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Mutational profiling in myelofibrosis: implications for management

Abstract

Mutational profiling, usually by targeted next-generation sequencing, is increasingly performed on patients with myeloproliferative neoplasm-associated myelofibrosis (MF), whether primary (PMF) or post-polycythemia vera/essential thrombocythemia (post-PV/ET MF). “Driver” mutations in JAK2, MPL and indels in CALR underlie the vast majority of cases of PMF and post-ET MF; the remainder (≈ 10%) lack identifiable driver mutations, but other clonal markers are usually detectable. Nearly all patients with post-PV MF carry activating JAK2 mutations. In both PMF and post-ET MF, type 1/-like CALR mutations confer a favorable prognosis. Since both type 1/-like and type 2/-like CALR mutations have essentially the same functional consequence, this is a subject of intense research. Additional, “non-driver” mutations, mostly affecting genes encoding epigenetic modifiers or spliceosome components, e.g., ASXL1, EZH2, TET2, DNMT3A, SRSF2 and U2AF1, are frequently found; some of these are associated with inferior survival and have been incorporated into prognostic models. Some mutations, e.g., IDH1/2, are relatively infrequent in chronic phase but are substantially more common in blast phase, and are now therapeutically targetable. While mutational information does not currently influence choice of drug therapy in chronic-phase MF, the presence of a “high molecular risk” genotype is now routinely taken into account for transplant decision-making.

Introduction

The discovery in 2005 of the activating V617F mutation in the tyrosine kinase Janus kinase 2 (JAK2), integral to downstream signaling upon cell surface receptor binding by a multitude of growth factors and cytokines, ushered in the molecular era in myeloproliferative neoplasm (MPN) research [1,2,3,4]. The discovery of activating mutations in MPL, the thrombopoietin receptor, in a small proportion of patients with essential thrombocythemia (ET) and primary myelofibrosis (PMF) followed in 2006 [5, 6]. The molecular driver underlying most cases of JAK2/MPL-wild type (WT) classic MPN remained elusive until insertions and deletions in exon 9 of the endoplasmic reticulum (ER) chaperone calreticulin (CALR) that activate the JAK-signal transducer and activator of transcription (STAT) pathway were discovered in 2013 [7, 8]. Thus today, only 10–15% of cases of ET and PMF, the so-called “triple negative” cases, lack a clearly identified molecular driver, although non-canonical JAK2 and MPL mutations have been described in some of these cases [9, 10]. Polycythemia vera (PV) is virtually exclusively a JAK2-driven disease [3], with ≈ 95% of cases harboring JAK2V617F and another ≈ 4% bearing activating mutations in exon 12 of the JAK2 gene [11]; thus, nearly all cases of post-PV MF are JAK2 mutated. Loss of function mutations in LNK, a negative regulator of JAK2, may explain some of the rare cases of JAK2-WT PV [12, 13]. Importantly, integrated genomic profiling approaches have shown universal activation of the JAK–STAT pathway in patients with MPNs [14] and, indeed, the JAK1/2 inhibitor ruxolitinib is effective in patients with MF regardless of driver mutation status [15, 16].

Mutations in a number of other genes, the vast majority involved in epigenetic modification of chromatin or in RNA splicing, have been found in patients with MPNs, particularly those with PMF [17]. In a recent study of 2035 patients with MPN (1321 with ET), mutations in JAK2, MPL and CALR were the sole abnormality in only 45% of patients [17]. The presence of one or more of these can be very helpful in diagnosing a MPN by providing evidence of clonality in triple-negative cases of ET or PMF [18]. In 2013, Vannucchi and colleagues reported a set of 5 “high molecular risk” (HMR) mutations (ASXL1, EZH2, SRSF2, IDH1/2) in patients with PMF, the presence of which correlated with worse outcomes [19]. Work by Tefferi et al. [20] has led to the recognition of U2AF1Q157 mutations as an additional “non-driver” mutation with adverse prognostic impact in PMF. On a disease pathogenesis level, there is evidence that the order of acquisition of certain non-driver and driver mutations influences disease phenotype [21, 22].

Driver mutations

Biology

Among patients with PMF as well as post-ET MF, JAK2V617F is detected in 50–60% of cases, CALR exon 9 indels in another 20–30%, and MPLW515L/K mutations in 5–10%. As alluded to above, virtually all cases of post-PV MF carry JAK2 mutations. The canonical V617F mutation in exon 14 affects the pseudokinase domain of JAK2, relieving its autoinhibitory action on the kinase domain, leading to constitutive activation of the latter [23]. JAK2 is critical for normal hematopoiesis in that the receptors for erythropoietin, interleukin-3, granulocyte/macrophage colony stimulating factor and thrombopoietin all signal via JAK2 through their cell surface receptors [24, 25]. Importantly, a JAK2V617F knock-in mouse model resembles human PV and the MPN is serially transplantable, with the hematopoietic stem cell (HSC) compartment (but not the myeloid progenitor cells) capable of initiating disease [26]. Germline variants in JAK2, the best known being the 46/1 (GGCC) haplotype [27], and other genes can predispose individuals to acquire JAK2V617F and develop JAK2V617F clonal hematopoiesis or a frank MPN [28, 29]. Among JAK2-mutated patients with PMF, those with a lower JAK2V617F allele burden may have a more myelodepletive than myeloproliferative phenotype and have been shown to have poorer survival [30, 31]. Interestingly, a JAK2V617F allele burden ≥ 50%, which has been associated with favorable survival [32], has also been reported to predict for greater responsiveness to ruxolitinib among patients with MF and splenomegaly requiring therapy [33].

Mice retrovirally transduced with MPLW515L develop a transplantable ET-like disorder with marked thrombocytosis and leukocytosis, splenomegaly and extramedullary hematopoiesis and minimal effect on reticulocytes; progressive reticulin fibrosis in the bone marrow develops over time [5]. More recent work shows that MPL activation by thrombopoietin or a thrombopoietin receptor agonist directly induces fibrocyte differentiation to cause bone marrow fibrosis [34]. Both the type 1 (52 base pair deletion) and type 2 (5 base pair insertion) mutations in exon 9 of CALR result in an altered C-terminus (loss of negative charge) of the protein with impaired Ca2+ binding and loss of the “KDEL” ER retention motif [7, 8]. Like in the case of mutant JAK2 and MPL, expression of mutant CALR alone is sufficient to engender MPN in mice [35, 36]. Mutant calreticulin must bind to the extracellular domain of MPL (N-glycosylation of MPL is required) to activate the JAK–STAT pathway and transform hematopoietic cells, and its positively charged C-terminus is required for this interaction [35,36,37,38].

Clinical and prognostic features

In general, patients with CALR-mutated PMF are younger, have higher platelet counts and are less likely to be anemic, thrombocytopenic, require transfusions or display leukocytosis [39]. They also have a lower risk of developing these latter disease features compared to their JAK2/MPL-mutated or triple-negative counterparts [40]. Like in ET [41], CALR mutations are also associated with a lower risk of thrombosis compared with JAK2V617F in patients with PMF; in fact, the clotting risk appears largely confined to the JAK2-mutated population [42]. Overall, studies have not shown any meaningful or consistent differences in clinical phenotype or outcomes between JAK2- and MPL-mutated PMF [43].

Early studies all confirmed that patients with CALR-mutated PMF enjoyed superior overall survival (OS) and leukemia-free survival (LFS) compared to those with JAK2 or MPL mutations and triple-negative patients, with the latter faring the worst [39, 40, 44]. In an Italian study of 617 patients with PMF, median survival was 17.7 years among CALR-mutant, 9.2 years among JAK2-mutant, 9.1 years among MPL-mutant, and 3.2 years among triple-negative patients [40]. It has since become apparent, however, that the survival advantage of CALR mutations in PMF is restricted to patients who carry the more common type 1/-like mutations [45,46,47]. Why this may be is poorly understood, given that both type 1/-like and type 2/-like CALR mutations have essentially the same functional consequence. Among 709 patients with PMF seen at the Mayo Clinic, survival was longer with type 1/-like CALR, compared to JAK2, type 2/-like CALR, MPL, and triple-negative driver mutation status, observations that were validated in a cohort of 386 Italian patients [48]. In post-ET MF, also, CALR mutations appear to exert a favorable prognostic impact, although differences between type 1/-like and type 2/-like were not apparent in the large myelofibrosis secondary to PV and ET (MYSEC) study [49]. In another, smaller, Italian series, triple negativity was associated with significantly shortened survival in post-ET MF [50].

Non-driver mutations

Targeted Sanger sequencing (10 genes, including JAK2 and MPL) performed on a cohort of 483 European patients at diagnosis of PMF revealed the following mutational frequencies: ASXL1 (21.7%), TET2 (9.7%), SRSF2 (8.5%), DNMT3A (5.7%), MPL (5.2%), EZH2 (5.1%), CBL (4.4%) and IDH1/2 (2.6%) [19]. Of these, mutations in ASXL1, EZH2 and SRSF2 inter-independently predicted worse survival, while ASXL1, SRSF2, IDH1 and IDH2 mutations were independently associated with leukemic transformation. Accordingly, the authors designated mutations in these 5 genes as HMR mutations, having ≥ 1 of which was independently associated with inferior OS and LFS. The presence of ≥ 2 HMR mutations was subsequently shown to be associated with a particularly dismal outcome (median OS, 2.6 years vs. 7 years for 1 mutation vs. 12.3 years for none) [51]. Two or more HMR mutations were also associated with inferior LFS. These findings were, in large part, validated in cohorts of patients from the Mayo Clinic, who underwent sequencing at the time of referral. In a later study (n = 182) from the Mayo Clinic that used a next-generation sequencing (NGS) panel of 27 genes, 81% of patients were found to have mutations/variants in genes other than JAK2, MPL or CALR [52]. The most frequent alterations were in ASXL1 (36%), TET2 (18%), SRSF2 (18%) and U2AF1 (16%). Based on multivariate analysis of impact on OS and LFS, mutations/variants in ASXL1, SRSF2, CBL, KIT, RUNX1, SH2B3 and CEBPA were designated as being adverse. Median OS times in patients with 0, 1 or 2, and ≥ 3 adverse mutations/variants were 8.5, 4 and 0.7 years, respectively.

Prognostic models

Prognostication of patients with PMF in the modern era really began with the publication of the International Prognostic Scoring System (IPSS) in 2009 [53], followed by the Dynamic IPSS (DIPSS) in 2010 [54]; these risk scoring systems rely on readily available clinical variables alone. The DIPPS-plus, published in 2011, additionally incorporated karyotype, platelet count and RBC transfusion need [55]. Of interest, in the study that led to the characterization of the HMR mutations discussed above, only ASXL1 mutations provided additional prognostic information in the context of the IPSS/DIPSS-plus [19]. A molecular prognostic model constructed just based on the mutational status of 2 genes found that survival was longest in CALR-mutated/ASXL1 WT patients (median, 10.4 years) and shortest in CALR WT/ASXL1 mutated patients (median, 2.3 years), with patients with both or neither mutations having an intermediate survival (median, 5.8 years) [56]. Importantly, CALR/ASXL1 mutational status was able to sub-divide both lower and higher risk DIPSS-plus categories of patients into sub-categories with significantly different survival. More recently, a number of prognostic models have emerged that incorporate mutational information and one that exclusively relies on genomic information: these are discussed below.

MIPSS70, MIPSS70-plus and MIPSS70-plus version 2.0

Developed as risk stratification scoring systems for transplant-eligible patients (i.e., aged ≤ 70 years) with PMF, the MIPSS70 (mutation enhanced International Prognostic Scoring System 70) and the MIPSS70-plus models were derived from the study of 805 patients with PMF up to the age of 70 recruited from multiple Italian centers and the Mayo Clinic and divided into independent learning and validation cohorts [57]. The MIPSS70 includes the following risk factors found to be significant on multivariate analysis for OS: hemoglobin < 10 g/dL (1 point), WBCs > 25 × 109/L (2 points), platelets < 100 × 109/L (2 points), circulating blasts ≥ 2% (1 point), bone marrow fibrosis grade ≥ 2 (1 point), presence of constitutional symptoms (1 point), absence of type 1/-like CALR mutation (1 point), presence of ≥ 1 HMR (ASXL1, EZH2, SRSF2, IDH1/2) mutation (1 point) and presence of ≥ 2 HMR mutations (2 points), and delineates 3 risk categories (Table 1). The MIPSS70-plus is similar, but additionally incorporates unfavorable karyotype (3 points) and assigns 2 points (instead of 1) to absence of type 1/-like CALR mutation but leaves out the leukocyte and platelet counts, as well as the grade of bone marrow fibrosis, and results in four prognostically distinct categories (Table 2). Unfavorable karyotype here refers to complex karyotype or sole or two abnormalities that include +8, -7/7q-, -5/5q-, 12p-, i(17q), inv(3) or 11q23 rearrangement [58].

Table 1 The molecularly enhanced International Prognostic Scoring System for patients with primary myelofibrosis up to the age of 70 (MIPSS70) [57]
Table 2 The molecularly enhanced International Prognostic Scoring System-plus for patients with primary myelofibrosis up to the age of 70 (MIPSS70-plus) [57]

Recognition of “very high risk” (VHR) karyotypes (Table 3) [59], the poor prognosis associated with U2AF1Q157 mutations [20] and the prognostic impact of severity of anemia in the context of patient sex [60] led to further refinement of the MIPSS70-plus to create the MIPSS70-plus version 2.0 [61]. This model was derived using the 311 Mayo Clinic PMF patients 70 years or younger, data on whom was used to inform the development of the MIPSS70 and MIPSS70-plus models. Severe anemia was defined as hemoglobin < 8 g/dL in a woman and < 9 g/dL in a man; moderate anemia was defined as hemoglobin of 8–9.9 g/dL and 9–10.9 g/dL, respectively. Hazard ratio (for death)-weighted points were allocated to VHR karyotype (4 points), unfavorable karyotype (3 points), ≥ 2 HMR mutations (3 points), 1 HMR mutation (2 points), absence of type 1/-like CALR mutation (2 points), presence of constitutional symptoms (2 points), severe anemia (2 points), moderate anemia (1 point) and ≥ 2% circulating blasts (1 point), resulting in a 5-tiered MIPSS70-plus version 2.0 model (Table 4).

Table 3 The revised cytogenetic risk classification in primary myelofibrosis [59]
Table 4 The molecularly enhanced International Prognostic Scoring System-plus, version 2.0 for patients with primary myelofibrosis up to the age of 70 (MIPSS70-plus version 2.0) [61]

GIPSS

The Genetically Inspired Prognostic Scoring System (GIPSS) was the result of another Mayo Clinic–Italian collaborative project that aimed to generate a prognostic model based entirely on genetic markers [62]. Derived from cytogenetic and molecular data on 641 patients with PMF, the only risk factors considered in this four-tiered model (Table 5) are VHR (2 points) and unfavorable karyotypes (1 point), absence of type 1/-like CALR mutation (1 point), and presence of ASXL1, SRSF2 or U2AF1Q157 mutations (1 point). The authors found the GIPSS to be non-inferior to the MIPSS70-plus and the DIPSS in terms of ability to discriminate and accuracy of prediction using standard statistical tools such as the Akaike information criterion and area under the curve. Of interest, investigators at the Moffitt Cancer Center have shown that the GIPSS outperforms the DIPSS in patients in whom the 2 models disagree [63]. Furthermore, they demonstrated that the GIPSS performs equally well in patients with PMF and post-PV/ET MF.

Table 5 The Genetically Inspired Prognostic Scoring System (GIPSS) for patients with primary myelofibrosis [62]

MYSEC-PM

Several groups have shown that prognostic models designed for PMF do not work well in risk stratifying patients with post-PV/ET MF [64, 65]. To address this shortcoming, the MYSEC investigators studied 685 molecularly annotated patients with post-PV/ET MF. Median survival (from diagnosis of post-PV/ET MF) for the whole cohort was 9.3 years, which compares favorably to what has been reported in large studies of patients with PMF [44, 66, 67]. Median OS for the 352 patients with post-PV MF was 8.1 years, and that for the 333 patients with post-ET MF was 14.5 years. The MYSEC prognostic model (MYSEC-PM) that emerged from this study allocates 2 points each to hemoglobin < 11 g/dL, circulating blasts ≥ 3%, and CALR WT genotype, 1 point each to platelets < 150 × 109/L and constitutional symptoms, and 0.15 points per year of age, delineating 4 prognostic categories with significantly different survival (median not reached for low risk, 9.3 years for intermediate risk, 4.4 years for intermediate-2 risk and 2 years for high risk). In practice, users plot patient age and the total number of points allocated for all the other risk factors on a nomogram to quickly find the prognostic category for a given patient. The MYSEC-PM has been independently validated, but the heavy reliance on age could be a shortcoming of this model [68].

Therapeutic implications

From a management standpoint, the main utility of all the prognostic information and models presented above is to help determine which patients to refer for allogeneic hematopoietic cell transplantation (allo-HCT). As a general rule, national and international guidelines recommend this approach for patients whose predicted (i.e., median for their prognostic category) survival is < 5 years [69, 70]. Generally, this corresponds to those with intermediate-2 or high-risk disease; however, the recent emergence of the above newer prognostic scoring systems has created confusion as to which one to use in everyday practice. Consensus guidelines on indications for allo-HCT for patients with PMF from a European Blood and Marrow Transplantation/European LeukemiaNet working group that predated these newer models suggest that patients younger than 70 with intermediate-2 or high-risk disease be considered candidates for allo-HCT, as well as those under 65 with intermediate-1 risk disease if they have refractory, transfusion-dependent anemia, circulating blasts > 2%, unfavorable cytogenetics (as defined in the DIPSS-plus) [55, 58], are triple negative or have an ASXL1 mutation [71].

While the MIPSS70-plus version 2.0 has been shown to predict survival after reduced intensity conditioning (RIC) allo-HCT using fludarabine/melphalan in a single-institution retrospective study of 110 patients with PMF or post-PV/ET MF [72], the myelofibrosis transplant scoring system (MTSS) was developed with the specific aim of predicting outcomes after allo-HCT using pre-transplant variables, using a training cohort of 205 patients with PMF or post-PV/ET MF and an external validation cohort (n = 156) [73]. Multivariate analysis identified age ≥ 57 years (1 point), Karnofsky performance status < 90% (1 point), platelets < 150 × 109/L (1 point), WBCs > 25 × 109/L (1 point), HLA-mismatched unrelated donor (2 points), ASXL1 mutation (1 point) and non-CALR/MPL driver mutation genotype (2 points) as adverse factors for survival post-transplant (Table 6). Comparison of concordance indices across prognostic models for PMF (i.e., DIPSS, DIPSS-plus, MIPSS70, MIPSS70-plus version 2.0 and GPSS) indicated better performance of the MTSS in discriminating between prognostic categories for patients undergoing allo-HCT. The same was true of the MTSS versus the MYSEC-PM for post-PV/ET patients. Interestingly, the MTSS also accurately predicted 5-year non-relapse mortality.

Table 6 The Myelofibrosis Transplant Scoring System (MTSS) [73]

At present, mutational information does not inform standard medical management of patients with MF with JAK inhibitors. However, mutational profiling of 95 patients with MF enrolled on the phase 1/2 trial of ruxolitinib at the MD Anderson Cancer Center has revealed some interesting insights. Using a 28-gene myeloid mutation (next-generation sequencing) panel, it was shown that patients with ≥ 1 mutations in ASXL1, EZH2, IDH1 and IDH2 and those with ≥ 3 mutations of any type were significantly less likely to have a spleen response and had significantly shorter OS than those with no ASXL1/EZH2/IDH1/2 mutations and those with ≤ 2 mutations [74]. Patients with ≥ 3 mutations also had a significantly shorter time to treatment discontinuation. Genes involved in RNA splicing were not interrogated by this panel. Our group subsequently looked at the 86 patients on this study who had discontinued ruxolitinib after a median follow-up of 79 months [75]. Thirty of these patients died while on therapy; among the remaining 56 patients (median follow-up 32 months), median OS was 14 months. Of 62 patients with paired (baseline and follow-up) molecular data available, 22 (35%) exhibited evidence of clonal evolution (ASXL1 in 14 (61%) cases); median OS after discontinuation for those with clonal evolution on ruxolitinib was significantly worse (6 months) compared to those without (16 months).

Mutational landscape of blast-phase MPN

Genomic and functional analyses of post-MPN acute myeloid leukemia (AML) samples [76] have unveiled a mutational profile that is quite distinct from that of de novo AML [77] as well as that of AML arising from myelodysplastic syndromes [78]. The JAK2V617F mutation is often no longer detected upon leukemic transformation of JAK2V617F-driven MPNs [79]. This suggests that the chronic and blast phases of the disease could be phylogenetically related, having arisen from a shared founder clone, or clonally unrelated, reflecting the transformation of independent HSCs [80]. Mutations in IDH1/2 and TP53, uncommon in chronic-phase MPNs, are substantially more frequent in blast phase [81, 82]. Given the success of enasidenib [83] and ivosidenib [84] in patients with relapsed/refractory IDH-mutated AML and high response rate of TP53-mutated AML to 10-day decitabine [85], these molecular findings may have important therapeutic implications. The combination of ruxolitinib and decitabine, although synergistic in the laboratory [76], has only been modestly successful in the clinic, but provides an important, well-tolerated option for the outpatient treatment of patients who may not be candidates for intensive chemotherapy [86, 87].

Conclusions

As with other hematologic malignancies, the management of patients with MF has very much entered the molecular era. The prognostic impact of several driver and non-driver mutations is now well-established; this has obvious relevance to both patient selection for allo-HCT and post-transplant outcomes. While mutational information does not guide selection of medical therapy yet, it can be valuable for treatment planning given what is known about response to ruxolitinib and outcomes after discontinuation. Finally, as new targeted agents, e.g., IDH inhibitors [83, 84], become increasingly available and others, e.g., splicing modulators [88], are developed, mutational information may allow more personalized/tailored therapy for patients with MF.

References

  1. 1.

    Levine RL, Wadleigh M, Cools J, Ebert BL, Wernig G, Huntly BJ, et al. Activating mutation in the tyrosine kinase JAK2 in polycythemia vera, essential thrombocythemia, and myeloid metaplasia with myelofibrosis. Cancer Cell. 2005;7:387–97.

  2. 2.

    Kralovics R, Passamonti F, Buser AS, Teo SS, Tiedt R, Passweg JR, et al. A gain-of-function mutation of JAK2 in myeloproliferative disorders. N Engl J Med. 2005;352:1779–90.

  3. 3.

    James C, Ugo V, Le Couedic JP, Staerk J, Delhommeau F, Lacout C, et al. A unique clonal JAK2 mutation leading to constitutive signalling causes polycythaemia vera. Nature. 2005;434:1144–8.

  4. 4.

    Baxter EJ, Scott LM, Campbell PJ, East C, Fourouclas N, Swanton S, et al. Acquired mutation of the tyrosine kinase JAK2 in human myeloproliferative disorders. Lancet. 2005;365:1054–61.

  5. 5.

    Pikman Y, Lee BH, Mercher T, McDowell E, Ebert BL, Gozo M, et al. MPLW515L is a novel somatic activating mutation in myelofibrosis with myeloid metaplasia. PLoS Med. 2006;3:e270.

  6. 6.

    Pardanani AD, Levine RL, Lasho T, Pikman Y, Mesa RA, Wadleigh M, et al. MPL515 mutations in myeloproliferative and other myeloid disorders: a study of 1182 patients. Blood. 2006;108:3472–6.

  7. 7.

    Klampfl T, Gisslinger H, Harutyunyan AS, Nivarthi H, Rumi E, Milosevic JD, et al. Somatic mutations of calreticulin in myeloproliferative neoplasms. N Engl J Med. 2013;369:2379–90.

  8. 8.

    Nangalia J, Massie CE, Baxter EJ, Nice FL, Gundem G, Wedge DC, et al. Somatic CALR mutations in myeloproliferative neoplasms with nonmutated JAK2. N Engl J Med. 2013;369:2391–405.

  9. 9.

    Cabagnols X, Favale F, Pasquier F, Messaoudi K, Defour JP, Ianotto JC, et al. Presence of atypical thrombopoietin receptor (MPL) mutations in triple-negative essential thrombocythemia patients. Blood. 2016;127:333–42.

  10. 10.

    Milosevic Feenstra JD, Nivarthi H, Gisslinger H, Leroy E, Rumi E, Chachoua I, et al. Whole-exome sequencing identifies novel MPL and JAK2 mutations in triple-negative myeloproliferative neoplasms. Blood. 2016;127:325–32.

  11. 11.

    Scott LM, Tong W, Levine RL, Scott MA, Beer PA, Stratton MR, et al. JAK2 exon 12 mutations in polycythemia vera and idiopathic erythrocytosis. N Engl J Med. 2007;356:459–68.

  12. 12.

    Oh ST, Simonds EF, Jones C, Hale MB, Goltsev Y, Gibbs KD Jr, et al. Novel mutations in the inhibitory adaptor protein LNK drive JAK-STAT signaling in patients with myeloproliferative neoplasms. Blood. 2010;116:988–92.

  13. 13.

    Lasho TL, Pardanani A, Tefferi A. LNK mutations in JAK2 mutation-negative erythrocytosis. N Engl J Med. 2010;363:1189–90.

  14. 14.

    Rampal R, Al-Shahrour F, Abdel-Wahab O, Patel JP, Brunel JP, Mermel CH, et al. Integrated genomic analysis illustrates the central role of JAK-STAT pathway activation in myeloproliferative neoplasm pathogenesis. Blood. 2014;123:e123–33.

  15. 15.

    Guglielmelli P, Biamonte F, Rotunno G, Artusi V, Artuso L, Bernardis I, et al. Impact of mutational status on outcomes in myelofibrosis patients treated with ruxolitinib in the COMFORT-II study. Blood. 2014;123:2157–60.

  16. 16.

    Verstovsek S, Mesa RA, Gotlib J, Levy RS, Gupta V, DiPersio JF, et al. The clinical benefit of ruxolitinib across patient subgroups: analysis of a placebo-controlled, Phase III study in patients with myelofibrosis. Br J Haematol. 2013;161:508–16.

  17. 17.

    Grinfeld J, Nangalia J, Baxter EJ, Wedge DC, Angelopoulos N, Cantrill R, et al. Classification and personalized prognosis in myeloproliferative neoplasms. N Engl J Med. 2018;379:1416–30.

  18. 18.

    Arber DA, Orazi A, Hasserjian R, Thiele J, Borowitz MJ, Le Beau MM, et al. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood. 2016;127:2391–405.

  19. 19.

    Vannucchi AM, Lasho TL, Guglielmelli P, Biamonte F, Pardanani A, Pereira A, et al. Mutations and prognosis in primary myelofibrosis. Leukemia. 2013;27:1861–9.

  20. 20.

    Tefferi A, Finke CM, Lasho TL, Hanson CA, Ketterling RP, Gangat N, et al. U2AF1 mutation types in primary myelofibrosis: phenotypic and prognostic distinctions. Leukemia. 2018;32:2274.

  21. 21.

    Ortmann CA, Kent DG, Nangalia J, Silber Y, Wedge DC, Grinfeld J, et al. Effect of mutation order on myeloproliferative neoplasms. N Engl J Med. 2015;372:601–12.

  22. 22.

    Nangalia J, Nice FL, Wedge DC, Godfrey AL, Grinfeld J, Thakker C, et al. DNMT3A mutations occur early or late in patients with myeloproliferative neoplasms and mutation order influences phenotype. Haematologica. 2015;100:e438–42.

  23. 23.

    Bandaranayake RM, Ungureanu D, Shan Y, Shaw DE, Silvennoinen O, Hubbard SR. Crystal structures of the JAK2 pseudokinase domain and the pathogenic mutant V617F. Nat Struct Mol Biol. 2012;19:754–9.

  24. 24.

    Parganas E, Wang D, Stravopodis D, Topham DJ, Marine JC, Teglund S, et al. Jak2 is essential for signaling through a variety of cytokine receptors. Cell. 1998;93:385–95.

  25. 25.

    Neubauer H, Cumano A, Muller M, Wu H, Huffstadt U, Pfeffer K. Jak2 deficiency defines an essential developmental checkpoint in definitive hematopoiesis. Cell. 1998;93:397–409.

  26. 26.

    Mullally A, Lane SW, Ball B, Megerdichian C, Okabe R, Al-Shahrour F, et al. Physiological Jak2V617F expression causes a lethal myeloproliferative neoplasm with differential effects on hematopoietic stem and progenitor cells. Cancer Cell. 2010;17:584–96.

  27. 27.

    Jones AV, Chase A, Silver RT, Oscier D, Zoi K, Wang YL, et al. JAK2 haplotype is a major risk factor for the development of myeloproliferative neoplasms. Nat Genet. 2009;41:446–9.

  28. 28.

    Hinds DA, Barnholt KE, Mesa RA, Kiefer AK, Do CB, Eriksson N, et al. Germ line variants predispose to both JAK2 V617F clonal hematopoiesis and myeloproliferative neoplasms. Blood. 2016;128:1121–8.

  29. 29.

    Tapper W, Jones AV, Kralovics R, Harutyunyan AS, Zoi K, Leung W, et al. Genetic variation at MECOM, TERT, JAK2 and HBS1L-MYB predisposes to myeloproliferative neoplasms. Nat Commun. 2015;6:6691.

  30. 30.

    Tefferi A, Lasho TL, Huang J, Finke C, Mesa RA, Li CY, et al. Low JAK2V617F allele burden in primary myelofibrosis, compared to either a higher allele burden or unmutated status, is associated with inferior overall and leukemia-free survival. Leukemia. 2008;22:756–61.

  31. 31.

    Guglielmelli P, Barosi G, Specchia G, Rambaldi A, Lo Coco F, Antonioli E, et al. Identification of patients with poorer survival in primary myelofibrosis based on the burden of JAK2V617F mutated allele. Blood. 2009;114:1477–83.

  32. 32.

    Rozovski U, Verstovsek S, Manshouri T, Dembitz V, Bozinovic K, Newberry K, et al. An accurate, simple prognostic model consisting of age, JAK2, CALR, and MPL mutation status for patients with primary myelofibrosis. Haematologica. 2017;102:79–84.

  33. 33.

    Barosi G, Klersy C, Villani L, Bonetti E, Catarsi P, Poletto V, et al. JAK2(V617F) allele burden 50% is associated with response to ruxolitinib in persons with MPN-associated myelofibrosis and splenomegaly requiring therapy. Leukemia. 2016;30:1772–5.

  34. 34.

    Maekawa T, Osawa Y, Izumi T, Nagao S, Takano K, Okada Y, et al. Myeloproliferative leukemia protein activation directly induces fibrocyte differentiation to cause myelofibrosis. Leukemia. 2017;31:2709.

  35. 35.

    Marty C, Pecquet C, Nivarthi H, El-Khoury M, Chachoua I, Tulliez M, et al. Calreticulin mutants in mice induce an MPL-dependent thrombocytosis with frequent progression to myelofibrosis. Blood. 2016;127:1317–24.

  36. 36.

    Elf S, Abdelfattah NS, Chen E, Perales-Paton J, Rosen EA, Ko A, et al. Mutant calreticulin requires both its mutant C-terminus and the thrombopoietin receptor for oncogenic transformation. Cancer Discov. 2016;6:368–81.

  37. 37.

    Araki M, Yang Y, Masubuchi N, Hironaka Y, Takei H, Morishita S, et al. Activation of the thrombopoietin receptor by mutant calreticulin in CALR-mutant myeloproliferative neoplasms. Blood. 2016;127:1307–16.

  38. 38.

    Chachoua I, Pecquet C, El-Khoury M, Nivarthi H, Albu RI, Marty C, et al. Thrombopoietin receptor activation by myeloproliferative neoplasm associated calreticulin mutants. Blood. 2016;127:1325–35.

  39. 39.

    Tefferi A, Lasho TL, Finke CM, Knudson RA, Ketterling R, Hanson CH, et al. CALR vs JAK2 vs MPL-mutated or triple-negative myelofibrosis: clinical, cytogenetic and molecular comparisons. Leukemia. 2014;28:1472–7.

  40. 40.

    Rumi E, Pietra D, Pascutto C, Guglielmelli P, Martinez-Trillos A, Casetti I, et al. Clinical effect of driver mutations of JAK2, CALR, or MPL in primary myelofibrosis. Blood. 2014;124:1062–9.

  41. 41.

    Alvarez-Larran A, Pereira A, Guglielmelli P, Hernandez-Boluda JC, Arellano-Rodrigo E, Ferrer-Marin F, et al. Antiplatelet therapy versus observation in low-risk essential thrombocythemia with a CALR mutation. Haematologica. 2016;101:926–31.

  42. 42.

    Finazzi MC, Carobbio A, Cervantes F, Isola IM, Vannucchi AM, Guglielmelli P, et al. CALR mutation, MPL mutation and triple negativity identify patients with the lowest vascular risk in primary myelofibrosis. Leukemia. 2015;29:1209–10.

  43. 43.

    Pardanani A, Guglielmelli P, Lasho TL, Pancrazzi A, Finke CM, Vannucchi AM, et al. Primary myelofibrosis with or without mutant MPL: comparison of survival and clinical features involving 603 patients. Leukemia. 2011;25:1834–9.

  44. 44.

    Tefferi A, Guglielmelli P, Larson DR, Finke C, Wassie EA, Pieri L, et al. Long-term survival and blast transformation in molecularly annotated essential thrombocythemia, polycythemia vera, and myelofibrosis. Blood. 2014;124:2507–13 ; quiz 2615.

  45. 45.

    Tefferi A, Lasho TL, Finke C, Belachew AA, Wassie EA, Ketterling RP, et al. Type 1 vs type 2 calreticulin mutations in primary myelofibrosis: differences in phenotype and prognostic impact. Leukemia. 2014;28:1568–70.

  46. 46.

    Tefferi A, Lasho TL, Tischer A, Wassie EA, Finke CM, Belachew AA, et al. The prognostic advantage of calreticulin mutations in myelofibrosis might be confined to type 1 or type 1-like CALR variants. Blood. 2014;124:2465–6.

  47. 47.

    Guglielmelli P, Rotunno G, Fanelli T, Pacilli A, Brogi G, Calabresi L, et al. Validation of the differential prognostic impact of type 1/type 1-like versus type 2/type 2-like CALR mutations in myelofibrosis. Blood Cancer J. 2015;5:e360.

  48. 48.

    Tefferi A, Nicolosi M, Mudireddy M, Szuber N, Finke CM, Lasho TL, et al. Driver mutations and prognosis in primary myelofibrosis: Mayo-Careggi MPN alliance study of 1,095 patients. Am J Hematol. 2018;93:348–55.

  49. 49.

    Passamonti F, Mora B, Giorgino T, Guglielmelli P, Cazzola M, Maffioli M, et al. Driver mutations’ effect in secondary myelofibrosis: an international multicenter study based on 781 patients. Leukemia. 2017;31:970–3.

  50. 50.

    Rotunno G, Pacilli A, Artusi V, Rumi E, Maffioli M, Delaini F, et al. Epidemiology and clinical relevance of mutations in postpolycythemia vera and postessential thrombocythemia myelofibrosis: A study on 359 patients of the AGIMM group. Am J Hematol. 2016;91:681–6.

  51. 51.

    Guglielmelli P, Lasho TL, Rotunno G, Score J, Mannarelli C, Pancrazzi A, et al. The number of prognostically detrimental mutations and prognosis in primary myelofibrosis: an international study of 797 patients. Leukemia. 2014;28:1804–10.

  52. 52.

    Tefferi A, Lasho TL, Finke CM, Elala Y, Hanson CA, Ketterling RP, et al. Targeted deep sequencing in primary myelofibrosis. Blood Adv. 2016;1:105–11.

  53. 53.

    Cervantes F, Dupriez B, Pereira A, Passamonti F, Reilly JT, Morra E, et al. New prognostic scoring system for primary myelofibrosis based on a study of the International Working Group for Myelofibrosis Research and Treatment. Blood. 2009;113:2895–901.

  54. 54.

    Passamonti F, Cervantes F, Vannucchi AM, Morra E, Rumi E, Pereira A, et al. A dynamic prognostic model to predict survival in primary myelofibrosis: a study by the IWG-MRT (International Working Group for Myeloproliferative Neoplasms Research and Treatment). Blood. 2010;115:1703–8.

  55. 55.

    Gangat N, Caramazza D, Vaidya R, George G, Begna K, Schwager S, et al. DIPSS plus: a refined Dynamic International Prognostic Scoring System for primary myelofibrosis that incorporates prognostic information from karyotype, platelet count, and transfusion status. J Clin Oncol. 2011;29:392–7.

  56. 56.

    Tefferi A, Guglielmelli P, Lasho TL, Rotunno G, Finke C, Mannarelli C, et al. CALR and ASXL1 mutations-based molecular prognostication in primary myelofibrosis: an international study of 570 patients. Leukemia. 2014;28:1494–500.

  57. 57.

    Guglielmelli P, Lasho TL, Rotunno G, Mudireddy M, Mannarelli C, Nicolosi M, et al. MIPSS70: mutation-enhanced international prognostic score system for transplantation-age patients with primary myelofibrosis. J Clin Oncol. 2017;36:310.

  58. 58.

    Caramazza D, Begna KH, Gangat N, Vaidya R, Siragusa S, Van Dyke DL, et al. Refined cytogenetic-risk categorization for overall and leukemia-free survival in primary myelofibrosis: a single center study of 433 patients. Leukemia. 2011;25:82–8.

  59. 59.

    Tefferi A, Nicolosi M, Mudireddy M, Lasho TL, Gangat N, Begna KH, et al. Revised cytogenetic risk stratification in primary myelofibrosis: analysis based on 1002 informative patients. Leukemia. 2018;32:1189–99.

  60. 60.

    Nicolosi M, Mudireddy M, Lasho TL, Hanson CA, Ketterling RP, Gangat N, et al. Sex and degree of severity influence the prognostic impact of anemia in primary myelofibrosis: analysis based on 1109 consecutive patients. Leukemia. 2018;32:1254–8.

  61. 61.

    Tefferi A, Guglielmelli P, Lasho TL, Gangat N, Ketterling RP, Pardanani A, et al. MIPSS70 + Version 2.0: mutation and karyotype-enhanced International Prognostic Scoring System for primary myelofibrosis. J Clin Oncol. 2018;36:1769.

  62. 62.

    Tefferi A, Guglielmelli P, Nicolosi M, Mannelli F, Mudireddy M, Bartalucci N, et al. GIPSS: genetically inspired prognostic scoring system for primary myelofibrosis. Leukemia. 2018;32:1631.

  63. 63.

    Kuykendall AT, Talati C, Padron E, Sweet K, Sallman D, List AF, et al. Genetically inspired prognostic scoring system (GIPSS) outperforms dynamic International Prognostic Scoring System (DIPSS) in myelofibrosis patients. Am J Hematol. 2019;94:87–92.

  64. 64.

    Hernandez-Boluda JC, Pereira A, Gomez M, Boque C, Ferrer-Marin F, Raya JM, et al. The International Prognostic Scoring System does not accurately discriminate different risk categories in patients with post-essential thrombocythemia and post-polycythemia vera myelofibrosis. Haematologica. 2014;99:e55–7.

  65. 65.

    Masarova L, Bose P, Daver N, Pemmaraju N, Newberry KJ, Manshouri T, et al. Patients with post-essential thrombocythemia and post-polycythemia vera differ from patients with primary myelofibrosis. Leuk Res. 2017;59:110–6.

  66. 66.

    Cervantes F, Dupriez B, Passamonti F, Vannucchi AM, Morra E, Reilly JT, et al. Improving survival trends in primary myelofibrosis: an international study. J Clin Oncol. 2012;30:2981–7.

  67. 67.

    Szuber N, Mudireddy M, Nicolosi M, Penna D, Vallapureddy RR, Lasho TL, et al. 3023 Mayo Clinic patients with myeloproliferative neoplasms: risk-stratified comparison of survival and outcomes data among disease subgroups. Mayo Clin Proc. 2019;94:599–610.

  68. 68.

    Hernandez-Boluda JC, Pereira A, Correa JG, Alvarez-Larran A, Ferrer-Marin F, Raya JM, et al. Performance of the myelofibrosis secondary to PV and ET-prognostic model (MYSEC-PM) in a series of 262 patients from the Spanish registry of myelofibrosis. Leukemia. 2018;32:553–5.

  69. 69.

    Barbui T, Tefferi A, Vannucchi AM, Passamonti F, Silver RT, Hoffman R, et al. Philadelphia chromosome-negative classical myeloproliferative neoplasms: revised management recommendations from European LeukemiaNet. Leukemia. 2018;32:1057.

  70. 70.

    Mesa R, Jamieson C, Bhatia R, Deininger MW, Gerds AT, Gojo I, et al. Myeloproliferative neoplasms, version 2.2017, NCCN clinical practice guidelines in oncology. J Natl Compr Canc Netw. 2016;14:1572–611.

  71. 71.

    Kroger NM, Deeg JH, Olavarria E, Niederwieser D, Bacigalupo A, Barbui T, et al. Indication and management of allogeneic stem cell transplantation in primary myelofibrosis: a consensus process by an EBMT/ELN international working group. Leukemia. 2015;29:2126.

  72. 72.

    Ali H, Aldoss I, Yang D, Mokhtari S, Khaled S, Aribi A, et al. MIPSS70 + v2.0 predicts long-term survival in myelofibrosis after allogeneic HCT with the Flu/Mel conditioning regimen. Blood Adv. 2019;3:83–95.

  73. 73.

    Gagelmann N, Ditschkowski M, Bogdanov R, Bredin S, Robin M, Cassinat B, et al. Comprehensive clinical-molecular transplant scoring system for myelofibrosis undergoing stem cell transplantation. Blood. 2019;133:2233–42.

  74. 74.

    Patel KP, Newberry KJ, Luthra R, Jabbour E, Pierce S, Cortes J, et al. Correlation of mutation profile and response in patients with myelofibrosis treated with ruxolitinib. Blood. 2015;126:790–7.

  75. 75.

    Newberry KJ, Patel K, Masarova L, Luthra R, Manshouri T, Jabbour E, et al. Clonal evolution and outcomes in myelofibrosis after ruxolitinib discontinuation. Blood. 2017;130:1125–31.

  76. 76.

    Rampal R, Ahn J, Abdel-Wahab O, Nahas M, Wang K, Lipson D, et al. Genomic and functional analysis of leukemic transformation of myeloproliferative neoplasms. Proc Natl Acad Sci USA. 2014;111:E5401–10.

  77. 77.

    Cancer Genome Atlas Research Network. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N Engl J Med. 2013;368:2059–74.

  78. 78.

    Lindsley RC, Mar BG, Mazzola E, Grauman PV, Shareef S, Allen SL, et al. Acute myeloid leukemia ontogeny is defined by distinct somatic mutations. Blood. 2015;125:1367–76.

  79. 79.

    Theocharides A, Boissinot M, Girodon F, Garand R, Teo SS, Lippert E, et al. Leukemic blasts in transformed JAK2-V617F-positive myeloproliferative disorders are frequently negative for the JAK2-V617F mutation. Blood. 2007;110:375–9.

  80. 80.

    Beer PA, Delhommeau F, LeCouedic JP, Dawson MA, Chen E, Bareford D, et al. Two routes to leukemic transformation after a JAK2 mutation-positive myeloproliferative neoplasm. Blood. 2010;115:2891–900.

  81. 81.

    Green A, Beer P. Somatic mutations of IDH1 and IDH2 in the leukemic transformation of myeloproliferative neoplasms. N Engl J Med. 2010;362:369–70.

  82. 82.

    Harutyunyan A, Klampfl T, Cazzola M, Kralovics R. P53 lesions in leukemic transformation. N Engl J Med. 2011;364:488–90.

  83. 83.

    Stein EM, DiNardo CD, Pollyea DA, Fathi AT, Roboz GJ, Altman JK, et al. Enasidenib in mutant IDH2 relapsed or refractory acute myeloid leukemia. Blood. 2017;130:722–31.

  84. 84.

    DiNardo CD, Stein EM, de Botton S, Roboz GJ, Altman JK, Mims AS, et al. Durable remissions with ivosidenib in IDH1-mutated relapsed or refractory AML. N Engl J Med. 2018;378:2386–98.

  85. 85.

    Welch JS, Petti AA, Miller CA, Fronick CC, O’Laughlin M, Fulton RS, et al. TP53 and decitabine in acute myeloid leukemia and myelodysplastic syndromes. N Engl J Med. 2016;375:2023–36.

  86. 86.

    Bose P, Verstovsek S, Naqvi K, Jabbour EJ, DiNardo CD, Alvarado Y et al. Phase 1/2 study of ruxolitinib (RUX) plus decitabine (DAC) in patients (PTS) with post-myeloproliferative neoplasm acute myeloid leukemia (post-MPN AML). Haemasphere. 2019;3(suppl 1):PF673.

  87. 87.

    Rampal RK, Mascarenhas J, Kosiorek HE, Bhave R, Hexner EO, Wang ES, et al. Efficacy of combined ruxolitinib and decitabine in patients with accelerated and blast-phase myeloproliferative neoplasms: results of a phase II study (MPN-RC 109 trial). Blood. 2018;132:3027.

  88. 88.

    Seiler M, Yoshimi A, Darman R, Chan B, Keaney G, Thomas M, et al. H3B-8800, an orally available small-molecule splicing modulator, induces lethality in spliceosome-mutant cancers. Nat Med. 2018;24:497–504.

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Acknowledgements

This work was supported, in part, by the MD Anderson Cancer Center support grant P30 CA016672 from the National Cancer Institute (National Institutes of Health).

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Correspondence to Srdan Verstovsek.

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Bose, P., Verstovsek, S. Mutational profiling in myelofibrosis: implications for management. Int J Hematol 111, 192–199 (2020). https://doi.org/10.1007/s12185-019-02758-z

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Keywords

  • Mutations
  • Myelofibrosis
  • JAK–STAT
  • Epigenetic
  • Splicing