The First Clinical Medical College, Lanzhou University, Lanzhou City, Gansu Province, China.
The Second Department of Gastrointestinal Surgery, Affiliated Hospital of North Sichuan Medical College, Nanchong City, Sichuan Province, China.
Comput Math Methods Med. 2021 Nov 11;2021:1205029. doi: 10.1155/2021/1205029. eCollection 2021.
Accumulating evidence proves that long noncoding RNA (lncRNA) plays a crucial role in maintaining genomic instability. However, it is significantly absent from exploring genomic instability-associated lncRNAs and discovering their clinical significance.
To identify crucial mutator-derived lncRNAs and construct a predictive model for prognosis and genomic instability in hepatocellular carcinoma.
First, we constructed a mutator hypothesis-derived calculative framework through uniting the lncRNA expression level and somatic mutation number to screen for genomic instability-associated lncRNA in hepatocellular carcinoma. We then selected mutator-derived lncRNA from the genome instability-associated lncRNA by univariate Cox analysis and Lasso regression analysis. Next, we created a prognosis model with the mutator-derived lncRNA signature. Furthermore, we verified the vital role of the model in the prognosis and genomic instability of hepatocellular carcinoma patients. Finally, we examined the potential relationship between the model and the mutation status of TP53.
In this study, we screened 88 genome instability-associated lncRNAs and built a prognosis model with four mutator-derived lncRNAs. Moreover, the model was an independent predictor of prognosis and an accurate indicator of genomic instability in hepatocellular carcinoma. Finally, the model could catch the TP53 mutation status, and the model was a more effective indicator than the mutation status of TP53 for hepatocellular carcinoma patients.
This research adopted a reliable method to analyze the role of lncRNA in genomic instability. Besides, the prognostic model with four mutator-derived lncRNAs is an excellent new indicator of prognosis and genomic instability in hepatocellular carcinoma. In addition, this finding may help clinicians develop therapeutic systems.
越来越多的证据表明，长链非编码 RNA（lncRNA）在维持基因组不稳定性方面发挥着关键作用。然而，在探索与基因组不稳定性相关的 lncRNA 及其临床意义方面，这方面的研究还明显缺失。
鉴定关键突变衍生的 lncRNA，并构建预测模型，以评估肝细胞癌的预后和基因组不稳定性。
首先，我们通过整合 lncRNA 表达水平和体细胞突变数量，构建了一个突变衍生的计算框架，以筛选肝细胞癌中与基因组不稳定性相关的 lncRNA。然后，我们通过单因素 Cox 分析和 Lasso 回归分析从与基因组不稳定性相关的 lncRNA 中选择突变衍生的 lncRNA。接下来，我们利用突变衍生的 lncRNA 特征构建了一个预后模型。此外，我们验证了该模型在肝细胞癌患者预后和基因组不稳定性中的重要作用。最后，我们检验了该模型与 TP53 突变状态之间的潜在关系。
在本研究中，我们筛选出 88 个与基因组不稳定性相关的 lncRNA，并构建了一个包含四个突变衍生的 lncRNA 的预后模型。此外，该模型是肝细胞癌预后的独立预测因子，也是基因组不稳定性的准确指标。最后，该模型可以捕捉到 TP53 的突变状态，而且作为肝细胞癌患者的指标，该模型比 TP53 突变状态更有效。
本研究采用了一种可靠的方法来分析 lncRNA 在基因组不稳定性中的作用。此外，包含四个突变衍生的 lncRNA 的预后模型是评估肝细胞癌预后和基因组不稳定性的一个优秀的新指标。此外，这一发现可能有助于临床医生开发治疗系统。
