Despite recent advances in understanding prostate cancer heterogeneity, better methods for classification of prostate cancer are still needed. Researchers at Cedars-Sinai have developed a new method to identify which patients with prostate cancer will develop aggressive types of disease even if their tumors at first appear to be lower risk. The findings, published in Cancer Research, could help enhance the management of prostate cancer and provide more effective, individualized treatment based on the genes that are activated in the individual tumor.
“These findings raise the possibility that by determining the gene expression profile of a patient’s tumor, physicians may be able to identify aggressive disease at the outset of diagnosis and start treatment earlier,” said Sungyong You, PhD, lead study author, in press statement.
Researchers analyzed the genetic profiles of 1321 human cancer samples to create a classification system consisting of three distinct subtypes: PCS1, PCS2, and PCS3. When the investigators matched this data with clinical outcomes of more than 4600 patient specimens in medical databases, they found that each subtype was associated with different levels of disease progression. Patients who were included in the PCS1 subtype were more likely to develop an aggressive form of the disease, with greater likelihood of spreading and progressing to poor clinical outcomes. The PCS2 and PSC3 subtypes progressed more slowly. Furthermore, the new subtyping can be performed on tumor cells circulating in the blood.
The study’s conclusions address a major clinical challenge that clinician’s face in determining which patients will develop aggressive forms of the disease and require more aggressive treatment. “About 60 percent of prostate cancer patients we treat won’t progress to aggressive cancer. The problem was that we didn’t have a way of knowing which patients fall into that 60 percent,” said Michael Freeman, PhD, the study’s principal investigator. “We hope our findings help physicians provide more patients with optimal treatments, resulting in healthier outcomes.”
