Plasma proteomics for risk prediction of lung cancer
Presenter: Tej Pandya, MBBCh Session: Cancer and Cancer Related Alterations, Detection Approaches, and Molecular Characterization Time: 4/22/2026 9:00:00 AM → 4/22/2026 12:00:00 PM
Authors
Tej Pandya 1 , Maria Zagorulya 1 , Michelle M. Leung 2 , Marcellus Augustine 1 , Lydia Y. Liu 1 , Oleg Blyuss 3 , Jincheng Wu 4 , Marc Pelletier 4 , Vernon Burk 5 , Neil Wright 6 , David Muller 7 , Ka Hung Chan 8 , Ekaterina Pazukhina 3 , Marc Gunter 9 , Elizabeth A. Platz 5 , Karl Smith-Byrne 10 , Nuno Rocha Nene 1 , Eva Camilla Gronroos 1 , Nicholas McGranahan 11 , William Hill 1 , Clare Weeden 1 , Charles Swanton 1 1 Francis Crick Institute, London, United Kingdom, 2 University College London, London, United Kingdom, 3 Centre for Prevention, Detection and Early Diagnosis, Wolfson Institute of Population Health, Queen Mary, University of London, London, United Kingdom, 4 Novartis (Cambridge, MA), Cambridge, MA, 5 Johns Hopkins Bloomberg Sch. of Public Health, Baltimore, MD, 6 Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom, 7 Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom, 8 University of Oxford, Oxford, United Kingdom, 9 Cancer Epidemiology and Prevention Research Unit, School of Public Health, Imperial College London, London, United Kingdom, 10 University of Oxford, Cancer Epidemiology Unit, United Kingdom, 11 UCL London Cancer Institute, London, United Kingdom
Abstract
Background: Current lung cancer screening programs rely heavily on age and smoking history, excluding never-smokers and those with minimal smoking exposure. Such criteria have a low positive predictive value (PPV), limiting molecular prevention strategies. Our previous work identified interleukin-1β (IL-1β) as a mediator of lung cancer initiation through environmental particulate matter (PM) exposure, suggesting potential targets for therapeutic cancer prevention. Here, we sought to identify circulating signals predictive of lung cancer prior to clinical diagnosis and determine if they were useful for clinical trial stratification of IL-1β therapy. Methods: Using human plasma proteomic data from the UK Biobank (n=48,099 individuals; 375 lung cancer cases), we developed a machine-learning framework to identify proteins predictive of lung cancer diagnosis. We validated this model in eight independent human cohorts (2,176 cases, 54,324 controls). We further analysed plasma proteomic murine data from EGFR-mutant mice exposed to PM as well as from baseline samples from the CANTOS trial which previously had demonstrated reduction of lung cancer incidence with IL-1β inhibition. Results: Our machine-learning approach identified a plasma signature of 14 proteins, predictive of lung cancer diagnosis up to 6 years before clinical detection, significantly outperforming current lung cancer risk models (p Discussion: Our findings indicate that a circulating plasma signature derived from alveolar niche remodelling and induced by PM and EGFR-driven oncogenesis can effectively identify individuals at high risk of lung cancer two years before clinical onset. The identified proteins may enable targeted stratification for molecular prevention trials. Future research should focus on extending this approach and developing absolute quantification assays to for clinical translation.
Disclosure
T. Pandya, Francis Crick Institute Patent. Francis Crick Institute Patent. FutureHouse Independent Contractor. M. Zagorulya, Baseimmune Ltd Employment, Stock. M. M. Leung, None. M. Augustine, Francis Crick Institute Patent. Francis Crick Institute Patent. Future House Independent Contractor. L. Y. Liu, None.. O. Blyuss, None. J. Wu, Novartis Employment. M. Pelletier, Novartis Employment. V. Burk, None.. N. Wright, None.. D. Muller, None.. K. Chan, None.. E. Pazukhina, None.. M. Gunter, None.. E. A. Platz, None.. K. Smith-Byrne, None. N. Rocha Nene, Francis Crick Institute Patent. E. C. Gronroos, None. N. McGranahan, University College London Patent. W. Hill, None.. C. Weeden, None. C. Swanton, AstraZeneca ). Boehringer-Ingelheim ). Bristol Myers Squibb ). Pfizer ). Roche-Ventana ). Invitae ). Ono Pharmaceutical ). Personalis ). GRAIL Independent Contractor, Other, Scientific Advisor Board. Bicycle Therapeutics Independent Contractor, Other, Scientific Advisory Board. Genentech Independent Contractor. Relay Therapeutics Other, Scientific Advisor Board. Saga Diagnostics Other, Scientific Advisory Board. Epic Bioscience Stock Option. Medicxi ). Illumina ). GlaxoSmithKline ). MSD ). China Innovation Centre of Roche ). Amgen ).
Cited in
Control: 796 · Presentation Id: 6802 · Meeting 21436