Clinical proteomics of breast cancer reveals a novel layer of breast cancer classification

Gali Yanovich, Hadar Agmon, Michal Harel, Amir Sonnenblick, Tamar Peretz, Tamar Geiger*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Breast cancer classification has been the focus of numerous worldwide efforts, analyzing the molecular basis of breast cancer subtypes and aiming to associate them with clinical outcome and to improve the current diagnostic routine. Genomic and transcriptomic profiles of breast cancer have been well established, however the proteomic contribution to these profiles has yet to be elucidated. In this work, we utilized mass spectrometry-based proteomic analysis on more than 130 clinical breast samples to demonstrate intertumor heterogeneity across three breast cancer subtypes and healthy tissue. Unsupervised analysis identified four proteomic clusters, among them, one that represents a novel luminal subtype characterized by increased PI3K signaling. This subtype was further validated using an independent protein-based dataset, but not in two independent transcriptome cohorts. These results demonstrate the importance of deep proteomic analysis, which may affect cancer treatment decision making.

Original languageEnglish
Pages (from-to)6001-6010
Number of pages10
JournalCancer Research
Issue number20
StatePublished - 15 Oct 2018


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