肝细胞癌中竞争性内源性RNA（ceRNA）网络与肿瘤浸润细胞之间关系的综合分析
Comprehensive analysis of the relationship between competitive endogenous RNA (ceRNA) networks and tumor infiltrating-cells in hepatocellular carcinoma.
作者信息
Zhu Jun, Wang Liang, Zhou Yifan, Hao Jun, Wang Shuai, Liu Lei, Li Jipeng
机构信息
State Key Laboratory of Cancer Biology, Institute of Digestive Diseases, Xijing Hospital, The Fourth Military Medical University, Xi'an, China.
Department of Ophthalmology, Eye Institute of Chinese PLA, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
出版信息
J Gastrointest Oncol. 2020 Dec;11(6):1381-1398. doi: 10.21037/jgo-20-555.
BACKGROUND
The innovation of immune checkpoint blockade (ICB) represents a promising shift in the treatment of advanced hepatocellular carcinoma (HCC). However, response to ICB has varied largely due to the high tumor heterogeneity and complex tumor microenvironment (TME). The competitive endogenous RNA (ceRNA) network also plays an important role in tumor occurrence and progression, but its relation with tumor-infiltrating immune cells (TICs) remains largely unexplored in HCC. The overriding objective of our study was thus to construct a prognosis-related risk model and to further evaluate the relationship between ceRNA networks and TICs.
METHODS
Differentially expressed gene (DEG) analysis was performed to identify the differentially expressed RNAs. Lasso and multivariable Cox regression analyses were used to construct risk models, which were assessed by the area under the receiver operating characteristic curve (AUC of ROC) and Kaplan-Meier (K-M) curves. Then, a single-sample gene set enrichment analysis (ssGSEA) algorithm was adopted to dissect the TICs in HCC samples. Nomograms were constructed and calibration curves were used to verify the discrimination and accuracy of the nomograms. Finally, integration analysis was performed to validate the correlation of ceRNA and TICs.
RESULTS
In the study, 7 differentially expressed RNAs [5 messenger RNA s (mRNAs) and 2 micro RNAs (miRNAs)] were incorporated to construct a ceRNA risk model. The AUC of the 1-, 3-, and 5-year overall survival (OS) were 0.784, 0.685, and 0.691 respectively. Likewise, 7 types TICs were in the TICs signature model and the AUC of the 1-, 3-, and 5-year OS were 0.706, 0.731, and 0.721 respectively. The integration analysis showed that 7 pairs of mRNA-TICs and 1 pair of miRNA-TICs had a close relation (all correlation coefficients >0.2, P<0.001).
CONCLUSIONS
Through constructing two risk models based on ceRNA network and TICs, we identified the hub RNAs and key TICs in the progression and prognosis of HCC, and further explored the relationship between ceRNA and TME. Importantly, targeting these hub RNAs may facilitate the remodeling of the TME and be a potential therapeutic alternative to enhancing the response to ICB, thus improving the prognosis of HCC patients.
背景
免疫检查点阻断（ICB）的创新代表了晚期肝细胞癌（HCC）治疗中一个有前景的转变。然而，由于肿瘤高度异质性和复杂的肿瘤微环境（TME），对ICB的反应差异很大。竞争性内源RNA（ceRNA）网络在肿瘤发生和进展中也起重要作用，但在HCC中其与肿瘤浸润免疫细胞（TICs）的关系仍 largely未被探索。因此，我们研究的首要目标是构建一个与预后相关的风险模型，并进一步评估ceRNA网络与TICs之间的关系。
方法
进行差异表达基因（DEG）分析以鉴定差异表达的RNA。采用Lasso和多变量Cox回归分析构建风险模型，通过受试者操作特征曲线下面积（ROC的AUC）和Kaplan-Meier（K-M）曲线进行评估。然后，采用单样本基因集富集分析（ssGSEA）算法剖析HCC样本中的TICs。构建列线图并使用校准曲线验证列线图的辨别力和准确性。最后，进行整合分析以验证ceRNA与TICs的相关性。
结果
在本研究中，纳入7个差异表达的RNA [5个信使RNA（mRNAs）和2个微小RNA（miRNAs）]构建ceRNA风险模型。1年、3年和5年总生存（OS）的AUC分别为0.784、0.685和0.691。同样，7种类型的TICs在TICs特征模型中，1年、3年和5年OS的AUC分别为0.706、0.731和0.721。整合分析显示7对mRNA-TICs和1对miRNA-TICs关系密切（所有相关系数>0.2，P<0.001）。
结论
通过基于ceRNA网络和TICs构建两个风险模型，我们在HCC的进展和预后中鉴定出枢纽RNA和关键TICs，并进一步探索了ceRNA与TME之间的关系。重要的是，靶向这些枢纽RNA可能有助于TME重塑，并且是增强对ICB反应从而改善HCC患者预后的潜在治疗选择。
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