Dataset Information

Clinical Proteomics of Breast Cancer Unravels a Novel Layer of Breast Cancer Classification

ABSTRACT: Breast cancer classification has been in the focus of numerous large worldwide efforts, analyzing the molecular basis of breast cancer subtypes, aiming to associate them with clinical outcome and improve the current diagnostic routine. Genomic and transcriptomic profiles of breast cancer have been well established, however the proteomic contribution to these profiles is yet to be elucidated. In this work, we examined inter-tumor heterogeneity by performing a mass-spectrometry (MS)-based proteomic analysis of more than 130 clinical breast samples originating from 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 cancer signaling. This subtype was further validated using an independent protein-based dataset, but not in two independent transcriptome cohorts. Altogether, our results demonstrate the importance of deep proteomic analysis, which may affect cancer treatment decision making.

INSTRUMENT(S): Q Exactive Plus, Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Breast Cancer Cell

DISEASE(S): Breast Cancer

SUBMITTER: Tamar Geiger

LAB HEAD: Tamar Geiger

PROVIDER: PXD009766 | Pride | 2019-07-29

REPOSITORIES: Pride

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			Action	DRS
	20130117_TG_HADAR_BC46_1.raw	Raw
	20130117_TG_HADAR_BC46_2.raw	Raw
	20130117_TG_HADAR_BC46_3.raw	Raw
	20130117_TG_HADAR_BC46_4.raw	Raw
	20130117_TG_HADAR_BC46_5.raw	Raw

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Clinical Proteomics of Breast Cancer Reveals a Novel Layer of Breast Cancer Classification.

Yanovich Gali G Agmon Hadar H Harel Michal M Sonnenblick Amir A Peretz Tamar T Geiger Tamar T

Cancer research 20180828 20

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 sampl ...[more]

PMID: 30154156

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