Molecular insights into gastric cancer: The impact of TGFBR2 and hsa-mir-107 revealed by microarray sequencing and bioinformatics.

BACKGROUND: Gastric carcinoma (GC) remains a significant therapeutic challenge, garnering widespread attention. Oxymatrine (OMT), an active component of the traditional Chinese medicine compound Kushen injection (CKI), has shown promising results in combination with chemotherapy for the treatment of GC. However, the molecular mechanisms underlying OMT's therapeutic effects in GC have yet to be elucidated. METHODS: The transcriptomic expression data of HGC-27 post-OMT intervention were obtained through microarray sequencing, while the miRNA and mRNA sequencing data for GC patients were sourced from the TCGA database. The mechanism of OMT intervention in GC is analyzed in multiple aspects, including Protein-Protein Interactions (PPI), Competitive Endogenous RNA (ceRNA) networks, correlation and co-expression analyses, immune infiltration, and clinical implications. RESULTS: By analyzing key modules, five critical mRNAs were identified, and their interacting miRNAs were predicted to construct a ceRNA network. Among these, TGFBR2 and hsa-miR-107 have correlations or co-expression relationships with other genes in the network. They are differentially expressed in most other cancers, associated with prognosis, and have diagnostic value. TGFBR2 also exhibits immune infiltration phenomena, and its high expression is linked to poor patient prognosis. Low expression of hsa-miR-107 is associated with poor patient prognosis. OMT may act on the TGFß/Smad signaling pathway or negatively regulate the WNT signaling pathway through the hsa-miR-107/BTRC axis, thereby inhibiting the onset and progression of GC. CONCLUSION: The mechanisms of OMT intervention in GC are diverse, TGFBR2 and hsa-miR-107 may serve as prognostic molecular biomarkers or potential therapeutic targets.

Systematic review and meta-analysis on the efficacy and safety of Injectable Lentinan combined with chemotherapy in the treatment of gastric cancer.

BACKGROUND: This study employed a meta-analysis to evaluate the efficacy and safety of adjunctive treatment with injectable Lentinan (LNT) in combination with chemotherapy for gastric cancer (GC). METHODS: Computer-based searches of 6 databases were performed to identify randomized controlled trials (RCTs) relevant to the treatment of GC with LNT through mid-March 2023. Two independent researchers performed risk of bias assessment and trial sequential analysis(TSA), extracted the data and used Revman 5.3 software for data analysis. The certainty of evidence was graded based on the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach. RESULTS: A total of 31 RCTs with 2729 patients were included in the analysis. The results revealed that adjunctive therapy with LNT was associated with improved treatment efficacy (RR = 1.48, 95%CI: 1.36 ∼ 1.61, p < 0.00001), improvement in clusters of differentiation (CD3+, CD4+, and CD4+/CD8+), natural killer (NK) cells, and quality of life assessment (RR = 1.32, 95%CI: 1.20 ∼ 1.45, p < 0.00001) compared to using chemotherapy alone. In addition, there was a reduction in CD8+ levels, incidence of white blood cell decline, gastrointestinal reactions, and platelet decline. TSA results indicated that there was sufficient evidence to draw firm conclusions about these outcomes, and the GRADE scores showed 'high' or 'moderate' quality of evidence for these outcomes. CONCLUSION: The efficacy of treatment of GC with LNT in combination with chemotherapy was found to be better than chemotherapy alone. And no serious adverse effects were observed. However, further RCTs are needed to further validate the results of this study.

A new strategy to identify ADAM12 and PDGFRB as a novel prognostic biomarker for matrine regulates gastric cancer via high throughput chip mining and computational verification.

BACKGROUND: Gastric cancer is a life-threatening disease that poses a serious risk to human health. Although there are numerous molecular targets for gastric cancer in clinical practice, they often exhibit low specificity and sensitivity. Consequently, this can result in a low early diagnosis rate, delayed treatment, and poor prognosis for patients with gastric cancer. Hence, it remains crucial to identify more precise diagnostic markers for this disease. METHODS: This study utilized ceRNA chips and bioinformatics methods to investigate the key genes and mechanisms involved in matrine intervention in gastric cancer cells. RESULTS: ADAM12 and PDGFRB are the key genes that are down-regulated after matrine intervention in gastric cancer cells. By conducting bioinformatics analysis, two ceRNA regulatory axes were identified, which are associated with the prognosis of gastric cancer. These axes are lncRNA DGCR5/hsa-miR-206/ADAM12 and circRNA ITGA3/hsa-miR-24-3p/PDGFRB. CONCLUSION: The low expression of ADAM12 may weaken the digestion of extracellular matrix (ECM) molecules, which can result in the invasion and metastasis of tumor cells. This occurs without the catalysis of ECM proteases, thereby impacting the invasion and metastasis of gastric cancer cells. Additionally, the analysis of immune infiltration suggests that ADAM12 and PDGFRB may influence changes in the tumor immune microenvironment, thereby affecting the occurrence and development of gastric cancer. This study contributes to a deeper understanding of the role of the matrine-related ceRNA network in gastric cancer, providing a reference for clinical diagnosis and treatment. It holds significant importance in discovering new drug treatment targets.

Identification of a disulfidptosis-related genes signature for prognostic implication in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is the most prevalent subtype of non-small cell lung cancer. Additionally, disulfidptosis, a newly discovered type of cell death, has been found to be closely associated with the onset and progression of tumors. METHODS: The study first identified genes related to disulfidptosis through correlation analysis. These genes were then screened using univariate cox regression and LASSO regression, and a prognostic model was constructed through multivariate cox regression. A nomogram was also created to predict the prognosis of LUAD. The model was validated in three independent data sets: GSE72094, GSE31210, and GSE37745. Next, patients were grouped based on their median risk score, and differentially expressed genes between the two groups were analyzed. Enrichment analysis, immune infiltration analysis, and drug sensitivity evaluation were also conducted. RESULTS: In this study, we examined 21 genes related to disulfidptosis and developed a gene signature that was found to be associated with a poorer prognosis in LUAD. Our model was validated using three independent datasets and showed AUC values greater than 0.5 at 1, 3, and 5 years. Enrichment analysis revealed that the disulfidptosis-related genes signature had a multifaceted impact on LUAD, particularly in relation to tumor development, proliferation, and metastasis. Patients in the high-risk group exhibited higher tumor purity and lower stromal score, ESTIMATE score, and Immune score. CONCLUSION: This study constructed a gene signature related to disulfidptosis in lung adenocarcinoma and analyzed its impact on the disease and its association with the tumor microenvironment. The findings of this research provide valuable insights into the understanding of lung adenocarcinoma and could potentially lead to the development of new treatment strategies.

Single-cell RNA sequencing integrated with bulk RNA sequencing analysis reveals diagnostic and prognostic signatures and immunoinfiltration in gastric cancer.

BACKGROUND: Early diagnosis and prognostic predication of gastric cancer (GC) pose significant challenges in current clinical practice of GC treatments. Therefore, our aim was to explore relevant gene signatures that can predict the prognosis of GC patients. METHODS: Here, we established a single-cell transcriptional atlas of GC, focusing on the expression of T-cell-related genes for cell-cell communication analysis, trajectory analysis, and transcription factor regulatory network analysis. Additionally, we conducted validation and prediction of immune-related prognostic gene signatures in GC patients using TCGA and GEO data. Based on these prognostic gene signatures, we predicted the immune infiltration status of GC patients by grouping the patient samples into high or low-risk groups. RESULTS: Based on 10 tumor samples and corresponding normal samples from GC patients, we selected 18,416 cells for subsequent analysis using single-cell sequencing. From these, we identified 3,284 T-cells and obtained 641 differentially expressed genes related to T-cells from 5 different T-cell subtypes. By integrating bulk RNA sequencing data, we identified prognostic signatures associated with T-cells. Stratifying patients based on these prognostic signatures into high-risk or low-risk groups allowed us to effectively predict their survival rates and the immunoinfiltration status of the tumor microenvironment. CONCLUSION: This study explored prognostic gene signatures associated with T-cells in GC patients, providing insights into predicting patients' survival rates and immunoinfiltration levels.

Study on the mechanism of Shujin Tongluo granules in treating cervical spondylosis based on network pharmacology and molecular docking.

BACKGROUND: To investigate the potential active ingredients and possible mechanisms of Shujin Tongluo granules (SJTLG) in the treatment of cervical spondylosis (CS) by network pharmacology and molecular docking. METHODS: The active ingredients and potential targets of SJTLG were obtained through databases such as traditional Chinese medicine system (TCMSP) and BATMAN-traditional Chinese medicine (TCM), and the relevant human targets of CS were identified through databases such as OMIM, GeneCards, and DisGeNET. The intersection targets were imported into STRING for protein-protein interaction (PPI) analysis. The obtained data were imported into Cytoscape 3.9.0 software for visualization, and module analysis was performed using the MCODE plug-in. The representative targets were screened through the Metascape website for pathway enrichment analysis in Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Cytoscape software was used to build networks such as "drug-compound-target" and "drug-compound-target-pathway." Finally, the key targets were selected for molecular docking with the corresponding compounds by Autodock Tools 1.5.7 and visualized by PyMol. RESULTS: A total of 132 active compounds and 996 targets from SJTLG and 678 targets from CS were screened with 116 intersection targets. The key targets were AKT1, GAPDH, ALB, IL-6, TP53, TNF, VEGFA, IL-1ß, EGFR, HSP90AA1, ESR1, and JUN. The results of GO and KEGG enrichment analysis showed that the treatment of CS was mainly related to biological processes such as cellular response to nitrogen compound, cellular response to organonitrogen compound, and positive regulation of locomotion, and the targets were mainly focused on pathways in cancer, Kaposi sarcoma-associated herpesvirus infection, PI3K-Akt signaling pathway, lipid, and atherosclerosis. Molecular docking results showed that the minimum binding energy between the core targets and the corresponding compound was <-5.0 kcal·mol-1. CONCLUSION: This study preliminarily elucidates the potential active ingredients and mechanism of anti-inflammatory, analgesic, microcirculation improvement, vasodilation, osteoporosis inhibition and nerve nutrition effects of SJTLG in the treatment of CS and provides a reference for its clinical application.

Elucidating the pharmacological effects of Compound Kushen injection on MYC-P15-CCND1 signaling pathway in nasopharyngeal carcinoma - An in vitro study.

ETHNOPHARMACOLOGICAL RELEVANCE: Compound Kushen injection (CKI) is a representative medication of Chinese herbal injection and is often used in the adjuvant treatment of nasopharyngeal carcinoma (NPC), but its antitumor mechanism is poorly understood. AIM OF THE STUDY: To preliminarily elucidate the effects and possible mechanisms of CKI on NPC. METHODS: In this work, we explored the possible molecular mechanisms of CKI against NPC by using network pharmacology and molecular docking. In addition, proteomics was used to explore the localization and quantitative information of protein in NPC C666-1 cells after the intervention of CKI, and enrichment analysis was used to obtain the potential targets and pathways. Finally, the effect and the core targets of CKI in the intervention of NPC were explored in vitro experiments. RESULTS: Network pharmacology analysis identified three active components of CKI and 13 key targets. Molecular docking analysis showed that TNF, PTEN, CCND1, MAPK3, IL6, HIF1A, MYC had high affinity with corresponding components. Then the key pathway, cell cycle and the core targets MYC, CCND1, and P15 related to the key pathway were obtained. The results of in vitro experiments showed that CKI could inhibit the proliferation, migration, and invasion of NPC 5-8F cells and C666-1 cells, induce apoptosis of C666-1 cells, and arrest cell cycle G0/G1 phase. In addition, RT-qPCR and western blot showed that the expression of P15 was up-regulated and E2F4, E2F5, c-Myc, CCND1, and P107 was down-regulated in 5-8F cells and C666-1 cells intervened by CKI. CONCLUSION: The key pathway, cell cycle and the corresponding core targets MYC, CCND1, and P15 were obtained from network pharmacology, molecular docking, and proteomics. CKI could inhibit the proliferation, migration, and invasion of NPC cells, induce apoptosis of C666-1 cells. Especially CKI may arrest cell cycle G0/G1 phase through regulating targets MYC/P15/CCND1 of cell cycle pathway.