IARC 60th Anniversary - 19-21 May 2026
Session : 19/05/26 - Posters
Comprehensive characterization of the blood proteome before lung cancer diagnosis.
GUENOUN A. 1, ZAHED H. 2, ALCALA K. 1, BURK D. 7, CHATTERJEE N. 4, SMITH-BYRNE K. 3, GUNTER M. 5, MULLER D. 6, PLATZ E. 7, ROBBINS H. 1, JOHANSSON M. 1
1 Early Detection, Prevention, and Infections Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France; 2 Cardiopulmonary Epidemiology Team, Johnson & Johnson, Zurich, Switzerland; 3 Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; 4 Department of Oncology, the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University School of Medicine, Baltimore, United States; 5 Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London., London, United Kingdom; 6 Cancer Epidemiology and Prevention Research Unit, School of Public Health, Imperial College London., London, United Kingdom; 7 Department of Epidemiology Johns Hopkins Bloomberg School of Public Health, Baltimore, United States
Background. Lung cancer is the leading cause of cancer mortality worldwide. Early detection through low-dose CT (LDCT) screening reduces mortality but current eligibility criteria overlook up to 50% of incident lung cancer cases. Improving risk stratification is therefore critical to enhance screening efficiency and circulating proteins represent a promising avenue.
Objectives. This study aims to identify a broader range of circulating proteins associated with lung cancer risk and to evaluate how the relevance of these protein associations changes across longer periods prior to diagnosis.
Methods. We conducted a large-scale proteomics discovery analysis in a case-cohort of 4,660 participants within the European Prospective Investigation into nutrition and Cancer (EPIC) study, including 545 incident lung cancer cases. Replication analyses were carried out in the Atherosclerosis Risk in Communities (ARIC) cohort. Relative concentrations for 7000 circulating proteins were measured using the SomaLogic platform.
Results. We found 610 proteins associated with lung cancer risk in participants with a history of smoking (false discovery rate<0.05), 269 of which were replicated in the independent ARIC cohort (p<0.05). Notable markers associated with increased risk included HE4 with a hazard ratios (HR) per standard deviation increment at 2.15 (95% CI: 1.89–2.44), 1.89 (95% CI: 1.63–2.19) for MIC-1, 1.79 (95% CI: 1.61–1.99) for PIGR, and 1.72 (95% CI: 1.51–1.95) for sICAM-5. Smoking exposure partly accounted for the observed risk associations, with smoking adjusted HR estimates of 1.72 (95% CI: 1.48–2.00) for HE4, 1.51 (95% CI: 1.31–1.74) for MIC-1, 1.42 (95% CI: 1.24–1.63) for sICAM-5 and 1.38 (95% CI: 1.24–1.55) for PIGR. Detailed smoking information accounted for up to 80% of the observed risk associations. While the strength of association remained stable over time for some markers (e.g. HE4), others such as C9 showed stronger associations when measured closer to diagnosis. For example, the HR at one year for C9 was 1.85 (95% CI: 1.34–2.54) compared to a HR of 1.48 (95% CI: 1.33–1.64) when measured 10 years before diagnosis.
Conclusions. This study demonstrates the importance of the blood proteome in predisposition of lung cancer and will inform the development of accurate biomarker-informed risk models.