Identification of potential novel differentially-expressed genes and their role in invasion and migration in renal cell carcinoma

SERPINE1 and its co-expressed genes are associated with the progression of clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma(ccRCC) is a frequently occurring malignant tumor of the urinary system. Despite extensive research, the regulatory mechanisms underlying the pathogenesis and progression of ccRCC remain largely unknown.

METHODS

We downloaded 5 ccRCC expression profiles from the Gene Expression Omnibus (GEO) database and obtained the list of differentially expressed genes (DEGs). Using String and Cytoscape tools, we determined the hub genes of ccRCC, and then analyzed their relationship with ccRCC patient survival. Ultimately, we identified SERPINE1 as a prognostic factor in ccRCC. Meanwhile, we confirmed the role of SERPINE1 in 786-O cells by cell transfection and in vitro experiments.

RESULTS

Our analysis yielded a total of 258 differentially expressed genes, comprising 105 down-regulated genes and 153 up-regulated genes. Survival analysis of SERPINE1 expression in The Cancer Genome Atlas (TCGA) confirmed its association with the increase of tumor grade, lymph node metastasis, and tumor stage, as well as with shorter survival. Furthermore, we found that SERPINE1 expression levels were associated with CD8 + T cells, CD4 + T cells, B cells, macrophages, neutrophils, and dendritic cells. Cell experiments showed that knockdown SERPINE1 expression could inhibit the proliferation, migration and invasion of ccRCC cells. Among the co-expressed genes with the highest correlation, ITGA5, SLC2A3, SLC2A14, SHC1, CEBPB, and ADA were overexpressed and associated with shorter overall survival (OS) in ccRCC.

CONCLUSIONS

In this study, we identified hub genes that are strongly related to ccRCC, and highlights the potential utility of overexpressed SERPINE1 and its co-expressed genes could be used as prognostic and diagnostic biomarkers in ccRCC.

The Choice of Candidates in Survival Markers Based on Coordinated Gene Expression in Renal Cancer

We aimed to identify and investigate genes that are essential for the development of clear cell renal cell carcinoma (ccRCC) and sought to shed light on the mechanisms of its progression and create prognostic markers for the disease. We used real-time PCR to study the expression of 20 genes that were preliminarily selected based on their differential expression in ccRCC, in 68 paired tumor/normal samples. Upon ccRCC progression, seven genes that showed an initial increase in expression showed decreased expression. The genes whose expression levels did not significantly change during progression were associated mainly with metabolic and inflammatory processes. The first group included CA9, NDUFA4L2, EGLN3, BHLHE41, VWF, IGFBP3, and ANGPTL4, whose expression levels were coordinately decreased during tumor progression. This expression coordination and gene function is related to the needs of tumor development at different stages. Specifically, the high correlation coefficient of EGLN3 and NDUFA4L2 expression may indicate the importance of the coordinated regulation of glycolysis and mitochondrial metabolism. A panel of CA9, EGLN3, BHLHE41, and VWF enabled the prediction of survival for more than 3.5 years in patients with ccRCC, with a probability close to 90%. Therefore, a coordinated change in the expression of a gene group during ccRCC progression was detected, and a new panel of markers for individual survival prognosis was identified.

Integrated Protein-Protein Interaction and Weighted Gene Co-expression Network Analysis Uncover Three Key Genes in Hepatoblastoma

Hepatoblastoma (HB) is the most common liver tumor in the pediatric population, with typically poor outcomes for advanced-stage or chemotherapy-refractory HB patients. The objective of this study was to identify genes involved in HB pathogenesis via microarray analysis and subsequent experimental validation. We identified 856 differentially expressed genes (DEGs) between HB and normal liver tissue based on two publicly available microarray datasets (GSE131329 and GSE75271) after data merging and batch effect correction. Protein–protein interaction (PPI) analysis and weighted gene co-expression network analysis (WGCNA) were conducted to explore HB-related critical modules and hub genes. Subsequently, Gene Ontology (GO) analysis was used to reveal critical biological functions in the initiation and progression of HB. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that genes involved in cell cycle phase transition and the PI3K/AKT signaling were associated with HB. The intersection of hub genes identified by both PPI and WGCNA analyses revealed five potential candidate genes. Based on receiver operating characteristic (ROC) curve analysis and reports in the literature, we selected CCNA2, CDK1, and CDC20 as key genes of interest to validate experimentally. CCNA2, CDK1, or CDC20 small interfering RNA (siRNA) knockdown inhibited aggressive biological properties of both HepG2 and HuH-6 cell lines in vitro. In conclusion, we identified CCNA2, CDK1, and CDC20 as new potential therapeutic biomarkers for HB, providing novel insights into important and viable targets in future HB treatment.

Overexpression of PKMYT1 Facilitates Tumor Development and Is Correlated with Poor Prognosis in Clear Cell Renal Cell Carcinoma

BACKGROUND Protein kinase membrane-associated tyrosine/threonine (PKMYT1) has been found in many tumors, but its association with clear cell renal cell carcinoma (ccRCC) remains unclear. MATERIAL AND METHODS PKMYT1 expression in ccRCC was examined in the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Tumor Immune Estimation Resource databases. The correlation between PKMYT1 expression and clinicopathological parameters was explored via the chi-square test. Receiver operating characteristic curves were used to estimate the diagnostic performance of PKMYT1. Kaplan-Meier curves, a Cox model, nomogram, time-dependent receiver operating characteristic curves, and decision curve analysis (DCA) were used to evaluate the prognostic value and clinical utility of PKMYT1. Genes coexpressed with PKMYT1 in ccRCC were identified based on TCGA, the gene expression profiling interactive, and cBioPortal. Gene Set Enrichment Analysis revealed biological pathways associated with PKMYT1 in ccRCC. RESULTS Weighted gene coexpression network analysis identified PKMYT1 as one of the genes most significantly correlated with progression of histological grade. PKMYT1 was significantly upregulated in ccRCC compared with normal tissue (P<0.001), with a trend toward differentiating between individuals with ccRCC and those who were healthy (area under the curve=0.942). High PKMYT1 expression was correlated with unsatisfactory survival (hazard ratio=1.67, P=0.001), indicating that it is a risk factor for ccRCC. A nomogram incorporating PKMYT1 level was created and showed a clinical net benefit. PKMYT1 was strongly positively correlated with the anti-silencing function of 1B histone chaperone (ASF1B) gene in ccRCC. CONCLUSIONS PKMYT1 is upregulated in ccRCC and its presence indicates poor prognosis, making it a potential therapeutic target for ccRCC.