Construction and validation of key genes-related prognosis model in children with acute myeloid leukaemia.

INTRODUCTION: To identify the differentially expressed genes of acute myeloid leukaemia (AML) and construct and verify a survival prognosis model combined with patient survival information. METHODS: The TARGET database was searched to identify differentially expressed peripheral blood genes in children with AML and healthy children. A gene set functional analysis and pathway analysis were performed using gene ontology and the KEGG pathway. A prognostic model for children with AML was constructed using univariate Cox, LASSO Cox regression and multivariate Cox regression analyses. Time-dependent receiver operating characteristic (ROC) curves were adopted to assess the predictive capacity of the prognostic models. RESULTS: In total, 1640 differentially expressed genes were screened (1119 upregulated and 521 downregulated genes). The differentially expressed genes were mainly involved in nutrient metabolism and cytochrome P450 metabolism. Six key genes related to the prognosis of AML, FAM157A, GPR78, IRX5, RP4-800G7.1, RP11-179H18.5 and RP11-61N20.3, were identified. Kaplan-Meier curves indicated that 3-year and 5-year overall survival was significantly higher in the low-risk group than in the high-risk group. The area under the ROC curve was 0.722. At different stages of AML, FAM157A and RP4-800G7.1 exhibited significant differences in expression. The expression levels of FAM157A were significantly decreased in AML, whereas the expression levels of GPR78, IRX5, RP4-800G7.1, RP11-179H18.5 and RP11-61N20.3 were significantly increased in AML. CONCLUSION: A prognosis-related gene model of AML was successfully constructed, and the expression levels of the model genes varied with AML stage.

Identification of a Novel Eight-Gene Risk Model for Predicting Survival in Glioblastoma: A Comprehensive Bioinformatic Analysis.

Glioblastoma (GBM) is one of the most progressive and prevalent cancers of the central nervous system. Identifying genetic markers is therefore crucial to predict prognosis and enhance treatment effectiveness in GBM. To this end, we obtained gene expression data of GBM from TCGA and GEO datasets and identified differentially expressed genes (DEGs), which were overlapped and used for survival analysis with univariate Cox regression. Next, the genes' biological significance and potential as immunotherapy candidates were examined using functional enrichment and immune infiltration analysis. Eight prognostic-related DEGs in GBM were identified, namely CRNDE, NRXN3, POPDC3, PTPRN, PTPRN2, SLC46A2, TIMP1, and TNFSF9. The derived risk model showed robustness in identifying patient subgroups with significantly poorer overall survival, as well as those with distinct GBM molecular subtypes and MGMT status. Furthermore, several correlations between the expression of the prognostic genes and immune infiltration cells were discovered. Overall, we propose a survival-derived risk score that can provide prognostic significance and guide therapeutic strategies for patients with GBM.

High-Throughput Sequencing Reveals That Rotundine Inhibits Colorectal Cancer by Regulating Prognosis-Related Genes.

BACKGROUND: Rotundine is an herbal medicine with anti-cancer effects. However, little is known about the anti-cancer effect of rotundine on colorectal cancer. Therefore, our study aimed to investigate the specific molecular mechanism of rotundine inhibition of colorectal cancer. METHODS: MTT and cell scratch assay were performed to investigate the effects of rotundine on the viability, migration, and invasion ability of SW480 cells. Changes in cell apoptosis were analyzed by flow cytometry. DEGs were detected by high-throughput sequencing after the action of rotundine on SW480 cells, and the DEGs were subjected to function enrichment analysis. Bioinformatics analyses were performed to screen out prognosis-related DEGs of COAD. Followed by enrichment analysis of prognosis-related DEGs. Furthermore, prognostic models were constructed, including ROC analysis, risk curve analysis, PCA and t-SNE, Nomo analysis, and Kaplan-Meier prognostic analysis. RESULTS: In this study, we showed that rotundine concentrations of 50 µM, 100 µM, 150 µM, and 200 µM inhibited the proliferation, migration, and invasion of SW480 cells in a time- and concentration-dependent manner. Rotundine does not induce SW480 cell apoptosis. Compared to the control group, high-throughput results showed that there were 385 DEGs in the SW480 group. And DEGs were associated with the Hippo signaling pathway. In addition, 16 of the DEGs were significantly associated with poorer prognosis in COAD, with MEF2B, CCDC187, PSD2, RGS16, PLXDC1, HELB, ASIC3, PLCH2, IGF2BP3, CLHC1, DNHD1, SACS, H1-4, ANKRD36, and ZNF117 being highly expressed in COAD and ARV1 being lowly expressed. Prognosis-related DEGs were mainly enriched in cancer-related pathways and biological functions, such as inositol phosphate metabolism, enterobactin transmembrane transporter activity, and enterobactin transport. Prognostic modeling also showed that these 16 DEGs could be used as predictors of overall survival prognosis in COAD patients. CONCLUSIONS: Rotundine inhibits the development and progression of colorectal cancer by regulating the expression of these prognosis-related genes. Our findings could further provide new directions for the treatment of colorectal cancer.

Identification of Potential Novel Prognosis-Related Genes Through Transcriptome Sequencing, Bioinformatics Analysis, and Clinical Validation in Acute Myeloid Leukemia.

Background: Acute Myeloid Leukemia (AML) is a complex and heterogeneous hematologic malignancy. However, the function of prognosis-related signature genes in AML remains unclear. Methods: In the current study, transcriptome sequencing was performed on 15 clinical samples, differentially expressed RNAs were identified using R software. The potential interactions network was constructed by using the common genes between target genes of differentially expressed miRNAs with transcriptome sequencing results. Functional and pathway enrichment analysis was performed to identify candidate gene-mediated aberrant signaling pathways. Hub genes were identified by the cytohubba plugin in Cytoscape software, which then expanded the potential interactions regulatory module for hub genes. TCGA-LAML clinical data were used for the prognostic analysis of the hub genes in the regulatory network, and GVSA analysis was used to identify the immune signature of prognosis-related hub genes. qRT-PCR was used to verify the expression of hub genes in independent clinical samples. Results: We obtained 1,610 differentially expressed lncRNAs, 233 differentially expressed miRNAs, and 2,217 differentially expressed mRNAs from transcriptome sequencing. The potential interactions network is constructed by 12 lncRNAs, 25 miRNAs, and 692 mRNAs. Subsequently, a sub-network including 15 miRNAs as well as 12 lncRNAs was created based on the expanded regulatory modules of 25 key genes. The prognostic analysis results show that CCL5 and lncRNA UCA1 was a significant impact on the prognosis of AML. Besides, we found three potential interactions networks such as lncRNA UCA1/hsa-miR-16-5p/COL4A5, lncRNA UCA1/hsa-miR-16-5p/SPARC, and lncRNA SNORA27/hsa-miR-17-5p/CCL5 may play an important role in AML. Furthermore, the evaluation of the immune infiltration shows that CCL5 is positively correlated with various immune signatures, and lncRNA UCA1 is negatively correlated with the immune signatures. Finally, the result of qRT-PCR showed that CCL5 is down-regulated and lncRNA UCA1 is up-regulated in AML samples separately. Conclusions: In conclusion, we propose that CCL5 and lncRNA UCA1 could be recognized biomarkers for predicting survival prognosis based on constructing competing endogenous RNAs in AML, which will provide us novel insight into developing novel prognostic, diagnostic, and therapeutic for AML.

Identification and characterization of prognosis-related genes in the tumor microenvironment of esophageal squamous cell carcinoma.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is the main pathological subtype of esophageal cancer with high incidence and mortality. Immune and stromal cells in the tumor microenvironment (TME) profoundly affect the development of ESCC. METHODS: In this study, we used the ESTIMATE algorithm to calculate the immune and stromal scores of ESCC samples in The Cancer Genome Atlas (TCGA) database. Next, we used the R package limma to identify differentially expressed genes (DEGs) from high- versus low-immune/stromal score groups and these DEGs were further utilized to analyze the functional annotations, protein-protein interaction (PPI) networks and overall survival of patients with ESCC. Finally, we identified the biological roles of core gene C3AR1 in the TME of ESCC using the TCGA database and in vitro experiments. RESULTS: We obtained the immune and stromal scores of ESCC samples and further evaluated the impact of these scores on the prognosis and clinical parameters of patients with ESCC. Next, we identified 410 DEGs from high- versus low-immune/stromal score groups and to gain better understanding of the biological functions and characteristics of DEGs. Among these DEGs, 69 were correlated with the overall survival of patients with ESCC and C3AR1 was identified as a core gene for the regulation of most genes in the network. We found that C3AR1 was positively correlated with M2 macrophages and immune inhibitory molecules (T-cell immunoglobulin and mucin domain 3 (TIM-3), programmed cell death-1 (PD-1)), but not with M1 macrophages. We also observed a higher expression of CD163 and CD206, which were the markers for M2 macrophages in the TLQP-21 TFA (the agonist of C3AR1)groups than in the control groups. CONCLUSION: Based on the ESTIMATE algorithm, we obtained and characterized prognosis-related genes in the TME of ESCC samples from the TCGA database. We have further revealed that C3AR1 may cause an immunosuppressive microenvironment by affecting the polarization of macrophages to M2 phenotype and lead to the progression of ESCC, which indicates that C3AR1 may be a potential target for immunotherapy.

Identification and Immunocorrelation of Prognosis-Related Genes Associated With Development of Muscle-Invasive Bladder Cancer.

Improved understanding of the molecular mechanisms and immunoregulation of muscle-invasive bladder cancer (MIBC) is essential to predict prognosis and develop new targets for therapies. In this study, we used the cancer genome atlas (TCGA) MIBC and GSE13507 datasets to explore the differential co-expression genes in MIBC comparing with adjacent non-carcinoma tissues. We firstly screened 106 signature genes by Weighted Gene Co-expression Network Analysis (WGCNA) and further identified 15 prognosis-related genes of MIBC using the univariate Cox progression analysis. Then we systematically analyzed the genetic alteration, molecular mechanism, and clinical relevance of these 15 genes. We found a different expression alteration of 15 genes in MIBC comparing with adjacent non-carcinoma tissues and normal tissues. Meanwhile, the biological functions and molecular mechanisms of them were also discrepant. Among these, we observed the ANLN was highly correlated with multiple cancer pathways, molecular function, and cell components, revealing ANLN may play a pivotal role in MIBC development. Next, we performed a consensus clustering of 15 prognosis-related genes; the results showed that the prognosis, immune infiltration status, stage, and grade of MIBC patients were significantly different in cluster1/2. We further identified eight-genes risk signatures using the least absolute shrinkage and selection operator (LASSO) regression analysis based on the expression values of 15 prognosis-related genes, and also found a significant difference in the prognosis, immune infiltration status, stage, grade, and age in high/low-risk cohort. Moreover, the expression of PD-1, PD-L1, and CTLA4 was significantly up-regulated in cluster1/high-risk-cohort than that in cluster2/low-risk-cohort. High normalized enrichment score of the Mitotic spindle, mTORC1, Complement, and Apical junction pathway suggested that they might be involved in the distinct tumor immune microenvironment (TIME) of cluster1/2 and high-/low-risk-cohort. Our study identified 15 prognosis-related genes of MIBC, provided a feasible stratification method to help for the future immunotherapy strategies of MIBC patients.