Prostate cancer (PCa) is the second most commonly diagnosed malignancy in men, with
incidence and mortality rates varying across Africans and Europeans. The vast majority of deaths
from PCa occur among the approximately 10-15% of patients diagnosed with aggressive PCa.
The etiology of PCa is poorly understood. Basic research supports a crucial role of certain proteins
in PCa development. Epidemiological studies also have identified multiple candidate protein
biomarkers for PCa. However, conventional epidemiologic studies were conducted primarily in
Europeans, and it is unclear which of the candidate protein biomarkers may be European-specific
or pan-ethnic. Also, findings with many of these biomarkers have been inconsistent, potentially
due to major methodological limitations, such as selection bias and uncontrolled confounding.
Besides understanding etiology, identifying causal protein biomarkers can potentially contribute
to improving risk prediction. For PCa, substantial efforts have been made to identify high-risk
populations for improving PCa screening. However, the performance of available PCa risk
prediction models remains unsatisfactory. There are critical needs to 1) apply a novel study design
with reduced limitations of conventional biomarker studies for characterizing PCa causally related
protein biomarkers across Africans and Europeans to improve the etiology understanding; and 2)
develop improved prediction models that may effectively facilitate PCa risk/aggressiveness
assessment across Africans and Europeans. One strategy to potentially decrease limitations of
unmeasured confounding is to use genetic instruments for assessing the relationship between
proteins and PCa. While our previous studies have utilized proteins measured in blood, it is also
critical to study prostate tissue, the most relevant tissue for PCa development, as levels of many
proteins show tissue-specific effects. The proposed project will apply a series of new studies to
address these important knowledge gaps. Specifically, we will 1) conduct a study to identify
putative causal protein biomarkers for PCa risk and aggressiveness across Africans and
Europeans by applying novel methods (Aim 1); 2) functionally characterize top protein biomarkers
for their roles in PCa biology (Aim 2); and 3) develop and validate ethnic-specific and pan-ethnic
prediction models for PCa risk and aggressiveness, by incorporating newly identified candidate
protein biomarkers and integrating results from multiple statistical methods (Aim 3). Our study will
generate important new knowledge for PCa etiology, and develop improved PCa
risk/aggressiveness prediction models across Africans and Europeans. The proposed new
methods can also be applied to other complex diseases.
