Network-pharmacology and molecular docking-based investigation of mechanism of Sophora flavescens on cancer and inflammation

Wenxuan Li,Lijuan Deng,Yuhe Lei,Junshan Liu

1 School of Traditional Chinese Medicine,Southern Medical University,Guangzhou 510515,P.R.China

2 Formula pattern Research Center, School of Traditional Chinese Medicine, Jinan University,Guangzhou 510632,P.R.China

3 Department of Pharmacy, Shenzhen Hospital of Guangzhou University of Chinese Medicine,Shenzhen,518034,P.R.China

Abstract

Keywords:Network-pharmacology,Molecular docking,Sophora flavescens,Cancer,Inflammation

Background

Cancer has been threatening human's life for a long time.According to the statistics, The increase in cancer incident cases have been incredibly reached to 52%over the recent decade and the majority of cancer disability-adjusted life-years came from years of life lost, and only 3% came from years lived with disability[1].It is well accepted that inflammation reaction, as the protective process of human body, is implicated in cancer.It is widely approved that inflammation promotes oncogenesis.Inflammation involves an array of cellular factors, biological processes and systemic reactions.As a consequence,cancer often follows inflammation with its proliferation pathways and reactions[2].And they usually act coordinately, which ultimately allows cancer to progress[3-5].However, it also participates in cancer rejection.The dynamic switch is dependent on the length of inflammatory process.Acute inflammation benefits human body as a protective reaction from microbial infection, tissue damage and oncogenesis[6].Chronic inflammation triggers oncogenesis and provides a more positive micro-environment to cancer through inflammatory factors which promote cell proliferation and angiogenesis[7].NF-κB, one of the major inflammatory factors, promotes cell proliferation with a carcinogenic micro-environment by activating chemokines, NOS, COX-2, TNF-α and other genes in nucleus[8].Besides, CXCR4/CXCL12 axis has been demonstrated as a vital inducer of cancer metastasis[9,10].Generally, inflammation links cancer through a dual-directional regulatory effect on micro-environment.

To meet the challenge,research on mechanisms and regulations of cancer and inflammation has last for several generations and great progress has made by mechanism study and drug discovery.Despite the rapid advances in new drug screening and chemical synthesis technologies, it has been increasingly difficult to search for highly efficient compounds with single target.Since cancer and inflammation have sophisticated formation pathways and work via several, specific points and pathways, which trapped us for a long time, a single approach is not enough to cure inflammation-related cancer.

Traditional Chinese Medicine (TCM) displays its unique advantages on the treatment of cancer and inflammation, such as low toxicity, side effect and availability of a wide range of sources.The function characteristics of TCM include multi-ingredient,multi-target and synergistic mechanism[11-13].Sophora flavescens(SF), also known as Kushen in Chinese,is one of most important TCM.SFis bitter in taste and cold in nature.Besides China, it has also been widely used in many countries, such as Japan,Korea.Accumulating studies performed by different laboratories have demonstrated thatSFexerts broad-spectrum pharmacological activities, including anti-inflammatory, anti-infectious and anti-tumor effects.It is reported thatSFis able to inhibit both microbial growth and its enzymes for cell wall protein anchoring and virulence[14].The anti-inflammatory effect ofSFis associated with inhibiting the pro-inflammatory environment through blockage of NF-κB translocation to nuclear[15].Moreover,SFsignificantly inhibit inflammation and infiltration of macrophages through suppressing the release of pro-inflammatory mediators and expression of adhesion molecule LFA-1 and chemoattractant protein MCP-1/CCL2[16].

Besides, it is also found thatSFhas potential inhibitory ability on cancer.SFinduces apoptosis in cancer cells through inhibition of cAMP-PDE, mTOR and Akt[17].Additionally, activating caspase proteases and increasing Bax/Bcl-2 ratio are also key mechanisms of anti-cancer effect ofSF[18].Although there are many researches on anti-inflammatory and anti-tumor mechanism ofSF, most of them focus on certain chemical components and targets, which barely matches to the comprehensive trait ofSFand cannot provide an overall description.

Network-pharmacology is a kind of comprehensive and predictive research method.It works through citing,comparing,connecting and analyzing data from multiple databases and published references.It aims to study the relationships among drugs, drug-target moleculars (e.g.proteins, RNAs) and diseases.With the rapid progress in bioinformatics, network pharmacology has been applied in many aspects of TCM, such as predicting new drug targets, action mechanism, new drug discovery, drug evaluation for PD/PK, safety and toxicology, quality control, and bioinformatics[19].Besides,the network-pharmacological methods are able to intuitively trace out the relation of different herbs and their interaction with targets, which may extend their applications in multi-drug combined therapies[20,21].Additionally, network pharmacology was also employed to elucidate the multi-active mechanism of a medicinal composition and to predict some key compounds and targets.Consequently, network pharmacology is considered to be a promising approach towards understanding of multiple ingredients and multiple targets of a disease.

In the study, we comprehensively reveal the effect ofSFon inflammation and cancer by network pharmacology.Our study reveals thatSFinhibits cancer and inflammation through multi-target,multi-pathway and synergistic processes.

Methods

Compound Library Construction and Drug-Likeness Screening.

Active compounds ofSFwere obtained from traditional Chinese medicine systems pharmacology(TCMSP)database((http://lsp.nwu.edu.cn/tcmsp.php).We inputted“kushen”and“Sophora flavescens”in the searching table and filtered the ingredients with ADME indexes including oral bioavailability (OB),drug-likeness (DL) and Caco-2 permiability (Caco-2)according to the oral delivery method of herbal medicine[22, 23].Ultimately, we set up the filtration rank as OB greater than or equal to 30 percent, DL greater than or equal to 0.18, Caco-2 greater than or equal to 0.40.

Prediction of SF Targets.

Key terms “Inflammation”, “Neoplasm”, “Malignant Tumor” and “Cancer” were inputted in GeneCards database, TTD database and OMIM database to retrieved targets of these diseases.At the meantime,targets of the filtered ingredients were obtained by retrieval in TCMSP.The bi-directional retrieval was accomplished by exporting all outcomes from databases and extracting the overlapped targets.To improve accuracy, Uniprot was used to correct the targets’names and symbols.

Construction of Protein-Protein Interaction (PPI)Network.

The STRING database was utilized to acquire the information of targets interaction in “Homo sapiens”with “high” interaction score predicted by active interaction sources-textmiming,experiments,databases, co-expression, neighborhood, gene fusion and co-occurrence.Then, Cytoscape was utilized to establish a ingredients-targets interaction network which is predicted by degree, betweenness centrality and combine score[24,25].

Molecular Docking.

According to the analysis results of the network,current knowledge and literature support,we extracted the potential key targets in the pathway.The Protein Database was used to obtain 3D structures of the targets.And the Scifinder and ChemDraw were used to obtain structures of relevant ingredients.Finally,SybylX-2.0 was used to accomplish the surflex-docking.

Gene Ontology (GO) Functional Enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)Pathway Enrichment.

We performed functional enrichment of selected targets via GO database with the screening condition of identifier as official gene symbol,species as human,P< 0.05 and FDR < 0.05[26].To determine the certain pathways that the ingredients affected on, we enriched the pathway through KEGG Mapper of KEGG database.Then,referring to current knowledge of the diseases and literature support, we remapped an integrative pathway through whichSFexerts its effect.

Results

Ingredients of SF.

We obtained 113 ingredients ofSFthrough retrieval in TCMSP at first.After filtration with OB, DL and Caco-2, 30 agreeable ingredients were selected and listed in Table 1.

Potential Targets of Active Components of SF.

TCMSP was used to download all 159 relevant targets of the active ingredients.GeneCards database, TTD database and OMIM database provided 77277 drug targets in the treatment of Inflammation, Neoplasm,Malignant Tumor and Cancer (Table 2).53 cancer-relevant targets and 52 inflammation-relevant targets were selected from the outcomes via comparison.Interestingly, after comparison of the target lists, we noticed that all inflammation-related targets were included in cancer (Figure 1).To explore the mechanism ofSFon cancer and inflammation and the potential mechanism connection between cancer and inflammation, we analyzed the targets both associated with inflammation and cancer.

Figure 1.Comparison of cancer and inflammation.

The disease-related genes were displayed by numbers and radius.The blue cycle representing neoplasm contains 53 gene.The red cycle representing inflammation only contains 52 gene, excepting HPSE.The Venn indicates a therapeutic relation between neoplasm and inflammation.

Table 1 Active components of Sophora flavescens and their parameters.

Table 2 Targets retrieval

The PPI Analysis.

The data of PPI was obtained from STRING platform.The top 12 enriched targets were displayed in a barplot (Figure 2).JUN, a protein-coding gene, is related with the Oxytocin signaling pathway and possessed the highest enrichment score.The CCR5 pathway in macrophages plays a significant role in the sequence-specific DNA binding process.Besides,IL-6 and MYC were also highly enriched.IL6 gene encodes a cytokine and functions in inflammation and the maturation of B cells.Additionally, this gene is implicated in a wide variety of inflammation-associated diseases which is related to the Th1 differentiation pathway.MYC encodes a nuclear phosphoprotein and plays a role in the cell cycle progression,apoptosis and cellular transformation.It is associated with protein metabolism pathways and the NGF pathway.

Cytoscape analysis.

Cytoscape was used to analyze the PPI network based on the date from STRING.The outcome displayed with the color of nodes, size of nodes and width of edge separately standing for degree, betweenness centrality and combine score (Figure 3).The results were quite similar to that of PPI analysis.JUN possess the highest score in degree and centrality.Moreover,MYC, IL6, CXCL8, MAPK14 and PTGS2 possessed relatively higher score in degree,and NCOA1,PTGS2,CXCL8 and other proteins possessed relatively higher score in centrality.

Medicine-Ingredient-Target-Disease Network.

A general outlook of relationships amongSF, its ingredients, potential targets, inflammation and cancer were displayed by Cytoscape (Figure 4).According to the results, it was obvious thatSFshowed mechanism on inflammation and cancer in a multi-target,multi-pathway and synergistic process.

Molecular Docking.

According to the results of PPI analysis,we eventually selected 10 potential targets.The Surflex-dock between related ingredients and potential targets was accomplished though analyzing molecules structures,preparing molecules and docking functions via SybylX-2.0 (Table 3).The results indicated that the most of active ingredients ofSFhad effective binding(total score>5) with different targets (Figure 5).What’s more, some of them had stronger combination with targets (total score>7)[27, 28].Additionally, a particular ingredient could affect multiple targets and a target could also be affected by different ingredients,which indicates the effect of TCM on diseases is characterized by multi-ingredients, multi-targets and synergistic process.

Figure 2.The top 12 enriched targets.

Figure 3.Cytoscape analysis.

Figure 4.Medicine-ingredient-target-disease network.

Table 3.Molecular docking

Figure 5.Heat Map of Molecule Docking.

PTGS2 5f19 (2S)-7-hydroxy-2-(4-hydroxyphenyl)-5-methoxy-8-(3-methylbut-2-enyl)c hroman-4-one 2.04 7.26 5f19 wighteone 2.04 6.34 5f19 inermine 2.04 5.96 5f19 8-isopentenyl-kaempferol 2.04 5.71 5f19 glyceolin 2.04 5.56 5f19 sophoridine 2.04 5.54 5f19 kushenin 2.04 5.04 PPARG 6ms7 (2S)-7-hydroxy-2-(4-hydroxyphenyl)-5-methoxy-8-(3-methylbut-2-enyl)c hroman-4-one 1.43 6.59 6ms7 kushenin 1.43 5.59 6ms7 8-isopentenyl-kaempferol 1.43 5.52 6ms7 sophocarpine 1.43 5.20 6ms7 inermin 1.43 5.19 6ms7 formononetin 1.43 5.15 6ms7 phaseolin 1.43

GO Functional Enrichment and KEGG Pathway Enrichment.

Results of cellular component (CC), molecular function (MF) and biological process (BP) were obtained from GO functional enrichment (Figure 6).According to the results,most targets locate in nucleus.The main molecular functions of the targets included transcriptional regulation (DNA-templated), positive regulation of cytosolic calcium ion concentration,sequence-specific DNA binding, positive regulation of transcription from RNA polymerase II promoter and inflammatory response.The main biological processes in which the targets participate are regulations of alpha 1-adrenergic receptor activity, steroid hormone receptor activity, and transcription factor activity(sequence-specific DNA binding).

Figure 6.GO functional enrichment.

Several pathways were exported from KEGG pathway enrichment.The top 20 highly enriched pathways were listed and drawn comprehensively in a map (Figure 7, Figure 8).They were virus infection related pathways, IL-17 signaling pathway, Th17 cell differentiation pathway, TNF signaling pathway,AGE-RACE signaling pathway, thyroid hormone signaling pathway and Estrogen signaling pathway.The pathways referred to immune system, endocrine system, digestive system, respiratory system and mainly regulate inflammatory factors,cell proliferation,senescence and apoptosis(Figure 8).

Figure 7.KEGG pathway enrichment.

Figure 8.Comprehensive pathway map of anti-cancer and anti-inflammation mechanism of SF

Discussion

As one of the representative herbs of TCM,SFhas received extensive investigation in modern pharmacology due to its effects on diseases induced by inflammation, such as cancer[16-18].To better understand the mechanisms behind the clinical applications ofSF, we built an integrated analytical platform based on network pharmacology, including target prediction, PPI network, topology analysis,gene enrichment analysis, and molecular docking.Using this platform, we revealed the underlying mechanisms of anti-inflammatory effects and therapeutic potential in cancer treatment ofSF.This study indicates thatSFdisplays effects on cancer and inflammation through multi-target, multi-pathway and synergistic processes.

According to ingredient-target interaction, the medicine-ingredient-target-disease network and outcomes of surflex-dock, it is obvious that a ingredient ofSFcould affect multiple targets while any single target could also be affected by different ingredients.Regarding the results od PPI and Cytoscape, JUN, IL6, MYC, MAPK14, CXCL8,PTGS2, RELA, AR, ICAM1, NCOA1, PPARG,ESR1 wre considered as the potential targets.The targets' potential effect on cancer and inflammation can be seen in relevant previous reseaches on the targets[35-54].Generally,SFmainly interferes DNA transcriptional activity to regulate inflammatory factors and cell proliferation, senescence and apoptosis.Besides, the enrichment of functions and pathways showed the DNA-binding activity,cycle-regulatory effect and inflammation-regulatory effect ofSF.The results reflects the functional characteristics ofSFon diseases including multi-ingredients, multi-targets and synergistic mechanism, like other herbal medicines[29-32].Moreover, during the research, we noticed that all selected targets of inflammation belong to the cancer’s,and sex hormone targets, like ESR1, NCoA1, AR are critical in the diseases.In this case,we speculated thatSFmay have a potent anti-cancer activity, especially on sex hormone related cancers, like breast cancer,cervical cancer,prostate cancer and et al.

According to our results, we drew a comprehensive map of the pathways through whichSFworks on cancer and inflammation (Figure 8).The NF-κB pathway, broadly relevant to ingredients-effected pathways, seems like one of the significant regulators which is indirectly affected by ingredients ofSF.NF-κB is often activated in inflammatory process and hyperactivation of NF-κB can also affect EGFR and other factors which are necessary for cancer cell invasion[8,34].In the map,we predict that NF-κB has broad-spectrum effects on inflammatory factors and cancer related factors, such as IL1, IL6, IL8, TNF-α,COX-2, Bcl-2, VEGF, ICAM1 and other factors,directly or indirectly.It is widely accepted that these factors prevent the body from inflammation and oncogenesis and dysregulated factors will induce oncogenesis by providing an environment to cancer cell for proliferation and metastasis.

The study does have limitations because of the imperfect databases which lack some aspects of data.However, the network pharmacology properly matches to herbal medicines’ study and current investigation on medicine[33].On one hand, it has a wide coverage of data and displays connections between multiple molecules, which is suitable for herbal medicine.On the other hand, it is valid in speculation of the capacity of herbs and pharmacological discovery field.

Conclusion

In this study, we deduce the potential targets,pathways and relevant ingredients ofSFin anti-cancer and anti-inflammation process, which indicates that the effects ofSFon cancer and inflammation are characterized by multi-ingredients, multi-targets and synergistic process.Additionally, the study also provides ideas and methods for further research and development ofSFand other traditional Chinese medicines as well.

Data Availability

The data used to support the findings of this study are included within the article.

Refference

1.Christina F, Degu A, Naghmeh A, 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 oncology,2018,4(11):1553-1568.

2.Lim C, Savan R.The role of the IL-22/IL-22R1 axis in cancer.Cytokine and Growth Factor Reviews,2014,25(3):257-271

3.Kapanadze T, Gamrekelashvili J, Ma C, et al.Regulation of accumulation and function of myeloid derived suppressor cells in different murine models of hepatocellular carcinoma.Journal of Hepatology,2013,59(5):1007-1013.

4.Ji Y,Zhang W.Th17 cells:positive or negative role in tumor?.2010,59(7):979-987.

5.Grivennikov S I, Greten F R, Karin M.Immunity,Inflammation, and Cancer.Cell, 2010, 140(6):883-899.

6.Mantovani A, Romero P, Palucka A K, et al.Tumour immunity: effector response to tumour and role of the microenvironment.The Lancet, 2008,371(9614):771-783.

7.Hussain S P,Harris C C.Inflammation and cancer:an ancient link with novel potentials.International journal of cancer,2007,121(11):2373-2380.

8.Jiang Q , Xiao Z , Willettebrown J , et al.Abstract 2561: IKKα links inflammation and tumorigenesis in a mouse model of lung squamous cell carcinoma.Cancer research,2012,72(8 Supplement):2561.

9.Muller A, Homey B, Soto H, et al.Involvement of chemokine receptors in breast cancer metastasis.Nature,2001,410(6824):50-56.

10.Kato M, Kitayama J, Kazama S, et al.Expression pattern of CXC chemokine receptor-4 is correlated with lymph node metastasis in human invasive ductal carcinoma.Breast Cancer Research, 2003,5(5):R144-50..

11.Ting-Ting L,Yuan L U,Shi-Kai Y,et al.Network Pharmacology in Research of Chinese Medicine Formula: Methodology,Application and Prospective.Chinese Journal of Integrative Medicine,2020,26(01):72-80.

12.Feng L, DU Xia,Pei-Rong L, et al.Screening and analysis of key active constituents in Guanxinshutong capsule using mass spectrum and integrative network pharmacology.Chinese Journal of Natural Medicines,2018,16(04):302-312.

13.Rui-Feng H U, Xiao-Bo S.Design of new traditional Chinese medicine herbal formulae for treatment of type 2 diabetes mellitus based on network pharmacology.Chinese Journal of Natural Medicines,2017,15(06):436-441.

14.Oh I,Yang W Y,Chung S C,et al.In vitrosortase a inhibitory and antimicrobial activity of flavonoids isolated from the roots ofSF.Archives of Pharmacal Research,2011,34(2):217-222.

15.Hee H M, Young L J, Hee J, et al.SFAiton inhibits the production of pro-inflammatory cytokines through inhibition of the NF kappaB/IkappaB signal pathway in human mast cell line(HMC-1).Toxicology in vitro:an international journal published in association with BIBRA,2009,23(2):0-258.

16.Dehua L, Chung-Lap C B, Ling C, et al.SFprotects against mycobacterial Trehalose Dimycolate-induced lung granuloma by inhibiting inflammation and infiltration of macrophages.Scientific reports,2018,8(1):3903.

17.Chen H, Yang J, Hao J, et al.A Novel Flavonoid Kushenol Z fromSFMediates mTOR Pathway by Inhibiting Phosphodiesterase and Akt Activity to Induce Apoptosis in Non-Small-Cell Lung Cancer Cells.Molecules,2019,24(24):4425.

18.Wen-Chung H, Pei-Yu G, Li-Wen F, et al.Sophoraflavanone G fromSFinduces apoptosis in triple-negative breast cancer cells.Phytomedicine :international journal of phytotherapy and phytopharmacology,2019,61:152852.

19.Liu C,Liu R,Fan H,et al.Network Pharmacology Bridges Traditional Application and Modern Development of Traditional Chinese Medicine.Chinese Herbal Medicines,2015,7(01):3-17.

20.Jianling L, Mengjie P, Chunli Z, et al.A systems-pharmacology analysis of herbal medicines used in health improvement treatment: predicting potential new drugs and targets.Evidence-based complementary and alternative medicine : eCAM,2013,2013(6):938764.

21.Chun-Song Z, Xiao-Jie X, Hong-Zhi Y, et al.Computational pharmacological comparison of Salvia miltiorrhiza and Panax notoginseng used in the therapy of cardiovascular diseases.Experimental and therapeutic medicine, 2013, 6(5):1163-1168.

22.Jinlong R, Peng L, Jinan W, et al.TCMSP: a database of systems pharmacology for drug discovery from herbal medicines.Journal of Cheminformatics,2014,6(1):13.

23.Li L, Li Y, Wang Y, et al.Prediction of human intestinal absorption based on molecular indices.Journal of Molecular Science, 2007, 23(4):286-291.

24.Yu-Keng S, Srinivasan P.Identifying functional modules in interaction networks through overlapping Markov clustering.Bioinformatics,2012,28(18):473-479.

25.Zhang S, Ning X, Zhang X.Identification of functional modules in a PPI network by clique percolation clustering.Computational Biology and Chemistry,2006,30(6).doi:10.1016/j.compbiolchem.2006.10.001.

26.Ashburner M, Ball C A, Blake J A, et al.Gene Ontology: Tool for the unification of biology.Nat Gene,2000,25(1):25-29.doi:10.1038/75556.

27.Qi-Meng F, Yan-Tao Y, Mei-Feng X, et al.Interaction between components of Buyang Huanwu Decoction and targets associated with ischemic stroke based on molecular docking method.Chinese Traditional and Herbal Drugs,2019,50(17):4200-4208.

28.Gui-Zhu D, Jie-Xin L, Chun-Wei W, et al.Molecular docking in Naomaitong Formula preparations multi-target effect on ischemic stroke.Chinese Traditional and Herbal Drugs, 2016, 38(8):1673-1678.

29.Yong-Li H, Qi M A, Zi-Wen Y, et al.A novel approach based on metabolomics coupled with network pharmacology to explain the effect mechanisms of Danggui Buxue Tang in anaemia.Chinese Journal of Natural Medicines,2019,17(04):275-290.

30.Xiao-Cong P, De K, Jian-Song F, et al.Network pharmacology-based analysis of Chinese herbal Naodesheng formula for application to Alzheimer's disease.Chinese Journal of Natural Medicines,2018,16(01):53-62.

31.Tao W, Tian L H, Zhang W S, et al.Use of Network Pharmacology and Molecular Docking to Investigate the Mechanism by Which Ginseng Ameliorates Hypoxia.Biomedical and Environmental Sciences,2018,31(11):855-858.

32.Tian Z I, Dong Y U.A network pharmacology study of Sendeng-4, a Mongolian medicine.Chinese Journal of Natural Medicines, 2015,13(02):108-118.

33.Xiao-Ming W U, Chun-Fu W U.Network pharmacology: A new approach to unveiling Traditional Chinese Medicine.Chinese Journal of Natural Medicines,2015,13(01):1-2.

34.Lehman Heather L, Kidacki Michal, Warrick Joshua I, et al.NFkB hyperactivation causes invasion of esophageal squamous cell carcinoma with EGFR overexpression and p120-catenin down-regulation.Oncotarget, 2018 , 9(13):11180-11196.

35.Dong E Tang,Yong Dai,Jia Xi He,et al.Targeting the KDM4B–AR–c‐Myc axis promotes sensitivity to androgen receptor‐targeted therapy in advanced prostate cancer.The Journal of Pathology, 2020,252(2):101-113.

36.Milly M A,Vera C,Samantha P et al Inflammatory infiltration is associated with AR expression and poor prognosis in hormone naïve prostate cancer.The Prostate,2020,80(15):1353-1364.

37.Ran M, Cong C D, Mei Lin, et al.KIAA1429 regulates cell proliferation by targeting c ‐ Jun messenger RNA directly in gastric cancer.Journal of Cellular Physiology,2020,235(10):7420-7432.

38.Jun Z, Dun X H, Chun B W, et al.Zbtb7b suppresses aseptic inflammation by regulating m 6 A modification of IL6 mRNA.Biochemical and Biophysical Research Communications, 2020,530(1):336-341.

39.Enana A, Anja M.The role of PKC in CXCL8 and CXCL10 directed prostate, breast and leukemic cancer cell migration.European Journal of Pharmacology,2020,886:173453.

40.Villa A L P,Parra R S,Feitosa M R,et al.PPARG expression in colorectal cancer and its association with staging and clinical evolution.Acta cirurgica brasileira,2020,35(7):e202000708.

41.Miao L, Meng P, Jing W, et al.miR-7 Reduces Breast Cancer Stem Cell Metastasis via Inhibiting RELA to Decrease ESAM Expression.Molecular Therapy-Oncolytics,2020,18:70-82.

42.Bohai F, Shen Y , Pastor H X, et al.Integrative Analysis of Multi-omics Data Identified EGFR and PTGS2 as Key Nodes in a Gene Regulatory Network Related to Immune Phenotypes in Head and Neck Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research,2020,26(14):3616-3628.

43.Siersbæk R, Scabia V, Nagarajan S, et al.IL6/STAT3 Signaling Hijacks Estrogen Receptor α Enhancers to Drive Breast Cancer Metastasis.Cancer cell,2020:412-423.

44.Felipe P M, Caroline AMN, Emerson L, et al.MAPK14 (p38 α ) inhibition effects against metastatic gastric cancer cells: A potential biomarker and pharmacological target.Toxicology in Vitro,2020,66:104839.

45.Bai Y, Li H, Dong J.Up-regulation of miR-20a weakens inflammation and apoptosis in high-glucose-induced renal tubular cell mediating diabetic kidney disease by repressing CXCL8 expression.Archives of physiology and biochemistry,2020:1-8.

46.Ryszard K, Bernadeta D, Bart K, et al.ESR Method in Monitoring of Nanoparticle Endocytosis in Cancer Cells.International Journal of Molecular Sciences,2020,21(12):4388.

47.Jun Z, Mao T, Shu Z, et al.Deamidation Shunts RelA from Mediating Inflammation to Aerobic Glycolysis.Cell Metabolism,2020,31(5):937-955.

48.Songda P, Shan P, Huijie W, et al.ICAM1 Regulates the Development of Gastric Cancer and May Be a Potential Biomarker for the Early Diagnosis and Prognosis of Gastric Cancer.Cancer management and research,2020,12:1523-1534.

59.Fengjuan Y, Xu W, Songen W, et al.C-Jun/C7ORF41/NF- κ B axis mediates hepatic inflammation and lipid accumulation in NAFLD.Biochemical Journal,2020,477(3):691-708.

50.Ying X, Yan M, Kodithuwakku ND, et al.Protective effects of Clematichinenoside AR against inflammation and cytotoxicity induced by human tumor necrosis factor- α .International immunopharmacology,2019,75:105563.

51.Hong L,Wenzhu L,Hongbo H,et al.Inflammation‐dependent overexpression of c‐Myc enhances CRL4DCAF4 E3 ligase activity and promotes ubiquitination of ST7 in colitis‐associated cancer.The Journal of Pathology,2019,248(4):464-475.

52.Wen W, Wei Z, Mihyun C, et al.Singer, David Jourd'heuil, Xiaochun Long.Vascular smooth muscle-MAPK14 is required for neointimal hyperplasia by suppressing VSMC differentiation and inducing proliferation and inflammation.Redox Biology,2019,22:101137.

53.Youming Z, Willis-Owen Saffron A G, Spiegel S,et al.The ORMDL3 Asthma Gene Regulates ICAM1 and Has Multiple Effects on Cellular Inflammation.American journal of respiratory and critical care medicine,2019,199(4):478-488.