Identification of Key MicroRNAs and Mechanisms in Prostate Cancer Evolution Based on Biomarker Prioritization Model and Carcinogenic Survey.
Identification of Key MicroRNAs and Mechanisms in Prostate Cancer Evolution Based on Biomarker Prioritization Model and Carcinogenic Survey.
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DOI：
10.3389/fgene.2020.596826
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发表时间：
2020
影响因子：
3.7
通讯作者：
Shen B
中科院分区：
文献类型：
--
作者：
Lin Y;Miao Z;Zhang X;Wei X;Hou J;Huang Y;Shen B
背景：前列腺癌（Prostate cancer，PCa）发病率逐年上升，发病机制复杂多样.虽然临床策略积累了PCa的预防，仍然缺乏敏感的生物标志物的PCa的发生和进展的整体管理。基于系统生物学和人工智能的翻译信息学为PCa生物标志物的优先排序和致癌性研究提供了新的视角。研究方法：在这项研究中，基因表达和miRNA-mRNA关联数据被整合，以构建特异性PCa发生和进展的条件网络，分别。基于网络建模，具有显著强的单线调节能力的枢纽miRNA被拓扑地鉴定，并且被条件特异性网络系统共享的那些被选择作为候选生物标志物用于计算验证和功能富集分析。结果：9个miRNAs，即，hsa-miR-1- 3 p、hsa-miR-125 b-5 p、hsa-miR-145- 5 p、hsa-miR-182- 5 p、hsa-miR-198、hsa-miR-22- 3 p、hsa-miR-24- 3 p、hsa-miR-34 a-5 p和hsa-miR-499 a-5 p优先作为PCa管理的关键参与者。这些miRNA中的大多数在区分不同前列腺样品中实现了高AUC值（AUC > 0.70）。其中，7个miRNAs先前已被报道为PCa生物标志物，这表明了所提出的模型的性能。剩余的hsa-miR-22- 3 p和hsa-miR-499 a-5 p可作为PCa预测和监测的新候选者。特别是，提取关键的miRNA-mRNA调控用于致病性理解。本文选择hsa-miR-145- 5 p作为研究对象，发现hsa-miR-145- 5 p/NDRG 2/AR和hsa-miR-145- 5 p/KLF 5/AR轴是PCa进化过程中的假定机制。此外，Wnt信号传导、前列腺癌、癌症中的microRNA等被鉴定的miRNA-mRNA显著富集，证明了鉴定的miRNAs在PCa发生中的功能作用。结论：计算鉴定并分析生物标志物miRNAs以及相关的miRNA-mRNA关系，用于PCa管理和致癌性破译。使用低通量技术和人类样本的进一步实验和临床验证预计将用于未来的翻译研究。
Background: Prostate cancer (PCa) is occurred with increasing incidence and heterogeneous pathogenesis. Although clinical strategies are accumulated for PCa prevention, there is still a lack of sensitive biomarkers for the holistic management in PCa occurrence and progression. Based on systems biology and artificial intelligence, translational informatics provides new perspectives for PCa biomarker prioritization and carcinogenic survey. Methods: In this study, gene expression and miRNA-mRNA association data were integrated to construct conditional networks specific to PCa occurrence and progression, respectively. Based on network modeling, hub miRNAs with significantly strong single-line regulatory power were topologically identified and those shared by the condition-specific network systems were chosen as candidate biomarkers for computational validation and functional enrichment analysis. Results: Nine miRNAs, i.e., hsa-miR-1-3p, hsa-miR-125b-5p, hsa-miR-145-5p, hsa-miR-182-5p, hsa-miR-198, hsa-miR-22-3p, hsa-miR-24-3p, hsa-miR-34a-5p, and hsa-miR-499a-5p, were prioritized as key players for PCa management. Most of these miRNAs achieved high AUC values (AUC > 0.70) in differentiating different prostate samples. Among them, seven of the miRNAs have been previously reported as PCa biomarkers, which indicated the performance of the proposed model. The remaining hsa-miR-22-3p and hsa-miR-499a-5p could serve as novel candidates for PCa predicting and monitoring. In particular, key miRNA-mRNA regulations were extracted for pathogenetic understanding. Here hsa-miR-145-5p was selected as the case and hsa-miR-145-5p/NDRG2/AR and hsa-miR-145-5p/KLF5/AR axis were found to be putative mechanisms during PCa evolution. In addition, Wnt signaling, prostate cancer, microRNAs in cancer etc. were significantly enriched by the identified miRNAs-mRNAs, demonstrating the functional role of the identified miRNAs in PCa genesis. Conclusion: Biomarker miRNAs together with the associated miRNA-mRNA relations were computationally identified and analyzed for PCa management and carcinogenic deciphering. Further experimental and clinical validations using low-throughput techniques and human samples are expected for future translational studies.