Dr D’Amico on Genomic Classifiers in Prostate Cancer

Anthony V. D'Amico, MD, PhD, professor of radiation oncology, Harvard Medical School, chief, Genitourinary Radiation Oncology, Dana-Farber Cancer Institute, provides insights into current prospective studies employing the Decipher Genomic Classifier in prostate cancer.

D'Amico explains that ongoing studies are aiming to stratify treatment based on genetic risk profiles determined by the Decipher test—a tissue-based genomic test designed to provide information to guide treatment decision-making in patients with localized prostate cancer.

Decipher evaluates a range of genes associated with the progression of prostate cancer and insensitivity to androgen blockers. A high Decipher score is associated with a greater presence of markers associated with a higher risk of developing distant metastatic disease within 5 years, despite receiving standard-of-care treatments.

A prospective phase 3 trial (NCT05050084) is assessing treatment strategies tailored according to Decipher risk scores. In this trial, patients undergo Decipher testing based on their biopsy or post-radical prostatectomy samples. Those identified with a low-risk Decipher score are randomly assigned to receive either standard-of-care treatment or a de-intensified regimen, such as reduced duration of hormonal therapy in conjunction with radiation therapy.

Conversely, patients with high-risk Decipher scores are randomly assigned treatment intensification arms consisting of standard-of-care radiation and 2 years of hormonal therapy or an enhanced regimen that includes standard hormonal therapy supplemented by next-generation androgen receptor inhibitors such as apalutamide (Erleada) or abiraterone acetate (Zytiga).

This type of study couple help determine the value of integrating genomic tools like the Decipher test into clinical decision-making, which could allow for the optimization of therapy based on individual genetic risk profiles, D'Amico says. This approach facilitates a more personalized treatment paradigm in prostate cancer, potentially improving outcomes by adjusting therapy intensity according to the genetic predisposition for disease progression and treatment resistance.