Ferroptosis-Related LncRNAs Signature Predicts the Prognosis of Stomach Adenocarcinoma
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摘要:
目的 通过研究胃癌细胞铁死亡相关LncRNA，建立预测胃腺癌患者的生存预后情况的预后模型，从而为其生物标志物与治疗靶点的开发提供理论依据。 方法 对 TCGA数据库中的胃腺癌患者的转录本测序数据进行分析，并与铁死亡相关基因取交集，通过共表达和差异分析方法，从而筛选出与铁死亡相关的 LncRNA。采用单因素和多因素 Cox回归分析，筛选出与胃腺癌患者预后相关的 LncRNA，从而建立预后评分模型。在此基础上，对每一样本进行风险值计算，并对模型的可靠性进行充分验证；根据模型结果对高低风险组之间进行免疫浸润与免疫反应等差异分析。 结果 肿瘤组织中相较正常组织筛选到与铁死亡相关的503个 LncRNA （上调431个，下调72个）；单因素Cox回归分析得出33个可作为独立风险因子的 LncRNA，而多因素Cox回归分析构建出一个由17个 LncRNA组成的预测模型。生存曲线表明高风险的患者比低高风险的患者的存活率显著降低（P < 0.001）；单因素和多因素独立预后分析表明，年龄、分期与风险值是患者的独立危险因素；时间依赖的ROC曲线提示，模型的1，2，3 a生存率预测AUC值为0.751，0.799，0.779，证明模型具备可靠与稳定性。高低风险组间多个免疫激活反应、免疫细胞的浸润程度与免疫检查点的表达水平存在显著差异。 结论 以铁死亡相关lncRNA为基础，建立胃腺癌患者预后预测模型，可较好地评估患者预后情况，纳入模型的LncRNA具备开发为生物标志物与治疗靶点的可行性。 Abstract:Objective To establish a prognostic model that predicts the survival and prognosis of gastric adenocarcinoma patients by studying the LncRNAs related to iron death in gastric cancer cells, thereby providing a theoretical basis for the development of their biomarkers and therapeutic targets. Methods The transcript sequencing data of gastric adenocarcinoma patients in the TCGA database were analyzed and intersected with iron death-related genes, which were screened for iron death-related LncRNAs by co-expression and differential analysis methods. One-way and multifactorial Cox regression analyses were used to screen out the prognostic-related LncRNAs in gastric adenocarcinoma patients, so as to establish the prognostic scoring models. On this basis, risk values were calculated for each sample, and the reliability of the model was fully verified. According to the model results, differences in the immune infiltration and immune response between the high- and low-risk groups were analyzed. Results Tumor tissues were screened for 503 LncRNAs （431 up-regulated and 72 down-regulated） associated with iron death compared to the normal tissues; univariate Cox regression analysis yielded 33 LncRNAs that could be used as the independent risk factors, whereas multivariate Cox regression analysis constructed a predictive model consisting of 17 LncRNAs. Survival curves indicated that patients with the high risk had the significantly lower survival rates than those with the low risk （P < 0.001）. Unifactorial and multifactorial independent prognostic analyses showed that age, stage, and risk value were independent risk factors for patients; Time-dependent ROC curves suggested that the predicted AUC values of the model's 1-, 2-, and 3-year survival rates were 0.751, 0.799, and 0.779 respectively, proving that the model was reliable and stable. There were significant differences in multiple immune activation responses, the degree of immune cell infiltration, and the expression levels of immune check points between the high- and low-risk groups. Conclusion The established prognostic prediction model based on iron death-related lncRNAs for gastric adenocarcinoma patients can better assess the prognosis of patients, and the lncRNAs included in the model have the feasibility of being developed into biomarkers and therapeutic targets. -
Key words:
- Stomach adenocarcinoma /
- Ferroptosis /
- LncRNA /
- Prognostic model
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图 1 差异基因功能富集
A：上调基因GO功能富集；B：下调基因GO功能富集；C：上调基因KEGG通路富集；D：下调基因KEGG通路富集。
Figure 1. Functional enrichment of differential genes
图 2 预后模型构建
A：单因素Cox回归分析；B：预后模型的风险系数；C：LncRNA-mRNA共表达关系。
Figure 2. Construction of the prognostic model
图 4 预后模型的评价
A：生存曲线；B：生存状态图；C：风险曲线；D：风险基因热图。
Figure 4. Evaluation of the prognostic model
图 5 独立预后分析
A：单因素独立预后分析；B：多因素独立预后分析；C：ROC曲线；D：DCA曲线；E；时间依赖的ROC曲线；F：nomogram图。
Figure 5. Independent prognostic analysis
图 8 高低风险组间表型的差异情况
A：免疫反应差异；B：免疫检查点表达差异；C：m6A甲基化调控基因表达差异。
Figure 8. Phenotypic differences between the high and low-risk group
表 1 患者临床基线资料表[n（%）]
Table 1. The clinical characteristics of patients in the TCGA database [n（%）]
临床特征 分类 人数 死亡人数 n 375 150 性别 女性 134 （35.7） 51（34） 男性 241 （64.3） 99（66） 年龄 ≤65 173 （46.1） 60（40） >65 202 （53.9） 90（60） 组织学分级 G1 10 （2.7） 3（2） G2 131 （34.9） 49（32.7） G3 234 （62.4） 98（65.3） 病理分期 Stage I 46 （12.3） 11（7.3） Stage II 123 （32.8） 34（22.7） Stage III 165 （44） 79（52.7） Stage IV 41 （10.9） 26（17.3） T 分期 T1 15 （4） 1（0.7） T2 80 （21.3） 27（18） T3 179 （47.8） 79（52.7） T4 101 （26.9） 43（28.6） N 分期 N0 114 （30.4） 29（19.3） N1 102 （27.2） 43（28.7） N2 75 （20） 31（20.7） N3 84 （22.4） 47（31.3） M 分期 M0 339 （90.4） 133（88.7） M1 36 （9.6） 17（11.3） 
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