Esophageal carcinoma (EC) is one of the most prevalent cancers in human populations worldwide. Baitouweng decoction is one of the most important Chinese medicine formulas, with the potential to treat cancer.

To investigate the role and mechanism of Baitouweng decoction on EC cells.

Differentially expressed genes (DEGs) in EC tissues and normal tissues were screened by the cDNA microarray technique and by bioinformatics methods. The target genes of microRNAs were predicted based on the TargetScan database and verified by dual luciferase gene reporter assay. We used Baitouweng decoction to intervene EC cells, and detected the activity of EC9706 and KYSE150 cells by the MTT method. Cell cycle and apoptosis were measured by flow cytometry. The expression of BUB1 mRNA and miR-495-3p was measured by qRT-PCR. The protein levels of BUB1, STAT3, p-STAT3, CCNB1, CDK1, Bax, Caspase3, and Caspase9 were measured by Western blot analysis. The migration and invasion abilities of the cells were measured by wound-healing assay and Transwell invasion assay, respectively.

DEGs identified are involved in biological processes, signaling pathways, and network construction, which are mainly related to mitosis. BUB1 was the key hub gene, and it is also a target gene of miR-495-3p. Baitouweng decoction could upregulate miR-495-3p and inhibit BUB1 expression. In vitro experiments showed that Baitouweng decoction significantly inhibited the migration and invasion of EC cells and induced apoptosis and G2/M phase arrest. After treatment with Baitouweng decoction, the expression of Bax, Caspase 3, and Caspase 9 in EC cells increased significantly, while the expression of BUB1, CCNB1, and CDK1 decreased significantly. Moreover, the STAT3 signaling pathway may play an important role in this process.

Baitouweng decoction has a significant inhibitory effect on EC cell growth. BUB1 is a potential therapeutic target for EC. Further analysis showed that Baitouweng decoction may inhibit the growth of EC cells by upregulating miR-495-3p targeting the BUB1-mediated STAT3 signal pathway.

Septic cardiomyopathy (SC) is a rare and harmful cardiovascular disease with decreased left ventricular (LV) output and multiple organ failure, which poses a serious threat to human life. Despite the advances in SC, its diagnostic basis and treatment methods are limited, and the specific diagnostic biomarkers and its candidate regulatory targets have not yet been fully established. In this study, the GSE79962 gene expression profile was retrieved, with 20 patients with SC and 11 healthy donors as control. Weighted gene coexpression network analysis (WGCNA) was employed to investigate gene modules that were strongly correlated with clinical phenotypes. Blue module was found to be most significantly related to SC. Moreover, Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on the coexpression genes in blue module and showed that it was associated with metabolic pathways, oxidative phosphorylation, and cardiac muscle contraction. Furthermore, a total of 10 hub genes NDUFB5, TIMMDC1, VDAC3, COQ10A, MRPL16 (mitochondrial ribosomal protein L16), C3orf43, TMEM182, DLAT, NDUFA8, and PDHB (pyruvate dehydrogenase E1 beta subunit) in the blue module were identified at transcriptional level and further validated at translational level in myocardium of an lipopolysaccharide-induced septic cardiac dysfunction mouse model. Overall, the results of quantitative real-time polymerase chain reaction were consistent with most of the microarray analysis results. Intriguingly, we observed that the highest change was NDUFB5, TIMMDC1, and VDAC3. These identified and validated genes provided references that would advance the understanding of molecular mechanisms of SC. Taken together, using WGCNA, the hub genes NDUFB5, TIMMDC1, and VDAC3 might serve as potential biomarkers for diagnosis and/or therapeutic targets for precise treatment of SC in the future.

Triple negative breast cancer (TNBC) is a specific subtype of breast cancer with a poor prognosis due to its aggressive biological behaviour and lack of therapeutic targets. We aimed to explore some novel genes and pathways related to TNBC prognosis through bioinformatics methods as well as potential initiation and progression mechanisms.

Breast cancer mRNA data were obtained from The Cancer Genome Atlas database (TCGA). Differential expression analysis of cancer and adjacent cancer, as well as, triple negative breast cancer and non-triple negative breast cancer were performed using R software. The key genes related to the pathogenesis were identified by functional and pathway enrichment analysis and protein-protein interaction network analysis. Based on univariate and multivariate Cox proportional hazards model analyses, a gene signature was established to predict overall survival. Receiver operating characteristic curve was used to evaluate the prognostic performance of our model.

Based on mRNA expression profiling of breast cancer patients from the TCGA database, 755 differentially expressed overlapping mRNAs were detected between TNBC/non-TNBC samples and normal tissue. We found eight hub genes associated with the cell cycle pathway highly expressed in TNBC. Additionally, a novel six-gene (TMEM252, PRB2, SMCO1, IVL, SMR3B and COL9A3) signature from the 755 differentially expressed mRNAs was constructed and significantly associated with prognosis as an independent prognostic signature. TNBC patients with high-risk scores based on the expression of the 6-mRNAs had significantly shorter survival times compared to patients with low-risk scores (P < 0.0001).

The eight hub genes we identified might be tightly correlated with TNBC pathogenesis. The 6-mRNA signature established might act as an independent biomarker with a potentially good performance in predicting overall survival.