Overall Survival and Efficacy Results of Second-line Treatment for Patients With Metastatic Clear Cell Renal Cell Carcinoma, BIONIKK Trial -Yann Vano
March 23, 2023
Yann-Alexandre Vano, MD, Medical Oncologist at Georges Pompidou European Hospital, Paris, France
Pedro C. Barata, MD, MSc, Leader of the Clinical GU Medical Oncology Research Program, University Hospitals Seidman Cancer Center, Associate Professor of Medicine, Case Western University, Cleveland, OH
ASCO GU 2023: Overall Survival and Efficacy Results of Second-Line Treatment in Patients with Metastatic Clear Cell Renal Cell Carcinoma (mRCC) Treated in the Randomized Phase II BIONIKK Trial
Nivolumab, nivolumab-ipilimumab, and VEGFR-tyrosine kinase inhibitors as first-line treatment for metastatic clear-cell renal cell carcinoma (BIONIKK): a biomarker-driven, open-label, non-comparative, randomised, phase 2 trial.
Pedro Barata: Hi. I'm very happy to be joined today by Dr. Yann Vano from the Medical Oncology Department out of Georges Pompidou in Paris, France. Dr. Vano, thank you so much for joining us once again.
Yann-Alexandre Vano: Thank you, Dr. Barata, for the kind invitation.
Pedro Barata: Absolutely. And it's really a pleasure. I mean, as we talk about biomarker in renal cell carcinoma, the BIONIKK work always comes to light as one of the first biomarker based approaches, especially the IO based approaches, IO based combos, particularly ipi-nivo, for these patients. So first of all, congratulations.
Yann-Alexandre Vano: Thank you.
Pedro Barata: Another great job presenting these follow-up data or updated analysis of your BIONIKK study. I think we got quite interesting findings and more important new information since the last time we chat about BIONIKK. So let me just start by just can you remind the audience what the BIONIKK study was, the way it was designed for patients with advanced renal cell carcinoma?
Yann-Alexandre Vano: Yeah. Thank you. The BIONIKK is a randomized phase II trial. It is a non-comparative trial based in France and we performed it in 16th Center in France. And basically the patients in first-line metastatic were randomized according to their tumor molecular group between nivo, nivo-ipi and VEGFR-TKI which was sunitinib or pazopanib. And we identified the molecular group of the tumors, group ccrc1-4. This is work previously published. And patient with ccrc1 or 4 tumors were randomized to receive nivo and nivo-ipi and patient with ccrc2 and 3 were randomized to receive nivo-ipi or VEGFR-TKI.
We previously published, as you said, the results, the first result, in the Lancet Oncology in May, 2022. And we had follow-up of 18 months and we showed that nivo based therapy were more effective in ccrc4 than in ccrc1 tumors. And nivo-ipi was more effective than nivolumab alone particularly in ccrc4. This is the first findings based on overall response rate, objective response rate, and median progression-free survival. And the second result is that in ccrc2 tumors, VEGFR-TKI alone provided high response rate and very prolonged median progression-free survival comparable to those with nivo-ipi. These were the first results.
Now we have made an update with 46 months of follow-up and we now have overall survival data because during the first publication we have 20% of events. Now we have 46% of events. So we update the overall survival. And by treatment arm, we are overall survival not reached yet with nivo-ipi, 35 months with nivolumab and 35 months with nivolumab and 45 with VEGFR-TKI. And when we look by molecular group, we see that nivo-ipi is clearly a superior to nivo alone in ccrc4, particularly in ccrc4. And so we confirm our previous results with OS data and we see that in ccrc2 tumors, nivo-ipi and TKI had not reached their median survival and they are quite comparable. The cures are similar.
This is very interesting to see differences between this molecular group and we also updated the median PFS has not changed.
Pedro Barata: Gotcha.
Yann-Alexandre Vano: But overall objective response rate increased because we have some stable disease patients who became responders. And we reached 55% of objective response with nivo-ipi in group four, in group two particularly. And we have 58% with VEGFR-TKI in group two. So we confirmed our previous results that in group four, nivo-ipi provides best results and better than nivo alone and TKI is still very relevant in ccrc2 tumors based on overall response rate, PFS and now overall survival.
Pedro Barata: So it's great summary and great job, because you showing this almost four years later and it's very relevant, it's clinically significant because the data seems to be quite mature. And that's great. Let me ask you a different question, which has to do with some of these patients, unfortunately still a good number of patients, end up progressing on IO based approach, on ipi-nivo or nivo based approach, I should say, in BIONIKK. And a lot of times, they go and end up getting TKIs for the most part. Not all of them. So let me ask you the question. Can you share with us what happened to these patients upon progression on frontline regimen? How is the... It's a European study. So perhaps there are different patterns there compared what we do in other places in the globe. Can you share to us a little bit of that?
Yann-Alexandre Vano: Yeah. Yeah. This is the second part of the results, is that we looked at the second-line treatment and based according to the first-line treatment and to the molecular group. So the first remark, it's that 20% of patient are still in first-line after 46 months. It's quite interesting to see that. The second point is that we have a majority of patients who have the second-line. We have nearly 67% of patients who have a second-line, and the vast majority of them have a VEGFR-TKI, which is quite logical in the context of the trial and the available molecules. If we look at the type of TKI, 54% of patients have cabozantinib, which is quite a very effective second-line treatments post-IO. And if we look the efficacy of TKI, we see that we have a particular efficacy in term of objective response rate, more efficient TKI in ccrc4 after nivo-ipi than after nivolumab alone.
Just an example, 33% of objective response rate of TKI post-nivo-ipi in ccrc4, 11% response rate post-nivo in ccrc4. So TKI post-nivo or post-nivo-ipi does not have the same result, the same efficacy. And if we look at the best response with this TKI in second-line was after TKI or nivo-ipi in ccrc2 with the highest response rate and the highest median progression-free survival. So we think that we still have an influence of the molecular group on the efficacy of the second-line and probably we have the influence of the type of first-line on the efficacy of this TKI in second-line. And we see it with the overall response rate and progression-free survival in second-line.
Pedro Barata: Right. It's very interesting results. And I agree with you. And that's why I think subsequent therapy is a relevant point because it kind of shows that the outcomes that you got, you know, in the context of patients having access to therapies that we commonly use. And I think that's a very important point clinical speaking. Let me talk a little bit about the biomarker, because we have been challenged by what signatures to use. We now have an emergence of a few of them. They seem to be more or less successful for their specific IO based approach. And then a lot of times, there's been shortcomings when you try to apply that specific signature to different combinations.
With that said, I do know that you're working on... I don't know if the right word is optimizing it, but you're working on the 2.0 signature based on the BIONIKK initial signatures. Can you address this point? Where are you going with that? Where is next steps for the genomic signatures that are evolving from BIONIKK? And what do you think is left to be done for us to actually have one signature that perhaps allows us to understand who can get class of agent rather than a specific drug? Can you comment on that?
Yann-Alexandre Vano: Yeah. You're right. We have a lot of gene expression signature. The advantage of our signature is that you can classify patient by patient. It is a very powerful tool to be able to classify each patient. At the opposite, the other gene expression signature needs to have a cohort to classify all patients. And now with this algorithm, we can classify each patient by patients. But the problem is that we are not able to apply this signature to another cohort. So this is a problem of our signature. And the other technical difficulty is that we performed, we made the signature on frozen tumors samples. So it's quite difficult to obtain. If we have biopsy, it's not... We have a lot of failure to classify the tumors. So we are working on a more simple signature and a more comprehensive and more specific signature related to a pathway, because we have a signature of 35 genes, but it relates to metabolism, gene...a little bit some genes of androgenesis, related to androgenesis and some are related to immune signature.
So we have an immune part signature in our 35 genes. This immune part is dedicated to distinguishing between ccrc1 and ccrc4, because ccrc4 are very enriched and inflamed tumors and ccrc1 are very desert tumors. So we have some genes that discriminate these two groups. And we are working on this minimal signature to look at the efficacy of IO based therapy and TKI as a control. This is a signature and transcriptomic part of the ancillary program. We have a protein in situ program and we have a result. We presented result at the last ESMO meeting on the [inaudible 00:11:15] structures as the predictors of efficacy of IO based treatment, nivo and nivo-ipi. And it is [inaudible 00:11:24] which was our postdoc and she's now in Boston who work on that and we are going to merge all this data, in situ data and transcriptomic data, so protein and transcriptomic, to see if we can enrich our predictors.
And the main problem in BIONIKK is we are lacking TKI-IO arms. I think this is the big point. We can predict IO, IO efficacy, but we don't know how it works with TKI-IO.
Pedro Barata: Right. So that's a great point. You talk about the performance when you bring a TKI to play, right?
Yann-Alexandre Vano: Yeah. Yeah. Because-
Pedro Barata: Especially if you go beyond the immune signature, if you will.
Yann-Alexandre Vano: Yeah. Because all the biomarkers that we looked at are not working with TKI alone, but we can't extrapolate and say if it don't work with TKI alone, it will not work with TKI plus IO. We don't know.
Pedro Barata: Right. Well, those are fantastic points. I mean, it's always, as usual, a fantastic conversation, discussion. Again, congratulations. Great job. I'm looking forward to see the updated analysis published. And I'm sure we're going to be chatting again about molecular signatures. You're really pioneering the work in this field. And I feel we're really getting closer to start using them as a way to select our patients better. So with that, thank you so much for joining us. Congrats.
Yann-Alexandre Vano: Thank you very much. Thank you.
Pedro Barata: Thank you.