The spectral data were imported to “Compass 4.1” software to generate the “.mgf” files, which were subsequently submitted to “Mascot 2.4” software (Matrix Science, London, UK) for protein identification. Database searches of each file were performed using the SwissProt (2013–6) homo sapiens species specific database with the following parameters: peptide tolerance, 10–30 ppm; MS/MS tolerance, 0.05 Da; Quantitation, itraq 4plex; Enzyme, typsin; Max missed cleavages, 2; Fixed modification, carboxymethyl, methylthio of cysteine, iTRAQ 4plex of lysine, and iTRAQ 4plex of the n-terminus; Variable modification, oxidation, phospho of serine, threonine and tyrosine, and iTRAQ 4plex of tyrosine. The identification results of peptides were acceptable when the similarity was >96% and the false discovery rate (FDR) was <1%. The resulting Mascot result files (*.dat) were loaded into the Scaffold Q + S 4.2.0 software (Proteome Software Inc., Portland, OR) for further processing. For relative quantitation, only peptides unique for a given protein were considered, thus excluding those common to other isoforms or proteins of the same family. Proteins were identified on the basis of having at least one peptide with an ion score above 99% confidence. Identified peptides that are unique to a specific protein were used to determine relative quantitation of a protein between the four samples or the two samples, and the intensities of the iTRAQ® reporter ion m/z values (114, 115, 116 and 117) were used to estimate the relative abundances of a particular peptide. For proteins with more than one qualified peptide matches, multiple average peak area ratios were calculated using the peak area ratios of the peptides originating from the same protein58. In the present study, only protein quantification data with relative expression of >1.5 or <0.66 were chosen as differentially expressed proteins, which were analyzed by IPA software version 9.0 (Ingenuity® Systems, California, USA; http://www.ingenuity.com). The functional analysis identified the top pathways and biological functions that were most significant to the data set.