SynthesisCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2023
Predicted Proteome Association Studies of Breast, Prostate, Ovarian, and Endometrial Cancers Implicate Plasma Protein Regulation in Cancer Susceptibility.
Synthesis in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Brain transcriptome-wide association studies in diverse ancestral populations reveal genes implicated in an anxiety-related phenotype.G3 (Bethesda, Md.) · 2026Pooled it
- Large-scale integration of omics and electronic health records to identify potential risk protein biomarkers and therapeutic drugs for cancer prevention.American journal of human genetics · 2026Article
- Protein markers of ovarian cancer and its subtypes: insights from proteome-wide Mendelian randomisation analysis.British journal of cancer · 2025Article
- Discovering plasma proteins associated with breast cancer incidence in postmenopausal women in the Atherosclerosis Risk in Communities study.Journal of the National Cancer Institute · 2025Article
- Multivariate proteome-wide association study to identify causal proteins for Alzheimer disease.American journal of human genetics · 2025Article
- Understanding genetic architecture of breast cancer: how can proteome-wide association studies contribute?British journal of cancer · 2024Article
- A proteome-wide association study identifies putative causal proteins for breast cancer risk.British journal of cancer · 2024Article
- Identifying therapeutic targets for breast cancer: insights from systematic Mendelian randomization analysis.Frontiers in oncology · 2024Article
- Elucidating the susceptibility to breast cancer: an in-depth proteomic and transcriptomic investigation into novel potential plasma protein biomarkers.Frontiers in molecular biosciences · 2023Article
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Authors and funding
8 authors at 6 institutions in 2 countries.
Funding
Abstract
backgroundPredicting protein levels from genotypes for proteome-wide association studies (PWAS) may provide insight into the mechanisms underlying cancer susceptibility.
methodsWe 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.
resultsUsing 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).
conclusionsWe 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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.