Session: 637. Myelodysplastic Syndromes—Clinical Studies: Poster III
Hematology Disease Topics & Pathways:
Diseases, MDS, Myeloid Malignancies
All untreated MDS patients diagnosed over a 3-year duration who underwent NGS were selected. Overall survival was calculated from diagnosis to death/ last follow-up. Univariate (UVA) Cox proportional hazards regression was used to identify any association of variables with outcome followed by multivariate modeling (MVA) (p-value 0.200 cutoff).
Of 509 patients, 94 (19%) had SF3B1mut: 59 men, 35 women; median age: 74 (39-92) years. Baseline characteristics: Table 1. Compared to SF3B1wt, SF3B1mut had a significantly higher median age (74 vs. 70, p=0.0008), MCV (105 vs. 96, p<0.0001), platelet count (188 vs. 78, p<0.0001) and lower BM blasts (2 vs. 4, p=0.003). SF3B1mut were less frequently therapy-related (18% vs. 34%, p=0.002), significantly enriched in R-IPSS VL/L and WHO MDS-RS and MDS with iso del(5q). Majority (~66%) had concomitant mutations: TET2 (25%), DNMT3A (21%), RUNX1 (15%), TP53 (10%), ASXL1 (7%), BCOR (4%), IDH1/2 (4%), SRSF2 (3%), RAS (3%) and EZH2 (3%) (Fig 1B). ~10% showed complex karyotype (CK). Among SF3B1mut, hotspot K700E mutation was seen in 55 (~60%). Non K700E mutations (n=39, 40%) frequently involved codons: H662, K666 and R625, seen in 8 patients each (Fig 1A). SF3B1 K700E showed a higher median RS% (50% vs. 34%; p=0.038), ANC (2.4 vs. 1.8, p=0.005) and a trend for higher platelet (196 vs. 124, p=0.05). SF3B1mut were less likely MDS-EB than non-K700E (22% vs. 49%, p=0.008). All 4 SF3B1mut patients that fit WHO criteria for MDS with isolated del(5q) had K700E (Table). The frequency of RUNX1 mutation was significantly higher in non-K700E cases (26% vs. 7.3%, p=0.012); mutations in BCOR (p=0.02), IDH2 (p=0.07) and SRSF2 (p=0.07) were exclusively noted in non-K700E cases (Fig 1C). There was no significant difference in TP53mut or CHIP-associated mutations DNMT3A, ASXL1 and TET2 or SF3B1 VAF. There was no significant differences in diploid vs. CK. However, K700E had lower CCCS categories (0/1, n=39; 2/3/4, n=10 vs. 0/1, n=19; 2/3/4, n=17); p=0.011).
Majority were treated with HMA [16/17 (94%) K700E; 15/19 (79%) non-K700, 217/ 277 (78%) SF3B1wt]. SF3B1mut had better OS than SF3B1wt in all MDS (NR vs. 25.2 months, p=0.0003; fig 1D), low-grade MDS (NR vs. 41.3 months, p=0.0015; fig 1E) and MDS-RS (NR vs. 22.3 months, p=0.0004; fig 1F). Four (7.3%) K700E died compared to 9 (23%; p=0.036) non-K700E. The outcome of non-K700E was similar to SF3B1wt, in all MDS, low-grade MDS and MDS-RS (median OS, NR for both; p=0.021). By UVA, the following associated with worse outcome: higher BM blasts, lower hemoglobin, platelet and MCV, prior chemo-radiation, CK, higher R-IPSS, absence of mutations in SF3B1 K700E, TET2 and U2AF1 and presence of TP53mut. Non-K700E did not associate with OS. By MVA, lower hemoglobin, higher R-IPSS, absence of SF3B1 K700E and presence of TP53mut were independent predictors of worse OS. Within MDS-RS categories, independent prognostic factors of worse OS included lower platelet, presence of mutations in non-K700E SF3B1mut, ASXL1, SRSF2 and TP53. TP53mut/CK was seen in 10% SF3B1mut MDS. No survival differences were noted between SF3B1mut with or without TP53mut/CK (median OS, NR) and SF3B1wt without TP53mut/CK (44.3 months), but TP53mut/CK with SF3B1wt MDS had a worse outcome (median OS, 12.9 months, HR 1.46, p=0.001; fig 1G). Same findings were noted within low-grade MDS and MDS-RS, suggesting SF3B1mut negates the poor prognostic effect of TP53mut/CK.
About 40% SF3B1mut MDS show non K700E mutations. K700E and non K700E SF3B1mut MDS show distinct clinical and mutational profiles, with K700E showing a significantly better OS compared to non K700E and SF3B1wt. Only SF3B1 K700E independently predicted for worse OS in MDS.
Disclosures: Sasaki: Novartis: Consultancy, Research Funding; Otsuka: Honoraria; Daiichi Sankyo: Consultancy; Pfizer Japan: Consultancy. Jabbour: Genentech: Other: Advisory role, Research Funding; BMS: Other: Advisory role, Research Funding; Pfizer: Other: Advisory role, Research Funding; AbbVie: Other: Advisory role, Research Funding; Takeda: Other: Advisory role, Research Funding; Adaptive Biotechnologies: Other: Advisory role, Research Funding; Amgen: Other: Advisory role, Research Funding. Kantarjian: Amgen: Honoraria, Research Funding; Ascentage: Research Funding; BMS: Research Funding; Daiichi-Sankyo: Honoraria, Research Funding; Immunogen: Research Funding; Jazz: Research Funding; Novartis: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; Sanofi: Research Funding; Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive biotechnologies: Honoraria; Aptitute Health: Honoraria; BioAscend: Honoraria; Delta Fly: Honoraria; Janssen: Honoraria; Oxford Biomedical: Honoraria; Abbvie: Honoraria, Research Funding. Garcia-Manero: Astex Pharmaceuticals: Consultancy, Honoraria, Research Funding; AbbVie: Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Merck: Research Funding; Onconova: Research Funding; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Helsinn Therapeutics: Consultancy, Honoraria, Research Funding; Acceleron Pharmaceuticals: Consultancy, Honoraria; H3 Biomedicine: Research Funding; Amphivena Therapeutics: Research Funding; Novartis: Research Funding; Jazz Pharmaceuticals: Consultancy.
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