Predicted Proteome Association Studies of Breast, Prostate, Ovarian, and Endometrial Cancers Implicate Plasma Protein Regulation in Cancer Susceptibility.

Abstract

BACKGROUND:

Predicting protein levels from genotypes for proteome-wide association studies (PWAS) may provide insight into the mechanisms underlying cancer susceptibility.

METHODS:

We performed PWAS of breast, endometrial, ovarian, and prostate cancers and their subtypes in several large European-ancestry discovery consortia (effective sample size: 237,483 cases/317,006 controls) and tested the results for replication in an independent European-ancestry GWAS (31,969 cases/410,350 controls). We performed PWAS using the cancer GWAS summary statistics and two sets of plasma protein prediction models, followed by colocalization analysis.

RESULTS:

Using Atherosclerosis Risk in Communities (ARIC) models, we identified 93 protein-cancer associations [false discovery rate (FDR) < 0.05]. We then performed a meta-analysis of the discovery and replication PWAS, resulting in 61 significant protein-cancer associations (FDR < 0.05). Ten of 15 protein-cancer pairs that could be tested using Trans-Omics for Precision Medicine (TOPMed) protein prediction models replicated with the same directions of effect in both cancer GWAS (P < 0.05). To further support our results, we applied Bayesian colocalization analysis and found colocalized SNPs for SERPINA3 protein levels and prostate cancer (posterior probability, PP = 0.65) and SNUPN protein levels and breast cancer (PP = 0.62).

CONCLUSIONS:

We used PWAS to identify potential biomarkers of hormone-related cancer risk. SNPs in SERPINA3 and SNUPN did not reach genome-wide significance for cancer in the original GWAS, highlighting the power of PWAS for novel locus discovery, with the added advantage of providing directions of protein effect.

IMPACT:

PWAS and colocalization are promising methods to identify potential molecular mechanisms underlying complex traits.

• Authors: Isabelle Gregga, Paul D P Pharoah, Simon A Gayther, Ani Manichaikul, Hae Kyung Im, Siddhartha P Kar, Joellen M Schildkraut, Heather E Wheeler
• Journal: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology (Cancer Epidemiol Biomarkers Prev) Vol. 32 Issue 9 Pg. 1198-1207 (09 01 2023) ISSN: 1538-7755 [Electronic] United States
• PMID: 37409955 (Publication Type: Meta-Analysis, Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't)
• Copyright: ©2023 American Association for Cancer Research.

Chemical References

• Proteome
• Blood Proteins

Topics

• Male
• Female
• Humans
• Proteome (genetics)
• Genetic Predisposition to Disease
• Prostate
• Bayes Theorem
• Genome-Wide Association Study
• Endometrial Neoplasms (genetics)
• Prostatic Neoplasms (genetics)
• Blood Proteins
• Polymorphism, Single Nucleotide