Identification and Verification of Biomarker in Clear Cell Renal Cell Carcinoma via Bioinformatics and Neural Network Model

Abstract

Background. Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer, which represents the 9th most frequently diagnosed cancer. However, the molecular mechanism of occurrence and development of ccRCC is indistinct. Therefore, the research aims to identify the hub biomarkers of ccRCC using numerous bioinformatics tools and functional experiments. Methods. The public data was downloaded from the Gene Expression Omnibus (GEO) database, and the differently expressed genes (DEGs) between ccRCC and normal renal tissues were identified with GEO2R. Protein-protein interaction (PPI) network of the DEGs was constructed, and hub genes were screened with cytoHubba. Then, ten ccRCC tumor samples and ten normal kidney tissues were obtained to verify the expression of hub genes with the RT-qPCR. Finally, the neural network model was constructed to verify the relationship among the genes. Results. A total of 251 DEGs and ten hub genes were identified. AURKB, CCNA2, TPX2, and NCAPG were highly expressed in ccRCC compared with renal tissue. With the increasing expression of AURKB, CCNA2, TPX2, and NCAPG, the pathological stage of ccRCC increased gradually (P<0.05). Patients with high expression of AURKB, CCNA2, TPX2, and NCAPG have a poor overall survival. After the verification of RT-qPCR, the expression of hub genes was same as the public data. And there were strong correlations between the AURKB, CCNA2, TPX2, and NCAPG with the verification of the neural network model. Conclusion. After the identification and verification, AURKB, CCNA2, TPX2, and NCAPG might be related to the occurrence and malignant progression of ccRCC.

Translational changes induced by acute sleep deprivation uncovered by TRAP-Seq

“…Although the timing of sleep deprivation was different for the microarray experiments with sleep deprivation performed for five hours starting between ZT 4 and ZT 6, the microarray data set was verified, in part by Vescey and colleagues through qPCR following experiments in which sleep deprivation was performed from ZT 0 to ZT 5 [ 10 ]. We analyzed the microarray data set from GEO using the available GEO2R function as has been done in other recently published studies [ 51 , 52 ] to find differentially expressed genes and genes not affected by sleep deprivation. Surprisingly, we found only 49 genes that were differentially expressed after sleep deprivation in common between the two data sets (Fig.…”

A New Stemness‐Related Prognostic Model for Predicting the Prognosis in Pancreatic Ductal Adenocarcinoma

“…TPX2 encodes a microtubule-associated protein. The upregulation of TPX2 levels has been found to promote the proliferation and invasion of renal cancer cells [ 39 ]. ZWINT and CDK1, which correct erroneous centromere-microtubule attachment and regulate the mitotic spindle checkpoint, are mainly involved in cell cycle control in adrenocortical carcinoma [ 40 ].…”

Identification of UBE2I as a Novel Biomarker in ccRCC Based on a Large-Scale CRISPR-Cas9 Screening Database and Immunohistochemistry

“…NCAPG encodes a subunit of the clusterin complex, which is responsible for the stability of chromosomes during meiosis and mitosis ( Murphy and Sarge, 2008 ). A high level of NCAPG was significantly associated with unfavorable survival in various cancer types such as hepatocellular carcinoma, lung cancer, gastric cancer, ovarian cancer, breast cancer, cardia adenocarcinoma, and ccRCC ( Liu et al, 2020 ; Peng et al, 2020 ; Xu et al, 2020 ; Wu et al, 2021 ; Liu et al, 2018 ; Zhang et al, 2020 ; Sun et al, 2020 ). In hepatocellular carcinoma, knockdown of NCAPG expression could not only reduce the viability of hepatocellular carcinoma cells, but also arrest the cells at the S phase of the cell cycle by regulating the expression of N-cadherin, E-cadherin, cleaved caspase-3, CDK2 (cyclin dependent–kinase 2), Bcl-2 (BCL2 apoptosis regulator), Bax (BCL2-associated X, apoptosis regulator), CCNA1 (cyclin A1), and HOXB9 (Homeobox B9) ( Wang et al, 2019b ).…”