TY - JOUR
T1 - Breast cancer quantitative proteome and proteogenomic landscape
AU - Consortia Oslo Breast Cancer Research Consortium (OSBREAC)
AU - Johansson, Henrik J.
AU - Socciarelli, Fabio
AU - Vacanti, Nathaniel M.
AU - Haugen, Mads H.
AU - Zhu, Yafeng
AU - Siavelis, Ioannis
AU - Fernandez-Woodbridge, Alejandro
AU - Aure, Miriam R.
AU - Sennblad, Bengt
AU - Vesterlund, Mattias
AU - Branca, Rui M.
AU - Orre, Lukas M.
AU - Huss, Mikael
AU - Fredlund, Erik
AU - Beraki, Elsa
AU - Garred, Øystein
AU - Boekel, Jorrit
AU - Sauer, Torill
AU - Zhao, Wei
AU - Nord, Silje
AU - Höglander, Elen K.
AU - Jans, Daniel C.
AU - Brismar, Hjalmar
AU - Haukaas, Tonje H.
AU - Bathen, Tone F.
AU - Schlichting, Ellen
AU - Naume, Bjørn
AU - Geisler, Jürgen
AU - Hofvind, Solveig
AU - Engebråten, Olav
AU - Geitvik, Gry Aarum
AU - Langerød, Anita
AU - Kåresen, Rolf
AU - Mælandsmo, Gunhild Mari
AU - Sørlie, Therese
AU - Skjerven, Helle Kristine
AU - Park, Daehoon
AU - Hartman-Johnsen, Olaf Johan
AU - Luders, Torben
AU - Borgen, Elin
AU - Kristensen, Vessela N.
AU - Russnes, Hege G.
AU - Lingjærde, Ole Christian
AU - Mills, Gordon B.
AU - Sahlberg, Kristine K.
AU - Børresen-Dale, Anne Lise
AU - Lehtiö, Janne
N1 - Publisher Copyright:
© 2019, The Author(s).
PY - 2019/12/1
Y1 - 2019/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85064079271&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85064079271&partnerID=8YFLogxK
U2 - 10.1038/s41467-019-09018-y
DO - 10.1038/s41467-019-09018-y
M3 - Article
C2 - 30962452
AN - SCOPUS:85064079271
SN - 2041-1723
VL - 10
JO - Nature communications
JF - Nature communications
IS - 1
M1 - 1600
ER -