We have developed a robust algorithm for copy number analysis of the human genome using high-density oligonucleotide microarrays containing 116,204 single-nucleotide polymorphisms. The advantages of this algorithm include the improvement of signal-to-noise (S/N) ratios and the use of an optimized reference. The raw S/N ratios were improved by accounting for the length and GC content of the PCR products using quadratic regressions. The use of constitutional DNA, when available, gives the lowest SD values (0.16 F 0.03) and also enables allele-based copy number detection in cancer genomes, which can unmask otherwise concealed allelic imbalances. In

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Tumor protein p53 (TP53) is the most frequently mutated gene in cancer 1,2. In patients with myelodysplastic syndromes (MDS), TP53 mutations are associated with high-risk disease 3,4 , rapid transformation to acute myeloid leukemia (AML) 5 , resistance to conventional therapies 6-8 and dismal outcomes 9. Consistent with the tumor-suppressive role of TP53, patients harbor both mono-and biallelic mutations 10. However, the biological and clinical implications of TP53 allelic state have not been fully investigated in MDS or any other cancer type. We analyzed 3,324 patients with MDS for TP53 mutations and allelic imbalances and delineated two subsets of patients with distinct phenotypes and outcomes. One-third of TP53-mutated patients had monoallelic mutations whereas two-thirds had multiple hits (multi-hit) consistent with biallelic targeting. Established associations with complex karyotype, few co-occurring mutations, high-risk presentation and poor outcomes were specific to multi-hit patients only. TP53 multi-hit state predicted risk of death and leukemic transformation independently of the Revised International Prognostic Scoring System (IPSS-R) 11. Surprisingly, monoallelic patients did not differ from TP53 wild-type patients in outcomes and response to therapy. This study shows that consideration of TP53 allelic state is critical for diagnostic and prognostic precision in MDS as well as in future correlative studies of treatment response. In collaboration with the International Working Group for Prognosis in MDS (Supplementary Table 1), we assembled a cohort of 3,324 peridiagnostic and treatment-naive patients with MDS or closely related myeloid neoplasms (Extended Data Fig. 1 and Supplementary Fig. 1). Genetic profiling included conventional G-banding analyses (CBA) and tumor-only, capture-based, next-generation sequencing (NGS) of a panel of genes recurrently mutated in MDS, as well as genome-wide copy number probes. Allele-specific copy number profiles were generated from NGS data using the CNACS algorithm 7 (see Methods and Code availability). An additional 1,120 samples derived from the Japanese MDS consortium (Extended Data Fig. 2) were used as a validation cohort. To study the effect of TP53 allelic state on genome stability, clinical presentation, outcome and response to therapy, we performed a detailed characterization of alterations at the TP53 locus. First, we assessed genome-wide allelic imbalances in the cohort of 3,324 patients, to include arm-level or focal (~3 Mb) ploidy alterations and regions of copy-neutral loss of heterozygosity (cnLOH) (Extended Data Fig. 3, Supplementary Figs. 2-4 and Methods).

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