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.

Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels T cell-related prognostic risk model and tumor immune microenvironment modulation in triple-negative breast cancer.

BACKGROUND: Triple negative breast cancer (TNBC) is an aggressive and fatal malignancy. The current success of tumor immunotherapy has focused attention on intermediate T-cell subsets and the tumor microenvironment, which are essential for activation of the anti-tumor response. Therefore, both areas require further research to accelerate progress in developing tailored immunotherapeutic approaches for patients with TNBC. METHODS: We obtained scRNA-seq data of TNBC from the GEO database. A multiplex strategy was used to analyze and identify the T-cell heterogeneity of TNBC. By combining the METABRIC and GEO databases, a prognostic risk model for T-cell marker genes was constructed and validated. In addition, the immune-infiltrating cells of TNBC was analyzed using CIBERSORT, and the association between the risk model and response to immunotherapy was investigated. RESULTS: Based on scRNA-seq data, 25,932 cells were identified for multiple analyzes. T cells were studied with a focus on 2 subtypes, including CD8+ and CD4+. There were also communication relationships between T cells and multiple cell types. The results of the enrichment analysis showed that the T-cell marker genes were focused in pathways related to the immune system. In addition, OPTN, TMEM176A, PKM and HES1 deserve attention as prognostic markers in TNBC. The immune infiltration results showed that the high-risk group had significant immune cell infiltration and immunosuppression status. CONCLUSION: This study provides a resource for understanding T-cell heterogeneity and the associated prognostic risk model for TNBC. The results show that the model helps predict prognosis and response to treatment in breast cancer.

Data mining combines bioinformatics discover immunoinfiltration-related gene SERPINE1 as a biomarker for diagnosis and prognosis of stomach adenocarcinoma.

Stomach adenocarcinoma (STAD) is a type of cancer which often at itsadvanced stage apon diagnosis and mortality in clinical practice. Several factors influencethe prognosis of STAD, including the expression and regulation of immune cells in the tumor microenvironment. We here investigated the biomarkers related to the diagnosis and prognosis of gastric cancer, hoping to provide insights for the diagnosis and treatment of gastric cancer in the future. STAD and normal patient RNA sequencing data sets were accessed from the cancer genome atlas (TCGA database). Differential genes were determined and obtained by using the R package DESeq2. The stromal, immune, and ESTIMATE scores are calculated by the ESTIMATE algorithm, followed by the modular genes screening using the R package WGCNA. Subsequently, the intersection between the modular gene and the differential gene was taken and the STRING database was used for PPI network module analysis. The R packages clusterProfiler, enrichplot, and ggplot2 were used for GO and KEGG enrichment analysis. Cox regression analysis was used to screen survival-related genes, and finally, the R package Venn Diagram was used to take the intersection and obtain 7 hub genes. The time-dependent ROC curve and Kaplan-Meier survival curve were used to find the SERPINE1 gene, which plays a critical role in prognosis. Finally, the expression pattern, clinical characteristics, and regulatory mechanism of SERPINE1 were analyzed in STAD. We revealed that the expression of SERPINE1 was significantly increased in the samples from STAD compared with normal samples. Cox regression, time-dependent ROC, and Kaplan-Meier survival analyses demonstrated that SERPINE1 was significantly related to the adverse prognosis of STAD patients. The expression of SERPINE1 increased with the progression of T, N, and M classification of the tumor. In addition, the results of immune infiltration analysis indicated that the immune cells' expression were higher in high SERPINE1 expression group than that in low SERPINE1 expression group, including CD4+ T cells, B cells, CD8+ T cells, macrophages, neutrophils and other immune cells. SERPINE1 was closely related to immune cells in the STAD immune microenvironment and had a synergistic effect with the immune checkpoints PD1 and PD-L1. In conclusion, we proved that SERPINE1 is a promising prognostic and diagnostic biomarker for STAD and a potential target for immunotherapy.

T cell-related prognostic risk model and tumor immune environment modulation in lung adenocarcinoma based on single-cell and bulk RNA sequencing.

BACKGROUND: T cells are present in all stages of tumor formation and play an important role in the tumor microenvironment. We aimed to explore the expression profile of T cell marker genes, constructed a prognostic risk model based on these genes in Lung adenocarcinoma (LUAD), and investigated the link between this risk model and the immunotherapy response. METHODS: We obtained the single-cell sequencing data of LUAD from the literature, and screened out 6 tissue biopsy samples, including 32,108 cells from patients with non-small cell lung cancer, to identify T cell marker genes in LUAD. Combined with TCGA database, a prognostic risk model based on T-cell marker gene was constructed, and the data from GEO database was used for verification. We also investigated the association between this risk model and immunotherapy response. RESULTS: Based on scRNA-seq data 1839 T-cell marker genes were identified, after which a risk model consisting of 9 gene signatures for prognosis was constructed in combination with the TCGA dataset. This risk model divided patients into high-risk and low-risk groups based on overall survival. The multivariate analysis demonstrated that the risk model was an independent prognostic factor. Analysis of immune profiles showed that high-risk groups presented discriminative immune-cell infiltrations and immune-suppressive states. Risk scores of the model were closely correlated with Linoleic acid metabolism, intestinal immune network for IgA production and drug metabolism cytochrome P450. CONCLUSION: Our study proposed a novel prognostic risk model based on T cell marker genes for LUAD patients. The survival of LUAD patients as well as treatment outcomes may be accurately predicted by the prognostic risk model, and make the high-risk population present different immune cell infiltration and immunosuppression state.

Lactoferrin Alleviates Lipopolysaccharide-Induced Infantile Intestinal Immune Barrier Damage by Regulating an ELAVL1-Related Signaling Pathway.

As the most important intestinal mucosal barrier of the main body, the innate immune barrier in intestinal tract plays especially pivotal roles in the overall health conditions of infants and young children; therefore, how to strengthen the innate immune barrier is pivotal. A variety of bioactivities of lactoferrin (LF) has been widely proved, including alleviating enteritis and inhibiting colon cancer; however, the effects of LF on intestinal immune barrier in infants and young children are still unclear, and the specific mechanism on how LF inhibits infantile enteritis by regulating immune signaling pathways is unrevealed. In the present study, we firstly performed pharmacokinetic analyses of LF in mice intestinal tissues, stomach tissues and blood, through different administration methods, to confirm the metabolic method of LF in mammals. Then we constructed in Vitro and in Vivo infantile intestinal immune barrier damage models utilizing lipopolysaccharide (LPS), and evaluated the effects of LF in alleviating LPS-induced intestinal immune barrier damage. Next, the related immune molecular mechanism on how LF exerted protective effects was investigated, through RNA-seq analyses of the mouse primary intestinal epithelial cells, and the specific genes were analyzed and screened out. Finally, the genes and their related immune pathway were validated in mRNA and protein levels; the portions of special immune cells (CD4+ T cells and CD8+ T cells) were also detected to further support our experimental results. Pharmacokinetic analyses demonstrated that the integrity of LF could reach mice stomach and intestine after oral gavage within 12 h, and the proper administration of LF should be the oral route. LF was proven to down-regulate the expression levels of inflammatory cytokines in both the primary intestinal epithelial cells and mice blood, especially LF without iron (Apo-LF), indicating LF alleviated infantile intestinal immune barrier damage induced by LPS. And through RNA-seq analyses of the mouse primary intestinal epithelial cells treated with LPS and LF, embryonic lethal abnormal vision Drosophila 1 (ELAVL1) was selected as one of the key genes, then the ELAVL1/PI3K/NF-κB pathway regulated by LF was verified to participate in the protection of infantile intestinal immune barrier damage in our study. Additionally, the ratio of blood CD4+/CD8+ T cells was significantly higher in the LF-treated mice than in the control mice, indicating that LF distinctly reinforced the overall immunity of infantile mice, further validating the strengthening bioactivity of LF on infantile intestinal immune barrier. In summary, LF was proven to alleviate LPS-induced intestinal immune barrier damage in young mice through regulating ELAVL1-related immune signaling pathways, which would expand current knowledge of the functions of bioactive proteins in foods within different research layers, as well as benefit preclinical and clinical researches in a long run.

Investigation on the efficiency of Brucea javanica oil emulsion injection with chemotherapy for treating malignant pleural effusion: A meta-analysis of randomized controlled trials.

Introduction: Systematic evaluation of the clinical efficacy and safety of Brucea javanica oil emulsion injection (BJOEI) in combination with chemotherapy in the treatment of malignant pleural effusion (MPE). Methods: The study searched CNKI, Wanfang database, VIP database, SinoMed, PubMed, Embase, the Cochrane Library, and the Web of Science database and retrieved randomized controlled trials (RCTs) on the treatment of MPE with BJOEI in combination with chemotherapy from seven electronic databases from inception to 31 March 2022. Meta-analysis and sensitivity analysis were performed using Revman 5.4 and Stata 13.0 software. Results: Ultimately, 30 RCTs with 2035 patients were included, including 1002 cases in the control group and 1033 cases in the treatment group. The results of the meta-analysis showed that the overall efficacy rate of BJOEI combined with chemotherapy was higher in the treatment of MPE compared with chemotherapy alone (RR = 1.45, 95%CI: 1.36-1.54, p < 0.00001). And it could improve the Karnofsky (KPS) score (RR = 1.54, 95%CI: 1.41-1.68, p < 0.00001), reduce adverse reactions such as fever (RR = 0.82, 95%CI:0.60-1.12), chest pain (RR = 0.90, 95%CI: 0.67-1.21), gastrointestinal reactions (RR = 0.70, 95%CI: 0.57-0.87, p < 0.005), and leukopenia (RR = 0.51, 95%CI: 0.43-0.61, p < 0.00001). Conclusion: BJOEI combined with chemotherapy has better clinical efficacy than chemotherapy alone in the treatment of MPE. It can further improve KPS score, improve patients' quality of life, and reduce the occurrence of adverse reactions. However, the conclusions of this study need to be confirmed by further randomized, double-blind, controlled trials with large sample size, reasonable design, and strict implementation.

Single-Cell and Bulk RNA Sequencing Reveal Malignant Epithelial Cell Heterogeneity and Prognosis Signatures in Gastric Carcinoma.

Gastric carcinoma (GC) heterogeneity represents a major barrier to accurate diagnosis and treatment. Here, we established a comprehensive single-cell transcriptional atlas to identify the cellular heterogeneity in malignant epithelial cells of GC using single-cell RNA sequencing (scRNA-seq). A total of 49,994 cells from nine patients with paired primary tumor and normal tissues were analyzed by multiple strategies. This study focused on the malignant epithelial cells, which were divided into three subtypes, including pit mucous cells, chief cells, and gastric and intestinal cells. The trajectory analysis results suggest that the differentiation of the three subtypes could be from the pit mucous cells to the chief cells and then to the gastric and intestinal cells. Lauren's histopathology of GC might originate from various subtypes of malignant epithelial cells. The functional enrichment analysis results show that the three subtypes focused on different biological processes (BP) and pathways related to tumor development. In addition, we generated and validated the prognostic signatures for predicting the OS in GC patients by combining the scRNA-seq and bulk RNA sequencing (bulk RNA-seq) datasets. Overall, our study provides a resource for understanding the heterogeneity of GC that will contribute to accurate diagnosis and prognosis.