The Uromigos: Perioperative Therapy in RCC

During the first annual The Uromigos Live & Unplugged event, which took place in Nashville, Tennessee, Brian Rini, MD, and Thomas Powles, MBBS, MRCP, MD, were joined by a panel of renal cell carcinoma (RCC) experts to discuss some of the recent ESMO data related to perioperative therapy in RCC, as well as thoughts on the next adjuvant therapy trials. The panel included Axel Bex, MD, PhD; David McDermott, MD; Sumanta Pal, MD, FASCO; and Tian Zhang, MD.

Transcript:

Brian: Welcome everyone. Welcome to the final session of Uromigos Live 22. We have an excellent kidney cancer panel. We’ve saved the best for last in kidney cancer. This is our livestream stream session. We’re going to talk about perioperative therapy. As you know at ESMO there was a bunch of trials that came out. It’s a lot of new data to talk about. A lot of uncertainty I think, in the field. So we thought this would be the most appropriate to talk about in this session. Final thanks to our sponsors. Again, thank you for supporting this, what we hope is an innovative meeting. We appreciate your support. And we’re going to go on our panel. We’ll start with you Tom. You can introduce yourself to-

Thomas: I’m Tom Powles. I’m an oncologist from London.

Brian: Very good-David?

David: David McDermott, oncologist from Boston.

Axel: I’m Axel Bex. I’m a urology surgeon from the Netherlands and I work at the Royal Free in London. I think the only urologist on the panel.

Brian: I’m sure of that too. Unless Tian has another skillset-Tian.

Tian: Tian Zhang, medical oncologist in Dallas.

Monty: And I’m Monty Powell, medical oncologist, The City of Hope in Los Angeles.

Brian: And the Twitter polls were extraordinary. We’ve all learned a lot from Monty about creating Twitter polls this week, this past week. All right, our title got a little cut off there, but this is basically the story of adjuvant therapy. On the upper left, the keynote study, which was positive Pembro data first presented, I don’t remember when, but many months ago now approved. Which was a pretty clean signal. Right? This is disease free survival. This is the updated data. And then at ESMO this year, and Axel reported one of these was Atezo neo/adjuvant Nivolumab and Ipi/Nivo all pretty flatly negative. You don’t even need numbers up there to see that those curves don’t split. So I’ll start, Tian, I’ll start with you. Were you surprised at the ESMO data? Just big picture, Were you surprised that all three of those came in negative? We’re going to talk about the individual trials in a second.

Tian: Sure. Big picture, absolutely surprised. We were hoping that we would see some signals in the other phase three trials. Obviously large numbers of patients. I think we’re still waiting to parse out who is that high risk population to treat. But certainly surprised at the three negative signals.

Brian: Yeah. How about you Axel you were very involved in-

Axel: Exactly the same. We know from Atezolizumab that it’s not very active in the metastatic setting. So if that were the only trial that was negative, I think as the community would’ve felt this was to be expected. But completely surprised.

Brian: Yeah.

Axel: I also had much higher hopes for PROSPER, to be honest.

Brian: David?

David: Well I’m good at predicting trials that are going to be negative since that’s-

Brian: Years of experience.

Monty: Years of experience.

Brian: Decades maybe.

Monty: Yeah, so I think to some extent there’s a surprise here in that we knew PD1 adjuvant was active in melanoma. We knew frontline PD1 was active in kidney cancer. So translating the melanoma experience to kidney cancer, you would assume these trials would be positive. But we went into these trials without knowing who benefits from PD1 blockade and-

Brian: Fair.

Monty: The reason they’re negative is probably because we put a bunch of patients on who would never benefit from checkpoint.

Brian: Okay, or you can talk about Tom final word on the big picture?

Thomas: I think you can explain what happened, but you can’t find one reason to explain what happened. And when there are lots of different bits and pieces going on, it’s quite hard to put it all together. The Pembro trial is clearly positive for disease free survival. It’s therefore hard to explain why Ipi/Nivo wouldn’t work. Neo adjuvant therapies gained a lot of attention in melanoma and in other areas, yet it’s not worked here. That’s hard to explain too. And then the Atezolizumab study, while the design with the Pembrolizumab trial, very, very similar. So it’s quite difficult to explain what’s happened.

Brian: Yeah. Anything you want to add, Monty?

Monty: I wonder if we can just jump into the first Twitter poll, actually. It might be a good time to just throw it up there.

Brian: Of course. It took us about 30 seconds.

Tian: To tag onto Tom’s point though. You had done the brilliant discussion at ESMO.

Thomas: That was sweet of you.

Tian: Your point that every happy trial is a happy in its own way, but unhappy negative trials are maybe negative in its particular way. I think that’s very well said.

Brian: Let’s get into the specifics of that. Do you want do the poll Monty?

Monty: We can hold off-

Thomas: No, let’s look at the poll. Let’s go the poll.

Brian: Let’s do the poll. The crowd is clamoring for the poll.

Monty: I think so. Right? So I basically put up that same slide that Brian had that you saw a second ago. And I basically asked the crowd, based on this data, how is your utilization of adjuvant IO going to change? And what was really interesting here is that the audience was split on less use versus no change in use. But what surprised me is about 20% of patients, actually patients, individuals who responded here, suggested that they actually use more adjuvant IO seeing this. So I don’t know if there’s any logical explanations for that. I’ll pass it back to you Brian.

Brian: Why anybody in the panel? Why would the collective data make people use adjuvant Pembro more? Anybody?

Thomas: Confusion.

Brian: Confusion. Press the wrong button? 20% of people?

Thomas: Maybe it shows a flaw in our polling system.

Brian: What’s that?

Thomas: So Tian, I’m just saying our polls clearly have problems with them.

Brian: Yeah, yeah.

Thomas: When one tries to pull this together, it’s quite difficult.

Tian: Right.

Thomas: But I think the one that people talk about may be the most is the Atezolizumab study because it’s a single agent.

Brian: Let’s go back to the slide.

Thomas: And it’s very similar in many respects to the Pembro trial.

Tian: Sure.

Thomas: And many people feel, is there a difference between PD1 and PDL1 therapy in kidney cancer? And that’s maybe not a bad place to start. And maybe you want to talk about that.

Tian: Well we’ve had a couple of Atezo trials now even in metastatic disease, and unfortunately we haven’t seen as clean signals. Right? For Atezo and bev then we did for the PD1 inhibitor based therapies. And so in the adjuvant space, we were hoping that the emotion trial would be positive. And to your point, the similar patient characteristics, is it the actual agent that’s different and the activity is not there? So I still think there’s a population that we need to tease out who will benefit from adjuvant treatment. It’s just not in all-

Brian: You think it’s a drug effect. PDL1 is less active?

Tian: Possibly.

Brian: Possibly. Okay.

Axel: Yeah, it could be. There was a, first of all, when we designed the trial, we used the same inclusion criteria. Actually we were first and then we saw many of these things being copied from the keynote team. With the exception that the T3A group for the inclusion in our motion required grade three to four, which was actually higher risk group. And the M1 reacted to ND population was actually more than a year after surgery. Because you have very good data, at least in the surgical specialties, that if you recur within the first year after surgery, you’re more likely to be a rapid progressor. And that would be more towards systemic therapy. But there’s one subgroup which showed a little bit of hazard ratio, which is interesting. So the more than 5% PD1 expression on tumor infiltrating immune cells. And that is probably something they could look into but the group is very small.

Brian: Very small group, small subset. David, what do you think? Why is it negative?

David: Well, I mean Atezo is active in the metastatic setting, PDL1 blockade is active, it’s probably less active. And motion 150, the response rate to Atezo was 25% compared to Keynote 427 where Pembro gets you at 36% or whatever.

Brian: But let’s look at-

David: But-

Brian: …The single agent data though. Right? Because you guys are all quoting combination data.

David: No, I just said single agent Atezo 25%, EMOTION 150.

Brian: Okay, it’s up on the screen.

David: There you go.

Brian: Yeah. David’s study. You’ll notice David authored a lot of these studies. So this is, let me just describe it and then I’m going to have you jump back in.

David: Okay, fine.

Brian: So this is David’s EMOTION 150 study, which had an Atezo monotherapy arm, he just described. A single agent avelumab arm from an early JAVELIN study. David’s keynote 427 study. And by the way, David, what’s your room number at the Thompson Hotel?

David: 427.

Brian: There you go. Good job. We don’t miss a trick here. And then Mike Atkins just reported it in JCO, the HCRN study, which was a little different that it was Nivo with Ipi added at progression or lack of response, but gives us a big data set of Nivo monotherapy. So two PDL1s on the left, two PD1s on the right. Do those numbers look different to you? Does the activity of the left two columns look different than the activity of the right two columns?

David: If you’re asking me, I would say slightly less active. But you still should have seen more of a signal than we saw in motion one.

Axel: Yeah.

David: 010.

Brian: Slightly less active based on what?

David: The response rate in 150 to single agent is 25%.

Brian: Okay. 10% less response rate.

David: Correct. So we should have seen more of a signal than we did. But I think to me, that’s Genentech’s problem. It’s not necessarily the field’s problem. Because I don’t think people are extrapolating what we did in VegF TKI adjuvant therapy to what we’re going to do in adjuvant PD1 therapy. And all of a sudden look at PD1 as maybe we shouldn’t do it because we have three negative studies in one positive study. I don’t think that’s going to happen. I don’t think people are going to use less Pembro because of these three negative studies. There may be reasons why they use less and we can talk about what those are. But it’s not because Atezo didn’t make it.

Brian: Okay.

David: There’s just a halo around immune therapy that didn’t exist with VegF TKIs.

Brian: Fair.

David: People are using them in practice like it’s in the drinking water and-

Brian: In part thanks to people like yourself.

David: Well, I’m here to talk about the rational application of immune therapy. What I’m saying is we’ve gotten irrational about our application.

Brian: Fair enough. Fair enough.

David: We can dial it back. But that’s going to be up to us. The industry is not going to die.

Brian: Tom, do you think PDL1 is less active than PD1?

Thomas: So I think PDL1 therapy has single agent activity.

Brian: Yep.

Thomas: And that’s true. So I think it’s an active drug. I think when you put it in a randomized phase three trial in unselected patients in the adjunct setting, it’s not worked and it doesn’t appear active there. I think that it’s fair to say with the data we have in bladder cancer, as it currently stands, there are more positive PD1 studies. In fact, there are no positive PDL1 studies. So it’s reasonable to include from that that PD1 is currently outperforming PDL1.

Brian: Yeah, sure.

Thomas: We need a box.

Brian: Throw a box. Nancy, can you or Matt? It’s a pretty long toss.

Thomas: That’s a-

Brian: Talk into the top. Yeah.

Jay Reno: Hey Tom, Jay Reno, I’m a urologist. Really interesting, our center has been very active in recruiting into these trials as well in the community. What about the fact that M1NED is this mystery group? The Atezo trial had a huge percentage of M1NED compared to the other trials. I think 17%, 18% were true M1NED compared to the Pembro trial, which is 4%, 5%. To me, those are metastatic patients. Those patients may be undertreated with single agent. And frankly, I don’t think CT scans, we don’t have great staging agents to understand if these patients are really metastatic. So could it just be that this group was just a higher risk group and we undertreated them?

Thomas: Two things, when you look at the control arm and the performance of the control arm in the two trials at landmarks, the Atezo trial and the Pembro trial are almost identical. The second issue is when you look at the subset of the Pembro trial and you remove the M1NED population because it’s only 6%, it actually doesn’t make a huge difference to the hazard ratio. It puts it up by a couple of percentage points. And so of course if Atezolizumab was active, you would expect it to be most active in that group because we showed response rate 25% in the metastatic setting. So you expect it to make a 25%. That essentially is progression free survival. That’s the delay and so if anything, the Atezolizumab study should have been more positive. So I think that’s a hard explanation.

Axel: I disagree slightly because I think if you look, so I agree with the fact that if you take the M1NED population out of the Keynote, then it remains still a positive study. Just look at the, I think the hazard ratio was 0.73 for that group. But if you look at the DFS hazard ratio in Keynote when they first reported is 0.29, that’s staggering. So it’s basically treating patients with an active agent versus not treating them. And we know from all these data retrospective, but recurrences in the first year, they have a very poor prognosis. So I think these patients were subclinically metastatic, but also with a progressive tendency. I think that’s something we should not underestimate.

Brian: Is anybody nervous, as Tom alluded to about treating M1NED, although they’re probably at the highest risk, you’re probably, you’re under treating them, you’re potentially under treating them and then you’re maybe compromising delivery?

Axel: I would agree

Brian: David?

David: For sure. That was one of the other things because we didn’t know when we started these trials is how long do you need to give therapy to these patients? We still don’t know the answer to that question.

Brian: Right. Monty, what do you think?

Monty: I’ll add some feedback from the YouTube chat if that’s okay. There’s a guy named Tony Chew. Does anybody know him? No.

Brian: How do you spell that?

Monty: Yeah, yeah. And he says he is from the northeast. And he points out that this M1NED population that we looked at primarily in the context of Atezo study, greater than one year might have just been cured. Really limited benefit there. So-

Brian: Decreased chance of benefit because those patients had a higher chance of being cured than-

Monty: Exactly.

Brian: -that one population.

Monty: Yeah.

Brian: Okay.

Tian: So.

Tian: Also, an active conversation, are these patients truly micrometastatic? And if we waited six more months, would we then put them on IO/IO combinations in the frontline metastatic setting or VEGF IO combinations in the frontline metastatic setting? So I think the point’s well taken, that there’s some patients that might have been undertreated a bit. But yours is too, Tom, that if they were a higher population, then the study should have been more positive if Atezo was more active.

Brian:                                  Let’s go now to the PROSPER study. So this was a sing, I don’t have the scheme up there, but it was a single dose of neoadjuvant Nivolumab, then nephrectomy, then nine months of adjuvant Nivolumab versus nephrectomy filed by observation. I got that right? You see the curves here. This was actually stopped early. You actually see from the abstract, this was not shown at the meeting, that overall survival hazard ratio, if anything, well above one, although early, in wide confidence intervals. And then, obviously, see the curves. You see that big drop at the beginning. David, you’re a neoadjuvant guy. What happened here?

David:                                 So I still think neoadjuvant immune therapy is a good idea. The idea to apply it is at least 10 years old. First time I heard this idea was from Chuck Drake, who had data in mice with his lab, and Dario MacNally’s lab. And when he said, this is what we should be doing, because we are treating not the so much the tumor, we’re treating the immune cells. So you should give the drug which activates the immune cells, when there was more immune cells in the patient. So you should give it before surgery. When he first said that, people thought he was crazy.

Brian: Which he may be.

David: Meaning people were like…

Tian: Defend himself…

David: “This can’t be right. This doesn’t compute, this doesn’t go with how we’ve been doing adjuvant therapy for decades.” So in that context, we tried to launch this trial, and there was a lot of resistance in all directions for that concept. Now fast forward, 10 years later, that concept looks pretty good, not in kidney cancer, but in other tumors.

Brian: So talk about this. This is the melanoma data, just your melanoma guy as well.

David: So this is from ESMO, just a few weeks ago. This is a US cooperative group trial, SWOG1801. And you’re looking at, essentially, neoadjuvant versus adjuvant therapy in melanoma. And you don’t have to be a statistician to see those curves. That’s a pretty big difference. So if you’re asking me what the next step is in the surgical perisurgical space in kidney cancer, it’s do this trial in kidney cancer, do it right, and make sure we get more buy-in, less dropout, less mess, that the PROSPER trial, being a cooperative group trial, was ridden with. This idea, there’s no reason why it wouldn’t work in kidney cancer. It’s working in lung, it’s working in bladder.

Brian: When you say do it right, what do you mean? This was more neoadjuvant therapy than a single dose.

David: Correct.

Brian: What else?

David: But also, ideally, it’s a sponsored trial, so that the investigators have bought into the concept of completing the regimen, as opposed to patients dropping out and falling off treatment. When you start getting into the PROSPER data, and this will come out in future meetings, there’s a lot of dropout. There’s not everyone got that therapy, which is understandable. It was a bold idea, but not everyone was bought into the concept. Not all the surgeons were bought in, people were diving off the study, at various time points. All of which is understandable then, but not… Now, it’s a good idea. It should work in kidney cancer. Maybe there’ll be more buy-in for both patient and clinician.

Brian: You think because of the melanoma data, because of general enthusiasm, people won’t drop out as much? They’ll be more committed because of these data, the data on the screen?

David: And you’re asking for what the next advance is, by giving the therapy, the only difference between those arms is giving it pre-surgery versus not. And there’s an advance there.

Tian: If I may, there’s a couple of differences between the melanoma trial and PROSPER. So one, they’re, I think, a bit more careful in the patient that they selected. And two, they have nine months, or sorry, three months of treatment, instead of one month of treatment prior to surgery. So there are nuances here. And I think that, certainly, we see the activity in melanoma. Kidney cancer is very immunogenic tumor. We would love to mirror that in kidney cancer. So if there would be an opportunity for such a trial, I agree.

Axel: Talking about the length of pretreatment, it’s actually quite interesting. We did this neoadjuvant trial with Nivolumab Axitinib for three months. And now, we have a second one in Amsterdam which is called NESCIO, where we treat patients for six weeks with Ipi/Nivo, Nivo relatlimab, and Nivo mono. And we recently had a patient, who had a complete response after six weeks of pre-treatment. So I think we do not necessarily need three months. And in my point of view, you see very little happening with Nivo mono, and I think that might be one of the reasons. I think if you design a new adjuvant study, it might be better to have a short pre-treatment with a combination and then, a maintenance following…

Brian: Yeah. More intense treatment. David?

David: Going back to what 10 was saying, which I agree with. We’ve learned a lot since the PROSPER trial was initiated. PROSPER originally started out as two doses before surgery, for example.

Thomas: Sounds like a good idea.

David: Right. Now, everyone thinks that’s a great idea, but the surgeons didn’t want to wait. You know what I’m saying? They’re not all as relaxed as Dr. Bex is. As far as going to the OR, patients didn’t want to wait. It was also a question was placebo trial versus not observation? This would be active therapy versus active therapy. Patients would buy-in. Clinicians would buy-in. We could avoid treating some of those early patients, those non-clear cell patients. Whatever we could learn and do better.

Brian: Let’s go to questions at the end, Monty’s going to put up a poll.

Monty: Okay, great. Yeah. So David, this is a higher risk population, right? I’m looking at that adjuvant arm. And in 18 months, already half the patients have relapsed. So is that part of our problem? Are we still not selecting a high enough risk kidney cancer population? Are there other factors we should be using to do a better job of that?

David: Right. I completely agree. I think we went based on the clinical staging criteria. It’s not clear to me that that is relevant or as relevant to IO therapies, as it would be with no therapy. So for example, a tumor that might be enormous in kidney cancer, but not metastatic, to me, that’s likely a relatively low grade tumor or likely a VEGF HIF driven tumor, not an aggressive high grade PDL one expressing tumor, that would be metastatic at a much smaller size. So in my mind, size is less important than biology, to your point. And we went into all of these studies without fully understanding that. I just don’t want the field to say, “We shouldn’t learn from this.” We need to learn and do it better the next time.

Thomas: Yeah, before we go on, just can I list the problems with the PROSPER, because…?

Brian: Please.

Thomas: So PROSPER was an open label trial. There was a randomization, but one of the arms forced to have a biopsy. Now that’s really complicated. At my institution, if you have to do a biopsy, it’s to delay you by four or five weeks, because by the time you’ve found it, you’ve got it, the patient’s had it, they’ve gone home, you’ve got the pathology result, and you’ve spoken to them, and you’ve booked the slot on the day unit. That’s a six or seven week process. That’s a problem. It’s a big imbalance in two arms, and that’s important. The second issue is, there is a super low risk population in that trial. They included lots of patients. It’s an investigating shared trial. We’ve all done it. Investigating the shared trial’s hard to recruit to, so you open up the inclusion criteria a bit to let some of the good risk patients in. The problem with that is lots of T ones and T twos. That’s a big issue. Number three, they had their assessment of progression-free survival, included, if you didn’t have surgery, that was an event. That’s a big problem.

David: But that’s pretty standard for many trials.

Thomas: No, it’s not.

David: It’s standard for this trial. Look at the curve. It goes like this.

Thomas: But it should be censored. You can’t say the reason you have progression free survival is it’s supposed to be a surrogate of overall survival. So let’s just go to a patient right now, David. Patient comes in…

Brian: I sat them together for a reason.

Thomas: Let’s have a patient. They come in, they have Nivolumab, they say, “A bit of a delay, a bit of toxicity. I want to scan before I have my surgery.” They have a scan. There’s no progression. The cancer’s a bit smaller. This says I don’t have the surgery. That patient is not a surrogate for a death. That’s not a surrogate for overall survival, whether you like it or not. And therefore…

Brian: We don’t know how many patients…

Thomas: We don’t. For their 15% of the patients, there were more patients who has had events in that respect, than actually went on to have real progression event. So more than 50%. So when you look at the story together, that is a big flaw. Now there are other flaws in the trial design as well.

Brian: You don’t have to give your whole ESMO presentation.

Thomas: I’m not going to. But we just need to be… Now, it’s a great study. It’s a huge investigator initiated randomized trial. It’s an enormous undertaking. It’s much better than any of the trials I’ve ever done. I’ve tried three or four of them. They’ve never been as good as this. But it highlights the difficulty of doing this trial. And so, I’m not being, I think the cooperative group did an amazing job, but I just feel that it is premature to let this story go.

David: You’re agreeing with me is what you’re saying?

Thomas: Well, it doesn’t sound like it.

David: No, I said, we should do this again better. And you’re saying, it’s premature to let this story go.

Monty: Oh no, we all agree.

Brian: Monty, why don’t you pull the poll? Yeah. And then, we’ll go question from back.

David: I think you agree with me.

Thomas: I do agree with you.

Monty: Share my screen, here, now.

Brian: Oh yeah, just do computer up.

Monty: Yeah. So we put up this poll across each one of the studies. And basically what you see in the top right hand over there sort of mirrors this dialogue that we’ve had around PROSPER. So you can see that a couple of folks, maybe a fifth of the audience, thinks that neoadjuvant therapy really just doesn’t stand a chance, based on principle in RCC. Most think that the depth of this study was low risk patients included. And then, the observation control is also cited as a reason. And I’ll use this opportunity, just to highlight sort of the dialogue on YouTube as well. So Toni Choueiri hits on many of the same notes, as Tom did. Sandy Srinivas from Stanford actually brings up something interesting. She says that she feels it’s actually going to take nine to 12 months of neoadjuvant therapy to really evoke a reasonable response.

Brian: What do you think of that, David?

David: There’s no data to support that statement. I love Sandy but… No, seriously, the first trial of what became Nivo was how many doses? One. One dose. You could only get a second dose if you responded to the first dose. We have no idea how much PD1 you need to evoke an immune response.

Brian: And it’s probably different for different patients.

David: Absolutely. And there’s some patients who need chronic therapy, and there’s some patients who could get away with just a few doses is the thing.

Monty: So David, there’s a lot of folks sort of pushing back on that on YouTube, suggesting that we probably need a longer duration of therapy. I wonder if we can just go down the row here and see how long is reasonable for a neoadjuvant window for an RCC.

Brian: Reasonable meaning practical? Or enough to give you an immune response? Or both?

Monty: Maybe both.

Tian: I think around three months, that’s when my patients are having their best responses. And then, right around six to nine months, I’m starting to see progression, if I’m getting perioperative.

Brian: Three months.

Axel: What gave me a little bit of a headache was that in the NeoAvAx when you did spatial transcriptomics, you saw some areas where there were responses and others where there’s no response at all. So if you go longer than three months, you’re actually delaying potentially curative therapy. I would really go for short term. I think all you need is the stimulation of the immune… So why am I…?

Brian: Give us a time or number of doses.

Axel: I would go for six weeks.

Brian: Six weeks. Okay. We’ve got 12 weeks, six weeks.

David: Six weeks sounds good to me.

Thomas: I’m nervous about six weeks, because it’s doing the same experiment a second time. And this is a very negative trial. I know there are flaws in it, but we are doing almost exactly the same thing twice. I think, unless we think it’s so flawed, because the clothes are on top of each other. It’s not even a near miss. And so, I think we should ask a different question and therefore, I’m inclined to agree with Tian. Say let’s go for a longer period this time.

Axel: But something happened in PROSPER…

Thomas: Something certainly happened.

Brian: But the slides back out.

Axel: So the dropout in the observation arm is really unusual in the population that are basically surgical candidates, that you already lose 10 to 12%. I don’t know where that drops down to of your population that does not have surgery. New accurately, you could argue, well they either have responses or they have toxicity. There’s always a reason. But 10 to 12% of the surgical population that doesn’t make it to surgery. I don’t get it.

Brian: It’s a big drop. We agree. David.

David: Called on me first. The explanation. So it’s on the right thing. He hits on the right thing in that we need to explain, we need to answer that. We need a full, what’s it called? Consort diagram, which we don’t have yet.

Brian: We don’t have a full one. I have a partial one, but go ahead, while you’re talking.

David: But the point is, the details will…

Brian: Details are important. Fair enough.

David: Yes. And until you see all the deets, I have some insight into some of the details. Can’t talk about it. Go to GU ASCO, there’ll be more data.

Tian: To your point, 30 patients.

Brian: Monty, did you want pull something up or you want to go back to the poll?

Monty: I was just going to add some comments from YouTube actually, so just on the same topic of PROSPER, and maybe this is relevant to some of the other studies, this guy, Toni Choueiri, again, if anybody knows him, definitely let me… He’s quite vocal on this YouTube chat, says that perhaps one of the other issues was the inclusion of non-clear cell patients in PROSPER. What do you guys think of that? Was that a contributor at all?

Brian: I think to Tom’s point, it’s a bunch of little things. It’s a little this, it’s a little that. There weren’t that many, I don’t remember the numbers. It was single digits, for sure.

Thomas: No, it was high.

Brian: Was it high?

Thomas: Yeah. I can’t remember. I think it’s 15 or 20%. It wasn’t 5%.

Brian: Somebody find out. It wasn’t 15 or 20.

Monty: Could that have made a difference, Tom?

Thomas: Yeah. So 15% the surgery, 10% non-clear cell, 5% and this, 2% that, eventually you end up with a big negative trial. The concern I have, Axel’s point, is if we say we’re going to stay exactly the same experiment a second time, it means we’re essentially saying we’re just disregarding this completely.

David: No one said we’re doing the exact experiment.

Thomas: But it’s six weeks. You said six weeks.

Axel: Combination therapy.

David: Well, he’s got a different…

Thomas: Okay well, now, we’re changing our mind. This is impossible.

David: But the other thing to point out is we’re going to learn a lot more about what happened to these patients. We’re also hopefully going to learn information from the biopsy and then, the nephrectomy, be able to compare in the patients who got paired specimens, what do we see? Do we see changes in the tumor that give us an idea of what we creating immune responses or not? Yeah, it’s going to be a lot. You can still learn.

Brian: I think that’s going to be very challenging, because of sample size of the biopsies.

David: But nephrectomies are like this big though.

Brian: No, I know, but I’m saying biopsies are like this big.

Axel: It didn’t match unfortunately.

David: Okay. We’ll see. I think just stay tuned is what I would say. Stay tuned.

Monty: Can I just push a little further there though? So Tony actually mentions that it’s 21% of folks that were non-clear cell in this context. And so, it’s a pretty sizable proportion. And so, with that in mind, with that in mind, what do we do for our non-clear cell patients? Do we forever exclude them from adjuvant trials?

Thomas: There’s a study called RAMPART. And RAMPART’s an ongoing study. It’s essentially Tremelimumab and Durvalumab best supported care three arm. There’s questions about what you do. Is it ethical to recruit to those trials? We cannot ask that question today. But one of the subpopulations of that study is non-clear cell, and I think that’s one of the really valuable questions that that study can answer.

Tian: You need to find what’s biologically relevant for each of those subtypes, right? Non-clear cell is actually many subtypes, and we have to actually see what is actually active for those patients. So in papillary, could it be Cabo adjuvantly, right? Is that the right treatment? So things that we’re learning in the metastatic space, we have to extrapolate. It may not be a single agent PD1 for all the non-clear cell types.

Brian: We’re going to move on to the next study. Adjuvant Ipi/Nivo CheckMate 914. Again negative study. David, you’re an Ipi kind of guy. You’re an Ipi/Nivo kind of guy. What happened here?

David: Okay, so if you had asked me what I would’ve predicted would happen in this study a year ago.

Brian: Okay, tell us.

David: I would’ve said Ipi won’t add anything to Nivo. Not because I’m some sort of clairvoyant individual, but because we did this study in melanoma of Nivo versus Ipi/Nivo. And the curves are like this. So I’m not surprised that Ipi is not adding to Nivo in kidney cancer. The problem is not that Ipi, although we can talk about the problems Ipi may have contributed, it’s that the combo doesn’t add much, which means it either implies that Nivo is not doing much here or by adding Ipi, you’re creating a toxicity issue that’s either limiting therapy or adding steroids. Both of which are probably not good to an ongoing immune response. But you essentially, to explain how Nivo performed in this trial, you essentially have to invoke the concept that Ipi was harmful in this setting, which may be a stretch. I don’t know.

Brian: Fair enough. Other thoughts? Other comments on why it was negative?

Thomas: I mean this is the hardest to explain. So you can say there was only six months of therapy, and that might be crucial. You can say that the addition of Ipi to Nivo made the toxic so great that you are unable to give the combination. But I think most people in the audience would accept that the PD1 inhibitor Nivolumab should have behaved quite similarly to the PD1 inhibitor Pembrolizumab. Now they might be different activities, and Pembro may indeed be the most active drug in this disease. We don’t know that yet, because we haven’t seen the single arm from this trial. And there is a single arm from this trial, and that’s going to turn out to be really important. Because if that single arm is also struggling, then we’re going to be quite confused about where we are. So this is, for me, I can explain PROSPER. I was okay with Atezolizumab 010. But I find the Ipi/Nivo one particularly challenging to explain.

Brian: Let’s put this slide up. That talks about toxicity, I think you both alluded to. Oh sorry. Actually Ben first, we’ll do a question. Sorry, I forgot.

Ben: Well, I was just thinking more in the perioperative space back in the neoadjuvant setting. Sorry, I’m Ben from Sarah Cannon here, embedded in the community at Tennessee Oncology. If you’re talking about adding duration of immune therapy, you’re also talking about when you borrow from the M1 space, right? There is a dropout rate where patients have primary progressive disease and there is a balance there of taking a patient who is curative and pushing them to non-curative potentially if you delay the nephrectomy. So what I would wonder is, and I think it was alluded to on the panel, is that combination with TKIO upfront, followed by adjuvant IO. I just didn’t hear if anybody else agreed or disagreed specifically with that comment. Because to me it makes a biological rationale when you’re keeping somebody away from that kind of progression, if you’re going to extend immune therapy for too many months.

Brian:                                  IO/TKI neoadjuvant followed by adjuvant IO.

Ben:                                     Correct.

Brian:                                  Anybody want to comment on that?

Thomas: I mean Axel’s well placed to do that. His neoadjuvant trial didn’t show a lot more activity from a response rate than single agent Axi.

Axel: Yeah. But I do believe, that is actually quite interesting, in the beginning I thought. So we work a lot together with the melanoma oncologists and they actually work by the international Neoadjuvant Melanoma Consortium. So they are much more into pathological responses. And interestingly the pathological response we see in NeoAvAx in the Avelumab/Axitinib trial is completely unrelated with your resist response. It’s all over the place. So I do think that immunotherapy initiates pathological responses and the downsizing effect we see is partly due to Axitnib. And that’s also what we saw in the neoadjuvant study.

Monty: Clearly there were toxic issues, issues as shown here. I think somebody alluded a high dose steroid use. We know it’s a toxic regimen, right? Perhaps even more so in the adjuvant setting that limited therapy.

David:                                 Monty if you want to pull up a poll relevant to that.

Monty: Yeah, I’m going to pull that up in just one second, because Cora Sternberg, who actually, I’ll do a Uromigos plug at a Uromigos live meeting who has a brilliant Legends and oncology podcast with you guys. It suggests that toxicity is one of the issues with Nivo IP was, we’ve already discussed, but length of therapy as well. That’s six months of treatment, and actually Sandy Srinivas from Stanford suggests the same. Anybody here on the panel think that perhaps the longer stretch of Nivolumab maintenance things have been different?

I see David about to heavy sigh.

David: No I’m not. I mean the short answer is, and I was a little abrupt earlier with Sandy’s questions.

I apologize, but I guess the short answer is we don’t know how much PD1 we have to give in any scenario for any cancer type. And as a field we probably should try to figure that out because we’ve given PD1 to so many patients, so there are some who probably need indefinitely. We learned that on the original trials of these agents, because you had to stop at two years. Some patients stayed in response like the melanoma patients. A lot of other patients, lung, bladder, kidney and some of those patients who progress after stopping actually could be salvaged. So we need to understand who those patients are and without understanding that we’re setting ourselves up for trials like this.

Monty: Fair enough.

David: That gives us negative results.

Monty: Everybody else want to comment on duration? It’s hard for me to believe six more months of Nivo would’ve made this a positive study.

Tian: Yeah, I’m very curious to see the Nivo lung report.

Monty: It’s pretty small. I don’t think anybody knows the size of it. Dan’s got the box.

Ben: Just real quick. So if you go back to the capital curve, you had probably the best placebo result here with two years at 74% disease-free survivals. Is that the issue here when again not picking the right patients for these kind of Studies?

Axel: Want to make a comment about this as well because I think that the placebo arm is at the level of the effectivity arm in the keynote. And what you alluded to before, I think we haven’t yet figured out, for example, the INDC score that largely coincides with this genetic risk profile, which still has to be validated or is being validated. But we don’t have anything like this for TNM. We don’t know whether the higher TNM stages are actually more responsive to IO.

Brian: In David’s point earlier, clinical way of stratifying patients in this setting probably has nothing to do with their response to I immunotherapy.

David: Biology’s more important than stage, it’s more important than nostalgia.

Brian: We just don’t know how to measure it. Thomas?

Thomas: I was a little bit frustrated that there was no survival data shown here. This is a negative trial. The primary point’s read out. It’s never going to be a positive trial. So it’s not like we’re waiting for an event that’s in the future going to be different. And I don’t see the disadvantage of showing survival data. And one of the things that I saw at ESMO in different areas was we didn’t see the survival curve for prosper either. I’m told that in the abstract, the hazard ratio for survival was 1.46. Then the hazard ratio 1.46 in the abstract then wasn’t in the presentation. Because that sort of hazard ratio, you look at in very few events, but you think that should be there, they’d done it and it’s a survival, it should be there. And then here again, this is a negative trial.

You can show it, you can say, it’s underpowered, but this is the curve for what it’s worth. But I’m nervous that in the kidney cancer community we really are getting into the habit of doing analyses and not showing them, and particularly for survival. And I think we as a group need to perhaps, and I’m maybe part of the problem, but we as a group need to make sure that we do when we do show survival signals when we know they’ve been seen. And it’s often people say, we haven’t finished the trial, it’s not unblinded yet, but actually in the adjuvant setting for example, you’ve had your year of therapy the minimum full of 16 months. Everyone’s been through that and no one’s going to volunteer to die in one or the arm or the other. So it’s actually okay to show these survival signals, even if they’re immature.

Brian: I Agree.

David: So that was a nice speech and we’ll have to remember it in a few minutes. Remember that everyone. It’s like Macbeth.

Audience Member: So this is kind of about the 914 data. So I think when we talk about risk, this trial excluded the M1 NEDs. It included the low grade T patients, T2 patients, which is why I think the control line was performing a lot better and maybe these people are going to be cured irrespective of therapy. I think that’s weighing in and I think with regards to duration, they were intended to receive the four doses of IPI on that six week schedule, not the three week schedule. Which is very different than what we do in the metastatic setting. So I don’t think we can chalk it all up to duration of therapy.

Brian: Okay. Monty, you want to pull up the poll?

Monty: Yeah, yeah, let’s do it. Let’s do it. While that’s coming up here, I’ll just point out that Sandy Srinvas says she is fine with your comments Dave.

Audience Member: Virtual hug.

Monty: And I’ll just point out the result of what we got ahead of the meeting with actually a pretty robust response to our polls I might say. So if you look to the bottom right over here, these are reasons that we posited for perhaps 914 being negative. So you can see if fifth of folks thought that adjuvant Ipi itself was not active in this setting, a fifth suggested that the trial needs more time to mature. I’d be curious to run thoughts on that. And then more than half suggested is this rationale of excess toxicity. And Mike Staler points out our good friend who’s a surgeon out in Germany, we all know him very well, suggests that there were five deaths on account of toxicity in the adjuvant Nivo study. To your point of looking at overall survival, is that an issue? Does it call out Tom’s point of looking at these OS curves perhaps

David: Who you’re addressing that to?

Monty: Not to you? I think just in a general direction. I think he’s saying Tom was saying we need to see survival and maybe that there could be a signal there even if there’s not in this. Right?

David: So in melanoma not to talk too much about melanoma, we don’t see OS in any of the trials and that has caused people in the field to pull back from the application of immune checkpoint blockade. Even in settings where it’s approved. So for example stage three a melanoma, which is most of the melanoma we see in clinic, we often don’t reflexively give immune therapy in part because of what Monte’s talking about is occasionally we’ll have a patient who’s a train wreck or a death with immune checkpoint blockade and that is completely unacceptable and it leaves a mark. So at some point you say, do I want to keep doing this? In some ways this data is more reflective of what you’d see in practice then what we see in Pembro, which is a very clear safety profile, but it’s probably unrealistically clear for what’s going to happen in the community when we start giving these drugs.

Thomas: In the Pembro trial there is a trend towards overall survival. It has ratio of 0.53, it’s not significant but it is a trend towards survival with a follow up we currently have. And that’s encouraging. And if that trend continues then that will be a significant result. When you see patients and have a conversation with them, because they’re not going to be able to make a decision in two years’ time today you have to imagine therapy in a short window. You can say to them we don’t, there’s uncertainty around survival, we’re clear it’s going to delay the times your cancer coming back. And there’s a trend towards survival with underlying toxicity. And that’s encouraging and that’s quite a positive thing to say. One of the issues that I had with Nivolumab yesterday with the bladder cancer is we haven’t seen that survival, so that makes that conversation in my opinion more complicated.

It would’ve been easy to show the survival curve here and if the curves are indeed on top of each other or the wrong way around, that’s even more evidence that you might say irrespective of the PFS analysis from PROSPER. If the curves are the wrong way around, all those issues, I said about how you measure PFS and all the bits and pieces, it’s difficult for them to have influence on OS. If OS is miles away, you can say well this approach clearly is not working. So I think there is a lot to learn even from early OS signals without making any significance from them.

Monty: Agreed. We’ll go back to the slides. This is a table that looks at kind of, David you brought this up, you maybe IPI is detracting in this setting, right? So this is single agent Nivo data again from HCRN from Titan, which was Oliver Grimshaw, I think updated at ESMO this year. The original Checkmate data, which is obviously the most mature. There was a study, a UK study called Prism, which gave modified IPI dosing. You see, in that second to last column, Q 12 weeks of IPI, it was a randomized phase two. And then the control arm of cosmic is obviously a big Ipi/Nivo data set. And I know there is tons of imperfections in these tables. You don’t need to point them out. Everybody on Twitter has pointed them out to me. Thank you. But they’re really just to, if we look at single agent data and combo data, and this gets to a bigger metastatic question that we can come to in our second section. Do you think IPI is adding or detracting to Nivo, David?

David: I think based on the data we have now, it’s adding, it may not be adding a lot but I think it’s adding in two places. It’s adding in the primary PD rate, which is the major weakness of pure IO regimens compared to VEGF PD1 is those early progressors who will die if they don’t get VEGF up front. But in C284 combos you see a little bit less primary pd. It’s adding in the CR rate, which in those deep responses like CRs and very good PRs tend to be those patients who are out at the tail of the curve and those who can come off therapy and live in remission. So I think it’s adding, but if you’re asking me what I’m expecting from the 8Y8 trial, which will address this question.

Monty: I wasn’t, but go ahead.

David: I’m nervous about that trial and we’ll see, hopefully we’ll get those results.

Monty: Because it adds in ways that may not be obvious on traditional endpoints.

David: Absolutely.

Monty: Early endpoints.

David: Right, so once again, if we continue to do IO studies with targeted therapy endpoints, we’re going to see confusing results. You need to look at things like landmark progression-free survival, for example, as opposed to median progression-free survival.

Brian: Agreed. Tian, UT Southwestern use a lot of Ipi/Nivo, right?

Tian: We do, we’re prescribers. But of the 214 data, what’s really impressive is that five-year progression free survival curve. There’s about a third of patients that don’t progress and those are the patients that we’re doing the most benefit. And also the treatment-free survival data that’s David and Meredith have put through. I mean think it’s really important the time that patients can stay off of treatment and so those end points are not captured in this table.

Thomas: Can I jump in?

Brian: Please.

Thomas: So the first thing is the progression-free survival curve of CheckMate 214 is a lot more complicated than it looks. That 30% at the landmark only represents 10% of patients. So 500 or a hundred percent of patients start on the trial at that PFSs at five years that we talk about in 10% of patients get there. So the censoring of two thirds of the patients beforehand, if for example you didn’t get the four cycles of Ipi/Nivo, you only got two, you’re censored. There are lots of early censoring and so although it says it’s 30%, it’s only 10% of patients and that creates a huge amount of uncertainty. Okay, that’s really important. Number one. No, let, keep going, let, let me keep going. So that curve is, it is a progression-free survival curve but there is a really heavy century and we’re not talking about that enough.

That’s important point number two if I may. Number two, this treatment-free interval is also complicated, cause it’s not like patients were going along happily say Okay, I’ll stop my drugs. Great. No, they have to get into toxicity, they’ve got to have problems. They can no longer have the drug. And once you’ve got into those problems with the drug, you can then stop. You have to crash the car before it will break. You for crash the car before you get out of it. The issue with that is there’s going to be a bias associated with that because we know that immunotherapy tends to work a bit better in those patients who get adverse events. So essentially you’re selecting out the winners and so this progression-free, this treatment-free survival piece is not pure treatment survival in a benevolent, you’ll stop the drug and see what happens. It’s you’ve got grade three or four trans and we have to stop the drugs and those patients do relatively well. So two problems with the CheckMate 214 study. Now don’t get me wrong, it’s a great trial. The landmark O is fantastic.

Brian: You’ve already done the damage. I wouldn’t bother with it. David?

David: Axel wants to speak.

Brian: Oh Axel first, then we’ll do David’s response.

Axel: So I would very much support your view David, because I think one, we have a couple of patients, we have a series about those doses who are treated with a primary tumor place. And if you look at those ones who have been treated with Nivo and those ones with Ipi/Nivo, they’re much more pathological responses in there. And I think it’s just a small group, but where you can achieve deep responses with the combination. And that’s also based on the adapter data that it with Nivo mono for example, did the theories are that if you do have a clonal T-cell response in your primary and you happen to have a very clonal reaction to a new antigen, then you’re in for a win and you give it. And I think that you need CTLA four to stimulate that.

Brian: So David may give you the last response on this, no swear words, don’t insult anybody and don’t hit Tom say your piece about TFS and what Tom said about the censoring and then we’re going to move on to the future of adjuvant therapy.

David: Okay, well what I would start by saying is Axel should be at more of these, your Uromigos podcasts.

Brian: We’d love to have him.

David: I’m only joking a little bit, but he’s a surgeon and this is a medical oncologist, a GU medical oncologist who spends most of his time taking care of what he thinks of as incurable cancers. Whereas the surgeon is only concerned with curing the patient. Anything short of curing the patient is a failure. Right? You don’t pat yourself on the back if you didn’t get the whole tumor. If you get the whole tumor, you’re like, we got it all. Thumbs up. That’s to me, we as medical oncologists need to move toward thinking in potentially curable cancers like kidney cancer, more like surgeons and less like geomedical oncologists. So kidney cancer can certainly be put, we all know this, you all, everyone in the room knows this now. You didn’t know this 20 years ago, but you know it now you have patients who are in remission after getting immune therapy for metastatic disease.

Brian: Yes.

David: Right. So to me, in the hierarchy of endpoints, remission is most important because it’s those patients in remission that will be potentially cured. I’m not sure all PD1 responders are cured, but sure they’re certainly in remission. Right. And TFS is a way of measuring, at least in part remissions for the entire cohort. Not just the winners. It’s not about showing that Nivo is better. It’s about, let’s take the whole cohort of patients and measure the pluses and the minuses of immune therapy. Because we’re not just talking about treatment-free survival alone, we’re talking about treatment-free survival with and without toxicity. So to your concern about crashing the car, whatever that means, if you were crashing the car with Ipi/Nivo, that time of treatment free survival would be spent mostly with toxicity. And it is not. Okay. It’s not. So there’s more treatment-free survival in the Ipi/Nivo arm versus the VEGF arm.

What we need to do is a head-to-head comparison of IOIO versus IO VEGF. And one of the tradeoffs with IO VEGF is you spend most of your time alive on drug and then you put it up to the patient. So you say to a patient, survival is similar with these regimens, but you might spend twice as much time off drug and some patients might be willing to go through the talks for that trade off, but it’s about agreed tradeoffs and it’s an end point that can be measured before treat treatment or can be explained before treatment. So it helps with clinical decision. It’s making, It’s not just about…

Brian: Don’t think we’re going to solve this today, I’m feeling.

David: I didn’t even get to the PFS thing, which is…

Brian: Okay, give me 30 seconds about. Tom’s PFS again.

Thomas: No go Dave go.

Brian: The only person ever to swear on a Uromigos podcast, David. 200 podcasts. Anyway, don’t worry about that. 30 seconds.

David: There’s a ton of patients on those curves.

Thomas: Yes.

David: At the end. You’re talking about the patients who haven’t been censored as if somewhat as censoring is somehow a bad thing. These are people who are out there. They’re alive, they’re more than you are estimating that are progression free. They’re just censored because they’re administratively censored based on when they did the data cut off.

Thomas: Yeah. No, I said that. But when you get to the five year time point, they’re not there on the PFS curve. They may be there on the OS curve.

David: They are there.

Thomas: No, they’re on the early part of the curve, not the late part of the curve. They’re not on the late part of the curve. I mean, there is the curve.

Tian: They’re not at the at risk. We haven’t seen them. They’re off the curve.

Thomas: Well, they’re on the OS curve. They’re no longer on the PFS curve.

Tian: That’s right.

Brian: I don’t think we’re going to settle the censoring issue, but I think there is a lot of censoring and it might actually be underestimating that plateau, right?

David: Absolutely.

Thomas: It could be. It could be.

Brian: It’s not just a bad thing.

David: Because TFS is a hard endpoint. You’re either on treatment or you’re not. In some ways it’s a better way of measuring the impact of an immune therapy than PFS is because PFS is a dodgy endpoint. Because you were just-

Thomas: Okay. I’ll accept that. I’ll accept that bit.

Brian: All right, let’s move on. Let’s move on. I think this is our last slide-

David: I’m ready to go.

Brian: -before we go to the future. So this is just a summary slide on Keynote. It’s the updated data. Anybody want to comment? We saw what the Twitter poll said about more or less use or the same. Anybody who gives this in practice want to comment on whether it’s impacting your practice? All the negative data we talked about and all the caveats in these data? Tian, you getting more or less the same?

Tian: So I mean, we have conversations with patients. These trials certainly show that if you’re going to use an adjuvant treatment, you’re going use adjuvant Pembrolizumab. But the person that you’re going to use it in may differ. And the patient who sits in front of us to tell us, “I’m accepting every three week visits, I’m accepting IO toxicity to potentially delay as much as I can. As much as we know in 2022, I want everything you have.” That’s a patient that should be treated and is at high enough risk. There’s another patient that comes in and says, “Doc, I will accept that there’s two-thirds in the control cohort that don’t progress by two years. I’m going to wait until I absolutely-”

Brian: But are those conversations different now with three negative trials? It’s always trade off in benefit risk.

Tian: I will say-

Brian: Are they different from your perspective?

Tian: It’s very binary for the patient in front of us, right? They’re either going to recur or not. And so I cannot look in the glass ball and predict that for them. So I can only help them make that decision of is a year-

Brian: I understand. Are you thinking about it any differently now with three negative trials or not?

Tian: I’m still having this conversation about Pembrolizumab.

Brian: Axel, what do you think?

Axel: We just updated the EAU guidelines and we also have patients representatives on the panel and they actually suggested, and we took this over as a recommendation, that patients are informed that there are other trials out there that are negative, but for them it doesn’t necessarily change the way it will be given, but the information should be out there. So it’s a shared decision making.

Brian: Does it change your approach, yes or no?

Axel: No.

Brian: No for Axel. David?

David: No. The only thing that would change my approach is if that OS signal goes away and it’s possible that it might, and if it does, we’ll get into a similar discussion as we do in melanoma, which about risk and risk reduction. I mean, Katie Beckerman had a great slide, which I think she might have borrowed partially from you about risk reduction. We need to understand what are the risks based on that person’s stage and how much is going to be reduced? Because when you have that conversation about that, when they realize that their risk of recurrence may be only 15% and the drug only brings it down to 10%, whatever it is, people think of it differently. That’s a hard conversation for me to have. But that is, I think more-

Brian: Thomas, yes or no?

Thomas: Dampen the enthusiasm in the field undoubtedly. I think there has to be a conversation with the patients around the fact that you haven’t got before it was easy. We’ve got lots of other trials coming through. Really exciting. I think now the conversation is, this is the standalone drug that seems to have been successful. Others for various reasons haven’t, we don’t quite know why and we haven’t seen overall survival yet. So I think it’s more complicated.

Brian: Awesome-Yeah, sure. Tom-Throw them the mic.

Tom: The one thing I would say is for the people up here who are designing the trials going forward is there is so much heterogeneity in this T3 group of patients and as a surgeon, it’s frustrating because to me, there are four levels of T3A. It’s really not that substratified in any guidelines, but there’s perinephric fat, renal sinus fat, small vessel invasion, large vessel invasion. Perinephric fat, especially in a small primary tumor, carries a minimal risk of recurrence. I mean these are 8%, 10% in your large vessel renal vein patients who are T3A, I mean could be 50-60% patients who were going to recur. So I understand the comment about biology trumping stage and I think it’s great. I hope something that comes out of all this is that these stages and some of these issues and the guidelines are addressed because really, one T3A patient is definitely not like all the others. So I’m hoping we can start throwing out some of these really low risk T3A patients.

Brian: Yeah, I totally agree, Tom. Thanks for your comment. All right, we’re going to move on. The last part of the live stream is where we’re going from here in adjuvant therapy. You each submitted a slide of what you would want to do for the next adjuvant trial. When your slide comes up, you’ll discuss. There is going to be a prize for the winner. We’re going to vote at the end and my patient, Michael, is here in the room, made a golden kidney. All right. It’s a 3D printer. 3D printer, Michael. So we’ll vote by applause or something. Whoever has basically the best trial. The best trial put forward will win the golden kidney. All right. Let’s see who’s first. Tian.

Tian: Oh, that’s mine.

Brian: Give us a 30 to 60 second summary. Then we’ll discuss.

Tian: I think in the adjuvant setting, finding the right patient to treat is really the important part. So I would love a future trial where we’re selecting on a biomarker and deciding on a negative thinking about surveillance versus IO alone versus in a biomarker positive, maybe IO alone versus VEGF IO presuming they’re all active treatments.

Brian: Can I ask a question? What’s the biomarker, to be determined?

Tian: To be determined.

Brian: And you’re comfortable doing surveillance, no therapy in a biomarker negative?

Tian: The placebo cohorts, I mean they’re all-

Brian: Okay, I’m just asking you. Okay. And you want to give VEGF IO and biomarker positive even though VEGF has been-

Tian: There’s microscopic disease and VEGF probably still has activity.

Brian: Okay. Others? Comments?

Axel: I think it’s good because it also has treatment deescalation in it. So it’s a bit like in the BIONIC trial if you thought about doing crossover, like looking at recurrence for survival and if that’s earlier then they go into the active treatment arm. Something like this.

Brian: You’ve also limited duration to six months in your biomarker negative as one of the arms.

Thomas: Tian, do you want to use HEF rather than VEGF? Would that be something that would be a different type of question?

Tian: That’s a really interesting question. There’s an active ongoing trial LITESPARK-022, which is asking that question, right? Of HEF IO in this space. So we’ll have that answer eventually.

Audience Member: Right. Very quickly.

Brian: Yeah, sure.

Audience Member: It’s about the duration of therapy, Tian, on the 6-12 months. Going back to that comment. I was looking at Keynote 564, 20% of patients stopped treatment because of toxicity. The number was 33% on the Ipi/Nivo. We don’t know how much was Nivo stopping? Does even adjuvant therapy in distal other tumors, that might be the treatment duration may play a role when you have recurrence. Does it matter if you give six verse 12 months? Based on all the above. Does longer therapy potentially explain part of the region why Ipi/Nivo is negative?

Brian: I think the summary could be part of the reason. I kind of doubt it’s the whole thing. Yeah, it’s hard to believe just six more months and Nivo would’ve rescued that trial. I don’t know if anybody has a different opinion.

Tian: Those T-cell are active, right? Once you’ve given six months, those T-cells will stay active for another six to nine months. So I don’t know that we’re stopping their activity. The people who stop, are they on steroids and things? But I think if we’re in a future state and we have a good biomarker, then maybe we can do some better patient selection.

Brian: Do you think maybe VEGF or HEF in the adjuvant setting maybe doesn’t make sense because the biology of rapidly recurring disease is probably not HEF driven. Right? Those are the indolent, long endocrine organ type recurrences. So that’s I think my biggest issue with HEF in the adjuvant setting. David.

David: Well, you did the HEF IO combo study. The only one that I’m aware of, right?

Brian: In the advanced setting, yes.

David: In the advanced setting. So what’s the evidence that HEF blockade enhances the immune response to the tumor or enhances the effect of Nivo? What’s the evidence?

Brian: I feel like you’re asking me a question you know the answer to. There’s no evidence in my knowledge.

David: Correct. Right. Zero. Unfortunately, that study was never published. But to go into the adjuvant setting without evidence that HEF blockade adds to PD1 blockade. Once again. I mean it might be a good idea, but we have no evidence why we’re going to… This is obviously not criticizing Tian. I’m just saying this is a larger trial. We should do this study-

Tian: I’d like to point out there’s no HEF on this slide.

David: No, I know. I’m criticizing Tom.

Brian: Oh, that’s allowed. That’s encouraged.

Thomas: That’s okay.

David: I didn’t want people to think I was criticizing you.

Brian: Of course. Of course. Tian, strong start for the golden kidney. All right. David, you’re up.

David: I already described this trial earlier, just essentially repeating the melanoma study in a selected group of patients. I think to Tian’s point, I don’t think we know exactly how to select, but we have some clues of patients who are more likely to benefit based on the studies we’ve done. So enroll patients, not based on stage, but based on these enrichment criteria, give half of them presurgical Pembrolizumab, the other half just post and see what happens. And it’s as good of an idea as any because we actually have randomized data in several tumor types that it’s a good idea.

Brian: I think you’re trying to influence the vote there. David is.

David: No, I’m not-

Brian: Yes, chop up. I don’t know where the cube is.

Audience Member: I have a question about the state. So you are proposing patients with stage 1B plus something should be offered adjuvant therapy.

David: Correct.

Audience Member: Then we saw the data with stage two and we discussed that maybe the stage two diluted the effect of Ipi/Nivo? Just curious.

David: Well, right. I think patients would know. In my opinion, PD1 only works if you have an immune response to your tumor before you give it. So these criteria that I pick there are enriched for patients who are more likely to have a tumor related immune response before treatment. That to me is more important than the actual size of the tumor. If you don’t have immune cells in your tumor head of treatment, PD1 doesn’t do anything.

Brian: All right. Good job. David. This is Axel.

Axel: It’s a bit like what David had in mind that I was a bit more hesitant whether it would be time for a phase three at the moment. So this would be randomized phase two. A bit like what they’re doing in melanoma, that you actually decide about treatment de-escalation. The thing is you need clinical TNM, but we have experience from NeoAvAx how to do that. And then you would randomize 1:1 40 patients per arm. The new adjuvant arm would be a Simon two-stage design where you would test the hypothesis because we have biomarkers, but they’re not validated yet. So you treat six weeks with Ipi/Nivo or Pembro/Axi, but I would say you have to hit the tumor hard. Then you do a nephrectomy and based on the pathological response, which is defined according to the melanoma criteria, you decide about whether you continue or not.

The theory is that you can at least say 40% of adjuvant therapy if you’ve taken your decision. Then secondary endpoint would be disease-free survival over survival. If you would already see massive differences there, then you would know you don’t have to take this theory to test. But if you wouldn’t, then this would be an ideal basis to continue with the phase three.

Brian: Adjuvant Pembro with neoadjuvant Ipi/Nivo just to match the other arm.

Axel: Exactly. But then based on the results in your primary tumor and the pre-treatment should be six weeks.

Brian: Okay. Thoughts? Tom, you want to say something?

Thomas: I think that there’s something really attractive about this as a sort of a second generation trial. I think one of the questions about whether or not you need to keep Ipi/Nivo neoadjuvantly and the fact that adjuvantly, it hasn’t worked, and that’s a complicated issue. And I think you’d have to tease out those components. I think the 8Y8 trial’s going to be important. I think that’s positive. There’s going to be a lot of weight behind Ipi and I think it’s going to be hard to say it doesn’t work. It is active and it’s working really well. It’s adding stuff. I think if that trial’s flatly negative, that’s going to be a problem. So the debate around Ipi will be solved relatively soon.

At the moment, it looks like the response rates are a little bit higher and the PFS is a little bit longer than you’d expect with Nivo alone. But it’s not turned out to perform well in this big randomized trial and that’s an issue. The question in this trial is, do we think this is going to cure a whole lot of additional patients that we weren’t curing before? And that would be a surprise if it did to me because Ipi/Nivo hasn’t been successful in the adjuvant setting and we’ve got PROSPER as a neoadjuvant trial, which hasn’t worked out that well. Having said that, this is the sort of trial randomized phase two, exactly the sort of trial that we should be doing because it’s a modest size and we can get really interesting biology from this. So I think this is a great trial design. I’d actually like to see a third arm with Ipi alone. And the reason why that’s the case is then we could do some comparison of tissue of Ipi versus Ipi/Nivo, which I think would be cool.

Brian: Yeah, agreed. Okay, last but not least, Dr. Pal.

Monty: Yeah. So I have to tell you, when I got the results from EMOTION it was near and dear to my heart, one of the kind saddest days of my academic career. But I was actually in Greece with Brian and Petros and we went out for drinks until about six in the morning. So I felt better. But what I would really love to do is really pull a rabbit out of the hat. And I’m really going to use something that was really born out of Tom’s genius, which is to really look heavily at biomarkers, in particular ctDNA in this context. It’s going to be harder to do in renal cell, and that’s why I’ve left the MRD assay here unspecified. Rena’s doing some really nice work with Natera. We have some biomarkers we’re looking at with a different company that we’re quite excited about for really assessing MRD in this population.

But if we can do something very much akin to what Tom has done, taking InVigor 0.0 to InVigor 0.1 in bladder, I think that that might be a win for us in kidney cancer.