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

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

doi:10.1016/j.ccell.2025.05.003

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

Jaco C. Knol
, Mengge Lyu
, Franziska Böttger
, Madalena Nunes Monteiro
, Thang V. Pham
, Frank Rolfs
, Andrea Vallés-Martí
, Tim Schelfhorst
, Richard R. de Goeij-de Haas
, Irene V. Bijnsdorp
, Shuaiyao Wang
, Fangfei Zhang
, Jun A
, Bart A. Westerman
, Barbara Sitek
, Janne Lehtiö
, Jan Koster
, Jan N.M. IJzermans
, Hanneke W.M. van Laarhoven
, Maarten F. Bijlsma

Jan Paul Medema, Alex A. Henneman, Sander R. Piersma, Ruud H. Brakenhoff, Jacqueline Cloos, Valentina Cordo', Daphne de Jong, Geert Kazemier, Danijela Koppers-Lalic, Mariette Labots, Tessa Y.S. Le Large, John W.M. Martens, Jules P.P. Meijerink, Madiha Mumtaz, Chantal Scheepbouwer, Robby E. Kibbelaar, David P. Noske, Renske D.M. Steenbergen, Nicole C.T. van Grieken, Winan van Houdt, Elisa Giovannetti, Geert J.L.H. van Leenders, Jos Jonkers, Tong Liu, Meisi Yan, Xiaolu Zhan, Tiannan Guo, Connie R. Jimenez

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Onderzoeksoutput: Bijdrage aan tijdschrift › Artikel › peer review

27 Citaten (Scopus)

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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.

Originele taal-2	Engels
Pagina's (van-tot)	1328-1346.e8
Tijdschrift	Cancer Cell
Volume	43
Nummer van het tijdschrift	7
DOI's	https://doi.org/10.1016/j.ccell.2025.05.003
Status	Gepubliceerd - 14 jul. 2025

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10.1016/j.ccell.2025.05.003

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Knol, J. C., Lyu, M., Böttger, F., Nunes Monteiro, M., Pham, T. V., Rolfs, F., Vallés-Martí, A., Schelfhorst, T., de Goeij-de Haas, R. R., Bijnsdorp, I. V., Wang, S., Zhang, F., A, J., Westerman, B. A., Sitek, B., Lehtiö, J., Koster, J., IJzermans, J. N. M., van Laarhoven, H. W. M., ... Jimenez, C. R. (2025). The pan-cancer proteome atlas, a mass spectrometry-based landscape for discovering tumor biology, biomarkers, and therapeutic targets. Cancer Cell, 43(7), 1328-1346.e8. https://doi.org/10.1016/j.ccell.2025.05.003

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

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.",

keywords = "bioinformatics, biomarker/ target, colorectal cancer subtypes, mass spectrometry, multi-cancer (sub)type classification, pan-cancer, proteome, Neoplasms/metabolism, Prognosis, Humans, Proteome/metabolism, Mass Spectrometry/methods, Proteomics/methods, Biomarkers, Tumor/metabolism",

author = "Knol, \{Jaco C.\} and Mengge Lyu and Franziska B{\"o}ttger and \{Nunes Monteiro\}, Madalena and Pham, \{Thang V.\} and Frank Rolfs and Andrea Vall{\'e}s-Mart{\'i} and Tim Schelfhorst and \{de Goeij-de Haas\}, \{Richard R.\} and Bijnsdorp, \{Irene V.\} and Shuaiyao Wang and Fangfei Zhang and Jun A and Westerman, \{Bart A.\} and Barbara Sitek and Janne Lehti{\"o} and Jan Koster and IJzermans, \{Jan N.M.\} and \{van Laarhoven\}, \{Hanneke W.M.\} and Bijlsma, \{Maarten F.\} and Medema, \{Jan Paul\} and Henneman, \{Alex A.\} and Piersma, \{Sander R.\} and Brakenhoff, \{Ruud H.\} and Jacqueline Cloos and Valentina Cordo' and \{de Jong\}, Daphne and Geert Kazemier and Danijela Koppers-Lalic and Mariette Labots and \{Le Large\}, \{Tessa Y.S.\} and Martens, \{John W.M.\} and Meijerink, \{Jules P.P.\} and Madiha Mumtaz and Chantal Scheepbouwer and Kibbelaar, \{Robby E.\} and Noske, \{David P.\} and Steenbergen, \{Renske D.M.\} and \{van Grieken\}, \{Nicole C.T.\} and \{van Houdt\}, Winan and Elisa Giovannetti and \{van Leenders\}, \{Geert J.L.H.\} and Jos Jonkers and Tong Liu and Meisi Yan and Xiaolu Zhan and Tiannan Guo and Jimenez, \{Connie R.\}",

year = "2025",

month = jul,

day = "14",

doi = "10.1016/j.ccell.2025.05.003",

language = "English",

volume = "43",

pages = "1328--1346.e8",

journal = "Cancer Cell",

issn = "1535-6108",

publisher = "Cell Press",

number = "7",

}

Knol, JC, Lyu, M, Böttger, F, Nunes Monteiro, M, Pham, TV, Rolfs, F, Vallés-Martí, A, Schelfhorst, T, de Goeij-de Haas, RR, Bijnsdorp, IV, Wang, S, Zhang, F, A, J, Westerman, BA, Sitek, B, Lehtiö, J, Koster, J, IJzermans, JNM, van Laarhoven, HWM, Bijlsma, MF, Medema, JP, Henneman, AA, Piersma, SR, Brakenhoff, RH, Cloos, J, Cordo', V, de Jong, D, Kazemier, G, Koppers-Lalic, D, Labots, M, Le Large, TYS, Martens, JWM, Meijerink, JPP, Mumtaz, M, Scheepbouwer, C, Kibbelaar, RE, Noske, DP, Steenbergen, RDM, van Grieken, NCT, van Houdt, W, Giovannetti, E, van Leenders, GJLH, Jonkers, J, Liu, T, Yan, M, Zhan, X, Guo, T & Jimenez, CR 2025, 'The pan-cancer proteome atlas, a mass spectrometry-based landscape for discovering tumor biology, biomarkers, and therapeutic targets', Cancer Cell, vol. 43, nr. 7, blz. 1328-1346.e8. https://doi.org/10.1016/j.ccell.2025.05.003

TY - JOUR

T1 - The pan-cancer proteome atlas, a mass spectrometry-based landscape for discovering tumor biology, biomarkers, and therapeutic targets

AU - Knol, Jaco C.

AU - Lyu, Mengge

AU - Böttger, Franziska

AU - Nunes Monteiro, Madalena

AU - Pham, Thang V.

AU - Rolfs, Frank

AU - Vallés-Martí, Andrea

AU - Schelfhorst, Tim

AU - de Goeij-de Haas, Richard R.

AU - Bijnsdorp, Irene V.

AU - Wang, Shuaiyao

AU - Zhang, Fangfei

AU - A, Jun

AU - Westerman, Bart A.

AU - Sitek, Barbara

AU - Lehtiö, Janne

AU - Koster, Jan

AU - IJzermans, Jan N.M.

AU - van Laarhoven, Hanneke W.M.

AU - Bijlsma, Maarten F.

AU - Medema, Jan Paul

AU - Henneman, Alex A.

AU - Piersma, Sander R.

AU - Brakenhoff, Ruud H.

AU - Cloos, Jacqueline

AU - Cordo', Valentina

AU - de Jong, Daphne

AU - Kazemier, Geert

AU - Koppers-Lalic, Danijela

AU - Labots, Mariette

AU - Le Large, Tessa Y.S.

AU - Martens, John W.M.

AU - Meijerink, Jules P.P.

AU - Mumtaz, Madiha

AU - Scheepbouwer, Chantal

AU - Kibbelaar, Robby E.

AU - Noske, David P.

AU - Steenbergen, Renske D.M.

AU - van Grieken, Nicole C.T.

AU - van Houdt, Winan

AU - Giovannetti, Elisa

AU - van Leenders, Geert J.L.H.

AU - Jonkers, Jos

AU - Liu, Tong

AU - Yan, Meisi

AU - Zhan, Xiaolu

AU - Guo, Tiannan

AU - Jimenez, Connie R.

PY - 2025/7/14

Y1 - 2025/7/14

N2 - 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.

AB - 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.

KW - bioinformatics

KW - biomarker/ target

KW - colorectal cancer subtypes

KW - mass spectrometry

KW - multi-cancer (sub)type classification

KW - pan-cancer

KW - proteome

KW - Neoplasms/metabolism

KW - Prognosis

KW - Humans

KW - Proteome/metabolism

KW - Mass Spectrometry/methods

KW - Proteomics/methods

KW - Biomarkers, Tumor/metabolism

UR - https://www.scopus.com/pages/publications/105006938550

UR - https://www.mendeley.com/catalogue/2f2ce30f-9bb9-3dcb-ab8f-59bda88f853e/

U2 - 10.1016/j.ccell.2025.05.003

DO - 10.1016/j.ccell.2025.05.003

M3 - Article

C2 - 40446800

AN - SCOPUS:105006938550

SN - 1535-6108

VL - 43

SP - 1328-1346.e8

JO - Cancer Cell

JF - Cancer Cell

IS - 7

ER -

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

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