Refractory anemia with ring sideroblasts and marked thrombocytosis (RARS-T) is a rare entity with characteristics of both myelodysplastic syndromes (MDS) and myeloproliferative neoplasms (MPN).1 Patients have been shown to be frequently JAK2V617F and SF3B1, and less commonly MPLW515, mutated (mut).41 Gene mutations that have been occasionally analyzed in limited cohorts include TET2, ASXL1 and DNMT3A.652 Recently, also CALRmut have been reported with varying frequencies of 0%–25%.107 However, a comprehensive mutational analysis of both MPN and MDS related markers has still not been made. To further characterize the genetic landscape of RARS-T, we analyzed 17 genes (ASXL1, CALR, CBL, DNMT3A, ETV6, EZH2, IDH1, IDH2, JAK2, MPL, NPM1, RUNX1, SF3B1, SRSF2, TET2, U2AF1, ZRSR2) in a large cohort of 92 RARS-T patients, and we were able to create a comprehensive mutational landscape in 75 patients.
Patients were diagnosed with RARS-T if they strictly fulfilled the criteria according to the WHO classification 2008.1 Part of the data has been published previously in Flach et al. (18 of 92),5 Jeromin et al. (47 of 92),4 and Broseus et al. (54 of 92)3 and (54 of 95),9 respectively, but these have been included in our study with the purpose of analyzing features not examined in the aforementioned articles. Of 92 patients, data for 36 (39.1%) have not been published before. Patients gave their informed consent to laboratory analyses and scientific studies. The study design adhered to the tenets of the Declaration of Helsinki and was approved by our institutional review board.
Male:female ratio was 1:1.4 and median age was 75 years (range: 44–89 years). Median white blood cell count (WBC) was 7.5 ×10/L (2.9–60.0 ×10/L), hemoglobin level 9.6 g/dL (6.9–13.2 g/dL), platelet count 659×10/L (454–1500 ×10/L), and percentage of ring sideroblasts (RS) 61% (18%–97%). Eighty-six patients were cytogenetically analyzed. Seventy-one patients (82.6%) had normal karyotype and 15 chromosomal aberrations (Online Supplementary Table S1). Screening for mutations in ASXL1, CALR, SF3B1, and SRSF2 was performed by direct Sanger sequencing. JAK2V617F, JAK2exon12 and MPLW515 were analyzed by melting curve analysis. All other genes were analyzed by a 454 deep-sequencing approach (NGS). For analysis of mutation burdens, cases were re-analyzed by NGS or a real-time quantitative approach for JAK2V617F (Online Supplementary Appendix).
Ninety-two patients were analyzed for mutations in the above-mentioned 17 different genes. As material was limited in some cases, 7.7% of all intended analyses could not be performed (Online Supplementary Table S2). The five most frequently mutated genes were: SF3B1 (90.2%), JAK2V617F (58.7%), TET2 (23.3%), DNMT3A (16.7%), and ASXL1 (14.3%). JAK2exon12, CALR, IDH1 and NPM1 showed no mutation. The remaining gene mutations occurred in less than 10% of cases (Online Supplementary Table S2). Altogether, in 98.9% of the patients at least one mutation was found. Only one patient carried no mutation and had normal karyotype. We further analyzed this case for mutations in PRPF8 that have recently been shown to occur in myeloid malignancies and to associate with ring sideroblasts.11 In addition, a pan-myeloid NGS gene panel was applied providing higher sensitivity and data on 11 additional genes (Online Supplementary Appendix). However, also with these approaches no mutation was detectable.
For the final comprehensive analysis we focused on 75 patients that had available mutation status for all 14 genes mutated in at least one of the cases (Figure 1A). JAK2V617F presented in combination with SF3B1mut in 49.3% (37 of 75). Interestingly, nearly all SF3B1 wild-type (wt) cases carried a JAK2V617F (85.7%; n.s.) and an ASXL1mut (85.7% vs. 7.4%; P<0.001). Furthermore, mutations in SRSF2 (2.9% vs. 42.9%; P=0.005) and U2AF1 (1.5% vs. 42.9%; P=0.002) were rare in SF3B1mut cases, but were associated with ASXL1mut (SRSF2mut: 36.4% vs. 1.6%; P=0.001; U2AF1mut: 27.3% vs. 1.6%; P=0.009). Of note, all 13 DNMT3Amut occurred concomitantly with SF3B1mut (n.s.) and were negatively associated with JAK2V617F (7.0% vs. 25.0%; P=0.046) (Online Supplementary Figure S1).
The number of gene mutations per patient ranged from 0 to 7 (mean: 2.4; median: 2.0). SF3B1mut were the only mutations that occurred as sole alteration (14 of 68, 20.6%) (Figure 1B) and were significantly associated with a low number of mutations (mean: 2.3 vs. 3.7; P=0.002) (Online Supplementary Tables S3 and S4). In contrast, 6 of 7 SF3B1wt patients carried a JAK2V617F and ASXL1mut accompanied by either an SRSF2mut (n=3) or U2AF1mut (n=3) (Figure 1A). Accordingly, JAK2V617F (3.0 vs. 1.6; P<0.001) and ASXL1mut (3.9 vs. 2.1; P<0.001) were correlated with high numbers of accompanied gene mutations (Online Supplementary Table S4).
We also analyzed the mutation burden of accompanying gene mutations in 50 cases with quantitative data. These analyses were carried out on unsorted cells, but aimed to analyze the relation of allelic frequencies and not absolute counts. In cases with SF3B1mut, this mutation usually had the highest burden (Figure 2A–E and Online Supplementary Figure S2A–D). Cases with SF3B1mut/JAK2V617F showed slightly lower mutation burdens for JAK2V617F in most patients. Furthermore, in one case a small clone and in 2 patients a homozygous state of JAK2V617F were detected, respectively (Figure 2A). In a further 13 patients, SF3B1mut were accompanied by a second mutation with similar mutation burden in 8 cases. In 3 cases, the additional mutation presented with a clearly lower and in 2 with a higher burden (Figure 2B). In 11 patients with SF3B1mut/JAK2V617F and a third mutation, two groups could be distinguished: either the third mutation (n=4) (Figure 2C) or JAK2V617F (n=8) (Figure 2D) showed the lowest burden. In 4 patients with three alterations not including JAK2V617F, the only mutation with a clearly higher burden than SF3B1mut was MPLW515. For the remaining cases, the third mutation showed a burden of 15% or less (Figure 2E). In 4 patients with 4 to 7 different gene mutations, including SF3B1mut, no definite pattern could be detected (Online Supplementary Figure S2A–D). Analysis of 6 SF3B1wt cases revealed that SRSF2mut or U2AF1mut had the highest mutation burdens, whereas ASXL1mut had either similar (n=2) or lower (n=4) burdens. The JAK2V617F presented as a subclonal mutation in 4 cases (Figure 2F and Online Supplementary Figure S3). The broad spectrum of JAK2V617F mutation burdens suggests diverse sequences of acquirement. Altogether, these data implicate that, in most RARS-T cases, spliceosome mutations either in SF3B1, U2AF1 or SRSF2 are the founder mutations. ASXL1mut and JAK2V617F seem to be acquired at different time points of the evolution of RARS-T and are in most cases subclonal mutations.
Analyzing the clinical characteristics, we detected associations of SF3B1mut with higher percentages of RS (mean: 61% vs. 41%; P=0.006) and of JAK2V617F with higher WBC (10.7 vs. 6.9×10/L; P=0.004) and platelet counts (807 vs. 599×10/L; P<0.001). ASXL1mut cases had lower percentages of RS, even though approximately half of these patients had concomitant SF3B1mut (43% vs. 62%; P=0.004). In contrast, DNMT3Amut/SF3B1mut patients had higher percentages of RS than DNMT3Awt/SF3B1mut cases (69% vs. 58%; P=0.017). Interestingly, the cases with sole SF3B1mut had lower platelet counts (546 vs. 749×10/L; P<0.001) and were younger (68.4 vs. 74.2 years; P=0.040). Survival analyses were not applicable since available data were limited (n=52) and because of the mild course of the disease (events=5). However, part of our cohort has been integrated into a large multicenter study showing that SF3B1mut, JAK2V617F and younger age at diagnosis were independent factors for a good prognosis in RARS-T.3
Taken together, we showed that SF3B1mut have a unique relevance in the development of RARS-T and seem to be the founding mutation in most cases. In SF3B1wt cases, however, U2AF1 and SRSF2 seem to be the founder mutations. Hence, 98.7% (74 of 75) RARS-T cases carried a spliceosome mutation. Furthermore, the high prevalence of ASXL1/JAK2V617F double mutations (6 of 7; 85.7%) in SF3B1wt cases is unique for RARS-T. It might be presumed that in contrast to SF3B1mut patients, SRSF2mut and U2AF1mut cases require mutations in ASXL1 and JAK2V617F for evolution of RARS-T.
There has been discussion as to whether RARS-T is a distinct entity, or a subset of essential thrombocythemia or a progression of RARS.1 Besides JAK2V617F and MPLW515 mutations that are characteristic for MPN, approximately half of the patients in our cohort show a more MDS-characteristic pattern of mutations. SF3B1mut, TET2mut, ASXL1mut and EZH2mut show similar frequencies as those found in MDS and exceed those seen in MPN.1412 Of note, we found a high occurrence of DNMT3Amut in RARS-T, as previously described by others.2 However, in our cohort, DNMT3Amut was always accompanied by an SF3B1mut, resembling data from RARS patients.15 Interestingly, CALRmut were not detected in any of our patients, whereas they can be found frequently in essential thrombocythemia and primary myelofibrosis.87 In other studies, varying frequencies of CALRmut of 0–25% have been reported in RARS-T.107 However, the frequency of CALRmut is most likely very low. High frequencies have been detected only in small cohorts: 12.5% (n=24)7 and 25.0% (n=12),10 whereas a large multicenter study reported a frequency of only 1.1% (n=95).9
In summary, RARS-T patients carry more mutations than previously reported and are specified by frequent occurrence of SF3B1mut (90.2%). Nearly all SF3B1wt patients show SRSF2mut or U2AF1mut in addition to ASXL1mut and JAK2V617F. Therefore, 99% of RARS-T cases can be characterized by mutations in these five genes. The alterations that mediate myeloproliferative character in those cases with a more MDS-characteristic mutation pattern are still unknown. Moreover, the patient with no detectable mutation in our cohort highlights the fact that some gene alterations in RARS-T have still not been discovered.
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