The pan-cancer proteome atlas, a mass spectrometry-based landscape for discovering tumor biology, biomarkers, and therapeutic targets

Most cancer proteomics studies to date have focused on a single cancer type. We report The Pan-Cancer Proteome Atlas (TPCPA) based on data-independent acquisition mass spectrometry, to better understand cancer biology and identify therapeutic targets and biomarkers. TPCPA includes 9,670 proteins derived from 999 primary tumors representing 22 cancer types. We describe pan-cancer and cancer type-enriched proteins with extensive external annotation, prioritizing candidate drug targets and biomarkers. Relevant for proteolysis-targeting chimeras, we identify E3-ubiquitin ligases highly expressed in specific tumor types, including HERC5 (esophageal cancer) and RNF5 (liver cancer). Co-expression analysis reveals 13 modules, including unexpected hub proteins as potential drug targets (e.g., GFPT1, LRPPRC, PINK1, DOCK2, and PTPN6). Analysis of 195 colorectal cancers identifies protein markers for RNA-based consensus molecular subtypes (CMSs) and two immune subtypes with prognostic value. We report a cancer type classifier for identification of cancers of unknown primary origin. All TPCPA data can be queried in a dedicated web resource.

Authors

Institutions

Publication Details

Journal
Cancer Cell
Published
2025-05-29
DOI
https://doi.org/10.1016/j.ccell.2025.05.003
Citations
26
Primary Topic
Advanced Proteomics Techniques and Applications
Type
article
Field-Weighted Citation Impact
19.66

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The pan-cancer proteome atlas, a mass spectrometry-based landscape for discovering tumor biology, biomarkers, and therapeutic targets

Maarten F. Bijlsma, Tiannan Guo, Thang V. Pham, Daphne de Jong et al.
26 citations
Cancer Cell
Advanced Proteomics Techniques and Applications
19.66
article

The pan-cancer proteome atlas, a mass spectrometry-based landscape for discovering tumor biology, biomarkers, and therapeutic targets

Maarten F. Bijlsma, Tiannan Guo, Thang V. Pham, Daphne de Jong, Danijela Koppers‐Lalic, Mariëtte Labots, Meisi Yan, Jun Arita, Franziska Böttger, Andrea Vallés‐Martí, Tessa Y. S. Le Large, Madiha Mumtaz, Jan Paul Medema, Tim Schelfhorst, Elisa Giovannetti, Alex A. Henneman, Irene V. Bijnsdorp, Shuaiyao Wang, Janne Lehtiö, Jules P.P. Meijerink, David P. Noske, Chantal Scheepbouwer, Madalena Monteiro, Jos Jonkers, Geert Kazemier, Barbara Sitek, Bart A. Westerman, John W.M. Martens, Jacqueline J Cloos, Winan J. van Houdt, Ruud H. Brakenhoff, Renske D.M. Steenbergen, Geert J.L.H. van Leenders, Valentina Cordo’, Nicole C.T. van Grieken, Connie R. Jiménez, Frank Rolfs, Jan N.M. IJzermans, Jan Köster, Tong Liu, Fangfei Zhang, Mengge Lyu, Hanneke W. M. van Laarhoven, Xiaolu Zhan, Robby E. Kibbelaar, Jaco C. Knol, Richard R. de Goeij‐de Haas, Sander R. Piersma
article en
26 citations

Abstract

Most cancer proteomics studies to date have focused on a single cancer type. We report The Pan-Cancer Proteome Atlas (TPCPA) based on data-independent acquisition mass spectrometry, to better understand cancer biology and identify therapeutic targets and biomarkers. TPCPA includes 9,670 proteins derived from 999 primary tumors representing 22 cancer types. We describe pan-cancer and cancer type-enriched proteins with extensive external annotation, prioritizing candidate drug targets and biomarkers. Relevant for proteolysis-targeting chimeras, we identify E3-ubiquitin ligases highly expressed in specific tumor types, including HERC5 (esophageal cancer) and RNF5 (liver cancer). Co-expression analysis reveals 13 modules, including unexpected hub proteins as potential drug targets (e.g., GFPT1, LRPPRC, PINK1, DOCK2, and PTPN6). Analysis of 195 colorectal cancers identifies protein markers for RNA-based consensus molecular subtypes (CMSs) and two immune subtypes with prognostic value. We report a cancer type classifier for identification of cancers of unknown primary origin. All TPCPA data can be queried in a dedicated web resource.

Cancer CellVol. 43(7)
Harbin Medical University (CN), University of the Punjab (PK), Science for Life Laboratory (SE), Erasmus MC (NL), Karolinska Institutet (SE), The Netherlands Cancer Institute (NL), Westlake University (CN), Third Affiliated Hospital of Harbin Medical University (CN), Princess Máxima Center (NL), Erasmus MC Cancer Institute (NL), Erasmus MC Transplant Institute
Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Cancer Center Amsterdam
Good health and well-being
Openalex Percentile: Top 0%
Advanced Proteomics Techniques and Applications
19.66
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.