Integrated bioinformatics analysis to decipher molecular mechanism of compound Kushen injection for esophageal cancer by combining WGCNA with network pharmacology

A study related to the treatment of gastric cancer with Xiang-Sha-Liu-Jun-Zi-Tang based on network analysis

Purpose

Xiang-Sha-Liu-Jun-Zi-Tang(XSLJZT) is a common formula for the treatment of Gastric Cancer(GC) and is widely used in clinical practice, however, there is a lack of investigation into its mechanism.

Methods

We collected and organized drug and disease targets, constructed the "XSLJZT-Active Ingredient-Target" visualization network, and performed GO and KEGG functional enrichment analysis of crossover genes, followed by molecular docking of active ingredients and core targets. The best docked monomers were combined with weighted gene co-expression network analysis(WGCNA) and macroscopically analyzed by GO and KEGG enrichment techniques. The results of cluster gene difference analysis, ROC evaluation, and CIBERSORT immune infiltration analysis were evaluated and finally supported by cellular experiments.

Results

The main components of XSLJZT are quercetin, stigmasterol, and naringenin, effectively treat GC by targeting STAT3, TP53 and MAPK3, which are involved in IL-17, TNF and HIF-1 signaling pathways. The results of molecular docking showed that quercetin bound better to the core targets. We performed an in-depth analysis of this monomer and found that quercetin acts on the core targets of TP53, MMP9, TIMP1 and MYC, and is involved in two key signaling pathways, TNF and IL-17, thus effectively treating GC. The experimental results are consistent with our analysis that quercetin inhibits the proliferation of GC cells and promotes apoptosis, and TP53, MYC and TIMP1 are the quercetin targets for the treatment of GC.

Conclusion

The present study tentatively suggests that quercetin, the main active ingredient in XSLJZT, can exert a therapeutic effect on GC by targeting TIMP1.

A pan-cancer analysis of pituitary tumor-transforming 3, pseudogene

BACKGROUND

Although evidence regarding pituitary tumor-transforming 3, pseudogene (PTTG3P) involvement in human cancers has been acquired via human and animal model-based molecular studies, there is a lack of pan-cancer analysis of this gene in human tumors.

METHODS

Tumor-causing effects of PTTG3P in 24 human tumors were explored using The Cancer Genome Atlas (TCGA) datasets from different bioinformatics databases and applying in silico tools such as The University of ALabama at Birmingham CANcer (UALCAN), Human Protein Atlas (HPA), Kaplan Meier (KM) plotter, cBioPortal, Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), Cytoscape, Database for Annotation, Visualization, and Integrated Discovery (DAVID), Tumor IMmune Estimation Resource (TIMER), and Comparative Toxicogenomics Database (CTD). Then, via in vitro experiments, including RNA sequencing (RNA-seq) and targeted bisulfite sequencing (bisulfite-seq), expression and promoter methylation levels of PTTG3P were verified in cell lines.

RESULTS

The PTTG3P expression was overexpressed across 23 malignancies and its overexpression was further found significantly effecting the overall survival (OS) durations of the esophageal carcinoma (ESCA) and head and neck cancer (HNSC) patients. This important information helps us to understand that PTTG3P plays a significant role in the development and progression of ESCA and HNSC. As for PTTG3P functional mechanisms, this gene along with its other binding partners was significantly concentrated in "Oocyte meiosis", "Cell cycle", "Ubiquitin mediated proteolysis", and "Progesterone-mediated oocyte maturation". Moreover, ESCA and HNSC tissues having the higher expression of PTTG3P were found to have lower promoter methylation levels of PTTG3P and higher CD8+ T immune cells level. Additionally, PTTG3P expression-regulatory drugs were also explored in the current manuscript for designing appropriate treatment strategies for ESCA and HNSC with respect to PTTG3P expression.

CONCLUSION

Our pan-cancer based findings provided a comprehensive account of the oncogenic role and utilization of PTTG3P as a novel molecular biomarker of ESCA and HNSC.

Breast Cancer Prognostic Hub Genes Identified by Integrated Transcriptomic and Weighted Network Analysis: A Road Toward Personalized Medicine

Breast cancer (BC) is the second-most common type and among the leading causes of worldwide cancer-related deaths. There is marked person-to-person variability in susceptibility to, and phenotypic expression and prognosis of BC, a predicament that calls for personalized medicine and individually tailored therapeutics. In this study, we report new observations on prognostic hub genes and key pathways involved in BC. We used the data set GSE109169, comprising 25 pairs of BC and adjacent normal tissues. Using a high-throughput transcriptomic approach, we selected data on 293 differentially expressed genes to establish a weighted gene coexpression network. We identified three age-linked modules where the light-gray module strongly correlated with BC. Based on the gene significance and module membership features, peptidase inhibitor 15 (PI15) and KRT5 were identified as our hub genes from the light-gray module. These genes were further verified at transcriptional and translational levels across 25 pairs of BC and adjacent normal tissues. Their promoter methylation profiles were assessed based on various clinical parameters. In addition, these hub genes were used for Kaplan-Meier survival analysis, and their correlation with tumor-infiltrating immune cells was investigated. We found that PI15 and KRT5 may be potential biomarkers and potential drug targets. These findings call for future research in a larger sample size, which could inform diagnosis and clinical management of BC, thus paving the way toward personalized medicine.

Systems biology and OMIC data integration to understand gastrointestinal cancers

Gastrointestinal (GI) cancers are a set of diverse diseases affecting many parts/ organs. The five most frequent GI cancer types are esophageal, gastric cancer (GC), liver cancer, pancreatic cancer, and colorectal cancer (CRC); together, they give rise to 5 million new cases and cause the death of 3.5 million people annually. We provide information about molecular changes crucial to tumorigenesis and the behavior and prognosis. During the formation of cancer cells, the genomic changes are microsatellite instability with multiple chromosomal arrangements in GC and CRC. The genomically stable subtype is observed in GC and pancreatic cancer. Besides these genomic subtypes, CRC has epigenetic modification (hypermethylation) associated with a poor prognosis. The pathway information highlights the functions shared by GI cancers such as apoptosis; focal adhesion; and the p21-activated kinase, phosphoinositide 3-kinase/Akt, transforming growth factor beta, and Toll-like receptor signaling pathways. These pathways show survival, cell proliferation, and cell motility. In addition, the immune response and inflammation are also essential elements in the shared functions. We also retrieved information on protein-protein interaction from the STRING database, and found that proteins Akt1, catenin beta 1 (CTNNB1), E1A binding protein P300, tumor protein p53 (TP53), and TP53 binding protein 1 (TP53BP1) are central nodes in the network. The protein expression of these genes is associated with overall survival in some GI cancers. The low TP53BP1 expression in CRC, high EP300 expression in esophageal cancer, and increased expression of Akt1/TP53 or low CTNNB1 expression in GC are associated with a poor prognosis. The Kaplan Meier plotter database also confirmed the association between expression of the five central genes and GC survival rates. In conclusion, GI cancers are very diverse at the molecular level. However, the shared mutations and protein pathways might be used to understand better and reveal diagnostic/prognostic or drug targets.

Identification of key pathways and genes in the progression of silicosis based on WGCNA

Silicosis, induced by inhaling silica particles in workplaces, is one of the most common occupational diseases. The prognosis of silicosis and its consequent fibrosis is extremely poor due to limited treatment modalities and lack of understanding of the disease mechanisms. In this study, a Wistar rat model for silicosis fibrosis was established by intratracheal instillation of silica (0, 50, 100 and 200 mg/mL, 1 mL) with the evidence of Hematoxylin and Eosin (HE) and Masson staining and the expressions of inflammatory and fibrotic proteins of rats' lung tissues. RNA of lung tissues of rats exposed to 200 mg/mL silica particles and normal saline for 14 d and 28 d was extracted and sequenced to detect differentially expressed genes (DEGs) and to identify silicosis fibrosis-associated modules and hub genes by Weighted gene co-expression network analysis (WGCNA). Predictions of gene functions and signaling pathways were conducted using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. In this study, it has been demonstrated the promising role of the Hippo signaling pathway in silicosis fibrosis, which will be conducive to elucidating the specific mechanism of pulmonary fibrosis induced by silica and to determining molecular initiating event (MIE) and adverse outcome pathway (AOP) of silicosis fibrosis.

Identification of molecular mechanisms underlying the therapeutic effects of Xintong granule in coronary artery disease by a network pharmacology and molecular docking approach

Coronary artery disease (CAD) is a cardiovascular disease characterized by atherosclerosis, angiogenesis, thrombogenesis, inflammation, etc. Xintong granule (XTG) is considered a practical therapeutic strategy in China for CAD. Although its therapeutic role in CAD has been reported, the molecular mechanisms of XTG in CAD have not yet been explored. A network pharmacology approach including drug-likeness (DL) evaluation, oral bioavailability (OB) prediction, protein-protein interaction (PPI) network construction and analysis, and Gene Ontology term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses was used to predict the active ingredients, potential targets, and molecular mechanisms of XTG associated with the treatment of CAD. Molecular docking analysis was performed to investigate the interactions between the active compounds and the underlying targets. Fifty-one active ingredients of XTG and 294 CAD-related targets were screened for analysis. Gene Ontology enrichment analysis showed that the therapeutic targets of XTG in CAD are mainly involved in blood circulation and vascular regulation. KEGG pathway analysis indicated that XTG intervenes in CAD mainly through the regulation of fluid shear stress and atherosclerosis, the AGE-RAGE signaling pathway in diabetic complications, and the relaxin signaling pathway. Molecular docking analysis showed that each key active ingredient (quercetin, luteolin, kaempferol, stigmasterol, resveratrol, fisetin, gamma-sitosterol, and beta-sitosterol) of XTG can bind to the core targets of CAD (AKT1, JUN, RELA, MAPK8, NFKB1, EDN1, and NOS3). The present study revealed the CAD treatment-related active ingredients, underlying targets, and potential molecular mechanisms of XTG acting by regulating fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, and relaxin signaling pathway.

Network pharmacology approach and molecular docking to explore the potential mechanism of Wu-Wei-Wen-Tong Chubi capsules in rheumatoid arthritis

Network pharmacology, a holistic approach based on the theory of biological network technology, integrates information from biological systems, drugs, and diseases. Here, this theory was used to predict the targets of Wu-Wei-Wen-Tong Chubi capsule (WWWT) to explore the mechanism in the treatment of rheumatoid arthritis (RA). The ingredients of each herbal medicine in WWWT were collected from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the active ingredients were screened through bioavailability (OB) ≥30% and drug-likeness (DL) ≥ 0.18. SwissTargetPrection and TCMSP were utilized to calculate and predict the targets of active ingredients. RA-related targets were obtained by searching the Genecards and OMIM databases. The common targets of RA and WWWT were used for gene ontology (GO), KEGG pathway enrichment, protein-protein interaction (PPI) analysis, and molecular docking. And then, four key genes were screened for subsequent verification experiments. In total, 90 active compounds and 330 potential targets of WWWT, 1310 targets of RA, and 135 intersection targets were found. Additionally, GO and pathway analysis identified 4610 significant GO terms and 147 significant KEGG pathways. Based on the PPI network, 11 key genes including IL-6, MMP-9, and TNF-α were screened out for molecular docking. Molecular docking showed that these key genes have good binding activities to active compounds of WWWT such as oroxylin a, kaempferol, and luteolin. Simultaneously, Western blot experimental validation demonstrated that the protein expressions of IL-6, MMP-9, TNF-α, and VEGFA significantly decreased after WWWT treatment. The mechanism of WWWT in treating RA involves multiple active compounds acting on multiple targets, and multiple pathways, which provides an important reference for further elucidation the mechanism and clinical applications of WWWT in the treatment of RA.

The Involvement of WDHD1 in the Occurrence of Esophageal Cancer as a Downstream Target of PI3K/AKT Pathway

Esophageal cancer is one of the most common malignant tumors in the world, which is characterized by high incidence, strong invasiveness, high mortality, and poor prognosis. At present, the therapies include surgery, endoscopic resection, radiotherapy and chemotherapy, targeted therapy, and immunotherapy. The five-year survival rate of esophageal cancer has not been significantly improved, although the medical level has been continuously improved and the management and application of different therapies have been improved day by day. At present, an abnormal gene expression is still regarded as an important factor in the occurrence and development of esophageal cancer. WD repeat and HMG-box DNA binding protein 1(WDHD1), as a key gene, plays an important role in the occurrence of esophageal cancer. It is known that the protein encoded by WDHD1 is the downstream target of the PI3K/AKT pathway. When PI3Ks is activated by extracellular signals, PI(4,5)P2 on the inner side of the plasma membrane will be converted into PI(3,4,5)P3. Then, PI(3,4,5)P3 can be converted into PI(3,4)P2,PI(4)P and PI(3)P by dephosphorylation of some regulatory factors. PI(3,4,5)P3 recruited AKT to the plasma membrane and combined with its pH domain, resulting in conformational change of AKT. Subsequently, AKT was completely activated by PDK1 and PDK2 and begins to move to the cytoplasm and nucleus. In this process, AKT continuously phosphorylates downstream substrates. WDHD1, as a downstream target of AKT, is also phosphorylated and induces DNA replication. Besides the abnormal regulation of cells by other downstream targets of AKT, it also becomes a potential pathway that may eventually lead to the occurrence of esophageal cancer.

Exploring the Multicomponent Synergy Mechanism of Yinzhihuang Granule in Inhibiting Inflammation-Cancer Transformation of Hepar Based on Integrated Bioinformatics and Network Pharmacology

Background

The Chinese patent drug Yinzhihuang granule (YZHG) is used to treat hepatitis B. This research is aimed at exploring the multicomponent synergistic mechanism of YZHG in the treatment of inflammation-cancer transformation of hepar and at providing new evidence and insights for its clinical application.

Methods

To retrieve the components and targets of Yinzhihuang granules. The differentially expressed genes (DEGs) of hepar inflammation-cancer transformation were obtained from TTD, PharmGKB, and GEO databases. Construct the compound-prediction target network and the key module network using Cytoscape 3.7.1.

Results

The results show that hepatitis B and hepatitis C shared a common target, MMP2. CDK1 and TOP2A may play an important role in the treatment with YZHG in hepatitis B inflammatory cancer transformation. KEGG pathway enrichment showed that key genes of modules 1, 2, and 4 were mainly enriched in the progesterone-mediated oocyte maturation signaling pathway and oocyte meiosis signaling pathway.

Conclusion

The multicomponent, multitarget, and multichannel pharmacological benefits of YZHG in the therapy of inflammation-cancer transition of hepar are directly demonstrated by network pharmacology, providing a scientific basis for its mechanism.

Cell cycle arrest is an important mechanism of action of compound Kushen injection in the prevention of colorectal cancer

Compound Kushen injection (CKI) is the most widely used traditional Chinese medicine preparation for the comprehensive treatment of colorectal cancer (CRC) in China, but its underlying molecular mechanisms of action are still unclear. The present study employed a network pharmacology approach, in which we constructed a "bioactive compound-target-pathway" network. Experimental RNA sequencing (RNA-Seq) analysis was performed to identify a key "bioactive compound-target-pathway" network for subsequent experimental validation. Cell cycle, proliferation, autophagy, and apoptosis assays and a model of azoxymethane/dextran sodium sulfate-induced colorectal carcinogenesis in mice were employed to detect the biological effect of CKI on CRC. Real-time reverse-transcription polymerase chain reaction, Western blot, and immunohistochemistry were performed to verify the selected targets and pathways. We constructed a predicted network that included 82 bioactive compounds, 34 targets, and 33 pathways and further screened an anti-CRC CKI "biological compound (hesperetin 7-O-rutinoside, genistein 7-O-rutinoside, and trifolirhizin)-target (p53 and checkpoint kinase 1 [CHEK1])" network that targeted the "cell cycle pathway". Validation experiments showed that CKI effectively induced the cell-cycle arrest of CRC cells in vitro and suppressed the development of CRC in vivo by downregulating the expression of p53 and CHEK1. Our findings confirmed that inducing cell-cycle arrest by CKI is an important mechanism of its anti-CRC action, which provides a direct and scientific experimental basis for the clinical application of CKI.

Comprehensive Analysis of Tripterine Anti-Ovarian Cancer Effects Using Weighted Gene Co-Expression Network Analysis and Molecular Docking

BACKGROUND Ovarian cancer has the highest mortality of gynecological cancers worldwide. The aim of this study was to identify the role of tripterine against ovarian cancer. MATERIAL AND METHODS GSE18520 and GSE12470 data sets were downloaded from the GEO database. WGCNA was used to analyze gene modules and hub genes related to ovarian cancer. These hub genes were intersected with tripterine targets, and GO and KEGG enrichment analyses were performed. HPA and GEPIA determined the expression of tripterine anti-ovarian hub genes in tumor tissues. Kaplan-Meier plotter was used to explore the role of hub genes in ovarian cancer prognosis. AutoDock was used to conduct molecular docking of tripterine and hub genes to observe whether the combination was stable. RESULTS By differential analysis of gene expression and the construction of WGCNA co-expression network, 5 hub genes, ARHGAP11A, MUC1, HBB, RUNX1T1, and FUT8, were screened by module gene screening. Seven biological processes and 20 KEGG-related pathways were obtained by gene enrichment. The expression of tripterine anti-ovarian hub genes ARHGAP11A, MUC1, and FUT8 were obtained by HPA and GEPIA. Using Kaplan-Meier plotter, the survival of ovarian cancer was negatively correlated with ARHGAP11A, MUC1, and FUT8. Molecular docking showed the combination of tripterine and FUT8 was most stable, having the greatest potential role. CONCLUSIONS Tripterine may be involved in megakaryocyte development and platelet production through potential genes ARHGAP11A, MUC1, HBB, RUNX1T1, and FUT8 and may have an anti-ovarian cancer effect in immune factors signaling, transporting and exchanging oxygen pathways, and autophagy pathways, through these 5 key genes.

Weighted Gene Correlation Network Analysis Identifies Specific Functional Modules and Genes in Esophageal Cancer

Objective

Esophageal cancer (ESCA) is one of the most aggressive malignancies globally with an undesirable five-year survival rate. Here, this study was conducted for determining specific functional genes linked with ESCA initiation and progression.

Methods

Gene expression profiling of ESCA was curated from TCGA (containing 160 ESCA and 11 nontumor specimens) and GSE38129 (30 paired ESCA and nontumor tissues) datasets. Differential expression analysis was conducted between ESCA and nontumor tissues with adjusted p value <0.05 and |log2fold-change|>1. Weighted gene coexpression network analysis (WGCNA) was conducted for determining the ESCA-specific coexpression modules and genes. Thereafter, ESCA-specific differentially expressed genes (DEGs) were intersected. Functional enrichment analysis was then presented with clusterProfiler package. Protein-protein interaction was conducted, and hub genes were determined. Association of hub genes with pathological staging was evaluated, and survival analysis was presented among ESCA patients.

Results

This study determined 91 ESCA-specific DEGs following intersection of DEGs and ESCA-specific genes in TCGA and GSE38129 datasets. They were remarkably linked to cell cycle progression and carcinogenic pathways like the p53 signaling pathway, cellular senescence, and apoptosis. Ten ESCA-specific hub genes were determined, containing ASPM, BUB1B, CCNA2, CDC20, CDK1, DLGAP5, KIF11, KIF20 A, TOP2A, and TPX2. They were prominently associated with pathological staging. Among them, KIF11 upregulation was in relation to undesirable prognosis of ESCA patients.

Conclusion

Collectively, we determined ESCA-specific coexpression modules and hub genes, which offered the foundation for future research concerning the mechanistic basis of ESCA.

[Therapeutic mechanism of natural astaxanthin against renal clear cell carcinoma based on network pharmacology and bioinformatics]

OBJECTIVE

To explore the molecular mechanism by which natural astaxanthin (AST) inhibits renal clear cell carcinoma (KIRC) based on network pharmacology and bioinformatics.

METHODS

PharmMapper database was used to retrieve the targets of natural astaxanthin, and TCGA database was used to identify the differentially expressed genes (DEGs) in KIRC and adjacent tissues. The target genes of AST was analyzed using Cytoscape software to construct the "drug-target" network diagram. The visual protein-protein interaction (PPI) network was constructed using String database, and GO enrichment analysis of the core targets was performed. Single gene bioinformatics was performed to verify the screened core target of AST, namely placental growth factor (PGF). The effect of natural AST on the viability of KIRC cells was tested using CCK-8 method, and the binding between natural AST and PGF was assessed with molecular docking technology. The effect of natural AST on the mRNA and protein expression of the target genes was analyzed using RT-qPCR and Western blotting.

RESULTS

We identified 278 candidate targets of AST, 1081 KIRC-related targets, and 7 core targets involved in the therapeutic mechanism of AST against KIRC. Among these 7 core targets, PGF showed significantly upregulated expression in KIRC (P < 0.001) in correlation with a poor prognosis (HR=1.37, P=0.043). Molecular docking showed that the binding energy of AST and PGF was -5.43 kcal/mol. CCK-8 assay showed that AST at the concentration of 50 μmol/L was capable of inhibiting the proliferation of KIRC cells, and a higher concentration resulted in a stronger inhibitory effect. The results of RT-qPCR and Western blotting showed that AST treatment significantly reduced the expression of PGF at both the mRNA and protein levels in KIRC cells.

CONCLUSION

Natural AST can suppress the proliferation of KIRC and inhibit the expression of PGF in the cells.

A systematic review and meta-analysis on the efficacy of Compound Kushen Injection in 3 kinds of digestive tract tumor

BACKGROUND

Chemotherapy has become the main means to prolong the life of patients with advanced digestive tract cancer; however, it is associated with serious toxicity and side effects. Compound Kushen Injection (CKI) is a pure Chinese herbal preparation, which can assist chemotherapy, inhibit tumor cell proliferation, and reduce adverse reactions of chemotherapy. In this study, we systematically evaluated reports of CKI as an adjuvant to chemotherapeutic treatment of digestive tract cancer in recent years and provided evidence for clinical diagnosis and treatment.

METHODS

The databases of PubMed, Chinese Biomedical Literature (CBM), China National Knowledge Infrastructure (CNKI) and Web Of Science were searched for clinical randomized controlled trials (RCTs) related to adjuvant chemotherapy with CKI in the treatment of advanced gastrointestinal tumors published from January 2000 to September 2021. After screening the qualified literatures, RevMan 5.4 software was used to evaluate the bias of the included literatures and perform meta-analysis.

RESULTS

A total of 12 articles were included in the selection, incorporating 1080 study participants in all; meta-analysis results showed that application of the CKI in the process of chemotherapy for digestive tract tumors could improve the efficacy [odds ratio (OR) =3.11; 95% confidence interval (CI): 2.26 to 4.47, Z=7.00, P<0.00001], increase the patients' median survival time (months) (OR =3.00; 95% CI: 1.47 to 4.52, Z=3.84, P=0.0001), increase the level of CD3+ [mean difference (MD) =4.11; 95% CI: 3.24 to 4.98], CD4+ level (MD =8.24; 95% CI: 3.72 to 12.76), reduce the CD8+ level (MD =-5.42; 95% CI: -8.09 to -2.76), reduce the tumor markers carcinoembryonic antigen (CEA; MD =-14.26; 95% CI: -14.81 to -13.71), CA199 (MD =-138.87; 95% CI: -143.21 to -132.52), and reduce the adverse reactions of chemotherapy: leukopenia (OR =0.28; 95% CI: 0.19 to 0.43), thrombocytopenia (OR =0.38; 95% CI: 0.24 to 061), decreased hemoglobin (OR =0.55; 95% CI: 0.31 to 0.98), and nausea and vomiting symptoms (OR =0.35; 95% CI: 0.24 to 0.53).

DISCUSSION

Adjuvant chemotherapy with CKI in the treatment of digestive tract tumors can effectively improve the symptoms of patients, improve immunity, reduce the level of serum tumor markers, improve efficacy, and reduce toxic and side effects.

Traditional Chinese Medicine Therapy for Esophageal Cancer: A Literature Review

Esophageal cancer (EC) is the sixth leading cause of cancer-related deaths worldwide. Western medicine has played a leading role in its treatment, but its prognosis remains unsatisfactory. Therefore, the development of effective therapies is important. Traditional Chinese medicine (TCM) has been practiced for thousands of years, and involves taking measures before diseases occur, deteriorate, and recur. Interestingly, there is growing evidence that TCM can improve the therapeutic effects in reversing precancerous lesions, inhibiting the recurrence and metastasis of EC. In this article, we review traditional Chinese herbs and formulas that have preventive and therapeutic effects on EC, summarize the application and research status of TCM in patients with EC, and discuss its shortcomings and prospects in the context of translational, evidence-based, and precision medicine.

High-Throughput In Vitro Gene Expression Profile to Screen of Natural Herbals for Breast Cancer Treatment

Breast cancer has surpassed lung cancer as the most commonly diagnosed cancer in women worldwide. Some therapeutic drugs and approaches could cause side effects and weaken the immune system. The combination of conventional therapies and traditional Chinese medicine (TCM) significantly improves treatment efficacy in breast cancer. However, the chemical composition and underlying anti-tumor mechanisms of TCM still need to be investigated. The primary aim of this study is to provide unique insights to screen the natural components for breast cancer therapy using high-throughput transcriptome analysis. Differentially expressed genes were identified based on two conditions: single samples and groups were classified according to their pharmaceutical effect. Subsequently, the sample treated with E. cochinchinensis Lour. generated the most significant DEGs set, including 1,459 DEGs, 805 upregulated and 654 downregulated. Similarly, group 3 treatment contained the most DEGs (414 DEGs, 311 upregulated and 103 downregulated). KEGG pathway analyses showed five significant pathways associated with the inflammatory and metastasis processes in cancer, which include the TNF, IL−17, NF-kappa B, MAPK signaling pathways, and transcriptional misregulation in cancer. Samples were classified into 13 groups based on their pharmaceutical effects. The results of the KEGG pathway analyses remained consistent with signal samples; group 3 presents a high significance. A total of 21 genes were significantly regulated in these five pathways, interestingly, IL6, TNFAIP3, and BRIC3 were enriched on at least two pathways, seven genes (FOSL1, S100A9, CXCL12, ID2, PRS6KA3, AREG, and DUSP6) have been reported as the target biomarkers and even the diagnostic tools in cancer therapy. In addition, weighted correlation network analysis (WGCNA) was used to identify 18 modules. Among them, blue and thistle2 were the most relevant modules. A total of 26 hub genes in blue and thistle2 modules were identified as the hub genes. In conclusion, we screened out three new TCM (R. communis L., E. cochinchinensis Lour., and B. fruticosa) that have the potential to develop natural drugs for breast cancer therapy, and obtained the therapeutic targets.