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dc.contributor.authorJohansson, Henrik J.
dc.contributor.authorSocciarelli, Fabio
dc.contributor.authorVacanti, Nathaniel M.
dc.contributor.authorHaugen, Mads Haugland
dc.contributor.authorZhu, Yafeng
dc.contributor.authorSiavelis, Ioannis
dc.contributor.authorFernandez-Woodbridge, Alejandro
dc.contributor.authorAure, Miriam Ragle
dc.contributor.authorSennblad, Bengt
dc.contributor.authorVesterlund, Mattias
dc.contributor.authorBranca, Rui M.
dc.contributor.authorOrre, Lukas M.
dc.contributor.authorHuss, Mikael
dc.contributor.authorFredlund, Erik
dc.contributor.authorBeraki, Else
dc.contributor.authorGarred, Øystein
dc.contributor.authorBoekel, Jorrit
dc.contributor.authorSauer, Torill
dc.contributor.authorZhao, Wei
dc.contributor.authorNord, Silje
dc.contributor.authorHöglander, Elen K.
dc.contributor.authorJans, Daniel C.
dc.contributor.authorBrismar, Hjalmar
dc.contributor.authorHaukaas, Tonje Husby
dc.contributor.authorBathen, Tone Frost
dc.contributor.authorSchlichting, Ellen
dc.contributor.authorNaume, Bjørn
dc.contributor.authorLuders, Torben
dc.contributor.authorBorgen, Elin
dc.contributor.authorKristensen, Vessela N.
dc.contributor.authorRussnes, Hege Elisabeth Giercksky
dc.contributor.authorLingjærde, Ole Christian
dc.contributor.authorMills, Gordon B.
dc.contributor.authorSahlberg, Kristine Kleivi
dc.contributor.authorBørresen-Dale, Anne-Lise
dc.contributor.authorLehtiö, Janne
dc.identifier.citationNature Researchnb_NO
dc.description.abstractIn 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.nb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.titleBreast cancer quantitative proteome and proteogenomic landscapenb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.source.journalNature Communicationsnb_NO
dc.description.localcode© The Author(s) 2019. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit licenses/by/4.0/.nb_NO
cristin.unitnameInstitutt for sirkulasjon og bildediagnostikk

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