PROGNOSTIC SIGNIFICANCE OF GENE MUTATIONS IN MDS DEPENDS ON THE LOCI OF GENE VARIANCES PROGNOSTIC SIGNIFICANCE OF GENE MUTATIONS IN MDS DEPENDS ON THE LOCI OF GENE VARIANCES T. Boneva1, L . Rai1, D. Brazma1, R. Dunn1, C. Grace1, E. Nacheva1,2 1 Department of OncoGenomics, HSL Analytics LLP, London UK 2 Cancer Institute, University College London, London UK Introduction Myelodysplastic syndromes are a collection of clonal hematopoietic disorders with a wide range of clinical manifestations and eventual outcomes. Predicting the prognosis is of great importance for defining the risk and select treatment options. Several models of risk stratification exist, all of which include genetic markers along with other clinical and paraclinical features. The Revised International Prognostic Scoring System (IPSS-R, Greenberg et al., Blood. 2012) defines 5 risk levels based on the presence of specific chromosome abnormalities. These genome aberrations provide evidence for disease although reports of frequent driver mutations (Papemauilie et al., Blood, 2013) and/or structural variants detected by single nucleotide polymorphism (SNP) arrays (Tiu et al., Blood, 2011) have shown a potential for score criteria in the diagnosis of MDS. Recent reports of the presence such genetic aberrations in disease free individuals makes this approach problematic (Genovese et al., N Engl J Med 2014; Lichman, Blood 2015, Kwok et al., Blood 2015). A study of patients without evidence for MDS identified a driver mutation and/or structural gene variants in 91% of pre-diagnostic samples with the mutational spectrum mirroring that seen in MDS population. The presence of mutations with greater median variant allele fraction (40% vs 9% to 10% in healthy individuals) and occurring with additional mutations (>2 mutations, 64% vs 8%) were shown to define a high-risk group with a shorter time to disease progression and poorer overall survival (Cargo et al. Blood, 2015). Results A total of 145 bone marrow samples from 58 women and 87 men, aged from 26 to 85 suspected to have myeloid dysplasia were investigated. Of these only 76 (52%) were found to fulfill the WHO, criteria referred to as MDS positive – MDS(+), the rest as MDS negative – MDS(-). Gene variances were detected in all but 7 samples (5%). The latter appear to be void of any gene mutations. Gene variances were detected in all samples for 47 of the 54 genes targeted by the TruSight myeloid panel. We observed driver type mutations as reported in myeloid malignancies in 68 (47%) samples , whilst 70 (48%) were found to carry variances seen in disease free individuals or considered to be tolerated. The most common variants in MDS(-) samples are TET2, CUX1, SRSF2, BCORL1 and RUNX1 while in MDS(+) samples the variants of TET2 , ASXL1, CUX1, CEBPA and SRSF2 are the most frequent. Multiple TET2 variants located within exon 3-11 were identified in both groups. Comparison of these variants identified the TET2 missense dbSNP variant at 106197285 (rs 116519313,NCBI) only in the MDS(+) group. Then we examined the distribution of individual variances rather than genes in all samples and found a number of loci of the genes ASXL at 131022441, DNMT3A at 25523096, U2AF at two locations 144524456 & 44514879 as well as SF3B1 at 74732959 and BCROL1 at 129190217 are far more commonly detected in the MDS positive group. Conclusion We compared 145 bone marrow samples from patents presenting with MDS of which 76 met the WHO criteria. There is little difference in their genomic profile when comparing the two groups on the basis of the most highly involved genes (TET2, CUX1, ASXL1 and SRSF2) but if we compare the two groups by variance ( i.e. genome address), several locations are consistently more frequently detected (on average > 5 fold higher) in the MDS positive group. Notably, these are usually part of a gene profiles with more than three variances. ACKNOWLEDGEMENTS The myeloid TruSight panel (Illumina) used in this study covers the following gene regions Objective To compare the genomic profile of bone marrow samples at presentation from 145 adults, 76 of whom met the WHO criteria for MDS. References Revised international prognostic scoring system for myelodysplastic syndromes, Greenberg et al., Blood, 2012 Sep 20;120(12):2454-65. Clinical and biological implications of driver mutations in myelodysplastic syndromes. Papemauilie et al., Blood, 2013 Nov 21;122(22):3616-27. Prognostic impact of SNP array karyotyping in myelodysplastic syndromes and related myeloid malignancies, Tiu et al., Blood, 2011 Apr 28;117(17):4552-60. Clonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence, Genovese et al., N Engl J Med 2014 Dec 25;371(26):2477-87. Clonal hematopoiesis: a "CHIP" off the old block, Lichman et al., Blood 2015 Jul 2;126(1):1-2. Targeted sequencing identifies patients with preclinical MDS at high risk of disease progression, Cargo et al. Blood, 2015 Nov 19;126(21):2362-5. MethodS All samples were screened by conventional G banding analysis and/ or molecular karyotyping using 8x60K oligonucleoitide arrays (Agilent, USA) and screened by FISH using probes (Cytocell, UK) targeting the most common aberrations associated with MDS as per IPSS-R classification (Greenberg et al., Blood, 2013). The target gene panel TruSight on a MiSeq platform (Illumina, USA) was used to screen mutational hotspots in 54 cancer-related genes relevant in myeloid malignancy. Gene variances were reported at allele frequencies (VAF) >10% and at minimum read depth of 300 as per manufacturers criteria. We used the Catalogue of Somatic Mutations In Cancer (COSMIC), dbSNP and 1000 genome (>2%) to classify gene variants as either drivers, variants of unknown significance and germline polymorphisms (SNPs). Genome addresses are  given according to hg19(GRCH37). CONTACT INFORMATION temenuzhka.boneva@nhs.net e.nacheva@ucl.ac.uk