Workflow of gene identification in TCGA database
As shown in figure 1, there were 304 and 237 genes with different expressions in OS and FPS analysis, respectively. By comparing early stage (Stage I+II) with advanced stage (Stage III+IV) HSOC, we identified 544 stage-related aberrantly expressed genes in HSOC patients. After cross-checking OS, FPS and stage-related genes, only FAP and SSC5D were still present. And, FAP was finally included because of its characteristics of typical enzyme-catalyzed activity in uniprot database (www.uniprot.org/) and its potential role in HSOC patient’s survival (Figure 1).
Associations of FAP expression with overall survival (OS) and progression-free survival (PFS)
Cox regression analysis based on FAP expression was performed to generate survival curves in OS and PFS. As shown in figure 2A, low FAP expression group showed a significant protective effect on HSOC prognosis in OS (P = 0.005). Longitudinally, low FAP expression group had 91.1% survival rate in a period of 12 months, compared with 84.4% in high FAP expression group. Survival rate in 50 months decreased to 31.9% in low FAP group and 21.4% in high group, respectively (Table 1). Results of PFS also showed similar patterns to OS between high and low FAP expression groups (P = 0.008, figure 2B).
Expression of FAP in HSOC patients
Sections of 151 HSOC patients’ tumor tissues in different stages were stained with FAP-antibody. We identified an increasing trend of FAP expression with respect to severity of cancer stages (figure 3). In addition, strong positive FAP-staining generally showed in membranous and cytosolic compartments in HSOC tissues. Figure 3b revealed the total difference scores between early stage HSOC patients and advanced patients (P = 0.016). Additionally, negative FAP was observed in 33 (21.85%) patients.
Prediction of network influenced by FAP
Based on STRING and Genecard, prediction of co-influence genes with FAP and their potential regulating effects was shown in figure 4. Specifically, fibronetin-1 (FN1), collagen family genes-COL1A1, COL1A2, COL3A1, COL5A2, Thy-1 cell surface antigen (THY1), and insulin (INS) were identified as co-influence genes.
FN1 was the only significant gene based on Cox regression with its hazardous influence on HSOC (P = 0.018, as shown in table 1). FN1 is demonstrated to over-express in ovarian cancer, which could eventually influence the formation of multicellular aggregate of ovarian cancer cells, migration and invasion of cancer cells, and aggravating platinum-resistance to deactivate chemotherapy. Additionally, epithelial-mesenchymal transition of ovarian cancer is shown to relate to aberrant expression of FN1. Therefore, FN1 and its regulatory factors, including genes, non-coding RNAs and epigenetic regulations, might be valuable candidates for ovarian cancer studies.
Considering the similar function of collagen (COL) family, we extended the search of collagen encoding genes. Additional COL genes that could influence HSOC included COL16A1 (HR = 2.50, P = 0.001 for Cox regression), COL5A1 (HR = 2.43, P = 0.002), COL8A1 (HR = 2.16, P = 0.006), and COL4A1 (HR = 1.83, P = 0.035) (Table 1).
Bioinformation of FAP in GO and KEGG analysis
For gene ontology (GO) analysis of FAP, the top three enriched GO annotations were listed as “regulation of fibrinolysis”, “negative regulation of extracellular matrix organization”, and positive regulation of execution phase of apoptosis” three in Biological Process, while as “dipeptidyl-peptidase activity”, “aminopeptidase activity”, and “metalloendopeptidase activity” in Molecular Function (figure 5). On the other hand, however, for KEGG analysis, there is no related available record for FAP in corresponding database.