Methylation-based prediction of myelodysplastic syndrome survival outcomes.

Abstract

7058 Background: Myelodysplastic syndromes (MDS) are a heterogeneous group of myeloid malignancies associated with a myriad of deleterious outcomes and a 5-year relative survival of 37%. MDS risk stratification is key for optimal treatment decisions. DNA methylation is associated with MDS biology due to frequent somatic mutations in genes (i.e. TET2, DNMT3A, IDH1, IDH2, and WT1) that affect DNA methylation. We hypothesized that methylation-based markers may help stratify risk and improve IPSS-R (the Revised International Prognostic Scoring System). Here, we evaluated the potential of both Bone Marrow (BM) Whole-genome Bisulfite Sequencing (WGBS) and Serum-based Targeted Methylation (TM) Sequencing to predict survival of MDS patients. Methods: We conducted paired BM WGBS and Serum-based TM sequencing on a cohort of 127 patients with MDS (N = 104) and secondary AML (N = 23) treated at the Columbia University Medical Center. We categorized patients based on an overall survival of > 3 (“long”, N = 50) or < 3 years (“short”, N = 77). We then identified differentially methylated regions (DMRs) differing between long and short survivor groups, and analyzed the biological pathways and functions enriched in these regions. To assess survival association, we trained a random forest classifier on principal components (“methylation classifier”) on the methylation fractions from a subset of 96 Serum and 98 BM MDS patient samples to predict long vs. short survival, and compared this against a logistic regression IPSS-R model. We optimized the hyperparameters and assessed classifier performance using six-fold nested cross-validation. Finally, we conducted a multivariable cox regression with predicted scores from the methylation classifier, IPSS-R scores (recalculated at sample collection), age, and gender. Results: We identified a total of 7,742 DMRs in the BM WGBS and 14,093 DMRs in the Serum TM as significantly different between long and short survivor groups. Signaling pathways for calcium, cAMP, MAPK, Rap1, and PI3K-Akt were significantly enriched in DMRs. We also identified a previously-reported CpG island hypermethylation signature associated with AML progression in BM and Serum. The methylation classifier achieved a comparable AUROC compared to IPSS-R logistic regression for both BM WGBS (0.80 vs 0.78) and Serum TM (0.77 vs 0.73) samples. Multivariable Cox regression demonstrated that both predicted scores from the methylation classifier (Serum p =0.002; BM p =0.016) and IPSS-R scores (Serum p =0.003; BM p =0.004) are significant predictors of survival. Conclusions: We demonstrated methylation-based sequencing represents a promising new tool for MDS patient risk stratification. As IPSS-R relies on bone marrow aspirates, the Serum-based TM assay offers a less-invasive method for MDS risk stratification.