© F e r r a t a S t o r t i F o u n d a t i o nR.G.W. Verhaak et al. between both AML sample populations. Mutational analyses to detect recurrent mutations in AML were performed as previously described. [13][14][15][16] All supervised class prediction analyses were performed with Prediction Analysis for Microarrays (PAM) software version 1.28 in R version 2.1.0. 17 Clinical, cytogenetic and molecular information as well as the gene expression profiles of all primary AML cases is available at the Gene Expression Omnibus (www.ncbi.nlm.nih.gov/geo, accession number GSE6891). Results and DiscussionIn this study of 461 clinically and molecularly well-characterized cases of AML (Table 1), we were able to comprehensively validate the application of GEP to predict therapeutically relevant molecular subtypes in AML.We applied PAM to investigate whether karyotypic and mutational abnormalities with prognostic or therapeutic value in AML were accurately predictable based on GEP. PAM allows the selection of the minimal number of genes required for optimal prediction, which may be beneficial in a diagnostic setting. The AML cohort1 (n=247) was used as training set to derive predictive signatures that were subsequently validated on AML cohort2 (n=214). The deduced expression signatures are available in the Online Supplementary Tables S1-18.The cytogenetic status of all AML patients with favorable risk, i.e. those with t(8;21), t(15;17) or inv(16) abnormalities, was predicted with 100 percent accuracy ( Table 2). In fact, among these predicted AML cases, there were cases with favorable cytogenetics that had previously been missed by routine cytogenetics (4 out of 37 inv(16) and 4 out of 25 t(15;17)). The presence of the translocation-related fusion transcripts in these specific cases was confirmed by real-time quantitative PCR. Thus, GEP is a reliable alternative to discriminate these three AML subtypes, 2,3 which represent approximately 20% of all cases.2,3 Prediction of t(15;17) and inv(16) required only few genes, as seen previously. 8 For the t(8;21) cases, 76 probe sets were needed to correctly classify all samples. However, as few as two probe sets, including one associated with the RUNX1T1 (ETO) gene, were sufficient to accurately classify all but one t(8;21) cases, which is also consistent with earlier studies 8 (Online Supplementary Figure S3). AML cases with mutations in the transcription factor CCAAT/enhancer binding protein α (CEBPA), which are associated with a relatively favorable treatment outcome, were predicted with positive and negative predictive values of 100% and 97% respectively. Six out of 15 CEBPA mutant cases were missed in the validation set (sensitivity 60%; Table 2). Of note, the misclassified cases all carried a single heterozygous CEBPA mutation, whereas samples with biallelic mutations (either homo-or heterozygous) were all correctly recognized (data not shown). In the training cohort, all but two (14/16) samples carried biallelic mutations 14,18 and in cross-validation in the training cohort ...

Somatic mutations in isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2) were recently demonstrated in acute myeloid leukemia (AML), but their prevalence and prognostic impact remain to be explored in large extensively characterized AML series, and also in various other hematologic malignancies. Here, we demonstrate in 893 newly diagnosed cases of AML mutations in the IDH1 (6%) and IDH2 (11%) genes. Moreover, we identified IDH mutations in 2 JAK2 V617F myeloproliferative neoplasias (n ‫؍‬ 96), a single case of acute lymphoblastic leukemia (n ‫؍‬ 96), and none in chronic myeloid leukemias (n ‫؍‬ 81). In AML, IDH1 and IDH2 mutations are more common among AML with normal karyotype and NPM1 mutant genotypes. IDH1 mutation status is an unfavorable prognostic factor as regards survival in a composite genotypic subset lacking IntroductionSomatic mutations in the genes encoding the isocitrate dehydrogenases IDH1 and IDH2 were revealed in more than 70% of World Health Organization grade 2 and 3 astrocytomas, oligodendrogliomas, and glioblastomas. [1][2][3] Mutations in IDH1 and IDH2 were mutually exclusive and affected the arginines on position 132 of IDH1 and position 172 of IDH2. 3 Patients with malignant gliomas with IDH1 or IDH2 mutations showed a better response to therapy than those with wild-type IDH genes. 3 Mutations in these residues of IDH significantly disturb the function of both isocitrate dehydrogenases, as demonstrated by impaired production of nicotinamide adenine dinucleotide phosphate. 3,4 In acute myeloid leukemia (AML), mutant IDH enzyme activity results in accumulation of the cancer-associated metabolite 2-hydroxyglutarate. 5,6 Recently, acquired mutations in the gene encoding IDH1 were identified in 8% 7 and 5.5% 8 of newly diagnosed AML cases. IDH1 mutations were significantly associated with normal karyotype and NPM1 mutations. 7,8 Overall, the IDH1 mutation status did not suggest a relationship with overall survival (OS), but the sample sizes were limited in these studies. 7,8 However, a trend for an adverse effect on OS was suggested in normal karyotype AML with NPM1 wild-type . 7 The prevalence and prognostic value of IDH mutations in AML, as well as other hematologic malignancies, remain to be further established. In this study, we determined the frequencies of both IDH1 and IDH2 mutations in cohorts of AML, acute lymphoblastic leukemia (ALL), chronic myeloid leukemia (CML), and JAK2 V617F myeloproliferative neoplasia (MPN). In a cohort of 893 cases of AML, we investigated their distribution in relationship with cytogenetic and molecular risk categories as well as recurrent gene mutations commonly apparent in AML, and we evaluated the impact of IDH mutations on treatment outcome. MethodsBone marrow aspirates or peripheral blood samples of cohorts of patients with various hematologic malignancies were collected after written informed consent in accordance with the Declaration of Helsinki. All experiments described were approved by the Erasmus University Medical Center Institutional Review Board....

Translocations involving nucleoporin 98kD (NUP98) on chromosome 11p15 occur at relatively low frequency in acute myeloid leukemia (AML) but can be missed with routine karyotyping. In this study, high-resolution genome-wide copy number analyses revealed cryptic NUP98/ NSD1 translocations in 3 of 92 cytogenetically normal (CN)-AML cases. To determine their exact frequency, we screened > 1000 well-characterized pediatric and adult AML cases using a NUP98/NSD1-specific RT-PCR. Twenty-three cases harbored the NUP98/NSD1 fusion, representing 16.1% of pediatric and 2.3% of adult CN-AML patients. NUP98/NSD1-positive AML cases had significantly higher white blood cell counts (median, 147 ؋ 10 9 /L), more frequent FAB-M4/M5 morphology (in 63%), and more CN-AML (in 78%), FLT3/internal tandem duplication (in 91%) and WT1 mutations (in 45%) than NUP98/ NSD1-negative cases. NUP98/NSD1 was mutually exclusive with all recurrent type-II aberrations. Importantly, NUP98/ NSD1 was an independent predictor for poor prognosis; 4-year event-free survival was < 10% for both pediatric and adult NUP98/NSD1-positive AML patients. NUP98/NSD1-positive AML showed a characteristic HOX-gene expression pattern, distinct from, for example, MLLrearranged AML, and the fusion protein was aberrantly localized in nuclear aggregates, providing insight into the leukemogenic pathways of these AMLs. Taken together, NUP98/NSD1 identifies a previously unrecognized group of young AML patients, with distinct characteristics and dismal prognosis, for whom new treatment strategies are urgently needed. (Blood. 2011;118(13):3645-3656)

The prevalence, the prognostic effect, and interaction with other molecular markers of DNMT3A mutations was studied in 415 patients with acute myeloid leukemia (AML) younger than 60 years. We show mutations in DNMT3A

Oncogene-expressing human papillomavirus type 16 (HPV16) is found in a subset of head and neck squamous cell carcinomas (HNSCC). HPV16 drives carcinogenesis by inactivating p53 and pRb with the viral oncoproteins E6 and E7, paralleled by a low level of mutations in TP53 and allelic loss at 3p, 9p, and 17p, genetic changes frequently found in HNSCCs of nonviral etiology. We hypothesize that two pathways to HNSCC exist: one determined by HPV16 and the other by environmental carcinogens. To define the critical genetic events in these two pathways, we now present a detailed genome analysis of HNSCC with and without HPV16 involvement by employing high-resolution microarray comparative genomic hybridization. Four regions showed alterations in HPV-negative tumors that were absent in HPV-positive tumors: losses at 3p11.2-26.3, 5q11.2-35.2, and 9p21.1-24, and gains/amplifications at 11q12.1-13.4. Also, HPV16-negative tumors demonstrated loss at 18q12.1-23, in contrast to gain in HPV16-positive tumors. Seven regions were altered at high frequency (>33%) in both groups: gains at 3q22.2-qter, 5p15.2-pter, 8p11.2-qter, 9q22-34.1, and 20p-20q, and losses at 11q14.1-qter and 13q11-33. These data show that HNSCC arising by environmental carcinogens are characterized by genetic alterations that differ from those observed in HPV16-induced HNSCC, and most likely occur early in carcinogenesis. A number of genetic changes are shared in both tumor groups and can be considered crucial in the later stages of HNSCC progression.