Division of Applied Bioinformatics

The availability of methods like next-generation sequencing, which allows one to interrogate all bases of the human genome and detect somatic mutations in cancer with unprecedented precision, have provided a basis to understand the genetic causes of cancer on the systems level. Such data have proven useful to select individual therapy strategies, in particular targeted cancer drugs and immunotherapeutics. However, the high-dimensional nature of such data requires sophisticated computational approaches for their analysis and for supporting medical decision making. The major aim of the division is to develop and apply such computational methods to better understand cancer initiation and progression, and to improve cancer care by predicting which drugs will work to combat an individual tumor. For this, we develop automated pipelines to detect different classes of genetic alterations in cancer, and link this to sensitivities to approved cancer drugs. We further aim to understand mutations in the non-coding part of the genome and to characterize cancer evolution and heterogeneity. We have contributed to several projects in the International Cancer Genome Consortium, to elucidate the genetic landscapes of, e.g., medulloblastoma, early-onset prostate cancer and malignant B-cell lymphoma.

FUTURE OUTLOOK
We are part of the Pan Cancer Analysis of Whole Genomes Project as well as the German Epigenetics Project, DEEP. We are systematically exploring epigenetic and genetic alterations in cancer outside of protein-coding genes, and aim to understand their regulatory consequences. We perform bioinformatic analysis for a number of precision oncology trials in the German Cancer Consortium (DKTK) and the National Center of Tumor Diseases, e.g. DKTK-MASTER, INFORM and N2M2. Current research also aims to integrate data from high-throughput screening experiments in cancer cell lines and xenografts, as well as to understand genetic alterations on the network level. We are involved in initiatives on genomic data sharing and integration with clinical and radiological data.

We are part of three different research networks within the International Cancer Genome Consortium (ICGC):

• ICGC-PedBrain on pediatric brain tumors
• ICGC-EOPC on early-onset prostate carcinoma
• ICGC-MMMLseq on molecular mechanisms in malignant lymphoma