{"title":"Identification of three subtypes of thyroid cancer based on IFN-γ-related genes to reveal their prognostic characteristics.","authors":"Fang Huang, Qian Sui, Ke Li","doi":"10.1007/s00423-025-03623-w","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Thyroid cancer is one of the deadliest malignancies. Increasing evidence suggests that interferon-γ (IFN-γ) plays an important role in anti-tumor immunity and its treatment. However, the effectiveness of classifying, predicting prognosis, and immunotherapy for thyroid cancer based on IFN-γ-related genes has not been discovered.</p><p><strong>Methods: </strong>We used the Gene Set Enrichment Analysis (GSEA) database to obtain IFN-γ-related genes and classified thyroid cancer patients from The Cancer Genome Atlas (TCGA). We systematically explored the differences among various thyroid cancer subtypes from multiple perspectives, such as Kaplan-Meier survival analysis, tumor mutation analysis, immune analysis, enrichment analysis, and drug sensitivity analysis. Finally, we screened some potential drugs suitable for each population.</p><p><strong>Results: </strong>Through clustering analysis, we obtained three thyroid cancer subtypes with different IFN-γ-related gene expression levels. The survival analysis results showed significant survival differences among these three subtypes. In addition, gene mutation analysis in different subtypes found that BRAF, TTN, and TG were the top three genes with the highest mutation frequency in the three subtypes, which may be related to their prognosis. Cluster 1 and cluster 2 were the two subtypes with the greatest difference in immune cell infiltration levels, and the differentially expressed genes were mainly enriched in immune-related biological processes or signaling pathways such as leukocyte-mediated immunity, regulation of T cell activation, and chemokine signaling pathway. Eighteen compounds such as Cyclopamine, Erlotinib, FH535, Imatinib, and A-770,041 were selected as potential therapeutic drugs in this study, and their sensitivity to different subtypes varied.</p><p><strong>Conclusion: </strong>Based on bioinformatics analysis, we discovered a new classification method based on IFN-γ genes, which could divide thyroid cancer patients into three populations with significant characteristics. Different populations had different mutation patterns, immune infiltration levels, and candidate therapeutic drugs.</p>","PeriodicalId":17983,"journal":{"name":"Langenbeck's Archives of Surgery","volume":"410 1","pages":"69"},"PeriodicalIF":2.1000,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11828823/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Langenbeck's Archives of Surgery","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00423-025-03623-w","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SURGERY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Thyroid cancer is one of the deadliest malignancies. Increasing evidence suggests that interferon-γ (IFN-γ) plays an important role in anti-tumor immunity and its treatment. However, the effectiveness of classifying, predicting prognosis, and immunotherapy for thyroid cancer based on IFN-γ-related genes has not been discovered.
Methods: We used the Gene Set Enrichment Analysis (GSEA) database to obtain IFN-γ-related genes and classified thyroid cancer patients from The Cancer Genome Atlas (TCGA). We systematically explored the differences among various thyroid cancer subtypes from multiple perspectives, such as Kaplan-Meier survival analysis, tumor mutation analysis, immune analysis, enrichment analysis, and drug sensitivity analysis. Finally, we screened some potential drugs suitable for each population.
Results: Through clustering analysis, we obtained three thyroid cancer subtypes with different IFN-γ-related gene expression levels. The survival analysis results showed significant survival differences among these three subtypes. In addition, gene mutation analysis in different subtypes found that BRAF, TTN, and TG were the top three genes with the highest mutation frequency in the three subtypes, which may be related to their prognosis. Cluster 1 and cluster 2 were the two subtypes with the greatest difference in immune cell infiltration levels, and the differentially expressed genes were mainly enriched in immune-related biological processes or signaling pathways such as leukocyte-mediated immunity, regulation of T cell activation, and chemokine signaling pathway. Eighteen compounds such as Cyclopamine, Erlotinib, FH535, Imatinib, and A-770,041 were selected as potential therapeutic drugs in this study, and their sensitivity to different subtypes varied.
Conclusion: Based on bioinformatics analysis, we discovered a new classification method based on IFN-γ genes, which could divide thyroid cancer patients into three populations with significant characteristics. Different populations had different mutation patterns, immune infiltration levels, and candidate therapeutic drugs.
背景：甲状腺癌是最致命的恶性肿瘤之一：甲状腺癌是最致命的恶性肿瘤之一。越来越多的证据表明，干扰素-γ（IFN-γ）在抗肿瘤免疫及其治疗中发挥着重要作用。然而，基于 IFN-γ 相关基因对甲状腺癌进行分类、预测预后和免疫治疗的有效性尚未被发现：方法：我们利用基因组富集分析（Gene Set Enrichment Analysis，GSEA）数据库从癌症基因组图谱（The Cancer Genome Atlas，TCGA）中获得了IFN-γ相关基因并对甲状腺癌患者进行了分类。我们从Kaplan-Meier生存分析、肿瘤突变分析、免疫分析、富集分析和药物敏感性分析等多个角度系统地探讨了各种甲状腺癌亚型之间的差异。最后，我们筛选出了一些适合不同人群的潜在药物：通过聚类分析，我们得到了三种甲状腺癌亚型，它们的IFN-γ相关基因表达水平各不相同。生存率分析结果显示，这三种亚型的生存率存在明显差异。此外，不同亚型的基因突变分析发现，BRAF、TTN和TG是三个亚型中突变频率最高的前三个基因，这可能与它们的预后有关。簇1和簇2是免疫细胞浸润水平差异最大的两个亚型，差异表达的基因主要富集在免疫相关的生物学过程或信号通路中，如白细胞介导的免疫、T细胞活化调控、趋化因子信号通路等。本研究选择了环丙胺、厄洛替尼、FH535、伊马替尼、A-77041等18种化合物作为潜在的治疗药物，它们对不同亚型的敏感性各不相同：基于生物信息学分析，我们发现了一种基于IFN-γ基因的新分类方法，可将甲状腺癌患者分为三个具有显著特征的人群。不同人群具有不同的突变模式、免疫浸润水平和候选治疗药物。
期刊介绍：
Langenbeck''s Archives of Surgery aims to publish the best results in the field of clinical surgery and basic surgical research. The main focus is on providing the highest level of clinical research and clinically relevant basic research. The journal, published exclusively in English, will provide an international discussion forum for the controlled results of clinical surgery. The majority of published contributions will be original articles reporting on clinical data from general and visceral surgery, while endocrine surgery will also be covered. Papers on basic surgical principles from the fields of traumatology, vascular and thoracic surgery are also welcome. Evidence-based medicine is an important criterion for the acceptance of papers.
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