This alongside discussions on industry – academia collaboration, among other things. All of this together is not only good research; it also makes a compelling image of the way immunology research is organized and approached. The notion of the need to map the dynamics of cellular processes in time and place runs like a thread through all topics.
Reading Sjoerd Schetters' thesis might seem confusing. It covers research about bacterial vaccine compounds like Outer Membrane Vesicles (OMVs) and Inclusion Bodies (IBs) from genetically engineered bacteria, Mouse DC-SIGN receptor targeting, tumor micro-environment PD1 Immune Checkpoint Blockade (ICB) and even some glycobiology. Could this be a collection of research articles written by different researchers operating under the 'Sjoerd Schetters' nom de plume? No, it turns out, Schetters is one highly collaborative person, originally trained as a neuroscientist. In his PhD research he was tasked to find new vaccine strategies to induce Dendritic Cell (DC)- mediated T cell responses against high grade glioma and melanoma, with a focus on DC and T-cell functioning. He did this in the group of professor Yvette van Kooyk in Amsterdam. It led to some adjuvants and antigenic compounds that enhance the binding of the vaccine to DC-SIGN on DCs, thus improving the vaccine's effectiveness.
“These data supported the development of a cancer treatment vaccine”, Schetters comments. “It hypothesized that when the vaccine preferred DC-SIGN binding on Dendritic Cells, this would induce a better anti-tumor T-cell response. In an in vivo setting, you have to establish if there is DCSIGN on Dendritic Cells. It turned out there could be. However, these Dendritic Cells were differentiated out of high plasticity monocytes that are present in the blood and not in tissue. In case of inflammation induced by adjuvants, these monocytes can differentiate to all sorts of cells, including Dendritic Cells.” The question thus arises what you're actually looking at when you establish the presence of certain cells in a particular compartment at a given point in time. The concept of molecular dynamics and cellular differentiation over time and location unites several chapters of the studies in the thesis. Schetters: “It represents a complication that explains why theories based on conventional 'static' or 'snapshot' research often doesn't deliver on expectations. Whereas the resolution of single time point measurements increase (single sequencing techniques), the temporal variable is still underappreciated.”
The experience in this research inspired Schetters to think at a more aggregated level about the immune system, but also about the goal of academic research. His conclusion: successful prophylactic vaccines seldom come from an academic setting, as academia aims at knowledge and scientific publications and not at maximally effective and safe vaccines as output. Schetters: “The immune system is extremely dynamic. As yet, there is just not enough fundamental knowledge on the immune system in academia to be able to operate as orchestrator; to predict and manipulate at every level of analysis. We cannot learn who plays what instrument in the immunological orchestra and what melody, as long as research is carried out as 'making snapshots'. It's too static.” “In the present academic setting, when a vaccine doesn't work, there are just too many options 2 explaining the failure to sort it out systematically”, Schetters concludes. “So, the next step is: repeating the same experiment with another immune regulator or vaccine antigen, for instance. In reality, it's making a new prediction, instead of systematically mapping the dynamics of cellular processes in time and place. When it does work, we call it rational vaccine design.” In fact, Schatters says, the Nobel Prize-winning idea of immune checkpoint blockade was based on fundamental research and its precise immunological mechanism is still not fully understood, regardless of clinical success. Super-specialization in academia is part of that equation. When you're overspecialized in a topic, as is often necessary, you are highly dependent on luck for breakthroughs. The breakthrough is either looming in your field, or it is not. In case of superspecialization and bad luck, it means you're out. Schetters: “But when you look at things from a more aggregated level, however, a failure at one point might hint at a possible win at another point. Rejecting the null hypothesis as fiercely as possible should be the goal, not trying to fulfil predictions. Even Einsteins predictions turned out wrong.”
Which compound will work best? “We cannot predict that”, Schetters concludes. “Unfortuntely, the explorative power of academia is not optimally linked to the executive power of pharma. It is too laborious and too expensive for academic scientists to systematically analyse multiple compound candidates. Pharma does have the funds for this. Academia could, however, fuel the direction of this compound testing in pharma, if both parties would be better aligned. The link would perhaps be stronger if the goals and rewards would not be so different. Also, the fact that data from big pharma experiments remain confidential is a brake on progress. It would be worthwhile to work on a better knowledge chain between academia and industry.” For prophilactic vaccines the bench-to-bedside fail rate is 94% and the average cost estimated between 165 and 289 million dollars. With these odds, academics seem to be poorly equipped to find the cure, Schetters concludes. “As academic scientists we cannot predict which compound will work best, it just needs to be systematically approached, which is too laborious and expensive for the charity case of academia.”
Schetters presently does research on eosinophils in asthma as part of the group of Bart Lambrecht at the Vlaams Instituut voor Biotechnologie (VIB) in Ghent. It is not yet known whether sub-types of this cell type exist. “My question is therefore: are there? Snapshot static research doesn't provide the answer. It doesn't tell you whether a certain cell migrated from the blood a day before, was already present in lung tissue and differentiated at some point. Four cell types measured at one point in time could well be the same original cell type changing over time in a dynamic manner.” Schetters states that his present employer invests a lot in aligning academia with the biotech industry. Fundamental research into disease goes together with a systematic search for the right target to disrupt the chain of events causing disease. “Look at disease as a tower of building blocks. Pull one block out and the tower collapses. When you look at the tower as a whole, by taking the entire complexity into account from foundation to spire, it allows you to select the best block closest to the foundation to hammer out. Looking at just one block dismisses a lot of complexity and offers a slimmer chance of finding a long-term solution.” In this setting it isn't by accident that the VIB also has a strong focus on deploying novel technology. It even has a specialized “tech-watch” team actively scouting and optimizing new technologies. New technology platforms such as single cell RNA sequencing (scRNAseq) enable enlarging the picture. “By using scRNAseq at different time points and from different organs, it allows you to follow a certain cell type, from for instance blood at some point to tissue three days later. It is still very challenging to describe this time-dependent change computationally, but it is where we're heading and it has already proved its case for our eosinophils.”
Leendert van der Ent