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Proteogenomic Workflow Reveals Molecular Phenotypes Related to Breast Cancer Mammographic Appearance
Author(s) -
Tommaso De Marchi,
Paul Theodor Pyl,
Martin Sjöström,
Stina Klasson,
Hanna Sartor,
Lena Tran,
Gyula Pekár,
Johan Malmström,
Lars Malmström,
Emma Niméus
Publication year - 2021
Publication title -
journal of proteome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.644
H-Index - 161
eISSN - 1535-3907
pISSN - 1535-3893
DOI - 10.1021/acs.jproteome.1c00243
Subject(s) - phenotype , proteogenomics , breast cancer , computational biology , cancer , biology , workflow , medicine , pathology , computer science , genetics , genomics , gene , genome , database
Proteogenomic approaches have enabled the generat̲ion of novel information levels when compared to single omics studies although burdened by extensive experimental efforts. Here, we improved a data-independent acquisition mass spectrometry proteogenomic workflow to reveal distinct molecular features related to mammographic appearances in breast cancer. Our results reveal splicing processes detectable at the protein level and highlight quantitation and pathway complementarity between RNA and protein data. Furthermore, we confirm previously detected enrichments of molecular pathways associated with estrogen receptor-dependent activity and provide novel evidence of epithelial-to-mesenchymal activity in mammography-detected spiculated tumors. Several transcript-protein pairs displayed radically different abundances depending on the overall clinical properties of the tumor. These results demonstrate that there are differentially regulated protein networks in clinically relevant tumor subgroups, which in turn alter both cancer biology and the abundance of biomarker candidates and drug targets.

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