Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Breast cancer quantitative proteome and proteogenomic landscape
Karolinska Inst, Dept Oncol Pathol, Sci Life Lab, S-17121 Solna, Sweden.ORCID iD: 0000-0003-4729-4205
Karolinska Inst, Dept Oncol Pathol, Sci Life Lab, S-17121 Solna, Sweden.
Karolinska Inst, Dept Oncol Pathol, Sci Life Lab, S-17121 Solna, Sweden;Cornell Univ, Div Nutrit Sci, Ithaca, NY 14853 USA.
Oslo Univ Hosp, Inst Canc Res, Dept Tumor Biol, N-0424 Oslo, Norway;Oslo Univ Hosp, Inst Canc Res, Dept Canc Genet, N-0424 Oslo, Norway.
Show others and affiliations
2019 (English)In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 10, article id 1600Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP , 2019. Vol. 10, article id 1600
National Category
Cancer and Oncology
Identifiers
URN: urn:nbn:se:uu:diva-398666DOI: 10.1038/s41467-019-09018-yISI: 000463695400015PubMedID: 30962452OAI: oai:DiVA.org:uu-398666DiVA, id: diva2:1379656
Funder
Swedish Research CouncilSwedish Cancer SocietySwedish Foundation for Strategic Research Knut and Alice Wallenberg FoundationAvailable from: 2019-12-17 Created: 2019-12-17 Last updated: 2019-12-17Bibliographically approved

Open Access in DiVA

fulltext(3915 kB)11 downloads
File information
File name FULLTEXT01.pdfFile size 3915 kBChecksum SHA-512
567d57f0a627d315331c77b05a86e85dbcd6d5c282aa473980b3e2dba919b0c28eb4c578bfa1e60a3e56237e5f42524b188dbda94226d3320a640a4bf0429a05
Type fulltextMimetype application/pdf

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Johansson, Henrik J.Fernandez-Woodbridge, AlejandroSennblad, BengtVesterlund, MattiasOrre, Lukas M.Huss, Mikael
By organisation
Molecular EvolutionScience for Life Laboratory, SciLifeLab
In the same journal
Nature Communications
Cancer and Oncology

Search outside of DiVA

GoogleGoogle Scholar
Total: 11 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 10 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf