3.1. Active Ingredients
In this study, we acquired a total of 9 active ingredients of FAA after ADME identification. Detailed information was shown in Table 1 (all Mol IDs could be tracked in the TCMSP database). All the FAA compounds before screening were presented in Table S1.
3.2. FAA Compound-Target Network
To further uncover the potential pharmacological mechanisms of FAA against breast cancer, target genes common to both active ingredients of FAA and breast cancer were selected in different databases. A total of 75 genes (Table S4) belonging to both the FAA target gene and breast cancer target gene networks were screened via Venn analysis (Figure 1a). The compound-target network was presented in Figure 1b, including 82 nodes and 171 edges, with a network density of 0.051 and a network diameter of 3. The detailed information of this network was depicted in Table 2. As could be seen from figure 1b, quercetin was the most critical component of FAA, which was connected to the most targets. It was one of the flavonoids from natural plant and exhibited a variety of activities such as antioxidant, anti-inflammatory, antiviral and antimicrobial through multiple signal transduction pathways [33, 34]. Several studies had validated that quercetin could inhibit various tumor progression, including breast cancer [35], prostate cancer [36], gastric cancer [37], ovarian cancer [38] and colorectal cancer [39]. Moreover, there were also some literatures reported that it not only had a synergistic effect when combined with chemotherapeutic or radiotherapy agents, but also could reduce an expected adverse side effect and a toxic reaction [40].
In addition, the results showed that many targets were affected by two or more compounds. For instance, Prostaglandin G/H synthase 1 (PTGS1) and Prostaglandin G/H synthase 2 (PTGS2) were both modulated by quercetin, stigmasterol, mandenol, etc. Constitutive PTGS1 and inducible PTGS2 belonged to two isozymes of PTGS which had pivotal effects both as a peroxidase and a dioxygenase [41]. Other study suggested that PTGS2 might inversely control the breast cancer metastasis and chemoresistance through the regulation of EMT, apoptosis and senescence [42]. And nuclear receptor coactivator 2 (NCOA2), a member of the p160 family, performed key roles in many different physiological and pathological processes, including cell growth, energy metabolism, endocrine regulation, and circadian rhythm [43]. More importantly, the expression of the NCOA2 gene played crucial roles in the development, progression, and metastasis of malignant tumors, such as breast cancer [44]. In prostate cancer patients, high expression of NCOA2 was more likely to relapse after androgen-deprivation therapy [45].
Similarly, Beta-2 adrenergic receptor (ADRB2), Gamma-aminobutyric acid receptor subunit alpha-1 (GABRA1), Heat shock protein HSP 90, Progesterone receptor (PGR) and Sodium channel protein type 5 subunit alpha (SCN5A) could also be regulated by more than two active ingredients. Not only was obtained an approximate observation of the relationship between these active ingredients and targets, but also discovered the potential pharmacological effects of FAA from this network of Figure 1b.
3.3. PPI Network
To explore the underlying mechanisms of FAA as a therapy against breast cancer, a PPI network of the FAA compound targets against breast cancer was constructed by connecting the targets of FAA compound and the breast cancer. First, we obtained a total of 75 target genes which belonged to both the FAA target gene and breast cancer target gene and got targets symbol names by uniprot. Next, all of these 75 target genes were imported into the STRING database to generate the PPI results (settings: Homo sapiens and confidence >0.4). The original STRING PPI network was presented in Figure S1. Then, we imported the PPI data generated in STRING into Cytoscape (version 3.6.1).
As Figure 2a showed, this PPI network included 75 nodes and 1247 edges, with a network diameter of 3, a clustering coefficient of 0.733 and an average number of 33.253 neighbors. The average node degree was 33.3 (both the different colors and the size of the circles indicated the degree). The detailed information of this network was displayed in Table 3. All target degrees were calculated using this network. In Figure 2b, the 10 targets with the greatest degrees were AKT1 (degree = 67), MYC (degree = 65), CASP3 (degree = 63), EGFR (degree = 62), JUN (degree = 61), CCND1 (degree = 60), VEGFA (degree = 60), ESR1 (degree = 59), MAPK1 (degree = 57) and EGF (degree = 55). As shown in Figure 3c, the cluster consisted of 68 nodes and 1155 edges. The average node degree was 34 and the clustering coefficient was 0.77. The red diamond in Figure 3c, AKT1, was the seed in this cluster and interacted with other FAA targets. This figure intuitively indicated that AKT1 played an important role in connecting other nodes in this PPI network. It was well-known that the serine/threonine kinase AKT1, one of the three isoforms in the Akt family, had emerged as a downstream effector of PI3K [46]. AKT inhibited apoptosis by suppressing the actions of BAD and caspase-9 [47]. In breast cancer, AKT1 activation accelerates cell proliferation, whereas Akt1 inhibition promotes Epithelial-to-Mesenchymal Transition [48].
3.4. GO Enrichment
To further discuss the multiple mechanisms of FAA as a treatment against breast cancer, we conducted GO enrichment analysis on the 75 common targets shared by the FAA compound targets and the breast cancer related targets [31]. To be more specific, the top 30 targets are as follows (Figure 2b): AKT1, MYC, CASP3, EGFR, JUN, CCND1, VEGFA, ESR1, MAPK1, EGF, IL6, PTGS2, ERBB2, FOS, MMP9, CXCL8, MMP2, BCL2L1, CASP8, AR, IL1B, CCL2,CDKN1A, IL10, PPARG, RELA, SPP1, ICAM1, PGR and SERPINE1. The significantly enriched GO targets were presented (adjusted p-value <0.001) in Figure 3. The top five GO enrichment targets included (1) transcription factor activity, RNA polymerase II proximal promoter sequence-specific DNA binding (GO:0000982); (2) transcriptional activator activity, RNA polymerase II transcription regulatory region sequence-specific DNA binding (GO:0001228); (3) ubiquitin-like protein ligase binding (GO:0044389); (4) cytokine receptor binding (GO:0005126); and (5) transcriptional activator activity, RNA polymerase II proximal promoter sequence-specific DNA binding (GO:0001077). Detailed GO enrichment information was shown in Table 4. Thus, we speculated that FAA probably executed its pharmacological effects on breast cancer by simultaneously involving these molecular functions.
3.5. KEGG Enrichment
Meanwhile, we further carried on KEGG [32] enrichment analysis on the 75 common targets in order to clarify the integral regulation of FAA for the treatment of breast cancer. We obtained 74 pathways in total which belonged to several categories, including human diseases, cellular processes, and drug resistance, among others, of which the top 30 significantly enriched KEGG targets were presented (adjusted p-value <0.001) in Figure 4. In the cancer-related disease, prostate cancer (hsa05215), bladder cancer (hsa05219), pancreatic cancer (hsa05212), breast cancer (hsa05224), colorectal cancer (hsa05210), non-small cell lung cancer (hsa05223), small cell lung cancer (hsa05222), gastric cancer (hsa05226), endometrial cancer (hsa05226), renal cell carcinoma (hsa05211), thyroid cancer (hsa05216), and small cell lung cancer (hsa05222) data were processed using KEGG enrichment analysis. Detailed KEGG information was shown in Table 5. This result showed that FAA had the highly potential to treat a wide range of cancers, such as breast cancer [10], prostate cancer [49], bladder cancer [50], colorectal cancer [51], and gastric cancer [52], which were confirmed by other researchers. Further, the results in Figure 5 also verified that these signaling pathways remarkably enriched by the potential targets of FAA in breast cancer were strongly associated with signal transduction, endocrine system, replication and repair, cell growth and death, most of which played a essential role in the development and progression of cancers, such as pathways in PI3K/AKT signaling pathway (hsa04151), Estrogen signaling pathway (hsa04915), MAPK signaling pathway (hsa04010), mammalian target of rapamycin (mTOR) signaling pathway (hsa04150), apoptosis (hsa04210) and cell cycle (hsa04110). Therefore, we speculated that the underlying mechanism of FAA against breast cancer might be attributed to coordinated regulation of several cancer-related pathways.