Table6_Identification of Potential Novel Prognosis-Related Genes Through Transcriptome Sequencing, Bioinformatics Analysis, and Clinical Validation in Acute Myeloid Leukemia.DOCX

Background: Acute Myeloid Leukemia (AML) is a complex and heterogeneous hematologic malignancy. However, the function of prognosis-related signature genes in AML remains unclear.
Methods: In the current study, transcriptome sequencing was performed on 15 clinical samples, differentially expressed RNAs were identified using R software. The potential interactions network was constructed by using the common genes between target genes of differentially expressed miRNAs with transcriptome sequencing results. Functional and pathway enrichment analysis was performed to identify candidate gene-mediated aberrant signaling pathways. Hub genes were identified by the cytohubba plugin in Cytoscape software, which then expanded the potential interactions regulatory module for hub genes. TCGA-LAML clinical data were used for the prognostic analysis of the hub genes in the regulatory network, and GVSA analysis was used to identify the immune signature of prognosis-related hub genes. qRT-PCR was used to verify the expression of hub genes in independent clinical samples.
Results: We obtained 1,610 differentially expressed lncRNAs, 233 differentially expressed miRNAs, and 2,217 differentially expressed mRNAs from transcriptome sequencing. The potential interactions network is constructed by 12 lncRNAs, 25 miRNAs, and 692 mRNAs. Subsequently, a sub-network including 15 miRNAs as well as 12 lncRNAs was created based on the expanded regulatory modules of 25 key genes. The prognostic analysis results show that CCL5 and lncRNA UCA1 was a significant impact on the prognosis of AML. Besides, we found three potential interactions networks such as lncRNA UCA1/hsa-miR-16-5p/COL4A5, lncRNA UCA1/hsa-miR-16-5p/SPARC, and lncRNA SNORA27/hsa-miR-17-5p/CCL5 may play an important role in AML. Furthermore, the evaluation of the immune infiltration shows that CCL5 is positively correlated with various immune signatures, and lncRNA UCA1 is negatively correlated with the immune signatures. Finally, the result of qRT-PCR showed that CCL5 is down-regulated and lncRNA UCA1 is up-regulated in AML samples separately.
Conclusions: In conclusion, we propose that CCL5 and lncRNA UCA1 could be recognized biomarkers for predicting survival prognosis based on constructing competing endogenous RNAs in AML, which will provide us novel insight into developing novel prognostic, diagnostic, and therapeutic for AML.

背景：急性髓系白血病（Acute Myeloid Leukemia, AML）是一类复杂且具有高度异质性的血液系统恶性肿瘤。然而，AML中与预后相关的特征基因的功能仍未明确。
方法：本研究对15例临床样本开展转录组测序，借助R软件筛选差异表达RNA。将差异表达微小RNA（microRNA, miRNA）的靶基因与转录组测序结果中的共有基因相结合，构建潜在互作调控网络。通过功能富集与通路富集分析，鉴定候选基因介导的异常信号通路。利用Cytoscape软件的cytoHubba插件筛选核心基因（hub genes），并拓展核心基因的潜在互作调控模块。采用肿瘤基因组图谱-急性髓系白血病队列（The Cancer Genome Atlas Acute Myeloid Leukemia, TCGA-LAML）临床数据对调控网络中的核心基因进行预后分析，并通过GVSA分析鉴定与预后相关核心基因的免疫特征。通过实时荧光定量聚合酶链式反应（quantitative Real-Time Polymerase Chain Reaction, qRT-PCR）验证独立临床样本中核心基因的表达水平。
结果：本研究从转录组测序数据中筛选得到1610个差异表达长链非编码RNA（long non-coding RNA, lncRNA）、233个差异表达miRNA以及2217个差异表达mRNA。构建的潜在互作网络包含12个lncRNA、25个miRNA和692个mRNA。随后，基于25个关键基因的拓展调控模块，构建了包含15个miRNA及12个lncRNA的子网。预后分析结果显示，CCL5与长链非编码RNA UCA1对AML患者的预后具有显著影响。此外，本研究发现三条潜在互作通路可能在AML中发挥重要作用，分别为lncRNA UCA1/hsa-miR-16-5p/COL4A5、lncRNA UCA1/hsa-miR-16-5p/SPARC以及lncRNA SNORA27/hsa-miR-17-5p/CCL5。进一步的免疫浸润评估结果表明，CCL5与多种免疫特征呈正相关，而lncRNA UCA1与免疫特征呈负相关。最后，qRT-PCR结果显示，AML样本中CCL5表达下调，lncRNA UCA1表达上调。
结论：综上，本研究通过构建AML的竞争性内源RNA（competing endogenous RNA, ceRNA）调控网络，提出CCL5与lncRNA UCA1可作为预测患者生存预后的潜在生物标志物，该研究为AML的预后评估、诊断及治疗策略开发提供了全新的视角。