Bioinformatics

The interaction between immune cells and leukemia/cancer stem cells

Group Ochsenbein   Our research unit examines the interaction between immune cells and cancer stem cells with a focus on leukemia stem cells. Cancer stem cells are resistant to most of the currently available drugs and are responsible for relapse after successful chemotherapy. We use state of the art techniques to analyse the molecular interactions between immune cells and cancer stem cells in murine models and in clinical samples from cancer patients. The aim is to develop improved immunotherapies that specifically target cancer stem cells for different types of cancer, especially in hemato-oncological diseases such as leukemia and multiple myeloma. These novel durgs are tested in in preclinical models and in clinical phase 1 and 2 studies. 

Design, synthesis, analysis, and optimization of novel small molecule inhibitors against prostate cancer

Group Pandey   Androgens are linked to pathology of prostate cancer. Cytochrome P450 CYP17A1 and Aldo-keto reductase AKR1C3 involved in steroid metabolism are drug targets. The current anti-prostate cancer drug, abiraterone, targeting CYP17A1, is not very effective, and has side effects. We found that Abiraterone inhibits CYP21A2 and cortisol production; and a metabolite of abiraterone is a potent androgen, which ultimately defeats the treatment. With computational and medicinal chemistry groups from Denmark, Poland, Italy and Spain, we produce novel inhibitors of CYP17A1 and AKR1C3. We design and improve the compounds and test them in the laboratory. After the virtual screening, we apply machine learning and automated workflows to identify pharmacophores for structural modifications and synthesis of novel chemicals. Nanoparticle based delivery is used to enhance the efficacy. Using several cell and recombinant protein models novel inhibitors are being tested which are now working at nano molar levels.

Leukemia stem cells and the bone marrow microenvironment

Group Riether   The bone marrow (BM) microenvironment is a unique cellular architecture which crucially regulates self-renewal and differentiation potential of hematopoietic stem and progenitor cells through cell-cell interaction or the release of soluble mediators. These evolutionary conserved processes that evolved to protect normal hematopoietic stem cells from elimination and to regulate demand-adapted responses during inflammation are frequently hijacked in cancer and leukemia. The goal of our research is to understand the molecular and cellular mechanisms how different components of the BM microenvironment such as immune cells and stromal cells affect disease-initiating and -maintaining leukemia stem cells (LSCs) and protect them from immune-mediated elimination. We take advantage of state-of-the art technologies, well-established chronic and acute myeloid leukemia mouse and patient-derived xenograft models in order strengthen our understanding on LSCs and to translate our findings into human disease.

Towards understanding the role of the minor spliceosome in cancer

Group Rubin   Genes are composed of coding units (exons), interspersed with non-coding regions called introns. The process of protein production involves splicing together exons while removing introns from the mRNA molecule. Evolution has given rise to a cellular apparatus called the spliceosome, responsible for carrying out this splicing process. Alternative splicing enables the generation of diverse protein isoforms from a single gene. Splicing is tightly regulated under normal physiological conditions. Our recent findings indicate that cancer cells use a specialized spliceosome, the so-called minor spliceosome, to increase cancer relevant mRNAs. As such cancer hijacks the minor intron-splicing machinery to enhance the expression of transcripts containing minor introns. Proteins encoded by those genes have been shown to activate critical cell survival pathways such as cell cycle regulation and DNA repair. Exploiting the reliance of cancer cells on minor intron-containing genes presents a novel therapeutic opportunity for targeting cancer. By inhibiting the minor spliceosome, we can selectively induce cell death in cancer cells while sparing healthy neighboring cells.

Easy and accurate quantification of mutational signatures in cancer samples

Group Zimmer, Medo   Mutations in the genome are often not random but follow distinct patterns. These patterns, termed mutational signatures, are footprints of biological processes or past exposures to specific carcinogens. Mutational signatures can help to elucidate tumor evolution and have prognostic and therapeutic implications.
Mathematical estimation of signature activities is a high-dimensional statistical problem. Although many tools for signature analysis have been developed, a recent analysis showed that no tool performs best under all conditions. We propose to identify the best-performing tool for a given task, cancer type, and number of mutations. This will be achieved by extensive prior testing of the existing tools on synthetic data under different conditions. We further propose to design a new tool that will explicitly include mutations that are not well explained by any known signature. With the two proposed tools, we aim to optimally use costly sequencing data and produce informed decisions for patient treatments.