Molecular Characterization Of Myelofibrosis Patients With Cytopenia Treated With Pomalidomide: Results From The Mpnsg 01-09 Study
Authors: Stegelmann Frank , Laaths Maximilian , Reiter Andreas , Jost Edgar , Griesshammer Martin , Gattermann Norbert , Hebart Holger , Waller Cornelius F. , Schafhausen Philippe , Platzbecker Uwe , Hochhaus Andreas , Verbeek Walter , Blau Igor W. , Blersch Carmen , Kuhn Susanne , Döhner Hartmut , Schlenk Richard F. , Döhner Konstanze 
Published: October 2019

Abstract

Background
In recent phase-I/II studies, pomalidomide (POM) has shown activity in myelofibrosis (MF) patients (pts) with anemia and/or thrombocytopenia. In the first cohort of the German multicenter MPNSG 01-09 phase-II trial, 38 MF pts were treated with POM 2 mg QD +/- prednisolone (PRED); 34% responded according to IWG-MRT criteria or became RBC-transfusion independent (Schlenk et al., ASH 2012). Additional 58 MF pts were treated in the second study cohort with POM 0.5 mg QD +/- PRED. Main inclusion criteria were age >50y, RBC-transfusion-dependency or Hb <10 g/dL, and/or PLT <50 /nL. The study population (n=96) represents advanced disease: 24% high-risk pts, 65% intermediate-II risk pts, and 11% intermediate-I risk pts according to the DIPS score (DIPSS).

Aims
To explore the presence of copy number alterations (CNAs), uniparental disomies (UPDs) and MPN-related gene mutations in the 01-09 study cohort and to correlate genetic parameters with treatment response.

Methods
Affymetrix 6.0 SNP arrays were used for genome-wide screening of CNAs and UPDs in 91% (87/96) of pts. Frequently mutated genes were analyzed in all pts using PCR-based techniques and sequence analysis of coding exons: JAK2 V617F, MPL W515L, ASXL1 (exon 12), EZH2 (exon 2-20), IDH1/2 (exons 4), SRSF2 (exon 1-2), and TP53(exon 4-10).

Results
In total, 78 CNAs were identified by SNP array analysis. The overall frequency of CNAs was 52% (45/87 pts); 24% (21 pts) showed ≥2 CNAs, while 7% (6 pts) had a complex genotype defined by ≥3 genomic aberrations. Recurrent large (>5 Mb) gains were trisomy 8 (7%; n=6), gain 1q, and trisomy 9 (5% each; n=4), whereas recurrent large losses were identified in 20q (11%; n=10), 5q (8%; n=7), 13q (7%; n=6), 7q/7 (6%; n=5), and 12p/12 (2%; n=2). Moreover, 20% (17/87) of pts showed 19 informative micro-deletions (<5 Mb).
Large UPDs (>10 Mb) affecting a terminal end of the chromosome were present in 32% (28/87) of pts. The most frequent UPDs occurred in 9p including JAK2 (17%; n=15). Other recurrent UPDs mapped to 1p (5%; n=4), 4q, and 7q (2% each; n=2). UPDs in 9p were associated with JAK2 V617F in all pts, whereas 75% (3/4) of pts with UPD in 1p were MPLW515L mutated.
Mutations in JAK2 (V617F) and MPL (W515L) were present in 55% (53/96) and 6% (6/96) of pts, respectively. The mutation frequencies for the remaining genes were 30% (ASXL1; n=29/96), 9% (SRSF2; n=9/96), 5% (EZH2; n=5/96), 2% (TP53; n=2/96), and 1% (IDH2; n=1/96). Taken together, at least one mutation was found in 79% (76/96) of pts, whereas 21% (20/96) of pts lacked any of these mutations; 28% (27/96) of pts showed ≥2 concurrent mutations.
To evaluate genetic differences and predictive factors, pts were separated into a responder (R, n=23) and a non-responder (Non-R, n=73) group. Regarding DIPSS, Non-R pts were not associated with higher risk compared to R pts: 27% (20/73) high risk vs. 17% (4/23) (p=0.334), 61% (44/73) intermediate-II risk vs. 79% (18/23), and 12% (9/73) intermediate-I vs. 4% (1/23) (p=0.275). However, the overall frequency of CNAs was in trend higher in the Non-R group: 56% vs. 39% (p=0.159). Since the total number of genomic losses was similarly distributed (27% vs. 29%), the difference was mainly due to the higher frequency of large genomic gains/trisomies: 4% (R) vs. 22% (Non-R) (p=0.083). UPDs were similar frequent in R and Non-R pts (26% vs. 34%) (p=0.466).
The total number of gene mutations was not different between both groups (n=25 in 23 R pts vs. n=77 in 73 Non-R pts) (p=0.475). However, genetic alterations being associated with unfavourable outcome were enriched in the Non-R group: ASXL1 mutation (39% vs. 22%), EZH2 mutation (5% vs. 0%), loss in 5q (30% vs. 4%), trisomy 8 (9% vs. 0%), 12p / ETV6 deletion (6% vs. 0%), 17p deletion / TP53 mutation (3% vs. 0%), and complex genotype (7% vs. 0%). Taken together, adverse genetic alterations were significantly more frequent in Non-R pts compared to R pts: 48% (35/73) vs. 22% (5/23) (p=0.026). Of note, adverse genetic alterations indicated high risk according to DIPSS in no more than 50% (12/24) of the pts.

Conclusion
Our study on a well-defined patient cohort with advanced MF revealed a high frequency of genetic alterations reflecting the molecular complexity of the disease. Pts with adverse genetic alterations identified by SNP-array and mutation analyses were not sufficiently represented by DIPSS and showed inferior response to POM +/- PRED.

Disclosures:
Reiter: Sanofi: Honoraria. Gattermann:Celgene: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Platzbecker:Celgene: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Hochhaus:Novartis: Consultancy, Honoraria, Research Funding, Travel Other; BMS: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Ariad: Consultancy, Honoraria. Schlenk:Amgen: Research Funding; Pfizer: Research Funding; Novartis: Research Funding; Chugai: Research Funding; Ambit: Honoraria.