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Medicine Matters oncology

At ASCO GU this year, I presented a study looking at molecular determinants of response to apalutamide, which is a next generation antiandrogen agent using molecular profiling of samples from the phase 3 SPARTAN trial. And the main findings were that signatures associated with immune cell activation were enriched in patients who had long-term response to apalutamide compared to patients who had early progression of their disease on the same treatment. And the implications of this are several fold.



First of all, you know, I think there's a critical need to identify subsets of patients who may respond better to certain therapies than others. And our study provides that the immune cell biology might be playing a role in response to hormone therapy. From a biomarker perspective, it may help us stratify patients or select patients better for treatment in the future.



The other main finding that's actually quite of interest, at least to me personally, is that these samples that were profiled were the diagnostic samples from the patients, meaning the samples they got before they got any major treatments. And so there was a seven-year gap between the diagnostic sample and when patients were enrolled on the SPARTAN study. What I think is a particularly important take home message is that samples that are seven-years-old can still predict what happens, in terms of patient response, down the road to therapy and more advanced disease states.



And so I think that has broad implications across all of prostate cancer management in the sense that one of the things that plagues the prostate cancer field is the difficulty in obtaining tissue in patients, let's say with nonmetastatic castrate resistant prostate cancer, because there's nothing to biopsy at that point, or even metastatic castrate resistant prostate cancer, because biopsies of metastases are not routinely done at many hospitals. And so what this suggests is that we can go back to very old samples, and that the biology of the disease, at least parts of it, still hold up over time. And so I think that's important to clinicians.



So the platform we used is a high density gene expression array that's actually offered by the company decipher. In terms of the potential to translate this, since the platform is clinical grade and insurance reimbursed, that aspect is definitely present, but in terms of our clinicians going to be ready to start selecting patients for treatments based on immune cell activation, I don't think clinicians will be ready for that quite yet. And I want to point out that on this particular analysis, all patients benefited from the addition of apalutamide, the standard androgen deprivation therapy.



It's just that patients with certain molecular subtypes benefited more, but it's not as if no patient-- you know, it's not as if we identified a patient population that doesn't derive any benefit. And so I think that these studies need to be validated on a larger cohorts, but when that validation does happen, I do believe, at least from the ease of having that platform available to clinicians, you know, that that will be a significant advantage in terms of how quickly this can influence care in the future.



What I would like to see personally is whether these findings of immune cell activation affecting response to next generation antiandrogen therapies, whether these findings hold true in other trials and other patient populations as well. And so, you know, right now, we are involved in a number of studies profiling tumors to look for determinants of response to next generation androgen directed therapies in the context of metastatic prostate cancer, both hormone sensitive and castrate resistant. So that's going to be a next step for us.



Another step that we haven't embarked upon, but certainly that I would be interested in doing, is looking at response to other next generation antiandrogens in the same setting of nonmetastatic castrate resistance. So, we can study whether what we found is more specific to apalutamide or is generalizable, kind of, across the multitude of hormonal therapy agents. And then, specifically, you know, it's always better to look at larger cohorts and gain kind of increased confidence in your findings. But our study was a hypothesis generating study, and in general, when you look at a biomarker, you always want to be able to validate it in an independent cohort, and we have not done that yet.