Department of Liver Transplantation and Hepatobiliary Surgery, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250021, Shandong Province, China.
Department of Liver Transplantation and Hepatobiliary Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong Province, China.
J Cancer Res Clin Oncol. 2022 Jul;148(7):1613-1626. doi: 10.1007/s00432-022-03985-4. Epub 2022 Mar 21.
Pancreatic cancer (PC) is a rare solid malignancy with a poor prognosis. N6-methyladenosine (m6A) and long noncoding RNAs (lncRNAs) play essential roles in tumorigenesis and progression. However, little is known about the role of m6A-related lncRNAs in PC.
m6A-related lncRNAs were extracted by Pearson analysis, and then prognosis-related lncRNAs were filtered from the m6A-related lncRNAs by univariate Cox regression analysis. Based on the expression patterns of the prognosis-related lncRNAs, samples were classified into distinct clusters. Least absolute shrinkage and selection operator (LASSO) Cox regression was used to construct a m6A-lncRNA-related prognostic signature for PC patients. Receiver operating characteristic (ROC) curves and the corresponding area under the curve (AUC) values were used to evaluate the prognostic ability of the model.
A total of 178 tumor and 4 normal samples were extracted from The Cancer Genome Atlas (TCGA) database in our study. Based on the expression of 12 filtered prognosis-related lncRNAs, two distinct clusters were eventually identified; these clusters were characterized by differences in the tumor immune microenvironment (TIME) and prognosis. A risk model comprising ten m6A-related lncRNAs was identified as an independent predictor of prognosis. ROC analysis revealed that this model had an acceptable prognostic value for PC patients. The prognostic signature was related to the TIME and the expression of critical immune checkpoint molecules.
This study comprehensively assessed the expression pattern and prognostic value of m6A-related lncRNAs in PC. The different clusters correlated with distinct TIMEs and prognoses. The study also constructed a ten-gene signature prognostic model based on m6A-related lncRNAs, which showed good accuracy in predicting overall survival.
胰腺癌（PC）是一种罕见的实体恶性肿瘤，预后不良。N6-甲基腺苷（m6A）和长非编码 RNA（lncRNA）在肿瘤发生和进展中发挥着重要作用。然而，关于 m6A 相关 lncRNA 在 PC 中的作用知之甚少。
通过 Pearson 分析提取 m6A 相关 lncRNA，然后通过单变量 Cox 回归分析从 m6A 相关 lncRNA 中筛选预后相关 lncRNA。根据预后相关 lncRNA 的表达模式，将样本分为不同的聚类。最小绝对收缩和选择算子（LASSO）Cox 回归用于构建 PC 患者的 m6A-lncRNA 相关预后特征。接收器操作特征（ROC）曲线和相应的曲线下面积（AUC）值用于评估模型的预后能力。
本研究共从癌症基因组图谱（TCGA）数据库中提取了 178 个肿瘤和 4 个正常样本。基于 12 个筛选出的预后相关 lncRNA 的表达，最终确定了两个不同的聚类；这些聚类的特点是肿瘤免疫微环境（TIME）和预后的差异。确定了一个包含十个 m6A 相关 lncRNA 的风险模型，作为预后的独立预测因子。ROC 分析表明，该模型对 PC 患者具有可接受的预后价值。该预后特征与 TIME 和关键免疫检查点分子的表达有关。
本研究全面评估了 m6A 相关 lncRNA 在 PC 中的表达模式和预后价值。不同的聚类与不同的 TIME 和预后相关。该研究还构建了一个基于 m6A 相关 lncRNA 的十个基因特征预后模型，该模型在预测总生存率方面具有良好的准确性。
