New Technique Predicts Prostate Cancer Relapse
(HealthDay News) – Copy number variation (CNV) in both malignant and benign prostate tissue is predictive of prostate cancer relapse.
Yan P. Yu, MD, of the University of Pittsburgh School of Medicine, and colleagues assessed whether CNV of the genomes of prostate cancer tumors, adjacent tissues, or blood samples can predict biochemical (prostate specific antigen [PSA]) relapse and the kinetics of the relapse. One hundred four prostate tumor samples, 49 samples of benign prostate tissue adjacent to a tumor, and 85 blood samples from patients with prostate cancer were analyzed.
Using gene-specific CNV from prostate cancer tumors, the researchers correctly predicted 73% of relapses and 75% of cases with a short PSA doubling time (PSADT) of less than four months. Using median-sized CNV from tumors, the genome model correctly predicted 75 and 80% of cases for relapse and cases for short PSADT, respectively. In adjacent tissue samples, the gene-specific CNV models correctly identified 67% of relapses and 77% of cases with short PSADT. Using blood samples, the gene-specific CNV model correctly predicted 81% of relapses and 69% of short PSADT cases.
"CNV analysis on the genome of blood, normal prostate, or tumor tissues of the patients with prostate cancer holds promise to become a more efficient and accurate way to predict the behavior of prostate cancer," the authors write.