Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, China.
Faculty of Medicine, Amsterdam UMC, Univ of Amsterdam, Amsterdam, Netherlands.
Bioengineered. 2021 Dec;12(2):12821-12838. doi: 10.1080/21655979.2021.2003925.
Long non-coding RNAs (lncRNAs) have been demonstrated to fine-tune gene regulations that govern a broad spectrum of oncogenic processes. Nonetheless, our understanding of the roles of lncRNAs and their interactions with miRNAs and mRNAs in HNSCC is still highly rudimentary. Here, we present a comprehensive bioinformatics analysis in which competing endogenous RNA (ceRNA) network construction and weighted gene co-expression network analysis (WGCNA) were combined to explore novel diagnostic and prognostic lncRNAs for HNSCC. Differentially expressed mRNAs (DEGs), miRNAs (DEMs) and lncRNAs (DELs) were identified based on the RNA sequencing data and clinical data retrieved from TCGA database. LncRNA-regulated ceRNA networks were constructed based on the interactive RNA pairs predicted by miRDB, miRcode and TargetScan. WGCNA was conducted to identify lncRNAs that were significantly correlated with patient overall survival (OS) and HNSCC tumor. RT-qPCR was employed to validate the expression of lncRNAs in HNSCC cell lines and patient sera. A ceRNA network consisting of 90 DEGs, 7 DEMs and 67 DELs associated with clinical traits was established. WGCNA and Kaplan-Meier survival analysis revealed that 5 DELs (MIR4435-2 HG, CASC9, LINC01980, STARD4-AS1 and MIR99AHG) were significantly correlated with OS of HNSCC patients, whereas DEL PART1 was most significantly correlated with the HNSCC tumor. The predicted expression patterns of PART1, LINC01980 and MIR4435-2 HG were further validated in HNSCC cell lines and patient sera. Collectively, the present study provided novel insights into the lncRNA-regulated ceRNA networks in HNSCC and identified novel lncRNAs that harbor diagnostic and prognostic potentials for HNSCC. BP, biological process. CC, cellular component. ceRNA, competing endogenous RNA. DEG, differential expressions of mRNA. DEL, differentially expressed lncRNA. DEM, differentially expressed miRNA. ESCC, esophageal squamous cell carcinoma. FPKM, Fragments Per Kilobase Million. GO, Gene Ontology. GS, gene significance. HNSCC, head and neck squamous cell carcinoma. KEGG, Kyoto Encyclopedia of Genes and Genomes. LncRNA, long non-coding RNA. MCC, Maximal Clique Centrality. ME, module eigengenes. MF, molecular functions. MM, module membership. MRE, miRNA-binding site. MYO5A, Myosin-Va. PART1, prostate androgen-regulated transcript 1. RBM3, RNA‑binding motif protein 3. TCGA, The Cancer Genome Atlas. TOM, topological overlap measure. TSCC, tongue squamous cell carcinoma. WGCNA, weighted gene co-expression network analysis.
长链非编码 RNA（lncRNA）已被证明可以精细调节基因调控，从而控制广泛的致癌过程。尽管如此，我们对 lncRNA 的作用及其与 miRNA 和 mRNA 在 HNSCC 中的相互作用的理解仍然非常基础。在这里，我们进行了一项全面的生物信息学分析，结合竞争性内源 RNA（ceRNA）网络构建和加权基因共表达网络分析（WGCNA），探索用于 HNSCC 的新型诊断和预后 lncRNA。根据 TCGA 数据库中检索的 RNA 测序数据和临床数据，鉴定差异表达的 mRNA（DEGs）、miRNA（DEMs）和 lncRNA（DELs）。基于 miRDB、miRcode 和 TargetScan 预测的互作 RNA 对构建 lncRNA 调控的 ceRNA 网络。进行 WGCNA 以鉴定与患者总生存期（OS）和 HNSCC 肿瘤显著相关的 lncRNA。实时定量 qPCR 用于验证 HNSCC 细胞系和患者血清中 lncRNA 的表达。建立了一个包含 90 个与临床特征相关的 DEG、7 个 DEM 和 67 个 DEL 的 ceRNA 网络。WGCNA 和 Kaplan-Meier 生存分析显示，5 个 DEL（MIR4435-2HG、CASC9、LINC01980、STARD4-AS1 和 MIR99AHG）与 HNSCC 患者的 OS 显著相关，而 DEL PART1 与 HNSCC 肿瘤最显著相关。PART1、LINC01980 和 MIR4435-2HG 的预测表达模式在 HNSCC 细胞系和患者血清中进一步得到验证。总之，本研究提供了 HNSCC 中 lncRNA 调控 ceRNA 网络的新见解，并鉴定了具有 HNSCC 诊断和预后潜力的新型 lncRNA。BP，生物过程。CC，细胞成分。ceRNA，竞争性内源 RNA。DEG，mRNA 的差异表达。DEL，差异表达的 lncRNA。DEM，差异表达的 miRNA。ESCC，食管鳞状细胞癌。FPKM，片段每百万碱基数。GO，基因本体论。GS，基因意义。HNSCC，头颈部鳞状细胞癌。KEGG，京都基因与基因组百科全书。LncRNA，长链非编码 RNA。MCC，最大团中心度。ME，模块特征基因。MF，分子功能。MM，模块成员。MRE，miRNA 结合位点。MYO5A，肌球蛋白-Va。PART1，前列腺雄激素调节转录物 1。RBM3，RNA 结合基序蛋白 3。TCGA，癌症基因组图谱。TOM，拓扑重叠度量。TSCC，舌鳞状细胞癌。WGCNA，加权基因共表达网络分析。
