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Background Minimally differentiated acute myeloid leukemia is heterogeneous in karyotype and is defined by immature morphological and molecular characteristics. This originally French-American-British classification is still used in the new World Health Organization classification when other criteria are not met. Apart from RUNX1 mutation, no characteristic molecular aberrations are recognized.Design and Methods We performed whole genome single nucleotide polymorphism analysis and extensive molecular analysis in a cohort of 52 patients with minimally differentiated acute myeloid leukemia.Results Many recurring and potentially relevant regions of loss of heterozygosity were revealed. These point towards a variety of candidate genes that could contribute to the pathogenesis of minimally differentiated acute myeloid leukemia, including the tumor suppressor genes TP53 and NF1, and reinforced the importance of RUNX1 in this leukemia. Furthermore, for the first time in this minimally differentiated form of leukemia we detected mutations in the transactivation domain of RUNX1. Mutations in other acute myeloid leukemia associated transcriptions factors were infrequent. In contrast, FLT3, RAS, PTPN11 and JAK2 were often mutated. Irrespective of the RUNX1 mutation status, our results show that RAS signaling is the most important pathway for proliferation in minimally differentiated acute myeloid leukemia. Importantly, we found that high terminal deoxynucleotidyl transferase expression is closely associated with RUNX1 mutation, which could allow an easier diagnosis of RUNX1 mutation in this hematologic malignancy.Conclusions Our results suggest that in patients without RUNX1 mutation, several other molecular aberrations, separately or in combination, contribute to a common minimally differentiated phenotype.

Of 52 AML-M0 patients studied, 16 presented a RUNX1 mutation (30.8 %) and 8 carried a trisomy 13 (15 %). We found a strong correlation between trisomy 13 and RUNX1 mutations, i.e, 7 out of 8 cases with trisomy 13 carried a mutation in RUNX1 (87.5 %, p

BackgroundRadiation is an effective anti-cancer therapy but leads to severe late radiation toxicity in 5%-10% of patients. Assuming that genetic susceptibility impacts this risk, we hypothesized that the cellular response of normal tissue to X-rays could discriminate patients with and without late radiation toxicity.Methods and findingsProstate carcinoma patients without evidence of cancer 2 y after curative radiotherapy were recruited in the study. Blood samples of 21 patients with severe late complications from radiation and 17 patients without symptoms were collected. Stimulated peripheral lymphocytes were mock-irradiated or irradiated with 2-Gy X-rays. The 24-h radiation response was analyzed by gene expression profiling and used for classification. Classification was performed either on the expression of separate genes or, to augment the classification power, on gene sets consisting of genes grouped together based on function or cellular colocalization.X-ray irradiation altered the expression of radio-responsive genes in both groups. This response was variable across individuals, and the expression of the most significant radio-responsive genes was unlinked to radiation toxicity. The classifier based on the radiation response of separate genes correctly classified 63% of the patients. The classifier based on affected gene sets improved correct classification to 86%, although on the individual level only 21/38 (55%) patients were classified with high certainty. The majority of the discriminative genes and gene sets belonged to the ubiquitin, apoptosis, and stress signaling networks. The apoptotic response appeared more pronounced in patients that did not develop toxicity. In an independent set of 12 patients, the toxicity status of eight was predicted correctly by the gene set classifier.ConclusionsGene expression profiling succeeded to some extent in discriminating groups of patients with and without severe late radiotherapy toxicity. Moreover, the discriminative power was enhanced by assessment of functionally or structurally related gene sets. While prediction of individual response requires improvement, this study is a step forward in predicting susceptibility to late radiation toxicity.