Immune and Metabolic Dysregulated Coding and Non-coding RNAs Reveal Survival Association in Uterine Corpus Endometrial Carcinoma.
Immune and Metabolic Dysregulated Coding and Non-coding RNAs Reveal Survival Association in Uterine Corpus Endometrial Carcinoma.
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DOI：
10.3389/fgene.2021.673192
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发表时间：
2021
影响因子：
3.7
通讯作者：
Qiu M
中科院分区：
文献类型：
--
作者：
Liu D;Qiu M
子宫体子宫内膜癌（UCEC）是最常见的妇科恶性肿瘤之一，但只有少数生物标志物已被证明是有效的在临床实践中。以往的研究已经证明了非编码RNA（ncRNA）在UCEC的诊断、预后和治疗选择中的重要作用，并建议在不同水平整合分子以解释潜在的分子机制的意义。在这项研究中，我们收集了570个样本的转录组数据，包括长链非编码RNA（lncRNA），microRNA（miRNAs）和信使RNA（mRNAs），其中包括537个UCEC样本和33个正常样本。首先，鉴定了区分侵袭性癌样本与正常样本的差异表达的lncRNA、miRNA和mRNA，进一步的分析表明这些RNA富集了癌症和代谢相关的功能。接下来，构建了由差异表达的lncRNA、miRNA和mRNA组成的整合的、失调的和无尺度的生物网络。该网络中的蛋白质编码基因和ncRNA基因显示出潜在的免疫和代谢功能。进一步的分析揭示了两个临床相关的模块，显示出与代谢和免疫功能密切相关。两个模块中的RNA经功能验证与UCEC相关。这项研究的结果表明，一个重要的临床应用，以改善预后预测UCEC。
Uterine corpus endometrial carcinoma (UCEC) is one of the most common gynecologic malignancies, but only a few biomarkers have been proven to be effective in clinical practice. Previous studies have demonstrated the important roles of non-coding RNAs (ncRNAs) in diagnosis, prognosis, and therapy selection in UCEC and suggested the significance of integrating molecules at different levels for interpreting the underlying molecular mechanism. In this study, we collected transcriptome data, including long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs), of 570 samples, which were comprised of 537 UCEC samples and 33 normal samples. First, differentially expressed lncRNAs, miRNAs, and mRNAs, which distinguished invasive carcinoma samples from normal samples, were identified, and further analysis showed that cancer- and metabolism-related functions were enriched by these RNAs. Next, an integrated, dysregulated, and scale-free biological network consisting of differentially expressed lncRNAs, miRNAs, and mRNAs was constructed. Protein-coding and ncRNA genes in this network showed potential immune and metabolic functions. A further analysis revealed two clinic-related modules that showed a close correlation with metabolic and immune functions. RNAs in the two modules were functionally validated to be associated with UCEC. The findings of this study demonstrate an important clinical application for improving outcome prediction for UCEC.
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