Project PXD003668

PRIDE Assigned Tags:
Biomedical Dataset

Summary

Title

Integrative proteomic profiling of ovarian cancer cell lines reveals precursor-cell associated proteins and functional status

Description

A cell line representative of human high-grade serous ovarian cancer (HGSOC) should not only resemble its tumor of origin at the molecular level, but also demonstrate functional utility in pre-clinical investigations. Here we report the integrated proteomic analysis of 26 ovarian cancer cell lines, HGSOC tumors, immortalized ovarian surface epithelial cells, and fallopian tube epithelial cells via a single-run mass spectrometric workflow. The in-depth quantitation of > 10,000 proteins results in three distinct cell line categories: epithelial (group I), clear cell (group II), and mesenchymal (group III). We identify a 67-protein cell line signature, which separates our entire proteomic dataset, as well as a confirmatory publicly available CPTAC/TCGA tumor proteome dataset, into a predominantly epithelial and mesenchymal HGSOC tumor cluster. This proteomics-based epithelial/mesenchymal stratification of cell lines and human tumors indicates a possible origin of HGSOC either from the fallopian tube or from the ovarian surface epithelium.

Sample Processing Protocol

Cell lysis was performed in lysis buffer (4% SDS, 10 mM Hepes pH 8.0) at 99°C for 10 min and by 15 min sonication (level 5, Bioruptor, Diagenode). HGSOC tissues were first homogenized in lysis buffer using an Ultra Turbax blender. Proteins in the lysate were reduced with 10 mM DTT for 30 min and alkylated with 55 mM iodoacetamide for an additional 30 min. Remaining SDS detergent was removed by acetone precipitation. Briefly, acetone (-20 °C) was added to 100 μg of proteins to a final concentration of 80% v/v and proteins were precipitated overnight at -20 °C. After centrifugation (15 min, 4 ºC, 16,000 g), the detergent-containing supernatant was removed and the protein pellet washed with 80% acetone (-20 °C). Protein pellets were then resolved in 100 μl 6 M urea/2 M thiourea (in 10 mM Hepes pH 8.0) and digested with 1 μg of LysC for 3 h at room temperature. After adding 4 volumes 50 mM ammonium bicarbonate, 1 μg trypsin was added and tryptic digestion carried out overnight. The next day, digestion was stopped by adding 1% TFA. Peptides were finally desalted on C18 StageTips and kept at -20°C until MS analysis.

Data Processing Protocol

MS raw files were analysed with MaxQuant software21 (version 1.5.0.38). MS/MS based peptide identification was carried out with the Andromeda search engine in MaxQuant20. Briefly, Andromeda uses a target-decoy approach to identify peptides and proteins at an FDR of less than 1%. As a forward database, the human UniProtKB database (Oct 2014) was used. A reverse database for the decoy search was generated automatically in MaxQuant. Enzyme specificity was set to “Trypsin”, and a minimum number of 7 amino acids were required for peptide identification. Default settings were used for variable and fixed modifications (variable modification, acetylation [N-terminus] and methionine oxidation; fixed modification, carbamidomethylation). For the protein identification process, at least 1 razor or unique peptide was required. Proteins that could not be discriminated by unique peptides were grouped into protein groups. For label-free protein quantification, the MaxLFQ algorithm was used as part of the MaxQuant environment22. Briefly, quantitative information was retrieved based on high-resolution 3D peptide profiles in mass-to-charge, retention time and intensity space. The algorithm first calculated pairwise protein ratios by taking the median of all pairwise peptide ratios per protein. Of note, only shared identical peptides were considered for each pairwise comparison. A minimum number of 1 ratio count was required for each pairwise comparison. To retrieve quantitative information for all possible sample comparisons, a least-squares analysis was used to reconstruct the relative abundance profile for each protein. This step preserved the total summed intensity for a protein over all samples. To maximize the number of quantification events across samples, we enabled the “Match Between Runs” option in MaxQuant, which allowed the quantification of high-resolution MS1 features that were not identified in each single measurement. Isobaric tag for relative and absolute quantification (ITRAQ)-based TCGA proteome raw files (PNNL study) generated by the Clinical Proteomic Tumour Analysis Consortium (NCI/NIH) were downloaded from the CPTAC data portal (https://cptac-data-portal.georgetown.edu/cptacPublic/) and analysed with MaxQuant. Logarithmic reporter intensities were normalised against the control reporter channel (channel 117, pooled sample of 84 TCGA ovarian tumour tissue samples) and each sample median normalised prior to data analysis.

Contact

Mario Oroshi, Proteomics
Matthias Mann, Max Planck Institute for Biochemistry Department of Proteomics and Signaltransduction Am Klopferspitz 18 D-82152 Martinsried ( lab head )

Submission Date

22/02/2016

Publication Date

24/08/2016

Publication

    Coscia F, Watters KM, Curtis M, Eckert MA, Chiang CY, Tyanova S, Montag A, Lastra RR, Lengyel E, Mann M. Integrative proteomic profiling of ovarian cancer cell lines reveals precursor cell associated proteins and functional status. Nat Commun. 2016 Aug 26;7:12645 PubMed: 27561551