Distinguishing Aggressive From Less-Threatening Types of Prostate Cancer
Posted: Thursday, April 30, 2020
Common approaches used for analyzing genomic platform data, such as hierarchical cluster analysis, fail to capture the heterogeneous composition of individual cancer samples. However, recent research findings, published in the British Journal of Cancer, suggested that using more complex analytic approaches may provide actionable information for clinical management of prostate cancers that require treatment. The more sophisticated analysis and stratification framework may also assist drug targeting for the disease.
“[Prostate cancer] usually develops slowly, and the majority of cancers will not require treatment in a man’s lifetime. However, doctors struggle to predict which tumors will become aggressive, making it hard to decide on treatment for many men,” Colin S. Cooper, PhD, of the University of East Anglia, Norwich, United Kingdom, stated in an institutional press release. “This means that many thousands of men are treated unnecessarily, increasing the risk of damaging side effects.”
The researchers used a latent process decomposition (LPD) model, an unsupervised model that can handle heterogeneity within individual prostate cancer samples. The LPD model was applied to genome-wide expression data, including 1,785 malignant samples from 8 clinical series.
The research team found that prostate-specific antigen failure was correlated with the level of DESNT, an expression signature indicating poor prognosis in patients with prostate cancer (hazard ratio [HR] = 1.52; P = .0017). Patients who have a majority DESNT signature seem to have a statistically higher metastatic risk than other patients (P = .0019); the test distinguished aggressive types of cancer from less-threatening tumors. The investigators also developed a classification framework incorporating levels of DESNT and identified three additional molecular subtypes of prostate cancer, which may help clinicians design treatment according to patients’ needs.
In the future, researchers predict that analyzing the value of DESNT and other LPD processes may aid in managing and predicting responses to drug treatments in patients with prostate cancer.
Disclosure: For full disclosures of the study authors, visit nature.com.
