基于双硫死亡相关lncRNA构建肺腺癌预后模型及ceRNA网络

Identification of a disulfidptosis related lncRNA prognostic model and ceRNA network in lung adenocarcinoma

摘要

目的 筛选与双硫死亡相关的长链非编码RNA（lncRNA）并用于构建预测肺腺癌患者生存风险的预后模型。方法 RNA-seq数据和临床信息来自癌症基因组图谱（TCGA）数据库。利用LASSO回归构建基于双硫死亡相关lncRNA的预后模型。根据风险评分将患者分为高、低风险组，比较两组间在总生存期、功能富集、肿瘤免疫细胞浸润、药物敏感性等方面的差异，构建内源竞争RNA（ceRNA）网络，并通过外部实验验证3个lncRNA在肺腺癌中的表达情况。结果 构建由3个双硫死亡lncRNA（AL365181.2、 AC012615.1、 AL606489.1）组成的风险预后模型，低风险组的生存率明显优于高风险组（P<0.001）。不同组患者免疫细胞浸润、富集分析、抗肿瘤药物敏感性的差异显著，进一步以模型相关的lncRNA构建ceRNA网络，3个lncRNA在肺腺癌肿瘤组织中的表达显著高于正常组织（均 P<0.001）。结论 使用3个双硫死亡相关的lncRNA构建预后模型可独立预测肺腺癌患者的生存状况，为双硫死亡机制在肺腺癌中的研究及治疗提供了新的潜在生物标志物。

Abstract

Objective To screen disulfidptosis-related lncRNAs for prognostic biomarkers for lung adenocarcinoma (LUAD) diagnosis and treatment. Methods RNA-seq data and clinical information were obtained from The Cancer Genome Atlas (TCGA) database. LASSO regression analysis was used to construct a prognostic model based on disulfidptosis-related lncRNA. Patients were divided into high/low risk groups based on their risk-scores. Differences in overall survival, functional enrichment, tumor immune cell infiltration and drug sensitivity were further explored between risk groups. Finally, the ceRNA network was constructed and the expression of three lncRNAs in LUAD was verified by external experiments. Results Developing a prognostic model consisting of three disulfidptosis lncRNA (AL365181.2, AC012615.1, AL606489.1), the survival rate of the low-risk group was significantly better than that of the high-risk group. There were significant differences in OS, immune cell infiltration, immune checkpoint expression and immunotherapy response among patients in different risk groups and in building ceRNA networks with model-associated lncRNA. Experimental validation showed that three lncRNA were expressed higher in LUAD tumor tissues than in normal tissues. Conclusion The present prognostic model was constructed using 3 disulfidptosis-related lncRNA and demonstrated that the model can independently predict survival in LUAD patients, providing new biomarkers for disulfidptosis in LUAD therapy.

关键词

肺腺癌 / 双硫死亡 / 长链非编码RNA / 预后模型 / 内源竞争RNA网络

Key words

lung adenocarcinoma / disulfidptosis / long non-coding RNA / prognostic model / competing endogenous RNA

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基金资助

国家自然科学基金资助项目(82103467)

西安交通大学基础-临床融合创新项目基金资助项目(YXJLRH2022033)