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bioRxiv · 10.1101/2025.08.03.668348

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

Kutkaite, G.·Avar, G.·Lu, D.·ONeill, T.·Krappmann, D.·Menden, M. P.
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Abstract

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=4.016x10- and 7.221x10-, 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 improve patient stratification and clinical outcomes in precision oncology.

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Kutkaite, G., Avar, G., Lu, D., ONeill, T., Krappmann, D., Menden, M. P.. 2025-08-04. Systematic identification of pan-cancer single-gene expression biomarkers in drug high-throughput screens. https://doi.org/10.1101/2025.08.03.668348

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