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Recent work by the team of Peter Carmeliet (VIB-KU Leuven Center for Cancer Biology) has pushed the boundaries of cancer research forward. They expanded their pioneering work on endothelial cells by providing an even more detailed, single-cell look at the cells and the blood vessels they line. The team used an array of high-end technologies, single-cell and bulk RNA sequencing, mass cytometry, proteomics, big data analysis, as well as functional testing of identified targets. Their description of distinct subsets of endothelial cells and blood vessels is an important addition to our understanding of the vasculature’s functions in health and disease, especially considering the changes in blood circulation in and around tumors. Their work has already resulted in four papers in top journals. We spoke to Peter about the accomplishments of his team.

Where did the idea for this research come from?
Peter: “As every organ resides in a specific micro-environment carefully adapted to meet the organ’s physiological needs, it is widely accepted that blood vessels are also phenotypically adapted accordingly. However, exactly how extensive these tissue-specific adaptations are has remained largely in the dark. Therefore, we aimed to categorize the vasculature on a cell-to-cell basis.”

“Research from our group previously showed that tumor vessels differ from vessels in healthy tissue, but it was unknown up to now which phenotypes constitute the tumor endothelium, what their  distribution is, and how this differs when compared to the endothelium in healthy surrounding tissue.”

Your team generated incredible amounts of data. How do you deal with this ‘data torrent’?
Peter: “The amount of biological data, generated with (single-cell) omics technologies, is rapidly
increasing, thereby exacerbating bottlenecks in the data analysis and interpretation of omics experiments. Data mining platforms that facilitate non-bioinformatician scientists to analyze a wide range of experimental designs and data types can aid the exploration of omics datasets. Therefore, our lab developed BIOMEX, a browser-based userfriendly software suite, designed to facilitate the Biological Interpretation Of Multi-omics EXperiments by bench scientists. BIOMEX is open source and freely available.” It’s an incredible piece of work.

How important were the Core Facilities/supporting staff?
Peter: “Immensely important! This kind of huge data generation and switch of research field is impossible without the efforts of a whole team. It was truly a joint effort, the structural changes, reorganization, and support of the entire lab was needed to achieve these findings.” 

“The Single Cell Core facility of Diether Lambrechts supported us, also Bernard Thienpont’s expertise was invaluable to develop the correct skills and knowledge in our team. We are truly grateful for their invaluable contribution. Our team progressively acquired know-how in data analysis, 10X Genomics GemCode technology, scRNAsequencing, bioinformatics analysis, etc. Combining the expertise of biologists and bioinformaticians not only led to a descriptive cell atlas but also to novel biological insights.”

In a world where time and funding would not be an issue, how would you like to follow up this work?
Peter: “The difficulty is no longer to generate a cell atlas; the challenge is to prioritize from large lists the targets that hold potential for drug development. If funding would be unlimited, I would use these resources to develop new drugs, or at least perform additional functional validation studies to expedite bridging the gap between a top publication and licensing patents to big pharma.”

“An impactful follow-up of this work would be the creation of a human tumor endothelial cell atlas. In fact, efforts are undertaken to start-up this project. Such data would create opportunities to further advance cancer treatment by tailoring the anti-angiogenic therapy to the tumor type-specific endothelial properties. These findings will form the basis of new drugs and personalized medicine. There is a pile of targetsthat could be validated, which potentially could create spin-off activities. A good example hereof is the recent creation of the spin-off company Montis BioSciences, based on scRNA-sequencing data from our lab and the input of Massimiliano Mazzone. Montis will investigate the interaction between immune and endothelial cells, it is the step forward to translate research findings into therapeutic applications."

Peter Carmeliet

Any pleasant surprises along the way?
Peter: “Getting a paper accepted in JASN within 55 days after initial submission on a fast track, after getting glowingly positive reports from six reviewers, or receiving highly enthusiastic feedback from the Cell editor (even before all reviewers had sent in their comments) with the request to resubmit as soon as possible with guided advice on how to revise our paper. Or the multiple spontaneous positive comments and congratulations by email and social media on the  publications, as evidence of their impact in the field.”

Any lessons or envisioned breakthroughs?
Peter: “Biology is even much more complex than we ever thought! The vasculature is known to play a critical role in a wide range of pathologies. Despite vast technological advances and the rise of single-cell compendia, blood vessels were somewhat overlooked until now, hampering detailed analyses of the importance of endothelial variety for blood vessel biology.”

“New tools will enable more singlecell studies, providing insight at a more detailed level. However, the bottleneck in omics approaches is becoming less and less about data generation, but more and more about data analysis, interpretation, and integration. The challenge will be to select and prioritize those candidate genes that are true targets for drug development. For instance, together with Max Mazzone, we are developing new CRISPR-based transgenic technologies to generate many more endothelial cell-specific conditional knockout mice much faster. Similar and alternative techniques will be needed to mine the large amounts of data for further translation.”

Rohlenova, Goveia, Garcia Caballero, Subramanian et al. (in press). Cell Metabalism Kalucka, de Rooij, Goveia et al. (2020). Cell Goveia, Rohlenova, Taverna, Treps et al. (2020). Cancer Cell Dumas, Meta, Borri et al. (2020). Journal of the American Society of Nephrology