前列腺癌差异基因标志物筛选有助于预后评价

Screening of prostate cancer related differentially expressed genes contribute to the prognosis evaluation

目的通过生物信息学分析筛选前列腺癌预后相关的潜在预测基因。方法对前列腺癌基因组图谱中的基因表达数据进行生物信息学分析,确定肿瘤与正常样本之间的差异表达基因,并进行了功能和通路的富集分析。使用KM生存分析确定与前列腺癌的预后有关的基因。最后结合患者的临床病理资料对各差异基因的临床意义进行深度挖掘。结果共确定了334个上调的差异基因和26个下调的差异基因。肌肉和神经相关通路是其主要的生物学过程。通过KM生存分析得出由12个基因(PATE1、TGM4、TPSB2、PRLR、UGT2B17、BCAN、KLHL40、MEI4、CACNG7、CRYGD、OR52E8、OLIG2)组成的在预测总体生存率方面表现良好的预后标志物。同时,构建了其对于TNM分期、高低风险的相关预测分析。并进行了肿瘤和正常样本之间(全部/配对)boxplot图验证。结论本研究发现了一组基于基因的标志物,可用于预测前列腺癌患者的预后,这可能有助于临床医生的决策,并可作为前列腺癌药物合成的潜在新靶点。

Objective To screen potential predictive genes related to the prognosis of prostate cancer through bioinformatics analysis.Methods The gene data in the TCGA database were analyzed to determine the differentially expressed genes(DEGs)between tumor and normal samples,and enrichment of function and signaling pathway was carried out.Genes related to the prognosis of prostate cancer were identified with KM survival analysis,and the clinical significance of the DEGs was analyzed.Results A total of 334 up-regulated DEGs and 26 down-regulated DEGs were identified,which were related to muscle and nerve pathways.KM survival analysis screened out 12 genes,including PATE1,TGM4,TPSB2,PRLR,UGT2B17,BCAN,KLHL40,MEI4,CACNG7,CRYGD,OR52E8 and OLIG2,which performed well in predicting the overall survival.The correlation between TNM stage,high risk and low risk was analyzed.The relationship between tumor and normal samples(all/paired)was verified with Boxplot.Conclusion Our study has identified a set of gene-based markers that can be used to predict the prognosis of prostate cancer patients,which may contribute to clinicians decision-making,and serve as potential new targets for drug development.