Construction of Potential Gene Expression and Regulation Networks in Prostate Cancer Using Bioinformatics Tools.

Heyu Liu,Changhong Zhu,Wei Xia,Yuan Fan,Lirong Li,Yaping Lu,Xiangmin Lv

doi:10.1155/2021/8846951

Abstract

Objective To identify the key genes involved in prostate cancer and their regulatory network. Methods The dataset of mRNA/miRNA transcriptome sequencing was downloaded from The Cancer Genome Atlas/the Gene Expression Omnibus database for analysis. The “edgeR” package in the R environment was used to normalize and analyze differentially expressed genes (DEGs) and miRNAs (DEmiRNAs). First, the PANTHER online tool was used to analyze the function enrichment of DEGs. Next, a protein-protein interaction (PPI) network was constructed using STRING and Cytoscape tools. Finally, miRNA-gene regulatory networks were constructed using the miRTarBase. Results We identified 4339 important DEGs, of which 2145 were upregulated (Up-DEGs) and 2194 were downregulated (Down-DEGs). Functional enrichment analysis showed that the Up-DEGs were related to the immune system and the cell cycle in prostate cancer, whereas the Down-DEGs were related to the nucleic acid metabolic process and metabolism pathways. Twelve core protein clusters were found in the PPI network. Further, the constructed miRNA-gene interaction network showed that 11 downregulated miRNAs regulated 16 Up-DEGs and 22 upregulated miRNAs regulated 22 Down-DEGs. Conclusion We identified 4339 genes and 70 miRNAs that may be involved in immune response, cell cycle, and other key pathways of the prostate cancer regulatory network. Genes such as BUB1B, ANX1A1, F5, HTR4, and MUC4 can be used as biomarkers to assist in the diagnosis and prognosis of prostate cancer.

Highlights

Prostate cancer (PCa) is one of the most common malignant tumors in urology
To know how genes respond in prostate cancer, we collected RNA-Seq datasets from the The Cancer Genome Atlas (TCGA)-PRAD project, including 449 tumor samples and 52 normal samples, and performed transcriptome profiling
The MA plot gives a quick overview of the 2145 upregulated differentially expressed genes (DEGs) (Up-DEGs) and 2194 downregulated DEGs (Down-DEGs) (Figure 1(a))

Summary

Introduction

Prostate cancer (PCa) is one of the most common malignant tumors in urology. Its incidence has been increasing in recent years, and it has become the leading cause of cancer-related deaths among middle-aged men [1]. The treatment of PCa is limited by the low selectivity of medication and drug resistance encountered in all radiotherapy, chemotherapy, and immunotherapy. The reduction of multidrug resistance and identification of a clear molecular target would significantly improve the efficacy of therapeutic interventions for PCa. With the development and clinical application of molecule-targeted drugs, the molecule-targeted treatment of tumors has been widely accepted. There is an urgent need to find new indicators to indicate the use of correct drugs and improve patient survival and quality of life [3].

Methods

Results

Conclusion