Gastric cancer is one of the most common malignant cancers, with high death rates, poor prognosis and limited treatment methods. Cyclovirobuxine D (CVB-D) is the main active component of the traditional Chinese medicine Buxus microphylla. In the present study, we test the effects of CVB-D on gastric cancer cells and the underlying mechanisms of action. CVB-D reduced cell viability and colony formation ability of MGC-803 and MKN28 cells in a time- and concentration-dependent manner. Flow cytometry showed that cell cycle of CVB-D treated cells was arrested at the S-phase. CVB-D also induced apoptosis in MGC-803 and MKN28 cells, especially early stage apoptosis. Furthermore, mitochondria membrane potential (Δψm) was reduced and apoptosis-related proteins, cleaved Caspase-3 and Bax/Bcl-2, were up-regulated in CVB-D-treated MGC-803 and MKN28 cells. Taken together, our studies found that CVB-D plays important roles in inhibition of gastric tumorigenesis via arresting cell cycle and inducing mitochondria-mediated apoptosis, suggesting the potential application of CVB-D in gastric cancer therapy.

Background: Patients with triple‐negative breast cancer (TNBC) face a major challenge of the poor prognosis, and N6‐methyladenosine‐(m6A) mediated regulation in cancer has been proposed. Therefore, this study aimed to explore the prognostic roles of m6A‐related long non‐coding RNAs (LncRNAs) in TNBC.Methods: Clinical information and expression data of TNBC samples were collected from TCGA and GEO databases. Pearson correlation, univariate, and multivariate Cox regression analysis were employed to identify independent prognostic m6A‐related LncRNAs to construct the prognostic score (PS) risk model. Receiver operating characteristic (ROC) curve was used to evaluate the performance of PS risk model. A competing endogenous RNA (ceRNA) network was established for the functional analysis on targeted mRNAs.Results: We identified 10 independent prognostic m6A‐related LncRNAs (SAMD12‐AS1, BVES‐AS1, LINC00593, MIR205HG, LINC00571, ANKRD10‐IT1, CIRBP‐AS1, SUCLG2‐AS1, BLACAT1, and HOXB‐AS1) and established a PS risk model accordingly. Relevant results suggested that TNBC patients with lower PS had better overall survival status, and ROC curves proved that the PS model had better prognostic abilities with the AUC of 0.997 and 0.864 in TCGA and GSE76250 datasets, respectively. Recurrence and PS model status were defined as independent prognostic factors of TNBC. These ten LncRNAs were all differentially expressed in high‐risk TNBC compared with controls. The ceRNA network revealed the regulatory axes for nine key LncRNAs, and mRNAs in the network were identified to function in pathways of cell communication, signaling transduction and cancer.Conclusion: Our findings proposed a ten‐m6A‐related LncRNAs as potential biomarkers to predict the prognostic risk of TNBC.

Introduction: This study aimed to explore the effect of activated T cells on breast cancer (BC) cells and provide a theoretical basis for the interaction mechanism studies between BC and immune cells. Methods: The microarray dataset GSE73527 was downloaded from the Gene Expression Omnibus database. The common differentially expressed mRNAs (co-DEMs) and the common differentially expressed long non-coding RNAs (co-DElncRNAs) were identified between MDA-MB-231 cells and MCF7 activated human T cells, respectively. The RNA–miRNA–lncRNA (ceRNA) network was constructed. Furthermore, the Kyoto encyclopedia of genes and genomes pathway and the gene ontology function analyses were performed on co-DEMs. The protein–protein interaction networks and modules were investigated. Results: A total of 639 co-DEMs (such as interleukin-6 [IL6] and signal transducer and activator of transcription 1 [STAT1]) were detected in this study. Defense response to other organisms and herpes simplex infection were the most outstanding function and pathway assembled with co-DEMs, respectively. One protein–protein interaction network and three modules were further constructed. A total of 88 mRNA–miRNA–lncRNA relationships such as BTN3A1-has-mir-20b-5p-HCP5 were explored in the ceRNA network. Conclusion: Activated T cells may play a crucial role in the defense response to other organism functions and herpes simplex infection pathways by upregulating IL6 and STAT1, which further affected the progression of BC. The BTN3A1-has-miR-20b-5p-HCP5 relationship may be the potential interaction mechanism between BC and immune cells.

Paclitaxel is a microtubule-stabilizing drug that has therapeutic effect on breast cancer. However, the molecular mechanism of paclitaxel on breast cancer has not been elucidated. Microarray data o... 目的：紫杉醇是一种能够使微管稳定的药物, 对乳腺癌有治疗作用。然而, 紫杉醇对治疗乳腺癌的分子机制尚未阐明。材料与方法：从公共数据库下载的GSE114403芯片测定的基因数据, 包括50个治疗前和50个治疗后样本的信息。比较治疗前后基因表达的差异, 进行功能富集分析。然后构建蛋白质-蛋白质相互作用（PPI）网络和转录因子-miRNA-mRNA网络。最后进行关键基因的生存分析。结果：治疗前后共...

Background: Regulatory T cells (Tregs) play a pivotal role in the development, prognosis, and treatment of breast cancer. This study aimed to develop a Treg-associated gene signature that contributes to predict prognosis and therapy benefits in breast cancer. Methods: Treg-associated genes were screened based on single-cell RNA-sequencing (RNA-seq) in TISCH2 database and the bulk RNA-seq in The Cancer Genome Atlas (TCGA) database. Treg-associated gene signature was identified via survival analysis, univariate cox, least absolute shrinkage and selection operator (LASSO) and multivariable Cox regression analyses. Immune status was assessed using single-sample gene set enrichment analysis (ssGSEA) and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithms. Drug sensitivity was estimated using pRRophetic. Gene set enrichment analysis (GSEA) was conducted to explore the changed pathways. Results: A total of 169 genes were identified as Treg-associated genes, and close interactions existed among these genes. Kaplan-Meier (KM) survival and univariate cox revealed 29 prognostic genes (all P<0.05), and finally a six-gene prognostic signature including TBC1D4, PMAIP1, IFNG, LEF1, MZB1 and EZR was identified by LASSO and multivariable Cox. Based on this signature, patients in high-risk group exhibited a worse survival probability than those in low-risk group in the TCGA training dataset (P<0.001). Additionally, this signature showed a moderate predictive power for 1-, 3- and 5-year survival for breast cancer patients in both training dataset [area under the curve (AUC) =0.705, 0.678 and 0.668, respectively]. Similar predictive power for 1-, 3- and 5-year survival was also observed in validation datasets. Risk scores significantly differed between subgroups divided by clinicopathologic features, especially by molecular subtypes. Patients in high- and low-risk groups showed significant differences on infiltration abundance of multiple types of immune cells (such as, activated B cells/CD8+ T cells/CD4+ T cells), immune and stromal scores (all P<0.05). Moreover, sensitivity to 83 chemotherapeutic drugs such as lapatinib, methotrexate, and gefitinib were significantly differed between the two risk groups (all P<0.001). Conclusions: This is the first to develop a Treg-associated gene signature for breast cancer, which could predict prognosis of patients and help to identify patients who might be benefit from immunotherapy and/or chemotherapy.