Human microRNA-4433 (hsa-miR-4443) Targets 18 Genes to be a Risk Factor of Neurodegenerative Diseases

BACKGROUND

Neurodegenerative diseases, such as Alzheimer's disease patients (AD), Huntington's disease (HD) and Parkinson's disease (PD), are common causes of morbidity, mortality, and cognitive impairment in older adults.

OBJECTIVE

We aimed to understand the transcriptome characteristics of the cortex of neurodegenerative diseases and to provide an insight into the target genes of differently expressed microRNAs in the occurrence and development of neurodegenerative diseases.

METHODS

The Limma package of R software was used to analyze GSE33000, GSE157239, GSE64977 and GSE72962 datasets to identify the differentially expressed genes (DEGs) and microRNAs in the cortex of neurodegenerative diseases. Bioinformatics methods, such as GO enrichment analysis, KEGG enrichment analysis and gene interaction network analysis, were used to explore the biological functions of DEGs. Weighted gene co-expression network analysis (WGCNA) was used to cluster DEGs into modules. RNA22, miRDB, miRNet 2.0 and TargetScan7 databases were performed to predict the target genes of microRNAs.

RESULTS

Among 310 Alzheimer's disease (AD) patients, 157 Huntington's disease (HD) patients and 157 non-demented control (Con) individuals, 214 co-DEGs were identified. Those co-DEGs were filtered into 2 different interaction network complexes, representing immune-related genes and synapserelated genes. The WGCNA results identified five modules: yellow, blue, green, turquoise, and brown. Most of the co-DEGs were clustered into the turquoise module and blue module, which respectively regulated synapse-related function and immune-related function. In addition, human microRNA-4433 (hsa-miR-4443), which targets 18 co-DEGs, was the only 1 co-up-regulated microRNA identified in the cortex of neurodegenerative diseases.

CONCLUSION

214 DEGs and 5 modules regulate the immune-related and synapse-related function of the cortex in neurodegenerative diseases. Hsa-miR-4443 targets 18 co-DEGs and may be a potential molecular mechanism in neurodegenerative diseases' occurrence and development.

Construction of a miRNA-Based Nomogram Model to Predict the Prognosis of Endometrial Cancer

Objective: To investigate the differential expression of microRNA (miRNA) in patients with endometrial cancer and its relationship with prognosis and survival. Method: We used The Cancer Genome Atlas (TCGA) database to analyze differentially expressed miRNAs in endometrial cancer tissues and adjacent normal tissues. In addition, we successfully screened out key microRNAs to build nomogram models for predicting prognosis and we performed survival analysis on the key miRNAs as well. Result: We identified 187 differentially expressed miRNAs, which includes 134 up-regulated miRNAs and 53 down-regulated miRNAs. Further univariate Cox regression analysis screened out 47 significantly differentially expressed miRNAs and selected 12 miRNAs from which the prognostic nomogram model for ECA patients by LASSO analysis was constructed. Survival analysis showed that high expression of hsa-mir-138-2, hsa-mir-548f-1, hsa-mir-934, hsa-mir-940, and hsa-mir-4758 as well as low-expression of hsa-mir-146a, hsa-mir-3170, hsa-mir-3614, hsa-mir-3616, and hsa-mir-4687 are associated with poor prognosis in EC patients. However, significant correlations between the expressions levels of has-mir-876 and hsa-mir-1269a and patients' prognosis are not found. Conclusion: Our study found that 12 significantly differentially expressed miRNAs might promote the proliferation, invasion, and metastasis of cancer cells by regulating the expression of upstream target genes, thereby affecting the prognosis of patients with endometrial cancer.

Novel MicroRNA Biomarkers, miR-142-5p, miR-550a, miR-1826, and miR-1201, Were Identified for Primary Melanoma

This study was aimed to identify novel miRNA biomarkers and explore the cooperative function of multi-RNAs in the progress of primary melanoma. The miRNA expression profile GSE62370 generated from 9 congenital nevi and 92 primary melanoma samples was downloaded from the Gene Expression Omnibus database. Differentially expressed miRNAs between primary melanoma and congenital nevi were compared and the target genes of them were selected. Pathway enrichment analysis and protein/protein interaction (PPI) network of miRNA target genes were performed. In addition, the differential expression of miRNAs to identify the tumor stage-dependent differences in miRNA expression was analyzed. Differentially expressed miRNAs, including 6 upregulated and 23 downregulated, were found in primary melanoma. Besides, the miRNA-associated gene regulatory network revealed 274 nodes, including miR-142-5p and miR-125b, and 307 miRNA-target pairs. miRNA-related Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, such as melanoma, was found. Target genes in the PPI module were mainly enriched in cancer-related pathways. Finally, the melanoma stage-related overexpressed miR-142-5p and the downregulated miR-550, miR-1826, miR-1201, miR-205, and miR-125b were identified. Some validated miRNAs, including miR-125a/b, let-7a/b, and miR-205, were found and illustrated the reliability of our study. Four novel miRNAs, including miR-142-5p, miR-550a, miR-1826, and miR-1201, were considered to have potential prognostic values for primary melanoma.

Preliminary identification of key miRNAs, signaling pathways, and genes associated with Hirschsprung's disease by analysis of tissue microRNA expression profiles

BACKGROUND

Hirschsprung's disease (HSCR) is a congenital gut motility disorder of infants, and if left untreated, it is fatal to the affected infants. This study aimed to identify key microRNAs (miRNAs), signaling pathways and genes involved in the pathogenesis of HSCR.

METHODS

The miRNA microarray dataset GSE77296 was downloaded. Nine colon tissue samples were available: six from HSCR patients and three matched control samples. Differentially expressed miRNAs (DEMs) were identified after data preprocessing. Target genes of the selected upregulated and downregulated DEMs were predicted. In addition, functional enrichment analyses for the selected DEMs and target genes were conducted. Finally, interaction networks between the DEMs and target genes were constructed.

RESULTS

A total of 162 DEMs (73 upregulated and 89 downregulated) were obtained. A total of 2511 DEM-target gene pairs for the 40 selected DEMs were identified, including 1645 pairs for the upregulated DEMs and 866 pairs for the downregulated DEMs. The upregulated DEM miR-141-3p and down-regulated DEM miR-30a-3p were identified as key miRNAs by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and network analyses. Besides, KEGG pathway enrichment analysis revealed that pathways in cancer and the mitogen-activated protein kinase (MAPK) signaling pathway were key pathways. The key genes frizzled class receptor 3 (FZD3) and docking protein 6 (DOK6) were obtained through the DEM-target gene interaction networks.

CONCLUSION

Two key miRNAs (miR-141-3p and miR-30a-3p), the MAPK signaling pathway and two key genes (FZD3 and DOK6) were implicated in the pathogenesis of HSCR.

Predicting associations between microRNAs and target genes in breast cancer by bioinformatics analyses

Breast cancer is the leading type of cancer among females. However, the association between microRNAs (miRNAs) and target genes in breast tumorigenesis is poorly studied. The original data set GSE26659 was downloaded from the Gene Expression Omnibus, and then the differentially expressed miRNAs among 77 breast cancer patients and 17 controls were identified using the Limma package in R software. Furthermore, breast cancer-related differentially expressed miRNAs were selected from a human miRNA disease database and their target genes were selected from five miRNA databases. Then, functional analysis was performed for the target genes followed by construction of a miRNA-target gene network. A total of 34 differentially expressed miRNAs were identified, including 13 breast cancer-related miRNAs. Moreover, the target genes of the 13 miRNAs were significantly enriched in regulation of transcription (P=7.43E-09) and pathways related to cancer (P=3.33E-11). Finally, eight upregulated miRNAs (including hsa-miR-425) and five downregulated miRNAs (including hsa-miR-143, hsa-miR-145 and hsa-miR-125b) were identified in the miRNA-target gene network. In conclusion, using bioinformatics approaches, we demonstrate that the changes in regulation of transcription and cancer pathways may play significant roles in the process of breast cancerogenesis. Differentially expressed miRNAs and their target genes may be new targets for breast cancer therapy.