Abstract:

In order to identify aging-related long noncoding RNAs （lncRNAs） with prognostic significance in patients with pancreatic adenocarcinoma （PAAD）， a prognostic prediction model was constructed based on aging-related genes （ARG）. The transcriptome information of PAAD and normal samples were obtained from The Cancer Genome Atlas Database （TCGA） and Genotypic Tissue Expression Database （GTEX）， and correlation analysis screened out lncRNAs with significant correlations among ARG. The target lncRNA was identified through differential analysis， univariate regression， Lasso regression and multivariate regression， and a PAAD prognostic risk model was constructed. A total of 1 109 aging-related lncRNAs were identified， and 9 lncRNAs were screened to construct a risk score prognostic model， including AC245041.2， AC244153.1， AC091057.1， MIR3142HG， AL137779.2， AC145207.5， TDRKH-AS1， AC068620.2 and AC127024.6. The receiver operating curve （ROC） curve and AUC （the area under the curve） reached 0.798. The patients were divided into high-risk group and low-risk group according to the median risk. Kaplan-Meier analysis showed a significant difference in overall survival （OS） between the two groups. Combining the risk score and clinicopathological characteristics， multivariate Cox regression analysis risk score （HR： 1.136， 95%CI： 1.090~1.183） and age （HR： 1.021， 95%CI： 1.000~1.042） were independent prognostic factors， and a nomogram for PAAD prognostic evaluation was constructed. Furthermore， immunological correlation analysis revealed the differences in immune infiltration and the expression of immune checkpoint genes in the high and low risk groups， and the predictive characteristics of the model were related to immune status. The study constructed a PAAD prognostic model based on 9 aging-related lncRNAs， which may help improve the prognosis management of PAAD patients.

Key words: pancreatic cancer, aging, lncRNA, prognosis, model

摘要：

为鉴定出胰腺癌（pancreatic adenocarcinoma，PAAD）患者中有预后意义的衰老相关长链非编码RNA（long noncoding RNAs，lncRNA），基于衰老相关基因（aging-related gene，ARG）构建预后预测模型。从癌症基因组图谱数据库（The Cancer Genome Atlas Database，TCGA）、基因型组织表达数据库（Genotypic Tissue Expression Database，GTEX）获取PAAD和正常样本的转录组信息，相关性分析筛选出ARG中具有显著相关性的lncRNA。通过差异分析、单因素回归、Lasso回归和多因素回归鉴定出目标lncRNA，并构建出PAAD预后风险模型。研究共鉴定出1 109个衰老相关的lncRNA，筛选后最终获得9个lncRNA构建风险评分预后模型，包括AC245041.2、AC244153.1、AC091057.1、MIR3142HG、AL137779.2、AC145207.5、TDRKH-AS1、AC068620.2和AC127024.6。模型的ROC（receiver operating curve）曲线和曲线下AUC（area under the curve）达到0.798。根据风险中值分为高风险组和低风险组，Kaplan-Meier分析两组总体生存期（overall survival，OS）具有显著差异，将风险评分和临床病理特征结合，多因素Cox回归分析风险评分（HR：1.136，95%CI：1.090~1.183）、年龄（HR：1.021，95%CI：1.000~1.042）是预后独立因素，并构建出PAAD预后评估的列线图。进一步，免疫学相关分析揭示了高低风险组存在免疫浸润的差异以及免疫检查点基因的表达差异，模型的预测特征与免疫状态相关。研究基于9个衰老相关lncRNA构建了PAAD预后模型，有助于改善PAAD患者预后管理。

关键词: 胰腺癌, 衰老, lncRNA, 预后, 模型