Fan Yongfei, Zhou Yong, Lou Ming, Li Xinwei, Zhu Xudong, Yuan Kai
Department of Thoracic Surgery, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, People's Republic of China.
Department of Gastroenterology, Affiliated Cancer Hospital of Bengbu Medical College, Bengbu, People's Republic of China.
J Inflamm Res. 2022 Mar 23;15:1969-1989. doi: 10.2147/JIR.S356841. eCollection 2022.
The role of RNA N6-methyladenosine (mA) modification in the progression of multiple tumours and the tumour microenvironment (TME) has been progressively demonstrated and promises a new direction for tumour therapy. However, there have been no reports on systematic analyses of RNA mA modification in TME in non-small cell lung cancer (NSCLC).
In this study, we used unsupervised cluster analysis to identify three mA modification patterns of 28 mA regulators and three mA gene signature subgroups of commonly differentially expressed genes (co-DEGs) in the three mA modification patterns. Quantifying these subtypes using the ssGSEA and ESTIMATE algorithms to characterise the tumour immune microenvironment (TIME) in NSCLC. Based on the principal component analysis (PCA), we used co-DEGs to construct mA scores to analyse the characteristics of mA modifications in individual patients and assessed the practical clinical utility of mA scores using a nomogram for survival prediction.
A total of 28 mA regulators in 1210 NSCLC samples were mainly enriched in RNA modification and metabolic biological processes. The three following mA modification patterns were identified based on the role of the 28 mA regulators in TME: immune inflammation, immune evasion and immune desert. The mA scores calculated based on co-DEGs in these modification patterns were significantly positively correlated with immune infiltration and significantly negatively correlated with tumour mutational burden (TMB). Survival was significantly better in the high-mA-score group than in the low-mA-score group, and the mA score could be used as an independent favourable prognostic factor. In addition, assessment of both immune checkpoint inhibitors (ICIs) and immunophenoscore (IPS) revealed a better immunotherapeutic effect in the high-mA-score group.
The modification characteristics of 28 mA regulators in the TIME of NSCLC were analysed from a comprehensive to an individual basis, which may facilitate the development of more effective clinical immunotherapeutic strategies.
RNA N6-甲基腺嘌呤（m⁶A）修饰在多种肿瘤进展及肿瘤微环境（TME）中的作用已逐步得到证实，并为肿瘤治疗提供了新方向。然而，关于非小细胞肺癌（NSCLC）肿瘤微环境中RNA m⁶A修饰的系统分析尚无报道。
在本研究中，我们采用无监督聚类分析来识别28个m⁶A调节因子的三种m⁶A修饰模式，以及这三种m⁶A修饰模式中常见差异表达基因（共DEG）的三个m⁶A基因特征亚组。使用单样本基因集富集分析（ssGSEA）和ESTIMATE算法对这些亚型进行量化，以表征NSCLC中的肿瘤免疫微环境（TIME）。基于主成分分析（PCA），我们使用共DEG构建m⁶A评分，以分析个体患者中m⁶A修饰的特征，并使用列线图进行生存预测来评估m⁶A评分的实际临床效用。
1210例NSCLC样本中的28个m⁶A调节因子主要富集于RNA修饰和代谢生物学过程。基于这28个m⁶A调节因子在肿瘤微环境中的作用，确定了以下三种m⁶A修饰模式：免疫炎症、免疫逃逸和免疫荒漠。基于这些修饰模式中共DEG计算出的m⁶A评分与免疫浸润显著正相关，与肿瘤突变负荷（TMB）显著负相关。高m⁶A评分组的生存率显著高于低m⁶A评分组，且m⁶A评分可作为独立的有利预后因素。此外，对免疫检查点抑制剂（ICI）和免疫表型评分（IPS）的评估均显示，高m⁶A评分组的免疫治疗效果更好。
从整体到个体分析了NSCLC肿瘤免疫微环境中28个m⁶A调节因子 的修饰特征，这可能有助于制定更有效的临床免疫治疗策略。
