Construction of a Prognostic Model of Multiple Myeloma Based on Metabolism-Related Genes / 中国实验血液学杂志

OBJECTIVE@#To screen the prognostic biomarkers of metabolic genes in patients with multiple myeloma (MM), and construct a prognostic model of metabolic genes.@*METHODS@#The histological database related to MM patients was searched. Data from MM patients and healthy controls with complete clinical information were selected for analysis.The second generation sequencing data and clinical information of bone marrow tissue of MM patients and healthy controls were collected from human protein atlas (HPA) and multiple myeloma research foundation (MMRF) databases. The gene set of metabolism-related pathways was extracted from Molecular Signatures Database (MSigDB) by Perl language. The biomarkers related to MM metabolism were screened by difference analysis, univariate Cox risk regression analysis and LASSO regression analysis, and the risk prognostic model and Nomogram were constructed. Risk curve and survival curve were used to verify the grouping effect of the model. Gene set enrichment analysis (GSEA) was used to study the difference of biological pathway enrichment between high risk group and low risk group. Multivariate Cox risk regression analysis was used to verify the independent prognostic ability of risk score.@*RESULTS@#A total of 8 mRNAs which were significantly related to the survival and prognosis of MM patients were obtained (P<0.01). As molecular markers, MM patients could be divided into high-risk group and low-risk group. Survival curve and risk curve showed that the overall survival time of patients in the low-risk group was significantly better than that in the high risk group (P<0.001). GSEA results showed that signal pathways related to basic metabolism, cell differentiation and cell cycle were significantly enriched in the high-risk group, while ribosome and N polysaccharide biosynthesis signaling pathway were more enriched in the low-risk group. Multivariate Cox regression analysis showed that the risk score composed of the eight metabolism-related genes could be used as an independent risk factor for the prognosis of MM patients, and receiver operating characteristic curve (ROC) showed that the molecular signatures of metabolism-related genes had the best predictive effect.@*CONCLUSION@#Metabolism-related pathways play an important role in the pathogenesis and prognosis of patients with MM. The clinical significance of the risk assessment model for patients with MM constructed based on eight metabolism-related core genes needs to be confirmed by further clinical studies.

Analysis of Unfavorable Prognosis Gene Markers in Patients with Acute Myeloid Leukemia by Multiomics / 中国实验血液学杂志

OBJECTIVE@#To analyze the molecular markers associated with occurrence, development and poor prognosis of acute myeloid leukemia (AML) by using the data of GEO and TCGA database, as well as multiomics analysis.@*METHODS@#The transcriptome data meeting requirements were down-loaded from GEO database, the differentially expressed genes were screened by using the R language limma package, and the GO function enrichment analysis and KEGG pathway analysis were performed for differentially expressed genes, at the same time, the protein interaction network was contracted by using STRING database and cytoscape software to screen out the hub gene, then the prognosis analysis was carried out for hub gene by combination with the clinical information affected in TCGA database.@*RESULTS@#620 differentially expressed genes were screened out, among which 162 differentially expressed genes were up-regulated, and 458 differentially expressed genes were down-regulated. Based on the results of GO functional enrichment, the KEGG pathway enrichment and protein interaction network, CXCL4, CXCR4, CXCR1, CXCR2, CCL5 and JUN were selected as hub genes. The survival analysis showed that the high expression of CXCL4, CXCR1, and CCL5 was a risk factor for poor prognosis of patiants.@*CONCLUSION@#CXCL4, CXCR1 and CCL5 can be used as biomarkers for the occurrence and development of AML, which relateds with the unfavorable prognosis and can provide a basis for further study.

Bioinformatics analysis of genes related to poor prognosis of human hepatocellular carcinoma and its clinical significance / 中国应用生理学杂志

OBJECTIVE@#To screen genes associated with poor prognosis of hepatocellular carcinoma (HCC) and to explore the clinical significance of these genes.@*METHODS@#The proper expression profile data of HCC was obtained from the Gene Expression Omnibus (GEO) database, and the differentially expressed genes (DEGs) were identified by differential expression analysis. The DAVID and String database were used for function enrichment analysis and to construct the protein-protein interaction (PPI) network respectively. The Cancer Genome Atlas (TCGA) database and the Cox Proportional Hazard Model were used for prognosis analysis of the DEGs.@*RESULTS@#A eligible human HCC data set (GSE84402) met the requirements. A total of 1141 differentially expressed genes were identified, including 720 up-regulated and 421 down-regulated genes. The results of function enrichment analysis and PPI network performed that CDK1、CDC6、CCNA2、CHEK1、CENPE 、PIK3R1、RACGAP1、BIRC5、KIF11 and CYP2B6 were prognosis key genes. And the prognosis analysis showed that the expressions of CDC6、PIK3R1、KIF11 and RACGAP1 were increased, and the expression of CENPE was decreased, which was closely related to prognosis of HCC.@*CONCLUSION@#CDC6、CENPE、PIK3R1、KIF11 and RACGAP1 may be closely related to poor prognosis of HCC, and can be used as molecular biomarkers for future research of HCC prognosis.

Prognosis-related miRNA bioinformatics screening of lung adenocarcinoma and its clinical significance / 中国应用生理学杂志

OBJECTIVE@#To investigate the prognosis-related miRNA histological features and clinical significance of lung adenocarcinoma.@*METHODS@#Using The Cancer Genome Atlas (TCGA) data, the miRNA expression profile data of human lung adenocarcinoma were searched for differential analysis, and the prognosis-related miRNAs were screened by Cox risk regression model. The targeted miRNAs were predicted by mirwalk analysis platform, KEGG functional enrichment analysis, and finally, predict the function of prognosis-related miRNAs.@*RESULTS@#A total of 46 differential miRNAs in lung adenocarcinoma were screened, including 19 up-regulated and 27 down-regulated. Six prognostic-related miRNAs were screened by Cox survival analysis, namely hsa-mir-21, hsa-mir-142, hsa-mir-200a high expression, hsa-mir-101, hsa-let-7c, hsa-mir-378e low expression, hsa-mir-21 and hsa-mir-378e were associated with poor prognosis in patients with lung adenocarcinoma, and the survival time was shortened significantly (<0.05, AUC=0.618). KEGG analysis showed that the above prognosis-related miRNA targeting regulatory genes were related with immune response pathways, miRNA and cancer pathways, metabolic pathways and so on.@*CONCLUSIONS@#Hsa-mir-21 and hsa-mir-378e are associated with poor prognosis of lung adenocarcinoma, and may be used as a molecular marker for prognosis of lung adenocarcinoma after further clinical verification.