PuSH - Publication Server of Helmholtz Zentrum München

Kutkaite, G. ; Avar, G. ; Lu, D. ; O’Neill, T.J. ; Krappmann, D. ; Menden, M.P.

Systematic identification of pan-cancer single-gene expression biomarkers in drug high-throughput screens.

PLoS ONE 21, DOI: 10.1371/journal.pone.0330412 (2026)
Publ. Version/Full Text Research data DOI
Open Access Gold
Creative Commons Lizenzvertrag
Precision oncology relies on molecular biomarkers to stratify patients into responders and non-responders to a given treatment. Although gene expression profiles have historically been explored for biomarker discovery, fewer studies investigated single-gene expression biomarkers. Additionally, many approaches are limited to cancer type-specific associations, which constrain statistical power. To address these limitations, we developed a regression-based framework that corrects for tissue-specific biases and enhances detection of pan-cancer single-gene expression biomarkers of drug sensitivity in cancer cell line high-throughput drug screens. Our method maintains predictive performance post-correction, and successfully recovers established biomarkers, such as SLFN11 expression for DNA damaging agents. Notably, we identified SPRY4 and NES expression as biomarkers of sensitivity for compounds targeting ERK/MAPK signaling (adjusted p-value = 4.016 × 10 - 5 and 7.221 × 10 - 6, respectively). This approach offers a scalable strategy for biomarker discovery and holds potential for translation to more complex biological models and patient-derived datasets. Ultimately, pan-cancer single-gene expression biomarkers may inform patient stratification and warrant clinical validation in precision oncology.
Altmetric
Additional Metrics?
[➜Log in]
Edit extra informations Login
Publication type Article: Journal article
Document type Scientific Article
Keywords Learning-models; Nestin; Her2; Selection; Cells; Sensitivity; Resistance; Regression; Discovery; Vimentin
ISSN (print) / ISBN 1932-6203
Journal PLoS ONE
Quellenangaben Volume: 21, Issue: 5 Pages: , Article Number: , Supplement: ,
Publisher Public Library of Science (PLoS)
Publishing Place Lawrence, Kan.
Reviewing status Peer reviewed
Institute(s) Institute of Computational Biology (ICB)
Research Unit Signaling and Translation (SAT)
Grants European Research Council (ERC)
Deutsche Krebshilfe
HORIZON EUROPE European Research Council