2020); R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/). Hazards ratio was used to assess the prognostic impact of epigenetic mutations compared to wild type. The random-effects model was used to pool the results for the HR of OS. Pooled HR less than 1 indicated better outcome among mutated patients. A p-value of 0.05 or less is considered statistical significance. The heterogeneity among studies was assessed by Cochran I2 and Chi-squared test. I-square (I2) < 30%, 30%–50%, 50%–75%, and >75% were defined as low, moderate, substantial, and considerable heterogeneity, respectively. No ethical approval was required for this study as all data were abstracted from published papers.
Results
Study selection
The procedure of study selection is presented in Figure 1. Initially, 10,002 citations were retrieved from the database search. After title screening, 9862 articles were excluded either because not assessing epigenetic mutations, not AML patients or duplicates. We screened the remaining 140 articles. Of these, 49 were excluded after abstract screening for the following reasons: 14 full text not available, ten review articles/case reports and 25 not reporting the outcome of interest. Full-text screening further excluded 49 articles due to the absence of survival analysis or incomplete data. Finally, 42 articles were identified for the systematic review which met the full inclusion criteria. Of these, seven articles were for ASXL1 mutation (10–16), eight for TET2 (17–24), twelve for DNMT3A (25–36) and fifteen for IDH mutation (6, 7, 37–48).
Figure 1

Study selection for the systematic review and meta-analysis. AML, Acute myeloid leukemia; ASXL1, Additional Sex Combs-Like 1; TET2, Ten-Eleven Translocation 2; DNMT3A, DNA Methyltransferase 3 Alpha; IDH, Isocitrate dehydrogenase.
Study characteristics and risk of bias
Table 1 presents the characteristics of the 42 included studies. For ASXL1 mutation articles, five were from Europe and two from Asia. The total number of patients included was 4115 patients; among these, 276 harbored the mutation. One article was for pediatric patients, and the remaining six articles were for adult patients. Eight articles were for TET2 mutation, with a total number of patients 3286 among these 364 had TET2 mutation. Three studies were from Asia, four from Europe and one from Europe and the USA. Finally, for DNMT3A mutation papers total of 12 articles were included, seven from Europe, four from the USA and one from Asia, with a total number of patients 5555 and 1324 with the mutation.
Table 1
| First Author | Year | Region | Mutation | Description | NOS | Total | Mutated | Age (range) | WBC (Range) | Cytogenetic abnormalitis | HR estimation |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Chou WC | 2010 | Taiwan | ASXL1 | AML | 6 | 360 | 26 | 66 | _ | Favourable 8, Intermediate 17, Adverse 1, Unknown 0 | HR |
| Pratcorona M | 2012 | Netherlands | ASXL1 | AML | 6 | 807 | 41 | 54 (15-74) | 13 (1.1-220) | _ | HR |
| Schnittger S | 2013 | Germany | ASXL1 | CN-AML | 5 | 481 | 51 | 71.8 | 34.2 | Favourable 0, Intermediate 51, Adverse 0, Unknown 0 | Survival curve |
| El-Sharkawi D | 2014 | UK | ASXL1 | AML | 7 | 367 | 32 | 61.5 (19-74) | 42.75 (3-528) | Favourable 1, Intermediate 20, Adverse 2, Unknown 9 | HR |
| Devillier R | 2015 | France | ASXL1 | AML | 5 | 35 | 14 | _ | _ | Favourable 0, Intermediate 14, Adverse 0, Unknown 0 | HR |
| Paschka P | 2015 | Germany | ASXL1 | AML | 6 | 1696 | 103 | 53 (36-61) | 6.5 (0.7-126.5) | Favourable 10, Intermediate 65, Adverse 24, Unknown 4 | Survival curve |
| Yamato G | 2017 | Japan | ASXL1 | AML | 8 | 369 | 9 | 9 (2.2-17.9) | 6.9 (3.8-218.2) | Favourable 7, Intermediate 1, Adverse 0, Unknown 1 | Survival curve |
| Chou WC | 2011 | Taiwan | TET2 | AML | 6 | 486 | 46 | 68 (21-90) | 43.16 (1.68-277.25) | Favourable 0, Intermediate 46, Adverse 0, Unknown 0 | HR |
| Kosmider O | 2011 | France | TET2 | AML | 4 | 247 | 49 | 71 | 20.3 (6-98.9) | Favourable 0, Intermediate 25, Adverse 15, Unknown 9 | HR |
| Metzeler KH | 2011 | USA/Germany | TET2 | CN-AML | 5 | 418 | 95 | 66 (20-80) | 33.5 (1.6-450) | Favourable 0, Intermediate 95, Adverse 0, Unknown 0 | Survival curve |
| Gaidzik VI | 2012 | Germany | TET2 | AML | 8 | 783 | 60 | 51 (19-60) | 20.9 (0.8-192) | Favourable 11, Intermediate 39, Adverse 7, Unknown 3 | Survival curve |
| Aslanyan MG | 2014 | Netherlands | TET2 | AML | 7 | 357 | 27 | 54 (24-59) | 32.1 (1.1-240.8 | Favourable 0, Intermediate 15, Adverse 1, Unknown 11 | HR |
| Damm F | 2014 | Germany | TET2 | CN-AML | 7 | 215 | 13 | 53 (38-59) | 32.1 (1.4-98.8) | Favourable 0, Intermediate 13, Adverse 0, Unknown 0 | HR |
| Tian X | 2014 | China | TET2 | CN-AML | 6 | 373 | 60 | 50 (16-83) | 78.6 (1.3-397) | Favourable 0, Intermediate 60, Adverse 0, Unknown 0 | Survival curve |
| Ahn JS | 2015 | Korea | TET2 | CN-AML | 5 | 407 | 14 | _ | _ | Favourable 0, Intermediate 14, Adverse 0, Unknown 0 | HR |
| Ley TJ | 2010 | USA | DNMT3a | AML | 6 | 281 | 62 | 53.1 | 46.4 | Favourable 0, Intermediate 56, Adverse 4, Unknown 2 | Survival curve |
| LaRochelle O | 2011 | France | DNMT3a | AML-IR | 7 | 149 | 39 | 47 (20-63) | 52 (1-250) | Favourable 0, Intermediate 39, Adverse 0, Unknown 0 | HR |
| Thol F | 2011 | Germany | DNMT3a | AML | 6 | 489 | 87 | 52 (30-60) | 38 (0.5-328.2) | Favourable 1, Intermediate 82, Adverse 4, Unknown 0 | HR |
| Ribeiro AF | 2012 | Netherlands | DNMT3a | AML | 6 | 415 | 96 | 50.5 (18-60) | 52.9 (1.1-278) | Favourable 0, Intermediate 85, Adverse 6, Unknown 5 | HR |
| Marcucci G | 2012 | USA | DNMT3a | CN-AML | 6 | 415 | 142 | 61 (22-82) | 43.4 (0.9-434.1) | Favourable 0, Intermediate 142, Adverse 0, Unknown 0 | HR |
| Renneville A | 2012 | France | DNMT3a | CN-AML | 7 | 123 | 36 | 47 (23-58) | 13 (1-152) | Favourable 0, Intermediate 36, Adverse 0, Unknown 0 | Survival curve |
| Marková J | 2012 | Czechia | DNMT3a | AML-IR | 6 | 226 | 67 | _ | _ | Favourable 0, Intermediate 67, Adverse 0, Unknown 0 | Survival curve |
| Hou HA | 2012 | Taiwan | DNMT3a | AML | 6 | 500 | 70 | 61 (16-87) | 32.49 (0.65-340.4) | Favourable 0, Intermediate 62, Adverse 4, Unknown 4 | HR |
| Gaidzik VI | 2013 | Germany | DNMT3a | AML | 7 | 1770 | 367 | 50.5 (18-60) | 24.5 (0.2-532) | _ | Survival curve |
| Ostronoff F | 2013 | USA | DNMT3a | AML | 8 | 191 | 37 | 68 (57-81) | 37 | Favourable 0, Intermediate 24, Adverse 1, Unknown 12 | HR |
| Gale RE | 2015 | UK | DNMT3a | AML-IR | 6 | 914 | 272 | 48 (18-67) | 37.3 (0.7-439) | Favourable 0, Intermediate 272, Adverse 0, Unknown 0 | Survival curve |
| Sehgal AR | 2015 | USA | DNMT3a | AML | 5 | 152 | 49 | 54.4 (26-78) | 76.56 | Favourable 0, Intermediate 40, Adverse 5, Unknown 4 | Survival curve |
| Schnittger S | 2010 | Germany | IDH1 | AML | 7 | 769 | 52 | 67.2 (21.8-85.8) | 5 (0.3-255) | _ | Survival curve |
| Green CL | 2010 | UK | IDH1 | AML | 8 | 1333 | 107 | _ | _ | _ | HR |
| Boissel N | 2010 | France | IDH2 | CN-AML | 6 | 205 | 12 | 57 (41-66) | 3 (0.6-11) | Favourable 0, Intermediate 12, Adverse 0, Unknown 0 | Survival curve |
| Paschka P | 2010 | Germany | IDH | CN-AML | 8 | 89 | 29 | 47 (27-60) | 35 (0.2-175) | Favourable 0, Intermediate 29, Adverse 0, Unknown 0 | Survival curve |
| Abbas S | 2010 | Netherlands | IDH1 | AML | 6 | 743 | 49 | 50 (20-71) | 48 (1-400) | _ | Survival curve |
| Abbas S | 2010 | Netherlands | IDH2 | AML | 6 | 780 | 86 | 50 (18-72) | 42 (18-72) | _ | Survival curve |
| Marcucci G | 2010 | USA | IDH | CN-AML | 6 | 52 | 14 | 62 (21-82) | 24.6 (0.9-152.1) | Favourable 0, Intermediate 14, Adverse 0, Unknown 0 | Survival curve |
| Damm F | 2011 | Germany | IDH | AML | 7 | 459 | 18 | _ | _ | _ | Survival curve |
| Chou WC | 2011 | Taiwan | IDH2 | AML | 8 | 309 | 36 | 55 (19-84) | 16.5 (0.65-340) | Favourable 0, Intermediate 45, Adverse 5, Unknown 4 | Survival curve |
| Nomdedéu J | 2012 | Spain | IDH | CN-AML | 7 | 120 | 27 | 58 (17-71) | 23.05 (0.8-408) | Favourable 0, Intermediate 27, Adverse 0, Unknown 0 | Survival curve |
| Ravandi F | 2012 | USA | IDH | AML | 8 | 170 | 52 | _ | _ | _ | Survival curve |
| Lin J | 2012 | China | IDH | AML | 8 | 114 | 12 | _ | _ | _ | Survival curve |
| Guan L | 2013 | China | IDH1 | AML | 9 | 315 | 31 | 41 (14-66) | 56 (1.07-456) | _ | Survival curve |
| Yamaguchi S | 2014 | Japan | IDH | AML | 7 | 226 | 37 | 60 (16-82) | 16.5 (1-408) | _ | Survival curve |
| Aref S | 2015 | Egypt | IDH1 | CN-AML | 5 | 110 | 35 | _ | 52.1 | Favourable 0, Intermediate 35, Adverse 0, Unknown 0 | Survival curve |
Description of the studies included in the systematic review.
NOS, Newcastle-Ottawa-Scale; WBC, White blood cells; HR, Hazards ratio; AML, Acute myeloid leukemia; CN, cytogenetically normal; ASXL1, Additional Sex Combs-Like 1; TET2, Ten-Eleven Translocation 2; DNMT3A, DNA Methyltransferase 3 Alpha; IDH, Isocitrate dehydrogenase.
Furthermore, IDH mutation papers were 15 articles. The total number of patients was 5794, and mutated was 597. Eight papers were from Europe, four from Asia, two from the USA and one from Africa. NOS for all 42 included studies ranged from fair to good quality. Cohen kappa coefficient (k) ranged from 0 - 1, with the lowest agreement in exposure and duration of follow-up and highest agreement in confounders.
The details of chemotherapy protocol used in each publication are summarized in Supplementary Material. Majority received intensive cytarabine and anthracycline based chemotherapy. However a subset of frail patients received less intensive chemotherapy, palliative or best supportive care.
Overall survival
As shown in Figure 2, ASXL1 mutation was associated with worse overall survival (HR, 1.88; 95% CI, 1.49 – 2.36, P 0.1316; heterogeneity: I-squared 42.6%). However, this was statistically not significant and was associated with moderate heterogeneity. In addition, the funnel plot showed asymmetry suggesting publication bias or a small study effect.
Figure 2

Forest plot and funnel plot of the HR for overall survival in ASXL1 mutation. The first author and year of publication is provided for each study. The hazards ratio (boxes) with 95% confidence intervals (CI, horizontal lines) were calculated, the pooled hazards ratio (diamond) was estimated using random effect model. The P value for comparing heterogeneity between subgroups was calculated using I-squared. ASXL1, Additional Sex Combs-Like 1.
The results for TET2 mutation as presented in Figure 3. It shows that TET2 is associated with statistically insignificant worse overall survival with low heterogeneity (HR, 1.39; 95% CI, 1.18 – 1.63, P 0.1675; heterogeneity: I-squared 27.6%). The funnel plot is symmetrical, suggesting no publication bias.
Figure 3

Forest plot and funnel plot of the HR for overall survival in TET2 mutation. The first author and year of publication is provided for each study. The hazards ratio (boxes) with 95% confidence intervals (CI, horizontal lines) were calculated, the pooled hazards ratio (diamond) was estimated using random effect model. The P value for comparing heterogeneity between subgroups was calculated using I-squared. TET2, Ten-Eleven Translocation 2.
For DNMT3A mutations, the forest plot is shown in Figure 4, the pooled HR is associated with worse overall survival, and the results are statistically significant, however with substantial heterogeneity (HR, 1.35; 95% CI, 1.16 – 1.56, P < 0.05; heterogeneity: I-squared 71.0%). In addition, the funnel plot is suggestive of publication bias, given the asymmetry as assessed visually.
Figure 4

Forest plot and funnel plot of the HR for overall survival in DNMT3a mutation. The first author and year of publication is provided for each study. The hazards ratio (boxes) with 95% confidence intervals (CI, horizontal lines) were calculated, the pooled hazards ratio (diamond) was estimated using random effect model. The P value for comparing heterogeneity between subgroups was calculated using I-squared. DNMT3A, DNA Methyltransferase 3 Alpha.
As shown in Figure 5, IDH mutation is associated with statistically significant worse OS, however with considerable heterogeneity in results (HR, 1.54; 95% CI, 1.15 – 2.06, P <0.05; heterogeneity: I-squared 84.8%). The funnel plot presented is not suggestive of publication bias.
Figure 5

Forest plot and funnel plot of the HR for overall survival in IDH mutation. The first author and year of publication is provided for each study. The hazards ratio (boxes) with 95% confidence intervals (CI, horizontal lines) were calculated, the pooled hazards ratio (diamond) was estimated using random effect model. The P value for comparing heterogeneity between subgroups was calculated using I-squared. IDH, Isocitrate dehydrogenase.
Discussion
In this systematic review and meta-analysis, we found that all epigenetic modifiers mutations (ASXL1, TET2, DNMT3A and IDH) are associated with worse OS in patients with AML based on fair to good-quality studies. However, there was substantial heterogeneity for IDH and DNMT3A mutation studies, respectively.
For ASXL1 mutation, the results revealed a prominent worse overall survival among AML patients. This was consistent among all the included studies. Shivarov V. and his colleagues (49) reported a similar outcome based on the assessment of six large trials and a total of 3311 adult patients. Since there was a single study from the pediatric population, the results cannot be applied to this population. An adverse prognosis was also observed with TET2 mutations, consistent with what Wang R. and his colleagues (50) reported. DNMT3A mutation showed a significantly worse prognosis than the wild type, consistent with what is reported in the literature (51, 52).
Similarly, our data on IDH mutation is reported to show an adverse effect on prognosis. Moreover, we found out that these mutations were frequently found in the intermediate-risk group of the international prognostic scoring system, as shown in Table 1. They were also associated with older patient age and higher presenting white blood cell count.
Although there was substantial heterogeneity in DNMT3A and IDH studies, this could be explained by the year of the publication, age of the patients and cytogenetic risk profile. There has been improvement in supportive care over the last few years, and with the emergence of new targeted therapies, the OS of these patients slightly improved. Jakobsen and colleagues conducted a large population based registry study and they concluded a significant temporal overall survival improvement among patient with AML since 2000. This was particularly seen among the patients aged between 50-75 years where they got curative chemotherapy and option of allogenic stem cell transplant was offered in some cases (53). Furthermore, many other factors affect response to therapy and OS, especially the presence of FLT3 mutation. Publication bias was suggested among ASXL1 and DNMT3A mutation probably; studies with no effect were not published. This was a major limitation to our estimate of the outcome of these mutations.
Our study has several limitations. First, the lack of data from many studies and the high possibility of publication bias could impact the outcome. Second, we did not perform subgroup analysis to assess the impact of the year of the publication to explain the heterogeneity, as older publications probably had worse outcomes. Finally, we did not consider individual patient data, and our analysis was based on cumulative data from different studies.
In conclusion, this meta-analysis revealed that ASXL1, TET2, DNMT3A and IDH mutations had an adverse effect on the survival of AML patients albeit with considerable heterogeneity and possibly publication bias. Further studies are required to address these limitations.
Acknowledgments
Would like to thank Oman Medical Specialty Board (OMSB) library for providing full text articles.
Publisher’s note
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Statements
Data availability statement
The original contributions presented in the study are included in the article/Supplementary Material. Datasets are available on request from the corresponding author.
Author contributions
MA-K suggested the idea, optimized the search strategy, performed the analysis and reviewed and edited the manuscript. FA-B performed the search, extracted the information and drafted the manuscript. RA-R extracted the data and gave final approval. ZA-H and BA-A gave the final approval of the manuscript. All authors contributed to the article and approved the submitted version.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc.2022.967657/full#supplementary-material
Abbreviations
AML, Acute myeloid leukemia; ASXL1, Additional Sex Combs-Like 1; TET2, Ten-Eleven Translocation 2; DNMT3A, DNA Methyltransferase 3 Alpha; IDH, Isocitrate dehydrogenase; FLT3, Fms Related Receptor Tyrosine Kinase 3; OS, Overall survival; HR, Hazards Ratio; WBC, White Blood Cells.
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Summary
Keywords
AML, epigenetics, mutation, ASXL1, Dnmt3a, IDH, TET2, review – systematic
Citation
Al-Bulushi F, Al-Riyami R, Al-Housni Z, Al-Abri B and Al-Khabori M (2022) Impact of mutations in epigenetic modifiers in acute myeloid leukemia: A systematic review and meta-analysis. Front. Oncol. 12:967657. doi: 10.3389/fonc.2022.967657
Received
13 June 2022
Accepted
11 October 2022
Published
28 November 2022
Volume
12 - 2022
Edited by
Mohamed A. Yassin, Hamad Medical Corporation, Qatar
Reviewed by
Jatinder K. Lamba, University of Florida, United States; Honar Cherif, Hamad Medical Corporation, Qatar
Updates
Copyright
© 2022 Al-Bulushi, Al-Riyami, Al-Housni, Al-Abri and Al-Khabori.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Murtadha Al-Khabori, khabori@squ.edu.om; mkkhabori@gmail.com
This article was submitted to Hematologic Malignancies, a section of the journal Frontiers in Oncology
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