Yang Yifei, Zhang Shiqi, Guo Li
Department of Bioinformatics, Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing, China.
Department of Biology, Brandeis University, Waltham, MA, United States.
Front Oncol. 2022 Feb 3;12:807367. doi: 10.3389/fonc.2022.807367. eCollection 2022.
Lung adenocarcinoma (LUAD), one of the most common pathological subtypes in lung cancer, has been of concern because it is the leading cause of cancer-related deaths. Due to its poor prognosis, to identify a prognostic biomarker, this study performed an integrative analysis to screen curial RNAs and discuss their cross-talks. The messenger RNA (mRNA) profiles were primarily screened using robust rank aggregation (RRA) through several datasets, and these deregulated genes showed important roles in multiple biological pathways, especially for cell cycle and oocyte meiosis. Then, 31 candidate genes were obtained integrating 12 algorithms, and 16 hub genes (containing homologous genes) were further screened according to the potential prognostic values. These hub genes were used to search their regulators and biological-related microRNAs (miRNAs). In this way, 10 miRNAs were identified as candidate small RNAs associated with LUAD, and then miRNA-related long non-coding RNAs (lncRNAs) were further obtained. In-depth analysis showed that 4 hub mRNAs, 2 miRNAs, and 2 lncRNAs were potential crucial RNAs in the occurrence and development of cancer, and a competing endogenous RNA (ceRNA) network was then constructed. Finally, we identified CCNA2/MKI67/KIF11:miR-30a-5p:VPS9D1-AS1 axis-related cell cycle as a prognostic biomarker, which provided RNA cross-talks among mRNAs and non-coding RNAs (ncRNAs), especially at the multiple isomiR levels that further complicated the coding-non-coding RNA regulatory network. Our findings provide insight into complex cross-talks among diverse RNAs particularly involved in isomiRs, which will enrich our understanding of mRNA-ncRNA interactions in coding-non-coding RNA regulatory networks and their roles in tumorigenesis.
肺腺癌（LUAD）是肺癌中最常见的病理亚型之一，因其是癌症相关死亡的主要原因而备受关注。由于其预后较差，为了确定一种预后生物标志物，本研究进行了综合分析以筛选关键RNA并探讨它们之间的相互作用。通过稳健秩聚合（RRA）方法，利用多个数据集初步筛选信使RNA（mRNA）谱，这些失调基因在多个生物学途径中发挥重要作用，尤其是在细胞周期和卵母细胞减数分裂方面。然后，整合12种算法获得31个候选基因，并根据潜在预后价值进一步筛选出16个核心基因（包括同源基因）。利用这些核心基因搜索其调控因子和生物学相关的微小RNA（miRNA）。通过这种方式，鉴定出10个miRNA作为与LUAD相关的候选小RNA，随后进一步获得与miRNA相关的长链非编码RNA（lncRNA）。深入分析表明，4个核心mRNA、2个miRNA和2个lncRNA是癌症发生发展过程中的潜在关键RNA，并构建了一个竞争性内源性RNA（ceRNA）网络。最后，我们确定CCNA2/MKI67/KIF11:miR-30a-5p:VPS9D1-AS1轴相关的细胞周期作为一种预后生物标志物，它提供了mRNA和非编码RNA（ncRNA）之间的RNA相互作用，特别是在多个异源miR水平上，这进一步使编码-非编码RNA调控网络复杂化。我们的研究结果为不同RNA之间复杂的相互作用提供了见解，特别是涉及异源miR的相互作用，这将丰富我们对编码-非编码RNA调控网络中mRNA-ncRNA相互作用及其在肿瘤发生中的作用的理解。
