Background: MiR-182-5p, a cancer-related microRNA (miRNA), modulates tumorigenesis and patient outcomes in various human malignances. This study interroted the clinicopathological significance and molecular mechanisms of miR-182-5p in non-small cell lung cancer (NSCLC). Methods: The clinical significance of miR-182-5p in NSCLC subtypes was determined based on an analysis of 124 samples (lung adenocarcinomas [LUADs], n = 101; lung squamous cell carcinomas [LUSCs], n = 23) obtained from NSCLC patients and paired noncancer tissues and an analysis of data obtained from public miRNA-seq database, miRNA-chip database, and the scientific literature. The NSCLC samples (n = 124) were analyzed using the real-time quantitative polymerase chain reaction (RT-qPCR). Potential targets of miR-182-5p were identified using lists generated by miRWalk v.2.0, a comprehensive atlas of predicted and validated targets of miRNA-target interactions. Molecular events of miR-182-5p in NSCLC were unveiled based on a functional analysis of candidate targets. The association of miR-182-5p with one of the candidate target genes, homeobox A9 (HOXA9), was validated using inhouse RT-qPCR and dual-luciferase reporter assays. Results: The results of the in-house RT-qPCR assays analysis of data obtained from public miRNA-seq databases, miRNA-chip databases, and the scientific literature all supported upregulation of the expression level of miR-182-5p level in NSCLC. Moreover, the in-house RT-qPCR data supported the influence of upregulated miR-182-5p on malignant progression of NSCLC. In total, 774 prospective targets of miR-182-5p were identified. These targets were mainly clustered in pathways associated with biological processes, such as axonogenesis, axonal development, and Ras protein signal transduction, as well as pathways involved in axonal guidance, melanogenesis, and longevity regulation, in multiple species. Correlation analysis of the in-house RT-qPCR data and dual-luciferase reporter assays confirmed that HOXA9 was a direct target of miR-182-5p in NSCLC. Conclusions: The miR-182-5p expression level was upregulated in NSCLC tissues. MiR-182-5p may exert oncogenic influence on NSCLC through regulating target genes such as HOXA9.
Background Ovarian cancer (OV) is one of the most common malignant tumors of gynecology oncology. The lack of effective early diagnosis methods and treatment strategies result in a low five-year survival rate. Also, immunotherapy plays an important auxiliary role in the treatment of advanced OV patient, so it is of great significance to find out effective immune-related tumor markers for the diagnosis and treatment of OV. Methods Based on the consensus clustering analysis of single-sample gene set enrichment analysis (ssGSEA) score transformed via The Cancer Genome Atlas (TCGA) mRNA profile, we obtained two groups with high and low levels of immune infiltration. Multiple machine learning methods were conducted to explore prognostic genes associated with immune infiltration. Simultaneously, the correlation between the expression of mark genes and immune cells components was explored. Results A prognostic classifier including 5 genes (CXCL11, S1PR4, TNFRSF17, FPR1 and DHRS95) was established and its robust efficacy for predicting overall survival was validated via 1129 OV samples. Some significant variations of copy number on gene loci were found between two risk groups and it showed that patients with fine chemosensitivity has lower risk score than patient with poor chemosensitivity (P = 0.013). The high and low-risk groups showed significantly different distribution (P < 0.001) of five immune cells (Monocytes, Macrophages M1, Macrophages M2, T cells CD4 menory and T cells CD8). Conclusion The present study identified five prognostic genes associated with immune infiltration of OV, which may provide some potential clinical implications for OV treatment.
Cyclin B2 (CCNB2) belongs to type B cell cycle family protein, which is located on chromosome 15q22, and it binds to cyclin-dependent kinases (CDKs) to regulate their activities. In this study, 103 high-throughput datasets related to all subtypes of lung cancer (LC) and cerebral ischemic stroke (CIS) with the data of CCNB2 expression were collected. The analysis of standard mean deviation (SMD) and summary receiver operating characteristic (SROC) reflecting expression status demonstrated significant up-regulation of CCNB2 in LC and CIS (Lung adenocarcinoma: SMD = 1.40, 95%CI [0.98–1.83], SROC = 0.92, 95%CI [0.89–0.94]. Lung squamous cell carcinoma: SMD = 2.56, 95%CI [1.64–3.48]. SROC = 0.97, 95%CI [0.95–0.98]. Lung small cell carcinoma: SMD = 3.01, 95%CI [2.01–4.01]. SROC = 0.98, 95%CI [0.97–0.99]. CIS: SMD = 0.29, 95%CI [0.05–0.53], SROC = 0.68, 95%CI [0.63–0.71]). Simultaneously, protein-protein interaction (PPI) analysis indicated that CCNB2 is the hub molecule of crossed high-expressed genes in CIS and LC. Through Multiscale embedded gene co-expression network analysis (MEGENA), a gene module of CIS including 76 genes was obtained and function enrichment analysis of the CCNB2 module genes implied that CCNB2 may participate in the processes in the formation of CIS and tissue damage caused by CIS, such as “cell cycle,” “protein kinase activity,” and “glycosphingolipid biosynthesis.” Afterward, via single-cell RNA-seq analysis, CCNB2 was found up-regulated on GABAergic neurons in brain organoids as well as T cells expressing proliferative molecules in LUAD. Concurrently, the expression of CCNB2 distributed similarly to TOP2A as a module marker of cell proliferation in cell cluster. These findings can help in the field of the pathogenesis of LC-related CIS and neuron repair after CIS damage.
The funding was mainly used for data analysis and interpretation, and the costs incurred during the manuscript preparation Background:Wilms tumor, or nephroblastoma, is a malignant pediatric embryonal renal tumor that has a poor prognosis. This study aimed to use bioinformatics data, RNA-sequencing, connectivity mapping, molecular docking, and ligand-protein binding to identify potential targets for drug therapy in Wilms tumor. Material/Methods:Wilms tumor and non-tumor samples were obtained from high throughput gene expression databases, and differentially expressed genes (DEGs) were analyzed using the voom method in the limma package. The overlapping DEGs were obtained from the intersecting drug target genes using the Connectivity Map (CMap) database, and systemsDock was used for molecular docking. Gene databases were searched for gene expression profiles for complementary analysis, analysis of clinical significance, and prognosis analysis to refine the study. Results:From 177 cases of Wilms tumor, there were 648 upregulated genes and 342 down-regulated genes. Gene Ontology (GO) enrichment analysis showed that the identified DEGs that affected the cell cycle. After obtaining 21 candidate drugs, there were seven overlapping genes with 75 drug target genes and DEGs. Molecular docking results showed that relatively high scores were obtained when retinoic acid and the cyclin-dependent kinase inhibitor, alsterpaullone, were docked to the overlapping genes. There were significant standardized mean differences for three overlapping genes, CDK2, MAP4K4, and CRABP2. However, four upregulated overlapping genes, CDK2, MAP4K4, CRABP2, and SIRT1 had no prognostic significance. Conclusions:RNA-sequencing, connectivity mapping, and molecular docking to investigate ligand-protein binding identified retinoic acid and alsterpaullone as potential drug candidates for the treatment of Wilms tumor.
Objective The prevalence and mortality of cardiovascular diseases remain ranked first worldwide. Myocardial infarction (MI) is the central cause of death from cardiovascular diseases, seriously endangering human health. The clinical implication of toll-like receptor 2 (TLR2) remains contradictory, and its mechanism is still unknown. Hence, the objective of this study was to elucidate the clinical value and molecular mechanism of TLR2 in MI. Methods All high-throughput datasets and eligible literature were screened, and the expression levels of TLR2 were collected from the MI. The integrated expression level of TLR2 was displayed by calculating the standardized mean difference (SMD) and the area under the curve (AUC) of the summary receiver operating characteristic curve (sROC). The related TLR2 genes were sent for pathway analyses by gene ontology (GO), Kyoto encyclopedia of genes and genome (KEGG), and disease ontology (DO). Single-cell RNA-seq was applied to ascertain the molecular mechanism of TLR2 in MI. Results Nine microarrays and four reported data were available to calculate the comprehensive expression level of TLR2 in MI, including 325 cases of MI and 306 cases of controls. The SMD was 2.55 (95% CI = 1.35–3.75), and the AUC was 0.76 (95% CI = 0.72–0.79), indicating the upregulation of TLR2 in MI. The related TLR2 genes were primarily enriched in the pathways of atherosclerosis, arteriosclerotic cardiovascular disease, and arteriosclerosis, suggesting the clinical role of TLR2 in the progression of MI. Afterward, TLR2 was upregulated in myeloid cells in MI. Conclusions TLR2 may have a crucial role in progressing from coronary atherosclerosis to MI. The upregulation of TLR2 may have a favorable screening value for MI.
Pancreatic ductal adenocarcinoma (PDAC) is a malignant tumor with a specific tumor immune microenvironment (TIME). Therefore, investigating prognostic immune-related genes (IRGs) that are closely associated with TIME to predict PDAC clinical outcomes is necessary. In the present study, 459 samples of PDAC from the Genotype-Tissue Expression database, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) were included and a survival-associated module was identified using weighted gene co-expression network analysis. Based on the Cox regression analysis and least absolute shrinkage and selection operator analysis, four IRGs (2′-5′-oligoadenylate synthetase 1, MET proto-oncogene, receptor tyrosine kinase, interleukin 1 receptor type 2 and interleukin 20 receptor subunit β) were included in the prognostic model to calculate the risk score (RS), and patients with PDAC were divided into high- and low-RS groups. Kaplan-Meier survival and receiver operating characteristic curve analyses demonstrated that the low-RS group had significantly improved survival conditions compared with the high-RS group in TCGA training set. The prognostic function of the model was also validated using ICGC and GEO cohorts. To investigate the mechanism of different overall survival between the high- and low-RS groups, the present study included Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data and Cell Type Identification by Estimating Relative Subset of Known RNA Transcripts algorithms to investigate the state of the tumor microenvironment and immune infiltration inpatients in the cohort from TCGA. In summary, four genes associated with the TIME of PDAC were identified, which may provide a reference for clinical treatment.
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