空军军医大学学报2024，Vol.45Issue(7)：781-787,7.DOI:10.13276/j.issn.2097-1656.2024.07.010
机器学习算法确定的核心衰老基因在非远处转移性结直肠癌的预后和免疫微环境相关性分析
Correlation analysis of prognosis and immune microenvironment of core senescence genes identified by machine learning in non-distant metastatic colorectal cancer
摘要
Abstract
Objective To establish a senescence gene model for non-distant metastatic colorectal cancer(CRC),identify core senescence genes,and analyze their role in the tumor microenvironment.Methods Non-distant metastatic CRC databases of TCGA and GEO databases were downloaded,univariate Cox analysis was performed to identify prognostic-related senescence genes,and multivariate Cox analysis was performed to establish a senescence model for non-distant metastatic CRC.The ESTIMATE algorithm calculated the immune microenvironment score(stromal and immune score)of the cancerous sample and investigated the relationship between the aging model and it.The random survival forest algorithm was used to calculate the importance of aging genes and determine the core genes of aging.The CIBERSORT algorithm was used to evaluate the infiltration of tumor immune cells,and correlation analysis was conducted to study the relationship between core genes of aging and cell infiltration.Results Multivariate Cox analysis established a model composed of 6 senescence genes.Both TCGA and GEO showed that the prognosis of high-risk group was much worse than that of low-risk group(P＜0.001).The aging model was correlated with CRC microsatellite status,tumor immune score and stromal score.Three core senescence genes(TERT,SNAI1 and CSNK1A1)were identified by random survival forest algorithm and were associated with tumor immune cell infiltration.In addition,in the immunotherapy population,those with low expression of SNAI1(P=0.016)and CSNK1A1(P＜0.001)had longer survival times.Conclusion The greater the degree of senescence of tumor cells,the weaker their ability to proliferate,and the better the prognosis of non-distant metastatic CRC patients may be.As the core genes of senescence,TERT,SNAI1 and CSNK1A1 are related to the tumor microenvironment and may be used as biomarkers for immunotherapy.关键词
衰老基因/非远处转移结直肠癌/肿瘤免疫微环境/免疫细胞Key words
senescence genes/non-distant metastatic colorectal cancer/tumor immune microenvironment/immune cells分类
医药卫生引用本文复制引用
李世森,余鹏飞,乔一桓,王珂,李丹,李云龙..机器学习算法确定的核心衰老基因在非远处转移性结直肠癌的预后和免疫微环境相关性分析[J].空军军医大学学报,2024,45(7):781-787,7.基金项目
国家自然科学基金青年科学基金(82100680) （82100680）
