Prognostic Value and Immune Infiltration of Anoikis-related LncRNAs in Lung Adenocarcinoma
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摘要: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。
Abstract:ObjectiveTo explore the prognostic value and immune infiltration landscape of anoikis-related long noncoding RNAs (arlncRNAs) in lung adenocarcinoma.
MethodsRNA-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.
ResultsSeven 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.
ConclusionThe 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.
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Key words:
- Lung adenocarcinoma /
- Anoikis /
- LncRNA /
- Prognostic model /
- Immune
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Competing interests: The authors declare that they have no competing interests.利益冲突声明：所有作者均声明不存在利益冲突。作者贡献：李欣：文章设计与撰写贺娟：数据分析解释、文章撰写金山：数据分析、文章修改王若澜：实验设计、文章修改罗奇彪：文章修改夏伟：指导及审阅文章
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图 1 差异表达的arlncRNAs与关键模块arlncRNAs的维恩图
Figure 1 Venn diagram of differentially expressed arlncRNAs versus key module arlncRNAs
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图 2 基于预后相关的arlncRNAs构建风险模型
Figure 2 Constructing a risk model based on prognostic-related arlncRNAs
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图 3 训练集和两个验证集的风险评分分布、生存状态和生存时间的评估
Figure 3 Evaluation of risk score distribution, survival status, and survival time for training set and two validation sets
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图 4 整个TCGA数据集中高、低风险患者不同临床病理特征的生存分析
Figure 4 Survival analysis of high- and low- risk patients in the entire TCGA dataset according to different clinicopathological characteristics
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图 7 高、低风险组之间的基因集富集分析
Figure 7 Gene set enrichment analysis between high- and low-risk groups
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