Systems oncology is the future

Dr. Juliane Winkler is head of the Lab for Tumor Heterogeneity and Metastasis at the Medical University of Vienna. She is a licensed pharmacist and did her PhD at the University of Heidelberg.

How would you describe your research?

Metastasis is a multistep process that ultimately leads to the formation of a secondary tumor in an organ distant from the primary tumor site. This process involves not only intrinsic features of the primary tumor and the extrinsic tumor microenvironment such as immune, stroma cells, and the extracellular matrix but has systemic consequences on the whole body.

In my lab, we are using technology-driven systems oncology approaches that lead to meaningful insights into the complex biology of metastasis. We develop and apply single-cell and spatial omics technologies to better understand how tumor heterogeneity and plasticity contribute to metastasis, how the distant tissues are remodeled to host disseminated tumor cells, and why metastases are often therapy-resistant.

How did your research project comeabout?

I am fascinated by the complexity of cancer and in particular metastasis. During my PhD, I first heard about tumor heterogeneity at a conference and realized: the more details we learn about the tumor also enabled by the breakthroughs of technology developments and sequencing the less we are capable of understanding the complexity that unfolds in front of us.

In the context of metastasis, it is of most importance to consider cancer as a systemic disease that impacts immune cells, stroma cells, and distant organs – cancer changes the whole body. Therefore, I decided that a reductionist approach of studying one gene or pathway in a very narrow context won’t give me enough insights into how this process works.

In my lab, we are collecting as much data about the metastatic process as we can and are applying machine learning to detect features that can explain why certain tumors metastasize while others do not. With this systems oncology approach, we hope that we will provide new angles for our understanding of the metastatic process to help design innovative therapies.

Which aspect especially distinguishes your job from others?

I am a full-hearted researcher. I love the freedom of designing my research projects and strategies that I think are the most relevant and excite me. I am always on the lookout for a new challenge, a new technology, or a method that we can apply to understand metastasis better.

I am excited about trying and learning something new every day. I think in my job it is crucial to be curious and capable of learning quickly from others and being creative on how to apply this new skill in a different context. I love working with people from whom I can learn and who are just as excited as I am to jump into cold water and eventually learn to swim.

What does the future look like for your research?

We now have new technologies available such as single-cell and spatial omics that can profile tumor tissues while preserving the integrity of the tissue. Applying machine learning to this multifaceted data gives us unprecedented opportunities to study the complexity of metastatic progression on a completely new level and incorporate more tissue samples from patients to study the process in the original context.

We are currently generating our own datasets to answer our particular research questions. With the increasing availability of relevant datasets, we can mine and reuse these for many different research questions.

I think my lab and cancer research as a whole will move more and more in the direction of data science and computational biology. We will use machine learning and take advantage of carefully curated datasets and cell atlases to predict biological functions and therapeutic vulnerabilities. This will completely change how we design projects and experiments in the lab. These are fascinating times for scientists.

I am very excited to train the new generation of researchers enabling them to take on this challenge.