Skip to main content
An official website of the United States government
Grant Details

Grant Number: 5R01CA263494-02 Interpret this number
Primary Investigator: Wu, Lang
Organization: University Of Hawaii At Manoa
Project Title: Uncovering Causal Protein Markers to Improve Prostate Cancer Etiology Understanding and Risk Prediction in Africans and Europeans
Fiscal Year: 2023


Abstract

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.



Publications

Sensitivity analysis with iterative outlier detection for systematic reviews and meta-analyses.
Authors: Meng Z. , Wang J. , Lin L. , Wu C. .
Source: Statistics in medicine, 2024-04-15; 43(8), p. 1549-1563.
EPub date: 2024-02-06.
PMID: 38318993
Related Citations

Regional analysis to delineate intrasample heterogeneity with RegionalST.
Authors: Lyu Y. , Wu C. , Sun W. , Li Z. .
Source: Bioinformatics (Oxford, England), 2024-03-29; 40(4), .
PMID: 38579257
Related Citations

Proteome-wide association study and functional validation identify novel protein markers for pancreatic ductal adenocarcinoma.
Authors: Zhu J. , Wu K. , Liu S. , Masca A. , Zhong H. , Yang T. , Ghoneim D.H. , Surendran P. , Liu T. , Yao Q. , et al. .
Source: GigaScience, 2024-01-02; 13, .
PMID: 38608280
Related Citations

Identification of blood protein biomarkers associated with prostate cancer risk using genetic prediction models: analysis of over 140,000 subjects.
Authors: Zhong H. , Zhu J. , Liu S. , Ghoneim D.H. , Surendran P. , Liu T. , Fahle S. , Butterworth A. , Ashad Alam M. , Deng H.W. , et al. .
Source: Human molecular genetics, 2023-11-03; 32(22), p. 3181-3193.
PMID: 37622920
Related Citations

Combined CRISPRi and proteomics screening reveal a cohesin-CTCF-bound allele contributing to increased expression of RUVBL1 and prostate cancer progression.
Authors: Tian Y. , Dong D. , Wang Z. , Wu L. , Park J.Y. , PRACTICAL consortium , Wei G.H. , Wang L. .
Source: American journal of human genetics, 2023-08-03; 110(8), p. 1289-1303.
PMID: 37541187
Related Citations

THE EFFECT DIRECTION SHOULD BE TAKEN INTO ACCOUNT WHEN ASSESSING SMALL-STUDY EFFECTS.
Authors: Meng Z. , Wu C. , Lin L. .
Source: The journal of evidence-based dental practice, 2023 Mar; 23(1), p. 101830.
EPub date: 2022-12-24.
PMID: 36914304
Related Citations

Polygenic risk score improves the accuracy of a clinical risk score for coronary artery disease.
Authors: King A. , Wu L. , Deng H.W. , Shen H. , Wu C. .
Source: BMC medicine, 2022-11-07; 20(1), p. 385.
EPub date: 2022-11-07.
PMID: 36336692
Related Citations




Back to Top