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Breast cancer quantitative proteome and proteogenomic landscape

Author

Listed:
  • Henrik J. Johansson

    (Karolinska Institutet)

  • Fabio Socciarelli

    (Karolinska Institutet)

  • Nathaniel M. Vacanti

    (Karolinska Institutet
    Cornell University, Division of Nutritional Sciences)

  • Mads H. Haugen

    (Oslo University Hospital)

  • Yafeng Zhu

    (Karolinska Institutet)

  • Ioannis Siavelis

    (Karolinska Institutet)

  • Alejandro Fernandez-Woodbridge

    (Karolinska Institutet)

  • Miriam R. Aure

    (Oslo University Hospital)

  • Bengt Sennblad

    (Uppsala University)

  • Mattias Vesterlund

    (Karolinska Institutet)

  • Rui M. Branca

    (Karolinska Institutet)

  • Lukas M. Orre

    (Karolinska Institutet)

  • Mikael Huss

    (Stockholm University)

  • Erik Fredlund

    (Karolinska Institutet)

  • Elsa Beraki

    (Oslo University Hospital)

  • Øystein Garred

    (Oslo University Hospital)

  • Jorrit Boekel

    (Karolinska Institutet)

  • Torill Sauer

    (Akershus University Hospital
    University of Oslo)

  • Wei Zhao

    (The University of Texas MD Anderson Cancer Center)

  • Silje Nord

    (Oslo University Hospital)

  • Elen K. Höglander

    (Oslo University Hospital)

  • Daniel C. Jans

    (KTH Royal Institute of Technology)

  • Hjalmar Brismar

    (KTH Royal Institute of Technology
    Karolinska Institutet)

  • Tonje H. Haukaas

    (The Norwegian University of Science and Technology – NTNU)

  • Tone F. Bathen

    (The Norwegian University of Science and Technology – NTNU)

  • Ellen Schlichting

    (Oslo University Hospital)

  • Bjørn Naume

    (University of Oslo
    Oslo University Hospital)

  • Torben Luders

    (University of Oslo
    Akershus University Hospital)

  • Elin Borgen

    (Oslo University Hospital)

  • Vessela N. Kristensen

    (Oslo University Hospital
    University of Oslo
    Akershus University Hospital)

  • Hege G. Russnes

    (Oslo University Hospital)

  • Ole Christian Lingjærde

    (Oslo University Hospital
    University of Oslo)

  • Gordon B. Mills

    (The University of Texas MD Anderson Cancer Center)

  • Kristine K. Sahlberg

    (Oslo University Hospital
    Vestre Viken Hospital Trust)

  • Anne-Lise Børresen-Dale

    (Oslo University Hospital
    University of Oslo)

  • Janne Lehtiö

    (Karolinska Institutet)

Abstract

In the preceding decades, molecular characterization has revolutionized breast cancer (BC) research and therapeutic approaches. Presented herein, an unbiased analysis of breast tumor proteomes, inclusive of 9995 proteins quantified across all tumors, for the first time recapitulates BC subtypes. Additionally, poor-prognosis basal-like and luminal B tumors are further subdivided by immune component infiltration, suggesting the current classification is incomplete. Proteome-based networks distinguish functional protein modules for breast tumor groups, with co-expression of EGFR and MET marking ductal carcinoma in situ regions of normal-like tumors and lending to a more accurate classification of this poorly defined subtype. Genes included within prognostic mRNA panels have significantly higher than average mRNA-protein correlations, and gene copy number alterations are dampened at the protein-level; underscoring the value of proteome quantification for prognostication and phenotypic classification. Furthermore, protein products mapping to non-coding genomic regions are identified; highlighting a potential new class of tumor-specific immunotherapeutic targets.

Suggested Citation

  • Henrik J. Johansson & Fabio Socciarelli & Nathaniel M. Vacanti & Mads H. Haugen & Yafeng Zhu & Ioannis Siavelis & Alejandro Fernandez-Woodbridge & Miriam R. Aure & Bengt Sennblad & Mattias Vesterlund , 2019. "Breast cancer quantitative proteome and proteogenomic landscape," Nature Communications, Nature, vol. 10(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-09018-y
    DOI: 10.1038/s41467-019-09018-y
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    Cited by:

    1. Sophie A. Herbst & Mattias Vesterlund & Alexander J. Helmboldt & Rozbeh Jafari & Ioannis Siavelis & Matthias Stahl & Eva C. Schitter & Nora Liebers & Berit J. Brinkmann & Felix Czernilofsky & Tobias R, 2022. "Proteogenomics refines the molecular classification of chronic lymphocytic leukemia," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    2. Masashi Fujita & Mei-Ju May Chen & Doris Rieko Siwak & Shota Sasagawa & Ayako Oosawa-Tatsuguchi & Koji Arihiro & Atsushi Ono & Ryoichi Miura & Kazuhiro Maejima & Hiroshi Aikata & Masaki Ueno & Shinya , 2022. "Proteo-genomic characterization of virus-associated liver cancers reveals potential subtypes and therapeutic targets," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    3. Karama Asleh & Gian Luca Negri & Sandra E. Spencer Miko & Shane Colborne & Christopher S. Hughes & Xiu Q. Wang & Dongxia Gao & C. Blake Gilks & Stephen K. L. Chia & Torsten O. Nielsen & Gregg B. Morin, 2022. "Proteomic analysis of archival breast cancer clinical specimens identifies biological subtypes with distinct survival outcomes," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    4. Jennifer G. Abelin & Erik J. Bergstrom & Keith D. Rivera & Hannah B. Taylor & Susan Klaeger & Charles Xu & Eva K. Verzani & C. Jackson White & Hilina B. Woldemichael & Maya Virshup & Meagan E. Olive &, 2023. "Workflow enabling deepscale immunopeptidome, proteome, ubiquitylome, phosphoproteome, and acetylome analyses of sample-limited tissues," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
    5. Yuanyuan Qu & Jinwen Feng & Xiaohui Wu & Lin Bai & Wenhao Xu & Lingli Zhu & Yang Liu & Fujiang Xu & Xuan Zhang & Guojian Yang & Jiacheng Lv & Xiuping Chen & Guo-Hai Shi & Hong-Kai Wang & Da-Long Cao &, 2022. "A proteogenomic analysis of clear cell renal cell carcinoma in a Chinese population," Nature Communications, Nature, vol. 13(1), pages 1-21, December.
    6. Kang Wang & Ioannis Zerdes & Henrik J. Johansson & Dhifaf Sarhan & Yizhe Sun & Dimitris C. Kanellis & Emmanouil G. Sifakis & Artur Mezheyeuski & Xingrong Liu & Niklas Loman & Ingrid Hedenfalk & Jonas , 2024. "Longitudinal molecular profiling elucidates immunometabolism dynamics in breast cancer," Nature Communications, Nature, vol. 15(1), pages 1-24, December.
    7. Isabelle Rose Leo & Luay Aswad & Matthias Stahl & Elena Kunold & Frederik Post & Tom Erkers & Nona Struyf & Georgios Mermelekas & Rubin Narayan Joshi & Eva Gracia-Villacampa & Päivi Östling & Olli P. , 2022. "Integrative multi-omics and drug response profiling of childhood acute lymphoblastic leukemia cell lines," Nature Communications, Nature, vol. 13(1), pages 1-19, December.

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