Dataset Information

HiRIEF deep proteomics of A431 human vulvar cancer cell line and N2A mouse neuroblastoma cell line

ABSTRACT: Here we present high resolution data from two cancer cell lines. A human cell line, A431 was treated with a drug at different time points and then fractionated into its different subcellular compartments (nuclear, organellar, soluble,whole cell). Protein extracts were trypsinized, peptides separated by HiRIEF (high resolution isoelectric focusing) and analysed by LC-MS. From the mouse cell line N2A proteins were extracted and subjected to the same HiRIEF-LC-MS procedure. All MS/MS spectra were searched by Sequest/Percolator under the software platform Proteome Discoverer (PD, v1.3.0.339, Thermo Scientific) using a target-decoy strategy. The reference databases used were the human protein subset of Ensembl 63 and the mouse protein subset of Ensembl 64. Precursor mass tolerance of 10 ppm and product mass tolerances of 0.02 Da for HCD-FTMS and 0.8 Da for CID-ITMS were used. Additional settings were: trypsin with 1 missed cleavage; Lys-Pro and Arg-Pro not considered as cleavage sites; carbamidomethylation on cysteine and iTRAQ-8plex on lysine and N-terminal as fixed modifications; and oxidation of methionine and phosphorylation on serine, threonine or tyrosine as variable modifications. Quantitation of iTRAQ-8plex reporter ions was done using an integration window tolerance of 20ppm. Peptides found at 1% FDR (false discovery rate) were used by the protein grouping algorithm in PD to infer protein identities.

OTHER RELATED OMICS DATASETS IN: MSV000079945

INSTRUMENT(S): LTQ Orbitrap

ORGANISM(S): Homo Sapiens (human) Mus Musculus (mouse)

SUBMITTER: Rui Branca

PROVIDER: PXD000065 | Pride | 2013-09-27

REPOSITORIES: Pride

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Publications

HiRIEF LC-MS enables deep proteome coverage and unbiased proteogenomics.

Branca Rui M M RM Orre Lukas M LM Johansson Henrik J HJ Granholm Viktor V Huss Mikael M Pérez-Bercoff Åsa Å Forshed Jenny J Käll Lukas L Lehtiö Janne J

Nature methods 20131117 1

We present a liquid chromatography-mass spectrometry (LC-MS)-based method permitting unbiased (gene prediction-independent) genome-wide discovery of protein-coding loci in higher eukaryotes. Using high-resolution isoelectric focusing (HiRIEF) at the peptide level in the 3.7-5.0 pH range and accurate peptide isoelectric point (pI) prediction, we probed the six-reading-frame translation of the human and mouse genomes and identified 98 and 52 previously undiscovered protein-coding loci, respectivel ...[more]

PMID: 24240322

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Project description:About one-third of oestrogen receptor alpha- positive breast cancer patients treated with tamoxifen relapse. Here we identify the nuclear receptor retinoic acid receptor alpha as a marker of tamoxifen resistance. Using quantitative mass spectrometry-based proteomics, we show that retinoic acid receptor alpha protein networks and levels differ in a tamoxifen-sensitive (MCF7) and a tamoxifen-resistant (LCC2) cell line. High intratumoural retinoic acid receptor alpha protein levels also correlate with reduced relapse-free survival in oestrogen receptor alpha-positive breast cancer patients treated with adjuvant tamoxifen solely. A similar retinoic acid receptor alpha expression pattern is seen in a comparable independent patient cohort. An oestrogen receptor alpha and retinoic acid receptor alpha ligand screening reveals that tamoxifen-resistant LCC2 cells have increased sensitivity to retinoic acid receptor alpha ligands and are less sensitive to oestrogen receptor alpha ligands compared with MCF7 cells. Our data indicate that retinoic acid receptor alpha may be a novel therapeutic target and a predictive factor for oestrogen receptor alpha-positive breast cancer patients treated with adjuvant tamoxifen. Peptide and protein identification data set 1: Peptide identification from the MALDI-TOF/TOF data was carried out using the Paragon algorithm in the ProteinPilot 2.0 software package (Applied Biosystems) 46. Default settings for a 4800 instrument were used (i.e., no manual settings for mass tolerance was given). The following parameters were selected in the analysis method: iTRAQ 4plex peptide labelled as sample type, MMTS as alkylating agent of cysteine, trypsin as digesting enzyme, 4800 as instrument, gel based ID and Urea denaturation as special factors, biological modifications as ID focus, and thorough ID as search effort. Peptide identification from the Q-TOF data was carried out using the Spectrum Mill Protein Identification software (Agilent). Data was extracted between MH+ 600 and 4000 Da (Agilent's definition). Scans with the same precursor m/z 90 sec, 0.05 m/z matching with a minimum of 20 peaks in MS2 were merged. Peptide and protein identification data set 2: Proteome discoverer 1.3 with sequest-percolator was used for protein identification. Precursor mass tolerance was set to 10 ppm and for fragments 0.8 Da and 0.02 Da were used for detection in the linear iontrap and the orbitrap, respectively. Oxidized methionine and phosphorylation on S,T and Y was set as dynamic modifications, and carbamidomethylation, N-terminal 8plex iTRAQ, and lysyl 8plex iTRAQ as fixed modifications. Spectra were matched to ensembl 68 limited to human protein sequences, and results were filtered to 1% FDR.

Dataset Information

HiRIEF deep proteomics of A431 human vulvar cancer cell line and N2A mouse neuroblastoma cell line

Publications

HiRIEF LC-MS enables deep proteome coverage and unbiased proteogenomics.

Similar Datasets

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