Co-expression Network Analysis Identifies Fourteen Hub Genes Associated with Prognosis in Clear Cell Renal Cell Carcinoma

Weighted gene coexpression network analysis reveals ESR1, FLNA and Furin as hub genes for DEHP-induced prepubertal testicular injury

Di-(2-ethylhexyl) phthalate (DEHP) is an environmental endocrine disruptor that accumulates in organisms in various ways and induces male reproductive system disorders. In this study, we established a testicular injury model by gavage with different concentrations of DEHP. The testes were then collected for RNA sequencing (RNA-seq), and the results were analyzed by bioinformatics and verified by experiments. Our research results show that different concentrations of DEHP interfere with testicular development differently. Weighted gene coexpression network analysis (WGCNA) generated sixteen modules and identified the turquoise module as key. Then, estrogen receptor 1 (ESR1), filamin A (Flna) and Furin were identified as hub genes. qPCR and immunohistochemistry results revealed that all three hub genes were upregulated. We detected the locations of these genes by immunohistochemistry. ESR1 was mainly located in Leydig cells; Flna immunostaining is observed in the Leydig and some germ cells and Furin staining was seen in almost all types of testicular cells. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses showed enrichment mainly in MAPK signaling pathways, p53 signaling pathways, HIF-1 signaling pathways, protein processing in the endoplasmic reticulum, apoptosis, the cell cycle, RNA degradation, etc. This is the first study using WGCNA to investigate the mechanism of DEHP-induced injury in the prepubertal testis, providing new research angles to further understand the mechanism of DEHP-induced injury in the prepubertal testis.

A Novel mRNA-miRNA Regulatory Sub-Network Associated With Prognosis of Metastatic Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is a urinary disease with high incidence. The high incidence of metastasis is the leading cause of death in patients with ccRCC. This study was aimed to identify the gene signatures during the metastasis of ccRCC.

Methods

Two datasets, including one gene expression profile dataset and one microRNA (miRNA) expression profile dataset, were downloaded from Gene Expression Omnibus (GEO) database. The integrated bioinformatics analysis was performed using the (limma) R package, miRWalk, DAVID, STRING, Kaplan-Meier plotter databases. Quantitative real-time polymerase chain reaction (qPCR) was conducted to validate the expression of differentially expressed genes (DEGs) and DE-miRNAs.

Results

In total, 84 DEGs (68 up-regulated and 16 down-regulated) and 41 DE-miRNAs (24 up-regulated and 17 down-regulated) were screened from GSE22541 and GSE37989 datasets, respectively. Furthermore, 11 hub genes and 3 key miRNAs were identified from the PPI network, including FBLN1, THBS2, SCGB1A1, NKX2-1, COL11A1, DCN, LUM, COL1A1, COL6A3, SFTPC, SFTPB, miR-328, miR-502, and miR-504. The qPCR data showed that most of the selected genes and miRNAs were consistent with that in our integrated analysis. A novel mRNA-miRNA network, SFTPB-miR-328-miR-502-miR-504-NKX2-1 was found in metastatic ccRCC after the combination of data from expression, survival analysis, and experiment validation.

Conclusion

In conclusion, key candidate genes and miRNAs were identified and a novel mRNA-miRNA network was constructed in ccRCC metastasis using integrated bioinformatics analysis and qPCR validation, which might be utilized as diagnostic biomarkers and molecular targets of metastatic ccRCC.