African American (AA) men have an increased incidence and earlier age of onset of prostate cancer and two-fold higher rate of mortality from disease than Caucasian American (CA) men that does not correlate with socioeconomic status. Recent work in the PI's laboratory has shed light on the organization of the genomes of metastatic prostate cancers and primary prostate cancers from CA and AA men and has demonstrated that innate tumor characteristics may contribute to the observed health disparities. Compared to normal, non-cancerous genomes, the tumor genomes contain copy number alteration (CNA) gains or losses of genes that mediate initiation and progression. When matched for age, Gleason score and stage, the genomes of primary AA prostate cancers have a greater number of CNAs that predispose to metastasis compared to the genomes of CA prostate cancers. This study will validate the initial prostate cancer metastatic potential/health disparity study through somatic genomic DNA copy number analysis. A risk metric will be developed for each CNA that will be incorporated into a model that estimates the likelihood that a tumor will metastasize. The genetic predictors will be combined with clinical risk predictors to develop and evaluate a comprehensive statistical risk assessment model. Areas under the receiver-operator curves will be assessed to measure and compare the discriminatory accuracy. Paired analyses will be performed to demonstrate the presence of similar CNA profiles in biopsy and corresponding radical prostatectomy tumor specimens. In addition, whole genome sequencing will be applied to AA and CA tumors of different characteristics - primaries of different metastatic potential and metastases. These will be analyzed for mutations, duplications, and deletions that may have had a causal role.
This project is built on a study that identified innate genomic differences of AA and CA prostate cancers through a novel application of natural selection theory. The research of tumor biology will translate into a risk model for determining whether prostate cancers should be treated aggressively or with watchful waiting. The metastasis-promoting genes identified could become targets for new therapies.
| Pearlman, Alexander; Campbell, Christopher; Brooks, Eric et al. (2012) Clustering-Based Method for Developing a Genomic Copy Number Alteration Signature for Predicting the Metastatic Potential of Prostate Cancer. J Probab Stat 2012:873570 |
