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The common objective of developing and applying bioinformatics tools to better understand cancer biology fosters close interaction between the groups inside the Division of Applied Bioinformatics and cooperation with the Computational Oncology group in the Division of Theoretical Bioinformatics.



Clinical Bioinformatics

The Clinical Bioinformatics team headed by Dr. Barbara Hutter specializes in applying next generation sequencing data analysis for personalized oncology. We place emphasis on establishing workflows for fast and reliable detection of actionable mutations in individual cancer genomes. Our experience with sequencing and mapping artifacts coined the term “NGS data pathology”. We also take into account the role of mutagenesis by viruses in characterizing druggable lesions. A main focus of our research is translational communication with clinicians. In order to facilitate targeted therapy recommendation, we generate comprehensive lists of the "druggable genome". Currently we perform analyses of clinical genome and transcriptome sequencing data for two precison oncology projects: the INdividualized Therapy FOr Relapsed Malignancies in Childhood INFORM registry and the DKFZ-HIPO Project H021 in the NCT MASTER program that is directed towards younger adults with advanced-stage cancer across all histologies.

Comparative Cancer Genomics

The Comparative Cancer Genomics team lead by Dr. Lars Feuerbach focuses on integrating sequencing and array data across tumor subtypes and patient cohorts. In these Pan-Cancer studies the similarities and differences in the interplay of epigenome, genome and transcriptome during carciogenesis are investigated. Furthermore, dataset from orthogonal experimental techniques are integrated. We contribute to two Pan-Cancer projects of the International Cancer Genome Consortium ICGC, where we investigate the impact of point mutations in regulatory regions on gene expression across 50 tumor types and alterations of telomere length and structure during tumor progression. Furthermore, we perform pan-prostate cancer analysis in the ICGC Early-onset Prostate Cancer consortium. Our methodological expertise for high-level analysis comprises algorithm development, specialized datastructures for data integration, data mining, compact visualization of complex information, and statistical modeling.

Computational Oncoimmunology

The Computational Oncoimmunology team lead by Charles Imbusch focuses on questions regarding the immune system in general and more specifically under pathogenic conditions such as cancer. To address these questions NGS, as well as array technologies, are routinely utilized.

With the advent of multiple single cell technologies it is now possible to differentiate subpopulations captured in an assay, allowing to address cell heterogeneity and the discovery of rare cell populations. We focus on the downstream analysis of scRNA-seq and scTCR to robustly identify and describe cell populations, study dynamic cross-talk between tumor and immune cells while keeping up to date with most recent algorithmic developments.

Alternatively to single cell assays we apply and develop methods to deconvolute from bulk data cell types, integrating epigenetic and transcriptomic data to describe the tumor microenvironment.


The HIPO team is affiliated with both the Division of Applied Bioinformatics and the Computational Oncology group in the Division of Theoretical Bioinformatics. We provide bioinformatics service for the Heidelberg Center for Personalized Oncology (DKFZ-HIPO). Our research interests comprise comparative cancer genomics, cancer evolution, and methods development for analysis of epigenomic data and visualization. As an example, the team interaction graph is created with the circlize package.

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