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Breast cancer quantitative proteome and proteogenomic landscape.

ABSTRACT: 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.

SUBMITTER: Johansson HJ

PROVIDER: S-EPMC6453966 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Karsten Krug, Eric J. Jaehnig, Shankha Satpathy, Lili Blumenberg, Alla Karpova, Meenakshi Anurag et al., (2020) <a href="https://www.cell.com/cell/fulltext/S0092-8674(20)31400-8" target="_blank">Cell, 183, 1436-1456</a> DOI: https://doi.org/10.1016/j.cell.2020.10.036 The integration of mass spectrometry-based proteomics with next-generation DNA and RNA sequencing profiles tumors more comprehensively. Herein this "proteogenomic" approach was applied to 122 treatment-naive primary breast cancers purposely accrued to preserve post-translational modifications, including protein phosphorylation and acetylation. Proteogenomics challenged standard breast cancer diagnoses, provided detailed analysis of the ERBB2 amplicon, defined tumor subsets that could benefit from immune checkpoint therapy and allowed more accurate assessment of Rb status for the prediction of CDK4/6 inhibitor responsiveness. Phosphoproteomic profiles uncovered novel associations between tumor suppressor loss and targetable kinases. Acetylproteome analysis highlighted acetylation on key nuclear proteins involved in the DNA damage response and revealed cross-talk between cytoplasmic and mitochondrial acetylation and metabolism. Our results underscore the potential of proteogenomics for the clinical investigation of breast cancer through more accurate annotation of targetable pathways and biological features of this remarkably heterogeneous malignancy.Genomic Data for Breast Cancer tumors is available from the NCI Genomic Data Commons (GDC), <a href="https://portal.gdc.cancer.gov/projects/CPTAC-2" target="_blank">here</a> Gene Expression data in GCT file format is available under the metadata section below Proteomic Data Analysis for Breast Cancer tumors (PSMs and Summary Reports) is available from the CPTAC Common Data Analysis Pipeline (Study S039 Early Data Release), <a href="/study-summary/S039" target="_blank">here</a> <ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/study-summary/S060">https://cptac-data-portal.georgetown.edu/study-summary/S060</a> on 06/05/21</li></ul>

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Breast cancer quantitative proteome and proteogenomic landscape.

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