The conduction of Gene Ontology (GO) analysis Essay

The predicted number of SAAVs based on the SAAVs database is not consistent with that of the detected SAAVs in the MCF-7 cell line by mass spectrometry. The C, K M, N, O, S, V amino acid residues were found to increase while the amino acids F, H, P, R decreased, whereas the remaining amino acid residues remained basically unchanged. We also found that for most of frequent variations in the Swiss-CanSAAVs database and in the MCF-7 cell line that the top 32 and 23 variations were responsible for 50% of the SAAVs, respectively. The remaining 50% consists of 105 variations with 27, 26 and 16 of these being observed only one, two and three times respectively in the MCF-7 cell line. However, in the Swiss-CanSAAVs database, the remaining 50% consists of 247 variations with 63, 27 and 17 of these being observed only one, two and three times, respectively. There are a total 360 theoretical amino acid variation patterns, however, 276 and 102 amino acid variation patterns such as AH, AW do not exist in the MCF-7 cell line and the database, respectively.
It has been found that the codon frequency usage in all coding sequences shows bias for gene expression and likewise the base pair change also shows bias resulting in different frequencies between two amino acids such as RQ and QR in the database (Fig. 4). In most cases, the frequency of an amino acid variant relative to the frequency of the converse pattern is different. Some patterns show large differences such as RQ versus QR in the database and RH versus HR in the MCF-7 cell line (Fig. 5 A, B).
Gene Ontology (GO) analysis
Gene Ontology (GO) analysis was performed using the Ingenuity Pathway Analysis (IPA) bioinformatics tool and database. For proteins with SAAVs from the MCF-7 cell line, most proteins were found to be located in the cytoplasm, nucleus and plasma membrane (Fig. 6A). The dominant types of proteins included cytokines and other proteins with no assignments (Fig. 6B). Among the protein networks we found that the proteins TP53, TRRAP, PTEN and ERBB2 showed cancer related variations (Fig. 6C). BRCA2 has been reported as a marker that predisposes an individual for a high lifetime risk of breast cancer [22]. A previous study has also shown that TP53 and PTEN mutations are responsible for an increased risk for the development of breast and other cancers [23].
Cancer related proteins with SAAVs sites
Cancer related proteins with SAAVs may serve as candidate protein biomarkers or therapeutic targets.
95 unique SAAVs from 85 proteins related to cancer were identified based on manual searching against the CanProVar database (http//bioinfo.vanderbilt.edu/canprovar/). It should be noted that there is no variation information available for 6 proteins in the database search. Among 95 unique SAAVs, only 27 unique SAAVs in 19 proteins have cancer related variations (Supplemental Table 3). There are three breast cancer related proteins, Receptor tyrosine-protein kinase erbB-2, Cofilin-2 and 60S ribosome subunit biogenesis protein NIP7 homolog identified from the CanProVar database.