The Many Fates of T Cells with CRI Lloyd J. Old STAR Enrico Lugli, PhD

T cells are some of the most important human cells when it comes to cancer immunity. They come in a variety of types—killers, helpers, progenitors, and suppressors, to name a few—and their balance in cancer plays a large part in dictating how someone’s disease will progress and how they respond to immunotherapy.

To help us better understand why certain types of T cells predominate in tumors, Enrico Lugli, PhD, a CRI Lloyd J. Old STAR at the Humanitas Research Foundation (Fondazione Humanitas per la Ricerca) in Italy, is studying how different T cell lineages develop. Specifically, he is parsing what mechanisms promote the generation of pro-cancer versus anti-cancer subpopulations. Through discoveries that uncover ways to nudge T cell development in more favorable directions, Lugli—the principal investigator of the Laboratory of Translational Immunology and head of the Flow Cytometry Core at Humanitas—hopes this will guide clinical strategies designed to prime  the immune system into the right state and allow more patients to respond better to immunotherapy.

Recently, we spoke with Dr. Lugli to learn more about his exciting research.

Video TRANSCRIPT

Arthur Brodsky, PhD

Hi, I'm Dr. Arthur Brodsky, assistant director of scientific content at the Cancer Research Institute, and today I'm grateful to be speaking with Dr. Enrico Lugli, a CRI Lloyd J. Old STAR at the Humanitas Research Foundation in Italy. Welcome, Dr. Lugli!

Enrico Lugli, PhD

Thank you Dr. Brodsky for the invitation. Great pleasure to be here today.

Arthur Brodsky, PhD

Glad to have you. As a CRI STAR, you're exploring one of cancer immunotherapy's central paradigms, that cancer-killing T cells can become exhausted and dysfunctional against tumors over time. But through checkpoint immunotherapy, we aim to overcome this exhaustion. Along those lines, you recently discovered rare subpopulations of T cells that behave similar to stem cells. Unlike the T cells that can become exhausted, these T cell populations can maintain their ability to self renew themselves and are crucial to the immune system's ability to eliminate tumors, especially over the long term.

What do we know about these stem-like T cells and the factors that determine the exhaustion-versus-self-renewal balance, and what more do we still need to know about them?

Enrico Lugli, PhD

Thanks for the question. This is a very critical point because it started more than 10 years ago, when I was a postdoc. We identified a population of stem-like cells in healthy individuals, and then the work of many other people later on also found that in chronic infections in tumors, you find pretty much the same hierarchy of differentiation. It was very good to know that we have a population which has exhaustion traits, but at the same time can self-renew and differentiate.

It actually turned out that this population is among the memory cells, one of the major targets of immunotherapy. What we know is that this population can actually respond very well to anti-PD-1. We know that this population can self-renew and act as a sort of progenitor of the terminally exhausted cells. We also know that these cells have at the same time– this is critical, because they have this sort of hybrid phenotype, because at the same time they have stem-like traits–it seems a paradox–but stem-like traits but at the same time dysfunctional traits. This is determined at the level of epigenetic modifications. What we don't know, for example, is how these epigenetic modifications can be somehow overcome.

One thing that we have shown, and also other people have shown, is somehow these cells, even though they have this stem-like fashion, they're committed to dysfunction. So when you stimulate them, when they respond to immunotherapy, somehow they condemned to become terminally dysfunctional. It's difficult to have a function which is maintained in the long term. At least this is from the data in mice, the data in humans is much less clear because obviously the number of assays that we can do, it's much more difficult. Trying to identify, for example, what are the mechanisms that can overcome this imprinting in the population will be very important in the future.

Arthur Brodsky, PhD

The other side of the coin is, in contrast to these cancer-killing T cells that you want to minimize the exhaustion and promote their ability to self-renew, as well as be effectors that can go out and kill cancer cells. On the other side, you have regulatory T cells or T regs, that can actually help tumors survive by suppressing the immune responses against them. Do these T regs also have different subpopulations that can either become exhausted or long-lived and self-renewing? If so, how do they factor into the equation?

Enrico Lugli, PhD

Work from our collaborators in Milan–we have also advanced this even more, we have a phenotype in tumors which is very different compared to the peripheral blood or other tissues–

Arthur Brodsky, PhD

For the T regs?

Enrico Lugli, PhD

About the T regs, yes. For some reason these T regs are hyperactivated in tumors, are constantly activated and we have found heterogeneity, so they don't look alike. There is subsets, so there's different populations. We have found hyperactivated T regs, we have found more quiescent T regs, so that means T regs that probably are bystanders, but we don't really know very much. The subpopulation looks very hyperactivated and we have shown in collaboration with colleagues at the University of Melbourne, if you remove some proteins, which are called transcription factors–these are proteins that control the genetic architecture of a cell–if you remove these transcription factors, this hyperactivated population disappears and you can induce anti-tumor immunity and that's very important. That suggests that you have a target, or at least a number of genes that can be targeted in this way.

We have heterogeneity in that population, and T regs, we hope, will become the next target of cancer immunotherapy. There is very much hope, at least from preclinical testing. There is now some Phase 1 clinical trials. We don't have the data yet, but it looks like a very promising target to boost the immune response. The reason is because this population is so much suppressive. You find the cells pretty much in all the tumors and they have more or less the same phenotype, even though you might have some differences from tumor to tumor. If the behavior is the same, the important thing is ideally you could develop a drug that can target the same population in different types of cancer as, for example, anti-PD-1 might work for different types of cancer. It works in melanoma, it might work in renal cell (kidney) cancer, it might work in non-small cell lung cancer. Obviously, with different success rates, but still, the same drug ideally could be targeting the same population in different types of tumor, and that's the potency of immunotherapy.

Arthur Brodsky, PhD

That's exciting. It makes sense that just as you'd want to support the good cells, you'd also want to block the bad cells, in this case the T regs that are helping to suppress the immune response against the tumor. As you learn what makes the cancer-killing T cells behave in the way that you want them to, and what would make the T regs behave in the way that you want them to, as you as you learn to fine-tune the molecular programs of these different T cells, how might this aid the development of future immunotherapy strategies, including cell therapies?

Enrico Lugli, PhD

The field, as it was very much in the last decade, it really exploded with the capability to analyze one single cell at a time. Before it was done at the level of bulk populations. That means you identify a population, you isolate that population, you characterize the population. It's like taking people from a country and then you compare it–

Arthur Brodsky, PhD

Like an "average" person that doesn't really exist?

Enrico Lugli, PhD

Exactly. In this way, we can see every single person and every single cell and the behavior of every single cell. All the cells don't look alike, but they tend to cluster in subpopulations, and these subpopulations tend to have similar features. If you can pinpoint exactly the specific population which is most important, for example, for responding to tumor, or which is most important to suppressing the immune response, then you can have a more specific drug or a more specific approach to boost the anti-tumor immune response. That's the important thing.

At the same time, you can develop more effective immunotherapies, ideally in combination. As we talked about, stem-like memory cells, we know that those cells respond to anti-PD-1, but at the same time they have a lot of other proteins on the cell surface that we call co-stimulators. That means it's proteins that can help the immune response. Ideally, if you use two drugs, targeting, PD-1 on one side and a co-simulator on the other side, you can boost specifically that population, but not others that might not be very useful. That's the beauty of the system.

Arthur Brodsky, PhD

As you pursue these goals, which from hearing you describe it, it's easier to look at the average population of T cells, it takes a lot more work to look at the individual ones. But that's the kind of the precision that we will need to be able to help more patients. As you're pursuing this, can you explain why this CRI STAR funding is so important? Is this support enabling you to pursue things that you might not have been able to otherwise?

Enrico Lugli, PhD

First of all, it is very generous in terms of funding. We are really honored to be supported by this important international agency. I was very honored and humbled to be judged by pioneers in the field of cancer immunotherapy. That's very important. It's a great recognition also for the work that we have done in the past five to six years. This is just a premise that I wanted to give.

The beauty of this funding is it gives you the freedom to pursue your ideas. It is not really tied to a specific research project. Obviously, when I submitted the grant, I had to propose an idea, but it's not really tied to a specific research project. For example, if tomorrow we go to the lab, we do an experiment which gives you a result which is completely unexpected–and I have to say that most of the time it works like this–we can really follow that idea without thinking too much (about how we will get funding for it). CRI gives you that freedom. For us, the freedom for our mind is probably the most important thing that we want to have in the lab. We're really working at the edge of what is known and what is unknown, and when you enter the world of the unknown you don't really know what you're going to find. Sometimes the best discoveries were made by accident. In other cases, because scientists made mistakes. We really want to have that freedom and CRI grants that freedom. That's very important.

Arthur Brodsky, PhD

That's a great point, certainly. We have ideas, we have our educated guesses, and we look at the best available evidence and data to try to make a logical assumption about what the truth is actually, but you don't really know until you start exploring. Like you said, there's always lots of surprises, so that's great that you'll be able to follow the science wherever it points you.

Enrico Lugli, PhD

I just want to say that we're not really doing things by chance. That's important to say. We do something which is called hypothesis driven. We have an idea, we work on the shoulder of giants, as other people have said in the past. We rely on the data that were published by other people and we build on those data. And we make hypotheses, so we think it's going to be like this. Then we go to the lab, we test that and we follow the data, that's very important. We follow the data, and we follow the results and we interpret the results by talking also with other people, with other scientists, and exchanging ideas. Then we think, okay, so it might be a or b or c, and then we try maybe all of them, and then we'll see what gives us the best and most interesting result. Then we go down that way.

I think it's important to have an open mind, and not try to demonstrate what we think is going to happen, which in 90-95% of the cases it's not like that. We need to be open, we need to be critical, as much as possible.

Arthur Brodsky, PhD

It's nice, as you mentioned, that when an unexpected result does arise, or new discovery or interesting fact does arise, you can pursue that without having to write new grants and wait to see if it'll be funded and all that.

Arthur Brodsky, PhD

Just go after it. Now, looking at the big picture, what do you hope to accomplish over the next five years as a CRI STAR, and how do you hope that your work will impact the field?

Enrico Lugli, PhD

First of all, I hope that it will impact the field. We want to invest our time and resources in a couple of ideas that you mentioned. On one side, try to understand what are the molecular mechanisms that are the basis of successful responses. Why do patients respond to immunotherapy, which are the cells that respond to immunotherapy, and what are their characteristics? If you identify their characteristics with precision, then you can build new cells. What do I mean? You can take the– that's something that we do all the time in the lab, we take the blood of a patient, we can modify the characteristics of the cells, for example, by using gene transfer, by using small molecules, and you can direct differentiation the way you like by using these tools. Then you analyze those characteristics by using technologies like genomics or flow cytometry, and all these interesting tools that we have. Then we test the cells in an approach that we call adoptive immunotherapy.

That's a very potent immunotherapy approach. Basically, you take these cells, you transfer them into an individual, or at the preclinical level into– you can do this in vitro or in vivo. Then you see how these cells can control a tumor. You can mine these immune responses in this way, by directing differentiation in one way or the other. On the other side, we have also the suppression effect that we know exists and is very important. We try to understand what are the characteristics of the suppressive cells and in that case, we want to inhibit. Instead of boosting we want to inhibit. We aim to identify these molecular mechanisms, so on one side we can boost, on the other side we can inhibit, for example, by doing maybe a combinatorial approach, which will be able to have much more tumor regression than we're used to having right now.

Arthur Brodsky, PhD

I really look forward to following your work and can't wait to see what you discover and what your work reveals. Thank you again, Dr. Lugli for taking the time to speak with me today.

Enrico Lugli, PhD

Thanks for inviting me. It was a pleasure.

Arthur Brodsky, PhD

Of course, and great luck with your work!

Enrico Lugli, PhD

Thank you. Thanks again to the CRI.