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A signature of 18 immune‐related gene pairs to predict the prognosis of pancreatic cancer patients
Immunity, Inflammation and Disease ( IF 3.1 ) Pub Date : 2020-10-31 , DOI: 10.1002/iid3.363 Fanqin Bu 1 , Han Nie 2 , Xiaojian Zhu 3 , Ting Wu 4 , Kang Lin 1 , Jiefeng Zhao 1 , Jun Huang 1
Immunity, Inflammation and Disease ( IF 3.1 ) Pub Date : 2020-10-31 , DOI: 10.1002/iid3.363 Fanqin Bu 1 , Han Nie 2 , Xiaojian Zhu 3 , Ting Wu 4 , Kang Lin 1 , Jiefeng Zhao 1 , Jun Huang 1
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Pancreatic cancer is one of the most lethal malignancies. With the promising prospects conveyed by immunotherapy in cancers, we aimed to construct an immune‐related gene pairs (IRGPs) signature to predict the prognosis of pancreatic cancer patients. We downloaded clinical and transcriptional data of pancreatic cancer patients from The Cancer Genome Atlas data set as the training group and GSE57495 data set as the verification group. We filtered immune‐related transcriptional data by IMMPORT. With the assistance of lasso penalized Cox regression, we constructed our prognostic IRGPs signature and divided all samples into high‐/low‐risk groups by receiver operating characteristic curve for further comparisons. The comparisons between high‐ and low‐risk groups including survival rate, multivariate, and univariate Cox proportional‐hazards analysis, infiltration of immune cells, and Gene Set Enrichment Analysis (GSEA). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) are facilitated to analyze the proceedings in which our IRGPs signature may involve in. The results revealed that 18 IRGPs were defined as our prognostic signature. The prognostic value of this IRGPs signature was verified from the GSE57495 data set. We further demonstrated the independent prognostic value of this IRGPs signature. The contents of six immune cells between high‐/low‐risk groups were different, which was associated with the progression of diverse cancers. Results from GO, KEGG, and GSEA revealed that this IRGPs signature was involved in extracellular space, immune response, cancer pathways, cation channel, and gated channel activities. Evidently, this IRGPs signature will provide remarkable value for the therapy of pancreatic cancer patients.
中文翻译：
18个免疫相关基因对的特征预测胰腺癌患者的预后
胰腺癌是最致命的恶性肿瘤之一。随着癌症免疫疗法的前景广阔，我们旨在构建免疫相关基因对（IRGPs）特征来预测胰腺癌患者的预后。我们从 The Cancer Genome Atlas 数据集下载胰腺癌患者的临床和转录数据作为训练组，GSE57495 数据集作为验证组。我们通过 IMMPORT 过滤了免疫相关的转录数据。在套索惩罚 Cox 回归的帮助下，我们构建了我们的预后 IRGP 特征，并通过接收者操作特征曲线将所有样本分为高/低风险组以进行进一步比较。高风险和低风险组之间的比较，包括生存率、多变量和单变量 Cox 比例风险分析，免疫细胞浸润和基因集富集分析 (GSEA)。Gene Ontology (GO)、Kyoto Encyclopedia of Genes and Genomes (KEGG) 有助于分析我们的 IRGP 签名可能涉及的程序。结果显示 18 个 IRGP 被定义为我们的预后签名。从 GSE57495 数据集验证了该 IRGP 签名的预后价值。我们进一步证明了该 IRGP 签名的独立预后价值。高/低风险组之间6种免疫细胞的含量不同，这与多种癌症的进展有关。GO、KEGG 和 GSEA 的结果表明，这种 IRGPs 特征涉及细胞外空间、免疫反应、癌症途径、阳离子通道和门控通道活动。显然，
更新日期：2020-11-12
中文翻译：
18个免疫相关基因对的特征预测胰腺癌患者的预后
胰腺癌是最致命的恶性肿瘤之一。随着癌症免疫疗法的前景广阔，我们旨在构建免疫相关基因对（IRGPs）特征来预测胰腺癌患者的预后。我们从 The Cancer Genome Atlas 数据集下载胰腺癌患者的临床和转录数据作为训练组，GSE57495 数据集作为验证组。我们通过 IMMPORT 过滤了免疫相关的转录数据。在套索惩罚 Cox 回归的帮助下，我们构建了我们的预后 IRGP 特征，并通过接收者操作特征曲线将所有样本分为高/低风险组以进行进一步比较。高风险和低风险组之间的比较，包括生存率、多变量和单变量 Cox 比例风险分析，免疫细胞浸润和基因集富集分析 (GSEA)。Gene Ontology (GO)、Kyoto Encyclopedia of Genes and Genomes (KEGG) 有助于分析我们的 IRGP 签名可能涉及的程序。结果显示 18 个 IRGP 被定义为我们的预后签名。从 GSE57495 数据集验证了该 IRGP 签名的预后价值。我们进一步证明了该 IRGP 签名的独立预后价值。高/低风险组之间6种免疫细胞的含量不同，这与多种癌症的进展有关。GO、KEGG 和 GSEA 的结果表明，这种 IRGPs 特征涉及细胞外空间、免疫反应、癌症途径、阳离子通道和门控通道活动。显然，
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