Katsila Theodora, Matsoukas Minos-Timotheos, Patrinos George P, Kardamakis Dimitrios
1 Department of Pharmacy, School of Health Sciences, University of Patras , Patras, Greece .
2 Department of Pathology, College of Medicine and Health Sciences, United Arab Emirates University , Al Ain, United Arab Emirates .
OMICS. 2017 Aug;21(8):429-439. doi: 10.1089/omi.2017.0087.
Applications of omics systems biology technologies have enormous promise for radiology and diagnostics in surgical fields. In this context, the emerging fields of radiomics (a systems scale approach to radiology using a host of technologies, including omics) and pharmacometabolomics (use of metabolomics for patient and disease stratification and guiding precision medicine) offer much synergy for diagnostic innovation in surgery, particularly in neurosurgery. This synthesis of omics fields and applications is timely because diagnostic accuracy in central nervous system tumors still challenges decision-making. Considering the vast heterogeneity in brain tumors, disease phenotypes, and interindividual variability in surgical and chemotherapy outcomes, we believe that diagnostic accuracy can be markedly improved by quantitative radiomics coupled to pharmacometabolomics and related health information technologies while optimizing economic costs of traditional diagnostics. In this expert review, we present an innovation analysis on a systems-level multi-omics approach toward diagnostic accuracy in central nervous system tumors. For this, we suggest that glioblastomas serve as a useful application paradigm. We performed a literature search on PubMed for articles published in English between 2006 and 2016. We used the search terms "radiomics," "glioblastoma," "biomarkers," "pharmacogenomics," "pharmacometabolomics," "pharmacometabonomics/pharmacometabolomics," "collaborative informatics," and "precision medicine." A list of the top 4 insights we derived from this literature analysis is presented in this study. For example, we found that (i) tumor grading needs to be better refined, (ii) diagnostic precision should be improved, (iii) standardization in radiomics is lacking, and (iv) quantitative radiomics needs to prove clinical implementation. We conclude with an interdisciplinary call to the metabolomics, pharmacy/pharmacology, radiology, and surgery communities that pharmacometabolomics coupled to information technologies (chemoinformatics tools, databases, collaborative systems) can inform quantitative radiomics, thus translating Big Data and information growth to knowledge growth, rational drug development and diagnostics innovation for glioblastomas, and possibly in other brain tumors.
组学系统生物学技术在外科领域的放射学和诊断学方面具有巨大的应用前景。在此背景下，新兴的放射组学（一种使用包括组学在内的一系列技术的系统规模放射学方法）和药物代谢组学（利用代谢组学进行患者和疾病分层并指导精准医学）为外科诊断创新，尤其是神经外科的诊断创新，提供了诸多协同作用。组学领域与应用的这种整合恰逢其时，因为中枢神经系统肿瘤的诊断准确性仍然对决策构成挑战。考虑到脑肿瘤的巨大异质性、疾病表型以及手术和化疗结果的个体间差异，我们认为，通过将定量放射组学与药物代谢组学及相关健康信息技术相结合，同时优化传统诊断的经济成本，可以显著提高诊断准确性。在这篇专家综述中，我们对一种用于提高中枢神经系统肿瘤诊断准确性的系统级多组学方法进行了创新分析。为此，我们建议将胶质母细胞瘤作为一个有用的应用范例。我们在PubMed上搜索了2006年至2016年期间发表的英文文章。我们使用了“放射组学”“胶质母细胞瘤”“生物标志物”“药物基因组学”“药物代谢组学”“药物代谢组学/药物代谢组学”“协作信息学”和“精准医学”等搜索词。本研究列出了我们从该文献分析中得出的前4个见解。例如，我们发现：（i）肿瘤分级需要进一步优化；（ii）诊断精度应提高；（iii）放射组学缺乏标准化；（iv）定量放射组学需要证明其临床实用性。我们最后跨学科呼吁代谢组学、药学/药理学、放射学和外科学领域，药物代谢组学与信息技术（化学信息学工具、数据库、协作系统）相结合可以为定量放射组学提供信息，从而将大数据和信息增长转化为知识增长、合理的药物开发以及胶质母细胞瘤乃至其他脑肿瘤的诊断创新。
