Ran Zihan, Yang Jingcheng, Liu Yaqing, Chen XiuWen, Ma Zijing, Wu Shaobo, Huang Yechao, Song Yueqiang, Gu Yu, Zhao Shuo, Fa Mengqi, Lu Jiangjie, Chen Qingwang, Cao Zehui, Li Xiaofei, Sun Shanyue, Yang Tao
Department of Research, Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Inspection and Quarantine Department, The College of Medical Technology, Shanghai University of Medicine & Health Sciences, Shanghai, China.
Front Oncol. 2022 Aug 11;12:792055. doi: 10.3389/fonc.2022.792055. eCollection 2022.
Gliomas are the most frequent malignant and aggressive tumors in the central nervous system. Early and effective diagnosis of glioma using diagnostic biomarkers can prolong patients' lives and aid in the development of new personalized treatments. Therefore, a thorough and comprehensive understanding of the diagnostic biomarkers in gliomas is of great significance. To this end, we developed the integrated and web-based database GlioMarker (http://gliomarker.prophetdb.org/), the first comprehensive database for knowledge exploration of glioma diagnostic biomarkers. In GlioMarker, accurate information on 406 glioma diagnostic biomarkers from 1559 publications was manually extracted, including biomarker descriptions, clinical information, associated literature, experimental records, associated diseases, statistical indicators, etc. Importantly, we integrated many external resources to provide clinicians and researchers with the capability to further explore knowledge on these diagnostic biomarkers based on three aspects. (1) Obtain more ontology annotations of the biomarker. (2) Identify the relationship between any two or more components of diseases, drugs, genes, and variants to explore the knowledge related to precision medicine. (3) Explore the clinical application value of a specific diagnostic biomarker through online analysis of genomic and expression data from glioma cohort studies. GlioMarker provides a powerful, practical, and user-friendly web-based tool that may serve as a specialized platform for clinicians and researchers by providing rapid and comprehensive knowledge of glioma diagnostic biomarkers to subsequently facilitates high-quality research and applications.
胶质瘤是中枢神经系统中最常见的恶性侵袭性肿瘤。利用诊断生物标志物对胶质瘤进行早期有效诊断可以延长患者寿命，并有助于开发新的个性化治疗方法。因此，全面深入地了解胶质瘤中的诊断生物标志物具有重要意义。为此，我们开发了基于网络的综合数据库GlioMarker（http://gliomarker.prophetdb.org/），这是首个用于胶质瘤诊断生物标志物知识探索的综合数据库。在GlioMarker中，我们从1559篇出版物中手动提取了406种胶质瘤诊断生物标志物的准确信息，包括生物标志物描述、临床信息、相关文献、实验记录、相关疾病、统计指标等。重要的是，我们整合了许多外部资源，以便从三个方面为临床医生和研究人员提供进一步探索这些诊断生物标志物知识的能力。（1）获取生物标志物更多的本体注释。（2）识别疾病、药物、基因和变异的任意两个或更多组成部分之间的关系，以探索与精准医学相关的知识。（3）通过对胶质瘤队列研究的基因组和表达数据进行在线分析，探索特定诊断生物标志物的临床应用价值。GlioMarker提供了一个强大、实用且用户友好的基于网络的工具，通过为临床医生和研究人员提供关于胶质瘤诊断生物标志物的快速全面知识，它可以作为一个专门平台，随后促进高质量的研究和应用。
