New Professorship at the BIH: Cancer Bioinformatics

Professor Ishaque, congratulations on your professorship! Could you describe your field of research and your areas of focus?

My focus is on bioinformatics in cancer research, particularly at the intersection of spatial biology, single-cell genomics, and cancer genomics. In my view, cancer is not merely an intrinsic genetic disease of the cell, but an ecosystem at the tissue level. The spatial arrangement of tumor, immune, and stromal cells relative to one another contains information that cannot be captured using conventional approaches. Therefore, we are trying to understand the causal mechanisms that determine cell and tissue structure in the tumor microenvironment, with the goal of identifying robust approaches for new therapies.

In addition to our goal of gaining new biomedical insights, we are also developing new software tools. My group creates open-source tools for the entire field of spatial analysis, such as SSAM, SSAM-lite, and Sainsc. We also develop tools that identify data quality issues in spatial transcriptomics. For example, the ovrlpy tool detects cell overlaps that had previously gone undetected in all researchers’ data. Data quality and the reliability of analytical approaches are crucial for the research in my group.

Which of your past projects are particularly important to you?

I began my career in cancer research in 2013 at the DKFZ in Heidelberg when I joined Roland Eils’s department. During that time, I worked on many projects, but the three that are most important to me are:

1. The implementation of the bioinformatics workflows used in the DKFZ-HIPO and NCT-MASTER programs for cancer research. Here, I helped develop and coordinate a complete and reproducible end-to-end pipeline within the data management infrastructure.
2. Co-founding and leading the ELIXIR Single-Cell Omics Community. ELIXIR is Europe’s decentralized research infrastructure for life sciences data. To improve collaboration with researchers, ELIXIR also establishes “communities” that serve as collaborative networks and drive the development of standards, services, and training.
3. The launch of the SpaceHack hackathon series, which brought together leading figures in spatial transcriptomics to discuss challenges and develop solutions—not least for effective quality assessment strategies in spatial transcriptomics.

What are your plans for the professorship in Cancer Bioinformatics?

First, I want to investigate how the spatial arrangement of tumor, immune, and stromal cells influences whether patients benefit from immunotherapy or not. Research has already identified significant correlations in this area. However, we want to examine these for their causal significance to ensure that they are not merely biomarkers for underlying mechanisms that are still unknown. The development and application of AI systems will play a key role in this effort. I am particularly interested in AI models that link routine histopathological findings with molecular and spatial measurements.

It is also important to me that we view the breadth of our research as a strength. Our work is specifically rooted in oncology but also extends to immunology, neuropathology, reproductive biology, and hepatology. If we truly want to understand cancer, we must take this broad context into account so that findings and mechanisms can be generalized for the greatest possible benefit.

In addition to the focus on causality in cancer research and the integration of other disciplines, there is something else that is very important to me: the training of young scientists—and, ideally, those who are also actively practicing clinicians. I have found that clinician-scientists—who can simultaneously address a clinical question and apply a computer-based method—are crucial for the future of translational research. This professorship provides me with the perfect framework to foster such careers and advance translational research in the long term.

Speaking of translation: To what extent does your research—in addition to your efforts to support translational careers—align with the BIH’s translational mission? How might patients benefit from your work in the future?

In the future, we not only want to develop tools for analyzing spatial omics data, but also to anchor our spatial oncology program in clinical practice. This means we will apply spatial technologies on a large scale to defined clinical questions and further develop these technologies so that they actually benefit patients. Most spatial and single-cell results never reach patients because they cannot be independently reproduced. Work on quality control, benchmarking, and uncertainty assessments is crucial for translation. After all, translational projects can fail silently at this very stage. For this reason, I also view this work as part of translational research and not merely as one of its technical precursors.