Identification and characterisation of tumor relevant genes for acute myeloid leukemia (AML)

Coordinator:    Prof. Dr. Hartmut Döhner
Institution: Universität Ulm / Universitätsklinikum Ulm
Acute myeloid leukemia (AML) is characterized by deregulation of normal hematopoiesis and rapid expansion of immature hematopoietic progenitors. A high heterogeneity of mutations and chromosomal aberrations were found in this disease. In spite of intensive research, it is still discussed, which changes in genetic material are critical for initiation of AML. Until recently, AML has mostly been studied using the microarray technology, which enabled the characterization of chromosomal aberrations and gene expression fold-changes. While we are pursuing this approach to identify disease relevant genes, the mutational analysis of genome/transcriptome has so far been limited to selected genes, which were sequenced to discover the disease-relevant mutations. The advent of new technologies during the last years now offers the opportunity to capture large genomic regions on a microarray, followed by next-generation sequencing (NGS) of selected genomic DNA.
A subgroup of AML with a complex karyotype, which is defined by the presence of three or more chromosome abnormalities, might represent a model that points to chromosomal regions involved in leukemogenesis. Based on analysis of genomic aberrations in complex karyotype AML, we designed a custom microarray (NimbleGen) for sequence capture followed by NGS using Illumina technology. The microarray contains 1000 candidate genes covering tumor relevant genes located in the regions of losses or gains. These regions were identified in previous analyses of AML cases with complex karyotype using aCGH, 250k SNP (n~200) and Affymetrix 6.0 SNP (n=50) microarrays. Submicroscopic aberrations found in AML with normal karyotype (n=70, 500k SNP platform) were taken into consideration.

Based on our previous work in AML with complex karyotype (CK-AML) we have designed NimbleGen Sequence Capture microarrays covering the promoter regions and the entire coding region of 1000 candidate genes located in critical genomic regions. With this technology, we have enriched and sequenced 50 paired leukemia / germline AML samples in collaboration with the Genomic Core Facility of the DKFZ. We identified 120 missense/nonsense mutations as well as 60 insertions/deletions affecting 73 different genes (3.6 tumor-specific aberrations/AML). While most of the newly identified alterations were non-recurrent, we observed a significant enrichment of mutations affecting genes involved in epigenetic regulation including known candidates like TET2, TET1, DNMT3A and DNMT1, as well as mutations in histone methyltransferases NSD1, EZH2 and MLL3. Furthermore, we found a significant enrichment of alterations in genes involved in splicing. Thus, aberrant splicing and epigenetic regulation might play an important role in the molecular pathogenesis of AML (see Dolnik et al. Blood 2012, see Figure). In addition, we investigated clonal evolution by sequencing paired diagnosis/relapse AML samples, and first whole exome sequencing experiments have been successfully performed and analyses are currently ongoing.

Furthermore, we have performed an integrated analysis of our arrayCGH / SNP microarray data TP53 mutational screening in CK-AML to assess the frequency of TP53 alterations and their correlation with other genetic changes and outcome. We found TP53 mutations in 141 of 234 (60%) and TP53 losses were identified in 94 of 234 (40%) CK-AMLs; in total, 164 of 234 (70%) cases had TP53 alterations. TP53-altered CK-AMLs were characterized by a higher degree of genomic complexity (aberrations per case, 14.30 vs 6.16; P < .0001) and by a higher frequency of specific copy number alterations including a monosomal karyotype (MK). Furthermore, patients with TP53 alterations were older and had significantly lower complete remission rates, inferior event-free, relapse-free, and overall survival. In conclusion, we could identify TP53 as the most important prognostic factor in CK-AML, outweighing all other variables, including the MK category (see Rücker et al. Blood 2012). In addition, we also could in collaboration with Peter Lichter’s and Jan Korbel’s groups substantiate a link between TP53 mutation and chromothripsis that indicates a context-specific role for p53 in catastrophic DNA rearrangements in AML. These findings connect p53 status and chromothripsis, providing a genetic basis for understanding particularly aggressive subtypes of cancer such as CK-AML (see Rausch et al. Cell 2012). In addition, by integrative analysis of genomics and transcriptomics data we could demonstrate a deregulation of the p53 / miR-34a network in complex karyotype AML (see Rücker et al. Leukemia 2013).

Figure: Targeted resequencing results of 50 paired tumor-remission AML samples. Fraction of reads reporting mutated frameshift/missense/nonsense alleles from targeted resequencing data for each case. Mutations in recurrently mutated AML genes identified in this screen are shown as colored points, with non-recurrent mutations as black points. CBF-AML indicates core-binding factor AML; CK-AML, complex karyotype AML; CN-AML, cytogenetically normal AML; FLT3*, FLT3 with internal tandem duplications (FLT3-ITD); figure adapted from Dolnik et al. Blood 2012.

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