Mechanism of Sijunzi Decoction in the treatment of colorectal cancer based on network pharmacology and experimental validation.

ETHNOPHARMACOLOGICAL RELEVANCE: Sijunzi Decoction（SJZD）, as a famous classical prescription for the treatment of colorectal cancer(CRC) in the traditional Chinese medicine (TCM), has achieved good curative effects in clinical practice. However, its specific ingredients and molecular mechanisms is still unclear. AIM OF THE STUDY: To analyze the effective ingredients and molecular mechanisms of SJZD in the treatment of CRC through network pharmacology technology and experimental validation. MATERIALS AND METHODS: First, the TCM Systems Pharmacology database and analysis platform database were searched to screen the effective chemical components of SJZD. Swiss Target Prediction was used to predict corresponding potential target genes of compounds. After that, we constructed a components and corresponding target network by Cytoscape. Simultaneously, 5 disease databases were used to search and filter CRC targets, and then we constructed a drug-disease target protein-protein interaction (PPI) network. Cytoscape 3.7 was used for visualization and cluster analysis, and Metascape database was used for GO and KEGG enrichment analysis. We drew the main pathway-target network diagram. Autodock vina1.5.6 was applied to molecular docking for the main compounds and target proteins. Subsequently, the potential mechanism of SJZD on colon cancer predicted by network pharmacological analysis was experimentally studied and verified in vivo and in vitro. RESULTS: 144 effective active chemical components, 897 potential targets, and 2584 CRC target genes were screened out. The number of common targets between the SJZD and CRC was 414.3250 GO biological process items and 186 KEGG signal pathways were obtained after analysis. The main compounds and the target protein had a good binding ability in molecular docking. The results of cell and animal experiments showed that SJZD could promote apoptosis and autophagy of CRC cells through PI3K/Akt/mTOR pathway. CONCLUSIONS: SJZD can treat CRC through multiple components, multiple targets and multiple pathways. We initially revealed the effective components and molecular mechanisms of SJZD in the treatment of CRC, and we used molecular docking and experiment for preliminary verification.

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.

Unveiling Potential Mechanisms of Spatholobi Caulis against Lung Metastasis of Malignant Tumor by Network Pharmacology and Molecular Docking.

Background: Lung metastasis of malignant tumor signifies worse prognosis and immensely deteriorates patients' life quality. Spatholobi Caulis (SC) has been reported to reduce lung metastasis, but the mechanism remains elusive. Methods: The active components and corresponding targets of SC were obtained from the Traditional Chinese Medicine Database and Analysis Platform (TCMSP) database and the SwissTargetPrediction database. The disease targets were acquired from DisGeNET and GeneCards databases. Venn map was composed to figure out intersection targets by using R. The PPI network was constructed through STRING and Cytoscape, and MCODE plug-in was used to sift hub targets. Gene Ontology (GO)-Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was carried out by utilizing clusterProfiler package (R3.6.1) with adjusted P value <0.05. Network of SC-active components-intersection targets-KEGG pathway was accomplished with Cytoscape. Molecular docking between hub targets and active components was performed, analyzed, and visualized by AutoDockTools, AutoDock Vina, PLIP Web tool, and PYMOL. Results: 24 active components and 123 corresponding targets were screened, and the number of disease targets and intersection targets was 1074 and 47, respectively. RELA, JUN, MAPK1, MAPK14, STAT3, IL-4, ESR1, and TP53 were the 8 hub targets. GO analysis and KEGG analysis elucidated that SC could ameliorate lung metastasis mainly by intervening oxidative stress, AGE-RAGE signaling pathway, and microRNAs in cancer. All 8 hub targets were proven to combine successfully with active components of SC. Conclusion: Inflammation is the core factor that integrates all these targets, biological process, and signaling pathways, which indicates that SC prevents or reduces lung metastasis mainly by dispelling inflammation.

Prognostic Role of TIGIT Expression in Patients with Solid Tumors: A Meta-Analysis.

BACKGROUND: T cell immunoglobulin and ITIM domain (TIGIT) is a recently identified immunosuppressive receptor. The expression levels of TIGIT affect the prognosis of patients with solid tumors. To fully comprehend the role of TIGIT on the prognosis of patients with solid tumors, we conducted a meta-analysis. METHODS: We performed an online search of PubMed, Embase, Web of Science (WOS), and MEDLINE databases for literature published till March 31, 2021. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the literature, and Stata 16.0 and Engauge Digitizer 4.1 software were used for data analysis. RESULTS: Our literature search identified eight papers comprising 1426 patients with solid tumors. Increased expression of TIGIT was associated with poor prognosis. High expression of TIGIT was a risk factor for overall survival (OS) {hazard ratio (HR) = 1.66, 95% confidence interval (CI) [1.26, 2.20], P < 0.001} and progression-free survival (PFS) (HR = 1.44, 95% CI [1.15, 1.81], P = 0.01). We performed subgroup analysis to explore the source of heterogeneity, colorectal cancer (HR = 2.07, 95% CI [0.23, 18.82], P = 0.518), lung cancer (HR = 1.29, 95% CI [0.96, 1.72], P = 0.094), esophageal cancer (HR = 1.70, 95% CI [1.20, 2.40], P = 0.003), and other cancers (HR = 1.83, 95% CI [1.25, 2.68], P = 0.002). In addition to cancer type, expression location, sample size, and different statistical analysis methods are also considered the possible causes of heterogeneity between studies. Funnel plots suggested no publication bias for OS (P = 0.902), and Egger's test supported this conclusion (P = 0.537). CONCLUSION: TIGIT expression was associated with OS and PFS in patients with solid tumors. Patients with elevated TIGIT expression have a shorter OS and PFS, and TIGIT expression could be a novel biomarker for prognosis prediction and a valuable therapeutic target for solid tumors.

Research progress on the treatment of advanced prostate cancer with Olaparib.

Prostate cancer (PCa) is one of the most common malignancies in men worldwide, and metastatic castrate-resistant prostate cancer (mCRPC) has shown a poor prognosis. Although chemotherapy and androgen deprivation therapy (ADT) have improved clinical outcomes, the median survival (MS) of patients with mCRPC is still less than 2 years. With the development of poly adenosine diphosphate-ribose polymerase inhibitor (PARPi), the treatment strategy for patients with mCRPC has markedly evolved. Olaparib, a type of PARPi that can selectively induce synthetic lethality in cancer cells with homologous recombination (HR) deficiencies, was the first type of PARPi approved for treating patients with mCRPC harboring mutations in HR repair (HRR) genes. This review discusses and summarizes the latest progress on therapeutic mechanisms, monotherapy, combination therapy, and adverse events of Olaparib.

Prognostic and immunological value of LTB4R in pan-cancer.

BACKGROUND: LTB4 receptor 1 (LTB4R), as the high affinity leukotriene B4 receptor, is rapidly revealing its function in malignancies. However, it is still uncertain. METHODS: We investigated the expression pattern and prognostic significance of LTB4R in pan-cancer across different databases, including ONCOMINE, PrognoScan, GEPIA, and Kaplan-Meier Plotter, in this study. Meanwhile, we explored the significance of LTB4R in tumor metastasis by HCMDB. Then functional enrichment analysis of related genes was performed using GeneMANIA and DAVID. Lastly, utilizing the TIMER datasets, we looked into the links between LTB4R expression and immune infiltration in malignancies. RESULTS: In general, tumor tissue displayed higher levels of LTB4R expression than normal tissue. Although LTB4R had a negative influence on pan-cancer, a high expression level of LTB4R was protective of LIHC (liver hepatocellular carcinoma) patients' survival. There was no significant difference in the distribution of LTB4R between non-metastatic and metastatic tumors. Based on Gene Set Enrichment Analysis, LTB4R was implicated in pathways involved in inflammation, immunity, metabolism, and cancer diseases. The correlation between immune cells and LTB4R was found to be distinct across cancer types. Furthermore, markers of infiltrating immune cells, such as Treg, T cell exhaustion and T helper cells, exhibited different LTB4R-related immune infiltration patterns. CONCLUSION: The LTB4R is associated with immune infiltrates and can be used as a prognostic biomarker in pan-cancer.

Integrated Analysis of lncRNA-Mediated ceRNA Network Reveals a Prognostic Signature for Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common types of malignancy and is associated with high mortality. Prior research suggests that long non-coding RNAs (lncRNAs) play a crucial role in the development of HCC. Therefore, it is necessary to identify lncRNA-associated therapeutic biomarkers to improve the accuracy of HCC prognosis. Transcriptomic data of HCC obtained from The Cancer Genome Atlas (TCGA) database were used in the present study. Differentially expressed RNAs (DERNAs), including 74 lncRNAs, 16 miRNAs, and 35 mRNAs, were identified using bioinformatics analysis. The DERNAs were subsequently used to reconstruct a competing endogenous RNA (ceRNA) network. A lncRNA signature was revealed using Cox regression analysis, including LINC00200, MIR137HG, LINC00462, AP002478.1, and HTR2A-AS1. Kaplan-Meier plot demonstrated that the lncRNA signature is highly accurate in discriminating high- and low-risk patients (P < 0.05). The area under curve (AUC) value exceeded 0.7 in both training and validation cohort, suggesting a high prognostic potential of the signature. Furthermore, multivariate Cox regression analysis indicated that both the TNM stage and the lncRNA signature could serve as independent prognostic factors for HCC (P < 0.05). Then, a nomogram comprising the TNM stage and the lncRNA signature was determined to raise the accuracy in predicting the survival of HCC patients. In the present study, we have introduced a ceRNA network that could contribute to provide a new insight into the identification of potential regulation mechanisms for the development of HCC. The five-lncRNA signature could serve as a reliable biosignature for HCC prognosis, while the nomogram possesses strong potential in clinical applications.

Potential Molecular Mechanisms of Chaihu-Shugan-San in Treatment of Breast Cancer Based on Network Pharmacology.

Breast cancer is one of the most common cancers endangering women's health all over the world. Traditional Chinese medicine is increasingly recognized as a possible complementary and alternative therapy for breast cancer. Chaihu-Shugan-San is a traditional Chinese medicine prescription, which is extensively used in clinical practice. Its therapeutic effect on breast cancer has attracted extensive attention, but its mechanism of action is still unclear. In this study, we explored the molecular mechanism of Chaihu-Shugan-San in the treatment of breast cancer by network pharmacology. The results showed that 157 active ingredients and 8074 potential drug targets were obtained in the TCMSP database according to the screening conditions. 2384 disease targets were collected in the TTD, OMIM, DrugBank, GeneCards disease database. We applied the Bisogenet plug-in in Cytoscape 3.7.1 to obtain 451 core targets. The biological process of gene ontology (GO) involves the mRNA catabolic process, RNA catabolic process, telomere organization, nucleobase-containing compound catabolic process, heterocycle catabolic process, and so on. In cellular component, cytosolic part, focal adhesion, cell-substrate adherens junction, and cell-substrate junction are highly correlated with breast cancer. In the molecular function category, most proteins were addressed to ubiquitin-like protein ligase binding, protein domain specific binding, and Nop56p-associated pre-rRNA complex. Besides, the results of the KEGG pathway analysis showed that the pathways mainly involved in apoptosis, cell cycle, transcriptional dysregulation, endocrine resistance, and viral infection. In conclusion, the treatment of breast cancer by Chaihu-Shugan-San is the result of multicomponent, multitarget, and multipathway interaction. This study provides a certain theoretical basis for the treatment of breast cancer by Chaihu-Shugan-San and has certain reference value for the development and application of new drugs.

Optimization of the Cellulase-Ultrasonic Synergistic Extraction Conditions of Polysaccharides from Lenzites betulina.

Lenzites betulina has been recognized as a rich source of chemical components, including polysaccharides, sterides and sugar alcohols. In this study, cellulase-ultrasonic synergistic extraction method was applied to extract polysaccharides from L. betulina, and the response surface methodology was used to optimize the extraction conditions. The eight basic factors affecting extraction yield were evaluated by Plackett-Burman design (PBD). Then, the four important factors significantly affecting the yield of polysaccharides from L. betulina, including enzymolysis temperature, enzymolysis time, ultrasound time and ultrasound temperature, were optimized by Box-Behnken design (BBD). Maximum extraction yield of L. betulina polysaccharides was 13.64±0.09 % at a cellulase dosage of 0.8 %, enzymolysis temperature of 60 °C, enzymolysis time of 180 min, pH of 4.5, liquid-solid ratio of 45 ml/g, ultrasound power of 300 W, ultrasound time of 20 min and ultrasound temperature of 45 °C. Subsequently, the characteristic structure of crude polysaccharides was determined by FT-IR. Results indicated that cellulase-ultrasonic synergistic treatment is suitable for L. betulina polysaccharides extraction, and it has good prospect for development and utilization.