Read about some of our current research projects:

Project 1: Genome-wide analysis of germline CNPa and SNPs in PCa

We propose to identify germline CNPs in the genome among high-risk PCa patients using the Affymetrix 500K SNP mapping panel and test for associations of identified germline CNPs with PCa risk in high-risk PCa families using family-based association tests. This study will likely identify several genes that are associated with prostate cancer risk. The identified genes not only will contribute to our understanding on prostate cancer etiology, but also will have a significant impact on public health. The identified specific genes may be used to develop specific tests that improve prostate cancer risk assessment, and thus can provide more targeted screening and prevention. Identified genes may also have immediate relevance in developing drugs to either suppress or regain the function of implicated genes. Therefore, this study stands to eventually improve healthcare for large numbers of men.

Project 2: Confirmation of SNPs associated with aggressive PCa in a GWA Study

We propose to identify inherited sequence variants in the genome that confer moderate risk to prostate cancer (PCa) using a genome-wide association (GWA) study among more than 10,000 subjects from multiple study populations. The identified genes may advance our understanding on the etiology of PCa and could be used to better predict the risk for developing PCa. The focus on aggressive PCa is particularly important because this is the most clinically relevant form of PCa.

Project 3: Genetic profiling in PCPT: PCa risk, PSA levels, and chemoprevention

The overall hypothesis of the study is that multiple genetic variants, when combined, can be used to predict men at increased risk for PCa. We will use data and samples from the PCPT study, a phase III randomized, double-blind, placebo-controlled trial of finasteride in the prevention of prostate cancer. Results from this study may potentially benefit millions of men. Men at highest risk for PCa could be identified at an early age for intensive screening and chemoprevention such as finasteride. Genetic variants could also be used in combination with PSA and other existing clinical variables to considerably improve their predictive accuracy for positive prostate biopsy.

Project 4: The role of germline and somatic DNA changes at 8q24 in PCa risk

The overall hypothesis of this study is that germline and somatic genetic variants at 8q24 are associated with PCa risk. We are testing the joint effect of implicated germline risk variants and somatic genetic changes at 8q24 on PCa risk and aggressiveness of the disease among ~800 tumors. We will identify cis- or trans-effects of 8q24 risk variants on gene expression in prostate tissues by assessing correlation between the germline and somatic 8q24 variants and RNA/protein expression of genes in the 8q24 flanking region and elsewhere in the genome. Results from our study will improve our understanding of the most prominent genetic finding to date and may have important implications in disease prediction, diagnosis, and treatment.

Project 5: Genetic variants in the genome predisposing to aggressive PCa

Taking advantage of the publicly available CGEMS genome wide association data, as well as the large and unique PCa patient population at Johns Hopkins Hospital (JHH), we propose a systematic genetic association study to confirm, fine map, and better characterize genetic risk variants for aggressive PCa.

Project 6: Interaction of germline and somatic changes in PCa progression

Understanding factors associated with the progression of PCa will have a significant impact on management and treatment of the disease. This proposal intends to identify interaction effects on prostate cancer (PCa) progression for several known germline (PCa) risk variants genetic and somatic genetic and epigenetic changes identified in our study, using several global detection methods. We hypothesize that germline risk variants, combined with somatic genetic and epigenetic changes may increase the risk of prostate cancer progression. The results of this study may advance our understanding on the etiology of PCa progression and augment current methods to better predict which PCa patients are most likely to develop progressed disease at the time of diagnosis. The PCa patients with poor prognosis can receive intensive monitoring and treatment.

Project 7: Global genetic and epigentic approached to progression of PCa

We hypothesize that genetic changes in the germline or tumor genome, as well as epigenetic modifications, may independently or jointly affect the expression of the genes that are involved in the progression of PCa. We proposed to screen for germline DNA copy number variants (CNVs), somatic DNA copy number changes and modifications in methylation status across the whole genome among 160 intermediate- to high-grade PCa patients, with or without disease progression. By comparing the frequencies of germline CNVs, somatic deletions and gains, and hyper- or hypo-methylation between progressors and non-progressors, we expect to identify several alterations that are recurrent and have significantly higher frequencies among progressors. Secondly, we will test for association between PCa progression and implicated germline CNVs, somatic deletions or gains, or DNA methylation modifications identified in Aim 1 among an additional 500 high-grade PCa patients who have been followed-up for at least 5 years. Finally, we will correlate the protein expression of selected genes with their genetic and epigenetic alterations implicated in Aim 2 in order to deduce the complex mechanisms by which PCa progresses to death. The results of this study may advance our understanding on the etiology of PCa progression and augment current methods to better predict which PCa patient will likely develop progressed disease at the time of diagnosis. The PCa patients with poor prognosis can receive intensive monitor and treatment.

Project 8: Systematic search for gene-gene interaction effect on prostate cancer risk

In this proposal, we will apply two novel analytical methods that allow us to perform such gene-gene interaction analysis among millions of genetic changes in thousands of subjects. We will first utilize data (millions of genetic changes) from an existing and large National Cancer Institute Cancer Genetic Markers of Susceptibility (CGEMS) study to systematically discover gene-gene interactions in the genome among ~1,000 PCa patients and ~1,000 normal subjects. We then propose to confirm these discovered gene-gene interactions in our large population-based case-control study in Sweden (CAPS), with ~3,000 PCa patients and ~2,000 normal subjects. Such confirmation is necessary because many gene-gene interactions, whether true or by chance alone, will be found in the discovery stage. Only true gene-gene interactions will be replicated in independent study populations.