Dataset Information

Proteomic portrait of human breast cancer progression identifies novel prognostic markers

ABSTRACT: Triplicate analysis of eleven breast cancer cell lines, each separated to 12 offgel fractions. Proteomes were quantified relative to heavy SILAC-labeled MCF7 cells that served as a spike-in standard. In this study, we used system-wide analysis of breast cancer proteomes to identify proteins that are associated with the progression of ER(-) tumors. Our two-step approach included an initial deep analysis of cultured cells that were obtained from tumors of defined breast cancer stages, followed by a validation set using human breast tumors. Using high-resolution mass spectrometry and quantification by Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC), we identified 8,750 proteins and quantified 7,800 of them. A stage-specific signature was extracted and validated by mass spectrometry and immunohistochemistry on tissue microarrays. Data analysis: Raw MS files from the LTQ-Orbitrap were analyzed by MaxQuant (version 1.1.1.9). MS/MS spectra were searched against the decoy IPI-human database version 3.68 containing both forward and reverse protein sequences by the Andromeda search engine. For identification, the false discovery rate (FDR) was set to 0.01 on the protein and on the peptide levels.

REANALYSED by: PAe004809

INSTRUMENT(S): LTQ Orbitrap

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Mario Oroshi

LAB HEAD: Mario Oroshi

PROVIDER: PXD000309 | Pride | 2013-07-02

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	20080314_TG_Orbi2_HMEpC_01.RAW	Raw
	20080314_TG_Orbi2_HMEpC_02.RAW	Raw
	20080314_TG_Orbi2_HMEpC_03.RAW	Raw
	20080314_TG_Orbi2_HMEpC_04.RAW	Raw
	20080314_TG_Orbi2_HMEpC_05.RAW	Raw

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Publications

Proteomic portrait of human breast cancer progression identifies novel prognostic markers.

Geiger Tamar T Madden Stephen F SF Gallagher William M WM Cox Juergen J Mann Matthias M

Cancer research 20120313 9

Breast cancer is the second leading cause of cancer death for women in the United States. Of the different subtypes, estrogen receptor-negative (ER(-)) tumors, which are ErbB2+ or triple-negative, carry a relatively poor prognosis. In this study, we used system-wide analysis of breast cancer proteomes to identify proteins that are associated with the progression of ER(-) tumors. Our two-step approach included an initial deep analysis of cultured cells that were obtained from tumors of defined br ...[more]

PMID: 22414580

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