Computational Identification of Immune- and Ferroptosis-Related LncRNA Signature for Prognosis of Hepatocellular Carcinoma.
Computational Identification of Immune- and Ferroptosis-Related LncRNA Signature for Prognosis of Hepatocellular Carcinoma.
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DOI：
10.3389/fmolb.2021.759173
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发表时间：
2021
影响因子：
5
通讯作者：
Xia J
中科院分区：
文献类型：
--
作者：
Huang A;Li T;Xie X;Xia J
长链非编码RNA（lncRNA）在肝细胞癌（HCC）中表达异常，与肿瘤等多种病理生理过程密切相关。研究表明，铁凋亡和免疫可以调节肿瘤的生物学行为。因此，结合铁凋亡、免疫和lncRNA的生物标志物可能是癌症临床治疗中有希望的候选生物指示剂。采用Pearson相关分析、单变量考克斯比例风险回归分析、最小绝对收缩和选择算子（LASSO）分析、多变量考克斯比例风险回归分析等多种生物信息学方法，建立免疫和铁结合相关lncRNA（IFLSig）的预后风险特征。最后，八个免疫和铁凋亡相关的lncRNA（IFLncRNA）被确定为发展和肝癌患者的IFLSig。IFLSig高者预后差，IFLSig低者预后好。这些结果提供了一种有效的方法，将关键的临床信息与免疫学特征结合起来，从而能够估计总生存期（OS）。这种具有高预测能力的综合预后模型将在预后预测和个体化治疗策略中具有显着的影响和实用性。
Long non-coding RNAs (lncRNAs), which were implicated in many pathophysiological processes including cancer, were frequently dysregulated in hepatocellular carcinoma (HCC). Studies have demonstrated that ferroptosis and immunity can regulate the biological behaviors of tumors. Therefore, biomarkers that combined ferroptosis, immunity, and lncRNA can be a promising candidate bioindicator in clinical therapy of cancers. Many bioinformatics methods, including Pearson correlation analysis, univariate Cox proportional hazard regression analysis, least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox proportional hazard regression analysis were applied to develop a prognostic risk signature of immune- and ferroptosis-related lncRNA (IFLSig). Finally, eight immune- and ferroptosis-related lncRNAs (IFLncRNA) were identified to develop and IFLSig of HCC patients. We found the prognosis of patients with high IFLSig will be worse, while the prognosis of patients with low IFLSig will be better. The results provide an efficient method of uniting critical clinical information with immunological characteristics, enabling estimation of the overall survival (OS). Such an integrative prognostic model with high predictive power would have a notable impact and utility in prognosis prediction and individualized treatment strategies.
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影响因子：
16.6
作者：
Wang G;Xie L;Li B;Sang W;Yan J;Li J;Tian H;Li W;Zhang Z;Tian Y;Dai Y
通讯作者：
Dai Y
DOI：
10.1038/s41577-019-0218-4
发表时间：
2020-01
期刊：
Nature reviews. Immunology
影响因子：
--
作者：
Kalbasi A;Ribas A
通讯作者：
Ribas A
影响因子：
46.9
作者：
通讯作者：
--
影响因子：
16.2
作者：
Feng, Rui-Mei;Zong, Yi-Nan;Xu, Rui-Hua
通讯作者：
Xu, Rui-Hua
长非编码RNA LUCAT1通过抑制肝细胞癌中ANXA2磷酸化促进肿瘤发生
影响因子：
5.3
作者：
Lou, Yun;Yu, Yue;Li, Guoqiang
通讯作者：
Li, Guoqiang