Plasma signals of lung tumor promotion for molecular cancer prevention
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Tej Pandya Maria Zagorulya Michelle M Leung Marcellus Augustine Lydia Y Liu Aino-Maija Leppä Ulysse Baruchel Sin Wi Ng Tamara Klockner Miriam Mugabo Anthony J Griffen Oleg Blyuss Chrysante Iliakis Amalie Grenov Kerstin Haase David C Muller Ka Hung Chan Jincheng Wu Vernon A Burk Neil Wright Alix Le Marois Ekaterina Pazukhina Sophie Ward Hubert Slawinski Marc Pelletier Cian Murphy Matthew D Park Thomas Snoeks Alejandro Suárez-Bonnet Simon Priestnall Alexandros Hardas Charlotte Grieco Ami Archer Alpkaan Celik Alejandro Jimenez-Sanchez Rachel Scott Hana Zahed Léa Montégut Rafael Meza Clinton H Durney Stephen Lam Takahiro Karasaki Roel CH Vermeulen Huilei Xu Pablo Serrano-Fernandez Tatjana Crnogorac-Jurcevic Usha Menon Sophia Apostolidou Alexey Zaikin Richard Gunu Harry J Whitwell Zhe Huang Zonglun Li Xin Hu Bo Zhu Liming Li María-Dolores Chirlaque Marcela Guevara P Martijn Kolijn Aghiles Guenoun Neeloffer Mookherjee Mattias Johansson Ziqiao Wang Nilanjan Chatterjee Chao-Hua Chiu Zhengming Chen Dana Pe'er Erik Sahai Saskia Freytag Andreas Wack Marc J Gunter Miriam Merad Jianjun Zhang Christopher Carlsten Pan-Chyr Yang Hsuan-Yu Chen Elizabeth A Platz Lindsay M LaFave Karl Smith-Byrne Mariam Jamal-Hanjani Kevin Litchfield Nuno R Nene Nicholas Mcgranahan Eva Gronroos William Hill Clare Weeden Charles Swanton
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Abstract
Predicting lung cancer risk would enhance prevention trials. Although the Canakinumab Anti-inflammatory Thrombosis Outcome Study (CANTOS) trial demonstrated reduced lung cancer incidence with interleukin (IL)-1β inhibition, the high number needed to treat (NNT) to prevent lung cancer limits its use in unselected populations. Using machine learning, we identified a 14-protein plasma signature predicting lung cancer more than 5 years before diagnosis. The signature, validated across eight cohorts, was elevated in current smokers and individuals exposed to particulate matter (PM) and linked to lung myeloid and alveolar cells. In epidermal growth factor receptor (EGFR)-driven lung adenocarcinoma, diverse epithelial lineages converged on a keratin8+/claudin4+ alveolar transitional state (KAC), whose transcriptional programs correlated with signature emergence. Components of the signature were induced by PM, oncogenic EGFR, or IL-1β, whereas IL-1β inhibition restrained PM-driven KAC expansion and early tumorigenesis. In CANTOS, the signature identified individuals who seemed to benefit more from anti-IL-1β therapy, lowering the NNT threshold and nominating circulating signals of tumor promotion for prevention.
Journal details
Journal
Cell
Volume
189
Issue number
13
Pages
3903-3921.e26
Available online
Publication date
Full text links
Publisher website (DOI)
10.1016/j.cell.2026.05.005
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Europe PubMed Central
42242224
Pubmed
42242224
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