The Future of Prostate Cancer Risk Stratification and Treatment Planning - Eric Kim

May 10, 2024

Preston Sprenkle and Eric Kim discuss the future of prostate cancer diagnostics, emphasizing the role of genomic classifiers like PAM50 and MRI in refining patient treatment plans. Dr. Kim suggests that prostate cancer care may soon parallel advances in breast cancer, utilizing gene pathway analyses to guide treatment decisions more accurately. They explore how integrating complex biomarkers into clinical practice might offer more tailored patient care, though challenges remain in managing and interpreting this data effectively. The conversation highlights the need for streamlined diagnostic processes and raises questions about the cost-effectiveness and practical implementation of increasingly detailed genomic data in everyday clinical settings.

Biographies:

Eric Kim, MD, Urologist, The University of Nevada, Reno School of Medicine, Reno, NV

Preston Sprenkle, MD, Associate Professor of Urology, Director of the Urologic Oncology Fellowship and Research, Yale School of Medicine, New Haven, CT

Read the Full Video Transcript

Preston Sprenkle: Good morning. I'm Preston Sprenkle. I'm a urologic oncologist at Yale University. We're here at the AUA. I'm speaking with Dr. Eric Kim, a urologic oncologist just recently from Wash U and soon to be at the University of Nevada at Reno.

Eric Kim: Thanks for having us and happy to discuss our project.

Preston Sprenkle: Great. Can you just tell us a little bit more about the importance of the PAM50 and some of those little categories that you pulled out?

Eric Kim: Yeah. So, PAM50, as you know, is a breast cancer gene classifier, a gene pathway analysis that's been applied to prostate successfully. I think we in prostate can take a lot of clues from breast cancer. It feels like they're 100 years ahead of us, even though maybe it's only five, but it feels like they're way ahead of us. So I think that, again, in my mind or in my view, is going to be the future of prostate as well, that these subtypes end up being another category that you're adding in when you're making your decisions for the patient.

Like a luminal B patient with a Gleason score of 3+4, may be a totally different patient than a Basal 4+3. And so we were hoping that again, MRI was maybe not capturing Gleason or capturing Decipher GC, but that MRI is somehow capturing something about the tumor biology, whether that's the microenvironment or tumor behavior or stromal reaction to the tumor. So again, we thought subtypes was the most digestible way to summarize that. But no, I think we're going to keep working on diving through all of the Decipher grid, 46,000 gene expressions, to see if we can pull out more consistent or clearer signals. And as you know, unfortunately humans, it's tough for us to digest something that's more than, I don't know, three bytes of information. So we really have to, I think, break it down into something that's a clear take-home, if it's going to be clinically actionable.

Preston Sprenkle: Right, unless we have these super large multivariable models, which just take into account everything. But then you have to get all of that information on everyone and when a piece is missing, I think that's going to be our ongoing challenge is as we continue to do more tests, we are getting better information, as we talked about earlier. We're getting better information with everything additional, refining our risk more.

Eric Kim: For sure. But it's incremental, like you're getting at. It's a logarithmic curve. At some point, you can spend an extra $20,000 restratifying a patient, but maybe you're only getting an extra 1, 2% of accuracy. And how do you justify that cost for the most common cancer in men? How do you justify that cost in America?

Preston Sprenkle: Well, it seems like we're still in the exploration phase, right? We're still identifying what all of these variables are. I mean, we get that still with the markers for elevated PSA, all the biomarkers that are out there.

Eric Kim: For sure.

Preston Sprenkle: We don't know how to sequence them. They all seem relatively the same. Don't tell anyone I said that, but—

Eric Kim: Very close, but yeah.

Preston Sprenkle: ... we can use them sort of interchangeably to a certain extent. At some point, and we're not at that point yet, but we're going to have to try to consolidate and make a real effort to pick one.

Eric Kim: Yeah, ideally in terms of what's commercially available today, and I think this is what you're getting at, it would be great if there was, I don't want to say a cookbook because everyone should be allowed to practice medicine how they want to, but it'd be nice to pull out some bumpers, just give a little bit more guidance for people and patients who don't deal with this every day. You and I have how many patients with elevated PSA per clinic, how many prostate cancer patients per clinic? The general urologist may see one or two of those a day or three or four a week.

Preston Sprenkle: Who do you think is responsible for that?

Eric Kim: It's probably us now. I mean, I was going to blame Dr. Andrew, but it's my dear mentor. But no, I think it's probably on us to start figuring that out. But yeah, it'd be great to know a sequence of, yeah, start with this blood biomarker, if this then substratify with the urine test. If higher, get an MRI, whatever, and then that tells you who actually needs the biopsy. Get the genomic information on certain categories of risk that you already have, based on what you've already accumulated, to try to reduce again, the patients that you're not going to get too much more information on.

Preston Sprenkle: There are some published studies of things like that from different centers. I guess the question now is, what is the next step? Is the next step combining all of those and meta-analysis, is that enough or do we really need to do a better job? I mean, I know the Aqua database is combining a lot of this, but do we need to do a better job and be looking at really large national data sets that can pool and analyze all this information?

Eric Kim: The problem just ends up being the endpoint, right? If you pick prostate cancer mortality, good luck. I mean, that's going to be our entire career designing one trial that combines all the commercially available markers today to try to see 10 years from now, what the right sequencing is. And 10 years from now, there's going to be some other test or a hundred other tests. So that's the unfortunate thing.

And the other part that I struggle with as we've started to use biomarkers more, is there's a large number of patients that you're not getting biopsy on, based on the MRI, kind of like you're saying with Emberton, if the 4K for us is low enough, the clinical risk is low enough, no strong family history, Caucasian male in their '60s, PSA of 6, 4K is like 11, and you get the MRI and the MRI is negative, then we say, "Look, you probably don't need the biopsy." But then in terms of a study, how do you capture that data and reliably say, "Well, that patient was appropriately not biopsied," so you have to potentially biopsy everybody for the study's sake. But our clinical practice has already moved past that.

Preston Sprenkle: Well, I think that was one of the great pieces of the Precision Study is that they did ultimately follow those patients, or at least that was the discussion of following them. And then we have to follow those men closely, record what we do and see who ends up going on to needing a biopsy. At least, I'm sorry, it wasn't in the study, but that's where there was the rationale.

Eric Kim: The European study, MRIAS, for active surveillance, they had a three-year per protocol biopsy. Again, just to show, hey, that's probably the proportion of patients that we could have missed by just using PSA and MRI alone. But I think, and maybe I'm underestimating the grit of American men, but I think if the tide turns and we start avoiding biopsy rather appropriately with clinical judgment and good data to support it, I think it's going to be hard-pressed to tell these guys that they're going to need a biopsy for study purposes. I think it's going to be hard to enroll men to get a per protocol biopsy.

Preston Sprenkle: It will be, I think, but we actually, we were just discussing this yesterday. I mean, how long do we track those men that you don't biopsy then? They have to be still part of your study cohort to figure out what happens to them in the future. And probably, quite honestly, a lot of the men coming in, they don't know the data like we do. So they don't know that they don't need a biopsy for three years. They just know that they're scared and they have an elevated PSA. You will have some dropout, but I think you probably would still have pretty reasonable enrollments.

Eric Kim: Yeah, it's tough because, yeah, I guess you need to follow them for 10 to 15 years, and most funding windows are maybe three to five years. So how do you design a three-year or a five-year endpoint in prostate cancer, early detection? That's a real quagmire and something that's going to, I think, be tough for our field to figure out.

Preston Sprenkle: Eric, it's great talking with you. Thanks so much for your time this year at the AUA in San Antonio.

Eric Kim: Yeah, awesome. Thanks for having me, man.