In a collaborative study between Dr Mattias Farlik at the Department of Dermatology and Assoc. Prof. Michael Bergmann from the Department of General Surgery (both at Medical University Vienna), the authors present a model system for the study of colorectal cancer. The in vitro co-culture system includes cancer cell organoids, fibroblasts and monocytes/macrophages isolated from individual patients, and provides a dynamic environment for studying phenotypic changes in cell populations as well as effects of treatment intervention.
Here, one of the project’s lead researchers, Dr Anna Kusienicka, outlines how the single cell RNA sequencing component of the study, analyzed using Trailmaker™, was critical in reaching their experimental conclusions and publishing their data.
How did you come to use Trailmaker for your data analysis?
As a non-bioinformatician wet-lab scientist working with single cell data, I was playing around with user-friendly tools and found that Trailmaker offered much better visualizations compared to other tools like Loupe browser. Since Trailmaker supports data generated from multiple technologies, it was a perfect fit for our project.
How did Trailmaker contribute to advancing your research project?
The goal of our study was to develop a novel model system for studying treatment-responses in colorectal cancer. In the first step, we co-cultured cancer-associated fibroblasts (CAFs) isolated from colorectal cancer (CRC) patients with monocytes to test how CAFs shape the polarization of myeloid cells. We used single cell RNA sequencing, analyzing it with Trailmaker, to determine the cell types and their transcriptomic profiles. We discovered that CAFs instruct monocytes to gain tumor-associated macrophage (TAM) features. At the same time, monocytes induce an inflammatory phenotype in CAFs, so the crosstalk between both cell types is bidirectional. We further used these discoveries to establish a triple co-culture system with monocytes, CAFs and patient-derived organoids (PDOs), creating a unique precision medicine tool for studying the interaction between those cells under different therapies.
Once the in vitro system was established, what did you aim to achieve with Trailmaker next?
Next, we used our system to study the early treatment responses to chemotherapy and oncolytic virotherapy. This unique precision medicine tool, which combines CRC patient-derived organoids (PDOs), CAFs, and myeloid cells, enables us to investigate interactions between these cell types under various therapeutic conditions. For this purpose, we made use of the differential expression and pathway analysis tools within Trailmaker, which led us to the key findings in our paper: i) Chemotherapy induces immunomodulatory phenotypes in TAMs, resembling those triggered by oncoviral therapy, and ii) CAFs play a crucial role in therapy responses via conservative upregulation of TNF signals. These findings were further validated on a bigger CRC patient cohort on protein level.
What is the translational significance of your discoveries for colorectal cancer patients?
Our novel model enabled us to study the effects of commonly used chemotherapeutic treatments on immune and stromal cell populations. We found that some chemotherapies that are known to have long-term negative impacts on immune populations actually cause the activation of macrophage populations after short-term treatment. This is a fascinating discovery that might influence how we approach chemotherapy treatment in the clinic. Further investigation is now required to tease out the underlying mechanisms that control these gene expression changes. Furthermore, our novel model can be used to study the effects of other therapies, including immune checkpoint inhibitors and combinatorial therapies.
Meet Anna
Anna is a senior postdoctoral researcher in Dr Mattias Farlik’s lab at the Medical University of Vienna.
She is passionate about applying novel RNA sequencing and epigenetic techniques to clinical studies, with the goal to advance our understanding and treatment of cancer.
“Trailmaker really helped me to navigate the sequencing data with ease!”
Now that your study is published, what’s next?
We are planning to further investigate mechanisms underlying our findings and to use our novel model to study more treatment options for CRC. Trailmaker has been incredibly simple to use and helped uncover molecular mechanisms and visualize complex datasets. I look forward to continuing to use it as we generate new data and prepare for our next publication.
Read the full study
The publication can be read in full at the link below:
“Cancer-associated fibroblasts shape early myeloid cell response to chemotherapy-induced immunogenic signals in next generation tumor organoid cultures.”
Julijan Kabiljo, Anna Theophil, Jakob Homola, Annalena F Renner, Nathalie Stürzenbecher, Daphni Ammon, Rebecca Zirnbauer, Simone Stang, Loan Tran, Johannes Laengle, Askin Kulu, Anna Chen, Markus Fabits, Velina S Atanasova, Oliver Pusch, Wolfgang Weninger, Henning Walczak, Dietmar Herndler Brandstetter, Gerda Egger, Helmut Dolznig, Anna Kusienicka, Matthias Farlik, Michael Bergmann.
Journal for ImmunoTherapy of Cancer; doi: 10.1136/jitc-2024-009494 https://jitc.bmj.com/content/12/11/e009494
The associated press release is accessible via the following link: https://www.meduniwien.ac.at/web/en/about-us/news/2024/news-in-november-2024/novel-model-enables-research-of-individual-immune-responses-for-colorectal-cancer/
