Lung Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China.
Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, Shandong, China.
Comb Chem High Throughput Screen. 2022;25(13):2240-2254. doi: 10.2174/1386207325666220324092231.
The potential pathogenesis of LUAD remains largely unknown. In the present study, we evaluated the competing endogenous RNA (ceRNA) regulatory network and tumorinfiltrating immune cells in LUAD.
We obtained the RNA profiles and corresponding clinical information of LUAD patients from the TCGA data portal, and identified differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs), and miRNAs (DEmiRNAs) between LUAD samples and normal controls to build a ceRNA network. Additionally, the CIBERSORT algorithm was employed to analyze the patterns of immune cell infiltration. Then, two survival-predicting models were constructed based on the ceRNA network and tumor-infiltrating immune cells, which were validated by an independent GEO dataset GSE50081. Moreover, the correlation between prognosis-related ceRNAs and immune cells was also evaluated.
In total, 484 LUAD samples and 59 normal controls were included in this study, and 15 DEmiRNAs, 94 DEmRNAs, and 7 DElncRNAs were integrated to construct the ceRNA network of LUAD. Meanwhile, differentially expressed tumor-infiltrating immune cells were also identified, and the expressions of monocytes and regulatory T cells were related to the overall survival (OS) of LUAD patients. Moreover, the prognostic prediction model based on ceRNA network or tumor-infiltrating immune cells exhibited significant power in predicting the survival of LUAD patients. Furthermore, co-expression analysis revealed that some prognosis-related ceRNAs, such as CCT6A, E2F7, SLC16A1, and SNHG3, were positively or negatively correlated with several tumorinfiltrating immune cells, such as monocytes and M1 macrophages.
This study improves our understanding of the pathogenesis of LUAD and is helpful in exploring the potential therapeutic targets and prognostic biomarkers for LUAD.
LUAD 的潜在发病机制在很大程度上仍不清楚。本研究评估了 LUAD 中的竞争内源性 RNA（ceRNA）调控网络和肿瘤浸润免疫细胞。
我们从 TCGA 数据门户获取了 LUAD 患者的 RNA 谱和相应的临床信息，并鉴定了 LUAD 样本与正常对照之间差异表达的 mRNAs（DEmRNAs）、lncRNAs（DElncRNAs）和 miRNAs（DEmiRNAs），以构建 ceRNA 网络。此外，使用 CIBERSORT 算法分析免疫细胞浸润模式。然后，基于 ceRNA 网络和肿瘤浸润免疫细胞构建了两个生存预测模型，并通过独立的 GEO 数据集 GSE50081 进行了验证。此外，还评估了预后相关 ceRNA 与免疫细胞之间的相关性。
本研究共纳入 484 例 LUAD 样本和 59 例正常对照，整合了 15 个 DEmiRNAs、94 个 DEmRNAs 和 7 个 DElncRNAs 构建了 LUAD 的 ceRNA 网络。同时，还鉴定了差异表达的肿瘤浸润免疫细胞，单核细胞和调节性 T 细胞的表达与 LUAD 患者的总生存期（OS）相关。此外，基于 ceRNA 网络或肿瘤浸润免疫细胞的预后预测模型在预测 LUAD 患者的生存方面表现出显著的能力。此外，共表达分析表明，一些预后相关的 ceRNA，如 CCT6A、E2F7、SLC16A1 和 SNHG3，与单核细胞和 M1 巨噬细胞等几种肿瘤浸润免疫细胞呈正相关或负相关。
本研究提高了我们对 LUAD 发病机制的认识，有助于探索 LUAD 的潜在治疗靶点和预后生物标志物。
