基于生物信息学筛选影响前列腺癌预后的脂代谢基因

摘要/Abstract

摘要： 目的通过生物信息学筛选影响前列腺癌预后显著的脂质代谢基因。方法从TCGA数据库下载前列腺癌的临床资料及mRNA测序数据;利用R语言筛选正常组与前列腺癌组的差异基因,利用KEGG数据库检索脂质代谢基因,并筛选出差异表达的脂质代谢基因。结合患者的生存状态、生存时间与筛选的差异代谢基因的表达量,利用uniCOX函数筛选与前列腺癌预后密切相关的脂代谢基因。根据上述基因表达量的中位数,把患者分为高低风险组行生存分析。利用GSEA软件对关键基因进行富集分析。结果共筛选出1973个差异基因,其中包括83个差异的脂质代谢基因,使用uniCOX分析预后,共发现5个促癌脂质代谢基因,包括：CPT1B,AKR1C4,AKR1C2,UGT1A10,CYP4F3。对这5个基因进行生存分析,发现肉毒碱棕榈酰基转移酶1B(CPT1B)与前列腺癌的生存显著相关。通过富集分析发现,CPT1B与亚油酸、α亚麻酸代谢呈显著正相关,与WNT信号通路呈显著负相关。结论 CPT1B 高表达与前列腺癌的预后不良显著相关。

关键词: 前列腺癌, 生物信息学, 风险基因, 预后, 脂质代谢

Abstract: Objective Screening out lipid metabolic genes that are significantly related to the prognosis of prostate cancer. Methods The clinical data and mRNA expression data of prostate cancer were downloaded from the TCGA database; R language was applied to screen the differential genes between the normal tissue and the prostate cancer tissue. Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to search lipid metabolism genes. Combining the patient's survival status and survival time, the prognostic related lipid metabolic genes were screened out by uniCOX regression. The survival analysis was done by dividing the patients into high and low expression group. Gene Set Enrichment Analysis (GSEA) software was applied to the function enrichment of the key gene. Results A total of 1973 differential genes were screened, including 83 differential lipid metabolic genes. A total of five lipid metabolic genes were found which were related to promote prostate cancer, including CPT1B, AKR1C4, AKR1C2, UGT1A10, and CYP4F3. Survival analysis showed that CPT1B was significantly correlated with the prognosis of prostate cancer. Function enrichment analysis showed that CPTIB was significantly positively correlated with linoleic acid and α linolenic acid metabolism, and negatively correlated with WNT signaling pathway. Conclusion CPT1B overexpression is significantly associated with poor prognosis in prostate cancer.

Key words: prostate cancer, bioinformatics, risk genes, prognosis, lipid metabolism

中图分类号:

R737.25

朱少杰, 张友强. 基于生物信息学筛选影响前列腺癌预后的脂代谢基因[J]. 承德医学院学报, 2022, 39(5): 376-380.

ZHU Shao-jie, ZHANG You-qiang. Screening Out Prognostic Related Lipid Metabolic Genes to Predict the Prognosis of Prostate Cancer based on Bioinformatics[J]. Journal of Chengde Medical University, 2022, 39(5): 376-380.

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