Yu Jiaao, Lan Liqiang, Liu Caixin, Zhu Xiao
Clinical Laboratory, The First Affiliated Hospital of Wannan Medical College, Wuhu, China.
Computational Systems Biology Lab (CSBL), Institute of Bioinformatics, The Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, China.
J Cancer Res Clin Oncol. 2023 Nov;149(14):12737-12754. doi: 10.1007/s00432-023-05118-x. Epub 2023 Jul 15.
DNA-directed RNA polymerase (DDRP) related genes and long non-coding RNAs (lncRNAs) play an important role in the development of lung adenocarcinoma (LUAD), the leading cause of cancer-related death worldwide. Therefore, we aimed to construct a DDRP-associated lncRNA model to predict the prognosis of LUAD and to evaluate its sensitivity to immunotherapy and chemotherapy.
To construct a predictive signature, we used univariate and multivariate Cox regression analyses, as well as the least absolute shrinkage and selection operator regression analysis. The prognostic model was verified by applying the ROC curve analysis, Kaplan-Meier analysis, GO/KEGG analysis, and a predictive nomogram. Eventually, immunotherapy and drug susceptibility were examined and stemness indices were analyzed.
24 DDRP-associated lncRNAs were found as independent prognosis factors, which may be further developed as potential therapeutic vaccines for LUAD. The area under the ROC curve and the conformance index showed that the constructed model can predict the prognosis of LUAD patients. The predicted incidences of overall survival showed perfect conformance. And there were significant changes in immunological markers between the two risk subgroups in the model. Finally, an analysis of 50% maximum inhibitory concentration between the two risk subgroups showed that the high-risk subgroup was more sensitive to certain chemotherapy drugs.
We constructed a model that accurately predicts the outcomes of LUAD based on 24 DDRP-related lncRNAs and provided promising treatment options for the future.
DNA 指导的 RNA 聚合酶（DDRP）相关基因和长链非编码 RNA（lncRNA）在肺腺癌（LUAD）的发生发展中起重要作用，肺腺癌是全球癌症相关死亡的主要原因。因此，我们旨在构建一个与 DDRP 相关的 lncRNA 模型来预测 LUAD 的预后，并评估其对免疫治疗和化疗的敏感性。
为构建预测特征，我们使用了单变量和多变量 Cox 回归分析以及最小绝对收缩和选择算子回归分析。通过应用 ROC 曲线分析、Kaplan-Meier 分析、GO/KEGG 分析和预测列线图对预后模型进行验证。最终，检测免疫治疗和药物敏感性并分析干性指数。
发现 24 个与 DDRP 相关的 lncRNA 作为独立预后因素，它们可能进一步开发为 LUAD 的潜在治疗性疫苗。ROC 曲线下面积和一致性指数表明构建的模型可以预测 LUAD 患者的预后。预测的总生存发生率显示出完美的一致性。并且模型中两个风险亚组之间的免疫标志物有显著变化。最后，对两个风险亚组之间的 50%最大抑制浓度分析表明，高危亚组对某些化疗药物更敏感。
我们构建了一个基于 24 个与 DDRP 相关的 lncRNA 准确预测 LUAD 预后的模型，并为未来提供了有前景的治疗选择。
