Pacilli, Annalisa

Summary Survival prediction in essential thrombocythaemia (ET) and polycythaemia vera (PV) is currently based on clinically‐derived variables; we examined the possibility of integrating genetic information for predicting survival. To this end, 906 molecularly‐annotated patients (416 Mayo Clinic; 490 University of Florence, Italy), including 502 ET and 404 PV, were recruited. Multivariable analysis identified spliceosome mutations to adversely affect overall ( SF3B1 , SRSF2 in ET and SRSF2 in PV) and myelofibrosis‐free ( U2AF1 , SF3B1 in ET) survival; TP53 mutations predicted leukaemic transformation in ET; “adverse” mutations occurred in 51 (10%) ET and 8 (2%) PV patients. We confirmed the independent survival effect of adverse mutations [hazard ratio (HR) 2·4, 95% CI 1·6–3·5], age >60 years (6·6, 4·6–9·7), male sex (1·8, 1·3–2·4) and leukocytosis ≥11 × 10 9 /l (1·6, 1·1–2·2), in ET, and adverse mutations (7·8, 3·1–17·0), age >67 years (5·4, 3·6–8·1), leukocytosis ≥15 × 10 9 /l (2·8, 1·8–4·2) and thrombosis history (2·0, 1·4–2·9), in PV. HR‐based risk point allocation allowed development of three‐tiered mutation‐enhanced international prognostic systems (MIPSS) which were validated in both cohorts and performance was shown to be superior to conventional scoring systems. Spliceosome mutations enhance survival prediction in ET and PV and identify patients at risk for fibrotic progression. TP53 mutations predict leukaemic transformation in ET.

Abstract Background : Survival prediction in essential thrombocythemia (ET) and polycythemia vera (PV) is currently based on clinically-derived risk variables, including age, thrombosis history and leukocyte count (Blood. 2012;120:1197; Leukemia. 2013;27:1874). We have previously reported on the prognostic contribution of mutations, in both ET and PV (Blood Adv. 2016;1:21). The current study examines the possibility of integrating genetic and clinical information for predicting overall (OS), leukemia-free (LFS) and myelofibrosis-free (MFFS) survival in ET and PV. Methods : Study patients were recruited from the Mayo Clinic, Rochester, MN, USA and the University of Florence, Florence, Italy, based on availability of next-generation sequencing (NGS)-derived mutation information. Diagnoses were according to the 2016 World Health Organization criteria (Blood. 2016;127:2391). NGS-detected coding region variants were filtered through the Exome Aggregation Consortium (ExAC) database and annotated by the Catalogue of Somatic Mutations in Cancer (COSMIC) database as mutants or variants of uncertain significance (VUS). Conventional statistics was employed for outcome analysis and assessment of model performance. Results: 906 molecularly-annotated patients (416 from Mayo and 490 from Florence), including 502 ET and 404 PV cases, were included in the current study. The Mayo/Florence cohorts included 270/232 ET (median age 57/54 years, 60%/59% females) and 146/258 PV (median age 63/58 years, 52%/44% females) patients; median follow-up was 9.9/12.9 years for ET and 10.7/12.4 years for PV; during this time 39%/38% deaths and 4.4%/6.5% leukemic and 16%/33% fibrotic progressions were documented for ET, with the corresponding figures for PV being 50%/26%, 4.8%/3% and 13%/36%. Cytogenetic information was available in 84%/63% ET and 80%/49% PV cases in the Mayo/Florence cohorts. In both Mayo and Florence cohorts, multivariable analysis of mutations identified primarily spliceosome mutations to adversely affect OS (SF3B1 and SRSF2 in ET and SRSF2 in PV) and MFFS (U2AF1 and SF3B1 in ET); in addition, TP53 mutations was associated with leukemic transformation in ET, in both patient cohorts. Other mutations with independently significant contribution, validated in one but not both cohorts, included EZH2 (OS and LFS in ET), IDH2 (OS and LFS in PV) and RUNX1 (LFS in PV and ET). For the purposes of the current study, mutations considered "adverse" for subsequent analysis and development of prognostic models required validation in both Mayo and Florence cohorts. Age-adjusted, all-inclusive multivariable analysis of genetic and clinical variables identified the following as independent risk factors for OS, in both Mayo and Florence cohorts: ET ─ SRSF2/SF3B1 mutations, age >60 years and male sex; PV ─ SRSF2 mutations, age >67 years and leukocyte count ≥11 x 109/l. In addition, multivariable analysis flagged leukocytosis in ET (Florence cohort only) and abnormal karyotype in PV (Mayo cohort only) as additional factors. Development of mutation-enhanced international prognostic systems for ET and PV In order to optimize the number of informative cases, the two Mayo and Florence databases were subsequently combined and subjected to multivariable analysis that confirmed the independent survival effect, in ET, of SRSF2/SF3B1 mutations (HR 2.8, 95% CI 1.8-4.3), age >60 years (HR 6.7, 95% CI 4.8-9.4) and male sex (HR 1.8, 95% CI 1.4-2.4) and, in PV, of SRSF2 mutations (HR 7.0, 95% CI 2.3-17.4), age >60 years (HR 5.7, 95% CI 3.3-10.1), and leukocyte count ≥11 x 109/l (HR 2.4, 95% CI 1.5-3.9); the combined analysis also flagged independent prognostic contribution from abnormal karyotype in PV (HR 2.1, 95% CI 1.1-3.6). HR-weighted risk point allocation resulted in new, mutation-enhanced 4-tiered risk models for ET (MIPSS-ET based on mutations, age and sex; figure 1a) and PV (MIPSS-PV based on mutations, karyotype, leukocyte count and age; figure 1b). Both models displayed high predictive accuracy and were internally validated by bootstrapping. The combined analysis also confirmed the impact of TP53 mutations on LFS (figure 1c) and U2AF1/SF3B1 mutations on MFFS (figure 1d), in ET. Conclusions: Spliceosome mutation information enhances survival prediction in ET and PV and identifies those at risk for fibrotic progression. TP53 mutations predict leukemic transformation in ET. Disclosures No relevant conflicts of interest to declare.

Abstract Background : Thrombosis is a characteristic feature in essential thrombocythemia (ET) and polycythemia vera (PV). Previous studies had focused on thrombotic events occurring after diagnosis and did not always distinguish between arterial and venous thrombosis. Arterial thrombosis in ET has been associated with age >60 years, JAK2 mutations, leukocyte count >11 x 109/l, history of thrombosis and cardiovascular risk factors, and venous thrombosis with male sex (Blood 2011;117:5857). In the current two-enter study, we looked for associations between both driver and other mutations, with first incidences of arterial and venous thrombosis in ET and PV, analyzed together and separately. Methods : Study patients were recruited from the Mayo Clinic, Rochester, MN, USA and the University of Florence, Florence, Italy, based on availability of next-generation sequencing-derived mutation information. Diagnoses were according to the 2016 World Health Organization criteria (Blood. 2016;127:2391). Conventional statistics was employed to examine significance of associations, with separate analysis of arterial vs venous thrombosis, occurring at any time before or after formal diagnosis of ET or PV. For the purposes of the current study, only first events were considered. Results: 906 molecularly-annotated patients (416 from Mayo and 490 from Florence), including 502 ET and 404 PV cases, were included in the current study. The Mayo/Florence cohorts included 270/232 ET (median age 57/54 years, 60%/59% females) and 146/258 PV (median age 63/58 years, 52%/44% females) patients; median follow-up was 9.9/12.9 years for ET and 10.7/12.4 years for PV. Driver mutation distribution in ET was 55% JAK2, 27% CALR, 5% MPL and 13% triple-negative. Most frequent mutations, other than JAK2/CALR/MPL, were TET2 (14%; 11% in ET and 18% in PV) and ASXL1 (13%; 13% in ET and 13% in PV). 301 (33%) patients experienced first time thrombosis, before or after diagnosis, including 152 (30%) in ET and 149 (37%) in PV (p=0.03); arterial events occurred in 174 (19%) patients, including 96 (19%) in ET and 78 (19%) in PV (p=0.9); venous events occurred in 177 (20%) patients, including 82 (16%) in ET and 95 (24%) in PV (p=0.007). The number of vascular events after diagnosis was 174 (19%) for arterial and 154 (17%) for venous thrombosis, with no significant difference between ET and PV. Associations with arterial thrombosis: In multivariable logistic regression analysis that included both ET and PV (n=906), age >60 years (23% vs 16%; OR, 1.6, 95% CI 1.1-2.2) and absence of ASXL1 and RUNX1 mutations (21% vs 9%; OR 2.6, 95% CI 1.4-4.8) were associated with arterial thrombosis; these associations remained significant (or near significant) when ET and PV were analyzed separately; in addition, JAK2 mutations in ET displayed borderline significance (p=0.05). Overall incidence of arterial events in ET was estimated at 27% in the presence of all three risk factors (i.e. older age, presence of JAK2 mutations and absence of ASXL1/RUNX1 mutations), 21% with two risk factors, 13% with one risk factor and 9% in the absence of all three risk factors (p=0.01). Associations with venous thrombosis: In multivariable analysis, including both ET and PV (n=906), JAK2 mutations (p<0.001), higher leukocyte count (p=0.03) and younger age (p=0.04) were identified as being significant. Analysis of ET patients only (n=502) identified JAK2 mutations (p<0.001; OR 2.4, 95% CI 1.4-4.1), absence of SRSF2 mutations (p=0.03) and younger age (p=0.04) as independent risk factors and in PV patients (n=404), higher leukocyte count (p=0.06). Prognostic interaction between JAK2 mutations and age: In ET, the overall frequency of venous events was 27% for young patients with JAK2 mutations vs 13% for older JAK2 mutated cases vs 10% for JAK2 unmutated young patients vs 13% for JAK2 unmutated older patients (p<0.001). The corresponding percentages for arterial events were 20%, 24%, 14% and 19%, respectively (p=0.1). Conclusions: JAK2 mutations contribute to the risk of both venous (younger patients) and arterial (young and older patients) thrombosis, in an age-dependent manner; the association with venous thrombosis might explain the higher incidence of venous thrombosis in PV, compared to ET. Additional studies are required to confirm the observed lower risk of thrombosis in patients with ASXL1, RUNX1 and SRSF2 mutations and provide insight into the underlying biological explanation. Disclosures No relevant conflicts of interest to declare.

Abstract BACKGROUND. In primary myelofibrosis (PMF), survival from time of diagnosis is predicted by the international prognostic scoring system (IPSS), and from time of referral, by the dynamic IPSS (DIPSS) or DIPSS-plus. JAK2/CALR/MPL mutational status and presence and number of other prognostically-relevant mutations (ASXL1, SRSF2, EZH2, IDH1/2) provide IPSS/DIPSS-plus independent prognostic information. The objective in the current study was to revise IPSS, by including mutation-relevant prognostic information. METHODS. The study included 986 PMF patients divided into learning (n=588) and validation (n=398) cohorts. Previously published methods were used to screen for mutations involving JAK2,MPL, CALR, EZH2, ASXL1, IDH1/2 and SRSF2. The clinical variables assessed were those previously identified as being prognostically-relevant by IPSS or DIPSS-plus. The prognostic model (MIPSS) was developed through a stepwise selection process, based on a z-test of the regression coefficients, and its relative quality was measured by means of the Akaike information criterion. RESULTS. In the Italian learning cohort (n=588),median follow-up was 3.6years (95% CI, 0.03-30.8) for alive patients and 196 (33.3%) deaths and 67 leukemic transformations were documented. IPSS risk distribution was low in 26%, intermediate-1 in 30%, intermediate-2 in 24% and high in 20%. Mutational frequencies were approximately 63% for JAK2, 20% CALR, 6% MPL, 7% EZH2, 22% ASXL1, 2.5% IDH1/2 and 9% SRSF2. Constitutional symptoms were recorded in 28.6% of patients, splenomegaly 75% (18% >10cm from LCM) and grade 3 fibrosis 21%. Overall 252 patients were evaluable for karyotype and abnormalities were detected in 35%, including 9.5% unfavorable. Univariate analysis identified the following risk factors for inferior survival: age >60 years, constitutional symptoms, hemoglobin <100g/L, leukocytes >25x109/L, platelets <200x109/L, circulating blasts 1% or greater, splenomegaly >10cm, grade 3 fibrosis, unfavorable karyotype, triple-negativity for JAK2, MPL and CALR (TN), JAK2 or MPL mutation, and mutations in ASXL1, SRSF2, EZH2 or IDH1/2. In multivariable analysis, age >60 years, constitutional symptoms, hemoglobin <100g/L, platelets <200x109/L, TN, JAK2 or MPL mutation, ASXL1 and SRSF2 mutation remained significant; these variables were subsequently assigned the following HR-weighted adverse points: 1.5, 0.5, 0.5, 1.0, 1.5, 0.5, 0.5 and 0.5, respectively. Subsequently, four risk groups with no overlap in the 95% CI of their survival curves were delineated (Figure 1A): low (score 0-0.5); Intermediate-1 (score 1-1.5); Intermediate-2 (score 2-3.5); and high (score 4 or greater). The number of patients in each risk category, median survivals and HR and 95% CI values are included in figure 1A. Akaike information criterion indicated that MIPSS performed better than IPSS in predicting survival (1611.6 vs 1649.0). Leukemia-free survival was also predicted by high (p<0.01) and intermediate 1/2 (p<0.01) risk MIPSS. In the Mayo Clinic validation cohort (n=398), median age 63 years; males 64%,median follow-up for alive patients was 7.5 years and 271 (68%) deaths and 51 (13%) leukemic transformations were documented. DIPSS-plus risk distribution was low in 13%, intermediate-1 18%, intermediate-2 37% and high 32%. Mutational frequencies were approximately 51% for JAK2, 30% CALR, 7.5% MPL, 5% EZH2, 36% ASXL1, 5.6% IDH1/2 and 13% SRSF2. MIPSS performed equally well in this cohort, as illustrated in figure 1B, which includes number of patients in each risk category with their median survival and HR and 95% CI values. Leukemia-free survival in the Mayo cohort was also predicted by high (p<0.01) and intermediate-2 (p=0.04) risk MIPSS. Patients in the Mayo cohort were fully annotated for karyotype, which was MIPSS-independent in its prognostic value for both overall (p<0.01) and leukemia-free (p<0.01) survival. CONCLUSIONS. MIPSS addresses the mutation-relevant prognostic information gap in IPSS and performs equally well in the setting of patients seen at time of diagnosis or referral. Karyotype carries MIPSS-independent prognostic value that is recognized in an alternative GIPSS prognostic model (see accompanying ASH 2014 abstract), which complements MIPSS. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Key Points More than half of patients with PV or ET harbor DNA mutations/variants other than JAK2/CALR/MPL. The presence of some of these mutations adversely affects overall, leukemia-free, or myelofibrosis-free survival.

CALR (calreticulin) trails JAK 2 as the second most mutated gene in essential thrombocythemia (ET). Mutant CALR in ET is a result of frameshift mutations, caused by exon 9 deletions or insertions; type‐1, 52‐bp deletion (p.L367fs*46), and type‐2, 5‐bp TTGTC insertion (p.K385fs*47) variants constitute more than 80% of these mutations. The current study includes a total of 1027 patients divided into test ( n = 402) and validation ( n = 625) cohorts. Among the 402 ET patients in the test cohort, 227 (57%) harbored JAK 2, 11 (3%) Myeloproliferative leukemia virus oncogene ( MPL ), and 114 (28%) CALR mutations; 12% were wild‐type for all three mutations (i.e., triple‐negative). Among the 114 patients with CALR mutations, 51 (45%) displayed type‐1 and 44 (39%) type‐2 variants; compared to mutant JAK 2, both variants were associated with higher platelet and lower hemoglobin and leukocyte counts. However, male sex was associated with only type‐1 ( P = 0.005) and younger age with type‐2 ( P = 0.001) variants. Notably, platelet count was significantly higher in type‐2 vs. type‐1 CALR ‐mutated patients ( P = 0.03) and the particular observation was validated in the validation cohort that included 111 CALR ‐mutated ET patients ( P = 0.002). These findings, coupled with the recent demonstration of preferential expression of mutant and wild‐type CALR in megakaryocytes, suggest differential effects of CALR variants on thrombopoiesis. Am. J. Hematol. 89:E121–E124, 2014. © 2014 Wiley Periodicals, Inc.