Xu Guangyu, Ji Yutian, Wang Lufeng, Xu Hao, Shen Chaodong, Ye Haihao, Yang Xiangchou
Department of Hematology and Medical Oncology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325000, China.
Zhejiang University School of Medicine, Hangzhou 310030, China.
Vaccines (Basel). 2023 Feb 21;11(3):499. doi: 10.3390/vaccines11030499.
N6-methyladenosine (m6A) lncRNA plays a pivotal role in cancer. However, little is known about its role in pancreatic ductal adenocarcinoma (PDAC) and its tumor immune microenvironment (TIME). Based on The Cancer Genome Atlas (TCGA) cohort, m6A-related lncRNAs (m6A-lncRNA) with prognostic value were filtered using Pearson analysis and univariate Cox regression analysis. Distinct m6A-lncRNA subtypes were divided using unsupervised consensus clustering. Least absolute shrinkage and selection operator (LASSO) Cox regression was applied to establish an m6A-lncRNA-based risk score signature. The CIBERSORT and ESTIMATE algorithms were employed to analyze the TIME. The expression pattern of TRAF3IP2-AS1 was examined using qRT-PCR. The influence of TRAF3IP2-AS1 knockdown on cell proliferation was estimated by performing CCK8, EdU and colony-formation assays. Flow cytometry was applied to measure the effect of TRAF3IP2-AS1 knockdown on cell cycle and apoptosis. The in vivo anti-tumor effect of TRAF3IP2-AS1 was validated in a tumor-bearing mouse model. Two m6A-lncRNA subtypes with different TIME features were clarified. A risk score signature was constructed as a prognostic predictor based on m6A-lncRNAs. The risk score also correlated with TIME characterization, which facilitated immunotherapy. Finally, the m6A-lncRNA TRAF3IP2-AS1 was proved to be a tumor suppressor in PDAC. We comprehensively demonstrated m6A-lncRNAs to be useful tools for prognosis prediction, TIME depiction and immunotherapeutic guidance in PDAC.
N6-甲基腺嘌呤（m6A）长链非编码RNA（lncRNA）在癌症中起着关键作用。然而，其在胰腺导管腺癌（PDAC）及其肿瘤免疫微环境（TIME）中的作用却鲜为人知。基于癌症基因组图谱（TCGA）队列，通过Pearson分析和单因素Cox回归分析筛选出具有预后价值的m6A相关lncRNAs（m6A-lncRNA）。使用无监督一致性聚类划分不同的m6A-lncRNA亚型。应用最小绝对收缩和选择算子（LASSO）Cox回归建立基于m6A-lncRNA的风险评分特征。采用CIBERSORT和ESTIMATE算法分析TIME。使用qRT-PCR检测TRAF3IP2-AS1的表达模式。通过进行CCK8、EdU和集落形成试验评估TRAF3IP2-AS1敲低对细胞增殖的影响。应用流式细胞术测量TRAF3IP2-AS1敲低对细胞周期和凋亡的影响。在荷瘤小鼠模型中验证TRAF3IP2-AS1的体内抗肿瘤作用。阐明了具有不同TIME特征的两种m6A-lncRNA亚型。构建了基于m6A-lncRNAs的风险评分特征作为预后预测指标。风险评分还与TIME特征相关，这有助于免疫治疗。最后，证明m6A-lncRNA TRAF3IP2-AS1在PDAC中是一种肿瘤抑制因子。我们全面证明了m6A-lncRNAs是PDAC预后预测、TIME描绘和免疫治疗指导的有用工具。
