ASCO 2024: Latest in mRCC treatment
Dr Sumanta Kumar Pal – City of Hope, California, USA
Dr Stephanie Berg – Dana-Farber Cancer Institute, Boston, USA
Prof Viktor Grünwald – University Hospital Essen, Essen, Germany
Prof Thomas Powles – Barts Cancer Centre, London, UK
SKP: Welcome everyone to ecancer. My name is Monty Pal, I’m a medical oncologist at City of Hope in Los Angeles, California. I’m here at ASCO 2024, lots of exciting developments, including in the area of kidney cancer which is what we’re here today to talk about. I’ve got a terrific panel today and we’ll start with a quick round of introductions. Maybe we’ll start with you, Steph?
SB: Hi, good afternoon. My name is Stephanie Berg, I’m a GU medical oncologist at Dana-Farber Cancer Institute.
VG: Hi, my name is Viktor Grünwald, I’m a medical oncologist and I’m working at the University Hospital in Essen, Germany.
TP: I’m Tom Powles, I’m an oncologist in London.
SKP: So I’ll tell you what, we had a really nice conversation ahead of this regarding some of the top abstracts at this meeting in the kidney cancer domain and a couple really rose to the surface. Two of them reflect biomarkers from phase III clinical trials that we’ve seen mature in recent years, the CLEAR trial as well as KEYNOTE-426. Tom, I was just wondering if you’d give us some perspective on those two abstracts?
TP: These two trials, CLEAR and 426, more similarities than differences. VEGF TKI/IO versus sunitinib: 426 axitinib/pembrolizumab, CLEAR trial lenvatinib/pembrolizumab. Big frontline randomised phase IIIs, both have a survival signal. There have been studies going before looking at biomarkers and the summary of the biomarker story so far is T-effector interferon gamma signatures seem to be associated with higher responses for the immune therapy arm and we sort of know that a little bit. We haven’t seen much DNA analysis that has been very consistent, there’s debates about biomarkers such as PBRM1 and the PD-L1 biomarker has been pretty disappointing. But these two together give us the most robust biomarker data we’ve ever seen.
I’m going to start with the RNA signatures and they looked at two signatures particularly – one is an immune signature, it was a T-effector type signature, and the other was an angiogenic signature. Within the arms I’m going to start with sunitinib: it’s clear that the biomarker, the angiogenic high signature, in the sunitinib arm does better than the biomarker low arm. So an angiogenic signature is a good biomarker for sunitinib and I think that’s probably true. The problem is when you go into the study arm, the results between 426 and the CLEAR trial are inconsistent. Although in all the analysis the VEGF TKI/IO outperforms the sunitinib, in the 426 trial the interferon gamma type signature and the T-effector signature, the axitinib/pembrolizumab group does better if that is high than if it’s low but in the CLEAR trial that’s not the case.
That has created quite a lot of confusion in the field because previously the JAVELIN trial and the atezolizumab/bevacizumab study showed that if you had given a PD-L1 therapy and you had a high interferon gamma signature you did better with that combination. The biomarkers with PBRM1 were inconsistent across both arms and actually DNA analysis isn’t going to help us, moving forwards. So, to summarise this huge body of work, is any of this clinically applicable today? The answer is no. Have we learned about the biology of the disease? Yes, we have. Have we found biomarkers for sunitinib? Probably. Are they useful? Probably not. So I think we can now park this RNA/DNA analysis in these trials. The flaws with the study is that both arms have got a VEGF TKI on it so truly predictive biomarkers for one or the other is impossible. Actually, probably the more interesting biomarker data will come from the adjuvant trials where placebo is one arm, where you can identify truly predictive biomarkers.
SKP: And we’re definitely going to touch on the adjuvant biomarker data coming out of this meeting. I loved your distillation, Tom, I think the main message to the practising clinicians who are watching this video is that genomic testing at this point in time can’t really guide any treatment selection in the frontline setting, despite, as you point out, these massive, massive efforts to try to characterise it. Another topic that really intrigued me that was presented at ASCO 2024 was around chromophobe type kidney cancer, so non-clear cell kidney cancers, an interest of mine, of all of ours. Chromophobe just represents a small slice of that pie – about 5% of patients who have kidney cancer have chromophobe type disease. Viktor, can you tell us a little bit about what we learned about chromophobe at this meeting and treatment responsiveness?
VG: Yes, I think it’s really intriguing when it comes to rare cancer types, and chromophobe is one of those, the body of evidence is then really low. So what we have learned in the past years is really that when you work with combinations you may have a better outcome with regard to response and progression free survival. But these were all single arm phase II studies and only a proportion of patients had really chromophobe within it because it’s usually different diseases that are being put into those studies. So what we have learned today is really a comparison from retrospective data to look into the efficacy of single agent targeted therapies which could be VEGF-targeted therapies or mTOR inhibitors and then compared to IO, modern IO-based combinations. It’s the relevant question, isn’t it, because we would like to know do you need to have the combinations and there are always limitations when it comes to retrospective analysis – lots of bias that is also integrated in here in the decision process. But at the end, TKI/IO-based combinations, they prevailed so they did better versus the single agent targeted agents.
I think that’s where we are right now in our clinical reality. It depends on availability and accessibility whether you go ahead with a single agent TKI or you use modern combinations but I tend to use the combinations in my clinical practice.
SKP: I find datasets like this quite helpful because I doubt we’re going to see large, randomised studies in the context of chromophobe disease specifically. I liked one question that came up from the audience during this session and that really honed in on the specific TKI that was used in the analysis. It’s really struck me, looking across the data, that it seems that there might be something special about lenvatinib in this context. We see the limited data for lenvatinib have some of the data that Laurence has presented for lenvatinib and pembrolizumab in combination. I started to adopt lenvatinib-based therapy for chromophobe, is that something that you guys are doing as well in clinical practice? Stephanie, what’s your approach?
SB: I have two, also as a second line everolimus or lenvatinib/pembrolizumab, it does seem really promising compared to the other combination studies so I agree. There’s something there, maybe the mechanism of the drug and how it works and it’s really well tolerated as well compared to some of my experience with the other ones. So I agree with you.
SKP: Interesting, and what about you, Tom, chromophobe?
TP: I’m a bit anxious about saying one drug is better than another. I’m not sure we’ve done that robust analysis yet. It always worries me a little bit when we go from these really very robust trials and we show similarities or differences but we make bold statements which is reasonable then and then with a retrospective analysis of a relatively modest number of patients. There’s a lot of bias associated with the selection, so, for example, the lenvatinib patients may have been more recent, for example. So, honestly, I’m just a little bit nervous about saying one drug is better than another based off this.
I think the combination debate is really complicated for me because we haven’t asked those questions robustly either. Even in papillary renal cancer, I’m talking about obviously non-clear cell, we’ve answered them very clearly in clear cell. But in non-clear cell we’ve just adopted, we’ve been happy to adopt, because of the halo effect around the combination; we’ve been happy to say, ‘This is now the standard of care’ in what is a disease that’s very different from clear cell renal cancer. We haven’t got a strong rationale why the combination or lenvatinib should work particularly well in chromophobe cancer and normally we do trials based on a biological hypothesis and rationale. Our rationale is, ‘It works somewhere else so why not try it here,’ so I’m not super attracted to that. I actually think the VEGF TKI/IO combinations probably in papillary renal cancer are becoming a kind of standard and it’s pretty hard to row away from that but in chromophobe I’ve not seen enough data to say that the drug… to say yet that any preferred regime is better than another. Certainly from a guidelines perspective they’re all going to help here.
SKP: That’s totally fair and your comments around establishing standards in these rare diseases is very well taken. It’s so challenging where we’re really pulling together bits of data in this case. One of the more fiery dialogues that we had during these sessions here at ASCO 2024 was around an abstract that dealt… and I wasn’t anticipating this to be a fiery abstract, but it was around very favourable risk renal cell carcinoma. Stephanie, I was just wondering if you can just give us a topline sense of what that abstract entailed and maybe your interpretation of it.
SB: It was a little fiery, I agree. When we use IMDC database it’s something we’re all used to, it applies to our patients, we use it all the time, there’s a really nice calculator we can use. And we know that sometimes for very favourable or favourable risk patients do you really need combination therapy and they do very well with monotherapy. So it is something where, looking at that data when you’re sitting there yesterday, there were a lot of questions posed about what was the best TKI, should we really be… could we use ipilimumab/nivolumab, pazopanib was on there still, some monotherapy. So it was something when we talk to our patients and they have that type of very favourable and favourable risk, some of them can go with observation and close surveillance prior to treatment. So that was really great to see because we think about that all the time and where their metastases lie and using those tools in our clinic every day.
SKP: Yes, and this very, very favourable risk category included some variables that intuitively make sense. For instance, one of the criteria was three years elapsed or beyond from their time of original diagnosis to systemic therapy.
SB: Like number of metastases and things like that, right?
SKP: Right, exactly. Tom, what are your perspectives on this? Is very favourable risk something you might be looking at now in your clinics or no?
TP: I’ve been thinking about it for a while actually. You know that patient who had surgery six or seven years ago and they come back with a lymph node somewhere and it gets biopsied and it’s clear cell renal cancer? They say, ‘What’s this?’ This feels different, it feels to some extent like immunological escape – on the one hand, clearly the thing has been under control for a bit and is not under control. The temptation, therefore, would be to say, well why not give immune checkpoint inhibition to those patients because that, probably, is the best way of getting them. But actually the data didn’t suggest that. The data that I saw suggested that these are very, very highly VEGF-dependent tumours and VEGF TKI therapy is the attractive treatment for those patients. So I thought it was really informative in that respect.
I agree to some extent with Mike’s point is that it wasn’t particularly robust and I think it’s premature for all the reasons I’ve said previously to say that this drug is better than that drug. But I think it’s fair to say that VEGF TKIs look pretty good in that setting and that can be the standard of care if people want to give immune therapy in those circumstances, who am I to say? One has to remember that immune therapy is not licensed, ipilimumab/nivolumab is not licensed, in good risk patients anyway so to say it’s suddenly the right treatment for very good risk patients is probably a jump too far. It doesn’t mean it might or might not have a role, have that discussion another time, but the conclusion from my perspective is it’s actually quite binary.
It’s clear that there is a group of good risk patients, the biology of that disease seems to be VEGF driven, wouldn’t it be nice to actually get the biology right rather than putting them into these relatively false categories that are defined by three years here or two years there. It’s very clear that those patients that have late relapse it’s driven by clean VEGF-targeted therapy and therefore that probably is, from my perspective, the standard of care. I don’t think you have to add an immune checkpoint inhibitor in my opinion.
SKP: Brilliantly said. I’ll rehash for the audience today some of the dialogue that was had. The question was posed regarding whether or not a statement made by the presenter suggesting that TKI plus IO should be a standard in that very favourable risk population was appropriate or not. That was challenged by a very seasoned expert in immunotherapy. A reasonable discussion, I would say. Viktor, I’ll give you the last word on this very favourable risk disease. What did you take away from this presentation?
VG: Yes, first of all, Monty, what I’ve seen is really that with very simple measures you can tease out a fraction of patients that do extremely well in terms of prognosis. Something that is also that you can get the sense of from that presentation is also that there is more VEGF-driven disease behind it. So, going from a clinical few parameters that we use to identify those patients towards biology, you enrich for patients that are TKI sensitive or, let’s say, angiogenic driven. That’s something that we have seen today. Is it very certain we have randomised prospective controlled trials? The answer is no, we don’t have that. I think there is always uncertainty and controversies. But I also think it’s very reasonable to use TKIs in this setting.
SKP: It does help to have some datasets like this to lean on, just to justify our clinical practice. Viktor, maybe I’ll turn to you again, actually. There was an abstract that we discussed prior to our session today regarding lenvatinib and pembrolizumab in sites of metastasis. Maybe you could walk us through some of the key findings there?
VG: Yes, Monty, when I look at the data and when you see the response rate that you get out of the trial, objective response rate, one of my questions would be, really, how does it translate into my patient? My patient has lymph node metastasis or lung metastasis and I would like to know what are the chances to derive benefit for that specific presentation of metastatic disease. We looked into the progression rates, only counting those that occurred in the specific organ sites and I think it gives you a time to progression broken down by organs and that is something that is informative. Overall, what we have seen is that the signal from lenalidomide/pembrolizumab is so strong that it pervades across all those different organ metastatic sites basically.
The second topic has been really addressing a question which is not easy to answer – what is the contribution of first line towards really overall survival because it’s two years of progression free survival, it’s 50-55 months of median overall survival. So how is really that benefit translating into such a strong overall survival signal? So we looked into the tumour burden for that exercise, we looked into tumour burden at start of therapy and at time of progression. As it appeared, patients that have the combination have a larger tumour shrinkage, we know that, but at the time of progression, so when treatment fails, patients had about 48% of the tumour burden from the initial start of therapy. That might be a completely different state of disease at that time being, it may contribute to subsequent therapies and there could be more efficacy based on that. But that’s a hypothesis so far and we need to dig deeper here.
SKP: Interesting. We’re going to wrap up with a topic that I think is at top of mind for a lot of people – adjuvant therapies in use in renal cell carcinoma. Is there potentially a biomarker that we can lean on? Tom, something that you’ve done in bladder cancer that I think is just absolutely beautiful is brought ctDNA forward, and that great Nature paper, as a potential biomarker of responsiveness to adjuvant IO. We’ve longed for something like that in renal cell for a while; I don’t know that ctDNA at this point is necessarily going to pan out. There was the surprise at ASCO this year with KIM1, can you tell us a little bit about that?
TP: Monty, I think you lead that adjuvant trial so you can test me. KIM1 is kidney injury molecule 1 and it’s part of the TIM family, TIM1-4. TIM3 we know about because we know it’s an immune checkpoint. KIM1 is regulated, or it regulates kidney injury, as it sounds in the protein. In fact, if you get nephrotoxicity your KIM1 goes up. It’s interesting because if you have kidney cancer that probably is generating a lot of disruption in the kidney and that’s probably generating kidney injury. I suspect that’s why you have high KIM1 levels with kidney cancer and I suspect the bigger and more disruptive the cancer, the higher the level. It makes sense in that respect. But it’s intriguing it’s also associated with immunity and it’s associated with immunity because we know that KIM1 is associated with up-regulation of Treg and that’s associated with immune inhibition and, of course, that’s where the whole immune checkpoint inhibition story starts.
So there’s a strong rationale for KIM1 in kidney cancer, it’s a biomarker that you can measure, it’s a protein you can measure in the blood, which is good. As you said before, it’s very different from ctDNA, obviously it’s a protein. Actually we know a little bit about KIM1 from the ASSURE trial and from the ipilimumab/nivolumab trial before. So we’ve had two previous studies which have really implicated it but this is probably the most robust analysis in the study, the adjuvant trial, looking at atezolizumab versus placebo. The trial was overall a negative study but when you did the subset analysis of those patients with high KIM1 you could show two issues. Firstly, you could show not only was it prognostic, as you would expect, but it also looked predictive for response to immune therapy. It also had that issue around dynamic changes because you measured it not just at baseline but with time so you can see it going up in progression, which I thought was neat, and coming down in those patients who are doing well with atezolizumab.
So I looked at this and thought this is the most… We’ve talked previously about the other RNA and DNA biomarkers and I talked about the noise and the two arms, great pieces of work, fabulous. Not moving the field forward as much as we’d like. But I looked at this and thought this could actually be the first time that we can move the field forward and just because it’s not ctDNA, just because it’s a protein, we shouldn’t ignore it. I think we should take this forward, I’m very excited about it.
SKP: So, Viktor, Stephanie, you can probably see why I asked Tom to describe that abstract because I bet he did it better than I could frankly.
TP: I’m sure I didn’t. I’m sure I didn’t.
SKP: Very well done. We’ve discussed a really wide range of abstracts today. I think we’ve highlighted most of what’s going on at this meeting in kidney cancer without leaving too much out. I really want to thank all of you and our audience today for viewing our performance here. I’m sure that we’re going to have much more to talk about at ASCO 2025, so we’ll see you back again.
