Identification of Genetic Alterations in Prostate Cancer Using Gene Expression Profiling

Abstract

Aim: In this study, an open-access dataset of mRNAs from primary prostate cancer samples and matched normal tissue samples was used to identify genetic alterations that play a role in the development of prostate cancer, the most common malignant tumor in men with increasing incidence. Material and Methods: The dataset used in the study consists of 10 primary prostate cancer samples and a sample of normal tissue. 20024 genes were sequenced from these tissues. Gene expression analysis was performed with the data set using the limma package in the R programming language. Enrichment analysis was performed with the clusterProfiler package. Results: 1028 of 20024 genes showed different up- or down-regulation in primary prostate cancer tissues compared to normal tissues. According to the results of the enrichment analysis with these genes, the processes that play a role in primary prostate cancer are protein binding, binding, cellular process, biological process, and response to stimulus. Conclusion: As a result, it can be said that the genetic structure of primary prostate cancer tissues changes compared to normal tissues, with the information obtained from gene expression analysis and enrichment analysis. It can be said that it is possible to increase the therapeutic effectiveness of the disease by analyzing the biomarkers with comprehensive and various methods.