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Quantitative proteomic landscape of metaplastic breast carcinoma pathological subtypes and their relationship to triple-negative tumors

Authors :
Venkatesha Basrur
Celina G. Kleer
Shilpa R. Tekula
Sabra Djomehri
Ashley Cimino-Mathews
Maria E. Gonzalez
Marissa J. White
Alexey I. Nesvizhskii
Boris Burman
Pedram Argani
Hui Yin Chang
Felipe da Veiga Leprevost
Source :
Nature Communications, Vol 11, Iss 1, Pp 1-15 (2020), Nature Communications
Publication Year :
2020
Publisher :
Springer Science and Business Media LLC, 2020.

Abstract

Metaplastic breast carcinoma (MBC) is a highly aggressive form of triple-negative cancer (TNBC), defined by the presence of metaplastic components of spindle, squamous, or sarcomatoid histology. The protein profiles underpinning the pathological subtypes and metastatic behavior of MBC are unknown. Using multiplex quantitative tandem mass tag-based proteomics we quantify 5798 proteins in MBC, TNBC, and normal breast from 27 patients. Comparing MBC and TNBC protein profiles we show MBC-specific increases related to epithelial-to-mesenchymal transition and extracellular matrix, and reduced metabolic pathways. MBC subtypes exhibit distinct upregulated profiles, including translation and ribosomal events in spindle, inflammation- and apical junction-related proteins in squamous, and extracellular matrix proteins in sarcomatoid subtypes. Comparison of the proteomes of human spindle MBC with mouse spindle (CCN6 knockout) MBC tumors reveals a shared spindle-specific signature of 17 upregulated proteins involved in translation and 19 downregulated proteins with roles in cell metabolism. These data identify potential subtype specific MBC biomarkers and therapeutic targets.<br />Metaplastic breast carcinoma (MBC) is among the most aggressive subtypes of triple-negative breast cancer (TNBC) but the underlying proteome profiles are unknown. Here, the authors characterize the protein signatures of human MBC tissue samples and their relationship to TNBC and normal breast tissue.

Details

ISSN :
20411723
Volume :
11
Database :
OpenAIRE
Journal :
Nature Communications
Accession number :
edsair.doi.dedup.....4817f3231f023c2e8f922af94dffdcab