Identification of a Nine Immune-Related lncRNA Signature as a Novel Diagnostic Biomarker for Hepatocellular Carcinoma.
Identification of a Nine Immune-Related lncRNA Signature as a Novel Diagnostic Biomarker for Hepatocellular Carcinoma.
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DOI：
10.1155/2021/9798231
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发表时间：
2021
影响因子：
--
通讯作者：
Cheng Y
中科院分区：
文献类型：
--
作者：
Yuan M;Wang Y;Sun Q;Liu S;Xian S;Dai F;Zhang L;Fan Y;Wang F;Yang D;Zheng Y;Deng Z;Tan W;Liu Y;Cheng Y
肝细胞癌（HCC）在常见癌症中排名第五，是全球癌症相关死亡的第二大常见原因。本研究旨在鉴定免疫相关的长非编码RNA（lncRNA）特征作为具有预后价值的潜在生物标志物，以改善HCC患者的早期诊断并提供潜在的治疗靶点。本研究的受试者是具有完整转录组数据和从癌症基因组图谱（TCGA）数据库下载的临床信息的HCC样本。然后提取免疫相关的mRNA和lncRNA表达谱。基于免疫相关lncRNA的表达谱，我们确定了与HCC进展相关的9个lncRNA标记。根据每个样本的9种lncRNA的表达水平计算风险评分，将患者分为高风险组和低风险组。我们发现，增加的风险评分与肝癌患者预后不良有关。为了评估生存模型的准确性，我们计算了受试者工作特征（ROC）进行验证。曲线显示风险评分的曲线下面积（AUC）为0.792。此外，主成分分析（PCA）和基因集富集分析（GSEA）被进一步用于功能注释。我们发现PCA中低危组和高危组之间的分布模式不同，并且9种lncRNA促进HCC进展的潜在机制涉及异常的免疫状态。最后，利用ssGSEA算法分析了29种免疫细胞在HCC中的浸润和免疫功能的激活情况。结果表明，aDC、iDC、巨噬细胞、Tfh、Th 1、Treg和NK细胞与HCC患者的病情进展相关。高危组与低危组的免疫功能包括APC共刺激、CCR、检查点、HLA、MHC I类分子和II型干扰素反应也有显著性差异。总之，我们的研究确定了一个具有潜在预后价值的HCC患者的9-lncRNA签名，它可以用作HCC诊断和免疫治疗的新生物标志物。
Hepatocellular carcinoma (HCC) ranks fifth among common cancers and is the second most common cause of cancer-related mortality worldwide. This study is aimed at identifying an immune-related long noncoding RNA (lncRNA) signature as a potential biomarker with prognostic value to improve early diagnosis and provide potential therapeutic targets for HCC patients. The subjects of this study were HCC samples with complete transcriptome data and clinical information downloaded from The Cancer Genome Atlas (TCGA) database. We then extracted the immune-related mRNA and lncRNA expression profiles. Based on the expression profiles of immune-related lncRNAs, we identified a nine-lncRNA signature that was related to the progression of HCC. The risk score was calculated based on the expression level of the nine lncRNAs of each sample, which divided patients into high-risk and low-risk groups. We found that the increased risk score was associated with a poor prognosis of HCC patients. To assess the accuracy of the survival model, we calculated a receiver operating characteristic (ROC) for validation. The curve showed that the area under the curve (AUC) for the risk score was 0.792. Besides, both principal component analysis (PCA) and gene set enrichment analysis (GSEA) were further used for functional annotation. We found that the distribution patterns were different between the low-risk and high-risk groups in PCA, and the underlying mechanism by which the nine lncRNAs promoted the progression of HCC involved an abnormal immune status. Finally, we analyzed the infiltration of twenty-nine kinds of immune cells and the activation of immune function in HCC using the ssGSEA algorithm. The results showed that aDCs, iDCs, macrophages, Tfh, Th1, Treg, and NK cells were correlated with the progress of HCC patients. And the immune functions including APC costimulation, CCR, check point, HLA, MHC class I, and Type II IFN responses were also significantly different between the high-risk and low-risk groups. In conclusion, our study identified a nine-lncRNA signature with potential prognostic value for patients with HCC, which could be used as a new biomarker for the diagnosis and immunotherapy of HCC.
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