Computational Cancer Genomics

The main focus of the bioinformatics team is to improve and apply methods to interpret high throughput data especially to understand tumor diseases, their causes and clinical consequences. The bioinformatics team develops and applies methods and algorithms for the analysis of molecular genetics data in the clinical context. Currently the main focus is the understanding of biological processes in the context of clinical applications through the analysis of high throughput sequencing data. In addition, we use single cell technologies to disentangle tumor compositions and understand the tumor microenvironment. Furthermore, we are interested in bacterial and viral contributions to cancer analyzing the microbiome components of tumor samples to make use of the identified microbiota for tumor characterization and patient stratification.
Our current work in the context of several projects focuses on the following aspects:

• Improve and apply bioinformatics in the context of molecular tumor boards leading to improved treatment of breast cancer cases. In two clinical projects (CATCH and COGNITION) we perform the bioinformatic analyses and clinical interpretation of the genomic aberrations in breast cancer patients to guide treatment decisions [3]. In collaboration with Prof. Dr. med. Andreas Schneeweiss we work on clinical trials in oncology (Clinical Trials at NCT) and support the decision process in the personalized patient treatment by performing the variant calling and interpretation as well as preparation of the molecular tumor boards.

• Understanding of tumor development, microenvironment and clonal evolution based on transcriptomic, epigenetic and genomic changes applying bulk and single cell approaches

We recently analyzed the clonal evolution in chronic lymphocytic leukemia [2] and now together with Martina Seiffert use single cell methods to understand the tumor microenvironment in CLL. In addition, we analyze the tumor and microenvironment composition applying single cell technologies in brain metastases of breast cancer to understand the establishment of these metastases and their interactions with immune and brain cells.

• Identifying and characterizing the microbiome component in tumors and tumor patients

Recently we analyzed the viral contribution to cancer in a large cohort of cancer samples collected in the CGC/TCGA Pan-Cancer Analysis of Whole Genomes cohort (PCAWG) [1] and could identify relevant genomic lesions linked to viral infections. Currently we are analyzing the viral contribution to cancer in additional cohorts and extend our analysis to the bacterial microbiome especially in the context of chemo- and immune therapy of cancer.

• Zapatka M, Borozan I, Brewer DS, Iskar M, ..., Lichter P; PCAWG Consortium. The landscape of viral associations in human cancers. Nat Genet. 2020 Mar;52(3):320-330. PMID: 32025001. [1]

• Zapatka M, Tausch E, ..., Lichter P, Stilgenbauer S. Clonal evolution in chronic lymphocytic leukemia is scant in relapsed but accelerated in refractory cases after chemo(immune)therapy. Haematologica. 2021 Mar 11. PMID: 33691380. [2]

• Hlevnjak M, Schulze M, Elgaafary S, ..., Zapatka M, Lichter P, and Schneeweiss A. CATCH: A Prospective Precision Oncology Trial in Metastatic Breast Cancer. JCO Precision Oncology 2021 :5, 676-686. PMID: 34036222.

• Gröbner SN, Worst BC, ..., Chavez L*, Zapatka M*, Pfister SM*. The landscape of genomic alterations across childhood cancers. Nature. 2018 Mar 15;555(7696):321-327. PMID: 29489754.* Shared last authorship

• Hovestadt V, Jones DT, ..., Zapatka M, Radlwimmer B, Pfister SM, Lichter P. Decoding the regulatory landscape of medulloblastoma using DNA methylation sequencing. Nature. 2014 Jun 26;510(7506):537-41. PMID: 24847876.

• Rausch T*, Jones DT*, Zapatka M*, Stütz AM*, ..., Lichter P, Pfister SM, Korbel JO. Genome sequencing of pediatric medulloblastoma links catastrophic DNA rearrangements with TP53 mutations. Cell. 2012 Jan 20;148(1-2):59-71. PMID: 22265402.*shared first authorship