Project PXD002137

PRIDE Assigned Tags:
Biomedical Dataset



Proteome Landscapes of the Human Colorectal Mucosa, and its Adenoma and Cancer


Adenomatous polyps in the colorectal tract are benign tumors with the potential to develop cancer. In this study we perform a large scale proteomic study of comparing the proteomes of colorectal enterocytes (N) and the cells of the adenoma (A) and cancer (C). Using formalin fixed and paraffin embedded clinical material, we identified on average 10,000 proteins per sample of the microdissected cells and established a quantitative protein repository of the disease. Statistical analysis revealed 2300, 1780, and 2161 significant alterations between N and A, C and A, and C and N, respectively. In this work we did not aim identification of novel biomarkers but focus on depiction of the proteome alterations underlying the disease. The extent of the assessed changes reflects a varied cell size, the composition of different subcellular components, and basic biological processes including the energy metabolism, plasma membrane transport, DNA replication and transcription.

Sample Processing Protocol

Detergent was removed from the lysates and the proteins were processed according to the MED-FASP protocol using consecutive two step digestion with LysC and trypsin (21) using the 30k filtration units (Cat No. MRCF0R030, Millipore) (22). Peptides released by LysC and trypsin were fractionated into 4 and 2 SAX fractions, respectively.

Data Processing Protocol

The MS data were analyzed using the software environment MaxQuant (23) version and its built-in Andromeda search engine (24). Proteins were identified by searching MS and MS/MS data against the human or mouse complete proteome sequences from UniProtKB, version of May 2013, containing 88,820 and 50,807 sequences, respectively. Carbamido-methylation of cysteines was set as fixed modification. N-terminal acetylation and oxidation of methionines were set as variable modifications. Up to two missed cleavages were allowed. The initial allowed mass deviation of the precursor ion was up to 6 ppm and for the fragment masses it was up to 20 ppm (HCD, Orbitrap readout) and 0.5 Da (CID, ion trap readout), respectively. Mass accuracy of the precursor ions was improved by time-dependent recalibration algorithms of MaxQuant. The ‘match between runs’ option was enabled to match identifications across samples within a time window of 30 sec of the aligned retention times. The maximum false peptide and protein discovery rate was set to 0.01. Protein matching to the reverse database or identified only with modified peptides were filtered out. Proteins identified with single peptides were removed. Relative protein quantitation was performed using the LFQ algorithm of the Maxquant (25).A paired t-test was applied for testing of differences in protein intensities in clinical samples. Significance of outliers was calculated by multiple hypothesis testing (26) with the threshold value of 0.05. The protein titers were calculated using the Total Protein Approach (TPA) (16, 27), whereas the total protein content of the cells and the protein copy number per cells were assessed using the proteomic ruler (28).


Mario Oroshi, Proteomics
Jacek R Wisniewski, Max-Planck Institute of Biochemistry, Martinsried, Germany ( lab head )

Submission Date


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Q Exactive


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Experiment Type

Shotgun proteomics


    Wiśniewski JR, Dus-Szachniewicz K, Ostasiewicz P, Ziolkowski P, Rakus D, Mann M. Absolute proteome analysis of colorectal mucosa, adenoma and cancer reveals drastic changes in fatty acid metabolism and plasma membrane transporters. J Proteome Res. 2015 Aug 6 PubMed: 26245529