首页|失巢凋亡相关LncRNAs在肺腺癌中的预后价值及免疫浸润分析

失巢凋亡相关LncRNAs在肺腺癌中的预后价值及免疫浸润分析

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目的 探究失巢凋亡相关的长链非编码RNA(arlncRNAs)在肺腺癌中的预后价值和免疫浸润分析.方法 从TCGA数据库下载肺腺癌的RNA-seq数据及临床信息,从GeneCards和Harmonizome数据库获取失巢凋亡相关基因.通过共表达分析、差异分析和WGCNA分析,筛选与肺腺癌发生密切相关的差异表达的arlncRNAs.基于arlncRNAs构建预后风险模型,对其预测效能进一步验证.最后利用共识聚类识别肺腺癌失巢凋亡相关的分子亚型.结果 确定了7个预后arlncRNAs,其建立的预后风险模型、ROC曲线AUC值均大于0.7.生存分析和免疫浸润分析发现,低风险患者的总生存率较高,具有较高的免疫浸润,对低风险组患者可能有更好的免疫治疗效果.药物敏感性分析表明,高风险组患者对常用的化疗药更敏感.根据模型基因的表达,通过共识聚类确定了亚型C1和C2,C1显示较好的预后.结论 7个arlncRNAs建立的预后风险模型能有效预测肺腺癌患者的预后.免疫相关和药物敏感性分析结果,为肺腺癌患者精确的个体化治疗提供参考依据.
Prognostic Value and Immune Infiltration of Anoikis-related LncRNAs in Lung Adenocarcinoma
Objective To explore the prognostic value and immune infiltration landscape of anoikis-related long noncoding RNAs(arlncRNAs)in lung adenocarcinoma.Methods RNA-seq and clinical data of lung adenocarcinoma were downloaded from the TCGA database,and anoikis-related genes were obtained from the GeneCards and Harmonizome databases.Coexpression,differential,and WGCNA analyses were performed to screen differentially expressed arlncRNAs closely related to the occurrence of lung adenocarcinoma.A prognostic risk model was then constructed based on the arlncRNAs,and its predictive efficacy was further validated.Finally,consensus clustering was used to identify the molecular subtypes associated with anoikis in lung adenocarcinoma.Results Seven prognostic arlncRNAs were identified,and the prognostic risk models established based on them had AUC values of ROC curves greater than 0.7.Survival and immune infiltration analyses revealed that low-risk patients had high overall survival and immune infiltration,implying that they experienced good immune treatment effects.Drug sensitivity analysis showed that the high-risk patients were more sensitive to commonly used chemotherapeutic agents than the low-risk patients.According to the expression of model genes,subtypes C1 and C2 were identified through consensus clustering,and C1 showed a good prognosis.Conclusion The prognostic risk model based on the seven arlncRNAs can effectively predict the prognosis of lung adenocarcinoma patients.The results of immune-related and drug sensitivity analyses provide a reference for the precise individualized treatment of patients with lung adenocarcinoma.

Lung adenocarcinomaAnoikisLncRNAPrognostic modelImmune

李欣、贺娟、金山、王若澜、罗奇彪、夏伟

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671000 大理,大理大学药学院

650032 昆明,中国人民解放军联勤保障部队第九二〇医院药剂科

肺腺癌 失巢凋亡 LncRNA 预后模型 免疫

云南省基础研究计划

202301AY070001-099

2024

肿瘤防治研究
湖北省卫生厅,中国抗癌协会,湖北省肿瘤医院

肿瘤防治研究

CSTPCD
影响因子:0.737
ISSN:1000-8578
年,卷(期):2024.51(1)
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