Post-marketing Evaluation Study Of Compound Kushen Injection In The Treatment Of Gastric And Esophageal Cancer Based On Integrated Big Data

ObjectiveGastric cancer(GC)and esophageal cancer(ESCA)are high-incidence cancers of the digestive tract.At present,the clinical treatment methods for GC and ESCA are mostly chemotherapy or radiotherapy.Compound Kushen injection(CKI)has the effects of clearing heat and dampness,cooling blood and detoxification,dispersing masses and relieving pain and it plays a role of increasing efficiency and reducing toxicity in the treatment of tumors.It is one of the common anti-tumor traditional Chinese medicine(TCM)injections and is often used in the treatment of GC and ESCA.This study has explored and analyzed the clinical effects and molecular mechanism of CKI in the treatment of GC and ESCA by network Meta analysis,network pharmacology,bioinformatics and molecular biology.Methods1 Network Meta analysisFirstly,randomized controlled trials(RCTs)of anti-tumor Chinese medicine injections for the treatment of GC and ESCA were searched in domestic and foreign databases,and developed strict inclusion and exclusion criteria.According to the outcome indicators,including clinical total effective rate,improvement of quality of life and improvement of adverse reactions,data were entered,and software WinBugs1.4 and Stata13.0 were adopted for statistical analysis.According to the data under different outcome indicators,the network diagram,the surface under the cumulative ranking and a three-digit data cube diagram were generated to evaluate the therapeutic advantages and characteristics of CKI compared with other similar injections.2 Integrated bioinformatics analysisThis study has comprehensively adopted the methods of network pharmacology,weighted gene co-expression network analysis(WGCNA),chip Meta analysis,molecular docking and classical bioinformatics to explore the mechanism of CKI in the treatment of GC and ESCA.In the study of the mechanism of CKI in the treatment of GC,firstly,differential analysis of miRNA expression data in GEO and TCGA databases was performed to screen differentially expressed miRNAs in GC,and target genes were predicted.Afterwards,the key modules of WGCNA were screened for the RNA sequencing data and clinical information in TCGA.According to the component targets of CKI and the above key information of GC,the ceRNA network of CKI intervention for GC was constructed.In order to further explore the impact of key targets,this study conducted a chip Meta analysis of key genes to compare the expression differences of key genes between GC tissues and normal tissues.GO and KEGG functional enrichment analysis was utilized to understand the biological regulation pathways involved in key genes.In addition,survival analysis and immune infiltration analysis were used to further test the significance of key genes for the prognosis of GC.Finally,molecular docking simulation was used to verify the binding ability of CKI with key genes.In the study of the mechanism of CKI on ESCA,firstly,according to the screening in the GEO database,the ESCA high-throughput sequencing chip data was downloaded for integrated difference analysis;secondly,the ESCA RNA sequencing data in TCGA was analyzed for key model construction and screening;finally,according to the DisgeNET data,collecting targets of ESCA.Based on the above disease target information and the component targets of CKI,network pharmacology was performed to study the molecular mechanism of CKI in the treatment of ESCA.3 Molecular biology analysisIn this study,the MTT and CCK-8 methods were used to observe the effects of CKI on the proliferation of gastric cancer cells and esophageal cancer cells.Afterwards,RT-qPCR and Western blot were adopted to detect the effects of CKI on the expression of mRNA and protein in gastric cancer cells and esophageal cancer cells.At the same time,this study utilized the TMT method to systematically study the protein changes in gastric cancer cells after the administration of CKI.Results1 Clinical evaluation of CKI in the treatment of GC based on network Meta analysisIn this part of the study,a total of 68 RCTs were included,involving 8 anti-tumor Chinese medicine injections and 5525 patients.The results showed that compared with the control group only using FOLFOX,the CKI combined with FOLFOX increased the total clinical effective rate,alleviated the quality of life,improved immune function indicators and reduced adverse reactions.In addition,in the case of three-dimensional cluster analysis of outcome indicators based on improving the total clinical effectiveness and improving the quality of life,the CKI may be the most effective intervention.2 Clinical evaluation of CKI in the treatment of ESCA based on network Meta analysisIn this part of the study,a total of 52 RCTs were included,involving 7 anti-tumor Chinese medicine injections and 3876 patients.The results showed that CKI combined with chemotherapy may be the best intervention in terms of improving the total clinical effective rate,improving the quality of life,and reducing nausea and vomiting compared with the control group only using chemotherapy.In the cluster analysis of outcome indicators based on improving the clinical total effective rate,CKI has shown obvious advantages,and it is most likely to become the best intervention.3 Research on the mechanism of CKI on GC by network pharmacologyThis study has used network pharmacology as the core concept to identify the ceRNA network and key targets of CKI in the treatment of GC.Meta analysis of GC gene expression profiling chip revealed that key genes including AKR1B1,CTSK,MMP2,TLR4,ADRB2,PDE1C and PTGER3 have significant differences in gastric cancer tissues.Survival analysis also showed that AKR1B1,MMP2 and PTGER3 are of great significance in affecting the survival rate of gastric cancer.Analysis of the ceRNA network of CKI on GC illustrated that the potential molecular mechanism of CKI was possible to regulate PI3K-AKT and Toll-like receptor signaling pathways.4 Research on key genes of ESCA based on integrated high-throughput data analysisThis part aims to identify potentially key genes related to the pathogenesis and prognosis of ESCA.To this end,in the gene expression profile data set,an integrated bioinformatics method was used to screen the differentially expressed genes(DEGs)between ESCA tissue and normal tissue.Compared with normal tissues,there are a total of 134 up-regulated and 183 down-regulated DEGs in ESCA tissues,and a protein interaction network was constructed based on this.Ten hub genes(AURKA,CDC20,BUB1,TOP2A,ASPM,DLGAP5,TPX2,CENPF,UBE2C and NEK2)were screened according to the Degree value.Functional enrichment analysis showed that a variety of extracellular entries and ECM-receptor interaction pathways were closely related to ESCA.5 Study on the mechanism of CKI in the treatment of ESCA based on network pharmacologyThe blue and turquoise module in WGCNA combined with the chip analysis of differential genes and disease database genes and the predicted targets of CKI for network pharmacology analysis.Through network merge and protein interaction,29 gene targets were obtained,among which EGFR,ERBB2,CCND1 and AURKA are the hub genes.In addition,through functional enrichment analysis and prediction,it was found that CKI can also treat ESCA by regulating related pathways such as ERBB signaling pathway and PI3K-AKT signaling pathway.6 Based on proteomics analysis of the molecular mechanism of CKI in the treatment of GCIn this study,the TMT quantitative proteomics research method was used to analyze the differentially expressed protein after the CKI interfered with GC cells.The study found that a total of 794 differentially expressed proteins,including 490 up-regulated proteins and 304 down-regulated proteins.In addition,it was found that CKI can curb the progression of GC by influencing PI3K-AKT signaling pathway and MAPK signaling pathway.7 The effect of CKI on GC and ESCA cellsThe experimental results showed that CKI can inhibit the proliferation of GC and ESCA cells.RT-qPCR and Western blot experiments confirmed that CKI can inhibit the overexpression of AKR1B1 and MMP2 in GC cells and up-regulate PTGER3 in GC cells.In addition,it can also down-regulate abnormally high expression of EGFR and AURKA in ESCA.ConclusionsUnder the guidance of the concept of integrated big data,this study comprehensively used clinical big data and bioinformatics big data research methods to carry out clinical evaluation and mechanism research of CKI.The results showed that CKI has a definite therapeutic effect in the treatment of GC and ESCA and has advantages or characteristics compared with similar injections.Its core mechanism was closely related to the regulation of key genes in GC and ESCA.At the same time,this research also explored and practiced the TCM integrated big data research model based on the network meta-analysis,network pharmacology,bioinformatics,and molecular biology experiments,which provided a demonstration and path for the re-evaluation of TCM after the market,especially the effective connection of the efficacy and mechanism evaluation.