PS987 RIBOMETHYLOME CHANGES DEPEND ON DISTINCT PATTERNS OF C/D BOX SNORNAS IN AML SUBTPYES
Authors: C. Rohde, F. Zhou, Y. Liu, D. Gerloff, C. Walter, M. Köhn, D. Misiak, S. Hüttelmaier, C. Thiede, G. Ehninger, H. Serve, M. Dugas, C. Müller‐Tidow
Journal: HemaSphere (2019)

Background: Small nucleolar RNAs (snoRNAs) are a group of non‐coding RNAs. The most prominent role for snoRNA is to guide small nucleolar ribonucleoproteins (snoRNPs) to complementary regions of ribosomal (rRNA), where the snoRNP complexes catalyze ribosomal modifications. snoRNAs are divided into the two major classes: box C/D and box H/ACA snoRNAs. C/D box snoRNAs are involved in 2‐O‐methylation, whereas H/ACA snoRNAs guide pseudouridylation. Beyond the role in rRNA modification, functions in splicing and chromatin have been proposed. Recently, we demonstrated that snoRNAs play a critical role for AML1‐ETO induced leukemia (Zhou et al., Nat Cell Biol 2017). Aims: We aimed to elucidate snoRNA expression patterns and functions in acute myeloid leukemia and establish the first global map of 2’‐methylation of rRNA in AML patients. Methods: We analyzed snoRNA expression patterns in a cohort of 161 AML patients using small‐RNA sequencing. All patient samples were obtained at the time of diagnosis. Expression levels were calculated for known C/D‐box and H/ACA‐box snoRNA. Only regions with at least one reads per million (RPM) in at least one patient sample were included for further investigation. We applied ribomethseq to elucidate the entire ribosomal 2’‐0 methylation pattern in AML patients. We calculated the methylation scoreC from 5’‐read ends for all known sites from snOPY and an updated list from Krogh et al. 2016, Further, methylation patterns and snoRNA patterns were analysed with regard to AML mutations as analysed by panel sequencing. Results: Next generation sequencing data revealed expression o 354 known C/D box snoRNAs and 160 H/ACA box snoRNAs in primary AML patient samples. Expression patterns of snoRNAs varied according to specific genetic risk groups. High levels of snoRNA expression were observed in intermediate molecular risk group patients (215 C/D box and 68 H/ACA box snoRNAs, p≤0.05). Also, high levels of snoRNA were found in patients with a poor response to the first cycle of induction therapy (144 C/D box and 61 H/ACA box snoRNAs, p≤0.05). Of note, NPM1 mutations were associated with wide ranging changes in expression (almost all downregulation) in 232 C/D box and 61 H/ACA box snoRNA. In contrast, AMLs with ASXL1 or RUNX1 mutations predominantly expressed higher levels of snoRNA expression. We established the first map of ribosomal 2’‐0 methylation patterns in AML patients on published modification sites. This resulted in RiboMethylome data constituting 107 high quality ribosomal sites which were methylated in AML patients. In most instances, C/D box snoRNA expression was positively correlated with the respective levels of 2́‐O‐methylation in rRNA. Importantly, NPM1 mutation status strongly influenced the RiboMethylome in affected AML blasts. Summary/Conclusion: AML with different mutation patterns exhibit striking differences in snoRNA expression levels. Our data reveal widespread plasticity of epitranscriptomic modifications in the ribosomes of AML patients. These findings suggest that driver mutations in AML could induce specialized ribosomes which may contribute to leukemic transformation.