Dataset Information

Validation dataset on tamoxifen treated Estrogen Receptor (ER) positive breast cancer patients

ABSTRACT: 56 Estrogen Receptor Positive Breast cancer tissues coming from patients treated with tamoxifen upon recurrence (41 Good outcome vs 15 Poor outcome) have been microdissected to enrich for breast cancer tumor cells. Enriched tissue has been lysed and proteins digested and analyzed in an LTQ-Orbitrap coupled online with a Dionex nLC system. Thermo output .RAW files were analyzed through MaxQuant (version 1.4.1.2) using the human proteome FASTA (version 2012-09, human canonical proteome) as search library. LFQ parameters in MaxQuant have been enabled (Fast LFQ) and other settings have been kept as default.

INSTRUMENT(S): LTQ Orbitrap

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Tommaso De Marchi

PROVIDER: PXD000485 | Pride | 2015-08-21

REPOSITORIES: Pride

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Publications

4-protein signature predicting tamoxifen treatment outcome in recurrent breast cancer.

De Marchi Tommaso T Liu Ning Qing NQ Stingl Cristoph C Timmermans Mieke A MA Smid Marcel M Look Maxime P MP Tjoa Mila M Braakman Rene B H RB Opdam Mark M Linn Sabine C SC Sweep Fred C G J FC Span Paul N PN Kliffen Mike M Luider Theo M TM Foekens John A JA Martens John W M JW Umar Arzu A

Molecular oncology 20150807 1

Estrogen receptor (ER) positive tumors represent the majority of breast malignancies, and are effectively treated with hormonal therapies, such as tamoxifen. However, in the recurrent disease resistance to tamoxifen therapy is common and a major cause of death. In recent years, in-depth proteome analyses have enabled identification of clinically useful biomarkers, particularly, when heterogeneity in complex tumor tissue was reduced using laser capture microdissection (LCM). In the current study, ...[more]

PMID: 26285647

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Project description:Proteomic sample preparation typically involves multi-step workflows that can potentially perturb the biological system under analysis. These datasets were used to demonstrate that the entire processing pipeline, from cell lysis through elution of purified peptides, can be performed in a single, enclosed volume. This in-StageTip sample preparation method largely eliminates contamination or losses and is extremely robust and scalable. Peptides can be eluted in several fractions or in one step for single-run proteomics. In one day of gradient time we obtained the largest proteomes for budding and fission yeast to date. Applying the in-StageTip method to quadruplicate measurements of a human cell line yielded copy number estimates for more than 9000 human proteins. Data Analysis: MS raw files were analyzed by MaxQuant software (version 1.3.10.12) and peak lists were searched either against the human Uniprot FASTA database version 2/25/2012 (81213 entries), against the S. cerevisiae Uniprot FASTA database version 2/25/2012 (6649 entries) or the SGD based S. cerevisiae Fasta database orf_trans.20100105 (5904 entries), or against the S. pombe Uniprot FASTA database version 4/2/2013 (5096 entries) or pompep FASTA database version 4/2/2013 (5031 entries) and a common contaminants database (247 entries) by Andromeda search engine with cysteine carbamidomethylation as a fixed modification and N-terminal acetylation and methionine oxidation as variable modifications. False discovery rate (FDR) was set to 0.01 for proteins and peptides (minimum length of 7 amino acids) and was determined by searching a reverse database. Enzyme specificity was set as C-terminal to Arg and Lys, and a maximum of 2 miscleavages allowed. Peptide identification was performed with an allowed initial precursor mass deviation up to 7 ppm and an allowed fragment mass deviation 20 ppm. Quantification of SILAC pairs was carried out by MaxQuant with standard settings and without the re-quantification option.

Dataset Information

Validation dataset on tamoxifen treated Estrogen Receptor (ER) positive breast cancer patients

Publications

4-protein signature predicting tamoxifen treatment outcome in recurrent breast cancer.

Similar Datasets

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