Polygenic risk scores and plasma proteomics identify cancer-related proteins and trans-regulated protein networks.

Authors

Diptavo Dutta, Jingning Zhang, Xinyu Guo, Rosamund Quint, Mary R Rooney, Mitchell J Machiela, Kevin M Brown, Josef Coresh, Alexis J Battle, Elizabeth A Platz, Nilanjan Chatterjee

Published in

Cell genomics. Pages 101322. Aug 07, 2026. Epub Aug 07, 2026.

Abstract

Genome-wide association studies identify cancer susceptibility loci, but downstream protein mechanisms remain incompletely defined. We integrate polygenic risk scores (PRSs) for 21 cancers with 4,955 plasma proteins measured in cancer-free Atherosclerosis Risk in Communities (ARIC) participants to prioritize cancer-related proteins and protein networks. The protein quantitative trait score (pQTS) approach assesses associations between cancer PRS and individual protein levels, while ARCHIE partitions cancer risk variants into trans-regulated protein-network components using sparse canonical correlation analysis. Across cancers, pQTS identifies 90 protein associations, including 53 distal trans associations, and ARCHIE identifies 19 components spanning 433 proteins. Downstream analyses connect prioritized proteins to cancer driver genes, somatic alterations, immune cell populations, CRISPR dependency, and cancer-relevant pathways. Cervical cancer and basal cell carcinoma illustrate immune, human papillomavirus (HPV)-related, pigmentation, and inflammatory mechanisms. These findings show that PRS-proteome integration can reveal circulating protein networks underlying inherited cancer susceptibility.

PMID:
42567164
Bibliographic data and abstract were imported from PubMed on 08 Aug 2026.

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