Brief description of the planned work: Acute myeloid leukaemia (AML) is the most common and deadliest acute blood cancer with approximately 300 000 new cases every year worldwide. Five-year overall survival is still only about 30%, even though survival in paediatric patients is approaching 80%. The main reason for treatment failure is resistance to AML-directed drugs, in particular cytarabine (ara-C). Our laboratory has demonstrated that leukemic expression of the protein SAMHD1 leads to resistance against ara-C in adult and paediatric AML and that SAMHD1 expression at diagnosis is prognostic for outcomes in patients treated with ara-C (PMID: 28067901, 30341277). We have recently identified a novel family of endogenous SAMHD1 inhibitors, and when combining expression of both SAMHD1 and the endogenous SAMHD1 inhibitors in a score, treatment outcomes can be predicted even more accurately with a strong discrimination in several datasets including TCGA and TARGET-AML (unpublished; ethical permit: Dnr 2018/464-31/2). Recently, a score of 10 SNPs involving genes associated with ara-C metabolism as well as 3 additional SNPs involving SAMHD1 have been published to correlate with responses to ara-C treatment in AML (PMID: 34990262, 36689724). To allow even better prediction of ara-C responses, we now wish to compare the predictive potential of our gene expression score with predictions of 10-SNP and the 3-SAMHD1-SNP score for which we need to call the variants from whole-genome sequencing data. Data sensitivity statement: This project will involve handling of human whole genome sequencing data.