Integrated multi-dimensional comparison of proteomic profiles across 54 cancer cell lines

Human cancer cell lines are essential model systems in biomedical research. We conducted multi-level proteomics analyses on 54 widely used cancer cell lines derived from various tissues using two prominent proteomics technologies: mass spectrometry (MS) and reverse-phase protein array (RPPA). Our analysis identified 10,088 proteins, 33,161 phosphorylation sites across 7,469 phosphoproteins, and 56,320 site-specific glycans on 14,228 glycosylation sites from 5,966 glycoproteins, along with 305 drug-relevant protein and phosphoprotein targets. Analysis of this rich dataset yielded numerous biological insights, including protein features that distinguish tissue origins and cell line-specific kinase activation patterns, reflecting signaling diversity across cancer types. These findings may inform therapeutic strategies and support rational model system selection. Additionally, MS and RPPA showed consistent fold-change estimation and provided complementary views of proteome and signaling variation. This comprehensive resource facilitates biomarker discovery, signaling analysis, and translational oncology research across diverse human tumor types.