基于生物信息学方法发现前列腺癌和神经退行性疾病的基因特征共享
Discovering Gene Signature Shared by Prostate Cancer and Neurodegenerative Diseases Based on the Bioinformatics Approach.
机构信息
Clinical Laboratory Medicine, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China.
Neurosurgery Department, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China.
出版信息
Comput Math Methods Med. 2022 Jun 28;2022:8430485. doi: 10.1155/2022/8430485. eCollection 2022.
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: < 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.
背景
前列腺癌（PCa）是发病率最高的恶性肿瘤之一，其发病机制非常复杂。神经退行性疾病的基因可以影响肿瘤的进展。但其在 PCa 进展中的作用尚不清楚。本研究旨在确定预后不良的显著基因及其潜在机制。
方法
下载 GSE70768、GSE88808 和 GSE134051 数据集，筛选差异表达基因（DEGs）。DEG 筛选标准为： < 0.05 和差异倍数变化 |logFC| ≥ 1。采用稳健秩聚合（RRA）方法获取三个数据集的共同 DEGs（co-DEGs）。使用 R 软件对 co-DEGs 进行基因本体论（GO）功能注释和京都基因与基因组百科全书（KEGG）通路分析。使用 STRING 对 co-DEGs 进行蛋白质-蛋白质相互作用（PPI）网络分析，筛选关键基因。通过在线工具基因表达谱交互式分析 2（GEPIA2）分析关键基因的差异表达和预后。通过构建 Venn 图鉴定关键基因和神经退行性疾病基因的交集基因。
结果
从三个数据集中共鉴定出 263 个 co-DEGs。GO 分析表明，co-DEGs 主要参与肌肉收缩和血液循环调节。前 10 个关键基因分别为 ACTG2、APOE、F5、CALD1、MYH11、MYL9、MYLK、TPM1、TPM2 和 CALM1。GEPIA2 分析表明，APOE、MYH11 和 MYLK 在肿瘤组织和正常组织之间存在显著差异。这些关键基因与 PCa 的无病生存期（DFS）相关。APOE 是关键基因和阿尔茨海默病相关基因的交集基因。
结论
神经退行性疾病基因 APOE 可能是 PCa 潜在的预后和诊断生物标志物。
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