A phosphoproteome atlas of human cell lines reveals the landscape of kinase activity

Abstract Protein phosphorylation orchestrates cellular signaling and controls most biological processes, with its dysregulation driving diseases, notably cancer. Comprehensive, high-throughput phosphoproteomics remains limited by detection sensitivity, data completeness and computational bottlenecks, especially in low-input settings. Here we present a comprehensive empirical human phosphoproteome resource, regrouping over 200,000 class I phosphosites across 33 diverse human cell lines. We demonstrate that this spectral library dramatically improves single-shot phosphoproteomics with 30-fold faster data processing compared with library-free approaches and enhances confidence in phosphosite localization even from minimal sample input. Integrating proteome and phosphoproteome data, we develop a combined kinase activity score (Cscore), revealing cell line- and cancer-specific signaling vulnerabilities, many correlating with drug sensitivity. This resource accelerates deep and reproducible phosphoproteomics, enables the systematic mapping of cellular signaling networks and may empower precision oncology by highlighting actionable kinase targets in diverse cell states.

Authors

Institutions

Publication Details

Journal
Nature Structural & Molecular Biology
Published
2026-09-30
DOI
https://doi.org/10.1038/s41594-026-01877-6
Citations
1
Primary Topic
Advanced Proteomics Techniques and Applications
Type
article
Field-Weighted Citation Impact
1.87
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

A phosphoproteome atlas of human cell lines reveals the landscape of kinase activity

Hayoung Cho, Ilaria Piga, Pierre Sabatier, Jesper Velgaard Olsen et al.
1 citations
Nature Structural & Molecular Biology
Advanced Proteomics Techniques and Applications
1.87
article

A phosphoproteome atlas of human cell lines reveals the landscape of kinase activity

Hayoung Cho, Ilaria Piga, Pierre Sabatier, Jesper Velgaard Olsen, Ana Martínez‐Val, Kristina Bennet Emdal, Claire Koenig, Samuel Lozano-Juárez
article en
1 citations

Abstract

Abstract Protein phosphorylation orchestrates cellular signaling and controls most biological processes, with its dysregulation driving diseases, notably cancer. Comprehensive, high-throughput phosphoproteomics remains limited by detection sensitivity, data completeness and computational bottlenecks, especially in low-input settings. Here we present a comprehensive empirical human phosphoproteome resource, regrouping over 200,000 class I phosphosites across 33 diverse human cell lines. We demonstrate that this spectral library dramatically improves single-shot phosphoproteomics with 30-fold faster data processing compared with library-free approaches and enhances confidence in phosphosite localization even from minimal sample input. Integrating proteome and phosphoproteome data, we develop a combined kinase activity score (Cscore), revealing cell line- and cancer-specific signaling vulnerabilities, many correlating with drug sensitivity. This resource accelerates deep and reproducible phosphoproteomics, enables the systematic mapping of cellular signaling networks and may empower precision oncology by highlighting actionable kinase targets in diverse cell states.

Nature Structural & Molecular Biology
Uppsala University (SE), Novo Nordisk Foundation (DK), Copenhagen University Hospital (DK), Rigshospitalet (DK), Spanish National Centre for Cardiovascular Research (ES), Centro de Investigación en Red en Enfermedades Cardiovasculares (ES), Centro de Investigación Biomédica en Red (ES)
Openalex Percentile: Top 10%
Advanced Proteomics Techniques and Applications
1.87
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.