Abstract

Despite the successes of immunotherapy in cancer treatment over recent decades, less than <10%–20% cancer cases have demonstrated durable responses from immune checkpoint blockade. To enhance the efficacy of immunotherapies, combination therapies suppressing multiple immune evasion mechanisms are increasingly contemplated. To better understand immune cell surveillance and diverse immune evasion responses in tumor tissues, we comprehensively characterized the immune landscape of more than 1,000 tumors across ten different cancers using CPTAC pan-cancer proteogenomic data. We identified seven distinct immune subtypes based on integrative learning of cell type compositions and pathway activities. We then thoroughly categorized unique genomic, epigenetic, transcriptomic, and proteomic changes associated with each subtype. Further leveraging the deep phosphoproteomic data, we studied kinase activities in different immune subtypes, which revealed potential subtype-specific therapeutic targets. Insights from this work will facilitate the development of future immunotherapy strategies and enhance precision targeting with existing agents.

Original languageEnglish
Pages (from-to)1255-1277.e27
JournalCell
Volume187
Issue number5
DOIs
StatePublished - 29 Feb 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2024 The Author(s)

Funding

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) is supported by the National Cancer Institute of the National Institutes of Health under award numbers U24CA210955 , U24CA210985 , U24CA210986 , U24CA210954 , U24CA210967 , U24CA210972 , U24CA210979 , U24CA210993 , U01CA214114 , U01CA214116 , U01CA214125 , U24CA271114 , and U24CA270823 . This project has also been funded in part with federal funds from the National Cancer Institute of the National Institutes of Health under contract no. HHSN261201500003I , task order no. HHSN26100064 . The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products or organizations imply endorsement by the US Government. Additional funding support was provided by NIH awards U24CA224260 , U24CA264250 , R33CA263705 , P30ES017885 , T32GM136542 , 1F30CA265288 , and F30CA271622 ; HHMI Gilliam Fellowship GT15758 ; and Associazione Italiana Ricerca sul Cancro (AIRC) under IG 2018—ID. 21846 and AIRC 5 per Mille 2018—ID.21073 . The Pacific Northwest National Laboratory is operated for the DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) is supported by the National Cancer Institute of the National Institutes of Health under award numbers U24CA210955, U24CA210985, U24CA210986, U24CA210954, U24CA210967, U24CA210972, U24CA210979, U24CA210993, U01CA214114, U01CA214116, U01CA214125, U24CA271114, and U24CA270823. This project has also been funded in part with federal funds from the National Cancer Institute of the National Institutes of Health under contract no. HHSN261201500003I, task order no. HHSN26100064. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products or organizations imply endorsement by the US Government. Additional funding support was provided by NIH awards U24CA224260, U24CA264250, R33CA263705, P30ES017885, T32GM136542, 1F30CA265288, and F30CA271622; HHMI Gilliam Fellowship GT15758; and Associazione Italiana Ricerca sul Cancro (AIRC) under IG 2018—ID. 21846 and AIRC 5 per Mille 2018—ID.21073. The Pacific Northwest National Laboratory is operated for the DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830. Study conception & design: F.P. and P.W.; supervision, P.W. F.P. M. Ceccarelli, A.M. L.C.C. A.J.L. A.I.R. and Z.H.G.; data analysis, F.P. P.W. A.M. M. Ceccarelli, M. Cieslik, Z.H.G. D.F. R. Sebra, A.I.N. B.R. S.J.C.G. A.I. X.S. K.E.C. W.M. T.M.Y. F.P.C. N.T. J.M.W. D.C. J.L.J. E.M.H. G.B.M. J.E.E. M.E.S. D.R. A.K. R.J.K. D.R.M. X.Y. B.Z. D.A.L. E.Z.D. D.J.B.C. S.S. Y.W. M. Cieslik, M.A.G. R.J.K. Y.L. A.C. M.W. T.J.G.-R. and S.C.; data generation, J.R.W. J.J.K. L.Z. R.L.S. H.B. M.G.R. E.R.P. R. Soundararajan, X.T. A.G.P. and G.H.; writing: F.P. P.W. W.M. T.M.Y. F.P.C. N.T. A.C. J.M.W. J.L.J. A.M. M. Ceccarelli, A.J.L. G.S.O. D.F. Z.H.G. M.A.G. and L.C.C.; visualization, A.C. B.T. Z.H.G. and G.H.; funding acquisition, P.W. A.M. D.F. B.Z. A.I.N. L.C.C. A.G.P. M.G.R. M. Ceccarelli, R. Sebra, and Z.H.G.; all authors contributed to data interpretation, manuscript editing, and revision. R. Sebra is currently a paid consultant and equity holder at GeneDx. L.C.C. is a founder and member of the board of directors of Agios Pharmaceuticals; is a founder and receives research support from Petra Pharmaceuticals; has equity in and consults for Cell Signaling Technologies, Volastra, Larkspur, and 1 Base Pharmaceuticals; and consults for Loxo-Lilly. J.L.J. has received consulting fees from Scorpion Therapeutics and Volastra Therapeutics. T.M.Y. is a co-founder and stockholder of DeStroke. During the preparation of this work the authors used ChatGPT to improve English grammar. After using this tool/service, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication.

FundersFunder number
Clinical Proteomic Tumor Analysis Consortium
National Institutes of HealthU24CA270823, P30ES017885, HHSN261201500003I, U24CA264250, HHSN26100064, U24CA210955, U24CA224260, U24CA210954, U24CA210979, U24CA210967, U24CA210972, 1F30CA265288, R33CA263705, U24CA210986, U24CA210985, F30CA271622, T32GM136542, U24CA210993, U01CA214116, U01CA214114, U01CA214125, U24CA271114
Howard Hughes Medical InstituteGT15758
U.S. Department of Health and Human Services
National Cancer Institute
BattelleDE-AC05-76RL01830
Government of South Australia
Associazione Italiana per la Ricerca sul Cancro21846

    Keywords

    • histopathology
    • immune subtype
    • immunotherapy
    • kinase activity
    • multiomic deconvolution
    • proteogenomics
    • tumor immunity

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