Session: 636. Myelodysplastic Syndromes—Basic and Translational Studies: Poster III
Hematology Disease Topics & Pathways:
Diseases, MDS, Myeloid Malignancies
We collected molecular and clinical information of 3561 patients with MN from Cleveland Clinic and publicly shared data. Results of targeted deep sequencing of 176 MDS/ AML genes were included. We applied an in-house variant allele frequency (VAF) based bioanalytic method to resolve clonal hierarchy. VAF (adjusted for copy number and zygosity) was used to classify the mutations into dominant (if a cutoff of at least 5% difference between VAFs existed), secondary (any subsequent subclonal hit) and codominant hits (<5% difference of VAFs between 2 hits).
SF3B1MT were detected in 9% of patients (n=335): 140 were SF3B1DOM (42%), 121 were SF3B1SEC (36%) and 74 were codominant (SF3B1COD, 22%). Comparison of SF3B1MT VAFs among the 3 groups showed no significant difference (40 vs 39 vs 44%, P= .6). Due to lack of distinct partition, we delved into the implications of SF3B1COD on mutational stability, disease phenotypes, molecular associations and overall survival (OS) as compared to the other 2 configurations. Serially-collected samples (n=21) showed clear scenarios of dominant clones remaining stable or switching to secondary due to impending acquisition of other hits or secondary clones remaining as such but denoted an ambivalent framework of codominant clones with “sweeping” features. Cases with SF3B1COD had a trend of OS similar to that of SF3B1SEC (median OS: 18 vs 15.9 mo.) and as such a poorer outcome compared to that of SF3B1DOM (39.8 mo.; P= .02). Moreover, the mutational profile of SF3B1COD vs SF3B1DOM was partially similar to that of SF3B1SEC vs. SF3B1DOM with significantly higher odd ratios for DNMT3A (P< .0001), ASXL1, FLT3, RUNX1, TET2 (P≤ .05 for each). No variant morphologic features were observed when comparing SF3B1COD to the other 2 groups. By virtue, we strictly compared only cases with SF3B1DOM and SF3B1SEC, further supported by our single cell analysis (n=5), to show an unambiguous distinction between these two statii. Mutational burden analysis revealed that SF3B1DOM patients had a fewer number of mutations than those with SF3B1SEC (median 1.0 vs 2.6). SF3B1DOM was mostly detected in patients with a normocellular bone marrow as compared to SF3B1SEC (46 vs 29%, P= .02) and had a lower proportion of multidysplastic myeloid cells (29 vs 53%, P= .01). On the other side, SF3B1SEC were often present in the context of bilineage dysplasia (47vs. 26%, P= .02). Focused morphologic analysis revealed that SF3B1DOM cases were significantly associated with a higher RS% (median 37 vs 3%, P= .002; frequency of RS ≥15%: 77 vs 44%, P= .003) with higher VAF% significantly correlating with higher RS%. Patients with SF3B1SEC had shorter OS than those with SF3B1DOM (15.9 vs 39.7 mo., P< .0001). Even by dichotomizing according to VAF, the median OS of cases with VAF>40% was significantly shorter than those with VAF<20% (14.4 vs 33.9 mo.; P= .001) and between 20% and 40% (39.3 mo.). When the VAF of SF3B1SEC was >40%, the OS was shortened compared to SF3B1DOM (31 vs 11.6 mo., P= .001) and similarly when it laid between 20% and 40% (49.7 vs 25.6 mo., P= .01) suggesting a strong impact of associated hits. In SF3B1SEC, univariate analyses showed significantly higher odds of hits in RUNX1 (43 vs 19%, P< .0001), TET2 (29 vs 11%, P= .0005), FLT3 (22 vs 11%, P= .02), DNMT3A (20 vs 7%, P= .004), ASXL1 (16 vs 5%, P= .06), BCOR/L1 (17 vs 5%, P= .005), IDH1/2 (11 vs 2%, P= .008), CBL (8 vs 1%, P= .009) and CEBPA (7 vs 2%, P= .04) compared to SF3B1DOM. Interestingly, cases with co-existing TET2 mutations had a marked decrease in OS in SF3B1SEC vs SF3B1DOM(10.1 vs 96.1 mo., P= .02) suggesting that the mutational ranking in a disease triggered by SF3B1MT can be skewed by stronger hits.
In sum, our study suggests that molecular ranking in the context of SF3B1 clonal configuration is a key factor diverting the clinical and phenotypic trajectories of patients with MN and SF3B1MT.
Disclosures: Carraway: Abbvie: Other: Independent Advisory Committe (IRC); Takeda: Other: Independent Advisory Committe (IRC); Stemline: Consultancy, Speakers Bureau; Jazz: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau; BMS: Consultancy, Other: Research support, Speakers Bureau; ASTEX: Other: Independent Advisory Committe (IRC). Sekeres: Pfizer: Consultancy; BMS: Consultancy; Takeda/Millenium: Consultancy. Maciejewski: Alexion, BMS: Speakers Bureau; Novartis, Roche: Consultancy, Honoraria.
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