Poster abstracts
Poster number 109 submitted by Salma B. Abdelbaky
Identification of biological components and novel clinical subsets of NPM1-mutated AML using an integrated, multi-omics approach
Salma B. Abdelbaky (Molecular, Cellular, and Developmental Biology Graduate Program), Kyoko Yamaguchi (Division of Hematology, Department of Internal Medicine, The Ohio State University, Columbus, OH), Lianbu Yu (Biomedical Informatics), Ann-Kathrin Eisfeld (Division of Hematology, Department of Internal Medicine, The Ohio State University, Columbus, OH), Kevin R. Coombes (Department of Biomedical Informatics, The Ohio State University, Columbus, OH), Christopher Oakes (Department of Biomedical Informatics, The Ohio State University, Columbus, OH)
Abstract:
Acute myeloid leukemia is the most common acute leukemia in adults with a 5-year overall survival rate of only 28%. Due to a high degree of heterogeneity in biological and genetic features in AML tumor cells, current prognostic markers (including genetic aberrations) do not fully explain the ranges of phenotype and outcomes observed in AML patients. Recently, we characterized 13 DNA methylation signatures (epitypes) and a STAT hypomethylation signature (SHS) to be predictive of outcome and stable at relapse. Here, we used the integrative Multi-omics Factor Analysis (MOFA) approach to combine genetic, cytogenetic, transcriptomic, and our novel epigenetic information in an extensive multi-omics analysis to infer latent factors capable of explaining independent signatures comprising NPM1-mutated AML biology. The study used the well-annotated CALGB/Alliance AML cohort encompassing 581 NPM1-mutated patients. Surprisingly, genetic mutations contributed to only approximately 3% of the overall variance, while DNA methylation captured more than 15% of the total variance. We were able to infer 15 latent factors, 5 of which were associated with overall survival. All factors were significant after adjusting for established prognostic features, such as FLT3-ITD, sex, and age. Factors 2, 7 and 11 were associated with unfavorable outcomes, and variably included increased HOX signatures, suppressed TP53 activation, a stem cell-like phenotype, the epigenetic SHS signature, triple NPM1/FLT3-ITD/DNMT3A mutations, and alternative splicing, including NUP98. Factor 13 uncovered a unique expression pattern of X-linked cancer testis antigen gene family members dividing NPM1 patients independent of sex, age, or common mutations, and was inversely associated with the expression of CD34, MN1 and BAALC – prognostic genes related to stemness. Analysis of immune cell subsets indicated differences in proportions of CD8 effector T cell populations between patients with high vs. low factor 13.
References:
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Keywords: AML, Multi-omics, Epigenetics