Role of Hub Genes in the Occurrence and Development of Testicular Cancer Based on Bioinformatics

The role of Cyclin Dependent Kinase Inhibitor 3 (CDKN3) in promoting human tumors: Literature review and pan-cancer analysis

Background

Although many experiments and clinical studies have proved the link between the expression of CDKN3 and human tumors, we have not been able to identify any bioinformatics study in which the extensive tumor-promoting effect of CDKN3 was systematically analyzed.

Objective

Explore the extensive tumor-promoting effects of CDKN3 and review the research progress of CDKN3 in cancer.

Methods

We systematically reviewed the literature on CDKN3 and tumors. We explored the potential tumor-promoting effects of CDKN3 on different tumors in the TCGA database and the GTEx database using multiple platforms and websites. We studied the expression level of CDKN3, survival, prognosis, diagnosis, genetic variation, immune infiltration, and enrichment analysis using databases such as TIMER 2.0, GEPIA2, cBioPortal, and STRING.

Results

We found that CDKN3 is highly expressed in most tumors. The expression of CDKN3 is closely related to the prognosis of some tumors. And CDKN3 may have diagnostic value. The conclusion of our literature review is roughly the same, but there are differences, which are worthy of further study. Moreover, CDKN3 may be related to immune cell infiltration in tumor tissues. The genetic alteration of LUAD, STAD, SARC, PCPG, and ESCA with "Amplification" as the main type. In addition, through enrichment analysis, we found that CDKN3 affects tumors mainly through the control of the cell cycle and mitosis.

Conclusion

CDKN3 is highly expressed in most tumor tissues and has a statistical correlation with survival prognosis. It has extensive tumor-promoting effects that may be related to mechanisms such as immune infiltration.

A novel DNA methylation signature to improve survival prediction of progression-free survival for testicular germ cell tumors

This study aimed to develop a nomogram for predicting the progression-free survival (PFS) of testicular germ cell tumors (TGCT) patients based on DNA methylation signature and clinicopathological characteristics. The DNA methylation profiles, transcriptome data, and clinical information of TGCT patients were obtained from the Cancer Genome Atlas (TCGA) database. Univariate Cox, lasso Cox, and stepwise multivariate Cox regression were applied to identify a prognostic CpG sites-derived risk signature. Differential expression analysis, functional enrichment analysis, immunoinfiltration analysis, chemotherapy sensitivity analysis, and clinical feature correlation analysis were performed to elucidate the differences among risk groups. A prognostic nomogram integrating CpG sites-derived risk signature and clinicopathological features was further established and evaluated likewise. A risk score model based on 7 CpG sites was developed and found to exhibit significant differences among different survival, staging, radiotherapy, and chemotherapy subgroups. There were 1452 differentially expressed genes between the high- and low-risk groups, with 666 being higher expressed and 786 being lower expressed. Genes highly expressed were significantly enriched in immune-related biological processes and related to T-cell differentiation pathways; meanwhile, down-regulated genes were significantly enriched in extracellular matrix tissue organization-related biological processes and involved in multiple signaling pathways such as PI3K-AKT. As compared with the low-risk group, patients in the high-risk group had decreased lymphocyte infiltration (including T-cell and B-cell) and increased macrophage infiltration (M2 macrophages). They also showed decreased sensitivity to etoposide and bleomycin chemotherapy. Three clusters were obtained by consensus clustering analysis based on the 7 CpG sites and showed distinct prognostic features, and the risk scores in each cluster were significantly different. Multivariate Cox regression analysis found that the risk scores, age, chemotherapy, and staging were independent prognostic factors of PFS of TGCT, and the results were used to formulate a nomogram model that was validated to have a C-index of 0.812. Decision curve analysis showed that the nomogram model was superior to other strategies in the prediction of PFS of TGCT. In this study, we successfully established CpG sites-derived risk signature, which might serve as a useful tool in the prediction of PFS, immunoinfiltration, and chemotherapy sensitivity for TGCT patients.

Screening of the Key Genes for the Progression of Liver Cirrhosis to Hepatocellular Carcinoma Based on Bioinformatics

Hepatocellular carcinoma (HCC), which is among the most globally prevalent cancers, is strongly associated with liver cirrhosis. Using a bioinformatics approach, we have identified and investigated the hub genes responsible for the progression of cirrhosis into HCC. We analyzed the Gene Expression Omnibus (GEO) microarray datasets, GSE25097 and GSE17549, to identify differentially expressed genes (DEGs) in these two conditions and also performed protein-protein interaction (PPI) network analysis. STRING database and Cytoscape software were used to analyze the modules and locate hub genes following which the connections between hub genes and the transition from cirrhosis to HCC, progression of HCC, and prognosis of HCC were investigated. We used the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to detect the molecular mechanisms underlying the action of the primary hub genes. In all, 239 DEGs were obtained, with 94 of them showing evidence of upregulation and 145 showing evidence of downregulation in HCC tissues as compared to cirrhotic liver tissues. We identified six hub genes, namely, BUB1B, NUSAP1, TTK, HMMR, CCNA2, and KIF2C, which were upregulated and had a high diagnostic value for HCC. Besides, these six hub genes were positively related to immune cell infiltration. Since these genes may play a direct role in the progression of cirrhosis to HCC, they can be considered as potential novel molecular indicators for the onset and development of HCC.