Molecular predictors of survival in patients with myeloproliferative neoplasm-blast Phase (MPN-BP) treated with venetoclax and decitabine
Abstract
Abstract Background. MPN-BP after chronic phase MPN is characterized by dismal outcome, with OS <6 mo. Owing to disappointing results of intensive chemotherapy in MPN-BP, there is increasing interest for non-intensive regimens, such as venetoclax (VEN) plus hypomethylating (HMA) agents, successfully used in unfit, untreated, as well as relapsed/refractory, pts with de-novo AML. Genetic risk score specific for de-novo AML receiving VEN/HMA were developed: ELN24/mPRS (includes TP53, FLT3-ITD, NRAS and KRAS mut; Dohner H, Blood 2024); ELN24-refined (DDX41, NPM1, IDH1, IDH22, N/KRAS, PTPN11, FLT3-ITD, TP53 mut; Lachowiez CA, Blood 2024); Mayo Genetic Risk Model (adverse karyotype, KMT2Ar, TP53mut, KRASmut, absence of IDH2mut; Gangat N, AJH 2025). However, the cytogenetic and molecular landscape of MPN-BP is highly heterogeneous and usually lacks abnormalities typical of de-novo AML. Aim Using data from ENABLE, a phase 2 trial of VEN and decitabine in MPN-BP (submitted to ASH2025, AM Vannucchi et al), we aimed to define a prognostic risk profile associated with OS. Patients and Methods. The trial enrolled 101 pts. DNA was obtained from purified blasts at diagnosis. Mutations in driver and a 40-myeloid gene panel were determined by PCR assays and NGS sequencing, respectively. Karyotype abnormalities were classified according to Tefferi A (JCO 2018;1169) and ELN22 (Dohner H, Blood 2022). Results Karyotype and molecular information were available in 80 patients, of which 72 (90.0%) had a driver mutation (JAK2 73.8%, CALR 12.5%, MPL 3.7%) and 93.8% had >1 (median, 4) myeloid gene mutations. An abnormal karyotype was found in 59% of the pts, classified as adverse in 40 (50%) according to Tefferi and 22 (27.5%) according to ELN22. We first evaluated the performance of available predictive scores. We found that either ELN17 (p=0.82) and ELN22 (p=0.10) score failed to accurately predict outcome, as it could be anticipated since they were originally developed in the settings of intensive regimens for de-novo AML pts. On the other hand, ELN24/mPRS (p=0.05) better separated the favorable category (54% of the pts; median OS, 20.7mo) from the intermediate (17%, OS 8.9mo) and the adverse one (29%; OS 5.1mo); the latter 2 categories, however, were almost superimposable (p=0.35). In ELN24-ref system (p=0.12), OS was not reached for pts in favorable category (9% of the pts), compared to 14mo and 10mo in intermediate (57%) and adverse (24%), respectively, that again did not differ each to the other (p=0.10). Conversely, the Mayo Genetic Risk Model score failed to discriminate risk categories (p=0.88), possibly because of the lack of karyotype abnormalities typical of de-novo AML in our MPN-BP patients, except for chr17 involvement. In univariable analysis, OS was predicted by achievement of CR/PR within 2 cycles (55% of the pts; p=0.02), SRSF2mut (25%; p=0.048), U2AF1mut (7.5%; p<0.001), EZH2mut (16.3; p=0.047) and TP53mut (28.8%; p=0.01) irrespective of being multihit (17.5%). High molecular risk mutations (Guglielmelli P, JCO 2018; 36:301) (p=0.24) and adverse karyotype, according to either Tefferi (p=0.32) and ELN22 (p=0.72), were not significant. In multivariable analysis, the factors that maintained significance were SRSF2mut (HR 3.0; 95%CI 1.4-6.3; p=0.004), U2AF1mut (HR 4.2, 1.6-10.7; p=0.003) and TP53mut (HR2.7, 1.3-5.3; p=0.005). We attributed 2-points to SRSF2mut and U2AF1mut and 1-point to TP53mut, and obtained 3 survival curves in Kaplan-Meier analysis (p=0.006). In the favorable category (point 0; n=15 pts, 18.8%) OS was 28.1 mo (95%CI, 16.1-28.5) compared to 11.5mo (6.3-16.7) in the intermediate (point 1; n= 35 pts, 43.8%) and 4.4mo (0.1-11.5) in the adverse (n=30 pts, 37.4%) risk category. By using the favorable as reference category, the HR was 2.4 (95%CI, 1.0-7.1; p=0.049) and 2.7 (95%CI, 5.4-15.9; p=0.004) for intermediate and adverse category, respectively. With C-statistical analysis, the area under the curve was 0.71 for the 3-gene model, versus 0.60 for ELN22, 0.65 for ELN24 and 0.64 for ELN-ref. Corresponding concordance index (CI) value were 0.68 compared to 0.56, 0.59 and 0.57. Conclusions A 3-gene signature, including SRSF2, U2AF1 and TP53, was able to identify prognostically different risk categories among MPN-BP pts treated with VEN/DEC, resulting more accurate than genetic risk models specifically developed for de-novo AML pts. These findings warrant confirmation in independent series. [On behalf of ENABLE investigators].
Article Details
Authors (19)
Paola Guglielmelli
3Center for Research and Innovation of Myeloproliferative Neoplasms, AOU Careggi, University of Florence, Florence, Italy
Francesca Crupi
1SOD Ematologia, Università di Firenze, AOU Careggi, Firenze, Italy
Mirko Lomi
1CRIMM, Hematology Unit, AOU Careggi, University of Florence, Florence, Italy
Francesco Mannelli
1SOD Ematologia, Università di Firenze, AOU Careggi, Firenze, Italy
Jessica Caroprese
1CRIMM, Hematology Unit, AOU Careggi, University of Florence, Florence, Italy
Niccolò Bartalucci
1CRIMM, Hematology Unit, AOU Careggi, University of Florence, Florence, Italy
Stefano Soddu
2GIMEMA Foundation, Rome, Italy
Chiara Maccari
1CRIMM, Hematology Unit, AOU Careggi, University of Florence, Florence, Italy
Alessio Enderti
1CRIMM, Hematology Unit, AOU Careggi, University of Florence, Florence, Italy
Daniele Colazzo
1CRIMM, Hematology Unit, AOU Careggi, University of Florence, Florence, Italy
leonardo Signori
1CRIMM, Hematology Unit, AOU Careggi, University of Florence, Florence, Italy
Giada Rotunno
3Center for Research and Innovation of Myeloproliferative Neoplasms, AOU Careggi, University of Florence, Florence, Italy
Alfonso Piciocchi
4GIMEMA, Rome, Italy
Giuseppe Gaetano Loscocco
2University of Florence, Florence, Italy
Sara Bianchini
1CRIMM, Hematology Unit, AOU Careggi, University of Florence, Florence, Italy
Elena Nacca
1CRIMM, Hematology Unit, AOU Careggi, University of Florence, Florence, Italy
Paola Fazi
4GIMEMA, Rome, Italy
Marco Vignetti
1Italian Group for Adult Hematologic Diseases (GIMEMA), Data Center and Health Outcomes Research Unit, Rome, Italy
Alessandro Vannucchi
5Center Research and Innovation of Myeloproliferative Neoplasms, Dipartimento di Medicina Sperimentale e Clinica, Azienda Ospedaliero Universitaria Careggi, University of Florence, Florence, Italy