Machine learning-based proteogenomic data modeling identifies circulating plasma biomarkers for early detection of lung cancer
While these findings do not establish mechanistic causality, they highlight proteomic alterations reflecting systemic changes preceding the diagnosis. Our study contributes to understanding genome-proteome relationships in lung cancer and identifies circulating proteins warranting further investigation as potential early biomarkers for screening and risk stratification.
Authors
- Marcela A. Johnson (ORCID: https://orcid.org/0000-0002-8446-2493)
- Liping Hou (ORCID: https://orcid.org/0000-0003-3972-245X)
- Assieh Saadatpour
- Bevan E. Huang (ORCID: https://orcid.org/0000-0002-1981-5838)
- Abolfazl Doostparast Torshizi
- Shirley Nieves-Rodriguez
Institutions
- Johnson & Johnson (United States) (US)
- Janssen (United States) (US)
Publication Details
- Journal
- Communications Medicine
- Published
- 2026-03-13
- DOI
- https://doi.org/10.1038/s43856-026-01500-1
- Primary Topic
- Advanced Proteomics Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00