Development of a prognostic index based on an immunogenomic landscape analysis of papillary thyroid cancer
Development of a prognostic index based on an immunogenomic landscape analysis of papillary thyroid cancer
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DOI：
10.18632/aging.101754
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发表时间：
2019-01-31
期刊：
影响因子：
5.2
通讯作者：
Chen, Gang
中科院分区：
文献类型：
--
作者：
Lin, Peng;Guo, Yi-nan;Chen, Gang
背景资料：甲状腺乳头状癌（PTC）是甲状腺癌中最常见的亚型，炎症与其发生和预后密切相关。因此，迫切需要系统地探索其中的免疫基因组学景观以帮助PTC预后。癌症基因组图谱（TCGA）项目提供了大量的遗传PTC样本，使一个全面和可靠的immunogenomicstudy.Methods：我们整合了免疫相关基因（IRGs）和无进展间隔（PFIs）的表达谱在493 PTC患者的生存基于TCGA数据集。PTC患者的差异表达和生存相关IRGs通过计算差异算法和考克斯回归分析进行估计。这些PTC特异性IRGs的潜在分子机制和性质也在计算生物学的帮助下进行了探索。结果：46个免疫相关基因的差异表达与PTC患者的临床预后显著相关。功能富集分析显示，这些基因积极参与了一个嘌呤-细胞因子受体相互作用KEGG途径。基于IRG（AGTR 1、CTGF、FAM 3B、IL 11、IL 17 C、PTH 2 R和SPAG 11 A）的预后特征在预后预测中表现中等，并且与年龄、肿瘤分期、转移、病变数量和肿瘤负荷相关。有趣的是，基于IRGs的预后指数反映了几种类型的免疫细胞的浸润。结论：总之，我们的研究结果筛选了几个IRGs的临床意义，揭示了驱动程序的免疫库，并证明了个性化的，IRGs为基础的免疫签名的识别，监测和预后PTC的重要性。
Background: Papillary thyroid cancer (PTC) is the most common subtype of thyroid cancer, and inflammation relates significantly to its initiation and prognosis. Systematic exploration of the immunogenomic landscape therein to assist in PTC prognosis is therefore urgent. The Cancer Genome Atlas (TCGA) project provides a large number of genetic PTC samples that enable a comprehensive and reliable immunogenomic study.Methods: We integrated the expression profiles of immune-related genes (IRGs) and progression-free intervals (PFIs) in survival in 493 PTC patients based on the TCGA dataset. Differentially-expressed and survival-associated IRGs in PTC patients were estimated a computational difference algorithm and COX regression analysis. The potential molecular mechanisms and properties of these PTC-specific IRGs were also explored with the help of computational biology. A new prognostic index based on immune-related genes was developed by using multivariable COX analysis.Results: A total of 46 differentially expressed immune-related genes were significantly correlated with clinical outcome of PTC patients. Functional enrichment analysis revealed that these genes were actively involved in a cytokine-cytokine receptor interaction KEGG pathway. A prognostic signature based on IRGs (AGTR1, CTGF, FAM3B, IL11, IL17C, PTH2R and SPAG11A) performed moderately in prognostic predictions, and correlated with age, tumor stage, metastasis, number of lesions, and tumor burden. Intriguingly, the prognostic index based on IRGs reflected infiltration by several types of immune cells.Conclusions: Together, our results screened several IRGs of clinical significance, revealed drivers of the immune repertoire, and demonstrated the importance of a personalized, IRG-based immune signature in the recognition, surveillance, and prognosis of PTC.