Dr. Felix Feng is a physician-scientist at University of California, San Francisco (UCSF) keenly interested in improving outcomes for patients with prostate cancer.
His research centers on discovering prognostic/predictive biomarkers in prostate cancer and developing rational approaches to targeted treatment for therapy-resistant prostate cancer. He also sees patients through his prostate cancer clinic at UCSF.
Prostatepedia spoke with him about how genomics is personalizing medicine for patients.
How is genomics changing how doctors decide who needs treatment for prostate cancer and who doesn’t?
Dr. Felix Feng: Our field is in an exciting time in terms of advances in genomics and prostate cancer. For the vast majority of the past few decades, prostate cancer treatment has been selected and optimized outside of genomics. We’ve had a number of breakthroughs in the last few years that have suggested that a large part of prostate cancer treatment in the future may rely on genomics.
The most important example of this is the use of PARP inhibitors in men with prostate cancer that have DNA repair alterations, and most commonly, alterations in the genes BRCA1, BRCA2, and ATM. Including this example, we have three examples in the context of metastatic prostate cancer where genomics is actively being used to personalize therapy.
A study from Dr. Johann de Bono’s group at the Royal Marsden in the United Kingdom first demonstrated that patients who have DNA repair alterations have responded particularly well to the PARP inhibitor Lynparza (olaparib). In a follow-up study, which was run out of the University of Michigan, Drs. Maha Hussain, Arul Chinnaiyan, and I confirmed these findings in the context of a randomized trial. It’s clear that using PARP inhibitors for patients with DNA repair alterations is one example of using genomics for personalized medicine. There are a number of different companies now exploring a variety of trials trying to get PARP inhibitors FDA approved as a therapy for patients with metastatic castration-resistant prostate cancers.
A study reported by Dr. Johann de Bono at the European Society for Medical Oncology Conference about two years ago demonstrated that patients with prostate cancers in which a gene called PTEN is inactivated responded well in a randomized trial to an AKT inhibitor. That is now being evaluated in a Phase III trial.
Another use of genomics to advance medicine is in cancers with alternations in a class of genes called mismatch repair genes, which have been shown to confer sensitivity to various immunotherapies. That represents an approved syndication across all cancers, not just prostate cancer.
In the localized prostate cancer setting, there are two genomic classifiers based on RNA expression that help identify patients with low-risk prostate cancer who are more likely to progress to more aggressive disease. This may be used to determine which patients should be followed with active surveillance. The two classifiers that are most commonly utilized in this setting are Oncotype DX by Genomic Health and Prolaris by Myriad.
In the context of higher risk patients treated with surgery, there’s a classifier called Decipher made by GenomeDX Biosciences. That has been shown across very large numbers of patients to be a prognostic of metastatic progression after radical prostatectomy. Already, that classifier has been incorporated into ongoing clinical trials to select which patients with aggressive disease should be candidates for treatment intensification.
Can genomic classifiers be used to select specific patients for specific therapies?
Dr. Feng: My team has helped develop two of the first clinical grade classifiers predictive of their responses to specific therapies. One is a biomarker panel called PORTOS, which stands for Post- Operative Radiation Therapy Outcomes Score, and may be useful in predicting response to post-operative radiation therapy—those treated with radiation therapy after radical prostatectomy. PORTOS predicts specifically which men will benefit from radiation therapy. We validated its performance in a manuscript published in Lancet Oncology two years ago.
More recently, we’ve applied a genomic classifier utilized in breast cancer to prostate cancer. It’s called PAM50 and is used to determine which women with breast cancer should get hormone therapy after surgery. It turns out that these molecular subtypes of breast cancer also exist in prostate cancer. Specifically, we found that there are luminal A, luminal B, and basal subtypes of prostate cancer.
When we look at which patients are most likely to hormone therapy, our initial data suggests that it’s the luminal B patients who have the most aggressive disease and who also benefit from hormone therapy. We did all of these studies in large retrospective cohorts, but because we wanted to validate this prospectively, we are about to initiate a trial in the context of a national clinical trial called NRGGU006, run by the NRG Oncology Clinical Trials Group.
With NRG-GU006, we stratify patients by their PAM50 molecular subtype. These are patients who have been treated with radical prostatectomy and have had biochemical PSA recurrence.
These patients are stratified by PAM50 status, and then they are randomized to standard therapy—which is salvage radiation alone—or salvage radiation plus short-course Erleada (apalutamide), which is a next generation anti-androgen.
From all of these examples, you can see that, across different contexts— from active surveillance to the more aggressive, locally advanced prostate cancer to metastatic prostate cancer, there are now a number of strategies that use genomics to personalize medicine.
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