Dataset Information

System-level analysis of cancer and stomal cell specific proteomes reveals extensive reprogramming of phosphorylation networks by tumor microenvironment

ABSTRACT: DLD-1 cells and mouse were treated with DMSO, GDC0941 and CAL101 for 2 hours. Proteins were digested with trypsin and phospho peptides were enriched using TiO2. Enriched phosphopeptides and peptides were analysed by LTQ Orbitrap Velos mass spectrometer. (MS/MS data were converted to mgf files using Mascot Distiller (version 2.2) and searched against the UniProt-TrEMBL and UniProt SwissProt databases (release March 2012) and a decoy database using the Mascot search engine (version 2.2). The data was searched twice, restricting searches against human or mouse specific sequences in each separate search. For phosphoproteomics, tolerance windows were 3 p.p.m. and 600 mmu for parent and fragment ions, respectively. For proteomics, these were 5 p.p.m. and 50 mmu for parent and fragment ions, respectively. Allowed variable modifications were methionine oxidation, pyroglutamate at the N-terminus and phosphorylation of serine, threonine and tyrosine residues. Significance of peptide identification was assessed by comparing results returned by searches against random and forward databases. The probability of correct phosphorylation site assignment was determined by the Mascot delta score approach. Ambiguous phosphorylation site assignments are reported as gene name followed by start and end of the amino acid sequence

INSTRUMENT(S): LTQ Orbitrap, instrument model

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

TISSUE(S): Epithelial Cell, Colon

SUBMITTER: Vinothini Rajeeve

PROVIDER: PXD000218 | Pride | 2014-04-02

REPOSITORIES: Pride

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Publications

Cross-species proteomics reveals specific modulation of signaling in cancer and stromal cells by phosphoinositide 3-kinase (PI3K) inhibitors.

Rajeeve Vinothini V Vendrell Iolanda I Wilkes Edmund E Torbett Neil N Cutillas Pedro R PR

Molecular & cellular proteomics : MCP 20140319 6

The tumor microenvironment plays key roles in cancer biology, but its impact on the regulation of signaling pathway activity in cancer cells has not been systemically investigated. We designed an analytical strategy that allows differential analysis of signaling between cancer and stromal cells present in tumor xenografts. We used this approach to investigate how in vivo growth conditions and PI3K inhibitors regulate pathway activities in both cancer and stromal cell populations. We found that, ...[more]

PMID: 24648465

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Project description:The purpose of this study was to generate a basis for the decision of what protein quantities are reliable and find a way for accurate and precise protein quantification. To investigate this we have used thousands of peptide measurements to estimate variance and bias for quantification by iTRAQ (isobaric tags for relative and absolute quantification) mass spectrometry in complex human samples. A549 cell lysate was mixed in the proportions 2:2:1:1:2:2:1:1, fractionated by high resolution isoelectric focusing and liquid chromatography and analyzed by three mass spectrometry platforms; LTQ Orbitrap Velos, 4800 MALDI-TOF/TOF and 6530 Q-TOF. We have investigated how variance and bias in the iTRAQ reporter ions data are affected by common experimental variables such as sample amount, sample fractionation, fragmentation energy, and instrument platform. Based on this, we have suggested a concept for experimental design and a methodology for protein quantification. By using duplicate samples in each run, each experiment is validated based on its internal experimental variation. The duplicates are used for calculating peptide weights, unique to the experiment, which is used in the protein quantification. By weighting the peptides depending on reporter ion intensity, we can decrease the relative error in quantification at the protein level and assign a total weight to each protein that reflects the protein quantitation confidence. We also demonstrate the usability of this methodology in a cancer cell line experiment as well as in a clinical data set of lung cancer tissue samples. In conclusion, we have in this study developed a methodology for improved protein quantification in shotgun proteomics and introduced a way to assess quantification for proteins with few peptides. The experimental design and developed algorithms decreased the relative protein quantification error in the analysis of complex biological samples. Data analysis: LTQ Orbitrap Velos Proteome discoverer 1.1 with Mascot 2.2 (Matrix Science) was used for protein identification. Precursor mass tolerance was set to 10 ppm and for fragments 0.8 Da and 0.015 Da were used for detection in the linear iontrap and the orbitrap, respectively. Oxidized methionine was set as dynamic modification and carbamidomethylation, N-terminal 8plex iTRAQ, and lysyl 8plex iTRAQ as fixed modifications. 4800 MALDI TOF/TOF Peptide identification from the Maldi-TOF/TOF data was carried out using the Paragon algorithm in the ProteinPilot 2.0 software package (Applied Biosystems). 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 8plex peptide labeled as sample type, IAA 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. 6530 QTOF Peptide identification from the QTOF data was carried out using the Spectrum Mill Protein Identification software (Agilent). Data was extracted between MH+ 600 and 4000 Da (Agilent’s definition). Trypsin was used as digesting enzyme, and parent and daughter ion tolerance was set to 25 and 50 ppm, respectively. IAA for cysteine and iTRAQ partial-mix (N-term, K) were set as fixed modifications while oxidized methionine was set as variable modification. Database and peptide cut-off for all searches Searches were performed against the IPI database (build 3.64) limited to human sequences allowing 2 missed cleavages. False discovery rate (FDR) was estimated by searching the data against a database consisting of both forward and reversed sequences and set to < 1 % at the protein level using MAYU. Peptides corresponding to a <1% protein FDR rate was used in the calculations. Peptide and protein identification using Mascot for comparison between instruments Peptide identifications were performed using Mascot Daemon 2.3.2 with Mascot 2.4 for fractions 32 to 36 from IPG-IEF with 400 ug loaded peptides. Carbamidomethylation (CAM) for cysteine was set as fixed modification, oxidized methionine as variable modification and iTRAQ 8plex was set as quantification for all searches. MALDI-TOF/TOF search settings: Parent and daughter ion tolerance was set to 150 ppm and 0.2 Da, respectively. LTQ Orbitrap search settings: Precursor mass tolerance was set to 10 ppm and for fragments 0.8 Da and 0.015 Da were used for data generated in the linear ion trap and the orbitrap, respectively. QTOF search settings: Parent and daughter ion tolerance was set to 25 and 50 ppm, respectively.

Dataset Information

System-level analysis of cancer and stomal cell specific proteomes reveals extensive reprogramming of phosphorylation networks by tumor microenvironment

Publications

Cross-species proteomics reveals specific modulation of signaling in cancer and stromal cells by phosphoinositide 3-kinase (PI3K) inhibitors.

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