Alicia Morgans: Hi, my name is Alicia Morgans, and I am an Associate Professor of Medicine and a GU Medical Oncologist at Northwestern University in Chicago in the US. I’m so excited to have here with me today a good friend and colleague, Dr. Tom Powles, who is a Professor of Genitourinary Oncology, and the Director of the Barts Cancer center in London, in the UK.
Thank you so much for being here with me today, Tom.
Thomas Powles: Glad to see you, Alicia. How are you?
Alicia Morgans: I’m well, thanks. And I’m excited that we are able to talk about your presentation from ASCO 2021, giving us an update on the JAVELIN 100 bladder data, really kind of digging into that follow-up, as well as understanding some subgroups. Can you tell us a little bit more about it?
Thomas Powles: The JAVELIN Bladder 100 trial is essentially for metastatic front-line urothelial cancer patients whose tumors have not progressed on chemotherapy, and were randomized to receive avelumab or best supportive care. The hazard ratio for survival was 0.69, but it has become, actually, quite a widely used standard of care in the US and in Europe. Many people say that’s because we didn’t manage to supersede front-line chemotherapy, and that is a discussion, I think, for a different day.
But what we are doing at the moment is we’re looking at different pieces of analysis. So the first thing that we’ve kind of focused on over the last year is: are there subgroups that seem to benefit? Is there a biomarker-positive subgroup? And some of the work we’ve looked at in this particular presentation is some of the TCGA molecular subgroups. And the molecular subgroups, just in terms of Jonathan Rosenberg’s data from five years ago with the original IMvigor210, with just the four subgroups, showed papillary and luminal. And there were some papillary subgroups that had FGF alterations, and there was a luminal, I think. So it was a luminal type 1, luminal type 2, and there were just some slight indicators … and then the basal subgroups had stromal signatures and were resistant, but they had quite a high tier, high TMB.
It was a little bit confusing because one of the problems with the TCGA subgroups is that they are histopathology subgroups, almost, molecular RNA-type subgroups. They’re not designed based on the presence or absence of an immune-based biomarker. And so, it’s almost like sort of five or six different armies, one in red, one in yellow, one in blue, one in green, and they all have a different proportion of archers, and spearmen, and guys with swords. And actually, it might be better just to get the sword patients together and the archers patients together.
So I’m a bit worried about these RNA subgroups, I think we’re including lots of different patients. And so, when we looked at this, we showed that actually all of the subgroups, essentially there was some benefit, perhaps it was highest in the luminal-papillary, perhaps, although statistical noise will mean inevitably one group does better than another. And then when you looked at PD-L1, TMB, and Teffector-type signatures, you could see that there were some subtle differences. But those differences, for example, luminal-papillary had higher TMB, but actually, the PD-L1 Teffector signatures weren’t higher.
And we are doing different data, where we’re just looking at PD-L1, TMB, Teffector, B cells, B cell markers, and those biomarkers seem a whole load better in predicting outcome than actually these molecular subgroups based on RNA expression, which actually do not have that much to do, necessarily, with the presence or absence of specific immune biomarkers.
The one exception to the story may be, and I don’t know this, is the FGF story, but even that is looking a bit ropey from my perspective, and I think we need to do more work on that particular issue. So I’m nervous about the molecular subgroups and their relevance for immune checkpoint inhibition.
Alicia Morgans: So I love the way that you characterize these subgroups as really just sort of being different groups of different percentages of a lot of the same characteristics, and just sort of shuffled around into different categories, which may have made sense in the TCGA, but does not necessarily make sense within the context of an immune-based therapy. That makes a lot of sense. And thank you also for the action, that also brought it to life quite well.
But I think as we move forward, and you’ve noticed some other ways that we might be able to better predict and characterize these tumors so that we can better predict outcomes, tell us a little bit more about moving in that direction. Where do we go? And can you sort of outline that a little bit further?
Thomas Powles: Yeah, I can. So we’ve got a publication at the moment, which is in various rounds of reviews that go on and on. And I think the more science-y the journal gets, the more complex the review process becomes, but there is a piece of work out there at the moment. And actually, some of this data had been presented at ESMO last year, so I can talk about it, and none of it is offline.
I think what we’re beginning to show is … and by the way, number one is the maintenance avelumab study, which is a great place to investigate. The reason why is we have gone against the best supportive care. Because the problem with some of the other trials, which I’ve been involved in as well, so lots of problems, is they’re only the single-arm trials, which means you get caught up in prognostic and not predictive biomarkers, number one. Or number two is, we randomize against active control arms.
One of the problems with randomizing against active control arms is chemotherapy has its own group of biomarkers. So suddenly you find out the DDR-low signatures, immune therapy works well in them. Is that right? Or is it actually the DDR is a really good biomarker for chemotherapy? And actually, you can always flip it around the wrong way. And my mind begins to kind of explode when I start thinking about this against two active controls, because is it actually really predictive, or is it just a biomarker for the other arm of the trial? It’s very hard to determine that. You can sometimes do it, by the way, if you look at response rates and other bits and pieces, but it is difficult to do, and I’m not very good at it. If you go against the best supportive care, it’s much easier.
Now don’t get me wrong, there are shortcomings of the work because remember, some of the tissue is historical, it’s archived tissue, and patients have had chemotherapy, so it’s not perfect, as always. But what it does show us is two really important factors. The first is PD-L1 isn’t actually that great, it sort of helps a bit, but it’s not great. It misses a lot of the winners. Also, the PD-L1 positive patients are not exclusively Teffector high, TMB high. There are lots of patients who are TMB high who are PD-L1 negative, who respond really well to therapy.
The second piece is when you put PD-L1 and TMB together, you don’t solve all your problems. You create new problems, and you have new groups where they don’t …
And then the last piece of work, which, I think, for me is really interesting, is we’ve identified that actually, innate immunity is really important. And so, we’ve looked at macrophages, natural killer cells, antigen-presenting cells together, and we’ve shown that they are really important in driving response because we focused very much on adaptive immunity up to now. And then the last piece is within some aspects of that adaptive immunity, we’ve found B-cell signatures are relevant too.
And then I think the last piece, which I really like, is … and I know this work’s been done with atezolizumab also, but there are what was thought to be immune-independent signatures associated with resistance, so stromal signatures and eugenic-type signatures associated with resistance, and that is probably associated with T-cell trafficking. So when you look at the TCGA subgroups, it’s just this huge over-simplification of cancers that seem to be drawn to the same direction, because at the back of the room, the pictures look about the same, like Monet draws lots of pictures, you know what a Monet picture looks like, but one’s a boat and one’s a bus, they are completely different from each other.
And that’s the problem with the TCGA analysis, and actually what we’re doing much better now is if we compile these biomarkers on top of each other, we may actually be able to find signatures associated with response.
And the last bit I want to talk about in this is circulating tumor DNA. We are making good progress on that. And that’s a chapter for the future, but I think it’s going to be important.
And then there are these tertiary lymphoid structures, there is neoadjuvant work done with ipi/nivo and durva/tremi looking at tertiary lymphoid structures. And what they are essentially are cities of immune activation. It’s not just CD8 expression, it’s a whole series of different markers, often measured by multiplexed IHC, but actually, you can do it just by immunohistochemistry. And within this, you can see these tertiary lymphoid structures. It’s like an organ of different parts of immune activity balanced with each other. And it looks like these spheres of these planets of immune activity are really important in generating a response.
Coming back to our biomarker work, PD-L1 expression alone is never going to be enough to activate an immune signature. It’s going to be these structures interacting with one another that is resulting in the production of what essentially is going to have to be antibodies in the end, and T-cell recognition.
Alicia Morgans: So thank you so much for talking that through. Again, I feel like you’ve really very much brought these to life and I can actually envision these structures. And really, the way that you describe it, we’re bringing a two-dimensional picture on a page that seems quite oversimplified, as we’ve been saying for years, and sort of making it a three-dimensional interaction of many different systems that are involved in this immune response. And I agree with you, that is what will help us, I think, ultimately understand who is going to benefit. So thank you. That was actually incredibly exciting.
But just to circle back, as we do close out on this discussion of your phenomenal work, you and the team of JAVELIN 100 and the bladder study, it was universally effective across these subgroups, really changing the standard of care. Do you have any messages for the audience about the switch maintenance approach, and where you think it needs to fit into our treatment algorithms for these patients with metastatic disease?
Thomas Powles: I think there is a growing body of people who feel that single-agent immune therapy is not good enough for getting in control of the disease, and the biomarker is not accurate enough in selecting these patients, and that many patients that get upfront immune therapy do not get the opportunity to sequence chemotherapy, because their cancer is growing so fast.
The alternative approach of getting in control with chemotherapy, and then maintaining that with those durable responses, with maintenance avelumab, as it currently stands, looks more attractive to me. People say to me, “Yeah, but it’s a select group of patients.” And I think the answer is, “Yes, it is.” But remember which patients are not included: those patients with progression on chemotherapy. Patients with progressive disease on chemotherapy, unfortunately, they are a group of bladder cancer patients that neither chemotherapy nor immune therapy is really benefiting at the moment. And those patients, it’s not like you can salvage them with atezolizumab, atezo, or pembro, they go straight through that.
So I think that we need to investigate that group of patients with progression of disease, who are they, and what can we do to help? I hope enfortumab-vedotin can change the outcome for those patients.
As it currently stands, we haven’t managed to supersede chemotherapy. I wish we had, but the addition of immune therapy hasn’t salvaged those patients, the biomarkers and the immune combinations haven’t helped us a great deal. And so, we have this new approach of sequencing therapy, which I think is associated with a significant clinical benefit and will probably remain a standard of care until we can find something better: EV plus pembro, perhaps ipi/nivo. Who knows?
Alicia Morgans: Great. Well, thank you so much for presenting this data, to you and your collaborators on the phenomenal work, and for really rounding out our understanding of where things are, and where they are going, in terms of biomarkers of immunotherapy in urothelial carcinoma. Very, very wonderful time talking to you today. Thank you so much, Dr. Powles.
Thomas Powles: Thank you, Alicia.