Anthropology and Human Genetics

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Cancer Evolution (SFB 1243)

More specifically, we want to address the following questions:

1. What impact do somatic and germline mutations have on AML gene expression? Gene expression patterns differ between patients not only due to newly acquired somatic mutations, but also due to their germline genotype. If a gene or a regulatory region already carries slightly disadvantageous germline mutations, the barrier to become a malignant cell is already lowered and new mutations can push the cell over the edge more quickly. We will infer haplotypes of driver genes and test to what extent they impact gene expression patterns at diagnosis and relapse. To this end, we will use existing exome and RNA-Seq data from over 50 paired diagnosis-relapse samples (Philipp Greif, A08 and Karsten Spiekermann, A07) to initially explore this question.

2. How can we use expression profiles to infer clonal genealogies? Because gene expression is also influenced by environmental factors, cells with similar expression profiles are not necessarily related. To establish analysis methods that allow to correct for environmental effects, we are going to generate single cell RNA-seq data and genotype subclone identifying SNVs from available AML-PDX lines. For this aim, we will closely collaborate with Wolfgang Enard (A14) and Irmela Jeremias (A05).

3. How do expression changes correlate with changes in patterns of DNA-methylation? While it is known that epigenetic mechanisms are important for the evolution of hematopoietic neoplasms, it is not well known how well evolution of methylation patterns is correlated with evolution of expression patterns. DNMT3A, TET2, IDH1 and IDH2, which are frequently mutated in AML, are genes important for the maintenance of correct DNA-methylation. In fact most AML samples contain at least one mutated epigenetic regulator. Thus it is standing to reason that the epigenetic landscape will mutate quickly and here we want to explore how this is reflected in gene expression profiles. To this end, we will analyse time series of RRBS and RNA-Seq data from single PDX-AML clones gen-erated by Irmela Jeremias (A05).

4. How does chemotherapy influence mutation rates in AML? Chemotherapeutic agents often also have mutagenic properties and more specifically the mutation pattern observed in refractory AML dif-fers significantly from AML at first diagnosis. Here, we want to further characterize those differences, analysing AML PDX cells from a mouse under therapy as described in A05 and A07.