Fibroblast Growth Factor Receptor 3 Alterations and Response to PD-1/PD-L1 Blockade in Patients with Metastatic Urothelial Cancer - Matt Galsky
September 17, 2019
Matthew Galsky, MD Director of Genitourinary Medical Oncology, Tisch Cancer Institute, Professor of Medicine, Mount Sinai
Alicia Morgans, MD, MPH is an Associate Professor of Medicine in the Division of Hematology/Oncology at the Northwestern University Feinberg School of Medicine in Chicago, Illinois.
Alicia Morgans: Hi, my name is Alicia Morgans and I'm a Medical Oncologist at Northwestern University and I am so thrilled to have here with me today, Dr. Matt Galsky, who's a Professor of Medicine at Mount Sinai in New York. Thank you so much for coming to speak with me today, Matt.
Matt Galsky: Of course.
Alicia Morgans: Great. I wanted to talk to you about a really fascinating analysis and a really timely and important analysis that you recently published looking at FGFR mutations in patients who had received checkpoint inhibitor therapy on some clinical trials. And can you tell us a little bit about, first, why this was so important and then how you and your team performed this study.
Matt Galsky: Absolutely. Several years ago, molecular classifications of bladder cancer were published by a few different groups, and each of those groups had defined a group of bladder cancers that were characterized as more luminal-like. Really in line with what's been seen in breast cancer in the past. Those luminal-like bladder cancers were enriched for FGFR-3 mutations and they tended to be less infiltrated with T cells, at least inferred based on gene expression.
A subsequent analysis had confirmed a relationship between FGFR mutations or increased FGFR expression and decreased T cell infiltration, and so putting all of that together, people started to think that maybe luminal-like tumors or perhaps more specifically, maybe FGFR-3 mutant tumors wouldn't be responsive to immune checkpoint blockade. And that even went as far as to some people using that data to impact clinical decision making, which we thought was maybe a little bit premature. And so to try and answer this question in a relatively straightforward fashion, we took two large clinical trial data sets of patients with metastatic urothelial cancer who had received immune checkpoint blockade. One trial with a PD-L1 inhibitor, IMvigor 210, one with a PD-1 inhibitor or CheckMate 275. We had data from the primary archival specimens regarding FGFR-3 mutation status. And we simply looked at the prevalence of mutations in those cohorts. And then whether or not there was a relationship between response to treatment and mutation status.
Alicia Morgans: One of the reasons I think this was so important is because of exactly what you said, that people have been really kind of jumping to therapeutic decisions based on this theoretical risk that patients may or may not have a robust response to checkpoint therapy based on these FGFR alterations. And can you just share a little bit about what you found when you were looking in these data sets?
Matt Galsky: We found that the prevalence of FGFR-3 mutations in these two datasets is about what one might expect from other studies, like TCGA. About 18% of patients in IMvigor 210 harbored FGFR-3 mutations and 11% in the CheckMate 275 dataset. And when we looked at the relationship between those mutations and objective response rate, the treatment, we really saw no differences. In IMvigor 210, the response rates were 24% and 21% with atezolizumab in mutant versus wild type patients. And in CheckMate 275, the response rate was 20% versus 21% in mutant versus wild type patients.
Alicia Morgans: Really this is not something that we should use to make decisions, at least at this point until we have prospective randomized data. It's not something that we should use to make decisions about whether or not to treat patients with checkpoint inhibitors
Matt Galsky: That's our big picture take-home message.
Alicia Morgans: Great. And, you had multiple smaller picture hypothesis generating type statements in there. And I'd love to just hear, you had some nice thoughts about how you might've had these response rates that were similar, even if these are patients who might not have this infiltration of the immune cells. There was this, you had a balancing out hypothesis. Can you tell me a little bit about that?
Matt Galsky: First we wanted to confirm whether or not this relationship between FGFR-3 status and T cell infiltration really held up in these cohorts as well because that was a piece of the puzzle, and in fact it did. These prior analyses showing a relationship between increased FGFR-3 mutations or increased expression at the gene level and decreased inferred T cell infiltration really were seen in these two cohorts as well. And so that really led to this missing piece. We had decreased T cell infiltration, which we know is associated with a lower likelihood of response to immune checkpoint blockade. But the response rates were similar in the mutant versus wild type patients. And so what we started to think about was the fact that other independent predictive biomarkers have been identified. Tumor mutational burden, and these stromal gene signatures or TGF beta gene signatures that confer predictive information in urothelial cancer, but are independently associated with response rate compared to measures of adaptive immune resistance like PDL-1 status or T cell infiltration.
What we did simply is look at those three parameters and how those three parameters related to FGFR mutation status or FGFR-3 expression status. And to make a long story short, the FGFR-3 mutant tumors had lower T cell infiltration and they had a similar tumor mutational burden compared to the wild type patients. But interestingly, they had lower expression of these resistance markers, these stromal markers or these TGF beta gene signatures. What we really think is going on, and it's completely a hypothesis, but we think that there might be a balancing out of these good and bad predictive signatures in these tumors, which is why the response rate ends up being similar even though there's less T cell infiltration.
Alicia Morgans: Great. Well, I sincerely appreciate that we not only have the high-level clinical implications of these FGFR alterations, but we also then have at least some way to help us contextualize this finding in the face of all of the other biologic data that we have because it can be really hard to keep everything straight. I appreciate that you and the team took that extra step to do those further analyses and help us understand how both of these things could be true and leave us in the situation in which we are.
I just want to congratulate you again on this European urology paper. I encourage the listeners to look this up and to think about FGFR alterations in terms of using this to direct patients to treatments that may be helpful, but I wouldn't withhold things like checkpoint inhibitors from these patients because as Dr. Galsky's shown us in this really elegant analysis, this is not a marker of resistance to immunotherapy at this point in urothelial cancer. And Matt, do you have any closing thoughts for the listeners as they think through this data?
Matt Galsky: I would say two quick things. One is that I think this is just an example of how complicated this biology is and in what seems to be relatively straightforward on the surface is of course always more complex when we take a deeper dive into the biology. And the second is that this might be considered a reason not to combine FGFR-3 inhibition with immune checkpoint blockade. But in fact, we interpret this in the complete opposite way. We think that because these treatments are probably non-cross-resistant and both of them can be active in FGFR-3 mutant patients, it provides even a stronger rationale for combination therapy.
Alicia Morgans: Well, fantastic. I really do look forward to you launching that trial when you get to it, because I'm eager to see how these things may work, at least additively if not synergistically. It's always important to have completely separate mechanisms of action as we're thinking about combining therapies and increasing our response rates. Again, thank you for this really elegant paper. Thank you for helping to guide us as we're trying to sort through the murky data that exists at this point and for getting us a little closer to truth and understanding the biology. Thank you for your time.
Matt Galsky: Thank you.