结肠腺癌中 N6-甲基腺苷相关铁突变基因预后模型的特征描述与验证

IF 1.5 4区 医学 Q4 ONCOLOGY
Translational cancer research Pub Date : 2024-08-31 Epub Date: 2024-08-06 DOI:10.21037/tcr-24-88
Xiaoyu Liu, Jiaxuan An, Qi Wang, Hongyong Jin
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引用次数: 0

摘要

背景:据统计,结肠腺癌(COAD)在全球发病率中排名第三,死亡率中排名第二。N6-甲基腺苷(m6A)修饰依赖的铁突变在肿瘤发生和发展中的作用正受到越来越多的关注。因此,探讨 m6A 铁突变相关基因(m6A-Ferr-RGs)在 COAD 的预后和治疗中介导的生物学功能很有意义。本研究旨在基于COAD转录组数据集探讨m6A-Ferr-RGs在COAD中的调控机制和预后特征:方法:通过Ferr-RGs的表达数据以及与预后相关的m6A调控因子的相关分析,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 相交,得到 COAD 中差异表达的 m6A Ferr-RGs(DE-m6A-Ferr-RGs)。通过 Cox 回归分析建立了风险模型,并在 GSE17538 和 GSE41258 数据集中进行了验证。构建了提名图,并通过校准曲线进行了验证。此外,还使用肿瘤免疫功能障碍和排斥(TIDE)来评估两个风险组的免疫治疗反应。最后,通过定量反转录聚合酶链反应(qRT-PCR)验证了m6A-Ferr相关预后基因的表达:结果:共获得了6个模型基因(HSD17B11、VEGFA、CXCL2、ASNS、FABP4和GPX2)来构建风险模型。根据预测 COAD 存活率的独立预后因素建立了提名图。TIDE 评估表明,高风险组具有更强的免疫抵抗力。最终,实验结果证实,所有模型基因的表达趋势与来自公共数据库的数据一致:本研究利用转录组数据和公共数据库中的 COAD 临床数据构建了与 m6A-Ferr 相关的 COAD 预后模型,该模型可能具有潜在的免疫治疗和化疗指导意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Characterization and validation of a prognostic model for the N6-methyladenosine-associated ferroptosis gene in colon adenocarcinoma.

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 (HSD17B11, VEGFA, CXCL2, ASNS, FABP4, and GPX2) 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.

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来源期刊
CiteScore
2.10
自引率
0.00%
发文量
252
期刊介绍: Translational Cancer Research (Transl Cancer Res TCR; Print ISSN: 2218-676X; Online ISSN 2219-6803; http://tcr.amegroups.com/) is an Open Access, peer-reviewed journal, indexed in Science Citation Index Expanded (SCIE). TCR publishes laboratory studies of novel therapeutic interventions as well as clinical trials which evaluate new treatment paradigms for cancer; results of novel research investigations which bridge the laboratory and clinical settings including risk assessment, cellular and molecular characterization, prevention, detection, diagnosis and treatment of human cancers with the overall goal of improving the clinical care of cancer patients. The focus of TCR is original, peer-reviewed, science-based research that successfully advances clinical medicine toward the goal of improving patients'' quality of life. The editors and an international advisory group of scientists and clinician-scientists as well as other experts will hold TCR articles to the high-quality standards. We accept Original Articles as well as Review Articles, Editorials and Brief Articles.
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