Project PXD008743

PRIDE Assigned Tags:
Biomedical Dataset



Proteotranscriptomic profiling of potential E6AP targets


Prostate cancer is a common cause of cancer-related death in men. E6AP, an E3 ubiquitin ligase and a transcription cofactor, is elevated in a subset of prostate cancer patients. Genetic manipulations of E6AP in prostate cancer cells expose a role of E6AP in promoting growth and survival of prostate cancer cells in vitro and in vivo. However, the effect of E6AP on prostate cancer cells is broad and it cannot be explained fully by previously identified tumour suppressors, promyelocytic leukemia protein and p27, that are regulated by E6AP. To explore additional players that are regulated downstream of E6AP, we combined a transcriptomic and proteomic approaches. We identified and quantified 16,130 transcripts and 7,209 proteins in castration resistant prostate cancer cell line, DU145. A total of 2,763 transcripts and 308 proteins were considered significantly altered upon knockdown of E6AP. Pathway analyses supported the known phenotypic effect of E6AP knockdown in prostate cancer cells and in parallel exposed novel potential links of E6AP with cancer metabolism, DNA damage repair and immune response. Changes in expression of the top candidates were confirmed using real-time polymerase chain reaction. Of these, clusterin, a stress-induced chaperone protein commonly deregulated in prostate cancer was pursued further. Knockdown of E6AP resulted in increased clusterin transcript and protein levels in vitro and in vivo. Concomitant knockdown of E6AP and clusterin supported the contribution of clusterin to the phenotype induced by E6AP. Overall, results from this study provide insight intothe potential biological pathways controlled by E6AP in prostate cancer cells and identifies clusterin as a novel target of E6AP.

Sample Processing Protocol

Proteins were extracted from cell pellets with 1% sodium deoxycholate (SDC) in 50 mM HEPES pH 8.0. The lysates were boiled at 95°C for 5 minutes prior to probe sonication. Equal amount of protein (250 µg) from SILAC-labelled DU145 shE6AP and DU145 shControl cells was mixed. Proteins were reduced with 10 mM tris(2-carboxyethyl)phosphine hydrochloride (TCEP) andalkylated with 40 mM chloroacetamide (CAA) by boilingat 95°C for 5 minutes. Lysates were digested with sequencing grade modified trypsin (Promega) with an enzyme-to-substrate ratio of 1:100 overnight at 37°C. The trypsin was inactivated by acidification with formic acid (FA; Sigma-Aldrich) and SDC was removed from the tryptic digest by two extractions with ethyl acetate (Sigma-Aldrich). Peptides were reverse-phase fractionated as previously described (23). The lyophilised peptides were resuspended in 2% ACN/0.1% FA, aided by sonication (Ultrasonic Bath XUBA3, Grant Instruments Ltd, Cambridge, UK) prior to MS analysis. Data-dependent acquisition was performed on a QExactiveTM Plus Orbitrap mass spectrometer (Thermo Fisher Scientific) coupled to an UltiMate® 3000 Ultra High Performance Liquid Chromatography (Thermo Fisher Scientific) equipped with anAcclaim PepMap RSLC column (75 µm x 50 cm, nanoViper, C18, 2 µm, 100å; Thermo Fisher Scientific)using a 155 minute gradient. The precursor MSscan, whichcovered a range of 375-1600 m/z at a resolution of 70,000, was followed by up to 10 subsequent MS/MS scans measured at a resolution of 17,500. Only the most intense multiple charged precursors were selected for higher energy collision induced dissociation fragmentation. The automatic gain control targets were set to 1E6 for the MS scans and 5E4 for the MS/MS scans. Dynamic exclusion was applied for 20 seconds.

Data Processing Protocol

MaxQuant (version used for peptide and protein identification using the human proteome database downloaded from Uniprot (UP000005640) in February 2015. The parameters for MaxQuant searches were as follows: precursor mass tolerance was set to 20 ppm (parts per million) for the first search and 4.5 ppm for the main search. Carbamidomethylation of cysteines was entered as a fixed modification. Arg10 and Lys8 were used to specify heavy labelled amino acids, a maximum labelling of three amino acids was allowed and minimum peptide length was set to 7. Oxidation of methionines and acetylation of protein N-termini were considered as variable modifications. Enzyme digestion was setto trypsin with a maximum number of two missed cleavages. Using the target-decoy approach, the false discovery rate (FDR) for peptide, modification site and protein identifications was set to 1%. Match between runs was performed with a 2 minute retention time window. Only unmodified and razor peptides were used for quantification with the option to re-quantify. The ProteinGroups file obtained from MaxQuant was further analysed with Perseus (version Proteins that were identified as“only-by-site”, reverse hits and potential contaminants were removed. Outlier significance score for protein subsets was generated by intensity binning, called significance B, with a p-value <0.05 (24). Based on this statistical test, proteins could be significant in 1, 2 or 3 replicates. Proteins meeting all of the following three criteria in at least 2 replicates: significance, percentage of peptide quantitative variation of < 40% (as determined by MaxQuant in the ProteinGroups file) and ≥/ ≤ 1.5-fold difference were considered significant.


Ralf Schittenhelm, Monash University
Ygal Haupt, The Sir Peter MacCallum Department of Oncology, The University of Melbourne, Victoria, Australia ( lab head )

Submission Date


Publication Date



Q Exactive


Not available

Experiment Type

Shotgun proteomics


    Gulati T, Huang C, Caramia F, Raghu D, Paul PJ, Goode RJA, Keam SP, Williams SG, Haupt S, Kleifeld O, Schittenhelm RB, Gamell C, Haupt Y. Proteotranscriptomic measurements of E6-Associated Protein (E6AP) targets in DU145 prostate cancer cells. Mol Cell Proteomics. 2018 PubMed: 29463595