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Development of a prognostic index based on an immunogenomic landscape analysis of papillary thyroid cancer

机译:基于甲状腺乳头状癌免疫基因组学分析的预后指标的发展

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摘要

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 RGs (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.
机译:背景:乳头状甲状腺癌(PTC)是甲状腺癌最常见的亚型,炎症与它的发生和预后密切相关。因此,迫切需要对其中的免疫基因组环境进行系统的探索,以帮助PTC预后。癌症基因组图谱(TCGA)项目提供了大量的基因PTC样本,可以进行全面而可靠的免疫基因组学研究。方法:我们整合了免疫相关基因(IRG)和无进展间隔(PFI)的生存表达基于TCGA数据集的493位PTC患者中。通过计算差异算法和COX回归分析估计了PTC患者中差异表达的IRG和与生存相关的IRG。在计算生物学的帮助下,还探索了这些PTC特异性IRG的潜在分子机制和特性。通过多变量COX分析,建立了基于免疫相关基因的新的预后指标。结果:共有46个差异表达的免疫相关基因与PTC患者的临床预后显着相关。功能富集分析表明,这些基因积极参与细胞因子-细胞因子受体相互作用的KEGG通路。基于RGs(AGTR1,CTGF,FAM3B,IL11,IL17C,PTH2R和SPAG11A)的预后标记在预后预测中表现中等,并且与年龄,肿瘤分期,转移,病变数目和肿瘤负荷相关。有趣的是,基于IRG的预后指标反映了几种类型的免疫细胞的浸润。结论:我们的结果共同筛选了具有临床意义的几种IRG,揭示了免疫库的驱动因素,并证明了基于IRG的个性化免疫特征的重要性在PTC的识别,监视和预后方面。

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