ArticleiScience2025
Integrated multi-dimensional comparison of proteomic profiles across 54 cancer cell lines.
Article in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Scalable phosphotyrosine enrichment with SH2 superbinder enables deep profiling of EGF responses.The EMBO journal · 2026Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.