Characterization of Cell Cycle-Related Competing Endogenous RNAs Using Robust Rank Aggregation as Prognostic Biomarker in Lung Adenocarcinoma.
Characterization of Cell Cycle-Related Competing Endogenous RNAs Using Robust Rank Aggregation as Prognostic Biomarker in Lung Adenocarcinoma.
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使用稳健的Rank聚集作为肺腺癌的预后生物标志物表征细胞周期相关的竞争性内源RNA
DOI：
10.3389/fonc.2022.807367
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发表时间：
2022
影响因子：
4.7
通讯作者：
Guo L
中科院分区：
文献类型：
--
作者：
Yang Y;Zhang S;Guo L
肺腺癌（LUAD）是肺癌中最常见的病理亚型之一，因为它是癌症相关死亡的主要原因而受到关注。由于其预后差，为了确定预后生物标志物，本研究进行了综合分析，以筛选curial RNA并讨论它们的交叉作用。利用RRA技术对多个数据集的mRNA表达谱进行初步筛选，发现这些去调控基因在细胞周期和卵母细胞减数分裂等多个生物学途径中发挥重要作用。然后，通过整合12种算法得到31个候选基因，并根据潜在的预后价值进一步筛选16个枢纽基因（包含同源基因）。这些枢纽基因被用来寻找它们的调节子和生物相关的microRNAs（miRNAs）。通过上述方法，筛选出10个与LUAD相关的候选小分子RNA，并进一步获得与小分子RNA相关的长链非编码RNA（lncRNA）。深入分析发现，4个hub mRNAs、2个miRNAs和2个lncRNAs是参与肿瘤发生发展的潜在关键RNA，并构建了一个竞争性内源性RNA（ceRNA）网络。最后，我们将CCNA 2/MKI 67/KIF 11：miR-30 a-5 p：VPS 9D 1-AS 1轴相关细胞周期作为预后生物标志物，其提供了mRNA和非编码RNA（ncRNA）之间的RNA串扰，特别是在多个isomiR水平上，这进一步使编码-非编码RNA调控网络复杂化。我们的研究结果提供了对不同RNA之间复杂的交叉对话的深入了解，特别是涉及isomiR，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。
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 via 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.
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