Abstract
Although iron overload is a clinical challenge, little is known about the clinical impact of HFE-variants in myelodysplastic syndromes (MDS) to date. We analyzed the HFE status in 167 MDS patients and 494 healthy controls. One or more of the 3 HFE-variants (H63D, C282Y, S65C) were found in 65/167 (38.9%) MDS patients and in 164/494 (33.2%) controls. At diagnosis, the median serum ferritin levels were higher in MDS patients with HFE-variants (409 µg/L; range: 23-7415) compared to those without HFE-variants (346.5 µg/L; range: 10-5450) (P=0.62). Moreover, ‘HFE-mutated’ patients had a slightly faster increase in serum ferritin in follow up examinations. The percentage of patients with HFE-variants was higher in refractory anemia (RA) (22/53=41.5%) or RA with ring sideroblasts (RARS) (17/39=43.6%) compared to RA with excess of blasts (RAEB) (16/46=34.8%) or RAEB in transformation (RAEB-T) (5/17=29.4%). Differences were also detectable when comparing low- and high-risk MDS variants defined by the World Health Organization classification. There was no significant correlation between HFE-variants and MDS-related somatic mutations. Progression-free survival was substantially longer in patients with HFE-variants compared to those without HFE-variants H63D and C282Y (P=0.089). Together, the HFE-variants H63D and C282Y are frequently detected in Austrian MDS patients. These patients have substantially higher ferritin levels at diagnosis, accumulate iron slightly faster and have a better progression-free survival than non-mutated patients.
Keywords: MDS, ferritin, iron overload, HFE gene variants, iron chelation, NGS
Introduction
Myelodysplastic syndromes (MDS) are a heterogeneous group of myeloid neoplasms found most commonly in patients aged >60 years [1-4]. Clinical features of MDS include an abnormal differentiation and maturation of myeloid precursor cells, bone marrow (BM) failure with peripheral blood cytopenia, and a genetic instability with enhanced risk of progression to secondary acute myeloid leukemia (AML) [1-4]. The classification of MDS is based on morphologic and molecular criteria provided by the World Health Organization (WHO) and the French-American-British (FAB) cooperative study group [4-9]. However, in each diagnostic category, the course of disease and prognosis of patients vary. During the past decades a number of attempts have been made to establish useful scoring systems predicting survival and/or AML evolution [9-15]. These scoring systems are based on multiple prognostically important parameters, including the percentage of BM blasts and the number of peripheral cytopenias. The ‘International Prognostic Scoring System’ (IPSS) has been established in 1997 [15]. This scoring system is based on the percentage of BM blasts, number of cytopenias, and chromosomal abnormalities [15]. To improve the prognostic power, the IPPS score has recently been revised into the IPSS-R [16].
However, apart from WHO-related or IPSS-based variables, other prognostic parameters (not included in the IPSS or IPSS-R) have also been identified [9,13,17-19]. A number of previous and more recent studies have shown that an elevated serum lactate dehydrogenase (LDH) is associated with a poor prognosis in MDS [13,17-19]. Other studies have shown that age at diagnosis, the transfusion frequency, comorbidities, and elevated serum ferritin levels are associated with a poor survival in MDS [20-26]. Within the last 10 years, molecular markers have evolved to play a substantial role in the prognosis and evolution of MDS [9-27]. However, such molecular markers were also detected in the absence of an overt malignancy. When detected in healthy individuals these mutations are termed clonal hematopoiesis with indeterminate potential (CHIP) [27-31]. In many cases of CHIP, hematopoiesis remains normal over years or even decades. However, some of these mutations exhibit a higher risk and were thus also called clonal hematopoiesis with oncogenic potential (CHOP) [27].
Patients with MDS are often chronically transfused with significant transfusion-related morbidity. This is in part a result of chronic iron overload and reflected by high serum ferritin levels [25,26,32]. Other studies have shown that the susceptibility for iron uptake and iron overload in various tissues is determined by genetic factors and may increase with age [33,34]. One major regulator of iron uptake and metabolism is the HFE gene [34,35]. The HFE protein is involved in the regulation of hepcidin expression and secretion. In patients with HFE mutations, the interaction of HFE with transferrin receptors TFR1 and TFR2 is disrupted, resulting in decreased hepcidin expression which in turn is responsible for an increased iron uptake in target cells and thus iron overload [34,35].
The HFE gene variants (some also refer to these as mutations or single nucleotide polymorphism) H63D and C282Y are considered to be critically involved in iron overload. Interestingly, these variants were reported to be more frequently present in patients with MDS compared to healthy controls or patients with other hematologic neoplasms [36-40]. However, the number of cases examined in these studies was small, the exact incidence of these variants remains unknown, and so far, little is known about the influence of these genetic factors on survival or disease-progression in MDS.
In this study we determined the prevalence and impact of HFE gene variants on survival and AML-development in Austrian patients with MDS. Our data confirm previous studies suggesting that the HFE-variants H63D and C282Y can be detected frequently in patients with MDS. These HFE-variants may predispose for rapid iron overload in chronically transfused patients, but massive iron overload also occurs in those who do not have a HFE mutation. Finally, we show that the HFE status correlates with the prognosis and survival in MDS.
Patients and methods
Patients
A total number of 167 unselected patients with MDS (females, n=79; males, n=88; median age: 69 years; range: 28-84 years) were examined retrospectively for the presence of HFE gene variants in our center (observation period: 1992-2019). All patients gave their written consent before blood or bone marrow cells were analyzed. The study was approved by the ethics committee of the Medical University of Vienna (number: 402/2007). The patient’s characteristics are shown in Tables 1 and 2. All samples were collected during routine investigations. Patients were classified according to FAB cooperative study group criteria and WHO 2016 criteria. Moreover, samples from 494 healthy donors were collected as control cohort. All patients and controls were of Austrian origin, and all samples were collected at the Medical University of Vienna.
Table 1.
Patient characteristics according to FAB classification
| FAB-Subtype | Patients n (%) | WBC (G/L) median (range) | Hb (g/dL) median (range) | Plt (G/L) median (range) | Ferritin (µg/L) median (range) | LDH (U/L) median (range) |
|---|---|---|---|---|---|---|
| RA | 53 (31.5) | 3.44 (1.7-10.2) | 9.5 (5.6-13.3) | 115 (3-898) | 368 (42-2300) | 209 (127-1751) |
| RARS | 39 (15.4) | 5.04 (1.19-12.11) | 9.4 (5.9-11.4) | 199 (31-807) | 586.5 (23-7415) | 176 (103-457) |
| RAEB | 47 (27.9) | 2.88 (0.63-76.5) | 9.1 (6.8-13.6) | 89 (13-398) | 287.5 (36-1701) | 235 (147-1059) |
| RAEB-T | 17 (10.1) | 2.99 (0.58-25.38) | 8.9 (7.2-11.4) | 100 (25-390) | 598 (10-1980) | 272 (117-2600) |
| CMML | 12 (7.1) | 7.89 (2.83-26.64) | 10.5 (5.4-14.2) | 92 (3-241) | 488.5 (64-2180) | 184.5 (137-862) |
Abbreviations: FAB, French-American-British; WBC, white blood count; Hb, hemoglobin; Plt, platelets; LDH; lactate dehydrogenase; RA, refractory anemia; RARS, RA with ring sideroblasts; RAEB, RA with excess of blasts; RAEB-T, RAEB in transformation; CMML, chronic myelomonocytic leukemia.
Table 2.
Patient Characteristics according to WHO 2016 classification
| WHO 2016 Subtype | Patients n (%) | WBC (G/L) median (range) | Hb (g/dL) median (range) | Plt (G/L) median (range) | Ferritin (µg/L) median (range) | LDH (U/L) median (range) |
|---|---|---|---|---|---|---|
| MDS-5q | 10 (5.9) | 4.84 (2.32-8.26) | 9.15 (7.7-11.2) | 317 (114-898) | 371.5 (42-1390) | 178.5 (158-283) |
| MDS-EB-1 | 29 (17.2) | 3.26 (0.63-76.5) | 9.7 (6.8-13.6) | 90 (13-398) | 263 (36-1170) | 245 (147-1059) |
| MDS-EB-2 | 28 (16.6) | 2.69 (0.58-32) | 8.75 (7.1-12.6) | 93 (16-390) | 294 (10-1980) | 225 (144-2600) |
| MDS-SLD | 18 (10.7) | 4.12 (1.79-10.2) | 10.2 (5.6-12.2) | 144 (3-648) | 237.5 (96-902) | 227.5 (137-369) |
| MDS-RS-SLD | 26 (15.4) | 5.05 (1.66-12.11) | 9.5 (6.7-11) | 236 (31-369) | 453 (23-7415) | 180 (121-1751) |
| MDS-MLD | 26 (15.4) | 3.08 (1.7-6.8) | 9.7 (7.3-13.3) | 89 (6-295) | 538 (43-2300) | 203.5 (127-641) |
| MDS-RS-MLD | 12 (7.1) | 4.47 (1.19-6.8) | 9.3 (5.9-11.4) | 133 (64-807) | 695 (325-5450) | 162 (103-226) |
| CMML-1 | 10 (5.9) | 7.89 (2.83-18.89) | 10.5 (6.7-14.2) | 96 (3-241) | 488.5 (64-1100) | 179 (137-862) |
| CMML-2 | 2 (1.1) | 16.52 (6.4-26.64) | 8.4 (5.4-11.4) | 75 (71-80) | 1125.5 (71-2180) | 335 (301-369) |
| AML dys. | 7 (4.1) | 2.99 (1.14-24.37) | 10.1 (7.5-11.4) | 50 (28-241) | 879 (339-1250) | 264 (117-395) |
Abbreviations: WHO, World Health Organization; WBC, white blood count; Hb, hemoglobin; Plt, platelets; LDH; lactate dehydrogenase; MDS, Myelodysplatic Syndrome; MDS 5q-, MDS with isolated 5q-; MDS-EB1, MDS with excess of blasts-1; MDS-EB2, MDS with excess of blasts-2; MDS-SLD, MDS with single-lineage dysplasia; MDS-RS-SLD, MDS with ring sideroblasts (RS) and single-lineage dysplasia; MDS-MLD, MDS with multilineage dysplasia; MDS-RS-MLD, MDS with RS and multilineage dysplasia; CMML, Chronic Myelomonocytic Leukemia; AML dys., Acute Myeloid Leukemia with myelodysplasia-related changes.
Evaluation of disease-related parameters at diagnosis and in the follow-up
The following blood parameters were recorded at diagnosis: complete blood count including differential count, serum chemistry including serum ferritin, transferrin saturation, glutamic oxaloacetic transaminase (GOT), glutamic pyruvic transaminase (GPT), and LDH. In all patients, the transfusion frequency (red cell concentrates per month, recorded in the first 3 years of observation) as well as comorbidity according to the Charlson index and the hematopoietic cell transplantation-specific comorbidity index, were determined [41,42]. BM investigations included aspirate smears (Wright-Giemsa stains), routine histology and immunohistochemistry, flow cytometry (percent of CD34+ blast cells), and cytogenetics. Chromosome analysis and fluorescence in situ hybridization were performed and reported according to ISCN guidelines [43]. During the follow up, the following parameters were examined (at least every three months): blood counts and differential counts, serum chemistry including LDH, GOT, GPT, ferritin, and transferrin-saturation. The BM was re-examined in case of suspected progression.
Reverse hybridization to detect 18 mutations related to iron overload
In a first step, genomic DNA isolated from the BM of 52 patients with MDS was examined for the presence of mutations in genes relevant to iron uptake or metabolism. DNA samples were screened for 12 mutations in the HFE gene (V53M, V59M, H63D, H63H, S65C, Q127H, P160delC, E168Q, E168X, W169X, C282Y, Q283P), 4 mutations in the gene encoding transferrin receptor-2 (TRF2, E60X, M172K, Y250X, AVAQ594-597del), and 2 mutations in the gene coding for ferroportin (FPN1, N144H, V162del) using the Haemochromatosis StripAssay A (Vienna Lab Labordiagnostika GmbH, Vienna, Austria) as described [44].
Restriction fragment length polymorphism (RFLP) analysis of 3 common mutations (HFE H63D, S65C and C282Y mutation)
Genomic DNA was amplified by polymerase chain reaction (PCR) using PCR primers described by Feder et al. [45]. Identification of HFE H63D was performed using the restriction enzymes Mbo I. After cleavage with Mbo I, samples without mutations showed two fragments of 138 and 70 base pairs (bp), whereas samples with mutations exhibited an uncleaved PCR fragment of 208 bp. Detection of HFE S65C was conducted using the restriction enzymes Hinf I as described [46]. Cleavage with Hinf I in samples without mutation revealed two fragments of 147 and 61 bp, whereas in samples containing HFE S65C, the PCR fragment of 208 bp remained uncleaved. The HFE C282Y variant was analyzed using the restriction enzymes Rsa I, which revealed two fragments of 249 and 140 bp in samples without mutation and three fragments of 249, 111, and 29 bp in samples containing HFE C282Y. All restriction fragments were analyzed by electrophoresis using 6% polyacrylamide gels (Novex, San Diego, CA), followed by Sybr Green staining (Nucleic Acid Gel Stain, Molecular Probe, Eugene, Oregon). In patients with MDS, all three HFE-variants were analyzed. By contrast, in healthy controls, only the HFE-variants H63D and C282Y were examined because at the time of investigation, no RFLP for the HFE-variant S65C was available.
Next generation sequencing (NGS)
Genomic DNA (gDNA) was extracted from peripheral blood (PB) or bone marrow (BM) cells using the QIAsymphony Sp Instrument with the QIAsymphony DNA Midi Kit (Both Qiagen, Hilden, Germany). Quantification of gDNA was performed by fluorometric quantitation using the Qubit dsDNA BR Assay Kit and a Qubit 3.0 Fluorometer (Both Thermo Fisher Scientific, Waltham, USA) and diluted to a final concentration of 200 ng. Library preparation was performed with the Myeloid Solution (Sophia Genetics, Lausanne, Switzerland) according to the manufacturer’s instructions. MiSeq System (Illumina, San Diego, California) was used as sequencing platform. Variant calling was performed using the DDM Software (Sophia genetics). Mutations of ASXL1, SF3B1, SRSF2, TET2, DNMT3A and RUNX1 were classified as clonal hematopoiesis of indeterminate potential (CHIP) and mutations of IDH2, EZH2, SETBP1, U2AF1, CBL, IDH1, CSF3R, FLT3, JAK2, WT1, ZRSR2, KRAS, NPM1, CALR, MPL, ABL1, BRAF, CEBPA, ETV6, HRAS, KIT, PTPN11 as clonal hematopoiesis with oncogenic potential according to recently published criteria [27].
Statistical evaluations
Differences in the frequency of HFE-variants between subgroups of patients and controls were calculated by Chi-square test. The probability of cumulative survival and AML-free survival were calculated by the product limit method of Kaplan and Meier. Differences among various subgroups of patients concerning survival and AML-free survival were determined by log rank test. Differences between HFE-variants and clinical and/or laboratory parameters were analyzed by Mann-Whitney-U-test. Correlations between the presence of CHIP/CHOP and absence or presence of HFE-variants was assessed by Chi-square test. Concerning the primary endpoint, progression (AML)-free survival, a power analysis revealed that the study has sufficient power of 80% to detect a relevant hazard ratio of 1.6 at the 5% (two-sided) significance level.
Results
Initial screen using the haemochromatosis StripAssay A
In a first step, we applied a broad screen to detect variants of key genes involved in iron uptake and/or metabolism in 52 patients with MDS (data not shown). Because none of these patients showed TRF2-, FPN1- or rare HFE mutations, subsequent analyses were conducted using MDS patient-derived cells and restriction fragment length polymorphism (RFLP) to detect the more common HFE-variants H63D, C282Y, and S65C. In our cohort of healthy controls, RFLP analysis of H63D and C282Y was also performed.
Frequency of HFE-variants in patients with MDS and comparison to controls
In 65/167 patients with MDS (38.9%) one or more of the 3 HFE-variants (H63D, C282Y, S65C) were detected. The most frequent single HFE-variant, H63D, was detected in 50 patients with MDS (29.9%), followed by C282Y (8 patients, 4.8%) and S65C (3 patients, 1.8%) (Table 3). Four patients (2.4%) were found to harbor two HFE mutations, namely H63D and C282Y. Only one patient (subtype RARS) was homozygous for HFE-variant H63D. In the remaining patients only heterozygous HFE-variants were detected. We next compared our MDS patients with the control cohort and found a slightly higher frequency of HFE-variants (H63D, C282Y and S65C) in our MDS patients (38.9%) compared to healthy Austrian controls (33.2%) (P=0.18) (Table 3).
Table 3.
Distribution of HFE-variants in various FAB categories and comparison to controls
| FAB subtype | HFE-variant, subjects (n) in subgroup (%) | ||||
|---|---|---|---|---|---|
|
| |||||
| C282Y | H63D | S65C | Heterozygous* | all variants | |
| RA | 3/53 (5.7%) | 17/53 (32.1%) | 1/53 (1.9%) | 1/53 (1.9%) | 22/53 (41.5%) |
| RARS | 3/39 (7.7%) | 13/39 (33.3%)** | 1/39 (2.6%) | 0/39 (0%) | 17/39 (43.6%) |
| RAEB | 2/46 (4.3%) | 12/46 (26.1%) | 1/46 (2.2%) | 1/46 (2.2%) | 16/46 (34.8%) |
| RAEB-T | 0/17 (0%) | 4/17 (23.5%) | 0/17 (0%) | 1/17 (5.9%) | 05/17 (29.4%) |
| CMML | 0/12 (0%) | 4/12 (33.3%) | 0/12 (0%) | 1/12 (8.3%) | 05/12 (41.7%) |
| All MDS patients | 8/167 (4.8%) | 50/167 (29.9%) | 3/167 (1.8%) | 4/167 (2.4%) | 65/167 (38.9%) |
| Austrian healthy controls | 42/494 (8.5%)*** | 116/494 (23.5%)**** | n.d. | 6/494 (1.2%) | 164/494 (33.2%) |
Heterozygous for HFE-variants C282Y and H63D.
1/39 (2.8%) homozygous.
1/494 (0.2%) homozygous.
7/494 (1.4%) homozygous.
Abbreviations: FAB, French-American-British; RA, refractory anemia; RARS, RA with ring sideroblasts; RAEB, RA with excess of blasts; RAEB-T, RAEB in transformation; CMML, Chronic Myelomonocytic Leukemia; n.d., not detectable.
Frequency of HFE-variants in FAB, WHO, IPSS and IPSS-R subgroups
When examining FAB subgroups of MDS, the percentage of cases with HFE-variants was higher in those without blast cell increase (refractory anemia [RA], 41.5%; RA with ring sideroblasts [RARS], 43.6%) compared to patients with advanced MDS (RA with excess of blasts [RAEB], 34.8%; RAEB in transformation [RAEB-T], 29.4%) (Table 3). In chronic myelomonocytic leukemia (CMML) 41.7% of the patients had a HFE-variant (Table 3). Similar differences were also observed between subgroups of MDS patients classified by WHO criteria (Table 4). The prevalence of HFE-variants was 50.0% in patients with ring sideroblasts (RS) and multilineage dysplasia (MDS-RS-MLD), 50.0% in MDS-MLD, 42.3% in MDS with single-lineage dysplasia (MDS-SLD), 38.9% in MDS with RS and single-lineage dysplasia (MDS-RS-SLD), 41.4% in patients with excess of blasts-1 (MDS-EB1), 22.2% in MDS-EB2, and 20% in MDS with isolated 5q-. These differences in the prevalence of HFE-variants among the FAB- or WHO-subgroups of MDS or between the various FAB- or WHO subgroups and our healthy controls were not statistically significant.
Table 4.
Distribution of HFE-variants in various WHO 2016 categories
| WHO 2016 subtype | HFE-variant, subjects (n) in subgroup (%) | ||||
|---|---|---|---|---|---|
|
| |||||
| C282Y | H63D | S65C | Heterozygous* | all variants | |
| MDS 5q- | 1/10 (10%) | 1/10 (10%) | 0/10 (0%) | 0/10 (0%) | 2/10 (20%) |
| MDS-EB1 | 2/29 (6.9%) | 10/29 (34.5%) | 0/29 (0%) | 0/29 (0%) | 12/29 (41.4%) |
| MDS-EB2 | 0/27 (0%) | 3/27 (11.1%) | 1/27 (3.7%) | 2/27 (7.4%) | 6/27 (22.2%) |
| MDS-SLD | 0/26 (0%) | 11/26 (42.3%)** | 0/26 (0%) | 0/26 (5.9%) | 11/26 (42.3%) |
| MDS-RS-SLD | 0/18 (0%) | 7/18 (38.9%) | 0/18 (0%) | 0/18 (0%) | 7/18 (38.9%) |
| MDS-MLD | 2/13 (15.4%) | 9/13 (69.2%) | 1/13 (7.7%) | 1/13 (7.7%) | 13/26 (50%) |
| MDS-RS-MLD | 3/12 (25%) | 2/12 (16.7%) | 1/12 (8.3%) | 0/12 (0%) | 6/12 (50%) |
| CMML1 | 0/10 (0%) | 4/10 (40%) | 0/10 (0%) | 0/10 (0%) | 4/10 (40%) |
| CMML2 | 0/2 (0%) | 0/2 (0%) | 0/2 (0%) | 1/2 (50%) | 1/2 (50%) |
| AML dys. | 0/7 (0%) | 3/7 (42.9%) | 0/7 (0%) | 0/7 (0%) | 3/7 (42.9%) |
| All MDS patients | 8/167 (4.8%) | 50/167 (29.9%) | 3/167 (1.8%) | 4/167 (2.4%) | 65/167 (38.9%) |
Heterozygous for HFE-variants C282Y and H63D.
1/26 (3.8%) homozygous.
Abbreviations: WHO, World Health Organization; MDS, Myelodysplatic Syndrome; MDS 5q-, MDS with isolated 5q-; MDS-EB1, MDS with excess of blasts-1; MDS-EB2, MDS with excess of blasts-2; MDS-SLD, MDS with single-lineage dysplasia; MDS-RS-SLD, MDS with ring sideroblasts (RS) and single-lineage dysplasia; MDS-MLD, MDS with multilineage dysplasia; MDS-RS-MLD, MDS with RS and multilineage dysplasia; CMML, Chronic Myelomonocytic Leukemia; AML dys., Acute Myeloid Leukemia with myelodysplasia-related changes.
High or very high risk patients (according to the IPSS or IPSS-R, respectively) were found to have a lower prevalence of HFE-variants (IPSS high: 20.0%; IPSS-R very high: 17.6%) compared to the other risk groups (IPSS low: 37.8%, int-1: 42.1%, int-2: 31.3%; IPSS-R very low: 33.3%, low: 43.1%, int: 34.8%, high: 38.7%) (Tables 5 and 6). Again, these differences did not reach statistical significance which is best explained by the relatively low number of patients in the high risk groups.
Table 5.
Distribution of HFE-variants in IPSS categories
| IPSS subgroup | HFE-variant, subjects (n) in subgroup (%) | ||||
|---|---|---|---|---|---|
|
| |||||
| C282Y | H63D | S65C | Heterozygous* | all variants+ | |
| Low risk | 1/45 (2.2%) | 14/45 (31.1%) | 1/45 (2.2%) | 1/45 (2.2%) | 17/45 (37.8%) |
| Intermediate risk (all) | 7/89 (7.9%) | 22/89 (24.7%)** | 2/89 (2.2%) | 3/89 (3.4%) | 34/89 (38.2%) |
| Intermediate risk-I | 4/57 (7%) | 17/57 (29.8%)*** | 1/57 (1.8%) | 2/57 (3.5%) | 24/57 (42.1%) |
| Intermediate risk-II | 3/32 (9.4%) | 5/32 (15.6%) | 1/32 (3.1%) | 1/32 (3.1%) | 10/32 (31.3%) |
| High risk | 0/10 (0%) | 2/10 (20.0%) | 0/10 (0%) | 0/10 (0%) | 2/10 (20.0%) |
Due to missing parameters only 145 patients were included for IPSS subgroup analysis.
Heterozygous for HFE-variants C282Y and H63D.
1/89 (1.1%) homozygous.
1/57 (1.8%) homozygous.
Abbreviations: IPSS, international prognostic scoring system.
Table 6.
Distribution of HFE-variants in IPSS-R categories
| IPSS-R subgroup | HFE-variant, subjects (n) in subgroup (%) | ||||
|---|---|---|---|---|---|
|
| |||||
| C282Y | H63D | S65C | Heterozygous* | all variants+ | |
| Very Low risk | 0/15 (0%) | 5/15 (33.3%) | 0/15 (0%) | 0/15 (0%) | 5/15 (33.3%) |
| Low Risk | 4/58 (6.9%) | 18/58 (31%)** | 2/58 (3.4%) | 1/58 (1.7%) | 25/58 (43.1%) |
| Intermediate risk | 1/23 (4.3%) | 5/23 (21.7%) | 0/23 (0.0%) | 2/23 (8.7%) | 8/23 (34.8%) |
| High risk | 2/31 (6.5%) | 8/31 (25.8%) | 1/31 (3.2%) | 1/31 (3.2%) | 12/31 (38.7%) |
| Very high risk | 1/17 (5.9%) | 2/17 (11.8%) | 0/17 (0%) | 0/17 (0%) | 3/17 (17.6%) |
Due to missing parameters only 145 patients were included for IPSS-R subgroup analysis.
Heterozygous for HFE-variants C282Y and H63D.
1/58 (1.7%) homozygous.
Abbreviations: IPSS-R, revised international prognostic scoring system.
Frequency of the different HFE-variants in FAB, WHO, and IPSS subgroups
In a next step, we analyzed the prevalence of the distinct HFE gene variants. The H63D HFE gene mutation was found to be expressed most frequently in patients with RARS and CMML (33.3%, each). In the other FAB categories, this HFE-variant was also detectable, namely in RA (32.1%), RAEB (26.1%), and RAEB-T (23.5%). In all these MDS variants except for RAEB-T the prevalence of the H63D HFE-variant was higher compared to healthy controls (23.5%) (Table 3). The HFE-variant C282Y could be detected in all FAB categories except for RAEB-T and CMML (Table 3). In RARS patients the frequency of this gene variant was 7.7% and thus comparable to our healthy controls (8.5%). The expression of different HFE gene variants in the WHO subgroups is shown in Table 4. The prevalence of the three analyzed HFE-variants differed also substantially among the IPSS and IPSS-R-groups. High and very high risk patients had a markedly lower prevalence of HFE-variants (Tables 5 and 6).
Correlations between HFE gene variants and single prognostic variables
In this correlation, leukocytes, neutrophils, platelets, blast cells, age, glutamic oxaloacetic transaminase (GOT) and glutamic pyruvic transaminase (GPT) levels, the LDH level, and transfusion frequency were analyzed in patients with and patients without HFE gene variants. As assessed by Mann-Whitney-U-test, no significant differences were found in these correlations (data not shown). Patients with HFE-variants had a higher median ferritin level at diagnosis (409 µg/L) compared to patients without a detectable HFE-variant (346.5 µg/L) but this difference did not reach statistical significance (P=0.62) (Figure 1A).
Figure 1.
Effect of the HFE mutation status on the ferrtin levels during follow up. A: Median ferritin levels at diagnosis were slightly higher in patients with HFE-variants (409 µg/L; range: 23-7415) compared to HFE non-mutated patients (HFE-wt; 346.5 µg/L; range: 10-5450). B: During the first 2 years of transfusion therapy, patients with HFE-variants patients showed a slightly faster increase in serum ferritin levels compared to patients without HFE-variants (HFE-wt).
Increase in ferritin in MDS patients with or without HFE-variants over time
We next asked whether there is a faster increase in serum ferritin levels in transfused MDS patients harboring a HFE-variant compared to those without a HFE-variant, in this paper referred to as wild type HFE (HFE-wt). A rapid increase in serum ferritin levels was observed in patients with a HFE-variant and also in those with HFE-wt during the first three years of transfusion therapy (Figure 1B). However, there was a slightly faster increase in serum ferritin levels at 2 years observed in patients with HFE-variants (median ferritin level: 1610 µg/L) compared to MDS patients without a HFE mutation (HFE-wt) (median ferritin level: 1069 µg/L) (P=0.56).
Somatic mutations analyzed by NGS and correlation with HFE status
Somatic mutations are of increasing importance in patients with hematologic disorders, including MDS. To investigate a potential relationship between HFE gene variants and mutations in genes commonly affected in MDS, we performed a myeloid NGS gene panel analysis in 94 of our MDS patients. In 81 of these patients, at least one mutation was detected in neoplastic cells. However, no significant correlations were found when comparing HFE-variant expression with the most frequently detected somatic mutations in MDS (ASXL1, SF3B1, SRSF2, TET2, DNMT3A, RUNX1, NRAS, TP53, IDH2 or EZH2) or when comparing the frequency of age-related somatic mutations, including CHIP mutations and more oncogenic mutations (CHOP) (Figure 2A and 2B) [27].
Figure 2.
Somatic mutations analyzed by NGS according to HFE mutational status. A: A myeloid NGS gene panel was conducted in 94 of our MDS patients. In total 81 of all screened patients expressed at least on mutation. No significant correlations were found when comparing expression of HFE mutations with the most frequently detected somatic mutations in ASXL1, SF3B1, SRSF2, TET2, DNMT3A, RUNX1, NRAS, TP53, IDH2 or EZH2 detected by NGS. B: No significant correlation (assessed by Chi-square test) was found when comparing the frequency of mutations indicating clonal hematopoiesis of indeterminate potential (CHIP) or clonal hematopoiesis with oncogenic potential (CHOP) with the presence of HFE-variants in our MDS patients.
Influence of HFE-variants on overall survival and progression-free survival in MDS
We also asked whether the HFE-variant status would serve as a prognostic parameter predicting the outcome in our patients. In particular, we asked whether overall survival (OS) or progression-free survival (PFS) is different when comparing MDS patients with HFE-variants with those carrying HFE-wt. In these analyses, we found a markedly better PFS in patients with HFE-variants compared to patients with HFE-wt (Figure 3A) (P=0.089). Within the first seven years of observation, patients with HFE-variants had a better OS compared to those carrying HFE-wt (Figure 3B) (P=0.44).
Figure 3.
Progression-free survival and overall survival in MDS patients according to HFE mutation status. Progression-free survival (PFS) (A) and overall survival (OS) (B) was calculated according to the method of Kaplan and Meier. A clear but not significant difference in PFS between patients with HFE-variants (red line) and non-mutated patients (HFE-wt; blue line) was found (P=0.089 by log rank test). No differences in overall survival (OS) were found when comparing patients with HFE-variants (red line) with those without HFE-variants (HFE-wt; blue line) (P=0.44 by log rank test).
Discussion
MDS comprise a heterogeneous group of myeloid neoplasms characterized by clonal expansion of dysplastic myeloid cells, cytopenia(s), and an increased risk of progression to secondary AML [1-4]. Many patients suffer from chronic transfusion-dependent anemia, and several of them develop a significant iron overload [25,26,32]. A key regulator of iron uptake and distribution is the HFE gene. The highlighting example of the impact of HFE is hereditary hemochromatosis, a genetic disorder characterized by massive iron overload. We analyzed the HFE status in patients with MDS and a group of healthy Austrian controls. We found a slightly higher prevalence of the HFE-variants H63D and C282Y in patients with low risk MDS compared to healthy Austrian controls. The median ferritin level at diagnosis was slightly higher in MDS patients with HFE-variants and the increase in serum ferritin in these patients within the first 2 years of transfusion therapy was faster compared to non-mutated (HFE-wt) patients. However, these differences were not statistically significant. Finally, we found that the frequency of HFE gene variants differ among MDS subgroups.
Only a limited number of studies have examined the frequency of HFE-variants in patients with MDS so far (Tables S1 and S2) [36-40,47-50]. Looking at the patients’ cohorts, the highest prevalence of MDS patients with HFE gene variants, namely 52%, was found in a small Hungarian study [36]. However, two other Hungarian studies reported a lower prevalence of HFE gene mutations, namely 37.5% and 49.2% [37,47]. This relatively large range in the prevalence of HFE gene variants may be explained by the small number of patients included in each of these studies. In our current study performed in Austria and in other similar studies performed in Croatia, the US, and Brazil, the prevalence of HFE-variants in MDS patients ranged between 30.8% and 39.2% [38,40,48]. A markedly lower prevalence of HFE-variants was found in MDS patients in Greece and China, with 27.8% and 4.1%, respectively [39,50]. This variance in the prevalence can also be explained by the limited number of cases. Moreover, differences in the genetic background generated by ethnical or an environmental influence might be an alternative explanation for the varying prevalence of HFE-variants among these studies. Indeed, it is well known that the frequency of HFE-variants varies between different regions and areas (Table S3) [36,37,39,40,46-48]. Furthermore, the prevalence of particular HFE-variants, including C282Y and H63D, varies markedly among different populations, independent of the presence of MDS (Tables S1, S2, S3) [36-40,45-50].
In our study, no significant difference in the prevalence of HFE gene variants between patients and healthy controls was observed. This is in line with data from the USA and Croatia [38,48]. In contrast, the studies of Várkonyi et al. reported on an increased prevalence of HFE gene variants in patients with MDS compared to controls and similar data were published by de Souza et al. (Brazil) and Speletas et al. (Greece) [36,37,39,40]. On the other hand, Nie et al. reported a lower prevalence of HFE gene variants in Chinese MDS patients [50]. Here, apart from the limited number of MDS patients included in all these studies, the heterogeneity of MDS could be an alternative or additional explanation for the different results obtained. This is greatly supported by the fact that the distribution of patients among the different FAB or WHO categories varies substantially in these studies.
The next question we asked was whether HFE-variants cluster in distinct MDS variants. A higher prevalence of HFE-variants was found in RA, RARS and CMML compared to RAEB and RAEB-T. However, we were not able to detect a significant difference among the various MDS subgroups defined by FAB or WHO criteria. This is in line with most studies published so far [48,50]. Only Nearman et al. reported a significantly higher prevalence of HFE gene mutations in RARS patients (64.3%) [38]. A comparable but slightly lower prevalence of HFE gene mutations in RARS patients was found in our study (43.6%). These data are in contrast to the results reported from Croatian (17%) and Chinese (0%) study cohorts [38,48-50]. Again, the limited numbers of patients with RARS included in these studies may explain the different results. In particular, there were only 11 and 12 patients with known RARS included in the Chinese and Croatian study, respectively, whereas the data of Nearman et al. (n=42) and our study (n=39) are based on higher numbers of RARS patients [38,48,50]. In this regard it is noteworthy to state, that similar to the US cohort the prevalence of HFE-variants was higher in our RARS patients compared to controls, although not statistically significant. Another interesting observation was that HFE-variant C282Y was not detectable in our patients with CMML whereas the HFE-variant H63D was detected in several CMML cases.
Despite the availability of novel potent chelators, transfusion-related iron overload and the resulting organ damage remain clinical challenges in the management of MDS patients. In some of these patients rapidly increasing levels of serum ferritin, a marker of iron-overload, are found. In our patients, relatively high ferritin levels were even detected at diagnosis before transfusion therapy started. Little is known about genetic and other factors predisposing for such a rapid iron overload in chronically transfused MDS patients so far. We asked whether HFE-variants may be triggers of rapid iron overload in our MDS patients. We observed that the median ferritin levels measured at diagnosis and after 24 months were higher in patients harboring HFE-variants compared to non-mutated patients. However, this difference did not reach statistical significance. These data show that neither the basal (pre-treatment) ferritin levels nor the HFE gene status are reliable biomarkers predicting the rapidity of iron overload in transfusion-dependent patients with MDS. In other words, a rapid iron overload may well be found also in patients without any HFE-variant which may be explained by the many other molecules and mechanisms that contribute to iron uptake, storage and overload [25,26,32,33,36-40,47]. On the other hand, a very rapid increase in serum ferritin levels may be indicative of primary hemochromatosis, especially when detected in transfusion-independent MDS patients. Therefore, we recommend to examine the HFE gene status in these patients. However, based on our data we do not recommend a HFE test in all patients with MDS. In fact, in our study, we did not detect major differences in the levels of serum ferritin at diagnosis when comparing patients heterozygous for HFE mutations with those carrying wild type HFE. It is also worth noting that in our cohort, no MDS patient was found to be homozygous for the clinically relevant HFE-variant C282Y. We also asked whether HFE-variants are associated with prognostic factors and scores as well as the outcome in MDS. The rate of progression-free survival was higher in patients with HFE-variants compared to patients with HFE-wt. Within the first seven years of observation a slightly better OS was observed in patients with HFE-variants, but this difference was no longer visible after 7 years of observation. This may be explained by complications related to cytopenia including infection or bleedings. In this regard it is noteworthy, that comorbidities are frequently found in these patients and that they represent an important predictive factor for survival [21-23]. In a next step, we analyzed whether HFE-variants correlate with single prognostic variables. However, no correlation was found between HFE-variants and various disease-related laboratory variables.
Previous and more recent data suggest that the development of MDS and subsequently AML is a step-wise process triggered by acquisition of somatic mutations, with subsequent molecular diversification and clonal selection in stem cell compartments [27]. The genetic background may be an important factor contributing to the somatic evolution, course and progression in these neoplasms. However, little is known about gene variants that are specifically involved in the pathogenesis of the disease or in the acquisition of somatic mutations. Our data show that HFE-variants are rather frequently detectable in patients with MDS. The underlying mechanism of this ‘gene variant clustering’ remains unknown. In order to investigate potential effects of HFE gene variants on the occurrence of MDS-related somatic mutations, we performed NGS using a myeloid gene panel containing the most frequent mutations associated with MDS and AML, in 94 of our MDS patients. The majority (86.2%) of screened MDS patients were found to have at least one mutation detected by targeted NGS. However, no correlations between myeloid gene panel mutations and the HFE mutation status were found.
In summary, our data show that HFE-variants are frequently detected in patients with MDS. The presence of these mutations was found to correlate with IPSS and IPSS-R subsets of our MDS patients and with their survival in follow up studies. Furthermore, the serum ferritin levels increased more rapidly over time in transfused patients compared to non-transfused patients with MDS. Although clear differences were seen, the significance level was not reached in all these comparisons which is most probably due to the relatively small number of cases examined in each cohort. Therefore, more studies with more patients are required to finally elucidate the role of HFE-variants in MDS.
Acknowledgements
We would like to thank Dr. Igor Theurl for helpful discussion and Andrea Huber, Nadine Witzeneder, and Marika Fritz for skillful technical assistance. P.V. and his team were supported by: Austrian Science Fund (FWF), grant F4704-B20.
Disclosure of conflict of interest
P.V. has the following study-specific COI: Consultancy honoraria: Celgene, Novartis, Pfizer. In addition, P.V. has the following study-unrelated COI: Research grant: Pfizer, Celgene; consultancy honoraria: Blueprint, Incyte, Accord, Teva, Abbvie. W.R.S. has the following study-unrelated COI: honoraria from Novartis, Pfizer, AbbVie, Daiichi Sankyo, Amgen, Thermo Fisher, Deciphera, Incyte, Celgene and Jazz. G.H. has the following study-unrelated COI: honoraria from Novartis. K.V.G. has the following study-unrelated COI: honoraria from Novartis, Pfizer and Incyte.
Supporting Information
References
- 1.Mufti GJ. Pathobiology, classification, and diagnosis of myelodysplastic syndrome. Best Pract Res Clin Haematol. 2004;17:543–557. doi: 10.1016/j.beha.2004.08.007. [DOI] [PubMed] [Google Scholar]
- 2.Hofmann WK, Koeffler HP. Myelodysplastic syndrome. Annu Rev Med. 2005;56:1–16. doi: 10.1146/annurev.med.56.082103.104704. [DOI] [PubMed] [Google Scholar]
- 3.Nimer SD. Myelodysplastic syndromes. Blood. 2008;111:4841–4851. doi: 10.1182/blood-2007-08-078139. [DOI] [PubMed] [Google Scholar]
- 4.Valent P, Horny HP, Bennett JM, Fonatsch C, Germing U, Greenberg P, Haferlach T, Haase D, Kolb HJ, Krieger O, Loken M, van de Loosdrecht A, Ogata K, Orfao A, Pfeilstöcker M, Rüter B, Sperr WR, Stauder R, Wells DA. Definitions and standards in the diagnosis and treatment of the myelodysplastic syndromes: consensus statements and report from a working conference. Leuk Res. 2007;31:727–736. doi: 10.1016/j.leukres.2006.11.009. [DOI] [PubMed] [Google Scholar]
- 5.Bennett JM, Catovsky D, Daniel MT, Flandrin G, Galton DA, Gralnick HR, Sultan C. Proposals for the classification of the myelodysplastic syndromes. Br J Haematol. 1982;51:189–199. [PubMed] [Google Scholar]
- 6.Bennett JM, Catovsky D, Daniel MT, Flandrin G, Galton DA, Gralnick H, Sultan C, Cox C. The chronic myeloid leukaemias: guidelines for distinguishing chronic granulocytic, atypical chronic myeloid, and chronic myelomonocytic leukaemia. Proposals by the French-American-British Cooperative Leukaemia Group. Br J Haematol. 1994;87:746–754. doi: 10.1111/j.1365-2141.1994.tb06734.x. [DOI] [PubMed] [Google Scholar]
- 7.Arber DA, Orazi A, Hasserjian R, Thiele J, Borowitz MJ, Le Beau MM, Bloomfield CD, Cazzola M, Vardiman JW. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood. 2016;127:2391–2405. doi: 10.1182/blood-2016-03-643544. [DOI] [PubMed] [Google Scholar]
- 8.Bennett JM. A comparative review of classification systems in myelodysplastic syndromes (MDS) Semin Oncol. 2005;32:S3–S10. doi: 10.1053/j.seminoncol.2005.06.021. [DOI] [PubMed] [Google Scholar]
- 9.Valent P, Orazi A, Steensma DP, Ebert BL, Haase D, Malcovati L, van de Loosdrecht AA, Haferlach T, Westers TM, Wells DA, Giagounidis A, Loken M, Orfao A, Lübbert M, Ganser A, Hofmann WK, Ogata K, Schanz J, Béné MC, Hoermann G, Sperr WR, Sotlar K, Bettelheim P, Stauder R, Pfeilstöcker M, Horny HP, Germing U, Greenberg P, Bennett JM. Proposed minimal diagnostic criteria for myelodysplastic syndromes (MDS) and potential pre-MDS conditions. Oncotarget. 2017;8:73483–73500. doi: 10.18632/oncotarget.19008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Morel P, Hebbar M, Lai JL, Duhamel A, Preudhomme C, Wattel E, Bauters F, Fenaux P. Cytogenetic analysis has strong independent prognostic value in de novo myelodysplastic syndromes and can be incorporated in a new scoring system: a report on 408 cases. Leukemia. 1993;7:1315–1323. [PubMed] [Google Scholar]
- 11.Sanz GF, Sanz MA, Vallespí T, Cañizo MC, Torrabadella M, García S, Irriguible D, San Miguel JF. Two regression models and a scoring system for predicting survival and planning treatment in myelodysplastic syndromes: a multivariate analysis of prognostic factors in 370 patients. Blood. 1989;74:395–408. [PubMed] [Google Scholar]
- 12.Toyama K, Ohyashiki K, Yoshida Y, Abe T, Asano S, Hirai H, Hirashima K, Hotta T, Kuramoto A, Kuriya S. Clinical implications of chromosomal abnormalities in 401 patients with myelodysplastic syndromes: a multicentric study in Japan. Leukemia. 1993;7:499–508. [PubMed] [Google Scholar]
- 13.Aul C, Gattermann N, Heyll A, Germing U, Derigs G, Schneider W. Primary myelodysplastic syndromes: analysis of prognostic factors in 235 patients and proposals for an improved scoring system. Leukemia. 1992;6:52–59. [PubMed] [Google Scholar]
- 14.Mufti GJ, Stevens JR, Oscier DG, Hamblin TJ, Machin D. Myelodysplastic syndromes: a scoring system with prognostic significance. Br J Haematol. 1985;59:425–433. doi: 10.1111/j.1365-2141.1985.tb07329.x. [DOI] [PubMed] [Google Scholar]
- 15.Greenberg P, Cox C, LeBeau MM, Fenaux P, Morel P, Sanz G, Sanz M, Vallespi T, Hamblin T, Oscier D, Ohyashiki K, Toyama K, Aul C, Mufti G, Bennett J. International scoring system for evaluating prognosis in myelodysplastic syndromes. Blood. 1997;89:2079–2088. [PubMed] [Google Scholar]
- 16.Greenberg PL, Tuechler H, Schanz J, Sanz G, Garcia-Manero G, Solé F, Bennett JM, Bowen D, Fenaux P, Dreyfus F, Kantarjian H, Kuendgen A, Levis A, Malcovati L, Cazzola M, Cermak J, Fonatsch C, Le Beau MM, Slovak ML, Krieger O, Luebbert M, Maciejewski J, Magalhaes SM, Miyazaki Y, Pfeilstöcker M, Sekeres M, Sperr WR, Stauder R, Tauro S, Valent P, Vallespi T, van de Loosdrecht AA, Germing U, Haase D. Revised international prognostic scoring system for myelodysplastic syndromes. Blood. 2012;120:2454–2465. doi: 10.1182/blood-2012-03-420489. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Aul C, Gattermann N, Germing U, Runde V, Heyll A, Schneider W. Risk assessment in primary myelodysplastic syndromes: validation of the Dusseldorf score. Leukemia. 1994;8:1906–1913. [PubMed] [Google Scholar]
- 18.Wimazal F, Sperr WR, Kundi M, Meidlinger P, Fonatsch C, Jordan JH, Thalhammer-Scherrer R, Schwarzinger I, Geissler K, Lechner K, Valent P. Prognostic value of lactate dehydrogenase activity in myelodysplastic syndromes. Leuk Res. 2001;25:287–294. doi: 10.1016/s0145-2126(00)00140-5. [DOI] [PubMed] [Google Scholar]
- 19.Germing U, Hildebrandt B, Pfeilstöcker M, Nösslinger T, Valent P, Fonatsch C, Lübbert M, Haase D, Steidl C, Krieger O, Stauder R, Giagounidis AA, Strupp C, Kündgen A, Mueller T, Haas R, Gattermann N, Aul C. Refinement of the international prognostic scoring system (IPSS) by including LDH as an additional prognostic variable to improve risk assessment in patients with primary myelodysplastic syndromes (MDS) Leukemia. 2005;19:2223–2231. doi: 10.1038/sj.leu.2403963. [DOI] [PubMed] [Google Scholar]
- 20.Malcovati L, Germing U, Kuendgen A, Della Porta MG, Pascutto C, Invernizzi R, Giagounidis A, Hildebrandt B, Bernasconi P, Knipp S, Strupp C, Lazzarino M, Aul C, Cazzola M. Time-dependent prognostic scoring system for predicting survival and leukemic evolution in myelodysplastic syndromes. J. Clin. Oncol. 2007;25:3503–3510. doi: 10.1200/JCO.2006.08.5696. [DOI] [PubMed] [Google Scholar]
- 21.Boehm A, Sperr WR, Leitner G, Worel N, Oehler L, Jaeger E, Mitterbauer M, Haas OA, Valent P, Kalhs P, Rabitsch W. Comorbidity predicts survival in myelodysplastic syndromes or secondary acute myeloid leukaemia after allogeneic stem cell transplantation. Eur J Clin Invest. 2008;38:945–952. doi: 10.1111/j.1365-2362.2008.02041.x. [DOI] [PubMed] [Google Scholar]
- 22.Zipperer E, Pelz D, Nachtkamp K, Kuendgen A, Strupp C, Gattermann N, Haas R, Germing U. The hematopoietic stem cell transplantation comorbidity index is of prognostic relevance for patients with myelodysplastic syndrome. Haematologica. 2009;94:729–732. doi: 10.3324/haematol.2008.002063. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Sperr WR, Wimazal F, Kundi M, Baumgartner C, Nösslinger T, Makrai A, Stauder R, Krieger O, Pfeilstöcker M, Valent P. Comorbidity as prognostic variable in MDS: comparative evaluation of the HCT-CI and CCI in a core dataset of 419 patients of the Austrian MDS Study Group. Ann Oncol. 2010;21:114–119. doi: 10.1093/annonc/mdp258. [DOI] [PubMed] [Google Scholar]
- 24.Della Porta MG, Malcovati L, Strupp C, Ambaglio I, Kuendgen A, Zipperer E, Travaglino E, Invernizzi R, Pascutto C, Lazzarino M, Germing U, Cazzola M. Risk stratification based on both disease status and extra-hematologic comorbidities in patients with myelodysplastic syndrome. Haematologica. 2011;96:441–449. doi: 10.3324/haematol.2010.033506. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Valent P, Sperr WR, Födinger M, Kundi M. Comorbidity, iron overload and HFE variants: a new prognostic complex in MDS? Eur J Clin Invest. 2009;39:1112–1113. doi: 10.1111/j.1365-2362.2009.02196.x. [DOI] [PubMed] [Google Scholar]
- 26.Sperr WR, Kundi M, Wimazal F, Nösslinger T, Schönmetzler-Makrai A, Stauder R, Krieger O, Neukirchen J, Germing U, Pfeilstöcker M, Valent P. Proposed score for survival of patients with myelodysplastic syndromes. Eur J Clin Invest. 2013;43:1120–1128. doi: 10.1111/eci.12149. [DOI] [PubMed] [Google Scholar]
- 27.Valent P, Kern W, Hoermann G, Milosevic-Feenstra JD, Sotlar K, Pfeilstöcker M, Germing U, Sperr WR, Reiter A, Wolf D, Arock M, Haferlach T, Horny HP. Clonal hematopoiesis with oncogenic potential (CHOP): separation from CHIP and roads to AML. Int J Mol Sci. 2019;20:789. doi: 10.3390/ijms20030789. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Valent P, Akin C, Arock M, Bock C, George TI, Galli SJ, Gotlib J, Haferlach T, Hoermann G, Hermine O, Jäger U, Kenner L, Kreipe H, Majeti R, Metcalfe DD, Orfao A, Reiter A, Sperr WR, Staber PB, Sotlar K, Schiffer C, Superti-Furga G, Horny HP. Proposed terminology and classification of pre-malignant neoplastic conditions: a consensus proposal. EBioMedicine. 2017;26:17–24. doi: 10.1016/j.ebiom.2017.11.024. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Steensma DP, Bejar R, Jaiswal S, Lindsley RC, Sekeres MA, Hasserjian RP, Ebert BL. Clonal hematopoiesis of indeterminate potential and its distinction from myelodysplastic syndromes. Blood. 2015;126:9–16. doi: 10.1182/blood-2015-03-631747. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Valent P. ICUS, IDUS, CHIP and CCUS: diagnostic criteria, separation from MDS and clinical implications. Pathobiology. 2018;1:1–9. doi: 10.1159/000489042. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Malcovati L, Cazzola M. The shadowlands of MDS: idiopathic cytopenias of undetermined significance (ICUS) and clonal hematopoiesis of indeterminate potential (CHIP) Hematology Am Soc Hematol Educ Program. 2015;2015:299–307. doi: 10.1182/asheducation-2015.1.299. [DOI] [PubMed] [Google Scholar]
- 32.Roy NB, Myerson S, Schuh AH, Bignell P, Patel R, Wainscoat JS, McGowan S, Marchi E, Atoyebi W, Littlewood T, Chacko J, Vyas P, Killick SB. Cardiac iron overload in transfusion-dependent patients with myelodysplastic syndromes. Br J Haematol. 2011;154:521–524. doi: 10.1111/j.1365-2141.2011.08749.x. [DOI] [PubMed] [Google Scholar]
- 33.Burke W, Imperatore G, McDonnell SM, Baron RC, Khoury MJ. Contribution of different HFE genotypes to iron overload disease: a pooled analysis. Genet Med. 2002;2:271–277. doi: 10.1097/00125817-200009000-00001. [DOI] [PubMed] [Google Scholar]
- 34.Pietrangelo A. Hereditary hemochromatosis: pathogenesis, diagnosis, and treatment. Gastroenterology. 2010;139:393–408. doi: 10.1053/j.gastro.2010.06.013. [DOI] [PubMed] [Google Scholar]
- 35.Brissot P, Pietrangelo A, Adams PC, de Graaff B, McLaren CE, Loréal O. Haemochromatosis. Nat Rev Dis Primers. 2018;4:18016. doi: 10.1038/nrdp.2018.16. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Várkonyi J, Tarkovács G, Karádi I, Andrikovics H, Varga F, Varga F, Demeter J, Tordai A. High incidence of hemochromatosis gene mutations in the myelodysplastic syndrome: the Budapest Study on 50 patients. Acta Haematol. 2003;109:64–67. doi: 10.1159/000068487. [DOI] [PubMed] [Google Scholar]
- 37.Varkonyi J, Demeter J, Tordai A, Andrikovics H. The significance of the hemochromatosis genetic variants in multiple myeloma in comparison to that of myelodysplastic syndrome. Ann Hematol. 2006;85:869–871. doi: 10.1007/s00277-006-0178-1. [DOI] [PubMed] [Google Scholar]
- 38.Nearman ZP, Szpurka H, Serio B, Warshawksy I, Theil K, Lichtin A, Sekeres MA, Maciejewski JP. Hemochromatosis-associated gene mutations in patients with myelodysplastic syndromes with refractory anemia with ringed sideroblasts. Am J Hematol. 2007;82:1076–1079. doi: 10.1002/ajh.20995. [DOI] [PubMed] [Google Scholar]
- 39.Speletas M, Kioumi A, Mandala E, Katodritou E, Papaioannou G, Ritis K, Korantzis I. Prevalence of hemochromatosis gene (HFE) mutations in Greek patients with myelodysplastic syndromes. Acta Haematol. 2003;110:53–54. doi: 10.1159/000072419. [DOI] [PubMed] [Google Scholar]
- 40.De Souza GF, Ribeiro HL Jr, De Sousa JC, Heredia FF, De Freitas RM, Martins MR, Gonçalves RP, Pinheiro RF, Magalhães SM. HFE gene mutation and oxidative damage biomarkers in patients with myelodysplastic syndromes and its relation to transfusional iron overload: an observational cross-sectional study. BMJ Open. 2015;5:e006048. doi: 10.1136/bmjopen-2014-006048. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373–383. doi: 10.1016/0021-9681(87)90171-8. [DOI] [PubMed] [Google Scholar]
- 42.Sorror ML, Maris MB, Storb R, Baron F, Sandmaier BM, Maloney DG, Storer B. Hematopoietic cell transplantation (HCT)-specific comorbidity index: a new tool for risk assessment before allogeneic HCT. Blood. 2005;106:2912–2919. doi: 10.1182/blood-2005-05-2004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Brothman AR, Persons DL, Shaffer LG. Nomenclature evolution: changes in the ISCN from the 2005 to the 2009 edition. Cytogenet Genome Res. 2009;127:1–4. doi: 10.1159/000279442. [DOI] [PubMed] [Google Scholar]
- 44.Kotze MJ, de Villiers JN, Bouwens CS, Warnich L, Zaahl MG, van der Merwe S, Oberkanins C. Molecular diagnosis of hereditary hemochromatosis: application of a newly-developed reverse-hybridization assay in the South African population. Clin Genet. 2004;6:317–321. doi: 10.1111/j.1399-0004.2004.00222.x. [DOI] [PubMed] [Google Scholar]
- 45.Feder JN, Gnirke A, Thomas W, Tsuchihashi Z, Ruddy DA, Basava A, Dormishian F, Domingo R Jr, Ellis MC, Fullan A, Hinton LM, Jones NL, Kimmel BE, Kronmal GS, Lauer P, Lee VK, Loeb DB, Mapa FA, McClelland E, Meyer NC, Mintier GA, Moeller N, Moore T, Morikang E, Prass CE, Quintana L, Starnes SM, Schatzman RC, Brunke KJ, Drayna DT, Risch NJ, Bacon BR, Wolff RK. A novel MHC class I-like gene is mutated in patients with hereditary haemochromatosis. Nat Genet. 1996;13:399–408. doi: 10.1038/ng0896-399. [DOI] [PubMed] [Google Scholar]
- 46.Mura C, Raguenes O, Férec C. HFE mutations analysis in 711 hemochromatosis probands: evidence for S65C implication in mild form of hemochromatosis. Blood. 1999;93:2502–2505. [PubMed] [Google Scholar]
- 47.Várkonyi J, Szabó T, Sebestyén P, Tordai A, Andrikovics H, Kollai G, Karádi I. New aspects of copper and iron metabolism in the myelodysplastic syndromes. Chemotherapy. 2006;52:66–68. doi: 10.1159/000091307. [DOI] [PubMed] [Google Scholar]
- 48.Lucijanić M, Pejša V, Mitrović Z, Štoos-Veić T, Livun A, Jakšić O, Vasilj T, Piršić M, Hariš V, Prka Ž, Kušec R. Hemochromatosis gene mutations may affect the survival of patients with myelodysplastic syndrome. Hematology. 2016;21:170–174. doi: 10.1080/10245332.2015.1101964. [DOI] [PubMed] [Google Scholar]
- 49.List AF, Baer MR, Steensma DP, Raza A, Esposito J, Martinez-Lopez N, Paley C, Feigert J, Besa E. Deferasirox reduces serum ferritin and labile plasma iron in RBC transfusion-dependent patients with myelodysplastic syndrome. J. Clin. Oncol. 2012;30:2134–2139. doi: 10.1200/JCO.2010.34.1222. [DOI] [PubMed] [Google Scholar]
- 50.Nie L, Li L, Yang L, Zhang Y, Xiao Z. HFE genotype and iron metabolism in Chinese patients with myelodysplastic syndromes and aplastic anemia. Ann Hematol. 2010;89:1249–1253. doi: 10.1007/s00277-010-1016-z. [DOI] [PubMed] [Google Scholar]
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