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结肠腺癌中N6-甲基腺嘌呤相关铁死亡基因预后模型的特征分析与验证

Characterization and validation of a prognostic model for the N6-methyladenosine-associated ferroptosis gene in colon adenocarcinoma.

作者信息

Liu Xiaoyu, An Jiaxuan, Wang Qi, Jin Hongyong

机构信息

Department of Gastrointestinal Colorectal and Anal Surgery, The China-Japan Union Hospital of Jilin University, Changchun, China.

Department of General Practice, The Affiliated Hospital of Yan'an University, Yan'an, China.

出版信息

Transl Cancer Res. 2024 Aug 31;13(8):4389-4407. doi: 10.21037/tcr-24-88. Epub 2024 Aug 6.

DOI:10.21037/tcr-24-88
PMID:39262465
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11384320/
Abstract

BACKGROUND

According to statistics, colon adenocarcinoma (COAD) ranks third in global incidence and second in mortality. The role of N6-methyladenosine (m6A) modification-dependent ferroptosis in tumor development and progression is gaining attention. Therefore, it is meaningful to explore the biological functions mediated by m6A ferroptosis related genes (m6A-Ferr-RGs) in the prognosis and treatment of COAD. This study aimed to explore the regulatory mechanisms and prognostic features of m6A-Ferr-RGs in COAD based on the COAD transcriptome dataset.

METHODS

The expression data of Ferr-RGs and the correlated analysis with prognosis related m6A regulators were conducted to obtain candidate m6A-Ferr-RGs. Then, the differentially expressed genes (DEGs) between COAD and normal samples were intersected with candidate m6A-Ferr-RGs to obtain differentially expressed m6A Ferr-RGs (DE-m6A-Ferr-RGs) in COAD. Cox regression analyses were performed to establish risk model and validated in the GSE17538 and GSE41258 datasets. The nomogram was constructed and verified by calibration curves. Moreover, tumor immune dysfunction and exclusion (TIDE) was used to assess immunotherapy response in two risk groups. Finally, the expression of m6A-Ferr-related prognostic genes was validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR).

RESULTS

In total, 6 model genes (, , , , , and ) were obtained to construct the risk model. The nomogram was established based on the independent prognostic factors for predicting survival of COAD. TIDE assessed that the high-risk group suffered from greater immune resistance. Ultimately, the experimental results confirmed that the expression trends of all model genes were consistent among data from public database.

CONCLUSIONS

In this study, m6A-Ferr-related prognostic model for COAD was constructed using transcriptome data and clinical data of COAD in public database, which may have potential immunotherapy and chemotherapy guidance implications.

摘要

背景

据统计,结肠腺癌(COAD)的全球发病率排名第三,死亡率排名第二。N6-甲基腺苷(m6A)修饰依赖性铁死亡在肿瘤发生和发展中的作用日益受到关注。因此,探索m6A铁死亡相关基因(m6A-Ferr-RGs)介导的生物学功能在COAD的预后和治疗中具有重要意义。本研究旨在基于COAD转录组数据集探索m6A-Ferr-RGs在COAD中的调控机制和预后特征。

方法

对Ferr-RGs的表达数据以及与预后相关的m6A调节因子进行相关性分析,以获得候选m6A-Ferr-RGs。然后,将COAD与正常样本之间的差异表达基因(DEGs)与候选m6A-Ferr-RGs进行交集分析,以获得COAD中差异表达的m6A Ferr-RGs(DE-m6A-Ferr-RGs)。进行Cox回归分析以建立风险模型,并在GSE17538和GSE41258数据集中进行验证。通过校准曲线构建并验证列线图。此外,使用肿瘤免疫功能障碍和排除(TIDE)来评估两个风险组中的免疫治疗反应。最后,通过定量逆转录聚合酶链反应(qRT-PCR)验证m6A-Ferr相关预后基因的表达。

结果

总共获得了6个模型基因(、、、、、和)来构建风险模型。基于预测COAD生存的独立预后因素建立了列线图。TIDE评估高危组具有更强的免疫抗性。最终,实验结果证实所有模型基因在公共数据库数据中的表达趋势一致。

结论

在本研究中,利用公共数据库中COAD的转录组数据和临床数据构建了COAD的m6A-Ferr相关预后模型,这可能对免疫治疗和化疗指导具有潜在意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/3a47bc530a4e/tcr-13-08-4389-f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/e39e8a4149d0/tcr-13-08-4389-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/208f1cf3a764/tcr-13-08-4389-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/901474cce64e/tcr-13-08-4389-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/6d28f9dd71dc/tcr-13-08-4389-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/14f8fa3c62e5/tcr-13-08-4389-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/419f992ef6e5/tcr-13-08-4389-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/732f88fa0298/tcr-13-08-4389-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/874326e5aaaf/tcr-13-08-4389-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/3a47bc530a4e/tcr-13-08-4389-f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/e39e8a4149d0/tcr-13-08-4389-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/208f1cf3a764/tcr-13-08-4389-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/901474cce64e/tcr-13-08-4389-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/6d28f9dd71dc/tcr-13-08-4389-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/14f8fa3c62e5/tcr-13-08-4389-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/419f992ef6e5/tcr-13-08-4389-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/732f88fa0298/tcr-13-08-4389-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/874326e5aaaf/tcr-13-08-4389-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27e2/11384320/3a47bc530a4e/tcr-13-08-4389-f9.jpg

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