Uncovering the anticancer mechanism of Compound Kushen Injection against HCC by integrating quantitative analysis, network analysis and experimental validation

Advancements in the study of glucose metabolism in relation to tumor progression and treatment

Sugar serves as the primary energy source for mammals, with glucose metabolism facilitating energy acquisition in human cells. The proper functioning of intracellular glucose metabolism is essential for the maintenance of orderly and healthy physiological activities. Tumor cells, characterized by uncontrolled growth, exhibit dysregulated proliferation and apoptosis processes, leading to abnormal alterations in glucose metabolism. Specifically, tumor cells exhibit a shift towards aerobic glycolysis, resulting in the production of lactic acid that can be utilized as a metabolic intermediate for sustained tumor cell growth. This article provides a comprehensive overview of the enzymes involved in glucose metabolism and the alterations in gene expression that occur during tumor progression. It also examines the current research on targeting abnormal glucose metabolism processes for tumor treatment and discusses potential future directions for utilizing glucose metabolism as a therapeutic target.

Virtual screening and network pharmacology-based synergistic coagulation mechanism identification of multiple components contained in compound Kushen Injection against hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a primary liver malignancy commonly encountered in the setting of chronic liver disease and cirrhosis. Compound Kushen Injection (CKI) has been widely used in HCC, however, the underlying mechanisms are scarce.

OBJECTIVE

To explore the molecular mechanisms of CKI for HCC.

MATERIALS AND METHODS

The chemical ingredients of CKI were reviewed from published articles and the potential targets were got from Herbal Ingredients' Targets Platform. Coagulation-related targets were from Kyoto Encyclopedia of Genes and Genomes and HCC-related targets were from Therapeutic Target Database, Gene Expression Omnibus, and The Cancer Genome Atlas. Then the CKI-Herb-Target and CKI-Herb-Target-HCC networks were built. The shared targets between CKI and HCC were used for functional enrichment through Metascape and the shared coagulation-related target was used for molecular docking and survival analysis.

RESULTS

A total of 23 chemical ingredients and 41 potential targets shared between CKI and HCC were obtained. The results of functional enrichment indicated that several canonical pathways of CKI mostly participated in the treatment of HCC. Furthermore, a chemical ingredient of CKI formed a stable hydrogen bond link with the ASN-189 on PLG, with a best binding energy of -4.7 kcal/mol. Finally, PLG was confirmed as the shared coagulation-related target and interrelated with the prognosis of HCC.

CONCLUSION

CKI probably improves HCC prognosis through PLG. Our research undoubtedly deepened the understanding of the molecular mechanism of CKI anti-HCC.

Benefit-Risk Assessment of Chinese Medicine Injections for Primary Liver Cancer Based on Multi-criteria Decision Analysis

OBJECTIVE

To evaluate the benefit-risk of 3 commonly used Chinese medicine injections, Aidi Injection (ADI), Cinobufagin Injection (CINI) and Compound Kushen Injection (CKI), in the treatment of primary liver cancer (PLC), so as to provide a reference for clinical decision-making.

METHODS

Randomized controlled trials (RCTs) of ADI, CINI and CKI in the treatment of PLC published in the databases of China National Knowledge Infrastructure, Wanfang, China Science and Technology Journal Database, SinoMed, PubMed, Cochrane Library, and Web of Science were retrieved from January 2020 to October 2022. The data of benefit and risk indicators were combined to obtain the effect value. The multi-criteria decision analysis (MCDA) model was applied to build the decision tree. The benefit value, risk value and benefit risk value of the 3 injections in PLC treatment were calculated. Monte Carlo simulation was carried out to calculate the 95% confidence interval and probability of differences among the 3 injections, so as to optimize the evaluation results.

RESULTS

A total of 71 RCTs were included. The benefit values of ADI, CINI and CKI combined with transcatheter arterial chemoembolization (TACE) were 42, 38 and 36, respectively. The risk values were 42, 25 and 37, respectively. The benefit risk values were 42, 31 and 37, respectively. The benefit risk differences of ADI vs. CINI, ADI vs. CKI, and CKI vs. CINI were 11 (-0.86, 17.75), 5 (-5.01, 11.09), and 6 (-1.87, 12.63), respectively. The probability that ADI superior to CINI, ADI superior to CKI, and CKI superior to CINI was 96.26%, 77.27%, and 92.62%, respectively.

CONCLUSION

Based on the results of MCDA model, CINI combined with TACE has the greatest risk in the treatment of the PLC. Considering the efficacy and safety, the possible priority of the 3 Chinese medicine injections combined with TACE in the treatment of PLC is ADI, CKI and CINI.

Efficacy and safety of compound kushen injection for treating advanced colorectal cancer: A protocol for a systematic review and meta-analysis

Introduction

Compound Kushen Injection (CKI) is a traditional Chinese medicine extracted from Sophora flavescens Aiton and Heterosmilax japonica Kunth. Widely utilized in China for the comprehensive treatment of colorectal cancer (CRC), this study aims to systematically assess the efficacy and safety of CKI when combined with chemotherapy for the treatment of advanced CRC, based on available data.

Methods

Randomized controlled trials investigating the efficacy and safety of CKI combined with chemotherapy in the treatment of advanced CRC will be comprehensively searched from databases, including PubMed, Web of Science, Cochrane Library, EMBASE, China National Knowledge Infrastructure, Chinese Scientific Journal Database, Wanfang, Chinese Biomedicine Database Searches, Chinese Clinical Trial Registry, and ClinicalTrials.gov until November 2022. Two independent reviewers will screen the studies, assess the risk of bias, and extract data in duplicate. The ROB2 tool will be employed to assess the quality of included studies. Stata 16 will be used for data analysis, and publication bias will be assessed using funnel plots and Egger's test. The quality of evidence will be evaluated according to GRADE, and trial sequence analysis (TSA) will be utilized to calculate the final total sample size required for the meta-analysis. The results of this systematic review will be published in a peer-reviewed journal. The proposed review protocol has been registered with the International Prospective Register of Systematic Reviews (PROSPERO; CRD42022380106).

Discussion

This systematic review will integrate current evidence on CKI in advanced CRC and analyze the clinical efficacy and safety of CKI combined with different chemotherapy regimens, providing valuable guidance on the use of CKI in CRC patients.

Echinacea purpurea polysaccharide intervene in hepatocellular carcinoma via modulation of gut microbiota to inhibit TLR4/NF-κB pathway

Echinacea purpurea polysaccharide (EPP) exhibit various pharmacological activities, including immunomodulatory, anti-inflammatory, and anti-tumor effects. In this study, we investigated the potential mechanism of EPP intervention in hepatocellular carcinoma (HCC). The results demonstrated that EPP effectively mitigated liver injury caused by HCC, inhibited the proliferation of HCC, and induced apoptosis. Following EPP intervention, there was a significant increase in propionic acid and butyric acid-producing gut microbiota such as Coprococcus, Clostridium and Roseburia, leading to enhanced expression of intestinal tight junction proteins and the repair of the intestinal barrier. This controls lipopolysaccharide (LPS) leakage, which in turn inhibits the TLR4/NF-κB pathway and reduces the expression of inflammatory factors such as IL-6, as well as migration factors like MMP-2. Metabolomics revealed the downregulation of pyrimidine metabolism and nucleotide metabolism, along with the upregulation of butyrate metabolism in tumor cells. This study demonstrated that EPP effectively regulated LPS leakage by modulating gut microbes, and this modulation influenced the TLR4/NF-κB pathway, ultimately disrupting tumor cell survival induced by HCC in mice.

Development and Evaluation of a Novel Hyaluronic Acid and Chitosan-modified Phytosome for Co-delivery of Oxymatrine and Glycyrrhizin for Combination Therapy

BACKGROUND

Multidrug resistance (MDR) of cancer cells is a major obstacle to efficient cancer chemotherapy. Combination therapy is expected to enhance the anticancer effect and reverse MDR. Numerous patents involve different kinds of nanoparticles for the co-delivery of multiple chemotherapeutics, but the FDA has approved none.

OBJECTIVE

In this study, oxymatrine (OMT) and glycyrrhizin (GL) were co-loaded into phytosomes as the core of nanocarriers, and the shell was cross-linked with chitosan (CS) and hyaluronic acid (HA) with the capability for the controlled, sequential release and the targeted drug uptake.

METHODS

Phospholipid complexes of OMT and GL (OGPs) were prepared by a solvent evaporation technique and could self-assemble in an aqueous solution to form phytosomes. CS and HA were sequentially coated on the surface of OGPs via electrostatic interactions to obtain CS coated OGPs (CS-OGPs) and HA modified CS-OGPs (HA-CS-OGPs), respectively. The particle size and zeta potential were measured to optimize the formulations. In vitro cytotoxicity and cellular uptake experiments on HepG2 cells were performed to evaluate the anticancer activity.

RESULTS

OGPs were obtained with nano-size around 100 nm, and CS and HA coating on phytosomes could change the particle size and surface potential. The drug loading of OMT and GL showed that the nanocarriers could maintain a fixed ratio of 1:1. The in vitro release experiments indicated the release of OMT and GL was pH-dependent and sequential: the release of OMT from CS-OGPs and HA-CS-OGPs was significantly increased at pH 5.0 compared to the release at pH 7.4, while GL exhibited sustained released from CS-OGPs and HA-CS-OGPs at pH 5.0. Furthermore, in vitro cytotoxicity and cellular uptake experiments on HepG2 cells demonstrated that the co-delivery system based on phytosomes had significant synergistic anti-tumor activities, and the effects were enhanced by CS and HA modification.

CONCLUSION

The delivery of OMT and GL via HA-CS-OGPs might be a promising treatment to reverse MDR in cancer therapy.

Adjunctive effect of compound Kushen injection for cancer: An overview of systematic reviews

ETHNOPHARMACOLOGICAL RELEVANCE

Compound Kushen (Sophora flavescens Aiton) Injection (CKI) is a Chinese herbal injection made from extracts of Kushen and Baituling (Heterosmilax japonica Kunth), containing matrine (MAT), oxymatrine (OMT) and other alkaloids with significant anti-tumor activity, and is widely used as an adjuvant treatment for cancer in China.

AIM OF THE STUDY

The existing systematic reviews/meta-analyses (SRs/MAs) were re-evaluated to provide a reference for the clinical application of CKI.

MATERIALS AND METHODS

SRs/MAs of CKI adjuvant therapy for cancer-related diseases were searched in four English language databases: PubMed, Embase, Web of Science, and Cochrane Library, all from the time of database construction to October 2022. 5 researchers independently conducted literature search and identification according to the inclusion criteria, and the data of the final literature were independently extracted, and finally the AMSTAR 2 tool, PRISMA statement and GRADE classification were used to evaluate the methodological quality of the included SRs/MAs, the degree of completeness of reporting and the quality of evidence for outcome indicators. Database registration: PROSPERO ID：CRD42022361349.

RESULTS

Eighteen SRs/MAs were finally included, with studies covering non-small cell lung cancer, primary liver cancer, gastric cancer, colorectal cancer, breast cancer, head and neck tumors, and cancer-related bone pain. The evaluation showed that the methodological quality of the included literature was extremely low, but most of the literature reported relatively complete entries; nine clinical effectiveness indicators for non-small cell lung cancer and digestive system tumors were rated as moderate in the GRADE quality of evidence, and the quality of other outcomes was low to very low.

CONCLUSION

CKI is a potentially effective drug for the adjuvant treatment of neoplastic diseases and may be more convincing for the adjuvant treatment of non-small cell lung cancer and digestive system tumors; however, due to the low methodological and evidentiary quality of the current SRs, their effectiveness needs to be confirmed by more high-quality evidence-based medical evidence.

Elucidation of the anti-lung cancer mechanism of Juan-Liu-San-Jie prescription based on network pharmacology and experimental validation

Lung cancer is a malignancy characterized by high morbidity and mortality, with lung adenocarcinoma being the most prevalent subtype. Our preliminary studies have demonstrated that the Juan-Liu-San-Jie (JLSJ) prescription, a Traditional Chinese Medicine prescription, possesses anti-lung adenocarcinoma cancer properties. However, the molecular mechanism underlying the therapeutic effects of the JLSJ prescription for lung adenocarcinoma remains incompletely elucidated. To address the knowledge gap, the present study employed network pharmacology to identify potential therapeutic targets. Specifically, the study utilized TCMSP, TCMID, and related references, as well as ChemMapper, to identify and predict the main active components and potential targets. Additionally, differentially expressed genes associated with the disease were obtained from the microarray dataset GSE19804 and GSE118370. The protein-protein Interaction network and Target-pathway network were then constructed. We also conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and subsequently presented the top 20 enriched pathways. The results indicated that the anti-lung cancer effects of JLSJ prescription may be attributed to its ability to mediate apoptosis of tumor cells, potentially through the PI3K/Akt signaling pathway. Then, a series of in vitro and in vivo experiments were conducted to validate the molecular mechanism predicted by network pharmacology. The findings of the in vivo study suggested that the JLSJ prescription could inhibit the growth of xenograft tumors of lung adenocarcinoma with fewer adverse effects. Also, the in vitro experiments corroborated that the JLSJ prescription could induce apoptosis of A549 cells. Furthermore, the upregulation of pro-apoptosis-related proteins and mRNAs, coupled with the downregulation of anti-apoptotic-related proteins and mRNAs, was observed. In conclusion, inducing apoptosis by inhibiting the PI3K/Akt signaling pathway was one of the underlying mechanisms by which the JLSJ prescription exerted its anti-lung adenocarcinoma effect.

Identification of glycogen phosphorylase L as a potential target for lung cancer

Traditional Chinese medicine (TCM) has been widely used for cancer treatment. Identification of anti-cancer targets of TCM is the first and principal step in discovering molecular mechanisms of TCM as well as obtaining novel targets for cancer therapy. In this study, glycogen phosphorylase L (PYGL) was identified as one of the targeted proteins for several TCMs and was upregulated in various cancer types. The expression level of PYGL was positively correlated with the stage of lung cancer and the poor prognosis of patients. Meanwhile, knockdown of PYGL significantly inhibited proliferation and migration in lung cancer cells. In addition, PYGL was associated with spindle, kinetochore, and microtubule, the cellular components that are closely related to mitosis, in lung cancer. Moreover, PYGL was more susceptible to be upregulated by 144 mutated genes. Taken together, PYGL is a potential target for lung cancer treatment and its molecular mechanism probably influences the mitotic function of cells by regulating energy metabolism.

Evaluation of efficacy and safety for compound kushen injection combined with intraperitoneal chemotherapy for patients with malignant ascites: A systematic review and meta-analysis

Objectives: Compound Kushen injection (CKI) combined with intraperitoneal chemotherapy (IPC) is widely used in the treatment of malignant ascites (MA). However, evidence about its efficacy and safety remains limited. This review aimed to evaluate the efficacy and safety of CKI combined with IPC for the treatment of MA. Methods: Protocol of this review was registered in PROSPERO (CRD42022304259). Randomized controlled trials (RCTs) on the efficacy and safety of IPC with CKI for the treatment of patients with MA were searched through 12 electronic databases and 2 clinical trials registration platforms from inception until 20 January 2023. The Cochrane risk-of-bias tool was used to assess the quality of the included trials through the risk of bias assessment. We included RCTs that compared IPC single used or CKI combined with IPC for patients with MA schedule to start IPC. The primary outcome was identified as an objective response rate (ORR), while the secondary outcomes were identified as the quality of life (QoL), survival time, immune functions, and adverse drug reactions (ADRs). The Revman5.4 and Stata17 software were used to calculate the risk ratio (RR) at 95% confidence intervals (CI) for binary outcomes and the mean difference (MD) at 95% CI for continuous outcomes. The certainty of the evidence was assessed according to the GRADE criteria. Results: A total of 17 RCTs were assessed, which included 1200 patients. The risk of bias assessment of the Cochrane risk-of-bias tool revealed that one study was rated high risk and the remaining as unclear or low risk. Meta-analysis revealed that CKI combined with IPC had an advantage in increasing ORR (RR = 1.31, 95% CI 1.20 to 1.43, p < 0.00001) and QoL (RR = 1.50, 95% CI 1.23 to 1.83, p < 0.0001) when compared with IPC alone. Moreover, the combined treatment group showed a lower incidence of myelosuppression (RR = 0.51, 95%CI 0.40-0.64, p < 0.00001), liver dysfunction (RR = 0.33, 95%CI 0.16 to 0.70, p = 0.004), renal dysfunction (RR = 0.39, 95%CI 0.17 to 0.89, p = 0.02), and fever (RR = 0.51, 95%CI 0.35 to 0.75, p = 0.0007) compared to those of the control group. The quality of evidence assessment through GRADE criteria showed that ORR, myelosuppression, and fever were rated moderate, renal dysfunction and liver dysfunction were rated low, and QoL and abdominal pain were rated very low. Conclusion: The efficacy and safety of CKI combined with IPC were superior to that with IPC alone for the treatment of MA, which indicates the potentiality of the treatment. However, more high-quality RCTs are required to validate this conclusion. Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022304259], identifier [PROSPERO 2022 CRD42022304259].

Effectiveness of Jiedu granule on gut microbiota in patients with advanced hepatocellular carcinoma: a randomized controlled trial

OBJECTIVE

To observe whether Jiedu granule (, JDG) modulates the composition of the gut microbiota during advanced hepatocellular carcinoma (HCC).

METHODS

A randomized controlled trial was conducted. Sixty-two advanced HCC participants were randomly allocated to receive JDG or placebo. The median overall survival (OS) times of patients and the variation of relative abundance of bacteria over time were used as main outcome measures.

RESULTS

Patients who received JDG demonstrated significantly longer median OS times compared with the placebo group. Pyrosequencing of the V3 regions of 16S rRNA genes revealed a dose dependent deviation of gut microbiota in response to JDG treatment. Redundancy analysis identified and Peptostre-ptococcaceae which related to the onset of liver cancer disappeared after 1-month and 2-month JDG treatment, while in control group, no significant changes of these two bacteria were found. The variation tendency of relative abundance of (essential in immunoblocking therapy of tumor) in JDG group was not obvious while in control group, it was decreased significantly with time. The relative abundance of (correlated with the occurrence of liver cancer) was increased in JDG group and was decreased in control group over time.

CONCLUSION

Changes in the gut microbiota may be associated with the efficiency of JDG on survival period of advanced HCC patients. Trial registration：Chinese Clinical TRIAL Registry ChiCTR-OOC-16008002.

Computational Metabolomics Reveals the Potential Mechanism of Matrine Mediated Metabolic Network Against Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a complex issue in cancer treatment in the world at present. Matrine is the main active ingredient isolated from Sophora flavescens air and possesses excellent antitumor effects in HCC. However, the specific underlying mechanisms, especially the possible relationships between the anti-HCC effect of matrine and the related metabolic network of HCC, are not yet clear and need further clarification. In this study, an integrative metabolomic-based bioinformatics algorithm was designed to explore the underlying mechanism of matrine on HCC by regulating the metabolic network. Cell clone formation, invasion, and adhesion assay were utilized in HCC cells to evaluate the anti-HCC effect of matrine. A cell metabolomics approach based on LC-MS was used to obtain the differential metabolites and metabolic pathways regulated by matrine. The maximum activity contribution score model was developed and applied to calculate high contribution target genes of matrine, which could regulate a metabolic network based on the coexpression matrix of matrine-regulated metabolic genes and targets. Matrine significantly repressed the clone formation and invasion, enhanced cell–cell adhesion, and hampered cell matrix adhesion in SMMC-7721 cells. Metabolomics results suggested that matrine markedly regulated the abnormal metabolic network of HCC by regulating the level of choline, creatine, valine, spermidine, 4-oxoproline, D-(+)-maltose, L-(−)-methionine, L-phenylalanine, L-pyroglutamic acid, and pyridoxine, which are involved in D-glutamine and D-glutamate metabolism, glycine, serine and threonine metabolism, arginine and proline metabolism, etc. Our proposed metabolomic-based bioinformatics algorithm showed that the regulating metabolic networks of matrine exhibit anti-HCC effects through acting on MMP7, ABCC1, PTGS1, etc. At last, MMP7 and its related target β-catenin were validated. Together, the metabolomic-based bioinformatics algorithm reveals the effects of the regulating metabolic networks of matrine in treating HCC relying on the unique characteristics of the multitargets and multipathways of traditional Chinese medicine.

Medicinal Plants for the Treatment of Gastrointestinal Cancers From the Metabolomics Perspective

Gastrointestinal cancer (GIC), primarily including colorectal cancer, gastric cancer, liver cancer, pancreatic cancer, and esophageal cancer, is one of the most common causes of cancer-related deaths with increasing prevalence and poor prognosis. Medicinal plants have been shown to be a great resource for the treatment of GIC. Due to their complex manifestations of multi-component and multi-target, the underlying mechanisms how they function against GIC remain to be completely deciphered. Cell metabolism is of primary importance in the initialization and development of GIC, which is reported to be a potential target. As an essential supplement to the newest “omics” sciences, metabolomics focuses on the systematic study of the small exogenous and endogenous metabolites involved in extensive biochemical metabolic pathways of living system. In good agreement with the systemic perspective of medicinal plants, metabolomics offers a new insight into the efficacy assessment and action mechanism investigation of medicinal plants as adjuvant therapeutics for GIC therapy. In this review, the metabolomics investigations on metabolism-targeting therapies for GIC in the recent 10 years were systematically reviewed from five aspects of carbohydrate, lipid, amino acid, and nucleotide metabolisms, as well as other altered metabolisms (microbial metabolism, inflammation, and oxidation), with particular attention to the potential of active compounds, extracts, and formulae from medicinal plants. Meanwhile, the current perspectives and future challenges of metabolism-targeting therapies of medicinal plants for GIC were also discussed. In conclusion, the understanding of the action mechanisms of medicinal plants in GIC from the metabolomics perspective will contribute to the clinical application of potential candidates from the resourceful medicinal plants as novel and efficient adjuvant therapeutics for GIC therapy.

Identification of Anti-Proliferative Compounds from Genista monspessulana Seeds through Covariate-Based Integration of Chemical Fingerprints and Bioactivity Datasets

Genista monspessulana (L.) L.A.S. Johnson (Fabaceae) is a Mediterranean plant introduced to South America and other regions for ornamental purposes. However, it is considered an invasive shrub due to its reproductive vigor in many areas. Unlike other Genista plants, G. monspessulana has few studies disclosing its biologically active components, particularly cytotoxic agents against cancer cells. Thus, as part of our research on anti-proliferative bioactives, a set of ethanolic seed extracts from ten accessions of G. monspessulana, collected in the Bogotá plateau, were evaluated against four cell lines: PC-3 (prostate adenocarcinoma), SiHa (cervical carcinoma), A549 (lung carcinoma), and L929 (normal mouse fibroblasts). Extracts were also analyzed through liquid chromatography coupled with mass spectrometry (LC/MS) to record chemical fingerprints and determine the composition and metabolite variability between accessions. Using multiple covariate statistics, chemical and bioactivity datasets were integrated to recognize patterns and identify bioactive compounds among studied extracts. G. monspessulana seed-derived extracts exhibited dose-dependent antiproliferative activity on PC-3 and SiHa cell lines (>500 µg/mL < IC50 < 26.3 µg/mL). Seven compounds (1−7) were inferred as the compounds most likely responsible for the observed anti-proliferative activity and subsequently isolated and identified by spectroscopic techniques. A tricyclic quinolizidine (1) and a pyranoisoflavone (2) were found to be the most active compounds, exhibiting selectivity against PC-3 cell lines (IC50 < 18.6 µM). These compounds were used as precursors to obtain a quinolizidine-pyranoisoflavone adduct via Betti reaction, improving the activity against PC-3 and comparable to curcumin as the positive control. Results indicated that this composition−activity associative approach is advantageous to finding those bioactive principles efficiently within active extracts. This correlative association can be employed in further studies focused on the targeted isolation of anti-proliferative compounds from Genista plants and accessions.

Chinese Herbal Medicine for Primary Liver Cancer Therapy: Perspectives and Challenges

Primary liver cancer (PLC) is one of the most common solid malignancies. However, PLC drug development has been slow, and first-line treatments are still needed; thus, studies exploring and developing alternative strategies for effective PLC treatment are urgently needed. Chinese herbal medicine (CHM) has long been applied in the clinic due to its advantages of low toxicity and targeting of multiple factors and pathways, and it has great potential for the development of novel natural drugs against PLC.

Purpose: This review aims to provide an update on the pharmacological mechanisms of Chinese patent medicines (CPMs) and the latest CHM-derived compounds for the treatment of PLC and relevant clinical evaluations.

Materials and Methods: A systematic search of English literature databases, Chinese literature, the Clinical Trials Registry Platform, and the Chinese Clinical Trial Registry for studies of CHMs for PLC treatment was performed.

Results: In this review, we summarize the clinical trials and mechanisms of CPMs for PLC treatment that have entered the clinic with the approval of the Chinese medicine regulatory authority. These CPMs included Huaier granules, Ganfule granules, Fufang Banmao capsules, Jinlong capsules, Brucea javanica oil emulsions, and compound kushen injections. We also summarize the latest in vivo, in vitro, and clinical studies of CHM-derived compounds against PLC: icaritin and ginsenoside Rg3. Dilemmas facing the development of CHMs, such as drug toxicity and low oral availability, and future developments are also discussed.

Conclusion: This review provides a deeper the understanding of CHMs as PLC treatments and provides ideas for the development of new natural drugs against PLC.

Matrine injection inhibits pancreatic cancer growth via modulating carbonic anhydrases- a network pharmacology-based study with in vitro validation

ETHNOPHARMACOLOGICAL RELEVANCE

Matrine injection is a complex mixture of plant bioactive substances extracted from Sophora flavescens Aiton and Smilax glabra Roxb. Since its approval by the Chinese Food and Drug Administration (CFDA) in 1995, Matrine injection has been clinically used as a complementary and alternative treatment for various cancers; however, the underlying mechanism of pancreatic cancer treatment is yet to be elucidated.

AIM OF THE STUDY

The present study explores the potential mechanism of matrine injection on pancreatic cancer through network pharmacology technique and in vitro experimental validation.

MATERIALS AND METHODS

Genes differentially expressed in pancreatic cancer were obtained from the Gene Expression Omnibus (GEO) database (GSE101448). The potential active components of matrine injection were selected following a literature search, and target prediction was performed by the SwissTarget Prediction database. Overlapping genes associated with survival were screened by the Gene Expression Profiling Interactive Analysis (GEPIA) database. In vitro experimental validation was performed with cell counting kit-8 (CCK-8) assay, apoptosis detection, cell cycle analysis, immunoblotting, and co-immunoprecipitation of the identified proteins.

RESULTS

One thousand seven hundred genes differentially expressed among pancreatic tumor and non-tumor tissues were screened out. Sixteen active components and 226 predicted target genes were identified in matrine injection. A total of 25 potential target genes of matrine injection for the treatment of pancreatic cancer were obtained. Among them, the prognostic target genes carbonic anhydrase 9 (CA9) and carbonic anhydrase 12 (CA12) based on the GEPIA database are differently expressed in tumors compared to adjacent normal tissue. In vitro experiments, the results of CCK-8 assay, apoptosis and cell cycle analysis, immunoblotting, and co-immunoprecipitation showed that matrine injection inhibited Capan-1 and Mia paca-2 proliferation, arrested the cell cycle at the S phase, and induced apoptosis through up-regulated CA12 and down-regulated CA9.

CONCLUSIONS

In this study, bioinformatics and network pharmacology were applied to explore the treatment mechanism on pancreatic cancer with matrine injection. This study demonstrated that matrine injection inhibited proliferation, arrested the cell cycle, and induced apoptosis of pancreatic cancer cells. The mechanism may be related to the induction of CA12 over-expression, and CA9 reduced expression. As novel targets for pancreatic cancer treatment, Carbonic anhydrases require further study.

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.

An advanced network pharmacology study to explore the novel molecular mechanism of Compound Kushen Injection for treating hepatocellular carcinoma by bioinformatics and experimental verification

Background

Compound Kushen Injection (CKI) is a Chinese patent drug that exerts curative effects in the clinical treatment of hepatocellular carcinoma (HCC). This study aimed to explore the targets and potential pharmacological mechanisms of CKI in the treatment of HCC.

Methods

In this study, network pharmacology was used in combination with molecular biology experiments to predict and verify the molecular mechanism of CKI in the treatment of HCC. The constituents of CKI were identified by UHPLC-MS/MS and literature search. The targets corresponding to these compounds and the targets related to HCC were collected based on public databases. To screen out the potential hub targets of CKI in the treatment of HCC, a compound-HCC target network was constructed. The underlying pharmacological mechanism was explored through the subsequent enrichment analysis. Interactive Gene Expression Profiling Analysis and Kaplan-Meier plotter were used to examine the expression and prognostic value of hub genes. Furthermore, the effects of CKI on HCC were verified through molecular docking simulations and cell experiments in vitro.

Results

Network analysis revealed that BCHE, SRD5A2, EPHX2, ADH1C, ADH1A and CDK1 were the key targets of CKI in the treatment of HCC. Among them, only CDK1 was highly expressed in HCC tissues, while the other 5 targets were lowly expressed. Furthermore, the six hub genes were all closely related to the prognosis of HCC patients in survival analysis. Molecular docking revealed that there was an efficient binding potential between the constituents of CKI and BCHE. Experiments in vitro proved that CKI inhibited the proliferation of HepG2 cells and up-regulated SRD5A2 and ADH1A, while down-regulated CDK1 and EPHX2.

Conclusions

This study revealed and verified the targets of CKI on HCC based on network pharmacology and experiments and provided a scientific reference for further mechanism research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12906-022-03530-3.

Beneficial effects of mijianchangpu decoction on ischemic stroke through components accessing to the brain based on network pharmacology

ETHNOPHARMACOLOGICAL RELEVANCE

To explore the effective components, potential targets and neuroprotective related mechanisms of Mijianchangpu decoction (MJCPD), a well-known TCM used by the Chinese Hui minorities to treat stroke, on the prevention and treatment of ischemic stroke (IS) by using experimental models combined with network pharmacology.

MATERIALS AND METHODS

The neuroprotective efficacy of MJCPD was estimated by applying the middle cerebral artery occlusion (MCAO) induced cerebral ischemia rats, and the neurological deficits score, TTC and HE staining as well as behavioral evaluation tests were employed to evaluate the beneficial effects. Meanwhile, the bioactive components of MJCPD responsible for the neuroprotective effects were identified by detecting the constituents in the brain of the MCAO rats with UHPLC-QTOF-MS/MS techniques, and these compounds were then underwent for network pharmacology analysis. Firstly, the targets of the bioactive compounds of MJCPD were predicted using Pharmmapper database, and simultaneously, the targets of IS disease were obtained from disease databases including DisGenet, OMIM, and GeneCards. Secondly, the protein-protein interaction (PPI) network between the targets and diseases were established to give the possible therapeutic targets for IS. Thirdly, the go function and KEGG pathway enrichment analysis were carried out and the compound-target-pathway network was constructed by Cytoscape software. Finally, the effective compounds, core targets and possible pathways were obtained by analyzing the connectivity of the network. More importantly, the core targets were verified by western blot experiments to validate the reliability of this study.

RESULTS

MJCPD exhibited significant neuroprotective effect on IS, and 16 bioactive components of MJCPD were identified in the brain of the MCAO rats. 59 and 1982 targets related with IS disease were explored from Pharmapper and disease databases, respectively, and 32 intersecting targets were obtained as hypothetical therapeutic targets. Based on the results of the compound-target-pathway and PPI network with the degree was greater than the median, 8 effective compounds (suberic acid, epishyobunone, crocetin monomethyl ester, sfaranal, (Z)-6-octadccenoic acid, nerolidol and gurjunene) and 5 hub targets (SRC, MAPK8, MAPK14, EGFR and MAPK1) as well as 12 pathways were predicted. Western blot results showed that EGFR, p38, ERK and SRC proteins were expressed significantly different after MJCPD treatment as compared with the model group.

CONCLUSION

The present study employed network pharmacology, pharmacodynamics and molecular biology techniques to predict and validate the core potential targets and signaling pathways as well as the bioactive components of MJCPD responsible for the treatment of IS. All of which are very helpful to clarify the neuroprotective mechanism of MJCPD, and obviously, the active compounds and targets in this study can also provide clues for the treatment of IS.

Comparative Analysis of the Efficacy and Safety of Different Traditional Chinese Medicine Injections in the Treatment of Cancer-Related Pain: A Bayesian Network Meta-Analysis

Background: Given the limitations of three-step analgesic therapy and the extensive use of traditional Chinese medicine injections (TCMIs) for cancer-related pain (CRP), this network meta-analysis (NMA) aims to compare the efficacy and safety of different regimens of TCMIs for CRP.

Methods: A literature search was conducted in seven electronic databases for all related articles published before 12 April 2021. Randomized controlled trials (RCTs) were screened by a prior eligible criteria. The quality of literature was evaluated by the Cochrane risk of bias tool. We used Stata 16.0 software to analyze data including total pain relief rate, quality of life, and the incidence of adverse reactions. The surface under the cumulative ranking curve (SUCRA) probability values were applied to rank the interventions. Radar map was used to exhibit the most outstanding regimen for a certain outcome. Synthetic sorting bubble diagram was performed to show the relatively better regimen by integrating two or three outcomes.

Results: A total of 84 RCTs involving 8,044 patients were included. The results indicated that YDZYR + AN (Yadanziyouru injection plus analgesic) ranked first for pain relief rate, closely followed by KLT + AN (Kanglaite injection plus analgesic). AD + AN (Aidi injection plus analgesic) ranked first for quality of life, KLT + AN following closely. The total adverse reaction rate of FFKS + AN (Fufangkushen injection plus analgesic) was the lowest, and the constipation rate of FFKS was the lowest. In terms of the incidence of nausea and vomiting, KLT + AN was the best choice. In the plots analysis, the results of integrated total incidence of adverse reactions and pain relief rate analysis indicated that FFKS + AN was the most appropriate regimen. Meanwhile, it had the lowest incidence of integrated constipation, nausea and vomiting, and total adverse reactions. KLT + AN was the best in alleviating pain and improving quality of life integrated outcomes.

Conclusion: In conclusion, FFKS + AN was the best treatment regimen for the pain relief rate and total adverse reaction rate, and it was also the safest regimen for CRP treatment. KLT + AN was the most effective choice. Further, compared with analgesic treatment alone for patients with CRP, TCMIs + AN combination treatment strategies are significantly more effective. However, more high-quality RCTs are required to support these conclusions.

Systematic Review Registration: (https://www.crd.york.ac.uk/prospero/#recordDetails, https://www.crd.york.ac.uk/prospero/export_details_pdf.php), identifier (ChiCTR-ONC-CRD42021267829)

OMICS Applications for Medicinal Plants in Gastrointestinal Cancers: Current Advancements and Future Perspectives

Gastrointestinal cancers refer to a group of deadly malignancies of the gastrointestinal tract and organs of the digestive system. Over the past decades, considerable amounts of medicinal plants have exhibited potent anticancer effects on different types of gastrointestinal cancers. OMICS, systems biology approaches covering genomics, transcriptomics, proteomics and metabolomics, are broadly applied to comprehensively reflect the molecular profiles in mechanistic studies of medicinal plants. Single- and multi-OMICS approaches facilitate the unravelling of signalling interaction networks and key molecular targets of medicinal plants with anti-gastrointestinal cancer potential. Hence, this review summarizes the applications of various OMICS and advanced bioinformatics approaches in examining therapeutic targets, signalling pathways, and the tumour microenvironment in response to anticancer medicinal plants. Advances and prospects in this field are also discussed.

Compound Kushen Injection Protects Skin From Radiation Injury via Regulating Bim

Background: Radiation-induced skin injury is a major side-effect observed in cancer patients who received radiotherapy. Thus identifying new radioprotective drugs for prevention or treatment of post-irradiation skin injury should be prompted. A large number of clinical studies have confirmed that Compound Kushen injection (CKI) can enhance efficacy and reduce toxicity of radiotherapy. The aim of this study is to confirm the effect of CKI in alleviating radiotherapy injury in the skin and explore the exact mechanism.

Methods: 60 patients who met the inclusion/exclusion criteria were allocated to treatment group (CKI before radiotherapy) or control group (normal saline before radiotherapy) randomly. MTT assay, flow cytometry, Western Blot, and transient transfection were performed to detect the cell viability, cell apoptosis and Bim expression after treatment with CKI or/and radiotherapy.

Results: CKI had the effect of alleviating skin injury in cancer patients who received radiotherapy in clinic. CKI induced cancer cell apoptosis when combined with irradiation (IR), while it reversed the induction of cell apoptosis by IR in human skin fibroblast (HSF) cells. And Bim, as a tumor suppressor, was induced in cancer cells but had no change in HSF cells when treated with CKI. Moreover, the above effect could be attenuated when Bim was silenced by siRNA.

Conclusion: We conclude that CKI represents a promising radio-protective agent with a potential differential beneficial effect on both cancer cells (inducing apoptosis) and HSF cells (providing radio-protection via inhibiting IR-induced apoptosis), via regulating Bim. Our study uncovers a novel mechanism by which CKI inhibits human cancer cell while protects skin from radiotherapy, indicating CKI might be a promising radio-protective drug.

Clinical Trial Registration: Chinese Clinical Trial Registry (www.chictr.org.cn), identifier ChiCTR2100049164.

A System Pharmacology Model for Decoding the Synergistic Mechanisms of Compound Kushen Injection in Treating Breast Cancer

Breast cancer (BC) is one of the most common malignant tumors among women worldwide and can be treated using various methods; however, side effects of these treatments cannot be ignored. Increasing evidence indicates that compound kushen injection (CKI) can be used to treat BC. However, traditional Chinese medicine (TCM) is characterized by “multi-components” and “multi-targets”, which make it challenging to clarify the potential therapeutic mechanisms of CKI on BC. Herein, we designed a novel system pharmacology strategy using differentially expressed gene analysis, pharmacokinetics synthesis screening, target identification, network analysis, and docking validation to construct the synergy contribution degree (SCD) and therapeutic response index (TRI) model to capture the critical components responding to synergistic mechanisms of CKI in BC. Through our designed mathematical models, we defined 24 components as a high contribution group of synergistic components (HCGSC) from 113 potentially active components of CKI based on ADME parameters. Pathway enrichment analysis of HCGSC targets indicated that Rhizoma Heterosmilacis and Radix Sophorae Flavescentis could synergistically target the PI3K-Akt signaling pathway and the cAMP signaling pathway to treat BC. Additionally, TRI analysis showed that the average affinity of HCGSC and targets involved in the key pathways reached -6.47 kcal/mmol, while in vitro experiments proved that two of the three high TRI-scored components in the HCGSC showed significant inhibitory effects on breast cancer cell proliferation and migration. These results demonstrate the accuracy and reliability of the proposed strategy.

Uncovering the anti-NSCLC effects and mechanisms of gypenosides by metabolomics and network pharmacology analysis

ETHNOPHARMACOLOGICAL RELEVANCE

Lung cancer is the chief reason of cancer death worldwide, and non-small cell lung cancer (NSCLC) make up the majority of lung cancers. Gypenosides are the main active constituents from Gynostemma pentaphyllum. Previous studies showed that they were used to remedy many cancers. The effect of gypenosides on NSCLC has never been studied from the perspective of network pharmacology and metabolomics. The mechanism is still not clear and remains to be explored.

AIM OF THE STUDY

To explore the anti-NSCLC activity and mechanism of gypenosides in A549 cells.

MATERIAL/METHODS

Gypenosides of G. pentaphyllum were detected by HPLC-MS. The cytotoxicity was detected by MTT assay. The migration, cell cycle and apoptosis of gypenosides were studied by wound healing assay, JC-1 assay and flow cytometry. The mechanism of gypenosides on NSCLC was studied by metabolomics and network pharmacology. Some key proteins and pathways were further confirmed by Western blot.

RESULTS

Eleven gypenosides were detected by HPLC-MS. Gypenosides could suppress the proliferation of A549 cells, inhibit the migration of A549 cells, induce apoptosis and arrest cell cycle in G0/G1 phase. Metabolomics and network pharmacology approach revealed that gypenosides might affect 17 metabolite related proteins by acting on 9 candidate targets (STAT3, VEGFA, EGFR, MMP9, IL2, TYMS, FGF2, HPSE, LGALS3), thus resulting in the changes of two metabolites (uridine 5'-monophosphate, D-4'-Phosphopantothenate) and two metabolic pathways (pyrimidine metabolism; pantothenate and CoA biosynthesis). Western blotting indicated that gypenosides might inhibit A549 cells through MMP9, STAT3 and TYMS to indirectly affect the pathways of pyrimidine metabolism, pantothenate and CoA biosynthesis.

CONCLUSIONS

This study revealed that metabolomics combined with network pharmacology was conducive to understand the anti-NSCLC mechanism of gypenosides.

Compound Kushen Injection intervenes metabolic reprogramming and epithelial-mesenchymal transition of HCC via regulating β-catenin/c-Myc signaling

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most extensive and most deadly cancers worldwide. The invasion and metastasis characteristics of HCC dramatically affect the prognosis and survival of HCC patients. Compound Kushen Injection (CKI) is a GMP produced, proverbially applied traditional Chinese medicine formula in China to treat cancer-associated pains, and used as an adjunctive therapy for HCC. Until so far, whether CKI could suppress the metastasis of HCC through regulation of epithelial-mesenchymal transition or metabolic reprogramming is still ambiguous.

PURPOSE

In this study, the anti-metastasis effects of CKI were clarified and its pharmacological mechanisms were systematically explored.

METHODS

Cell invasion and cell adhesion assay were performed in SMMC-7721 cells to assess the anti-metastasis role of CKI, and the histopathological evaluation and biochemical detection were utilized in DEN-induced HCC rats to verify the anti-HCC effect of CKI. Serum and liver samples were analyzed with ¹H NMR metabolomics approach to screen the differential metabolites and further target quantification the content of key metabolites. Finally, western blotting and immunofluorescence assay were applied to verify the crucial signaling pathway involved in metabolites.

RESULTS

CKI markedly repressed the invasion and adhesion in SMMC-7721 cells and significantly improved the liver function of DEN-induced HCC rats. CKI significantly regulated the expression of epithelial-mesenchymal transition (EMT) markers (Vimentin and E-cadherin). Metabolomics results showed that CKI regulated the metabolic reprogramming of HCC by inhibiting the key metabolites (citrate and lactate) and enzymes (HK and PK) in glycolysis process. Importantly, we found that c-Myc mediates the inhibitory effect of CKI on glycolysis. We further demonstrated that CKI inhibits c-Myc expression through modulating Wnt/β-catenin pathway in SMMC-7721 cells and DEN-induced HCC rats. Furthermore, through activating Wnt/β-catenin pathway with LiCl, the inhibitory effects of CKI on HCC were diminished.

CONCLUSION

Together, this study reveals that CKI intervenes metabolic reprogramming and epithelial-mesenchymal transition of HCC via regulating β-catenin/c-Myc signaling pathway. Our research provides a new understanding of the mechanism of CKI against invasion and metastasis of HCC from the perspective of metabolic reprogramming.

Advances in analytical techniques and quality control of traditional Chinese medicine injections

Traditional Chinese medicine injections (TCMIs) are a new pharmaceutical form in the modernization of traditional Chinese medicines (TCMs). Its efficacy is rapid, the curative effect is improved, and is widely used in critical and acute diseases, complicated and severe diseases, and other treatment. However, with the broad applications of TCMIs, clinical adverse reactions frequently occur, and safety problems become more prominent. Therefore, the quality control of TCMIs is essential. Chemical analysis methods and biological analysis methods are widely used in the quality control of TCMIs. This article describes the current status of TCMIs, the analytical techniques, and methods currently used, and the quality control of TCMIs. A summary of the advantages and disadvantages of the current analysis methods is presented. An overview of the quality control of TCMIs is introduced. In addition, emerging techniques of the quality control of TCMIs are introduced.

An Advanced Systems Pharmacology Strategy Reveals AKR1B1, MMP2, PTGER3 as Key Genes in the Competing Endogenous RNA Network of Compound Kushen Injection Treating Gastric Carcinoma by Integrated Bioinformatics and Experimental Verification

Gastric carcinoma (GC) is a severe tumor of the digestive tract with high morbidity and mortality and poor prognosis, for which novel treatment options are urgently needed. Compound Kushen injection (CKI), a classical injection of Chinese medicine, has been widely used to treat various tumors in clinical practice for decades. In recent years, a growing number of studies have confirmed that CKI has a beneficial therapeutic effect on GC, However, there are few reports on the potential molecular mechanism of action. Here, using systems pharmacology combined with proteomics analysis as a core concept, we identified the ceRNA network, key targets and signaling pathways regulated by CKI in the treatment of GC. To further explore the role of these key targets in the development of GC, we performed a meta-analysis to compare the expression differences between GC and normal gastric mucosa tissues. Functional enrichment analysis was further used to understand the biological pathways significantly regulated by the key genes. In addition, we determined the significance of the key genes in the prognosis of GC by survival analysis and immune infiltration analysis. Finally, molecular docking simulation was performed to verify the combination of CKI components and key targets. The anti-gastric cancer effect of CKI and its key targets was verified by in vivo and in vitro experiments. The analysis of ceRNA network of CKI on GC revealed that the potential molecular mechanism of CKI can regulate PI3K/AKT and Toll-like receptor signaling pathways by interfering with hub genes such as AKR1B1, MMP2 and PTGERR3. In conclusion, this study not only partially highlighted the molecular mechanism of CKI in GC therapy but also provided a novel and advanced systems pharmacology strategy to explore the mechanisms of traditional Chinese medicine formulations.

High Throughput Transcriptome Data Analysis and Computational Verification Reveal Immunotherapy Biomarkers of Compound Kushen Injection for Treating Triple-Negative Breast Cancer

Background

Although notable therapeutic and prognostic benefits of compound kushen injection (CKI) have been found when it was used alone or in combination with chemotherapy or radiotherapy for triple-negative breast cancer (TNBC) treatment, the effects of CKI on TNBC microenvironment remain largely unclear. This study aims to construct and validate a predictive immunotherapy signature of CKI on TNBC.

Methods

The UPLC-Q-TOF-MS technology was firstly used to investigate major constituents of CKI. RNA sequencing data of CKI-perturbed TNBC cells were analyzed to detect differential expression genes (DEGs), and the GSVA algorithm was applied to explore significantly changed pathways regulated by CKI. Additionally, the ssGSEA algorithm was used to quantify immune cell abundance in TNBC patients, and these patients were classified into distinct immune infiltration subgroups by unsupervised clustering. Then, prognosis-related genes were screened from DEGs among these subgroups and were further overlapped with the DEGs regulated by CKI. Finally, a predictive immunotherapy signature of CKI on TNBC was constructed based on the LASSO regression algorithm to predict mortality risks of TNBC patients, and the signature was also validated in another TNBC cohort.

Results

Twenty-three chemical components in CKI were identified by UPLC-Q-TOF-MS analysis. A total of 3692 DEGs were detected in CKI-treated versus control groups, and CKI significantly activated biological processes associated with activation of T, natural killer and natural killer T cells. Three immune cell infiltration subgroups with 1593 DEGs were identified in TNBC patients. Then, two genes that can be down-regulated by CKI with hazard ratio (HR) > 1 and 26 genes that can be up-regulated by CKI with HR < 1 were selected as key immune- and prognosis-related genes regulated by CKI. Lastly, a five-gene prognostic signature comprising two risky genes (MARVELD2 and DYNC2I2) that can be down-regulated by CKI and three protective genes (RASSF2, FERMT3 and RASSF5) that can be up-regulated by CKI was developed, and it showed a good performance in both training and test sets.

Conclusions

This study proposes a predictive immunotherapy signature of CKI on TNBC, which would provide more evidence for survival prediction and treatment guidance in TNBC as well as a paradigm for exploring immunotherapy biomarkers in compound medicines.

Artificial intelligence to deep learning: machine intelligence approach for drug discovery

Drug designing and development is an important area of research for pharmaceutical companies and chemical scientists. However, low efficacy, off-target delivery, time consumption, and high cost impose a hurdle and challenges that impact drug design and discovery. Further, complex and big data from genomics, proteomics, microarray data, and clinical trials also impose an obstacle in the drug discovery pipeline. Artificial intelligence and machine learning technology play a crucial role in drug discovery and development. In other words, artificial neural networks and deep learning algorithms have modernized the area. Machine learning and deep learning algorithms have been implemented in several drug discovery processes such as peptide synthesis, structure-based virtual screening, ligand-based virtual screening, toxicity prediction, drug monitoring and release, pharmacophore modeling, quantitative structure-activity relationship, drug repositioning, polypharmacology, and physiochemical activity. Evidence from the past strengthens the implementation of artificial intelligence and deep learning in this field. Moreover, novel data mining, curation, and management techniques provided critical support to recently developed modeling algorithms. In summary, artificial intelligence and deep learning advancements provide an excellent opportunity for rational drug design and discovery process, which will eventually impact mankind. The primary concern associated with drug design and development is time consumption and production cost. Further, inefficiency, inaccurate target delivery, and inappropriate dosage are other hurdles that inhibit the process of drug delivery and development. With advancements in technology, computer-aided drug design integrating artificial intelligence algorithms can eliminate the challenges and hurdles of traditional drug design and development. Artificial intelligence is referred to as superset comprising machine learning, whereas machine learning comprises supervised learning, unsupervised learning, and reinforcement learning. Further, deep learning, a subset of machine learning, has been extensively implemented in drug design and development. The artificial neural network, deep neural network, support vector machines, classification and regression, generative adversarial networks, symbolic learning, and meta-learning are examples of the algorithms applied to the drug design and discovery process. Artificial intelligence has been applied to different areas of drug design and development process, such as from peptide synthesis to molecule design, virtual screening to molecular docking, quantitative structure-activity relationship to drug repositioning, protein misfolding to protein-protein interactions, and molecular pathway identification to polypharmacology. Artificial intelligence principles have been applied to the classification of active and inactive, monitoring drug release, pre-clinical and clinical development, primary and secondary drug screening, biomarker development, pharmaceutical manufacturing, bioactivity identification and physiochemical properties, prediction of toxicity, and identification of mode of action.

Investigating the Pharmacological Mechanisms of SheXiang XinTongNing Against Coronary Heart Disease Based on Network Pharmacology and Experimental Evaluation

SheXiang XinTongNing (XTN), which is composed of six traditional Chinese herbs, is a commercially available Chinese patent medicine that has been widely used as the treatment of coronary heart disease (CHD). Its mechanisms against coronary heart disease, however, remain largely unknown. This study aimed to investigate the pharmacological mechanisms of XTN against CHD via network pharmacology and experimental evaluation. In this study, GO enrichment and KEGG pathway enrichment were firstly performed for acquiring the potentially active constituents of XTN, the candidate targets related to coronary heart disease, the drug-components-targets network as well as the protein-protein interaction network and further predicting the mechanisms of XTN against coronary heart disease. Subsequently, a series of in vitro experiments, specifically MTT assay, flow cytometry and Real-time quantitative polymerase chain reaction analysis, and a succession of in vivo experiments, including Tunel staining and immunohistochemical staining were conducted for further verification. Results showed that Bcl-2, IGF1, CASP3 were the key candidate targets which significantly associated with multiple pathways, namely PI3K-Akt signaling pathway and MAPK signaling pathway. It indicated that the potential mechanism of XTN against CHD may be predominantly associated with cell apoptosis. The in vitro experimental results showed that XTN treatment remarkably decreased the apoptotic rate and Bax/Bcl-2 ratio of H9c2 cells. Histological results confirmed that XTN not only effectively alleviated oxidative damage caused by myocardial ischemia but inhibited cell apoptosis. Given the above, through the combined utilization of virtual screening and experimental verification, the findings suggest that XTN makes a significant contribution in protecting the heart from oxidative stress via regulating apoptosis pathways, which lays the foundations and offers an innovative idea for future research.

Mechanisms exploration of Xiaojin Pills on lung cancer based on metabolomics and network pharmacology

OBJECTIVES

This study was designed to evaluate the pharmacological activity and therapeutic mechanism of Xiaojin Pills (XJW) on lung cancer.

METHODS

Mice were orally administered with Xiaojin Pills for 21 days. Tumour samples were collected to evaluate the antilung cancer effect, and blood samples were collected to identify differential metabolites with metabolomics. Through the analysis of network pharmacology, the active ingredients and targets related to XJW therapy for lung cancer were filtered.

KEY FINDINGS

Different expression of seven metabolites related to seven pathways, including Arachidonic acid metabolism, Citrate cycle, tryptophan metabolism, glyoxylate and dicarboxylate metabolism, arginine and proline metabolism, primary bile acid biosynthesis and nicotinate and nicotinamide metabolism, were demonstrated to explain the efficacy of XJW in the treatment of lung cancer. Furthermore, a total of 19 active ingredients (ursolic acid, α-thujone, pelargonidin, succinic acid, boswellic acid, muscone, daidzein, xanthorrhizol, isoeugenol, oleic acid, β-caryophyllene, vanillin, β-sitosterol, lupeol, palmitic acid, eugenol, methylbutenol, β-elemene and quercetin) acted directly on 9 targets (CAT, PTGS2, PTGS1, CTH, ABTA, ALT1, ME2, AGXT and AGXT 2) and regulated 3 out of 7 metabolites (3-Hydroxyanthranilic acid, Pyruvate and Prostaglandin G2).

CONCLUSIONS

Through metabolomics and network pharmacology analyses, this study demonstrated that the major metabolites of XJW in treating lung cancer were regulated by multitarget and multicomponent interaction network.

A systems pharmacology approach based on oncogenic signalling pathways to determine the mechanisms of action of natural products in breast cancer from transcriptome data

BACKGROUND

Narrow spectrum of action through limited molecular targets and unforeseen drug-related toxicities have been the main reasons for drug failures at the phase I clinical trials in complex diseases. Most plant-derived compounds with medicinal values possess poly-pharmacologic properties with overall good tolerability, and, thus, are appropriate in the management of complex diseases, especially cancers. However, methodological limitations impede attempts to catalogue targeted processes and infer systemic mechanisms of action. While most of the current understanding of these compounds is based on reductive methods, it is increasingly becoming clear that holistic techniques, leveraging current improvements in omic data collection and bioinformatics methods, are better suited for elucidating their systemic effects. Thus, we developed and implemented an integrative systems biology pipeline to study these compounds and reveal their mechanism of actions on breast cancer cell lines.

METHODS

Transcriptome data from compound-treated breast cancer cell lines, representing triple negative (TN), luminal A (ER+) and HER2+ tumour types, were mapped on human protein interactome to construct targeted subnetworks. The subnetworks were analysed for enriched oncogenic signalling pathways. Pathway redundancy was reduced by constructing pathway-pathway interaction networks, and the sets of overlapping genes were subsequently used to infer pathway crosstalk. The resulting filtered pathways were mapped on oncogenesis processes to evaluate their anti-carcinogenic effectiveness, and thus putative mechanisms of action.

RESULTS

The signalling pathways regulated by Actein, Withaferin A, Indole-3-Carbinol and Compound Kushen, which are extensively researched compounds, were shown to be projected on a set of oncogenesis processes at the transcriptomic level in different breast cancer subtypes. The enrichment of well-known tumour driving genes indicate that these compounds indirectly dysregulate cancer driving pathways in the subnetworks.

CONCLUSION

The proposed framework infers the mechanisms of action of potential drug candidates from their enriched protein interaction subnetworks and oncogenic signalling pathways. It also provides a systematic approach for evaluating such compounds in polygenic complex diseases. In addition, the plant-based compounds used here show poly-pharmacologic mechanism of action by targeting subnetworks enriched with cancer driving genes. This network perspective supports the need for a systemic drug-target evaluation for lead compounds prior to efficacy experiments.

A metabolic data-driven systems pharmacology strategy for decoding and validating the mechanism of Compound Kushen Injection against HCC

ETHNOPHARMACOLOGICAL RELEVANCE

Compound Kushen Injection (CKI) is a widely used TCM formula for treatment of carcinomatous pain and tumors of digestive system including hepatocellular carcinoma (HCC). However, the potential mechanisms of CKI for treatment of HCC have not been systematically and deeply studied.

AIM OF STUDY

A metabolic data-driven systems pharmacology approach was utilized to investigate the potential mechanisms of CKI for treatment of HCC.

MATERIALS AND METHODS

Based on phenotypic data generated by metabolomics and genotypic data of drug targets, a propagation model based on Dijkstra program was proposed to decode the effective network of key genotype-phenotype of CKI in treating HCC. The pivotal pathway was predicted by target propagation mode of our proposed model, and was validated in SMMC-7721 cells and diethylnitrosamine-induced rats.

RESULTS

Metabolomics results indicated that 12 differential metabolites, and 5 metabolic pathways might be involved in the anti-HCC effect of CKI. A total of 86 metabolic related genes that affected by CKI were obtained. The results calculated by propagation model showed that 6475 shortest distance chains might be involved in the anti-HCC effect of CKI. According to the results of propagation mode, EGFR was identified as the core target of CKI for the anti-HCC effect. Finally, EGFR and its related pathway EGFR-STAT3 signaling pathway were validated in vivo and in vitro.

CONCLUSION

The proposed method provides a methodological reference for explaining the underlying mechanism of TCM in treating HCC.

Study of the Neurotransmitter Changes Adjusted by Circadian Rhythm in Depression Based on Liver Transcriptomics and Correlation Analysis

Depression has drawn increasing attention from the public around the world in recent years. Studies have shown that liver injury caused by chronic stress is relevant to depression and neurotransmitter changes. It is essential to clarify the relationship between neurotransmitter changes and hepatic gene expression in depression. In this study, we used the chronic unpredictable mild stress (CUMS) model combined with UHPLC-MS to explore the changes of neurotransmitters in serum and hippocampus and to decipher the differential gene expression in the liver by using the RNA-Seq combined with multivariate statistical analysis. Compared with the control group, the levels of neurotransmitters including 5-hydroxytryptamine (5-HT), acetylcholine, glutamate (Glu), and dopamine (DA) in the hippocampus and 5-HT, norepinephrine, γ-aminobutyric acid (GABA), and 5-hydroxyindoleacetic acid in serum were significantly changed in the CUMS rats. The results of liver transcriptomic analysis and correlation analysis showed that the Glu, DA, 5-HT, and GABA were impacted by 68 liver genes which were mainly enriched in three pathways including circadian rhythm, serotonergic synapse, and p53 signaling pathway. The expressive levels of clock genes and serotonergic synapse genes were validated by using q-PCR, and the diurnal rhythms of neurotransmitters were validated by in vivo hippocampus microdialysis. The CUMS stressors might cause phase advance of Glu and GABA by adjusting clock genes. The transcriptomic technique combined with correlation analysis and in vivo microdialysis could be used to discover comprehensive pathways of depression. It provides a new strategy for the rational assessment of the mechanism of disease.

Compound kushen injection relieves tumor-associated macrophage-mediated immunosuppression through TNFR1 and sensitizes hepatocellular carcinoma to sorafenib

Background

There is an urgent need for effective treatments for hepatocellular carcinoma (HCC). Immunotherapy is promising especially when combined with traditional therapies. This study aimed to investigate the immunomodulatory function of an approved Chinese medicine formula, compound kushen injection (CKI), and its anti-HCC efficiency in combination with low-dose sorafenib.

Methods

Growth of two murine HCC cells was evaluated in an orthotopic model, a subcutaneous model, two postsurgical recurrence model, and a tumor rechallenge model with CKI and low-dose sorafenib combination treatment. In vivo macrophage or CD8⁺ T cell depletion and in vitro primary cell coculture models were used to determine the regulation of CKI on macrophages and CD8⁺ T cells.

Results

CKI significantly enhanced the anticancer activity of sorafenib at a subclinical dose with no obvious side effects. CKI and sorafenib combination treatment prevented the postsurgical recurrence and rechallenged tumor growth. Further, we showed that CKI activated proinflammatory responses and relieved immunosuppression of tumor-associated macrophages in the HCC microenvironment by triggering tumor necrosis factor receptor superfamily member 1 (TNFR1)-mediated NF-κB and p38 MAPK signaling cascades. CKI-primed macrophages significantly promoted the proliferation and the cytotoxic ability of CD8⁺ T cells and decreased the exhaustion, which subsequently resulted in apoptosis of HCC cells.

Conclusions

CKI acts on macrophages and CD8⁺ T cells to reshape the immune microenvironment of HCC, which improves the therapeutic outcomes of low-dose sorafenib and avoids adverse chemotherapy effects. Our study shows that traditional Chinese medicines with immunomodulatory properties can potentiate chemotherapeutic drugs and provide a promising approach for HCC treatment.

Matrine: A review of its pharmacology, pharmacokinetics, toxicity, clinical application and preparation researches

ETHNOPHARMACOLOGICAL RELEVANCE

"Dogel ebs" was known as Sophora flavescens Ait., which has been widely utilized in the clinical practice of traditional Chinese Mongolian herbal medicine for thousands of years. Shen Nong's Materia Medica (Shen Nong Ben Cao Jing in Chinese pinyin) recorded that it is bitter in taste and cold in nature with the effect of clearing heat and eliminating dampness, insecticide, diuresis. Due to its extensive application in the fields of ethnopharmacological utilization, the pharmaceutical researches of Sophora flavescens Ait.s keeps deepening. Modern pharmacological studies have exhibited that matrine, which is rich in this traditional herbal medicine, mediates its main biological properties.

AIMS OF THE REVIEW

This review aimed at summarizing the latest and comprehensive information of matrine on the pharmacology, pharmacokinetics, toxicity, clinical application and preparation researches to explore the therapeutic potential of this natural ingredient. In addition, outlooks and perspective for possible future researches that related are also discussed.

MATERIALS AND METHODS

Related information concerning matrine was gathered from the internet database of Google scholar, Pubmed, ResearchGate, Web of Science and Wiley Online Library with the keywords including "matrine", "pharmacology", "toxicology" and "pharmacokinetics", "clinical application", etc. RESULTS: Based on literatures, matrine has a variety of pharmacological effects, including anti-cancer, anti-inflammatory, anti-microbial, detoxification and so on. Nevertheless, there are still some doubts about it due to the toxicity and questionable bioavailability that does exist.

CONCLUSIONS

Future researches directions probably include elucidate the mechanism of its toxicity and accurately tracing the in vivo behavior of its drug delivery system. Without doubt, integration of toxicity and efficiency and structure modification based on it are also pivotal methods to enhance pharmacological activity and bioavailability.

Comprehensive Analysis Strategy of Nervous-Endocrine-Immune-Related Metabolites to Evaluate Arachidonic Acid as a Novel Diagnostic Biomarker in Depression

Depression is one of the most complex multifactorial diseases affected by genetic and environmental factors. The molecular mechanism underlying depression remains largely unclear. To address this issue, a novel nervous-endocrine-immune (NEI) network module was used to find the metabolites and evaluate the diagnostic ability of patients with depression. During this process, metabolites were acquired from a professional depression metabolism database. Over-representation analysis was performed using IMPaLA. Then, the metabolite-metabolite interaction (MMI) network of the NEI system was used to select key metabolites. Finally, the receiver operating characteristic curve analysis was evaluated for the diagnostic ability of arachidonic acid. The results show that the numbers of the nervous system, endocrine system, and immune system pathways are 10, 19, and 12 and the numbers of metabolites are 38, 52, and 13, respectively. The selected shared metabolite-enriched pathways can be 97.56% of the NEI-related pathways. Arachidonic acid was extracted from the NEI system network by using an optimization formula and validated by in vivo experiments. It was indicated that the proposed model was good at screening arachidonic acid for the diagnosis of depression. This method provides reliable evidences and references for the diagnosis and mechanism research of other related diseases.

System Pharmacology-Based Strategy to Decode the Synergistic Mechanism of GanDouLing for Wilson's Disease

Results

Firstly, 324 active compounds have been identified in the GDL formula. Meanwhile, we identified 1496 human genes which are related to WD or liver cirrhosis. Functional and pathway enrichment analysis indicated that NOD-like receptor signaling pathway, bile secretion, calcium signaling pathway, steroid hormone biosynthesis, T cell receptor signaling pathway, apoptosis, MAPK signaling pathway, and so forth can be obviously regulated by GDL. Further, in a mouse model of WD, in vivo experiments showed that GDL treatment can not only reduce the pathological symptoms of the liver but also reduce the apoptosis of hepatocytes.

Conclusions

In this study, systemic pharmacological methods were proposed and the mechanism of GDL combined therapy for WD was explored. This method can be used as a reference for the study of other mechanisms of traditional Chinese medicine.

Exploring the Active Components of Simotang Oral Liquid and Their Potential Mechanism of Action on Gastrointestinal Disorders by Integrating Ultrahigh-Pressure Liquid Chromatography Coupled with Linear Ion Trap-Orbitrap Analysis and Network Pharmacology

Simotang oral liquid (SMT), a well-known traditional Chinese medicine formula composed of four medicinal and edible plants, has been extensively used for treating gastrointestinal disorders (GIDs) since ancient times. However, the major active constituents and the underlying molecular mechanism of SMT on GIDs are still partially understood. Herein, the preliminary chemical profile of SMT was first identified by ultrahigh-pressure liquid chromatography coupled with linear ion trap-Orbitrap tandem mass spectrometry (UHPLC-LTQ-Orbitrap). In total, 70 components were identified. Then, a network pharmacology approach integrating target prediction, pathway enrichment analysis, and network construction was adopted to explore the therapeutic mechanism of SMT. As a result, 170 main targets were screened out and considered as effective players in ameliorating GIDs. More importantly, the major hubs were found to be highly enriched in a calcium signaling pathway. Furthermore, 26 core SMT-related genes were identified, which may play key roles in ameliorating gastrointestinal motility. In conclusion, this work would provide valuable information for further development and clinical application of SMT.

Integrating Study on Qualitative and Quantitative Characterization of the Major Constituents in Shuanghuanglian Injection with UHPLC/Q-Orbitrap-MS and UPLC-PDA

As a clinically effective traditional Chinese medicine injection (TCMI), Shuanghuanglian injection (SHLI) is widely used in the treatment of upper respiratory tract infection and pneumonia. However, the shortage of quality analysis is a limitation that remains to be improved in the clinical application of SHLI. In this study, taking advantage of ultra-high-performance liquid chromatography tandem Q-Exactive Orbitrap high-resolution mass spectrometry (UHPLC/Q-Orbitrap-MS), 31 chemical components (eight organic acids, eleven flavonoids, five iridoid glycosides, four phenylethanoid glycosides, and three lignans) in SHLI were characterized, among which 22 components were unambiguously identified by reference compounds. The brief prediction results of network pharmacology indicated that the 22 targeted components may have anti-inflammatory, antibacterial, antiviral, and immunomodulatory activities. Using multiwavelength switching method, the 22 targeted components were quantified by ultra-performance liquid chromatography with photodiode array detector (UPLC-PDA) after the methodological validation. Based on the successfully established method, the total content of 22 components in 20 batches of SHLIs was efficiently determined with a slight variation between 10.25 and 11.28 mg/mL, which accounted for 38.7% in total solid of SHLI. This study performed a reliable chemical identification and provided a rapid and effective method for quality analysis, which contributed to the in-depth investigation and application of SHLI.

Anticancer activities of TCM and their active components against tumor metastasis

Traditional Chinese Medicine (TCM) has the characteristics of multiple targets, slight side effects and good therapeutic effects. Good anti-tumor effects are shown by Traditional Chinese Medicine prescription, Chinese patent medicine, single Traditional Chinese Medicine and Traditional Chinese medicine monomer compound. Clinically, TCM prolonged the survival time of patients and improved the life quality of patients, due to less side effects. Cancer metastasis is a complex process involving numerous steps, multiple genes and their products. During the process of tumor metastasis, firstly, cancer cell increases its proliferative capacity by reducing autophagy and apoptosis, and then the cancer cell capacity is stimulated by increasing the ability of tumors to absorb nutrients from the outside through angiogenesis. Both of the two steps can increase tumor migration and invasion. Finally, the purpose of tumor metastasis is achieved. By inhibiting autophagy and apoptosis of tumor cells, angiogenesis and EMT outside the tumor can inhibit the invasion and migration of cancer, and consequently achieve the purpose of inhibiting tumor metastasis. This review explores the research achievements of Traditional Chinese Medicine on breast cancer, lung cancer, hepatic carcinoma, colorectal cancer, gastric cancer and other cancer metastasis in the past five years, summarizes the development direction of TCM on cancer metastasis research in the past five years and makes a prospect for the future.

Systematic review and network meta-analysis comparing Chinese herbal injections with chemotherapy for treating patients with esophageal cancer

Objective

Methods

Results

Conclusions

Matrine Inhibitory Effect on Self-renewal and Re-sensitization of 5-FU Resistant NSCLC Stem Cells were through Let-7b dependent Downregulation of CCND1

Matrine is one of the major alkaloids extracted from Sophora flavescens Ait of the traditional Chinese medicine, was the main chemical ingredient of compounds of Kushen injection. The Matrine is considered as a promising therapeutic agent for curing nonsmall cell lung cancer (NSCLC), used either alone or combined with chemotherapeutic agents. In the present study, we focused on the possible roles of Matrine exerted on the self-renewal ability of stem-like cells of the NSCLC group, as well as the cytotoxicity of chemotherapeutic agents, in vitro and in vivo. Here we reported that Matrine inhibits cancer stem-like cell (CSC) properties through upregulation of Let-7b and suppression of the Wnt pathway. Overexpression of Let-7b suppressed the ability of tumorsphere formation, decreased Wnt pathway activation through inhibiting its transcriptional activity in lung CSCs. Further studies revealed that Let-7b directly targeted CCND1 and decreased its expression, whereas Matrine increased Let-7b levels and followed by inactivation of the CCND1/Wnt signaling pathway and inhibition of EMT, which was characterized by loss of epithelial markers and acquisition of a mesenchymal phenotype in lung CSCs. What is more, we found that Matrine increased Let-7b level in an endoribonuclease DICER1-dependent manner. And xenografts in nude mice evidenced that Matrine increased the sensitivity of lung CSCs to 5-FU and inhibited the accumulation of CCND1 in tumor tissues induced by 5-FU. Taken together, these data illustrate the role of Let-7b in regulating lung CSCs traits and DICER1/let-7/CCND1 axis in Matrine or in combination with 5-FU intervention of lung CSCs' expansion, helping to fulfill the anti-cancer action of Matrine.

Investigation of the Potential Mechanism Governing the Effect of the Shen Zhu San on COVID-19 by Network Pharmacology

BACKGROUND

Since December 2019, coronavirus disease 2019 (COVID-19) due to SARS-CoV-2 infection has emerged in Wuhan and rapidly spread throughout China and even to other countries. Combined therapy with modern medicine and traditional Chinese medicine has been proposed, in which Shen Zhu San (SZS) was regarded as one of the basic prescriptions.

METHODS

Network pharmacological approaches along with candidate compound screening, target prediction, target tissue location, protein-protein interaction network, gene ontology (GO), KEGG enrichment analyses, and gene microarray analyses were applied.

RESULTS

A total of 627 targets of the 116 active ingredients of SZS were identified. Targets in immune cells and tissues were much more abundant than those in other tissues. A total of 597 targets were enriched in the GO biological cellular process, while 153 signaling pathways were enriched according to the KEGG analysis. A total of 450 SARS-related targets were integrated and intersected with the targets of SZS to identify 40 common targets that were significantly enriched in five immune function aspects of the immune system process during GO analysis. Several inflammation-related pathways were found to be significantly enriched throughout the study.

CONCLUSIONS

The therapeutic mechanisms of the effects of SZS on COVID-19 potentially involve four effects: suppressing cytokine storms, protecting the pulmonary alveolar-capillary barrier, regulating the immune response, and mediating cell death and survival.

Scutellaria barbata and Hedyotis diffusa herb pair for breast cancer treatment: Potential mechanism based on network pharmacology

ETHNOPHARMACOLOGICAL RELEVANCE

The Scutellaria barbata and Hedyotis diffusa (SH) herb pair is extensively used in Traditional Chinese Medicine for efficacy enhancement in cancer treatment in China and Asian countries. Superior clinical efficacy observations based on high dosages (≥60 g) motivated us to explore appropriate dosages and the underlying mechanisms of action.

AIM OF THE STUDY

To explore the efficacy and potential mechanisms of actions of SH through in vitro and in vivo experiments and network pharmacology.

MATERIALS AND METHODS

SH lyophilized powder (SHLP) was prepared from decoctions and the active ingredients were identified using high performance liquid chromatography (HPLC). Proliferation and migration experiments in vitro and tumor growth in vivo were performed to evaluate the effects of SHLP on breast cancer. Corresponding potential target genes for SHLP components and breast cancer were extracted from established databases and the Protein-Protein Internetwork of shared genes were constructed using STRING database. Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotation clusters were acquired and the top 30 pathways were presented. At last, as one of pathways indicated by enriched results, apoptosis was validated with flow cytometric analysis and caspase-3, 8, 9 activities.

RESULTS

Seventy-five ingredients were identified from SHLP by HPLC. High SHLP doses inhibited proliferation and migration of three types of breast cancer cells in vitro and tumor growth in nude mice. After target genes extraction and intersection, the top 30 KEGG clusters were enriched, including PI3K-Akt, cell cycle and other related pathways like VEGF, Micro-RNAs and NF-κB, besides, key genes in apoptosis were mapped. In the last, apoptosis was validated by flow cytometric analysis and caspase-3, 8, 9 activities after SHLP treatment.

CONCLUSION

High SHLP dosages inhibited breast cancer in vitro and in vivo, enriched by network pharmacology and confirmed by flow cytometric analysis and caspase activation, with apoptosis was identified as one of the mechanisms of action of SHLP. SHLP administration with higher doses is recommended for clinical usage.

Orchestration of Intracellular Circuits by G Protein-Coupled Receptor 39 for Hepatitis B Virus Proliferation

Hepatitis B virus (HBV), a highly persistent pathogen causing hepatocellular carcinoma (HCC), takes full advantage of host machinery, presenting therapeutic targets. Here we aimed to identify novel druggable host cellular factors using the reporter HBV we have recently generated. In an RNAi screen of G protein-coupled receptors (GPCRs), GPCR39 (GPR39) appeared as the top hit to facilitate HBV proliferation. Lentiviral overexpression of active GPR39 proteins and an agonist enhanced HBV replication and transcriptional activities of viral promoters, inducing the expression of CCAAT/enhancer binding protein (CEBP)-β (CEBPB). Meanwhile, GPR39 was uncovered to activate the heat shock response, upregulating the expression of proviral heat shock proteins (HSPs). In addition, glioma-associated oncogene homologue signaling, a recently reported target of GPR39, was suggested to inhibit HBV replication and eventually suppress expression of CEBPB and HSPs. Thus, GPR39 provirally governed intracellular circuits simultaneously affecting the carcinopathogenetic gene functions. GPR39 and the regulated signaling networks would serve as antiviral targets, and strategies with selective inhibitors of GPR39 functions can develop host-targeted antiviral therapies preventing HCC.

The effect of compound kushen injection on cancer cells: Integrated identification of candidate molecular mechanisms

Traditional Chinese Medicine (TCM) preparations are often extracts of single or multiple herbs containing hundreds of compounds, and hence it has been difficult to study their mechanisms of action. Compound Kushen Injection (CKI) is a complex mixture of compounds extracted from two medicinal plants and has been used in Chinese hospitals to treat cancer for over twenty years. To demonstrate that a systematic analysis of molecular changes resulting from complex mixtures of bioactives from TCM can identify a core set of differentially expressed (DE) genes and a reproducible set of candidate pathways. We used in vitro cancer models to measure the effect of CKI on cell cycle phases and apoptosis, and correlated those phenotypes with CKI induced changes in gene expression. We treated two cancer cell lines with or without CKI and assessed the resulting phenotypes by employing cell viability and proliferation assays. Based on these results, we carried out high-throughput transcriptome data analysis to identify genes and candidate pathways perturbed by CKI. We integrated these differential gene expression results with previously reported results and carried out validation of selected differentially expressed genes. CKI induced cell-cycle arrest and apoptosis in the cancer cell lines tested. In these cells CKI also altered the expression of 363 core candidate genes associated with cell cycle, apoptosis, DNA replication/repair, and various cancer pathways. Of these, 7 are clinically relevant to cancer diagnosis or therapy, 14 are cell cycle regulators, and most of these 21 candidates are downregulated by CKI. Comparison of our core candidate genes to a database of plant medicinal compounds and their effects on gene expression identified one-to-one, one-to-many and many-to-many regulatory relationships between compounds in CKI and DE genes. By identifying genes and promising candidate pathways associated with CKI treatment based on our transcriptome-based analysis, we have shown that this approach is useful for the systematic analysis of molecular changes resulting from complex mixtures of bioactives.

Uncovering the Complexity Mechanism of Different Formulas Treatment for Rheumatoid Arthritis Based on a Novel Network Pharmacology Model

Traditional Chinese medicine (TCM) with the characteristics of “multi-component-multi-target-multi-pathway” has obvious advantages in the prevention and treatment of complex diseases, especially in the aspects of “treating the same disease with different treatments”. However, there are still some problems such as unclear substance basis and molecular mechanism of the effectiveness of formula. Network pharmacology is a new strategy based on system biology and poly-pharmacology, which could observe the intervention of drugs on disease networks at systematical and comprehensive level, and especially suitable for study of complex TCM systems. Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease, causing articular and extra articular dysfunctions among patients, it could lead to irreversible joint damage or disability if left untreated. TCM formulas, Danggui-Sini-decoction (DSD), Guizhi-Fuzi-decoction (GFD), and Huangqi-Guizhi-Wuwu-Decoction (HGWD), et al., have been found successful in controlling RA in clinical applications. Here, a network pharmacology-based approach was established. With this model, key gene network motif with significant (KNMS) of three formulas were predicted, and the molecular mechanism of different formula in the treatment of rheumatoid arthritis (RA) was inferred based on these KNMSs. The results show that the KNMSs predicted by the model kept a high consistency with the corresponding C-T network in coverage of RA pathogenic genes, coverage of functional pathways and cumulative contribution of key nodes, which confirmed the reliability and accuracy of our proposed KNMS prediction strategy. All validated KNMSs of each RA therapy-related formula were employed to decode the mechanisms of different formulas treat the same disease. Finally, the key components in KNMSs of each formula were evaluated by in vitro experiments. Our proposed KNMS prediction and validation strategy provides methodological reference for interpreting the optimization of core components group and inference of molecular mechanism of formula in the treatment of complex diseases in TCM.