Pedro Barata: Hi, and welcome to another UroToday video here post ESMO. And today, I have the pleasure to be talking to Dr. Berkay Simsek. He's a pathologist. He's also a postdoc fellow at the Brigham Hospital, doing amazing work in renal cell carcinoma. Very happy to get him here today to talk to us a little bit about the exciting correlative work from the COSMIC-313 trial. So welcome, Dr. Simsek. Thanks for joining us.

Berkay Simsek: Oh, hello, Dr. Barata. It's a pleasure to join you in this discussion.

Pedro Barata: I appreciate that. So congratulations. You are part of the mini oral session at ESMO. You presented really interesting results around the COSMIC-313. Specifically, you're looking at around immune cell populations, biomarkers of response on this trial. But perhaps, first things first, would you be so kind and remind us of the COSMIC-313 trial that was conducted in the frontline space and read out?

Berkay Simsek: So COSMIC-313 clinical trial is a clinical trial that is comparing ipilimumab plus nivolumab therapy to cabozantinib plus ipilimumab plus nivolumab therapy, as first line in the advanced clear renal cell carcinoma patients. And my work is mostly focusing on the ipilimumab plus nivolumab, the pure immune checkpoint inhibitor therapy.

Pedro Barata: Right. So that's great. And just a reminder for our audience that the study was positive for progression-free survival, but there was no overall survival difference identifying the trial. And therefore, it did not change practice at that point. We learned a lot from bringing a TKI on top of a dual immunotherapy, which was, as you said, the standard of care arm. So I would love to dive right into what you presented at ESMO. You're doing an amazing work on the correlatives for this study. Can you please describe to us what you and your group have been doing in regards to the immune cell population and what your findings were?

Berkay Simsek: So our group is mainly focusing on the tissue-based biomarkers, and we are investigating, actually, either biomarkers of response or resistance to immune checkpoint inhibitor therapy. And in this regard, like my work on the ESMO that I presented, specifically on the ipilimumab plus nivolumab. But we have been working also in some previous clinical trials like CheckMate 010, CheckMate 025, like salvage mono anti PD-1 therapy or HCRN GU16-260, the first-line nivolumab therapy. And we are investigating the tumor microenvironment with multiplex immunofluorescence staining, focusing on various immune cells. But the focus of part of the study that I presented was about the cytotoxic T-cells and actually the various stages of exhaustion of the cytotoxic T-cells.

Pedro Barata: I see. And I believe you did the study on many patients, almost 200 patients, and you really show very interesting findings. Can you summarize them for us?

Berkay Simsek: Yes. In the end, we were able to retrieve data from 198 patients on the ipilimumab plus nivolumab arm. And we found out that density of, as we call them, non-terminal exhausted cytotoxic T-cells, which are CD8 positive, PD-1 positive, but negative for additional immune checkpoints like TIM-3 or LAG-3 is positively correlated with objective response rate and progression-free survival. And this was true both as a continuous variable. And also using the Contal and O'Quigley method, we got an optimized cutoff based on PFS. And the high group for this biomarker, the high density group, they didn't reach the median PFS, and the low group had a median PFS of 9.3 months.

Pedro Barata: Got you. So in other words, the CD8 positive, PD-1 positive TIM-3 negative LAG-3 TILs was associated with improved outcomes on ipi/nivo.

Berkay Simsek: Yes.

Pedro Barata: So how far do you think we are from ... Do you see this as possible to be using clinic, I guess? How do you see the logistical aspect of it? How can we implement something like this in clinical practice? It sounds like we're getting closer of getting the patients right, who are likely to benefit the most from it. I'm just wondering, what do you think about the feasibility of this in the real life?

Berkay Simsek: So our group, as I mentioned previously, have been working on this specific biomarker in previous clinical trial samples in a very similar manner. And we showed in CheckMate 010, 025 and HCRN GU16-260 several times that this biomarker works. But logistically it can be hard because it is very much laboratory dependent, and it is multiplex immunofluorescence staining. And we are, again, just validating this image analysis by our eyes. Even though we have been doing this in very long time, this needs very extensive validation in multiple labs. It shouldn't be only just coming studies from only one lab and only one method. Because even just multiplex immunofluorescence staining, there are various methods. There could be different fluorophores that are used, different antibodies that are used. It is important that many people are working on this, but a biomarker like this, a proposition like this would need really extensive validation.

Pedro Barata: Absolutely. And I do appreciate the thoughtfulness of your comments regarding, it's important that different labs around the world validate the same results. So they are credible and ultimately maybe they can be incorporated in clinical setting. And so I guess that's my last question to you is, where do you go from here? This seems to suggest is a promising biomarker, and how do you see moving forward? What do you envision next steps might be?

Berkay Simsek: So from my perspective or from our laboratory's perspective and with the technical capabilities we have, we see the tumor microenvironment as a whole. It's actually a niche that can be targeted. It is not just the T cells, it is not just the TRX, it is not just the macrophages, but there are many, many cells that are present in the tumor microenvironment. And I think we need a holistic approach for this, and we need to study the tumor-associated macrophages. In fact, another arm of the work that I'm doing is actually studying the PD-1 expression on tumor-associated macrophages.

And I was able to show that they are residing in a spatial niche between the cytotoxic T-cells. And there are previous work that show that actually there are interactions between these TAMs and the TILs that creating this immune microenvironment, this cytokine storm going on actually. And there are the antigen-presenting aspect of it with the TAMs and the B-cells. And what I'm trying to do, what we are trying to do in the lab, is we are trying to identify many of these immune markers on the protein level. But in a very wide aspect, we also have the transcriptomic studies. We also have the markers on the blood circulating that could also predict response to the therapy. And there is also the coming of the digital pathology and the AI aspect and these AI modules that see things that we don't even understand. And there needs to be a way to combine all these to get the most optimized biomarker actually.

Pedro Barata: Absolutely. Well, this sounds super interesting, amazing work, and this is fantastic to be out there. And that's actually proved that even though it's a negative study from that perspective, really good data can come out of this. So I'm looking forward to see what your lab is going to keep going and doing specifically for renal cell carcinoma patients as we need to really take steps forward to exactly identify the patients to benefit the most from immunotherapies that we have available and new immunotherapies coming up in the future. So thank you so much, Dr. Simsek, for joining us today. Super interesting work. Congratulations on the great presentation, and I'm looking forward to reading the paper when it comes out.

Berkay Simsek: Thank you so much for the opportunity.

Pedro Barata: Thank you.