Analytical Strategies in Immunology for Cancer and COVID-19 with Dr. Katie Campbell

The past decade has provided proof that the immune system can be harnessed to fight cancer, but many challenges and unanswered questions remain. Among the most critical of the questions that CRI scientists remain committed to answering is: “Why do people have different immune responses to threats like viruses, bacteria, and cancer, or to treatment?”

CRI postdoctoral fellow Katie Campbell, PhD, has been exploring that question in multiple contexts. Working at the University of California, Los Angeles (UCLA) under Antoni Ribas, MD, PhD, a member of the CRI Clinical Accelerator Leadership, she has been characterizing the factors associated with immunotherapy’s success or failure in cancer patients. When the novel SARS-CoV-2 coronavirus began spreading though, she quickly adapted her skills to address the current crisis. We spoke with Dr. Campbell to get the latest on her efforts against both cancer and COVID-19.

Arthur N. Brodsky, PhD:

Hi, Dr. Campbell, and thank you for taking the time to speak with us today. With the support of a CRI postdoctoral fellowship, you are seeking to improve our understanding of why only some patients respond to checkpoint immunotherapy, a type of treatment that can unleash patients’ T cells against their tumors. To do this, you’re trying to identify the factors associated with response or resistance in patients.

Can you share how you came to pursue this work, and the thinking behind your approach?

Katie M. Campbell, PhD:

My work started back in 2018, when I joined the lab of Dr. Antoni Ribas at UCLA. At the time, he was the translational research lead on three clinicals trials using PD-1 checkpoint immunotherapy, either alone or in combination, to treat patients with melanoma. My postdoctoral research is focused on studying the clinical features of these patients and how they’re linked to therapeutic outcomes, particularly focusing on the mechanisms of resistance so that we can better treat these patients.

In particular, my work seeks to standardize how clinical research is conducted with respect to PD-1 immunotherapies. There are more than a thousand ongoing clinical trials using these treatments, both alone and in combination with a variety of other agents. These trials have different sampling protocols, too, so it’s created complicated scenarios with respect to analyzing for trends. Unfortunately, it’s become somewhat scattered and unorganized, so we’re working to help standardize the quality of analyses that can be carried out with these diverse studies.

Initially we’re looking at three clinical trials, and are attempting to standardize the sampling and experimental strategies across these three clinical trials—which are using PD-1 immunotherapy alone, in combination with anti-CTLA-4 checkpoint immunotherapy, and in combination with oncolytic virus immunotherapy. By doing so, we hope to dive deeper into some key questions because these trials allow us to interrogate clinical responses and enhance the power of our statistical analysis by aggregating the results.

We started by sequencing patients’ tumor samples in several ways to see if we could molecularly stratify these patient populations based upon the characteristics of their disease. So, much of my work involves developing the appropriate analytical strategies and then using this information to try to decipher the mechanisms underlying response or resistance to immunotherapy.

Arthur N. Brodsky, PhD:

What kinds of factors and mechanisms are you investigating with regard to their impact on the effectiveness of immunotherapy in individuals?

Katie M. Campbell, PhD:

First, we’re analyzing the genomes of tumors to identify the genetic mutations they possess, and the mutated proteins they produce, which can tell us how the tumor is presenting itself to the immune system and how the immune system is potentially seeing the cancer. In addition to identifying the potential targets that mark tumors as “foreign” to the immune system, we can also look for pathways that are commonly mutated in patients that were either responsive or resistant to treatment, which might indicate that these pathways are important in the context of cancer immunotherapy.

Toni’s lab has already found some genetic mutations associated with resistance in patients, including ones that affect the JAK/STAT pathway and interfere with how cancer cells normally present themselves to the immune system.

We’re also analyzing gene expression, to determine if some genes are either overactive or silenced consistently in a certain group of patients. This allows us to characterize the behavior of cancer cells as well as immune cells within the tumor and get an idea of which pathways might be responsible for the behaviors we’re seeing.

Arthur N. Brodsky, PhD:

Given how many potential factors might be involved in such a complex process, I’m sure your search will benefit from the comprehensive sequencing and data analysis approaches you’re employing. From the cancer patient’s perspective, once you’ve discovered some insights and identified some significant pathways, how might these insights eventually lead to better treatment strategies for them in the clinic?

Katie M. Campbell, PhD:

The first obvious answer is that two of these clinical trials are using other treatments—anti-CTLA-4 immunotherapy in one, and an oncolytic virus in the other—in addition to PD-1 immunotherapy. So, if we can create a global genetic and expression map of what resistance looks like, we can then develop criteria to stratify patients based on their tumor’s molecular features. This knowledge of whether a particular patient is likely to respond to a given treatment could then be used by doctors to improve their clinical decision making.

This information might also enable us to think about how to target the patients who aren’t responding to these immunotherapies. So, if the immune system isn’t infiltrating into “cold” tumors, we can look for patterns that might indicate why, and then think about therapeutic strategies—whether it be another immunotherapy or chemotherapy or radiation therapy—that might be able to target the relevant pathways and make immunotherapy more effective.

Arthur N. Brodsky, PhD:

And if there aren’t existing treatments that target these pathways, your work might at least provide a strong rationale for developing new therapies to target them.

Katie M. Campbell, PhD:

Exactly. One of the most advantageous ways to approach such a rich dataset is to consider what questions can directly be addressed with what we already have. But we’re also thinking about the discovery capability associated with it, which may give us a lot of information about underlying mechanisms as well. So we have to consider it from both angles.

Arthur N. Brodsky, PhD:

Speaking of unveiling new targets, like many others in healthcare, you’re lending your data analysis expertise to efforts to address the novel coronavirus pandemic, in addition to your ongoing work in cancer. Specifically, you led the development of a database of potential coronavirus molecules that could serve as targets for vaccines. How did the skills you’ve honed against cancer come into play with COVID-19?

Katie M. Campbell, PhD:

First, I just want to say that this work was a large and wonderful collaboration between Toni Ribas’ lab here at UCLA and the bioinformatics group at the Parker Institute for Cancer Immunotherapy. We also got some guidance and feedback from some other scientists associated with CRI as we sought to answer an important question about this novel SARS-CoV-2 coronavirus—why are some people asymptomatic, but others experience very severe disease?

Obviously, there are a lot of environmental variables at play, but we wanted to focus on the role of the adaptive immune system. T cells, specifically, because an effective T cell response is very important for recognizing and clearing viral infections as well remembering them to protect against future encounters. And we wanted to know how T cells were seeing cells that were infected by the virus.

Fortunately, we didn’t have to reinvent the wheel because of recent advances in the field of cancer immunology, where there’s been a heavy focus on trying to understand how the abnormal proteins that arise from genetic mutations make tumors appear foreign to the immune system.

We have already developed powerful algorithms to predict which fragments of mutated tumor proteins might make for the optimal targets for T cells to see and eliminate. We’ve used these to design personalized vaccines for patients with cancer, so we considered the fact that we could use them predict how likely it is that certain viral proteins are being presented effectively on the surfaces of infected cells.

When we do this in cancer genomics, usually we’re doing it specific to a single patient, so it’s a pretty succinct analysis. But if we want a vaccine against the coronavirus that works for everyone, it becomes a not-so-trivial task due to humanity’s genetic diversity. Once again, through these collaborative efforts, we were able to perform this large number of calculations to really address this question in terms of whose T cells might naturally be responding successfully against the virus.

Because of the immensity of this data set and the amount of information there, we also wanted to make sure that it was publically available as a resource because there’s only so many questions we alone can address computationally. We wanted to make sure that those addressing questions related to other aspects of COVID-19 could also use this information to either support or guide their ongoing research. The evolution of this resulted in this very rich data set as a public resource.

Arthur N. Brodsky, PhD:

Could this presumably be used to guide the development of vaccines against this novel coronavirus?

Katie M. Campbell, PhD:

I don’t want to overclaim that, but yes, in some ways it could. It could also help us understand why certain people are not effectively clearing the virus. If their T cells aren’t actually seeing the virus—via a system known as the major histocompatibility complex, or MHC—then they may not be successfully clearing it or maintaining a memory response.

Arthur N. Brodsky, PhD:

Now I want to step away from the science a little bit. Can you talk about why you decided to take up this challenge? Was there a specific moment or conversation that really motivated you?

Katie M. Campbell, PhD:

Yeah, a couple things. First, I’m from Pennsylvania. So, seeing everything as it started to unfold in New York—I’m not going to claim to be a New Yorker, but growing up in the Northeast, it was very hard seeing everything from a distance going bad.

Also, my mom, who taught me how to sew as a kid, started sewing masks. She’s up to hundreds of these things and has been sharing them with local healthcare workers and sent them to some of my friends in New York. Seeing her do this was really motivating. It made me think that, while I’m not a medical doctor so there are things that I physically cannot do, there are some ways I can help.

I’m not going to pretend to be an MD I’m not even going to pretend to be an infectious disease expert because I come from a cancer genomics background. But I understood the overlap in my research and knew I had a skillset that could contribute something, even something small to help. And really, science made me feel better under the circumstances.

Arthur N. Brodsky, PhD:

That’s very admirable. It’s very inspiring to hear how you and so many others in the scientific community have risen to the challenge and have been determined to pitch in any way you can during this difficult time.

I’m sure it’s also been great to have someone in your corner like Toni Ribas, someone who has been a great leader—as both a clinician and a researcher—in the cancer immunology community. [Editor’s note: For his career achievements, Dr. Ribas received the AACR-CRI Lloyd J. Old Award in Cancer Immunology in 2018.]

What’s it like working with him, and how important has his support been?

Katie M. Campbell, PhD:

Toni’s the best. As a mentor, he’s one of the most supportive people. So, as my work has shifted slightly, he’s been completely understanding. He recognizes the state of the world, recognizes the importance of this right now. He’s been as supportive a mentor as I could imagine through these studies. It’s been really enjoyable to learn more alongside him, too, because we’re starting to understand how we can think about viral diseases better. We’re bringing some of the fundamental immunology back into the equation in terms of how we’re addressing problems in cancer immunology, too. So all of this work is definitely bridging back into my other cancer-focused research.

Arthur N. Brodsky, PhD:

Lastly, could you talk a bit about the importance of CRI, and how our commitment to investing in basic immunology research has been crucial to helping us combat a variety of deadly diseases. Your fellowship is a perfect example of this, in that it’s enabled you to improve our understanding of both cancer and COVID-19.

How valuable has CRI’s support been to the field as well as to you personally?

Katie M. Campbell, PhD:

It’s invaluable. A lot of these tools we have today wouldn’t be possible without an understanding of fundamental immunology, which CRI and its many scientists have undoubtedly helped to advance over the past seven decades.

It’s also been very motivating to see the efforts across the different investigators and collaborations associated with CRI, which are utilizing multi-faceted expertise and technologies to come together and help. This is so important because what’s been clear through this entire pandemic is that it is going to require a very, very large collaborative and open effort to overcome such a terrible disease.

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