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基于铁死亡相关长链非编码 RNA 表达的预测胃腺癌预后的潜在关键标志物。

Potential Key Markers for Predicting the Prognosis of Gastric Adenocarcinoma Based on the Expression of Ferroptosis-Related lncRNA.

机构信息

Taizhou Municipal Hospital, Taizhou 318000, China.

出版信息

J Immunol Res. 2022 Apr 29;2022:1249290. doi: 10.1155/2022/1249290. eCollection 2022.

DOI:10.1155/2022/1249290
PMID:35528617
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9076347/
Abstract

BACKGROUND

Gastric cancer is one of the most common malignant tumors, and it ranks third in global cancer-related mortality. This research was aimed at identifying new targeted treatments for gastric adenocarcinoma by constructing a ferroptosis-related lncRNA prognostic feature model.

METHODS

The gene expression profile and clinical data of gastric adenocarcinoma patients were downloaded from TCGA database. FerrDb database was used to determine the expression of iron death-related genes. We used R software to clean the TCAG gastric adenocarcinoma gene expression cohort and screen iron death-related differential genes and lncRNAs. The potential prognostic markers and immune infiltration characteristics were determined by constructing prognostic model and multivariate validation of lncRNA related to ferroptosis prognosis. Finally, the characteristics of immune infiltration were determined by immune correlation analysis.

RESULTS

We identified 26 ferroptosis-related lncRNAs with independent prognostic value. The Kaplan-Meier analysis identified high-risk lncRNAs associated with poor prognosis of STAD. The risk scoring model constructed by AC115619.1, AC005165.1, LINC01614, and AC002451.1 was better than traditional clinicopathological features. The 1-, 3-, and 5-year survival rates of STAD patients were predicted by the nomogram. GSEA reveals the oxidative respiration and tumor-related pathways in different risk groups. Immune analysis found significant differences in the expression of immune checkpoint-related genes TNFSF9, TNFSF4, and PDCD1LG2 between the two groups of patients. Meanwhile, there were significant differences in APC co stimulation, CCR, and checkpoint between the two groups.

CONCLUSION

Based on the prognostic characteristics of ferroptosis-related lncRNAs, we identified the potential ferroptosis-related lncRNAs and immune infiltration characteristics in gastric adenocarcinoma, which will help provide new targeted treatments for gastric adenocarcinoma.

摘要

背景

胃癌是最常见的恶性肿瘤之一，其在全球癌症相关死亡率中排名第三。本研究旨在通过构建铁死亡相关长链非编码 RNA 预后特征模型，为胃腺癌寻找新的靶向治疗方法。

方法

从 TCGA 数据库中下载胃腺癌患者的基因表达谱和临床数据。使用 FerrDb 数据库确定铁死亡相关基因的表达。我们使用 R 软件清理 TCGA 胃腺癌基因表达队列，筛选铁死亡相关差异基因和 lncRNA。通过构建预后模型和铁死亡预后相关 lncRNA 的多变量验证，确定潜在的预后标志物和免疫浸润特征。最后，通过免疫相关性分析确定免疫浸润特征。

结果

我们确定了 26 个具有独立预后价值的铁死亡相关 lncRNA。Kaplan-Meier 分析确定了与 STAD 预后不良相关的高风险 lncRNA。由 AC115619.1、AC005165.1、LINC01614 和 AC002451.1 构建的风险评分模型优于传统的临床病理特征。通过列线图预测了 STAD 患者的 1 年、3 年和 5 年生存率。GSEA 揭示了不同风险组中氧化呼吸和肿瘤相关途径的差异。免疫分析发现两组患者的免疫检查点相关基因 TNFSF9、TNFSF4 和 PDCD1LG2 的表达存在显著差异。同时，两组之间 APC 共刺激、CCR 和检查点存在显著差异。

结论

基于铁死亡相关 lncRNA 的预后特征，我们确定了胃腺癌中潜在的铁死亡相关 lncRNA 和免疫浸润特征，这将有助于为胃腺癌提供新的靶向治疗方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8da/9076347/edc89828bf52/JIR2022-1249290.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8da/9076347/c79a44e8058c/JIR2022-1249290.001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8da/9076347/5e31ca5e0846/JIR2022-1249290.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8da/9076347/d1351fdfe784/JIR2022-1249290.006.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8da/9076347/edc89828bf52/JIR2022-1249290.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8da/9076347/c79a44e8058c/JIR2022-1249290.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8da/9076347/39bb35402ea6/JIR2022-1249290.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8da/9076347/9cb743c0ecc3/JIR2022-1249290.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8da/9076347/8b76ad2df95e/JIR2022-1249290.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8da/9076347/5e31ca5e0846/JIR2022-1249290.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8da/9076347/d1351fdfe784/JIR2022-1249290.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8da/9076347/c641550977af/JIR2022-1249290.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8da/9076347/7702e59ff7ed/JIR2022-1249290.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8da/9076347/edc89828bf52/JIR2022-1249290.009.jpg

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