Interview with Interview with Lisa Schweizer and Thierry Nordmann, Department "Proteomics and Signal Transduction", Max Planck Institute of Biochemistry
Proteins are frequently called the building blocks of life because they are found everywhere, including in our cells. This makes them an important factor when it comes to diseases. As a result, mapping the protein landscape within cells and analyzing their individual composition can be a crucial ally in the fight against cancer and other diseases. Now, a German-Danish team spearheaded by Matthias Mann has developed a method that provides researchers with unprecedented insights into cancer.
Lisa Schweizer, co-author of the study, and Thierry Nordmann from Matthias Mann's research department at the Max Planck Institute of Biochemistry explain what is meant by "Deep Visual Proteomics" and what significance protein analysis can have for personalized medicine.
Thierry Nordmann and Lisa Schweizer are both in the team of the research department "Proteomics and Signal Transduction" at the Max Planck Institute of Biochemistry. Together with Danish researchers, the team led by Prof. Dr. Matthias Mann has succeeded in revolutionizing cancer diagnostics.
What is Deep Visual Proteomics?
Lisa Schweizer: Deep Visual Proteomics (DVP) is a multidisciplinary approach that combines high-resolution imaging, artificial intelligence (AI) – guided image analysis and the latest single-cell mass spectrometry (MS) to study cellular heterogeneity in tissues. To accomplish this, we have merged the expertise and skills from several countries and developed a novel technology under the direction of Professor Matthias Mann and the two first authors Andreas Mund and Fabian Coscia. This now allows us to study the proteome of a particular tissue with a view to disease.
Thierry Nordmann: The proteome is the protein composition in a cell, a tissue or a whole organism. Until now, tissues with many cell types were analyzed as a single unit. Now, instead of looking at the big picture, we can look at individual pieces of the puzzle, individual cell types, separately. It is important to understand that there are specific sets of proteins in each cell that are responsible for the function or even dysfunction of a cell. With DVP technology, we will better understand the progression of a disease and thus hope to revolutionize the field of MS-based proteomics.
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Why did you combine these four specific technologies?
Lisa Schweizer: For our DVP, we can use any tissue from routine clinical care, especially formalin-fixed and paraffin-embedded (FFPE) specimens. First, sections of these tissues are illustrated using high-resolution imaging. Based on these images, machine learning and artificial intelligence algorithms are then used to classify the cells of the respective tissue structures. Guided by an AI-generated template, individual cells of interest are subsequently extracted from the tissue via precise laser cut and collected within the predefined cell type. Thousands of proteins in these samples are classified by using ultra-high sensitive mass spectrometry and can be back-projected onto the original image information – like onto a map.
Thierry Nordmann: This allows us to go beyond conventional immunohistochemistry or immunofluorescence and analyze the thousands of proteins present in the cell populations without the need for prior knowledge or a hypothesis.
Lisa Schweizer: The research groups of Professor Matthias Mann have specialized in technological developments in mass spectrometry for decades. These advances are critical in this setting. The recently achieved sensitivity of the instruments – which we played a big part in co-developing – enables single-cell proteome analysis in a time-efficient manner. Another key aspect is bioinformatics analysis, which we use to generate maps of proteins that provide spatial resolution of protein signatures across highly complex diseases. Our technology provides researchers and clinicians with valuable, protein-based information to understand the mechanisms in health and disease in a greater detail.
Proteomic analyses can be used to visualize mechanisms that drive tumor development. However, the technological progress of mass spectrometry was also decisive for this.
What significance could this methodology have for personalized cancer medicine?
Thierry Nordmann: The spatial resolution of the proteome plays a key role, especially in cancer. While every cell in a tumor is part of the disease, certain subpopulations of cells drive tumor malignancy and foster the invasion of surrounding tissues or metastasis. By differentiating particular cell types in tumor tissue, we can identify the role of different signaling pathways and even individual proteins within the tissue architecture. The technology allows us to compare the regions near blood vessels with the initial tumor area and identify processes that contribute to metastasis at distant sites. The precision of our laser system also facilitates an improved extraction of tumor cells from the background of the target organ and enables us to trace the cells back to where they started, meaning the primary tumor site.
Lisa Schweizer: DVP is taking us closer towards making personalized medicine a reality since we can extract malignant cells and compare them directly with surrounding healthy cells. We can also track the tumor development through the tissue structure and visualize the different cell populations and their characteristics. Not only does this deepen our understanding of the factors that influence tumor heterogeneity, but it also allows the identification of individual disease-associated mutations. Although we can classify cancers based on the site at which they started and their gene expression profiles, thanks to factors such as environmental forces, every tumor is truly unique - just like every human being. Accordingly, with the help of our technology, the tumor of an individual patient could be dealt with in a much more individualized way, and this in turn could be treated in a more effective manner.
Could the deep visual proteomics method also be applied to other diseases besides cancer?
Thierry Nordmann: Definitely! Our technology facilitates the characterization of any disease in which spatial resolution in tissue plays a role. Automation and reproducibility of all processes of our technology make it possible to apply the concept to a broad range of unanswered questions – also in medicine.
Lisa Schweizer: We also don't just limit ourselves to diseases, but also include the characterization of tissues and their underlying biology. The field of so-called 'omics' technologies examines the architecture of tissue at the DNA or RNA level as it pertains to the cellular components. Now, DVP allows this field to also extend the analysis to the proteins. Unlike genetic information, the latter are the cell’s executive force.
In summary, with our technology, we hope to push the boundaries of what is possible in proteomics and, in particular, to better understand complex (cancer) diseases.
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