A New Stemness-Related Prognostic Model for Predicting the Prognosis in Pancreatic Ductal Adenocarcinoma.

OBJECTIVE: This study is aimed at identifying stemness-related genes in pancreatic ductal adenocarcinoma (PDAC). METHODS: The RNA-seq data of PADC patients were downloaded from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. The mRNA expression-based stemness index (mRNAsi) and epigenetically regulated mRNAsi (EREG-mRNAsi) of PADC patients were evaluated. The mRNAsi-related gene sets in PADC were identified by weighted gene coexpression network analysis (WGCNA). The key genes were further analyzed using functional enrichment analysis. The Kaplan-Meier survival analysis and the Cox proportional hazards model were used to evaluate the prognostic value of the key genes. Prognostic hub genes were used to establish nomograms. The receiver operating characteristic (ROC) curves, concordance index (C-index), and calibration curves were used to assess the discrimination and accuracy of the nomogram. Finally, these results were validated in the Gene Expression Omnibus (GEO) database. RESULTS: A total of 36 key genes related to mRNAsi were identified by WGCNA. A prognostic gene signature compromising seven genes (TPX2, ZWINT, UBE2C, CCNB2, CDK1, BUB1, and BIRC5) was established to predict the overall survival (OS) of PADC patients. The Cox regression analysis revealed that the risk score was an independent prognostic factor for PADC. Patients were then divided into the high-risk and low-risk groups. The ROC curves, C-index, and calibration curves indicated good performance of the prognostic signature in the TCGA and GEO datasets. Moreover, the nomogram incorporating clinical parameters showed better sensitivity and specificity for predicting the OS of PADC patients. CONCLUSION: The stemness-related prognostic model successfully predicted the OS of PADC patients and could be used for the treatment of PADC.

Mangiferin Inhibits Human Lung Adenocarcinoma by Suppressing MiR-27b and MiR-92a.

Lung adenocarcinoma (LUAD) is one of the most prevalent malignancies. However, its mechanism and therapeutic strategy remain to be clarified. Mangiferin is a flavonoid derived from the leaves of mango trees of the lacquer family that has many pharmacological and physiological effects. This research aimed to elucidate the biological effect of mangiferin in LUAD cell lines and clarify the in vitro mechanism of mangiferin. Mangiferin was shown to significantly restrain the proliferation of LUAD cells (A549, H1299, and H2030 cells) in a dose- and time-dependent manner. Furthermore, mangiferin was capable of stimulating apoptosis, and more cells were blocked in G1 and S phase in the mangiferin-treated cells than in those not treated with mangiferin. Microarrays and micro-RNA sequencing data suggested that there is a higher level of miR-27b and miR-92a in LUAD tissues than in non-LUAD tissues. Additional experiments indicated that mangiferin may be related to the downregulated levels of miR-92a and miR-27b. In conclusion, mangiferin likely regulates proliferation and apoptosis in LUAD cells by reducing the expression levels of miR-92a and miR-27b.

Identification of prognostic immune genes in laryngeal cancer.

OBJECTIVE: In this study, we aimed to identify prognostic immune-related genes and establish a prognostic model for laryngeal cancer based on these genes. METHODS: Transcriptome profiles and clinical data of patients with laryngeal cancer were downloaded from The Cancer Genome Atlas database. Integrated bioinformatics analyses were performed to identify genes associated with prognosis. RESULTS: Thirty prognostic immune-related genes for laryngeal cancer were identified. We constructed a regulatory network of prognosis comprising transcription factors and immune-related genes. Multivariate Cox regression analyses identified 15 immune-related genes in the network that were used to establish the prognostic model. The model exhibited excellent prognostic prediction ability with a high area under the curve value (0.916). The calculated risk score based on expression of the 15 immune-related genes was shown to be an independent prognostic factor for laryngeal cancer. CONCLUSION: We identified prognostic immune-related genes and established a prognostic model for laryngeal cancer, which might help identify novel predictive biomarkers and therapeutic targets of laryngeal cancer.

Identification of Potential Biomarkers and Biological Pathways in Juvenile Dermatomyositis Based on miRNA-mRNA Network.

OBJECTIVE: The aim of this study is to explore the potential pathogenesis of juvenile dermatomyositis by bioinformatics analysis of gene chips, which would screen the hub genes, identify potential biomarkers, and reveal the development mechanism of juvenile dermatomyositis. MATERIAL AND METHODS: We retrieved juvenile dermatomyositis's original expression microarray data of message RNAs (mRNAs) and microRNAs (miRNAs) from NCBI's Gene Expression Omnibus database (GEO, http://www.ncbi.nlm.nih.gov/geo/); through the R package of limma in Bioconductor, we can screen the differentially expressed miRNAs and mRNAs, and then we further analyzed the predicted target genes by the methods such as Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and miRNA-mRNA regulatory network construction and protein-protein interaction (PPI) network using Cytoscape 3.6.1. RESULTS: Compared with normal juvenile skin tissues, 6 upregulated microRNAs and 5 downregulated microRNAs were identified from 166 downregulated microRNAs and 58 upregulated microRNAs in juvenile dermatomyositis tissues. The enrichment pathways of differentially expressed microRNAs include cell adhesion molecules (CAMs), autoimmune thyroid disease, Type I diabetes mellitus, antigen and presentation, viral myocardium, graft-versus-host disease, and Kaposi sarcoma-associated herpes virus infection. By screening of microRNA-messenger RNA regulatory network and construction of PPI network map, three target miRNAs were identified, namely, miR-193b, miR-199b-5p, and miR-665. CONCLUSION: We identified mir-193b, mir-199b-5p, and mir-6653 target miRNAs by exploring the miRNA-mRNA regulation network mechanism related to the pathogenesis of juvenile dermatomyositis, which will be of great significance for further study on the pathogenesis and targeted therapy of juvenile dermatomyositis.

Pretreatment triglycerides-to-high density lipoprotein cholesterol ratio in postmenopausal women with endometrial cancer.

Raised triglycerides (TG) and reduced high density lipoprotein cholesterol (HDL-c) are components of metabolic syndrome. Both high TG and metabolic syndrome have been reported to be risk factors of endometrial cancer. Therefore, triglycerides-to-high density lipoprotein cholesterol ratio (TG/HDL-c ratio) may be a useful biological indicator in managing endometrial cancer. We aimed to explore the association between pretreatment TG/HDL-c ratio and endometrial cancer in postmenopausal women, and to evaluate its potential role in the disease. Pretreatment serum lipid profile and TG/HDL-c ratio were retrospectively analyzed for 167 postmenopausal women with endometrial cancer and 464 matched noncancer controls. Compared with controls, pretreatment TG/HDL-c ratio in endometrial cancer patients significantly elevated regardless of whether patients had diabetes or overweight/obesity (P < 0.05). Further analyses showed that pretreatment TG/HDL-c ratio increased significantly with advanced tumor stage. Interestingly, TG/HDL-c ratio of type I endometrial cancer patients was higher than those with type II endometrial cancer. A positive association was found between pretreatment TG/HDL-c ratio and tumor stage (adjusted r = 0.176, P = 0.027) in endometrial cancer group. Receiver operating characteristic curve analysis yielded the cut-off value of 1.52 for TG/HDL-c ratio to discriminate patients with cancer from controls (area under the curve, 0.689; sensitivity, 51.5%; specificity, 84.1%). Multivariate logistic regression model identified TG/HDL-c ratio ≥ 1.52 (odds ratio = 4.123; P < 0.001) as an independent predictor of endometrial cancer. TG/HDL-c ratio was positively associated with endometrial cancer clinical features, such as tumor stage and pathogenetic type. Accordingly, pretreatment TG/HDL-c ratio might be a potential marker for endometrial cancer.