DNA Test For Prostate Cancer Relapse Prediction: Study
Researchers have found the solution for predicting clinical outcomes of prostate cancer post diagnosis in the GENES. The research team from the University of Pittsburgh School of Medicine have discovered that copy number variations or CNV (genetic abnormality) in
- prostate tumor cells
- benign tissues adjacent to tumor
- blood of patients with prostate cancer
may help in predicting relapse of the cancer as well as the nature of relapse (whether aggressive or indolent), in patients.
What are Copy Number Variations?
Copy Number Variations (CNV) refers to structural variation in the DNA of a genome. The change causes the cell to have abnormal number of copies of one or more section of the DNA. Usually, CNV are large regions of genome that are either deleted or duplicated. CNVs can be inherited or caused due to de-novo mutation. CNVs can occur in both cancer and non-cancer tissues.
The researchers found that copy number variations were high in prostate cancer patients. The size of CNV was greater in those patients who had a rapid relapse. This information was used to build models of CNV that could help in predicting prostate cancer prognosis in different types of tissue samples.
Study in brief:
In the comprehensive genome analysis conducted by the researchers, they analyzed:
- 238 samples from men undergoing radical prostectomy
- 104 prostate tumor samples
- 85 blood samples from patients with prostate cancer
- 49 samples of benign prostate tissues adjacent to tumor
- 3 commercially available prostate cancer cell lines for validation of results
One third of these samples were taken from patients who were exhibiting rapid increase in PSA levels (values doubling in <4months) indicating recurrence, a third from patients with recurrence and slow rising PSA levels (doubling time >15 months) and another third with no relapse for 5 years after surgery. These samples were analyzed for genetic differences to the different outcome the men had experienced.
The researchers found the predictions of the CNV model to be correct.
- Gene specific CNV model – 73% of relapse cases and 75% of short PSA doubling cases
- CNV model from adjacent tissues – 67% for relapse and 77% for short PSA doubling time
- CNV from blood – 81% of relapse cases and 69% for short PSA doubling time
The study is exiting since it opens up new avenues to predict prognosis of prostate cancer patients which could be instrumental in aiding treatment decisions.
The study titled, Genome Abnormalities Precede Prostate Cancer and Predict Clinical Relapse, and authored by Yan P. Yu, Chi Song, George Tseng, Bao Guo Ren, William Laframboise, George Michalopoulos, Joel Nelson and Jian-Hua Luo, has been published in The American Journal of Pathology.