竞争的内源性RNA通过转录后相互作用中的串扰在细胞分子机制中发挥关键作用。关于ceRNA串扰的研究,这尤其取决于大量的自由转录本,通常涉及大规模和小规模研究,涉及整合来自组织和相关性分析的转录组数据。ceRNA相互作用的这种丰度依赖性表明组织和条件特异性ceRNA动力学可能会波动。然而,没有全面的研究调查正常组织中的ceRNA相互作用,在癌组织或其相互作用中丢失和/或出现的ceRNA。在这项研究中,我们全面分析了在三种发病率最高的癌症中观察到的肿瘤特异性ceRNA波动,LUAD,PRAD,和BRCA,与健康的肺相比,前列腺,和乳房组织,分别。我们对肿瘤特异性竞争性内源性RNA(ceRNA)相互作用的观察表明,在肺腺癌(LUAD)的情况下,前列腺腺癌(PRAD),和乳腺浸润性癌(BRCA),3,204,1,233和406个CERNA,分别,参与肿瘤组织内的转录后通讯,与它们在相应健康样本中的缺失相反。我们还发现,三种癌症类型共有90个ceRNA,与正常组织相比,这些ceRNA参与肿瘤组织中的ceRNA相互作用。在与miRNAs直接相互作用的90个ceRNAs中,我们发现了一个由165个miRNAs和63个ceRNAs组成的核心网络,这些核心网络在未来的研究中应该被考虑用于RNA靶向和RNA介导的方法,并且可以用于这三种侵袭性癌症类型.更具体地说,在这个核心互动网络中,ceRNAs如GALNT7、KLF9和DAB2,miRNAs如miR-106a/b-5p,miR-20a-5p,miR-519d-3p可能作为三种关键癌症的共同靶标。与使用与正常组织相比的差异表达基因构建ceRNA网络的常规方法相反,我们提出的方法通过考虑ceRNA:miRNA相互作用中的上下文来识别ceRNA参与者。我们的结果有可能揭示癌症类型中独特和常见的ceRNA相互作用,并确定关键RNA。从而为对抗癌症的基于RNA的策略铺平了道路。
Competing endogenous RNAs play key roles in cellular molecular mechanisms through cross-talk in post-transcriptional interactions. Studies on ceRNA cross-talk, which is particularly dependent on the abundance of free transcripts, generally involve large- and small-scale studies involving the integration of transcriptomic data from tissues and correlation analyses. This abundance-dependent nature of ceRNA interactions suggests that tissue- and condition-specific ceRNA dynamics may fluctuate. However, there are no comprehensive studies investigating the ceRNA interactions in normal tissue, ceRNAs that are lost and/or appear in cancerous tissues or their interactions. In this study, we comprehensively analyzed the tumor-specific ceRNA fluctuations observed in the three highest-incidence cancers, LUAD, PRAD, and BRCA, compared to healthy lung, prostate, and breast tissues, respectively. Our observations pertaining to tumor-specific competing endogenous RNA (ceRNA) interactions revealed that, in the cases of lung adenocarcinoma (LUAD), prostate adenocarcinoma (PRAD), and breast invasive carcinoma (BRCA), 3,204, 1,233, and 406 ceRNAs, respectively, engage in post-transcriptional intercommunication within tumor tissues, in contrast to their absence in corresponding healthy samples. We also found that 90 ceRNAs are shared by the three cancer types and that these ceRNAs participate in ceRNA interactions in tumor tissues compared to those in normal tissues. Among the 90 ceRNAs that directly interact with miRNAs, we uncovered a core network of 165 miRNAs and 63 ceRNAs that should be considered in RNA-targeted and RNA-mediated approaches in future studies and could be used in these three aggressive cancer types. More specifically, in this core interaction network, ceRNAs such as GALNT7, KLF9, and DAB2 and miRNAs like miR-106a/b-5p, miR-20a-5p, and miR-519d-3p may have potential as common targets in the three critical cancers. In contrast to conventional methods that construct ceRNA networks using differentially expressed genes compared to normal tissues, our proposed approach identifies ceRNA players by considering their context within the ceRNA:miRNA interactions. Our results have the potential to reveal distinct and common ceRNA interactions in cancer types and to pinpoint critical RNAs, thereby paving the way for RNA-based strategies in the battle against cancer.