Identifying Plasma Proteins Associated with Risk of Solid Cancers: A 25-Year Prospective Analysis of 4,712 Circulating Proteins in the ARIC Study

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Authors: Ziqiao Wang, Vernon Burk, Zhe Huang, Hana Zahed, David C. Muller, James Yarmolinsky, Matthew A. Lee, Corinne E. Joshu, Zhike Lin, Anna Prizment, Kenneth R. Butler, David J. Couper
+8 more Karl Smith-Byrne, Martijn Kolijn, Roel C.H. Vermeulen, Elio Riboli, Marc Gunter, Josef Coresh, Nilanjan Chatterjee, Elizabeth A. Platz
Cited by: 1

Abstract

5K assay, we analyzed 4,712 unique plasma proteins (4,955 aptamers) in the Atherosclerosis Risk in Communities (ARIC) study among 9,391 middle-aged and older Black (23%) and White (77%) men and women. Over a maximum follow-up of 25.9 years, incident cases included 136 bladder, 271 colorectal, 96 kidney, 22 liver, 416 lung, 88 pancreatic, and 588 prostate cancers. After false discovery rate (FDR) correction, we identified 144 unique protein-cancer associations in common risk-factor adjusted models, and 41 protein-cancer associations in both common and cancer site-specific risk-factor adjusted models. Associations included several novel circulating proteins related to liver (33 proteins) and lung (4 proteins) cancer risk, and confirmed previously established proteins associated with kidney (HAVCR1 and MMP7) and prostate (KLK3 and ACP3) cancer risk. External validation in the European Prospective Investigation into Cancer and Nutrition cohort (SomaScan 7K) confirmed that the majority of FDR-significant proteins showed consistent effect directions and nominal significance, with the proportion of confirmed proteins varying between 75% and 100% depending on the cancer site. Time-lagged analysis demonstrated that 90% of the identified cancer-associated proteins are markers for long-term cancer risk, with observed associations more than 5 years pre-diagnosis after multiple-testing correction. These findings underscore the potential of circulating proteomic markers beyond known risk factors for elucidating etiologic mechanisms and improving risk stratification across cancers.

Fields of Study & Subjects

Advanced Proteomics Techniques and Applications Ferroptosis and cancer prognosis Cancer Lipids and Metabolism

Publication details

Journal / source
medRxiv
Publisher
openRxiv
Publication date
18 March 2026
Language
EN
Document type
Preprint