基于衰老相关基因探索肾透明细胞癌的亚组和个体化治疗

Exploring the grouping and individualized treatment of renal clear cell carcinoma through senescence related genes

目的 肾透明细胞癌(ccRCC)的发病率较高,肿瘤异质性的存在导致ccRCC患者的预后存在明显差异,本研究推测在ccRCC中可能存在潜在的亚组,并通过衰老相关基因(SRGs)进行ccRCC的风险建模、分组以及亚组间的差异探索。方法 从TCGA网站中获得ccRCC患者的mRNA-seq数据,筛选出正常和肿瘤组织中存在差异表达的SRGs。使用单因素Cox-Lasso-多因素Cox的方法建立风险模型,根据风险评分将患者分为高、低风险组。在内部队列和外部队列中验证模型和分组的效能。分析二组间功能通路和免疫微环境的差异。结果 内部和外部队列的验证表明模型有良好的预测效能并且分组方法有效。功能通路以及免疫浸润分析发现两亚组间的免疫微环境存在差异。结论 基于SRGs对ccRCC患者的预后模型构建和分组是有效的,免疫微环境的差异可能是导致二组生存差异的原因。

Objective Clear cell renal cell carcinoma(ccRCC)has a high incidence rate.The existence of tumor heterogeneity leads to differences in prognosis of patients.It is speculated that there may be potential subgroups.Senescence related genes are used for risk modeling,grouping,and exploring differences between subgroups of ccRCC.Methods Download mRNA seq data about ccRCC patients in TCGA database,analyze the expression of senescence related genes in normal and tumor tissues,and screen for differentially expressed genes.Establish a risk model using the single factor Cox-Lasso-multi factor Cox method,and divide patients into high and low risk groups based on risk scores.Verify the effectiveness of the model and grouping in the validation queue and external queues.Analyzed the differences in functional pathways and immune microenvironment between two groups.Results The validation of internal and external queues indicates that the model has good predictive performance and the grouping method is effective.Functional pathways and immune infiltration analysis revealed differences in the immune microenvironment between two subgroups.Conclusion The construction and grouping of risk models for ccRCC patients based on senescence related genes is effective,and the differences in immune microenvironment may be the reason for the survival differences between the two groups.