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Discovering Gene Signature Shared by Prostate Cancer and Neurodegenerative Diseases Based on the Bioinformatics
Qiang Su1, Bin Dai2, Hanjian Zhang3
1Clinical Laboratory Medicine, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China.
Background:
Prostate cancer (PCa) is one of the highest frequent malignant tumors with very complicated pathogenesis. Genes of neurodegenerative diseases can influence tumor progression. But its role in the progression of PCa remains unclear. The purpose of the present academic work was to identify significant genes with poor outcome and their underlying mechanism.
Methods:
The GSE70768, GSE88808, and GSE134051 datasets were downloaded to screen the differentially expressed genes (DEGs). The DEG screening criteria were as follows: P < 0.05 and differential fold change |logFC| ≥ 1. The common DEGs (co-DEGs) of the three datasets were obtained by the Robust Rank Aggregation (RRA) method. Gene Ontology (GO) function annotation and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis were performed using R software. Protein-protein interaction (PPI) network analysis was performed for co-DEGs using STRING to screen critical genes. Differential expression and prognosis of key genes were analyzed by the online tool Gene Expression Profiling Interactive Analysis 2 (GEPIA2). The intersection gene between key genes and neurodegenerative genes was identified by constructing a Venn diagram.
Results:
A total of 263 co-DEGs were identified from the three datasets. GO analysis showed that co-DEGs were mainly involved in muscle contraction and blood circulation regulation. The top ten key genes were ACTG2, APOE, F5, CALD1, MYH11, MYL9, MYLK, TPM1, TPM2, and CALM1. GEPIA2 analysis showed that APOE, MYH11, and MYLK differ dramatically between tumor and normal tissues. These key genes are related to disease-free survival (DFS) in PCa. APOE was the intersection gene between key genes and Alzheimer-related genes.
Conclusion:
The neurodegenerative gene APOE may be a potential prognostic and diagnostic biomarker for PCa.
