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Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
Published on: August 19, 2025
Polygenic risk scores and plasma proteomics identify cancer-related proteins and trans-regulated protein networks
Diptavo Dutta1, Jingning Zhang2, Xinyu Guo3
1Integrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA.
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.
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