As a kind of traditional Chinese medicine, HQ is widely mentioned in the treatment of cancerous diseases in China, which has been proven to have a therapeutic effect on cancerous diseases, such as prostate cancer. To predict the specific mechanism of HQ in the treatment of CRPC, we will conduct preliminary verification and discussion based on a comprehensive consideration of network pharmacology and molecular docking.
TCMSP was used to obtain the compounds and reach the effective targets of HQ. The targets of CRPC were reached based on GeneCards database and CTD database. GO and KEGG were utilized for the analysis of overlapping targets. The software of Openbabel was used to convert the formats of ligands and reporters. In addition, molecular docking studies were performed by using the software of Autodock Vina.
It can be seen from the database results that there were 87 active compounds (20 key active compounds) in HQ, and 33 targets were screened out for CRPC treatment. GO and KEGG pathway enrichment analyses identified 81 significant GO terms and 24 significant KEGG pathways. There is a difference in terms of the expression of core protein between cancer patients and healthy people. The expression of core protein in patients also has an impact on the life cycle. The results of molecular docking showed that the docking activity of drug molecules and core proteins was better.
It is concluded from the results of this network pharmacology and molecular docking that HQ makes a multi-target and multi-biological process, and results in the multi-channel synergistic effect on the treatment of CRPC by regulating cell apoptosis, proliferation and metastasis, which still needs further verification by experimental research.
Citation: Lin Z, Zhang Z, Ye X, Zhu M, Li Z, Chen Y, et al. (2022) Based on network pharmacology and molecular docking to predict the mechanism of Huangqi in the treatment of castration-resistant prostate cancer. PLoS ONE 17(5): e0263291. https://doi.org/10.1371/journal.pone.0263291
Editor: Yibin Deng, University of Minnesota Medical School Twin Cities, UNITED STATES
Received: June 26, 2021; Accepted: January 17, 2022; Published: May 20, 2022
Copyright: © 2022 Lin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The datasets generated and analysed during the current study are available in the “https://figshare.com/” repository, doi: 10.6084/m9.figshare.13073252; 10.6084/m9.figshare.13073237; 10.6084/m9.figshare.13073222.
Funding: The authors received funding, staff, and equipment support for the following research projects: Fundamental Research Ability Improvement Project for Young and Middle aged Teachers in Guangxi Universities (Natural Science), Agreement No. 2022KY0300. Administration of Traditional Chinese Medicine of Guangxi Zhuang Autonomous Region Self-funded Scientific Research Project (Natural Science), Agreement No. GXZYZ20210346. Health Commission of Guangxi Zhuang Autonomous Region self-funded scientific research project (Youth Fund), Agreement No. Z20211659. Natural Science Research Project of Guangxi University of Traditional Chinese Medicine (Youth Fund), Agreement No. 2021QN029.
Competing interests: The authors have declared that no competing interests exist.
Prostate cancer (PCa) ranks the second among the most common malignancies diagnosed in men. It was the third largest source of cancer-related deaths across the world in 2018, with 1,276,106 new cases annually and 358,989 deaths . According to the data of 2016, the incidence of prostate cancer was 6.25%, which was the fifth most prevalent cancer across the world. The number of PCa cases increased from 1.0 million in 2006 to 1.4 million in 2016. The expected population growth rate is the function of rain-on-snow (ROS), density, and age structure, with the cases correlated with population growth rate and age structure . This number is likely to continue to increase with the growth and aging of the population. The incidence of prostate cancer showed a remarkable increase among Chinese between 2010 and 2014, and prostate cancer was one of the fastest growing malignancies in China, and the sixth most prevalent cancer in Chinese . A majority of Chinese PCa patients develop regionally advanced disease or widespread metastases. The patients with extensive metastases who are unable to be treated with radical surgery can only receive endocrine treatment and chemotherapy . The treatment methods, such as endocrine treatment and antiandrogen treatment blocking androgens produced by the adrenal glands are able to control and improve the condition of most patients. However, after the remission period (the median period of remission period is between 14 and 30 months), most patients will enter the castrate-resistant stage, and develop into castration-resistant prostate cancer (CRPC) . CRPC is divided into two types, i.e., the metastatic castration-resistant prostate cancer (mCRPC) and non-metastatic castration-resistant prostate cancer (nmCRPC). The progress of metastases of nmCRPC can be delayed by using apalutamide and enzalutamide approved by the US Food and Drug Administration, but the disease will eventually develop to mCRPC  which is mostly treated with docetaxel, abiraterone, prednisolone, enzalutamide, cabazitaxel and radium 223. After radical prostatectomy, adverse reactions may occur, such as decreased sexual satisfaction and voiding dysfunction. Radiotherapy patients are under the risk of second cancers. Totally 93% of patients after androgen deprivation treatment (ADT) experienced a decrease in sexual desire, as well as a decrease in the quality of life and local dysfunction . Long-term ADT and chemotherapy are likely to cause adverse reactions, such as fatigue, hot flashes, muscle weakness, decreased libido, neutropenia, and vomiting . Chinese herbal medicine is widely utilized in adjuvant endocrine therapy. A meta-analysis shows that this method is available for the improvement of the efficacy of adjuvant endocrine therapy without adverse reactions. However, due to the lack of uniform assessment criterion and poor methodologies, the clinical application value of Chinese herbal medicine has to be explored . Chinese herbal medicine HQ has been proved by many studies to have various effects, such as anti-proliferation, pro-apoptosis, improvement of immune function, prevention of tumor metastasis, etc.  Astragalus (HQ) injection has an effect on breast cancer cell proliferation and Akt phosphorylation . In addition, Astragalus (HQ) extract inhibits the destruction of gastric cancer cells into mesothelial cells through anti-apoptosis . In our domestic research, the active ingredients of HQ were found to have an effect on the proliferation and apoptosis of prostate cancer cell line PC3 cells, and be able to inhibit the proliferation of prostate cancer cell line PC3 cells and induce their apoptosis . This indicates that HQ and its active ingredients have the effects on the regulation of proliferation and apoptosis in the treatment of cancer diseases, including prostate cancer. The Chinese medicine compound containing Huangqi shows a good effect on the treatment of CRPC, prolonging the survival period of patients, and improving symptoms and the quality of life. On the other hand, the Chinese medicine compound mentioned above can also increase the anticancer activity of docetaxel , therefore, we suspected that HQ has the similar effects on CRPC disease. In that case, we plan to predict the mechanism of action and target by using network pharmacology and molecular docking, so as to provide a basis for the subsequent experimental research.
Materials and methods
1.1 Bioactive ingredient and target identification for Huangqi (HQ)
The Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP)  is a platform for the integration of pharmacokinetics, medicinal chemistry, and drug-target-disease networks. We followed the methods of Jing Zhang et al. 2020 . Based on to the TCMSP platform (http://lsp.nwu.edu.cn/tcmsp.php), the bioactive ingredients (OB) and targets of HQ were obtained. The former refers to the rate and extent of the absorption of the drug into the body’s circulation. Drug-like properties (DL) reflect the nature of a drug with a specific functional group or the same or similar physical characteristics. Bioactive ingredients were collected under the condition of OB≥30% and DL≥0.18. After that, the corresponding molecular targets of these collected active compounds were obtained by using the same database.
1.2 Target prediction of HQ in the treatment of CRPC
Search for CRPC-related targets with “castration-resistant prostate cancer” as a search term by using GeneCards database (https://www.genecards.org/) and the Comparative Toxicogenomics Database (CTD, ctd.mdibl.org). Venny2.1.0 (http://bioinfogp.cnb.csic.es/tools/venny/index.html) was employed to construct over-lapping targets for CRPC treatment and bioactive ingredients of HQ, allowing the identification of targets of HQ in the treatment of CRPC.
1.3 Construction and topological properties of compound-target networks
Compound–target networks were constructed by using the software of Cytoscape 3.7.2. The nodes degree centrality and corresponding closeness centrality obtained from compound-target networks were topologically analyzed to identify the key compounds and targets.
1.4 PPI networks of overlapping targets construction
The STRING database  (https://string-db.org/) can be used for the analysis of the interaction between proteins. In our study, the species was limited to “Homo sapiens”, and the lowest interaction score was set to medium confidence (0.400). After obtaining the PPI networks from the STRING database, Cytoscape software was utilized for further topology analysis. Finally, the node size and colour were adjusted with the software of Cytoscape to construct the complete PPI networks of overlapping targets, so as to clarify the key regulatory proteins functioned in the networks.
1.5 GO terms and KEGG pathway enrichment analysis
The Database for Annotation, Visualization, and Integrated Discovery (DAVID, https://david.ncifcrf.gov/) database  was utilized to perform Gene ontology (GO) and Kyoto encyclopedia of genes and genome (KEGG) pathway enrichment analysis. The GO terms were classified into three categories, i.e., biological process (BP), cellular component (CC) and molecular function (MF). The condition of P<0.01 was considered to indicate a statistically significant difference.
1.6 Immunohistochemical comparison and survival analysis of core targets
The immunohistochemical images of core targets were screened from The Human Protein Atlas (https://www.proteinatlas.org/) database, after that, the expressions of these targets in prostate tissues of cancer patients and normal people were compared. The cBioportal For Cancer Genomic (https://www.cbioportal.org/) database is used for the survival analysis to analyze the impact of changes in core targets on the prognosis of cancer patients.
1.7 Molecular docking simulation
Select corresponding ligands obtained from TCMSP database and receptors performed in the Protein Data Bank database (PDB, https://www.rcsb.org/) for molecular docking based on the compound-target network relationship. Respectively, the software of Openbabel and AutoDock Vina were used for chemical format conversion and molecular docking. The active sites of the cocrystal ligands were used as the pockets of receptors for molecular docking. The interaction of the compounds with the lowest binding free energy was analyzed on the Biotechnology Center of the TU Dresden (BIOTEC, https://projects.biotec.tu-dresden.de) platform [19–21].
2.1 Collection and screening of candidate active compounds in HQ
The molecular structure of each active compound was confirmed based on the TCMSP database, and then 87 compounds of HQ were retrieved. According to the criteria of OB≥30% and DL≥0.18, a total of 20 chemical ingredients were selected (as shown in Table 1).
2.2 Screening of overlapping targets
CTD and GeneCards databases were employed for the prediction of the potential targets for CRPC. Totally 2294 target genes from the CTD database and 1213 target genes from the GeneCards database were verified to be involved in CRPC. According to “Inference Score” and “Relevance score”, the top 200 results with the highest correlation in the CTD database and the top 200 results in Genecards database were obtained, respectively. 114 corresponding targets of active compounds in HQ were screened by using TCMSP database. The targets obtained above were uploaded to the Venny2.1.0 website, then the 33 overlapping targets were confirmed (as shown in Fig 1).
2.3 Construction of the compound–target network of HQ and CRPC
By analyzing the overlapping targets, only 16 compounds were found to be related to CRPC. After importing data into Cytoscape, a compound–target network was constructed (as shown in Fig 2). The parameters of the core compounds and targets involved were shown in Table 2.
The Compound-target network of HQ. The blue circle is the compound and the purple triangle is the target protein.
2.4 Constructing PPI network of the overlapping targets
The STRING database and the software of Cytoscape were used for the construction of the PPI network (as shown in Fig 3). The size and colour of the nodes represent the degree value, and the larger the size and the darker the colour, the greater the relative degree of the node. "Edge" represents the combined score, and the thicker edge represents the greater combined score. These nodes include AHR, CDK2, ESR1, ESR2, HSP90AA1, HSPA5, KDR, PGR, PPARG, TP53, AKR1C3, AR, BCL2, CCL2, EGF, EGFR, GSTP1, IL6, JUN, MAPK1, MET, MMP2, PTGS2, RB1, VEGFA, CCNA2, CYP1A2, CYP3A4, F3, IL1B, NCOA1, NQO1 and VCAM1.
2.5 Go and KEGG pathway enrichment analysis
We performed Go and KEGG enrichment analysis by using the DAVID database. Totally 20 items related with Biological process (BP), 5 items related with Molecular function (MF) and 56 items related with Cellular component (CC) were obtained, after Go enrichment analysis (p-value<0.05) (as shown in Fig 4 and Table 3). After that, 24 pathways were obtained after KEGG enrichment analysis (p-value<0.01). We uploaded the result of KEGG enrichment analysis to Omicshare (https://www.omicshare.com/) website, and then we got the Advanced Bubble Chart (Fig 5). The path of prostate cancer model in KEGG was shown in the figure (Fig 6).
33 overlapped genes were analysis by GO annotation. BP/CC/MF are all shown in the figure, the specific meaning can be seen in the text under the bar graph.
33 overlapped genes was analysis by KEGG, which enriched in 24 pathways. The darker the color, the greater the weight, and the larger the circle, the greater the genenumber.
Prostate cancer pathway information generated by KEGG. The highlighted part of the pathways and protein nodes related to this research.
2.6 Immunohistochemistry and survival analysis
The Human Protein Atlas database showing the expressions of these targets in prostate tissues of cancer patients and normal people is different. Prostate tumor and normal prostate tissues show elevated AR expression instead of ESR1 expression. Though normal prostate tissues show no HSP90AA1 expression, in prostate tumor tissues, the gene is weakly expressed or not expressed. PPARG gene is not expressed in normal prostate tissues but weakly expressed or not expressed in prostate tumor tissues. Normal prostate tissues show elevated PTGS2 expression, but prostate tumor tissues show elevated expression or no expression (as shown in Fig 7). It can be seen from the results that most of these core proteins change in prostate tissue after having cancer. We further used the existing cancer database (https://www.cbioportal.org/) for survival analysis for five core proteins (as shown in Fig 8). The blue line in the figure indicates the survival of prostate cancer patients whose targets have not changed. These prostate cancer patients have survived for more than 200 months. Non-blue lines show the changes in the survival of prostate cancer patients with changed targets. The results show that regardless of the effect of a single target or five core targets, the average survival of patients is less than 160 months (P<0.0001). We performed a survival analysis of the AR gene using cancer database (https://www.cbioportal.org/) (Fig 9) (Querying 6875 patients / 7161 samples in 22 studies). It can be seen from the results that whether the AR gene is changed or not has a significant impact on the life cycle of Pa patients (P<0.05).
The expressions of 5 targets in prostate tissues of cancer patients and normal people.
Survival analysis involves five core proteins. The blue line in the figure indicates the survival of prostate cancer patients whose targets had not changed. Non-blue lines show changes in the survival of prostate cancer patients with changed targets.
Survival analysis involves AR gene. The blue line in the figure indicates the survival of prostate cancer patients whose targets had not changed. Non-blue lines show changes in the survival of prostate cancer patients with changed targets.
2.7 Molecular docking simulation
The top five targets in Degree of PPI network were utilized for molecular docking. The molecular docking scores of PTGS2, HSP90AA1, AR, PPARG and ESR1 are as follows (as shown in Table 4). According to the results, the active compounds could produce active binding with the core targets.
We selected the compounds with the lowest score of Vina in the docking (as shown in Fig 10) for further analysis. The results show that, from the perspective of spatial structure, small drug molecules are located in the active sites where the cocrystal ligands are located. In addition, there are multiple hydrophobic interactions, atom binding site and hydrogen bonding between small drug molecules and protein residues.
Prostate cancer is a common malignant tumor in male genito-urinary system. There is currently no way to prevent the disease, and there are many side effects in the treatments . In the United States, although most cases are diagnosed early, some cases will still manifest or proceed into metastatic diseases and eventually develop metastatic castration-resistant prostate cancer. Metastatic prostate cancer is a global disease with a high incidence, and the median survival of patients with mCRPC is less than two years with their mortality rate exceeding 50%. In contrast, few treatments are able to delay the progression of nmCRPC to mCRPC, or delay the time for patients with nmCRPC to be treated with cytotoxic chemotherapy. Although there are many drugs for the patients to choose from, the sad fact is that mCRPC is an incurable disease. The existing drugs have little effect on the survival rate of patients with CRPC [23,24], therefore, we have to find new treatments or combined treatments to improve the curative effect, and reduce the side effects of the treatment to extend the patient’s life cycle and improve the patient’s quality of life. The researches on network pharmacology and verification measures of molecular docking emerged in recent years have provided us with the possibility to find new treatments.
The objects studied in this paper include the HQ and its extracts which play an anti-tumor role through multicellular pathways in breast cancer, gastrointestinal cancer and ovarian cancer [25–27]. MOL000098 (quercetin), MOL000422 (kaempferol), MOL000442 (1,7-Dihydroxy-3,9-dimethoxy pterocarpene), MOL000417 (Calycosin), MOL000392 (formononetin), MOL000379 (9,10-dimethoxypterocarpan-3-O-β-D-glucoside), MOL000378(7-O-methylisomucronulatol), MOL000371 (3,9-di-O-methylnissolin), MOL000354 (isorhamnetin) are flavonoids which are available to inhibit the production of fatty acids in cancer cells, and have cancer cell toxicity [28,29]. The results of Liquid Chromatography Analysis suggested that flavonoids and saponins were the main active substances of HQ [30,31]. Quercetin with the effect of antitumor proliferation may cause tumor cell apoptosis by regulating mitochondrial cytochrome C, which can also inhibit the production of cancer stem cells causing cancer to recur . Calycosin enhances the effect of TGF-β on apoptosis, which can inhibit the proliferation of cancer cells through WDR7-7-GPR30 signaling [33,34]. Formononetin can induce prostate cancer transformation through the ERK1/2 MAPK-Bax pathway , which can also inhibit the G1 cell cycle by inactivating Akt/cyclin D1/CDK4, making it exhibit inhibitory activity on human prostate cancer cells both in vivo and in vitro . Isorhamnetin can selectively inhibit the PI3K–Akt–mTOR pathway, which can inhibit overexpression of matrix metalloproteinase 2 (MMP-2) and MMP-9, as well as the cell migration and invasion in a concentration-dependent manner. These findings suggest that Isorhamnetin has therapeutic potential in androgen-independent prostate cancer . MOL000433 (FA) is a phenolic compound with the functions of antioxidant, antibacterial, anti-allergen, anti-inflammatory, anti-hypoglycemia, anti-pathogenicity and anti-virus. FA can reduce the expression of genes causing cell cycle arrest in the G1/S phase of prostate cancer cells by enhancing the cellular response of prostate cancer cell lines, resulting in cell cycle arrest. In experimental studies, it was found that the expression of tumor suppressor genes and apoptosis genes in prostate cancer cells after FA treatment increased significantly. On the contrary, the gene expression of anti-apoptotic protein BCL2 was significantly reduced, indicating that FA has apoptotic activity on prostate cancer cells . MOL000387 (Bifendate) is also called Mairin (Betulinic acid). BA is able to prevent the growth of various human cancer cells by changing the key signaling pathways involved in apoptosis, which may induce apoptosis by stabilizing p53 in human prostate cancer cells and down-regulating the NF-κB pathway . Other active compounds have not been reported to have an effect on tumor diseases. Though they may have an effect of anti-tumor, further research is still necessary. Through the analysis of prostate cancer pathways, the main pathways include P13-Aktsignal pathway, P53 and MAPK signal pathway. P13K-Aktsignal pathway is related to various cancers, such as PCa [40–43]. As one of the most important tumor suppressor genes, P53 has the potential to resist apoptosis of PCa cells, and its functional status is important in the progress of PCa. The P53 with a higher mutation rate has more mutations in advanced metastatic PCa. This mutation not only seriously destroys the function of P53 protein, but also reduces the disease-free survival of patients [44–46]. The mutation of TP53 is also active in CRPC, which is related to the poor prognosis of CRPC . The RAS-MAPK signaling pathway with therapeutic potential in CRPC involves a wide range of cellular processes, including differentiation, proliferation and survival. Besides, RAS-MAPK has become a key pathway for human cancer. In many human cancers, the abnormal activation of RAS-MAPK has an important carcinogenic effect [48,49].
The core targets involved in this study include PTGS2, HSP90AA1, AR, PPARG and ESR1. PTGS2 produces inflammatory prostaglandins, and the upregulation of PTGS2 is associated with the increase of cell adhesion, phenotypic changes, resistance to apoptosis and tumor angiogenesis. PTGS2 related to the proliferation, invasion, apoptosis, host immune response and angiogenesis of malignant tumors as well as tumor radioresistance is associated with the growth and survival of PCa, which has been shown to be overexpressed in malignant tumors . Increased COX-2 expression occurs in high-grade PCa . HSP90AA1 is expressed highly in most cancers, but poorly in prostate cancer tissue . Besides, its mechanism of action in prostate cancer has to be further studied. Almost all prostate cancer cells depend on androgen and AR signals which are closely related to prostate development. Experimental studies have shown that long-term exposure to high or low systemic androgens can increase the incidence of prostate cancer . The occurrence and development of CRPC mainly depend on androgen-androgen receptor signaling pathway . And 40% to 60% of mCRPC patients have AR, DNA mismatch repair, PI3K and other gene mutations . By further research on the pathogenesis of CRPC, it is found that AR available to drive tumor progression is still the key factor to promote the occurrence and development of CRPC, therefore, androgen deprivation therapy remains the basic means to control the occurrence and development of CRPC . In clinical investigations, it was found that the lack of PPARG (PPARγ) might be related to the development of PCa . PARG and PRKAR2B genes may act as the potential biomarkers for the treatment of PCa . The activity of PPARγ is related to the occurrence and development of prostate cancer. Besides, the inhibition of the expression of PPARγ may have a preventive and therapeutic effect on prostate cancer. Therefore, some scholars have identified PPARγ as an important new therapeutic target for prostate cancer . ESR1 has the effects of stimulating abnormal prostate growth, controlling prostate cell growth and programming prostate cell death, and these effects are associated with prostate cancer susceptibility. Some meta-analyses suggest that ESR1 polymorphisms may increase the risk of prostate cancer in American and Indian populations . These studies indicate that core targets play a role in prostate cancer and CRPC. According to the survival analysis, the survival time of prostate cancer patients with changed core targets was shortened accordingly. It can be seen that these targets play an important role in the progression of prostate cancer, and interventions to these targets may lead to a positive effect on the improvement of the prognosis of patients with prostate cancer. The results of molecular docking and interaction analysis exhibit good docking activity, therefore, the results of this molecular docking simulation are of reference value for the development of CRPC drugs.
This study reveals the pharmacological mechanism of HQ in the treatment of CRPC at the system level through network pharmacology. We speculate that the active ingredients of the drug have a curative effect on the regulation of the proliferation, apoptosis and metastasis of prostate cancer cells. Network pharmacological analysis and molecular docking verification show that HQ has a potential therapeutic effect on the treatment and control of prostate cancer, and it also has the potential to delay the late conversion of the disease into CRPC. However, the traditional Chinese medicine HQ has a multi-target and multi-level regulation effect. This research only studied the pharmacological effects on the micro level, and these results have to be further confirmed by experimental research. Due to the fact that this research is mainly carried out at the theoretical level, in the later stage, the research group will purify key compounds, explore the appropriate therapeutic concentration, and conduct animal experiments as well as clinical trials around pharmacokinetics and pharmacodynamics, thereby providing the theoretical and practical basis.
- 1. Bray Freddie, Ferlay Jacques, Soerjomataram Isabelle, Siegel Rebecca L, Torre Lindsey A, Jemal Ahmedin. Global cancer statistics 2018:GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin. 2018 Nov;68(6):394–424. pmid:30207593
- 2. Global Burden of Disease Cancer Collaboration, Fitzmaurice C, Akinyemiju TF, et al. Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life-years for 29 cancer groups, 1990 to 2016: A systematic analysis for the Global Burden of Disease Study. JAMA Oncol, 2018, 4 (11): 1553–1568. pmid:29860482
- 3. CHEN W, SUN K, ZHENG R, et al. Cancer incidence and mortality in China,2014[J].Chin J Cancer Res, 2018, 30(1):1–12. DOI: pmid:29545714
- 4. Chen W, Zheng R, Baade PD, et al. Cancer statistics in China, 2015. CA Cancer J Clin, 2016, 66 (2): 115–132. pmid:26808342
- 5. Mateo J, Fizazi K, Gillessen S, et al. Managing Nonmetastatic Castration-resistant Prostate Cancer. Eur Urol. 2019 Feb;75(2):285–293. pmid:30119985
- 6. El-Amm J, Aragon-Ching JB. The Current Landscape of Treatment in Non-Metastatic Castration-Resistant Prostate Cancer. Clin Med Insights Oncol. 2019 Mar 7;13:1179554919833927. pmid:30872920
- 7. Mottet N, Bellmunt J, Bolla M, Briers E, Cumberbatch MG, De Santis M, et al. EAU-ESTRO-SIOG Guidelines on Prostate Cancer. Part 1: Screening, Diagnosis, and Local Treatment with Curative Intent. Eur Urol. 2017 Apr;71(4):618–629. Epub 2016 Aug 25. https://www.ncbi.nlm.nih.gov/pubmed/27568654. pmid:27568654
- 8. Greasley RU, Turner R, Collins K, Brown J, Bourke L, Rosario DJ. Treatment in the STAMPEDE era for castrate resistant prostate cancer in the UK: ongoing challenges and underappreciated clinical problems. BMC Cancer. 2018 Jun 19;18(1):667. pmid:29914436
- 9. Cao Huijuan, Mu Yujie, Li Xun Wang Yuyi, Chen Shiuan, Liu Jian-Ping. A Systematic Review of Randomized Controlled Trials on Oral Chinese Herbal Medicine for Prostate Cancer.PLoS One. 2016 Aug 4;11(8):e0160253. pmid:27490098
- 10. Li S, Sun Y, Huang J, Wang B, Gong Y, Fang Y, et al. Anti-tumor effects and mechanisms of Astragalus membranaceus (AM) and its specific immunopotentiation: Status and prospect. J Ethnopharmacol. 2020 Mar 31:112797. pmid:32243990
- 11. Deng Ying, Chen Hong-feng. Effects of Astragalus injection and its ingredients on proliferation and Akt phosphorylation of breast cancer cell lines. Zhong Xi Yi Jie He Xue Bao. 2009 Dec;7(12):1174–80. pmid:20015441
- 12. Na Di, Liu Fu-Nan, Miao Zhi-Feng, Du Zong-Min, Xu Hui-Mian. Astragalus extract inhibits destruction of gastric cancer cells to mesothelial cells by anti-apoptosis. World J Gastroenterol. 2009 Feb 7;15(5):570–7. pmid:19195058
- 13. Weizhen Bu, Peng Liu, Haiyang Kuai, Jianjun Pang, Zhifang Ma. Effect of astragalus polysaccharide on proliferation and apoptosis of prostate cancer cell line PC3. Chinese Remedies & Clinics. 2019,19(16),2707–2709. CNKI:SUN:YWLC.0.2019-16-002.
- 14. Fu W, Hong Z, You X, et al. Enhancement of anticancer activity of docetaxel by combination with Fuzheng Yiliu decoction in a mouse model of castration-resistant prostate cancer. Biomed Pharmacother. 2019 Oct;118:109374. pmid:31545228
- 15. Ru J, Li P, Wang J, et al. TCMSP: a database of systems pharmacology for drug discovery from herbal medicines. J Cheminform. 2014;6:13. pmid:24735618
- 16. Zhang J., Huang Q., Zhao R. et al. A network pharmacology study on the Tripteryguim wilfordii Hook for treatment of Crohn’s disease. BMC Complement Med Ther 20, 95 (2020). pmid:32293395
- 17. von Mering C, Jensen LJ, Snel B, et al. STRING: known and predicted protein-protein associations, integrated and transferred across organisms. Nucleic Acids Res. 2005;33:D433–7. pmid:15608232
- 18. Dennis GJ, Sherman BT, Hosack DA, et al. DAVID: database for annotation, visualization, and integrated discovery. Genome Biol. 2003;4:P3. pmid:12734009
- 19. O’Boyle NM, Banck M, James CA, Morley C, Vandermeersch T, Hutchison GR. Open Babel: An open chemical toolbox. J Cheminform. 2011 Oct 7;3:33. pmid:21982300
- 20. The Open Babel Package, version 2.3.1 http://openbabel.org (accessed Oct 2011).
- 21. Trott O1, Olson AJ. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem. 2010 Jan 30;31(2):455–61. pmid:19499576
- 22. Torre LA, Siegel RL, Ward EM, Jemal A. Global Cancer Incidence and Mortality Rates and Trends—An Update. Cancer Epidemiol Biomarkers Prev. 2016 Jan;25(1):16–27. pmid:26667886
- 23. Handy CE, Antonarakis ES. Sequencing Treatment for Castration-Resistant Prostate Cancer. Curr Treat Options Oncol. 2016 Dec;17(12):64. pmid:27822685
- 24. Lowrance WT, Murad MH, Oh WK, Jarrard DF1, Resnick MJ, Cookson MS. Castration-Resistant Prostate Cancer: AUA Guideline Amendment 2018. J Urol. 2018 Dec;200(6):1264–1272. pmid:30086276
- 25. Guo Y, Zhang Z, Wang Z, Liu G, Liu Y, Wang H. Astragalus polysaccharides inhibit ovarian cancer cell growth via microRNA-27a/FBXW7 signaling pathway. Biosci Rep. 2020 Mar 27;40(3). pmid:32159214
- 26. Yang S, Sun S, Xu W, Yu B, Wang G, Wang H. Astragalus polysaccharide inhibits breast cancer cell migration and invasion by regulating epithelial mesenchymal transition via the Wnt/β catenin signaling pathway. Mol Med Rep. 2020 Feb 12. pmid:32319619
- 27. Auyeung KK, Han QB, Ko JK. Astragalus membranaceus: A Review of its Protection Against Inflammation and Gastrointestinal Cancers. Am J Chin Med. 2016;44(1):1–22. pmid:26916911
- 28. Hertog M G, Feskens E J, Hollman P C, Katan M B, Kromhout D. Dietary flavonoids and cancer risk in the Zutphen Elderly Study [J]. Nutr Cancer, 1994, 22(2): 175. pmid:14502846
- 29. Brusselmans 1 Koen, Vrolix Ruth, Verhoeven Guido, Swinnen Johannes V. Induction of cancer cell apoptosis by flavonoids is associated with their ability to inhibit fatty acid synthase activity [J]. J Biol Chem, 2005, 280(7): 5636. pmid:15533929
- 30. Peng HS, Wang J, Zhang HT, Duan HY, Xie XM, Zhang L, et al. Rapid identification of growth years and profiling of bioactive ingredients in Astragalus membranaceus var. mongholicus (Huangqi) roots from Hunyuan, Shanxi. Chin Med. 2017 May 19;12:14. pmid:28533813
- 31. Yin M, Yang M, Chu S, Li R, Zhao Y, Peng H, et al. Quality Analysis of Different Specification Grades of Astragalus membranaceus var. mongholicus (Huangqi) from Hunyuan, Shanxi. J AOAC Int. 2019 May 1;102(3):734–740. pmid:31027520
- 32. Ezzati Maryam, Yousefi Bahman, Velaei Kobra, Safa Amin. A review on anti-cancer properties of Quercetin in breast cancer [J]. Life Sci, 2020, 248: 117463. pmid:32097663
- 33. Wang Qun, Lu Weijun, Yin Tao, and Lu Li. Calycosin suppresses TGF-β-induced epithelial-to-mesenchymal transition and migration by upregulating BATF2 to target PAI-1 via the Wnt and PI3K/Akt signaling pathways in colorectal cancer cells. J Exp Clin Cancer Res. 2019; 38: 240. pmid:31174572
- 34. Tian J, Wang Y, Zhang X, Ren Q, Li R, Huang Y, et al. Calycosin inhibits the in vitro and in vivo growth of breast cancer cells through WDR7-7-GPR30 Signaling. J Exp Clin Cancer Res. 2017 Nov 2;36(1):153. pmid:29096683
- 35. Ye Y, Hou R, Chen J, Mo L, Zhang J, Huang Y, Mo Z. Formononetin-induced apoptosis of human prostate cancer cells through ERK1/2 mitogen-activated protein kinase inactivation. Horm Metab Res. 2012 Apr;44(4):263–7. pmid:22328166
- 36. Li T, Zhao X, Mo Z, Huang W, Yan H, Ling Z, Ye Y. Formononetin promotes cell cycle arrest via downregulation of Akt/Cyclin D1/CDK4 in human prostate cancer cells. Cell Physiol Biochem. 2014;34(4):1351–8. pmid:25301361
- 37. Cai F, Zhang Y, Li J, Huang S, Gao R. Isorhamnetin inhibited the proliferation and metastasis of androgen-independent prostate cancer cells by targeting the mitochondrion-dependent intrinsic apoptotic and PI3K/Akt/mTOR pathway. Biosci Rep. 2020 Mar 27;40(3). pmid:32039440
- 38. Eroğlu C, Seçme M, Bağcı G, Dodurga Y. Assessment of the anticancer mechanism of ferulic acid via cell cycle and apoptotic pathways in human prostate cancer cell lines. Tumour Biol. 2015 Dec;36(12):9437–46. pmid:26124008
- 39. Shankar E, Zhang A, Franco D, Gupta S. Betulinic Acid-Mediated Apoptosis in Human Prostate Cancer Cells Involves p53 and Nuclear Factor-Kappa B (NF-κB) Pathways. Molecules. 2017 Feb 10;22(2). pmid:28208611
- 40. Shankar S, Ganapathy S, Srivastava RK. Sulforaphane enhances the therapeutic potential of TRAIL in prostate cancer orthotopic model through regulation of apoptosis, metastasis, and angiogenesis. Clin Cancer Res. 2008 Nov 1;14(21):6855–66. pmid:18980980
- 41. Zhao X, Feng P, He W, Du X, Chen C, Suo L, et al. The Prevention and Inhibition Effect of Anthocyanins on Colorectal Cancer. Curr Pharm Des. 2019;25(46):4919–4927. pmid:31830892
- 42. Gao H, Wang H, Peng J. Hispidulin induces apoptosis through mitochondrial dysfunction and inhibition of P13k/Akt signalling pathway in HepG2 cancer cells. Cell Biochem Biophys. 2014 May;69(1):27–34. pmid:24068521
- 43. Xu J, Li Z, Su Q, Zhao J, Ma J. TRIM29 promotes progression of thyroid carcinoma via activating P13K/AKT signaling pathway. Oncol Rep. 2017 Mar;37(3):1555–1564. pmid:28098872
- 44. Hong B, van den Heuvel AP, Prabhu VV, Zhang S, El-Deiry WS1. Targeting tumor suppressor p53 for cancer therapy: strategies, challenges and opportunities. Curr Drug Targets. 2014 Jan;15(1):80–9. pmid:24387333
- 45. Chappell WH1, Lehmann BD, Terrian DM, Abrams SL, Steelman LS, McCubrey JA. p53 expression controls prostate cancer sensitivity to chemotherapy and the MDM2 inhibitor Nutlin-3. Cell Cycle. 2012 Dec 15;11(24):4579–88. pmid:23187804
- 46. Li J, Li Y, Chen L, Yu B, Xue Y, Guo R, Su J, Liu Y, Sun L. p53/PGC 1α mediated mitochondrial dysfunction promotes PC3 prostate cancer cell apoptosis. Mol Med Rep. 2020 May 5. pmid:32377739
- 47. Maughan BL, Guedes LB, Boucher K, Rajoria G, Liu Z, Klimek S, et al. p53 status in the primary tumor predicts efficacy of subsequent abiraterone and enzalutamide in castration-resistant prostate cancer. Prostate Cancer Prostatic Dis. 2018 Jun;21(2):260–268. pmid:29302046
- 48. Li S, Fong KW, Gritsina G, Zhang A, Zhao JC, Kim J, et al. Activation of MAPK Signaling by CXCR7 Leads to Enzalutamide Resistance in Prostate Cancer. Cancer Res. 2019 May 15;79(10):2580–2592. Epub 2019 Apr 5. pmid:30952632
- 49. Masliah-Planchon J, Garinet S, Pasmant E. RAS-MAPK pathway epigenetic activation in cancer: miRNAs in action. Oncotarget. 2016 Jun 21;7(25):38892–38907. DOI: pmid:26646588
- 50. King L, Christie D, Arora D, Anoopkumar-Dukie S. Cyclooxygenase-2 inhibitors delay relapse and reduce Prostate Specific Antigen (PSA) velocity in patients treated with radiotherapy for nonmetastatic prostate cancer: a pilot study. Prostate Int. 2020 Mar;8(1):34–40. pmid:32257976
- 51. Shappell SB, Manning S, Boeglin WE, Guan YF, Roberts RL, Davis L, et al. Alterations in lipoxygenase and cyclooxygenase-2 catalytic activity and mRNA expression in prostate carcinoma. Neoplasia. 2001 Jul-Aug;3(4):287–303. pmid:11571629
- 52. Chen W, Li G, Peng J, Dai W, Su Q, He Y. Transcriptomic analysis reveals that heat shock protein 90α is a potential diagnostic and prognostic biomarker for cancer. Eur J Cancer Prev. 2019 Sep 26. pmid:31567483
- 53. Zhou Y, Bolton EC, Jones JO. Androgens and androgen receptor signaling in prostate tumorigenesis. J Mol Endocrinol. 2015 Feb;54(1):R15–29. pmid:25351819
- 54. Logothetis Christopher J, Gallick Gary E, Maity Sankar N, Kim Jeri, Aparicio Ana, Efstathiou Eleni, et al. Molecular classification of prostate cancer progression:foundation for marker-driven treatment of prostate cancer[J].Cancer Discov, 2013, 3 (8):849–861. pmid:23811619
- 55. Robinson D, Van Allen EM, Wu YM, et al. Integrative clinical genomics of advanced prostate cancer[J].Cell, 2015, 162 (2):454. pmid:28843286
- 56. Wang Keshan, Ruan Hailong, Xu Tianbo, Liu Lei, Liu Di, Yang Hongmei, et al. Recent advances on the progressive mechanism and therapy in castration-resistant prostate cancer[J].Onco Targets Ther,2018,11:3167–3178. pmid:29881290
- 57. Lin SJ, Yang DR, Wang N, Jiang M, Miyamoto H, Li G, et al. TR4 nuclear receptor enhances prostate cancer initiation via altering the stem cell population and EMT signals in the PPARG-deleted prostate cells. Oncoscience. 2015 Feb 9;2(2):142–50. eCollection 2015. pmid:25859557
- 58. Fang E, Zhang X, Wang Q, Wang D. Identification of prostate cancer hub genes and therapeutic agents using bioinformatics approach. Cancer Biomark. 2017 Dec 6;20(4):553–561. pmid:28800317
- 59. Elix C, Pal SK, Jones JO. The role of peroxisome proliferator-activated receptor gamma in prostate cancer. Asian J Androl. 2018 May-Jun;20(3):238–243. pmid:28597850
- 60. Wang Yu-Mei, Liu Zu-Wang, Guo Jing-Bo, Wang Xiao-Fang, Zhao Xin-Xin, and Zheng Xuan. ESR1 Gene Polymorphisms and Prostate Cancer Risk: A HuGE Review and Meta-Analysis. PLoS One. 2013 Jun 21;8(6):e66999. DOI: pmid:23805288