Andrea K. Miyahira: Hi, I'm Andrea Miyahira with the Prostate Cancer Foundation. I'm here at ASCO 2025, joined by Dr. Marina Sharifi, an Assistant Professor at the University of Wisconsin and a 2022 PCF Young Investigator. Thank you for joining us, Dr. Sharifi.

Marina Sharifi: Thanks for having me, Andrea.

Andrea K. Miyahira: So you presented a poster here at ASCO on a study where you did prospective multiomic profiling of mCRPC, looking at next generation sequencing of tissue biopsy, ctDNA, and RNA-seq. So tell us about the rationale for that study.

Marina Sharifi: Yeah, I think we all know that we could do better when it comes to precision oncology approaches for mCRPC. We know there's a subset of patients who will have very stable disease on androgen deprivation therapy and ARPI therapies for many years, and other patients who have much more aggressive disease biology, who need more-- who would benefit from more aggressive interventions and treatment approaches. And in the clinic, we still don't have great tools to tell those groups of patients apart to really understand, in advance, what is the patient's disease biology?

And one of the challenges to understanding not only being able to predict patients who have more aggressive disease, but also understanding how mCRPC tumors evolve under pressure of different treatments and maybe become more aggressive has been that even though we have had some very large and really wonderful resources funded by PCF, among others, in sampling tissue biopsies from patients with mCRPC, with the Stand Up to Cancer West Coast Dream Team, East Coast Dream Team samples, it's still very challenging to obtain tissue biopsies routinely from our patients, and particularly to obtain tissue biopsies over time on treatment.

And so that is what really drew us to the potential of liquid biopsies as a way to molecularly profile mCRPC tumors in a way that would be more scalable for more patients and also would allow us to sample tumor cells over time on treatment, which would really allow us to understand how mCRPC tumors evolve under treatment pressure.

And we have some pretty unique technologies that we had developed at the University of Wisconsin. My mentor from IYI, Dr. Josh Lang, who is himself a PCF-supported investigator, had developed some tools that would allow us to isolate circulating tumor cells from patients with mCRPC with really high purity, which would in turn allow us to do some types of profiling, like RNA sequencing, that have been really challenging in circulating tumor cell samples previously.

And also some novel approaches to cell-free DNA or circulating tumor DNA profiling that allow us to look beyond just DNA mutations and into actually inferring gene expression or tumor phenotypes from the circulating tumor DNA. And so we recently published a study in Cancer Discovery, where we profiled circulating tumor cells by RNA sequencing from a cohort of 117 patients with mCRPC.

And we're able to identify different gene expression phenotypes that were associated with more versus less aggressive disease biology. And in this poster that I'm presenting at ASCO on Monday, we move beyond that to say we've identified these different circulating tumor cell phenotypes that are associated with outcomes. What are the DNA mutations that are associated with those different phenotypes?

Because as you know, there are certain recurrent DNA mutations in mCRPC that have been associated previously with more aggressive disease, like mutations in p53, RB, PTEN. And so the goal of this poster or this study was to layer that in in addition to our circulating tumor cell transcriptional phenotypes, to understand, what is the intersection between genomic markers of poor prognosis or aggressive disease and are the gene expression biomarkers that we found?

Andrea K. Miyahira: Oh, thanks. And what were your major findings?

Marina Sharifi: What we found was very interesting. And that both the transcriptional phenotype and the genomic mutations contributed to prognosis. So what we observed was that among patients who had one of these high risk genotypes, so a mutation in p53, RB, PTEN or AR, having one of the high risk circulating tumor cell phenotypes was actually associated with worse prognosis than not having one. So even among those patients with high risk mutations, the circulating tumor cell phenotype split patients as having better or worse prognosis.

And then we saw the same thing in patients who did not have any of those high risk mutations. Overall, they did better than the patients with the high risk mutations, which is what we expected. But again, the circulating tumor cell phenotype added additional information in distinguishing between patients who had longer versus shorter survival.

Andrea K. Miyahira: OK, thank you. And of these different subtypes that you've identified, how do they compare with previously published mCRPC subtypes?

Marina Sharifi: That's a great question-- I think something that we've been really interested in exploring. And what we're finding in these circulating tumor cell phenotypes is that we certainly detect neuroendocrine prostate cancer. We do detect a phenotype that still has androgen signaling, still appears to be luminal, but does have very aggressive disease biology and does express some neuroendocrine markers.

And so that may be the circulating tumor cell equivalent of the double-- the AR, any positive subtype that's been identified by Pete Nelson and others. I think what's been really interesting for us is that we have not identified the double negative phenotype that's been associated with aggressive disease in some tissue biopsy series.

We do identify a double negative phenotype in our CTCs. But in the circulating tumor cell samples, that phenotype seems to be associated with better prognosis. And one of the things that we speculated is that the double negative phenotype seen in tissue biopsies may have some input from the stromal or microenvironmental components that is distinct from what is present in our circulating tumor cell samples.

Andrea K. Miyahira: OK, thank you. And you mentioned that you saw high risk mutations and tumor suppressor genes in AR. So across your different other subtypes when you subtype them by gene expression, how frequent did you see tumor suppressor mutations in these different subtypes?

Marina Sharifi: That's, again, a great question. And so what we saw was that in our high risk CTC phenotypes, which were our neuroendocrine, and then what we were calling our luminal B phenotype, which is more still androgen-driven and luminal but has a poor prognosis, there was an enrichment of those high risk mutations. But they were still only present in just over half of samples. So there was a significant minority of samples that had that high risk CTC phenotype but did not have a mutation in one of those high risk genes.

Andrea K. Miyahira: Thank you. And a number of your patients went on to receive PLUVICTO. So did you identify any biomarkers in your study that can indicate response versus resistance to PLUVICTO?

Marina Sharifi: Absolutely. So it was a smaller substudy, just 37 out of 117 patients. So our findings are very exploratory. We did find that patients with a high risk circulating tumor cell phenotype, specifically that luminal B phenotype, had a lower rate of clinical benefit, a significantly lower rate of clinical benefit with PLUVICTO and also significantly shorter progression-free and overall survival.

The way this study was designed, we can't say whether it was predictive. We certainly see that it's prognostic in that PLUVICTO cohort, just as it is in the all comers cohort. And interestingly, what we saw in that luminal B subtype that had this poor response to PLUVICTO is that they had a signature-- transcriptional signature that's previously been associated with radiation response, the PORTOS signature. It was significantly different between those luminal B CTC samples and samples that were in our favorable risk CTC group.

And it really suggested that potentially one of the reasons that luminal B group did not benefit from PLUVICTO may be because of payload resistance. And we do, as I mentioned, we find that the high risk genomic mutations are also enriched in those luminal B samples. And so that may also be contributing.

Andrea K. Miyahira: OK, thanks. And have you yet integrated ctDNA assays from these patients into the study? And are you yet able to compare ctDNA with CTCs? And how are we going to go forward with liquid biopsies as biomarkers for patients?

Marina Sharifi: Absolutely. So I think that's one of the really, really important next steps that we're currently working on. We have sequenced ctDNA from all of these samples that's matched to the circulating tumor cell phenotyping or transcriptional gene expression phenotyping. And we're in the process of integrating those with several major goals. One is to explore more deeply the genomic underpinnings of our gene expression phenotypes, particularly those associated with poor prognosis to see if we can identify any novel genomic mutations that might be associated with those high risk gene expression phenotypes.

And then the other avenue that I'm really excited about that George Zhao and I just received a DOD award to support is to integrate some of the gene expression prediction that we can do with circulating tumor DNA sequencing to see if we can actually predict the circulating tumor cell gene expression phenotypes from circulating tumor DNA. That would be a way to really develop a clinical biomarker from these circulating tumor cell phenotypes if we would be able to develop a predictor in ctDNA that we could use to then classify patients by these different circulating tumor cell phenotypes.

Andrea K. Miyahira: Thanks. And do you have any other next steps or final messages that you want to share with our viewers?

Marina Sharifi: The study was certainly very intriguing in terms of identifying potentially some gene expression profiles in CTCs that are associated with prognosis. But the next step is really to validate, what is the relationship between these CTC phenotypes and treatment response across different therapies?

And so the CTC RNA sequencing assay that we developed is now integrated into multiple different prospective trials of different-- so trial of ARPI therapy, the ARCTIC trial that Josh Lang is the PI of, and actually a number of other trials of novel therapies in mCRPC. And we also are expanding our cohort of PLUVICTO-treated patients. We're nearing 100 patients now, and our goal there is, again, to look at these CTC phenotypes as predictive biomarkers in these larger groups of patients, which will help us move what we've already identified as potential predictive or prognostic biomarkers closer to the clinic.

Andrea K. Miyahira: Well, thank you so much, Dr. Sharifi, for sharing this study with us today.

Marina Sharifi: Thank you so much. And thank you for the support of PCF, which without that support, this study wouldn't have been possible. And I think it has really led to some really exciting findings that I really hope will help us improve treatment for patients who are living with mCRPC.