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Abstract：
BACKGROUND: We aimed to comprehensively analyze the clinical value of immune-related eRNAs-driven genes in lung adenocarcinoma (LUAD) and find the potential biomarkers for prognosis and therapeutic response to improve the survival of this malignant disease.
METHODS: Pearson\'s correlation analysis was performed to identify the immune-related eRNAs-driven genes. Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were used to construct this prognostic risk signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to investigate the underlying molecular mechanism. The single sample gene set enrichment analysis (ssGSEA) algorithm was conducted to evaluate the immune status based on the signature. The quantitative real-time PCR (qRT-PCR) analysis was performed to evaluate the expression value of the signature genes between LUAD tissues and adjacent lung tissues.
RESULTS: Five immune-related eRNAs-driven genes (SHC1, GDF10, CCL14, FYN, and NOD1) were identified to construct a prognostic risk signature with favorable predictive capacity. The patients with high-risk scores based on the signature were significantly associated with the malignant clinical features compared with those with low-risk scores. Kaplan-Meier analysis demonstrated that the sample in the low-risk group had a prolonged survival compared with those in the high-risk group. This risk signature was validated to have a promising predictive capacity and reliability in diverse clinical situations and independent cohorts. The functional enrichment analysis demonstrated that humoral immune response and intestinal immune network for IgA production pathway might be the underlying molecular mechanism related to the signature. The proportion of the vast majority of immune infiltrating cells in the high-risk group was significantly lower than that in the low-risk group, and the immunotherapy response rate in the low-risk group was significantly higher than that in the high-risk group. Moreover, BI-2536, sepantronium bromide, and ULK1 were the potential drugs for the treatment of patients with higher risk scores. Finally, the experiment in vivo and database analysis indicated that CCL14, FYN, NOD1, and GDF10 are the potential LUAD suppressor and SHC1 is a potential treatment target for LUAD.
CONCLUSIONS: Above all, we constructed a prognostic risk signature with favorable predictive capacity in LUAD, which was significantly associated with malignant features, immunosuppressive tumor microenvironment, and immunotherapy response and may provide clinical benefit in clinical decisions.
METHODS: Pearson\'s correlation analysis was performed to identify the immune-related eRNAs-driven genes. Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were used to construct this prognostic risk signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to investigate the underlying molecular mechanism. The single sample gene set enrichment analysis (ssGSEA) algorithm was conducted to evaluate the immune status based on the signature. The quantitative real-time PCR (qRT-PCR) analysis was performed to evaluate the expression value of the signature genes between LUAD tissues and adjacent lung tissues.
RESULTS: Five immune-related eRNAs-driven genes (SHC1, GDF10, CCL14, FYN, and NOD1) were identified to construct a prognostic risk signature with favorable predictive capacity. The patients with high-risk scores based on the signature were significantly associated with the malignant clinical features compared with those with low-risk scores. Kaplan-Meier analysis demonstrated that the sample in the low-risk group had a prolonged survival compared with those in the high-risk group. This risk signature was validated to have a promising predictive capacity and reliability in diverse clinical situations and independent cohorts. The functional enrichment analysis demonstrated that humoral immune response and intestinal immune network for IgA production pathway might be the underlying molecular mechanism related to the signature. The proportion of the vast majority of immune infiltrating cells in the high-risk group was significantly lower than that in the low-risk group, and the immunotherapy response rate in the low-risk group was significantly higher than that in the high-risk group. Moreover, BI-2536, sepantronium bromide, and ULK1 were the potential drugs for the treatment of patients with higher risk scores. Finally, the experiment in vivo and database analysis indicated that CCL14, FYN, NOD1, and GDF10 are the potential LUAD suppressor and SHC1 is a potential treatment target for LUAD.
CONCLUSIONS: Above all, we constructed a prognostic risk signature with favorable predictive capacity in LUAD, which was significantly associated with malignant features, immunosuppressive tumor microenvironment, and immunotherapy response and may provide clinical benefit in clinical decisions.
摘要：
背景：我们旨在全面分析免疫相关eRNAs驱动基因在肺腺癌（LUAD）中的临床价值，并寻找潜在的预后和治疗反应的生物标志物，以改善这种恶性疾病的生存率。
方法：进行Pearson的相关性分析以鉴定免疫相关的eRNA驱动基因。Cox回归和最小绝对收缩和选择算子（LASSO）分析用于构建该预后风险特征。使用基因本体论（GO）和京都基因和基因组百科全书（KEGG）途径分析来研究潜在的分子机制。进行单样品基因集富集分析(ssGSEA)算法以基于签名评估免疫状态。进行定量实时PCR(qRT-PCR)分析以评估LUAD组织和邻近肺组织之间的标记基因的表达值。
结果：五个免疫相关的eRNAs驱动基因（SHC1，GDF10，CCL14，FYN，和NOD1）被鉴定为构建具有良好预测能力的预后风险特征。与具有低风险评分的患者相比，具有基于特征的高风险评分的患者与恶性临床特征显着相关。Kaplan-Meier分析表明，与高风险组相比，低风险组的样本具有延长的生存期。该风险特征被验证为在不同临床情况和独立队列中具有有希望的预测能力和可靠性。功能富集分析表明，IgA产生途径的体液免疫反应和肠道免疫网络可能是与该特征相关的潜在分子机制。高危组绝大多数免疫浸润细胞的比例明显低于低危组,低危组的免疫治疗反应率明显高于高危组。此外，BI-2536,去甲溴铵,ULK1是治疗风险评分较高的患者的潜在药物.最后,体内实验和数据库分析表明，CCL14、FYN、NOD1和GDF10是潜在的LUAD抑制剂，SHC1是LUAD的潜在治疗靶标。
结论：最重要的是，我们在LUAD中构建了具有良好预测能力的预后风险标志，这与恶性特征显著相关，免疫抑制肿瘤微环境，和免疫治疗反应，并可能在临床决策中提供临床益处。
方法：进行Pearson的相关性分析以鉴定免疫相关的eRNA驱动基因。Cox回归和最小绝对收缩和选择算子（LASSO）分析用于构建该预后风险特征。使用基因本体论（GO）和京都基因和基因组百科全书（KEGG）途径分析来研究潜在的分子机制。进行单样品基因集富集分析(ssGSEA)算法以基于签名评估免疫状态。进行定量实时PCR(qRT-PCR)分析以评估LUAD组织和邻近肺组织之间的标记基因的表达值。
结果：五个免疫相关的eRNAs驱动基因（SHC1，GDF10，CCL14，FYN，和NOD1）被鉴定为构建具有良好预测能力的预后风险特征。与具有低风险评分的患者相比，具有基于特征的高风险评分的患者与恶性临床特征显着相关。Kaplan-Meier分析表明，与高风险组相比，低风险组的样本具有延长的生存期。该风险特征被验证为在不同临床情况和独立队列中具有有希望的预测能力和可靠性。功能富集分析表明，IgA产生途径的体液免疫反应和肠道免疫网络可能是与该特征相关的潜在分子机制。高危组绝大多数免疫浸润细胞的比例明显低于低危组,低危组的免疫治疗反应率明显高于高危组。此外，BI-2536,去甲溴铵,ULK1是治疗风险评分较高的患者的潜在药物.最后,体内实验和数据库分析表明，CCL14、FYN、NOD1和GDF10是潜在的LUAD抑制剂，SHC1是LUAD的潜在治疗靶标。
结论：最重要的是，我们在LUAD中构建了具有良好预测能力的预后风险标志，这与恶性特征显著相关，免疫抑制肿瘤微环境，和免疫治疗反应，并可能在临床决策中提供临床益处。
