MassIVE MSV000095715

Complete Public PXD055306

Multi-omics analysis of triple-negative breast cancers

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Description

Abstract The triple-negative breast cancer (TNBC) accounts for approximately 15% of all Breast Cancer (BC) cases. However, the prognosis and clinical outcomes of TNBC are worse than those of other BC subtypes due to a greater tumor and few therapeutically targetable oncogenic drivers. Numerous studies have employed genomic and transcriptomic approaches to identify clinically actionable TNBC subtypes in a comprehensive and unbiased manner using. While these analyses have advanced our knowledge of the molecular changes underlying TNBC, their clinical utility remains limited thus far. Given that proteins are the principal effector molecules of cellular signaling and function, we use a proteomic approach to quantitatively compare the abundances of 6,306 proteins across 55 formalin-fixed and paraffin-embedded (FFPE) TNBC tumors to reveal actionable pathways for anti-cancer treatment. We identified four major TNBC clusters by unsupervised clustering analysis of protein abundances. In addition, analyses of clinicopathological characteristics revealed associations between proteomic results and clinical phenotypes exhibited by each subtype. We validate the findings of our proteomics analysis, by inferring immune and stromal cell type composition from genome-wide DNA methylation profiles. Finally, quantitative proteomics on TNBC cell lines was conducted to identify representative in vitro models for each subtype. Collectively, our multi-omics data provide novel subtype-specific insights such as potential biomarkers, molecular drivers, and pharmacologic vulnerabilities for further investigations. [doi:10.25345/C5K35MR6X] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: TNBC, cancer, tumor, subtypes

Contact

Principal Investigators:
(in alphabetical order) 		Arminja Kettenbach, Geisel School of Medicine at Dartmouth, United States
Submitting User: Arminja
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