Breast cancer is the most common malignancy among women all over the world whose mortality rate is the highest [
However, the long-term endocrine therapeutic strategy is frequently associated with adverse side effects, which decrease patient compliance [
Danzhi Xiaoyao powder (DXP) is a herbal formula that comes from
Herbal formulae can act on the multiple targets through their multiple components and play an integral role in the key biological process of disease development, which promotes the body back to equilibrium, and thus they play a therapeutic role [
To collect the compounds of DXP, we used the TCM Database@Taiwan [
Due to the disadvantages of biological experiments as being time-consuming and of high cost, identification of ADME (absorption, distribution, metabolism, and excretion) properties by in silico tools has now become an inevitable paradigm in pharmaceutical research. In this study, three ADME-related models, namely, the evaluation of oral bioavailability (OB), Caco-2 permeability, and drug-likeness (DL), are employed to identify the potential bioactive compounds of DXP [
In this work, the compounds of OB ≥ 30%, Caco-2 > −0.4, and DL ≥ 0.18 are selected for subsequent research, and others are excluded.
According to these indexes, several compounds are included: ergosterol peroxide, ethyl oleate (NF), glabridin, glycyrrhetinic acid, linoleyl acetate, longikaurin A, mairin, mandenol, MOL000273, MOL001910, 508-02-1, 64997-52-0, 8
In fact, reality constraints of most biological models force the dependent variables to lie in some finite bounds [
According to the texts [
Input all the active compounds into SciFinder (
Acquire associated known target proteins with their target name, DrugBank ID, and validated status information from TCMSP. The targets proteins of TCMSP come from DrugBank and other databases and are almost the experimental validated drug-target pairs retrieved from HIT database and so on [
Because of the nonstandard naming, we use UniProtKB (
We collected different genes associated with ER-positive breast cancer from two resources. (1) Genecards (
We searched these databases with keywords “luminal A breast cancer”, “luminal A type breast cancer”, “luminal B type breast cancer”, “luminal B breast cancer”, and “ER-positive breast cancer”, and got 85 genes totally. The details are described in Table
The data of protein-protein interaction (PPI) (such as the breast cancer target-compound target interaction) come from String [
All the networks can be created via utilizing the network visualization software Cytoscape [
Input the targets and the data of PPI into Cytoscape to construct different networks based on this research. Network construction was performed as follows: (1) ER-positive breast cancer network; (2) compound-compound target network of DXP; (3) DXP-ER-positive breast cancer network; (4) compound-known target-ER-positive breast cancer network.
The densely connected regions in large protein-protein interaction networks that may represent molecular complexes is defined as topological modules or clusters [
The Database for Annotation, Visualization and Integrated Discovery (DAVID,
Construct this “gene-gene interaction” network based on the data of ER-positive breast cancer genes’ PPI and ER-positive breast cancer genes. This network contains 71 nodes and 497 edges (Figure
ER-positive breast cancer target PPI network.
In this network, the red nodes (ESR1, TP53, CCND1, EGFR, BCL2, MYC, SRC, ERBB2, and PGR) have higher degrees. The number of edges (which means the number of gene nodes that they are associated with) of each node is quite large (44 in ESR1 and TP53, 41 in CCND1, 40 in EGFR, 39 in BCL2 and MYC, 37 in SRC and ERBB2, 28 in PGR). This demonstrates that these genes are closely related to other genes in the network, suggesting that these genes may play an important role in ER-positive breast cancer. Pathogenic factors may directly influence ER-positive breast cancer-related genes or indirectly influence ER-positive breast cancer-related genes by affecting these genes, thereby affecting the development of ER-positive breast cancer, which suggests that these genes may be the key or central genes.
Analyze the network by MCODE, and two clusters are returned (Table
Cluster of ER-positive breast cancer PPI network.
Cluster | Score | Nodes | Edges | Genes |
---|---|---|---|---|
1 | 17 | 19 | 153 | EIF4E, MTOR, EGFR, ERBB3, PIK3CA, SRC, PGR, IGF1, ESR1, CCND1, ERBB2, TP53, BCL2, FOXO3, JAK2, STAT5B, MYC, KDR, PTGS2 |
2 | 3 | 7 | 9 | FOXA1, RUNX1, NCOR2, GATA3, TFF1, EZH2, SIRT1 |
Cluster of ER-positive breast cancer target PPI network ((a), (b) stand for clusters 1 and 2).
Cluster 1 has (GO: 0018108) peptidyl-tyrosine phosphorylation, (GO: 0038128) ERBB2 signaling pathway, (GO: 0043066) negative regulation of apoptotic process, (GO: 0008283) cell proliferation, (GO: 0032355) response to estradiol, (GO: 0071364) cellular response to epidermal growth factor stimulus, (GO: 0048146) positive regulation of fibroblast proliferation, (GO: 0050679) positive regulation of epithelial cell proliferation, (GO: 0014068) positive regulation of phosphatidylinositol 3-kinase signaling, (GO: 0007169) transmembrane receptor protein tyrosine kinase signaling pathway, (GO: 0000165) MAPK cascade, (GO: 0038083) peptidyl-tyrosine autophosphorylation, (GO: 0007173) epidermal growth factor receptor signaling pathway, (GO: 0043406) positive regulation of MAP kinase activity, (GO: 0050727) regulation of inflammatory response, (GO: 0048010) vascular endothelial growth factor receptor signaling pathway, (GO: 0070374) positive regulation of ERK1 and ERK2 cascade, (GO: 0060397) JAK-STAT cascade involved in growth hormone signaling pathway, (GO: 0030330) DNA damage response, signal transduction by p53 class mediator, (GO: 0042523) positive regulation of tyrosine phosphorylation of Stat5 protein, (GO: 0030520) intracellular estrogen receptor signaling pathway, (GO: 0001525) angiogenesis, (GO: 0045737) positive regulation of cyclin-dependent protein serine/threonine kinase activity, (GO: 0034612) response to tumor necrosis factor, (GO: 0007259) JAK-STAT cascade, and (GO: 0000186) activation of MAPKK activity.
Cluster 2 gets (GO: 0032355) response to estradiol, (GO: 0071356) cellular response to tumor necrosis factor, and (GO: 0045766) positive regulation of angiogenesis.
In summary, we get the clusters through analyzing the network and get the biological processes of clusters through GO enrichment analysis; and, in analysis, two clusters and thirty-three biological processes were acquired. These biological processes are related to breast cancer; for example, some of them are related to limitless replicative potential like cell proliferation (GO: 0008283), positive regulation of ERK1 and ERK2 cascade (GO: 0070374), and tumor promotion inflammation, such as regulation of inflammatory response (GO: 0050727) and response to tumor necrosis factor (GO: 0034612), while others are associated with the response to stimulation of breast cancer, such as response to estrogen (GO: 0032355). Pathogenic factors may directly or indirectly affect the genes enriched to each biological process so as to influence these ER-positive breast cancer-related biological processes, which thereby affect the development of ER-positive breast cancer. In this network analysis, we can observe the molecular mechanism of the development of ER-positive breast cancer more clearly.
Recent research shows that ER (including ER
In classic ERE mode, unbound ER can be nuclear localized and bound loosely to the ERE [
In non-ligand-dependent genome mode, in the absence of estrogen, the growth factor-activated intracellular signaling pathway induces nER to bind to ERE to regulate gene transcription; the epidermal growth factor (EGF) activates the MAPK signaling pathway through the EGF receptor and then phosphorylates the nER, which allows nER to be activated in the absence of estrogen [
In nonclassical pathways of ERE signaling, ERs can stimulate gene transcription by interacting with other transcription factors bound to promoters of responsive genes. Genes that are regulated by estrogen but do not have an ERE include cyclin D1, p21, and the PR [
In breast cancer, membrane estrogen receptor- (mER-) mediated signaling can make estradiol exert early signaling events within target cells minutes after stimulation, which makes it likely that these effects are independent of transcription. The activation of mER not only leads to activation of MAPK signaling and PI3K signaling and a rise in cytoplasmic calcium levels but also activates the release of EGF and IGF, thus leading to stimulation of EGFR and IGFR, respectively [
The absence of ER is a sign of poor prognosis, and the status of coactivators and corepressors of ER in the nucleus also greatly affects the pathogenic ability of estrogen in breast cancer cells [
Input all of the genes into DAVID to do pathway enrichment analysis and get sixteen significant breast cancer associated pathways (Figure
Pathway of ER-positive breast cancer target PPI network (blue circle stands for breast cancer gene; red diamond stands for pathway).
These pathways with so many breast cancer associated genes may be the key pathways in breast cancer’s development. We can find that these pathways have several of the same genes (e.g., both estrogen signaling pathway and VEGF signaling pathway have SRC and PIK3CA). Meanwhile, the downstream effects of these signaling pathways are also complex and multiple, suggesting that different signal pathways are closely related and have great complexity. Intervening in these 16 signaling pathways may be the potential strategy of treating ER-positive breast cancer in the future.
As a systemic disease, the abnormality of the signaling of hormone, cytokines, growth factors, and so on may lead to excessive amplification of certain genes and thus causes normal cells to receive abnormal proliferation, differentiation, and growth signals, which ultimately promote normal cell carcinogenesis. Meanwhile, their respective mediated signaling pathways cross each other to jointly promote the occurrence, invasion, and metastasis of breast cancer. The study finds that the rapid nongenomic effect of estrogen is activating the PI3K/AKT pathway by stimulating IGF-1R in breast cancer cell so as to lead to increased mitosis of breast cancer cells. In breast cancer cells, the utilization of ICI182780 (Faslodex), an estrogen receptor antagonist, can reduce the response of EGF, suggesting that, among ER, EGFR, and IGFR signaling pathways, there is not a single linear relationship, but the interaction with each other [
In the cell, there are multiple signaling pathways associated with the development, invasion, and metastasis of breast cancer, such as receptor tyrosine kinase- (RTK-) mediated signaling pathways, estrogen-regulated ER signaling pathway, TGF-
The estrogen-regulated signaling pathways mainly contain the PI3K/AKT signaling pathway, MAPK/ERK signaling pathway, cAMP/PKA signaling pathway, and JNK signaling pathway. These pathways are thought to have the role of regulating the growth, development, and cell proliferation of mammary glands. Meanwhile, they are also the molecular basis of normal mammary gland tissue transformation, uncontrolled proliferation, and antiapoptosis. TGF-
As a highly heterogeneous disease, multiple antiapoptotic pathways associated with inflammatory pathways and certain signaling molecules also mediate the development of breast cancer. For instance, MAPK/ERK1/2 pathway, NF-
This network is composed of 454 nodes (374 compound target nodes and 80 compound nodes) and 10371 edges. In this network we can find that many targets are hit by multiple compounds (central nodes, e.g., HSD17B1, CA2, MAPK14, BACE1, and HSP90AA1, can be hit by all compounds), but some can be modulated by only one compound (peripheral nodes, e.g., FGFR2, ALDH2, PPIA, and IGLV2-8). In other words, these compounds are able to regulate the compound targets. For example, all (+)-catechin, ammidin, dehydroeburicoic acid, octalupine, and paeoniflorin can regulate ESR1, ESR2, PGR, and IGF1R (Figure
Compound-compound target network of DXP consists of 374 compound targets and 87 compounds (pink hexagon stands for compound targets; red, orange, yellow, green, blue, and purple circles stand for compounds of
This suggests that DXP’s compounds may act on these targets and thus play a pharmacological role in other diseases besides breast cancer, which invisibly shows herbal formulae’s feature of multicompound-multitarget-multidisease. Its potential effect can be carried out by this network. However, we do not know whether the relationship between them is synergistic, antagonistic, or otherwise. Therefore, it needs further research.
Integrating ER-positive breast cancer network and compound-compound target network, we can get DXP-ER-positive breast cancer network. This network contains 519 nodes and 15855 edges. Compared with ER-positive breast cancer network, this network adds 448 nodes and 15385 edges (Figure
DXP-ER-positive breast cancer network (the representation of red, orange, yellow, green, blue, and purple circle, purple and blue hexagon, and blue, green, yellow, orange, and red diamonds is the same as Figure
Analyze the network by MCODE, and eleven clusters are returned. Cluster 2 gets ergosterol peroxide, ethyl oleate (NF), glabridin, glycyrrhetinic acid, linoleyl acetate, longikaurin A, mairin, mandenol, MOL000273, MOL001910, 508-02-1, 64997-52-0, 8
Cluster of herbal formula-disease PPI network.
Cluster | Score | Nodes | Edges | Genes |
---|---|---|---|---|
1 | 30.486 | 38 | 564 | CCND1, STAT1, IGF1, MAP2K1, PIK3CA, BCL2, F2, PTK2, MYC, JAK2, RHOA, PIK3R1, BCL2L1, AKT2, NOS3, AKT1, IGF1R, HMOX1, MMP9, ABL1, KIT, RAF1, IL2, CDC42, GRB2, LCK, MMP2, KDR, ERBB2, ERBB3, STAT5B, RAC1, TP53, PTPN11, MAPK8, MTOR, FOXO3, MET |
| ||||
2 | 16 | 52 | 408 | Ergosterol peroxide, ethyl oleate (NF), PPARD, PAK1, PDPK1, EPHA2, EGF, RET, SYK, RARA, CCL2, WT1, YAP1, NOS2, glabridin, glycyrrhetinic acid, NME2, BRAF, ZAP70, PPARG, ESRRG, PPARA, HSP90AA1, HCK, CASP3, linoleyl acetate, longikaurin A, mairin, mandenol, CDK6, MOL000273, MOL001910, 508-02-1, 64997-52-0, 8 |
| ||||
3 | 10.421 | 20 | 99 | XIAP, ESR1, MAPK1, FGFR1, MAPK14, MMP1, RAC2, MYB, PTGS2, PTPN1, MAPK12, EIF4E, AR, SRC, ERBB4, INSR, JAK3, GSK3B, SIRT1, ALB |
| ||||
4 | 9.143 | 43 | 192 | NR1H2, F7, ferulic acid, MAPK10, BTK, MOL000285, RARG, 4-O-methylpaeoniflorin, APAF1, THRA, CASP1, GATA3, MUC1, PLK1, HSP90AB1, PRKACA, PLG, VDR, CTSD, RUNX1, glabrene, CHEK1, PRKCQ, LGALS3, poricoic acid A, glycyrrhizin, ITK, FGFR2, EZH2, RARB, HSPA8, TNFRSF11B, CASP7, sudan III, CA2, ZINC02816192, THRB, HRAS, HNF4G, kaempferol, TEK, licochalcone G, NCOA3 |
| ||||
5 | 7.829 | 36 | 137 | APRT, IMPDH2, MMP3, NR3C1, NR1H3, ELANE, 7,9(11)-dehydropachymic acid, GMPR2, paeoniflorgenone, paeoniflorin sulfonate, PGF, areapillin, UMPS, quercetin, senkyunolide I, stigmasterol, ARF1, CALM2, DHFR, TGFB2, butylidenephthalide, isoliquiritigenin, (+)-anomalin, isorhamnetin, vestitol, crocetin, 113269-36-6, CANT1, |
| ||||
6 | 6.368 | 39 | 121 | MMP8, PARP1, GSTM1, RAN, PPP5C, 3 |
| ||||
7 | 4.848 | 34 | 80 | Dehydroeburicoic acid, ergosta-7,22E-dien-3beta-ol, RAP2A, MOL000280, MOL000287, mudanpioside H, HDAC4, NSC684433, octalupine, 18103-41-8, RXRA, PLAU, formononetin, albiflorin, 1-methoxyphaseollidin, HSPD1, paeoniflorin, KAT2B, TOP2A, glycyrin, ammidin, poricoic acid B, poricoic acid C, CTNNA1, sainfuran, sitosterol, isoimperatorin, isolicoflavonol, cerevisterol, 3-methylkempferol, RND3, CDK2, licoisoflavone B, cubebin |
| ||||
8 | 4.762 | 22 | 50 | SDS, SHMT1, CTSG, AK1, ACE, TYMS, GMPR, MME, GP1BA, METAP2, DCK, PIP, (+)-catechin, ATIC, GART, FKBP1A, PSPH, CBS, ITGAL, NT5M, LYZ, PDE4D |
| ||||
9 | 3.538 | 14 | 23 | G6PD, RAB5A, ARF4, LDHB, BACE1, AHCY, PKLR, PYGL, RAB11A, HK1, ADAM17, GSR, MMP13, SOD2 |
| ||||
10 | 3.333 | 4 | 5 | GALK1, GPI, GCK, ME2 |
| ||||
11 | 3 | 3 | 3 | TPH1, CBR1, SPR |
Cluster of DXP-ER-positive breast cancer network ((a), (b), (c), (d), and so on stand for clusters 1, 2, 3, 4, and so on. The representation of red, orange, yellow, green, blue, and purple circle, purple and blue hexagon, and blue, green, yellow, orange, and red diamonds is the same as Figure
In addition, there are some breast cancer-related genes in clusters. Cluster 1 gets MTOR, BCL2, FOXO3, ERBB3, ERBB2, TP53, MYC, PI3KCA, IGF1, CCND1, STAT5B, JAK2, and KDR. Cluster 2 has ESR2, CSK, PGR, EGFR, CCL2, WT1, YAP1, NCOR2, PAK1, EGF, and RET. Cluster 3 includes EIF4E, SRC, ERBB4, ESR1, SIRT1, MYB, and PTGS2. Cluster 4 gets PLK1, CTSD, RUNX1, EZH2, TNFRSF11B, NCOA3, GATA3, and MUC1. Cluster 6 has GSTP1 and MKI67. Cluster 7 gets HSPD1, TOP2A, and HDAC4. Cluster 8 includes PIP. These genes may be the key genes of DXP treating ER-positive breast cancer.
Deal with these clusters by GO enrichment analysis. Clusters 8, 10, and 11 do not return ER2-positive breast cancer-related biological processes. And, after filtering by
Cluster 1 gets (GO: 0048015) phosphatidylinositol-mediated signaling, (GO: 0014066) regulation of phosphatidylinositol 3-kinase signaling, (GO: 0018108) peptidyl-tyrosine phosphorylation, (GO: 0000165) MAPK cascade, (GO: 0014068) positive regulation of phosphatidylinositol 3-kinase signaling, (GO: 0048010) vascular endothelial growth factor receptor signaling pathway, (GO: 0038128) ERBB2 signaling pathway, (GO: 0038083) peptidyl-tyrosine autophosphorylation, (GO: 0007169) transmembrane receptor protein tyrosine kinase signaling pathway, (GO: 0008283) cell proliferation, (GO: 0007173) epidermal growth factor receptor signaling pathway, (GO: 0048009) insulin-like growth factor receptor signaling pathway, (GO: 0042523) positive regulation of tyrosine phosphorylation of Stat5 protein, (GO: 0050731) positive regulation of peptidyl-tyrosine phosphorylation, (GO: 0043552) positive regulation of phosphatidylinositol 3-kinase activity, (GO: 0071364) cellular response to epidermal growth factor stimulus, (GO: 0001525) angiogenesis, (GO: 0036092) phosphatidylinositol-3-phosphate biosynthetic process, (GO: 0007259) JAK-STAT cascade, (GO: 0070374) positive regulation of ERK1 and ERK2 cascade, (GO: 0007265) Ras protein signal transduction, (GO: 0060070) canonical Wnt signaling pathway, (GO: 0032355) response to estradiol, (GO: 0033209) tumor necrosis factor-mediated signaling pathway, (GO: 0060644) mammary gland epithelial cell differentiation, (GO: 0008631) intrinsic apoptotic signaling pathway in response to oxidative stress, (GO: 0030330) DNA damage response, signal transduction by p53 class mediator, (GO: 0060397) JAK-STAT cascade involved in growth hormone signaling pathway, and (GO: 0043123) positive regulation of I-kappaB kinase/NF-kappaB signaling.
Cluster 2 has (GO: 0043401) steroid hormone mediated signaling pathway, (GO: 0001525) angiogenesis, (GO: 0006954) inflammatory response, and so forth.
Cluster 4 includes (GO: 0043401) steroid hormone mediated signaling pathway, (GO: 0043627) response to estrogen, (GO: 0008285) negative regulation of cell proliferation, (GO: 0043410) positive regulation of MAPK cascade, (GO: 0070374) positive regulation of ERK1 and ERK2 cascade, and (GO: 0000165) MAPK cascade.
Analyzing another cluster by the same way, we get the same related biological processes. The details are described in Table
Overall, we obtain the biological processes through analyzing the network and GO enrichment analysis clusters; and, in analysis, eleven clusters and forty-five biological processes were acquired. These biological processes are associated with breast cancer; for instance, some of them are associated with sustained angiogenesis (e.g., GO: 0048010 and GO: 0001525), while others are related to the signal response, such as ERBB2 signaling pathway (GO: 0038128) and response to estradiol (GO: 0032355); there are also some biological processes related to limitless replicative potential, like cell proliferation (GO: 0008283) and regulation of phosphatidylinositol 3-kinase signaling (GO: 0014066). Beside these, there are many other biological processes associated with breast cancer characteristics; and all of them can be found in Table
Importing all targets into DAVID, we can get fifteen ER-positive breast cancer-related significant pathways (Figure
Pathway o of DXP-ER-positive breast cancer network (blue circle stands for compound target; red diamond stands for pathway; green hexagon stands for herb).
DXP, as a multiherb formula, can act on multiple ER-positive breast cancer-related targets by its multiple components in each herb. For example, ammidin, dehydroeburicoic acid, (+)-catechin, paeoniflorin, and so on can regulate ESR1, ESR2, and PGR; this can be observed in Figures
For the compounds in cluster 2, ergosterol peroxide is able to kill MCF7 by inducing apoptosis [
For the compounds in cluster 4, kaempferol is a phytoestrogen that can suppress triclosan-induced epithelial-mesenchymal transition and metastatic-related behaviors of MCF-7 breast cancer cells [
For the compounds in cluster 5, quercetin can influence the Akt/AMPK/mTOR signaling; thus it has the potential of being anti-breast cancer [
For the compounds in cluster 6, licochalcone B can upregulate the expressions of Caspase 3, Caspase 9, Bax, Cyclin A, Cdk2, Cdc25 A, and so on and downregulate the expression of Bcl-2, p21, and so on to arrest cell cycle progression and induces apoptosis in MCF-7 cells [
However, there are still lots of compounds’ pharmacological effects in DXP that need to be clarified. This analysis may provide some clue, such as important compounds and central targets (genes and proteins), for researchers who want to grope the pharmacological or molecular mechanism of the compounds in whole formula or in each herb.
This network consists of 280 nodes (225 compound target nodes and 55 compound nodes) and 877 edges. The compound-known target network is smaller than the compound-target network. These known targets come from DrugBank and so on and have been reported in the literature. These networks are set up for confirming and supplementing DXP’s effect on ER-positive breast cancer.
Compound-known target-ER-positive breast cancer network is composed of 336 nodes and 5536 edges (Figure
Compound-known target network (blue hexagon stands for known target; the representation of red, orange, yellow, green, blue, and purple circle and blue, green, yellow, orange and red diamonds is the same as Figure
Compound-known target-ER-positive breast cancer network (blue hexagon stands for known target. The representation of red, orange, yellow, green, blue, and purple circle, blue and purple octagon, and blue, green, yellow, orange, and red diamonds is the same as Figure
Analyzing the network by MCODE, eleven clusters are returned (Table
Cluster of known target-breast cancer PPI network.
Cluster | Score | Nodes | Edges | Genes |
---|---|---|---|---|
1 | 44.125 | 49 | 1059 | MAPK8, MMP1, STAT1, HMOX1, F2, AR, PPARG, ICAM1, NOS3, KDR, SRC, MTOR, STAT5B, MAPK14, FOXO3, IGF1, STAT3, CCND1, MAPK1, PGR, EGFR, VEGFA, BCL2L1, CDKN1A, MMP2, IL6, TP53, RAF1, HIF1A, ERBB2, MYC, JUN, IL8, BIRC5, TGFB1, IL2, SERPINE1, CTNNB1, PTEN, FOS, PPARA, JAK2, RELA, ERBB3, ESR1, HSP90AA1, AKT1, BCL2, TNF |
2 | 10 | 10 | 45 | CXCL11, ADRA2A, CHRM2, CXCL2, ADRA2C, OPRM1, CHRM4, ADRA2B, CXCL10, PTGER3 |
3 | 8 | 22 | 84 | ERBB4, CAT, VCAM1, CDK1, BAX, IL1B, CCL2, Quercetin, IL4, SIRT1, RUNX2, GSK3B, HSPB1, INSR, CDK2, PIK3CA, PTGS2, IGFBP3, IL10, CCNB1, RB1, CDK4 |
4 | 3.9 | 21 | 39 | CASP3, HSPA5, WT1, RUNX1, CHEK2, CAV1, AHR, FOSL1, ESR2, MMP3, NCOA3, SLC2A4, PIK3CG, EIF4E, IRF1, MYB, NFKBIA, IKBKB, CHEK1, GJA1, CASP8 |
5 | 3.882 | 18 | 33 | Hederagenin, CALM3, GABRA2, GABRA5, GABRA6, stigmasterol, GABRA3, ADH1B, 1-methoxyphaseollidin, licoricone, CYP1A2, GABRA1, isorhamnetin, KCNH2, GSTM2, XDH, 18103-41-8, KCNMA1 |
6 | 3.429 | 15 | 24 | RXRA, CHRM3, ADRA1A, CYP3A4, NR1I2, ADRA1B, ADRA1D, GSTM1, F10, glabridin, PLAT, HTR2A, CYP2E1, CALM1, CALM2 |
7 | 3.333 | 4 | 5 | CYP1A1, NFE2L2, kaempferol, GSTP1 |
8 | 3 | 15 | 21 | ABCG2, NOS2, MAPK10, HSF1, PLK1, CHUK, TOP2A, CCNA2, NCOR2, IFNG, GATA3, IL1A, HDAC4, TOP1, EZH2 |
9 | 3 | 3 | 3 | PLAU, E2F1, E2F2 |
10 | 3 | 3 | 3 | PPP3CA, PIM1, ACACA |
11 | 3 | 3 | 3 | SLC6A2, ferulic acid, MAOB |
Cluster of compound-known target-ER-positive breast cancer network ((a), (b), (c), (d), and so on stand for clusters 1, 2, 3, 4, and so on. The representation of red, orange, yellow, green, blue, and purple circle, blue and purple octagon, and blue, green, yellow, orange, and red diamonds is the same as Figure
In this analysis, we get several compounds (quercetin, hederagenin, stigmasterol, 1-methoxyphaseollidin, licoricone, isorhamnetin, 18103-41-8, glabridin, kaempferol, and ferulic acid) and several ER-positive breast cancer genes (KDR, BCL2, ESR1, ERBB3, JAK2, MYC, ERBB2, TP53, EGFR, PGR, CCND1, IGF1, FOXO3, STAT5B, MTOR, SRC, PTGS2, SIRT1, CCL2, PIK3CA, ERBB4, ESR2, EIF4E, NCOA3, FOSL1, RUNX1, WT1, MYB, GSTP1, TOP2A, NCOR2, PLK1, EZH2, HDAC4, and GATA3). Most of them are the same as those in the clusters of DXP-ER-positive breast cancer network, which indirectly confirm DXP’s effects.
Deal with these clusters by GO enrichment analysis. Clusters 5, 7, 10, and 11 do not return ER-positive breast cancer-related biological processes. And, after filtering by
Cluster 1 has (GO: 0043066) negative regulation of apoptotic process, (GO: 0008284) positive regulation of cell proliferation, (GO: 0071456) cellular response to hypoxia, (GO: 0050731) positive regulation of peptidyl-tyrosine phosphorylation, (GO: 0008283) cell proliferation, (GO: 0070374) positive regulation of ERK1 and ERK2 cascade, (GO: 0032355) response to estradiol, (GO: 0008285) negative regulation of cell proliferation, (GO: 0001525) angiogenesis, (GO: 0050679) positive regulation of epithelial cell proliferation, (GO: 0000165) MAPK cascade, (GO: 0038128) ERBB2 signaling pathway, (GO: 0018108) peptidyl-tyrosine phosphorylation, (GO: 0043406) positive regulation of MAP kinase activity, (GO: 0043627) response to estrogen, (GO: 0071364) cellular response to epidermal growth factor stimulus, (GO: 0060397) JAK-STAT cascade involved in growth hormone signaling pathway, (GO: 0043536) positive regulation of blood vessel endothelial cell migration, (GO: 0051092) positive regulation of NF-kappaB transcription factor activity, (GO: 0007265) Ras protein signal transduction, (GO: 0048010) vascular endothelial growth factor receptor signaling pathway, (GO: 0050729) positive regulation of inflammatory response, (GO: 0042517) positive regulation of tyrosine phosphorylation of Stat3 protein, (GO: 0043401) steroid hormone mediated signaling pathway, (GO: 0042523) positive regulation of tyrosine phosphorylation of Stat5 protein, (GO: 0060070) canonical Wnt signaling pathway, (GO: 0007179) transforming growth factor beta receptor signaling pathway, (GO: 0007169) transmembrane receptor protein tyrosine kinase signaling pathway, (GO: 0014065) phosphatidylinositol 3-kinase signaling, (GO: 0033209) tumor necrosis factor-mediated signaling pathway, (GO: 0032570) response to progesterone, (GO: 0000186) activation of MAPKK activity, (GO: 0043123) positive regulation of I-kappaB kinase/NF-kappaB signaling, (GO: 0007173) epidermal growth factor receptor signaling pathway, (GO: 0033598) mammary gland epithelial cell proliferation, (GO: 0048009) insulin-like growth factor receptor signaling pathway, (GO: 0030330) DNA damage response, and signal transduction by p53 class mediator.
Cluster 6 has (GO: 0008202) steroid metabolic process, (GO: 0007223) Wnt signaling pathway, calcium modulating pathway, (GO: 0008283) cell proliferation, and (GO: 0043401) steroid hormone mediated signaling pathway.
Analyzing another cluster by the same way, we get the same related biological processes. The details are described in Table
Meanwhile, we get eighteen ER-positive breast cancer-related pathways. They are the same as pathways in Figures
Overall, although the potential anticancer compounds have been shown to have a therapeutic effect on breast cancer, respectively, through this network analysis, this still needs further research. Through this network relationship, we can select the real anticancer compounds in DXP and explore the pharmacological and molecular mechanism of DXP treating ER-positive breast cancer. Through our research, we can find that Ras signaling pathway, MAPK signaling pathway, PI3K/AKT signaling pathway, ErbB signaling pathway, Prolactin signaling pathway, Hippo signaling pathway, HIF-1 signaling pathway, FoxO signaling pathway, and so on may be the focus of the future study of the effect of DXP formula and its compounds (Figures
Pathway of compound-known target-ER-positive breast cancer network (blue circle stands for compound target; red diamond stands for pathway; green hexagon stands for herb).
Currently, SERMs, SERDs, and so on are still the pharmacology options for breast cancer in clinical practice. Our research finds that some of the compounds in DXP may play an anticancer role, such as pachymic acid quercetin, ergosterol peroxide, and licochalcone B. In this study, a number of network-based computational methods and algorithm-based approaches to predict targets, collect known targets, and construct networks are combined to predict, illuminate, and confirm the molecular synergy of DXP for ER-positive breast cancer. This method provides clues to the researcher who explores ethnopharmacological or/and herbal medicine’s or even multidrugs’ various synergies. We also successfully found the potential ER-positive breast cancer associated targets, cluster, biological processes, and pathways. The ER-positive breast cancer network and DXP-ER-positive breast cancer network had shown the probable molecular mechanism of ER-positive breast cancer’s development and the potential pharmacological and molecular mechanism of DXP treating this breast cancer. And the compound-known target-ER-positive breast cancer network confirmed these mechanisms and indirectly proved the rationality of herb combinations of DXP.
Estrogen receptor
Progesterone receptor
Human epidermal growth factor receptor
Selective estrogen receptor modulator
Selective estrogen receptor downregulator
Aromatase inhibitors
Complementary and alternative medicine
Traditional Chinese medicine
Danzhi Xiaoyao powder
Oral bioavailability
Drug-likeness
Protein-protein interaction
Gene Ontology
Estrogen responsive element
Insulin-like growth factor
IGF-1 receptor
Mitogen-activated protein kinase
Signal transducers and activators of transcription
Epidermal growth factor
EGF receptor
Heparin-binding EGF-like growth factor
Insulin receptor substrate
Transforming growth factor
Phosphoinositide 3-kinase
G-protein coupled estrogen receptor
Growth factor receptor
Receptor tyrosine kinase.
Kailin Yang and Liuting Zeng are jointly first authors.
All authors have no financial or scientific conflicts of interest with regard to the research described in this manuscript.
Kailin Yang and Liuting Zeng contributed equally to this work and are jointly first authors. All the authors listed have approved the manuscript that is enclosed.
This work is supported by the National Natural Science Foundation of China (no. 81274008).
Table S1: compound targets for DXP. Table S2: known targets for DXP. Table S3: ER-positive breast cancer targets. Table S4: enrichment analysis of clusters based on Gene Ontology (GO) annotation. Table S5: pathway enrichment analysis. Table S6: enrichment analysis of clusters based on Gene Ontology (GO) annotation. Table S7: pathway enrichment analysis. Table S8: enrichment analysis of clusters based on Gene Ontology (GO) annotation. Table S9: pathway enrichment analysis.