Prognostic significance of TOP2A in non-small cell lung cancer revealed by bioinformatic analysis

Abstract

Background Lung cancer has been a common malignant tumor with a leading cause of morbidity and mortality, current molecular targets are woefully lacking comparing to the highly progressive cancer. The study is designed to identify new prognostic predictors and potential gene targets based on bioinformatic analysis of Gene Expression Omnibus (GEO) database. Methods Four cDNA expression profiles GSE19188, GSE101929, GSE18842 and GSE33532 were chosen from GEO database to analyze the differently expressed genes (DEGs) between non-small cell lung cancer (NSCLC) and normal lung tissues. After the DEGs functions were analyzed, the protein–protein interaction network (PPI) of DEGs were constructed, and the core gene in the network which has high connectivity degree with other genes was identified. We analyzed the association of the gene with the development of NSCLC as well as its prognosis. Lastly we explored the conceivable signaling mechanism of the gene regulation during the development of NSCLC. Results A total of 92 up regulated and 214 down regulated DEGs were shared in four cDNA expression profiles. Based on their PPI network, TOP2A was connected with most of other genes and was selected for further analysis. Kaplan–Meier overall survival analysis (OS) revealed that TOP2A was associated with worse NSCLC patients survival. And both GEPIA analysis and immunohistochemistry experiment (IHC) confirmed that TOP2A was aberrant gain of expression in cancer comparing to normal tissues. The clinical significance of TOP2A and probable signaling pathways it involved in were further explored, and a positive correlation between TOP2A and TPX2 expression was found in lung cancer tissues. Conclusion Using bioinformatic analysis, we revealed that TOP2A could be adopted as a prognostic indicator of NSCLC and it potentially regulate cancer development through co-work with TPX2. However, more detailed experiments are needed to clarify its drug target role in clinical medical use.

Systems Biology Integration and Screening of Reliable Prognostic Markers to Create Synergies in the Control of Lung Cancer Patients

“…In the present scenario, the integration of high-throughput omics technology and bioinformatics analysis continues to be a significant and effective research method in clinical research to discover target molecules associated with diseases. Moreover, it is considered to be a reliable technique for bioinformatics analysis of the integration of a huge quantity of omics data to discover targets that have potential application importance, for instance, researches on colorectal cancer (Luca et al, 2019), oral cancer (Di et al, 2019;Pan et al, 2019), ovarian cancer (Hu et al, 2019), osteosarcoma (Ma et al, 2019), and lung cancer (Feng et al, 2019). In the present study, the first step we did was to collect expression profiles of NSCLC mRNA from the GEO database and inspected them for genes that are commonly differentially expressed.…”

<p>TOP2A Promotes Cell Migration, Invasion and Epithelial–Mesenchymal Transition in Cervical Cancer via Activating the PI3K/AKT Signaling</p>

“…21,22 With the help of bioinformatic analysis and immunohistochemistry (IHC) technology, Ma at al. 23 revealed that TOP2A was overexpressed in non-small cell lung cancer (NSCLC) comparing to normal lung tissues, which associated with the worse overall survival in NSCLC patients. Song et al 24 demonstrated that TOP2A expression was dramatically increased following human cytomegalovirus (HCMV) infection in glioma cells, and miR-144-3p upregulation significantly reduced TOP2A expression to inhibit cell viability and invasion of HCMVpositive glioma cells.…”

Thymosin β4 Identified by Transcriptomic Analysis from HF Anagen to Telogen Promotes Proliferation of SHF-DPCs in Albas Cashmere Goat

“…Second, we analyzed DEGs from skin samples and cell samples of HF anagen and telogen stages, and then further analyzed the overlap of DEGs of the two sample groups. This screening strategy not only further narrowed the screening scope [38], but, more importantly, the genes of the overlap, which form the upstream gene set involved in the regulation of the growth and development of SHF, are theoretically involved in the whole process of the growth and development of skin. Third, the RNA-seq raw data of the skin we used for our analysis were obtained prior to the publication of the goat genome sequence, which was de novo assembled [39].…”