School of Computer Science, Shaanxi Normal University, Xi'an 710119, China.
Department of Mechanical Engineering and Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, SK S7N 5A9, Canada.
Int J Biol Sci. 2018 Nov 1;14(14):1950-1959. doi: 10.7150/ijbs.28260. eCollection 2018.
Circular RNAs (circRNAs) are a large group of endogenous non-coding RNAs which are key members of gene regulatory processes. Those circRNAs in human paly significant roles in health and diseases. Owing to the characteristics of their universality, specificity and stability, circRNAs are becoming an ideal class of biomarkers for disease diagnosis, treatment and prognosis. Identification of the relationships between circRNAs and diseases can help understand the complex disease mechanism. However, traditional experiments are costly and time-consuming, and little computational models have been developed to predict novel circRNA-disease associations. In this study, a heterogeneous network was constructed by employing the circRNA expression profiles, disease phenotype similarity and Gaussian interaction profile kernel similarity. Then, we developed a computational model of KATZ measures for human circRNA-disease association prediction (KATZHCDA). The leave-one-out cross validation (LOOCV) and 5-fold cross validation were implemented to investigate the effects of these four types of similarity measures. As a result, KATZHCDA model yields the AUCs of 0.8469 and 0.7936+/-0.0065 in LOOCV and 5-fold cross validation, respectively. Furthermore, we analyze the candidate association between hsa_circ_0006054 and colorectal cancer, and results showed that hsa_circ_0006054 may function as miRNA sponge in the carcinogenesis of colorectal cancer. Overall, it is anticipated that our proposed model could become an effective resource for clinical experimental guidance.
环状 RNA（circRNAs）是一大类内源性非编码 RNA，是基因调控过程的关键成员。人类的那些 circRNAs 在健康和疾病中发挥着重要作用。由于其普遍性、特异性和稳定性的特点，circRNAs 正在成为疾病诊断、治疗和预后的理想生物标志物。识别 circRNAs 与疾病之间的关系有助于了解复杂的疾病机制。然而，传统实验既昂贵又耗时，并且很少有计算模型被开发出来以预测新的 circRNA-疾病关联。在这项研究中，通过使用 circRNA 表达谱、疾病表型相似性和高斯相互作用谱核相似性构建了一个异质网络。然后，我们开发了一种用于人类 circRNA-疾病关联预测的 KATZ 度量计算模型（KATZHCDA）。采用留一法交叉验证（LOOCV）和 5 倍交叉验证来研究这四种相似性度量的效果。结果，KATZHCDA 模型在 LOOCV 和 5 倍交叉验证中的 AUC 值分别为 0.8469 和 0.7936+/-0.0065。此外，我们分析了 hsa_circ_0006054 与结直肠癌之间的候选关联，结果表明 hsa_circ_0006054 可能在结直肠癌的发生中作为 miRNA 海绵发挥作用。总的来说，预计我们提出的模型可以成为临床实验指导的有效资源。
