Kent, it was a pleasure to have you here hear your thoughts on biomarkers, specifically when it comes to muscle-invasive bladder cancer and in bladder preservation in the trimodal field. I'd love to hear your summary of what you discussed and where you think the field is headed.
Kent Mouw: Great. Thanks so much, Dr. Kamat. It's a pleasure to be here and to share some of my thoughts on the biomarker session at the IBCG.
And so just to set the stage, so the annual retreat took place last month in Houston. I was happy to be a part of it. This brings together real stakeholders, clinicians, researchers, industry representatives, and importantly patients and their caregivers to really put our heads together and try to make some advances and provide some guidance in the field. Each year we talk about a couple of topics. This year we had a very timely, interesting topics for discussion. The session one focused on biomarkers, and session two on toxicity of local therapies.
As you mentioned, I was most involved in the biomarkers session, and so today I wanted to give a couple of thoughts on muscle-invasive, or MIBC, bladder biomarkers. We had specific sessions in teams that were formed around guidance regarding the selection of new adjuvant therapies around bladder preservation, adjuvant therapy, and then germline and somatic genetics. Given the limited time, I'm going to really focus my discussion today on bladder preservation. I'm a radiation oncologist, and so that's a topic near and dear to my heart.
And so I think as many people in bladder cancer field are aware, there has never been a successfully completed randomized trial that's compared cystectomy-based treatment to trimodality therapy, which consists of transurethral resection followed by chemo radiation. A result of the lack of clinical randomized data in this space is that there's also a dearth of comparative biomarker data, and so I think everyone in the field is motivated to identify predictive biomarkers that could help us select the right treatment for the right patient. One of the challenges is that most of the biomarker work that's been done has either been done in cohorts of patients who receive cystectomy or separately in cohorts of patients who've received trimodality therapy. And so I think that there's lots of work to do in this space, again, with biomarkers typically limited to one or the other type of treatment cohort.
Touch briefly on different types of biomarkers, so lots of things in our armamentarium to really try to understand and dissect tumor biology and make predictions. I'll talk a little bit about RNA-based or gene expression signatures that are correlated with outcomes; DNA-based, so gene mutation or copy number alterations and outcomes. I'm not going to really touch on protein-based biomarkers, but these are things like histochemical or immunofluorescence-based markers. And then I think a really interesting and exciting new area are around circulating biomarkers, specifically circulating tumor DNA, which I'll touch on briefly.
And so there's been a long history of using trimodality therapy as a curative intent treatment strategy for MIBC. From the large cohorts of patients who've been treated with TMT, there have been a number of biomarker studies that have been performed. I wanted to touch on a couple of them here.
First, starting with the RNA-based biomarkers, so the UK has conducted a series of randomized trials in the bladder preservation space using radiation-based treatment. The one I wanted to highlight here was this randomized trial that compared radiation alone to radiation plus hypoxia-targeting therapy with CON. CON is the combination of IV nicotinamide plus inhaled carbogen, which is a higher oxygen percentage than normal ambient air. The purpose of these treatments is to provide additional oxygen to the tumor and increased radiation sensitivity. It was a positive trial for survival. Some of the interesting biomarker work that's emanated from that completed trial has demonstrated that the addition of that hypoxia-targeting therapy really only benefits those patients whose tumors have gene expression consistent with hypoxia. And so that's what's shown in Panel A here. You can see that the addition of the hypoxia targeting therapies improves survival in patients with high hypoxia tumors, whereas there's really no benefit in the patients with low hypoxia tumors.
I think this is an interesting and important type of biomarker study that can be performed in the context of a randomized trial and really give us some insights into predictive qualities of these biomarkers.
In the US we've done also a series of RNA-based biomarker studies from cooperative group and single institution cohorts of patients treated with TMT in the US. These are some of the work that I've been involved with demonstrating that gene expression signatures of immune inflammation are associated with better outcomes in patients treated with TMT. And so you can see that with a couple of different validated signatures. One signature of T-cell inflammation on the left bottom, and interferon gamma, which is a pro-inflammatory anti-tumor signaling network on the lower right. In both cases, patients whose tumors express high activity of those gene expression signatures have better outcomes than patients with lower expression.
Moving then briefly to DNA-based biomarkers, so these are tumors that have been removed. They've undergone generally next-generation sequencing to look for specific cancer gene alterations. We did a study a couple of years ago demonstrating that mutations in DNA damage and repair, or DDR genes, are associated with improved survival after trimodality therapy. That's shown in the upper in the Kaplan-Meier curves in the upper right. This is a similar demonstration as had been previously observed in patients receiving neoadjuvant chemotherapy followed by cystectomy. And so it was reassuring and nice to see the same association holding up in patients who received combination chemotherapy and radiation in a bladder preserving approach.
And then at the bottom is some of our prelim work in circulating tumor DNA biomarkers. And so I think people in the field are aware that circulating tumor DNA dynamics have been associated with outcomes in patients with metastatic disease, in muscle-invasive patients receiving cystectomy based treatment. This was really a first look at the behavior of this type of biomarker in patients receiving trimodality therapy. What we can see here is a really strong correlation between ctDNA detectability and bladder intact event-free survival outcomes following TMT. Here, patients with no detectable ctDNA generally did very well after bladder preserving TMT, whereas those with persistently detectable ctDNA in the post TMT setting did unfortunately much more poorly. This type of association is also what was seen in the cystectomy space, but it's reassuring and interesting to see that similar dynamics really apply in the TMT space.
And so briefly the take home messages here I think is that overall it's a really exciting time for trimodality therapy and other bladder sparing treatment approaches for MIBC. We have multiple platforms and types of biomarkers that have been correlated with outcomes in TMT, but none of them importantly have been prospectively validated and none yet are currently used in clinical practice. And so lots of work to do.
I think one thing that's going to get us to where we want to be is that many of the trials that are being performed now are banking biospecimens for planned biomarker studies. I think collecting and analyzing these samples from large, often randomized, clinical trials has the potential to really identify prognostic and even arguably more importantly predictive biomarkers that, again, if validated could help ultimately inform the therapy selection for our patients with MIBC.
With that, I'd like to finish up, thank the other members of the MIBC biomarkers guidelines statements team from IBCG 2025. You see the team leads at the top and then team members across the different therapy settings that I had mentioned earlier. And so thanks for the opportunity to present today, and happy to chat further.
Ashish Kamat: Thanks so much, Kent. I mean, again, you're always such an integral part of the work that we do at the IBCG, so I want to thank you for taking the time and presenting this to us as well.
As you alluded, this is a work in progress. Biomarkers essentially allows us as a community to provide personalized recommendations to patients, right? One of the things that I want to put you a little bit on the spot for is are there biomarkers that help you, and this may not be bladder specific, decide which patient will have less toxicity from radiation therapy? And if so, how does that fit in with the stated goals that we had, of course, at the retreat of biomarkers to predict response? Some thoughts there?
Kent Mouw: Yeah, no, thanks. That's such an important topic.
We think a lot about radiation toxicity and trying to select patients appropriately with the opportunity to maximize disease control but minimize toxicity. I think the short answer is that right now, that discussion and those decisions are based strictly on clinical factors. We were looking for folks with good baseline bladder function without known risk factors like bleeding disorders, previous radiation.
There's been a ton of work not just in the bladder cancer space or even just in the GU space, but in the radiation oncology space more generally regarding things like germline genetic predictors of radiation toxicity. There certainly are, I would say, very uncommon genetic predispositions that patients can carry that can increase the risk of toxicity.
But by and large, unfortunately, we're not yet at the place where we're routinely using germline genetics to guide our risk stratification and therapy selection in the MIBC space. But I agree that from a patient-centric lens, which is what we all ought to be focused on, minimizing toxicity is a really important part of our therapy decision making. I hope in the years to come, we have better ways to predict and to guide patients in that way.
Ashish Kamat: Yeah, just like medicine, medicine, 1.0, 2.0, and we hope we'll get to 3.0, which is more preventative, I think biomarkers are also going through this evolution. We now have the tools to actually dig really deep down into biomarkers, which we've had for some time.
But we now also have computing tools, right? We have the ability, for example, with the AI platform, machine learning platform to take tons of data, aggregate it together, and then spit out relatively personalized recommendations. We hope. Again, it's not been validated. I don't want to assume that, or have those listening assume it's been validated. But what are your thoughts on using platforms such as machine learning, AI-based algorithms to take all the knowledge that we have to date, everything that's coming out, and then trying to get us down not just at a population level, but an individual patient level predictor or prognosticator of outcomes?
Kent Mouw: Yeah, that's exciting to think about, right? That's the goal. That's where we all want to go.
Involved in some of these efforts, I think it's hard to bet against that. I mean, the timeframe over which that happens and how we validate that, I mean, we're going to have to be really careful to do it in a thoughtful way to get where we want to go in most efficient and safest way. But I think it's hard to envision a future three, five, 10 years from now that doesn't incorporate components of exactly what you're describing at probably every level of care at diagnosis, therapy selection, disease monitoring, and then post-treatment surveillance.
Ashish Kamat: Right. Kent, as always, it's a pleasure. Thank you for taking the time. Look forward to seeing you soon.
Kent Mouw: Great, thanks so much. Pleasure to be here today.