Picciani M, Soleymaniniya A, Müller J, Sakhteman A, Tzanakis K, Bernett J, Kahl E, Hamood F, Kersting J, Pourjam M, Nagai LAE, List M, Kuster B, The M, Wilhelm M (2026)
Publication Type: Journal article
Publication year: 2026
Book Volume: 54
Pages Range: D470-D480
Journal Issue: 1
DOI: 10.1093/nar/gkaf1265
Proteomic and phenotypic cell sensitivity datasets are increasingly important for understanding chemoproteomics and the underlying drug mechanisms of action. Yet, integrating such heterogeneous datasets remains challenging due to inconsistent annotations, incompatible IDs, and variable data processing methods. Here, a major update to ProteomicsDB (https://www.proteomicsdb.org) is presented that combines over 1300 proteomic and 1000 transcriptomic profiles with phenotypic cell sensitivity data across >1500 human cancer cell lines and 1470 drugs. Harmonizing cell line and drug names and applying a standardized normalization and refitting pipeline for dose–response curves enables consistent, statistically robust analysis across studies. Three new graphical user interfaces support interactive exploration of cell sensitivity data, exploring the protein targets and dose-resolved changes in protein expression in the presence of a drug, and comparing the expression profiles of cell lines. With this update, ProteomicsDB is strengthening its future role as a central hub for proteomics and multi-omics, providing researchers with a unified framework to explore phenotypic cell sensitivity in combination with dose-resolved expression proteomics at the molecular level, supporting biomarker discovery, drug repurposing, and precision medicine applications.
APA:
Picciani, M., Soleymaniniya, A., Müller, J., Sakhteman, A., Tzanakis, K., Bernett, J.,... Wilhelm, M. (2026). Mapping drug mechanisms with ProteomicsDB: unified omics and cell sensitivity data at scale. Nucleic Acids Research, 54(1), D470-D480. https://doi.org/10.1093/nar/gkaf1265
MLA:
Picciani, Mario, et al. "Mapping drug mechanisms with ProteomicsDB: unified omics and cell sensitivity data at scale." Nucleic Acids Research 54.1 (2026): D470-D480.
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