Single Cell Analysis and Transcriptomics in Colorectal Cancer

At the 2023 World Congress on Gastrointestinal Cancers, Sabine Tejpar, MD, PhD, University Hospitals Leuven, Belgium, gave a keynote address on the application of single cell analysis and transcriptomics to colorectal cancer.

Dr Tejpar explained colorectal cancer has "all kinds of features and facets and cell types," adding, "we strongly believe that knowing each of the states of these cells will lead us to better therapies and to better prognostication."

Transcript:

Hi, everybody. My name is Sabine Tejpar. I'm a GI oncologist from Leuven in Belgium. I'm here at the 2023 World Congress on GI Cancers in Barcelona. And I just gave a talk on a rather complex issue, single cell analysis in colorectal cancer. But to phrase why we do this, it's basically trying to peel away the layers of a disease, which is considered just a nomer, it's colorectal cancer. But it has all kinds of features and facets and cell types that are there. And we strongly believe that knowing each of the states of these cells will lead us to better therapies and to better prognostication.

Let's give it some more detail on what I mean. In this case, I talked a lot about epithelial cells. Epithelial cells are the cells that are also there in your normal colon and then they form polyps. There are the mass that forms the polyp, and then they are the mass that forms the tumor. Those epithelial cells, how they evolve from the normal state to the polyp state then to the tumor state, and specifically, what is the worst for the patient, is when the epithelial cell actually leaves the tumor, and can enter into the bloodstream, and then becomes metastatic, the metastatic state. And by studying that, all those states in extreme detail with technologies, which are only possible in the last few years, this would've been impossible a few years ago, we do start to see all kinds of patterns and rules which are repetitive across patients and which are telling us a lot about the addictions of D cells. The very early cells are in state A, B, C, and the later cells are moving more towards another state, et cetera.

We do see differences across patients, but also non-random. Today, we can really say patients belong to a certain set of subcategories, which we can now easily name and recognize. And with within those categories, we are seeing very specific biologies. And so, that's one take home message already. I'm very hopeful on the diagnostic part, that instead of just going, "you have colorectal cancer," we will absolutely be able to give you a very clear name to what subset of the disease it is. And the second part is get to the point of even identifying which cells are specifically in your tumor. Why is that important? Because cells are in a transitioning state. You have to imagine that going from polyp to tumor, to metastasis is a continuous transition. And so, when you catch a patient at diagnosis, he's somewhere in that transition stage. That's the second part we're trying to see, to look deeply at the cells of the patient and say, "you are in this or that transition state." Not only you get a very correct name of your disease—and they're quite different among each other, these colorectal tumors—but also, we give you a chronology time of where are you on this axis of going from very friendly little polyp to an aggressive cell that could actually migrate into your blood. That's on the diagnostic side. I think a lot of very important work that needs to be done, and we try to lay, let's say, the foundation for that.

But the second part that is really interesting for us is to understand what allows these cells to evolve. Every time you have to evolve, just even in Darwinian evolution, there's a trade-off. You can't just evolve on your own. You lose certain features, you gain some features, you do this evolution thanks to some help and pushes and evolutionary pressures. We do hope that there's actually a system to that and we think we can start to see that certainly it's non-random. And targeting the system would be our ultimate aim. Really saying, these are the pressures that are driving to this state, that state that we really don't want the cell to reach, and how can we stop that?

And those things which we first described= very well in the humans, and then we found models. Then we take cell lines, but also mouse models that we analyze in the same way, to then do the manipulations on. That's the next stage we're slowly getting into. We've identified the models, both in cell lines and bias, that are really recapitulating all those different cell types and stages. And that's where we're starting to do manipulations and also can do drug screens to identify how you can deviate those paths. In a nutshell, that's kind of what we're doing.

I just want to give a bit of a context: I spoke only about epithelial cells, and that's the second thing I said in my talk — for me, it's important to start with epithelial cell, because it is driving the whole system. The very popular immune cells and the very popular fibroblast, they're basically following the cues of the epithelial cells. I think you really have to figure out the epithelial cell very well. And the others are just logical nearly consequences of those states. But of course, all 3 cell types are identifiable, describable, and targetable. You can describe the whole ecosystem. But I think the lead and the evolutionary pressures and the evolutionary memories, very important, memories are in the epithelial cell. You see, I personify colorectal cancer very strongly: enemy number one. But we just chipping away at this with these new technologies. I think there's a lot of hope in redefining the disease and then completely out-of-the-box approaches also.

Thanks for listening.

Source:

Tejpar S. Single Cell Analysis and Transcriptomics. Presented at the 2023 World Congress on Gastrointestinal Cancers; June 28-July 1, 2023; Barcelona, Spain.