Association between gene mutations and certain blood cell indices in patients diagnosed with myelodysplastic neoplasms
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- Published online on: March 22, 2024 https://doi.org/10.3892/wasj.2024.238
- Article Number: 23
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Copyright : © Nguyen et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY 4.0].
Abstract
Introduction
Myelodysplastic neoplasms (previous terminology, myelodysplastic syndromes; MDS) are characterized by ineffective hemopoiesis, bone marrow dysplasia, cytopenia and an increased risk of leukemic transformation (1). Gene myeloid mutations play a role in the pathogenesis of MDS; thus, these mutations become a contributing factor to the diagnosis, classification and prognosis of patients with the disease (2-5). The minimal diagnostic criteria proposed by the World Health Organization (WHO; from 2001 to 2008) included gene mutations [e.g., splicing factor 3b subunit 1 (SF3B1)] in the co-criteria (6). The WHO 2016 classification had used the SF3B1 mutation as a criterion in the classification of MDS (7). Subsequently, in the WHO 2022 classification, the SF3B1 and TP53 mutations were used to classify MDS (8). Therefore, gene mutations play an increasingly critical role in the diagnosis and classification of MDS. Furthermore, previous studies have demonstrated that gene mutations can be considered a key prognostic factor for MDS (9-11). The Molecular International Prognostic Scoring System (IPSS-M), which combines the International Prognostic Scoring System-Revised (IPSS-R) with molecular data including 31 gene mutations, appears to be superior to previous prognostic systems (12-14). However, its disadvantage is its high cost; thus, it is difficult for this new system to be applied in developing countries.
Of note, these gene mutations can also directly influence hematopoiesis due to their involvement in pathogenesis. The SF3B1 mutation is related to sideroblastic anemia; thus, the WHO 2022 classification determined that the detection of 15% ring sideroblasts may substitute for the SF3B1 mutation (15). It would be of interest to determine whether it is possible to use blood or bone marrow cell indices to predict the presence of gene mutations, thus providing reasonable and economical indications. Thus, the aim of the present study was to assess the association between gene mutations and certain cell indices in patients diagnosed with MDS.
Patients and methods
Patients
A retrospective cross-sectional study was conducted at the National Institute of Hematology and Blood Transfusion, Hanoi, Vietnam. Patients newly diagnosed with MDS who had been examined for myeloid genes mutations from January, 2018 to June, 2021 were consecutively recruited in the present study. The study protocol was approved by the Institutional Review Board of the National Institute of Hematology and Blood Transfusion (no. 939/QĐ-HHTM). Patient consent was waived by the committee, since this study was a retrospective observational study. All details of the patients were deidentified.
Next-generation sequencing (NGS)
NGS was performed with 51 myeloid gene mutations. The panel included gene groups for DNA methylation, chromatin modification, RNA splicing, cohesin complex, transcription, cytokine receptor/tyrosine kinase, RAS signaling, checkpoint/cell cycle and others (Table I). SF3B1, TET2, ASXL1 and DMNT3A were analyzed using the MiSeq Reagent kit (Illumina, Inc.). Other gene mutations were analyzed using the Hema 50 Panel (Dxome Co., Ltd., Korea).
Data collection
Data from patients, including clinical characteristics, peripheral blood and bone marrow cell indices, as well as cytogenetics report, recorded before starting treatment, were collected from medical record of the patients.
Diagnosis and classification of MDS
The determination of the diagnosis of MDS was based on the proposal of the minimal diagnostic criteria of MDS (5). Patients with MDS were classified according to the WHO 2022 criteria (15). The risk was calculated according to IPSS-M (9,16).
Statistical analysis
Qualitative variables (clinical characteristic, karyotype, cytogenetic risk, type of MDS and IPSS-M) and quantitative variables (hemoglobin, neutrophil count, platelet count, percentage of peripheral blood blast, bone marrow cell count and the percentage of bone marrow blasts) were analyzed according to sex and classification of age (50 years). Comparisons of qualitative variables were performed using the χ2 test or Fisher's exact test. Comparisons of quantitative variables were performed using an independent samples t-test or the Mann-Whitney U test according to normal or non-normal distribution. The presence of gene mutations was expressed as frequency and percentage. The differences between quantitative variables (hemoglobin, neutrophil count, platelet count, the percentage of peripheral blood blast, bone marrow cell count and the percentage of bone marrow blasts) were compared between two groups according to the presence of each mutation using an independent samples t-test or the Mann-Whitney U test according to normal or non-normal distribution. In variables for which a statistically significant difference was found, receiver operating characteristic (ROC) curve analysis was performed to separate the significant variables to determine a cut-off value. An area under the curve (AUC) value >0.8 was considered good for separation. The cut-off value was determined based on the coordinates of the curve. The cut cut-off value, the sensitivity (Se) and the specificity (Sp) were selected according to the Youden index (J) as follows: [J=max (Se + Sp -1)] with the highest value. Fisher's exact test was used to examine the association between the presence of the gene mutations and the cut-off value found. Statistical analysis was performed using SPSS 25 software (IBM Corp.). P<0.05 was considered to indicate a statistically significant difference. The bias was controlled as no data were lost. The study reporting conforms to the STROBE guidelines (17).
Results
Patient characteristics
The present study included 34 patients, with 21 males (61.8%) and 13 females (38.2%). The median age of the patients was 66 years (range, 28-81 years). All patients were Vietnamese, of Kinh ethnicity. The peripheral blood and bone marrow cell indices of the patients are presented in Table II. The clinical characteristics of the patients, as well as the classification results (WHO 2022 classification, karyotype, risk of cytogenetics and risk stratification according to the criteria of IPSS-M) are presented in Table III. The common clinical symptom was anemia (97.1%), followed by hemorrhage and infection. There were 3 to 4 patients with hepatomegaly, splenomegaly or lymphadenopathy, which were not massive. A total of 12 patients (35.3%) had comorbidities that included chronic obstructive pulmonary disease, hypertension, diabetes and dyslipidemia. In addition, 10 patients (29.4%) had an abnormal karyotype at the time of diagnosis, of which 2 patients had a complex karyotype (≥3 chromosomal abnormalities), 2 patients had isolated del(5q) and 6 patients had other abnormalities [such as del(20q), -7/del(7q), translocation]. A total of 11 patients were diagnosed with MDS with a low blast count, which accounted for the highest rate (32.4%) and 1 patient was diagnosed with MDS-biTP53, accounting for the lowest rate (2.9%); others types included MDS 5q-, MDS-SF3B1, MDS-IB1 and MDS-IB2. According to IPSS-M, 9 patients were classified as moderate-high risk, with the highest proportion (26.5%) and no patients were classified as very low risk. No statistically significance differences were found between the males and females, and between patients aged <50 and ≥50 years when these characteristics were compared (P>0.05).
Gene mutation data
NGS was performed to evaluate 51 myeloid gene mutations. A total of 20 patients (58.8%) had mutations. The remaining 14 patients did not have mutations. There were 18 mutations to be detected (Table IV). The ASXL transcriptional regulator 1 (ASXL1) mutation (17.6%) was the most commonly encountered, followed by the Runt-related transcription factor 1 (RUNX1), Tet methylcytosine dioxygenase 2 (TET2) (14.7%), and SF3B1 and TP53 mutations (11.8%) (Table IV). The number of gene mutations ranged between 1 to 7 per patient with a mean value of 1.35 (Table V).
Association between mutations and cell indices
As shown in Table VI, patients with the U2 small nuclear RNA auxiliary factor 1 (U2AF1) or TET2 mutation had a lower hemoglobin level than patients without this mutation. In addition, patients with the BCL6 corepressor (BCOR) or the serine and arginine rich splicing factor 2 (SRSF2) mutation had a higher percentage of peripheral blood blasts than patients without this mutation. Furthermore, patients with the BCOR mutation had a higher percentage of bone marrow blasts than those without it. On the other hand, patients with the SF3B1 mutation had a higher platelet count compared to the patients without it. These differences were statistically significant (P<0.05).
ROC analysis determined that the significant separation only appeared in variables, such as the hemoglobin level, platelet count and peripheral blood blasts, with an AUC value >0.8 and P<0.05 (Table VII). Based on the coordinates of the curve with the results of calculating the J index, the optimal cut-off values for the hemoglobin level, platelet count and the percentage of peripheral blood blasts were determined with the possible highest values of sensitivity (Se) and specificity (Sp). The cut-off value, the Se and the Sp are presented in Table VII. The optimal cut-off value for the hemoglobin level to separate the presence of the U2AF1 mutation was 56.5. The optimal cut-off value for the percentage of peripheral blood blasts to separate the presence of the BCOR and SRSF2 mutation was 7.5 and 5.5, respectively. The optimal cut-off value for the platelet count to separate the presence of the SF3B1 mutation was 228.5. Otherwise, ROC did not determine the separation of the hemoglobin level or the percentage of bone marrow blasts according to the presence of the TET2 and BCOR mutation.
 | Table VIIROC analysis of the separation of cell indices according to the presence of some gene mutations. |
The results of Fisher's exact test indicated that a hemoglobin level <56.5 g/l, a platelet count >228.5 G/l, a percentage of peripheral blood blasts >7.5% and a percentage of peripheral blood blasts >5.5% was associated with the U2AF1, SF3B1, BCOR and SRSF2 mutations, respectively (Table VIII).
Discussion
The development of MDS may be associated with cumulative genetic changes involving hematopoietic stem cells; thus, gene mutations are often detected in patients with MDS (18). Some studies have demonstrated that the majority of patients with MDS (50-90%) have at least one mutation (19-22). In the present study, gene mutations were observed in 58.8% of the patients. In fact, this rate also depended on the panel of NGS, as well as the sample size. The present study demonstrated that the most frequent genetic mutation was the ASXL1 mutation, followed by RUNX1, TET2, SF3B1 and TP53. Liu et al (23) also indicated that the ASXL1, RUNX1 and TP53 mutations were common. The TET2, SF3B1, ASXL1, SRSF2, DNA methyltransferase 3 alpha (DNMT3A) and RUNX1 mutations were the most commonly observed mutations in the study by Haferlach et al (20). In their study, Zhao et al (21) suggested that the most prevalent mutations were the U2AF1, SF3B1, ASXL1, TET2, BCOR, TP53 and DNMT3A mutations. In general, it has been indicated that genetic mutations, such as ASXL1, RUNX1, BCOR, TET2, DNMT3A, SF3B1, SRSF2, U2AF1 and TP53 are the most common mutations. These mutations also belong to the most known gene groups according to pathways/functions including chromatin modification (ASXL1), transcription factors (RUNX1), transcriptional regulator (BCOR), DNA methylation (TET2 and DNMT3A), RNA splicing (SF3B1, SRSF2 and U2AF1) and tumor suppressor (TP53) (24,25).
The accumulation of gene mutations alters hematopoiesis in MDS; thus, features such as cytopenia and bone marrow dysplasia may be associated with the activation of these mutations. Some studies, although a limited number, have indicated this association. Bejar et al (19) considered that the RUNX1, TP53 and NRAS mutations were strongly related to severe thrombocytopenia. The SF3B1 mutation was the most notable one. Martín et al (10) claimed that the majority of patients with MDS with ring sideroblasts carried the SF3B1 mutation. The SF3B1 mutation is involved in iron transport and causes abnormal iron deposition around the mitochondria to form ring sideroblasts (24). Polprasert et al (26) demonstrated that patients with the SF3B1 mutation had lower hemoglobin levels than those with the wild-type variant, but had normal platelet counts. Stockton et al (27) conducted a meticulous study that included numerous mutations and also indicated that patients with the SF3B1 mutation had anemia and a higher platelet count. In the present study, patients with this mutation also had a higher platelet count. A platelet count >228.5 G/l was associated with the presence of the SF3B1 mutation. The U2AF1 mutation, although valuable for consideration, had an ununified effect. Polprasert et al (26) hypothesized that it was associated with more severe leukopenia; however, Stockton et al (27) indicated that it was related to thrombocytopenia. In the present study, the U2AF1 mutation was associated with severe anemia. Patients with hemoglobin levels <56.5 g/l had the U2AF1 mutation. The present study also indicated that a percentage of peripheral blood blasts >7.5 and >5.5% was associated with the presence of the BCOR and SRFS2 mutations, respectively. Otherwise, Stockton et al (27) assumed that the SRFS2 mutation was related to higher hemoglobin levels. There were differences between the results of the studies. However, with the exception of the role of the SF3B1 mutation in increasing the number of sideroblasts, the mechanisms of gene mutations as regards the genesis of each cell clone are still being investigated.
The present study had certain limitations which should be mentioned: The most notable one was the is small sample size. Although the number of genes for the analysis was 51 genes, it still did not cover all myeloid genetic changes. The present study was only a cross-sectional study; thus, patients were not followed-up to determine their progress or any changes of the cell clone over time. The present study was conducted in Vietnam, a developing country. Due to the difficulty in accessing novel drugs, as well as the high cost of treatments such as stem cell transplantation, treatment outcome and survival time were difficult to evaluate, so the prognostic role of gene mutations has not been mentioned. In addition, the association between gene mutations and hematopoiesis is very complex, requiring additional valuable tests such as reticulin staining, Prussian blue staining (to detect ring sideroblasts), iron metabolism, etc. for more detailed analyses. These are also limitations of the study.
In conclusion, the present study demonstrates that there is an association between gene mutations and blood cell indices in patients diagnosed with MDS. The U2AF1 mutation may be related to severe anemia, while the BCOR and SRSF2 mutations may be related to MDS with an increased number of blasts. The SF3B1 mutation may be related to a good platelet count. Based on the levels of these blood cell indices, the appropriate gene mutations may be considered for examination. However, further research is required in order to determine the association between genetic changes, and changes in blood and bone marrow cells so that a model based on cell indices can be constructed to predict genes. This may promote reasonable genetic testing in patients with MDS. We also hope to carry out studies with large sample sizes and long follow-up periods to be able to determine the time when gene mutations appear based on changes in cell indices.
Acknowledgements
Not applicable.
Funding
Funding: No funding was received.
Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Authors' contributions
MPV and QHN conceived and designed the study. QHN, TAT, QCD and DBV participated in data collection and processing. MPV, QHN, TAT, QCD, DBV, HTN and QKB participated in data analysis and interpretation, as well as in the literature search, and wrote the manuscript. All authors have read and approved the final manuscript. QHN and TAT confirm the authenticity of the raw data.
Ethics approval and consent to participate
The study protocol was approved by the Institutional Review Board of the National Institute of Hematology and Blood Transfusion (no. 939/QĐ-HHTM). Patient consent was waived by the committee since the present study was a retrospective observational study.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that have no competing interests.
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