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ROCHESTER, Minn. — In a new study published in Molecular Cancer Research, Mayo Clinic researchers identified critical genomic changes in response to abiraterone acetate/prednisone, a standard treatment option for men with progressive, incurable and castration-resistant prostate cancer.
"We defined a potential strategy for both responders and nonresponders of the drug that may help men overcome resistance and prolong survival," says Liewei Wang, M.D., Ph.D., the Bernard and Edith Waterman Director, Pharmacogenomics Program, Mayo Clinic's Center for Individualized Medicine. Dr. Wang is the corresponding author of the study.
Dr. Wang explains that while several drug choices are available to control disease progression, many questions remain over which drugs to use in individual cases. Also, predictive biomarkers for drug resistance and sensitivity remain primarily unknown.
Abiraterone acetate is a standard treatment option for men with castration-resistant prostate cancer. However, the response rate is limited, no known biomarkers predict prognosis, and alternative therapies for those who failed treatment are unavailable.
In the Prostate Cancer Medically Optimized Genome Enhanced Therapy study, also known as PROMOTE, Mayo researchers revealed DNA sequences associated with response to abiraterone acetate to identify additional treatment options for men with advanced prostate cancer resistant to all standard therapies. They identified an 11-gene drug panel that provided a new tool to individualize treatment for abiraterone acetate. A genetic testing panel is a laboratory test that looks at a select group of genes. The 11-gene panel predicted a worse prognosis for a subset of primary or metastatic patients enrolled in the study.
In the next step of their analysis in this prospective study, the researchers analyzed whole-exome sequencing and RNA sequence data from 83 patients with metastatic biopsies before and after 12 weeks of abiraterone acetate/prednisone treatment. They identified genomic alterations associated with acquired resistance after 12 weeks of this treatment.
"We analyzed the posttreatment genomic landscape of metastatic biopsies in these patients with metastatic castration-resistant prostate cancer to identify mechanisms of acquired resistance," says Hugues Sicotte, Ph.D., a Mayo Clinic bioinformatician and lead author of the study. "These results may assist with selecting alternative therapies in a subset of abiraterone acetate-resistant patients with the highest risk of having the poorest outcome."
Dr. Sicotte says biomarkers based on the stage-specific landscape of genomic changes in prostate cancer are under investigation.
"Further studies will be needed to test these drug treatments to overcome abiraterone acetate/prednisone resistance and define subgroups of nonresponders," says Dr. Sicotte. "Our goal is to incorporate these into clinical practice for physicians and patients with castration-resistant prostate cancer."
Prostate cancer is the most commonly diagnosed solid organ malignancy in the U.S., with more than 268,490 new diagnoses annually and an estimated 34,500 deaths. It is the second leading cause of cancer deaths among men, according to the National Cancer Institute's Surveillance Epidemiology and End Results Program.
This work was supported by Mayo Clinic's Center for Individualized Medicine (MC1351 to MK and LW); Minnesota Partnership for Biotechnology and Medical Genomics (MNP No.14.37 to MK and SMD); Department of Defense (W81XWH-15-1-0634to SMD and MK); National Institutes of Health-National Cancer Institute, R01 CA174777 to SMD; AT Suharya and Ghan DH.; Joseph and Gail Gassner; and Mayo Clinic Schulze Center for Novel Therapeutics in Cancer Research (MK and LW). Other contributing groups include the Mayo Clinic Comprehensive Cancer Center (no grant numbers apply), the Pharmacogenomics Research Network (no grant numbers apply), and Janssen Research & Development LLC (no grant numbers apply), which provided partial drug support on the study from April 2014 onward for study patient numbers 45–92 and funding support for collaborative bioinformatics analysis.
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