RESUMO
BACKGROUND: DNA-directed RNA polymerase (DDRP) related genes and long non-coding RNAs (lncRNAs) play an important role in the development of lung adenocarcinoma (LUAD), the leading cause of cancer-related death worldwide. Therefore, we aimed to construct a DDRP-associated lncRNA model to predict the prognosis of LUAD and to evaluate its sensitivity to immunotherapy and chemotherapy. METHODS: To construct a predictive signature, we used univariate and multivariate Cox regression analyses, as well as the least absolute shrinkage and selection operator regression analysis. The prognostic model was verified by applying the ROC curve analysis, Kaplan-Meier analysis, GO/KEGG analysis, and a predictive nomogram. Eventually, immunotherapy and drug susceptibility were examined and stemness indices were analyzed. RESULTS: 24 DDRP-associated lncRNAs were found as independent prognosis factors, which may be further developed as potential therapeutic vaccines for LUAD. The area under the ROC curve and the conformance index showed that the constructed model can predict the prognosis of LUAD patients. The predicted incidences of overall survival showed perfect conformance. And there were significant changes in immunological markers between the two risk subgroups in the model. Finally, an analysis of 50% maximum inhibitory concentration between the two risk subgroups showed that the high-risk subgroup was more sensitive to certain chemotherapy drugs. CONCLUSION: We constructed a model that accurately predicts the outcomes of LUAD based on 24 DDRP-related lncRNAs and provided promising treatment options for the future.
RESUMO
Hepatitis B virus (HBV) infection is a major cause of acute liver failure (ALF) in China, and mortality rates are high among patients who do not receive a matched liver transplant. This study aimed to determine potential mechanisms involved in HBV-ALF pathogenesis. Gene expression profiles under access numbers GSE38941 and GSE14668 were downloaded from the Gene Expression Omnibus database, including cohorts of HBV-ALF liver tissue and normal samples. Differentially expressed genes (DEGs) with false discovery rates (FDR) <0.05 and |log2(fold change)| >1 as thresholds were screened using the Limma package. Gene modules associated with stable disease were mined using weighed gene co-expression network analysis (WGCNA). A co-expression network was constructed and DEGs were analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. A gene-based network was constructed to explore major factors associated with disease progression. We identified 2238 overlapping DEGs as crucial gene cohorts in ALF development. Based on a WGCNA algorithm, 10 modules (modules 1-10) were obtained that ranged from 75 to 1078 genes per module. Cyclin-dependent kinase 1 (CDK1), cyclin B1 (CCNB1), and cell-division cycle protein 20 (CDC20) hub genes were screened using the co-expression network. Furthermore, 17 GO terms and 6 KEGG pathways were identified, such as cell division, immune response process, and antigen processing and presentation. Two overlapping signaling pathways that are crucial factors in HBV-ALF were screened using the Comprehensive Toxicogenomics Database (CTD). Several candidate genes including HLA-E, B2M, HLA-DPA1, and SYK were associated with HBV-ALF progression. Natural killer cell-mediated cytotoxicity and antigen presentation contributed to the progression of HBV-ALF. The HLA-E, B2M, HLA-DPA1, and SYK genes play critical roles in the pathogenesis and development of HBV-ALF.
