Table_5_Comprehensive Review of Web Servers and Bioinformatics Tools for Cancer Prognosis Analysis.XLSX

Prognostic biomarkers are of great significance to predict the outcome of patients with cancer, to guide the clinical treatments, to elucidate tumorigenesis mechanisms, and offer the opportunity of identifying therapeutic targets. To screen and develop prognostic biomarkers, high throughput profiling methods including gene microarray and next-generation sequencing have been widely applied and shown great success. However, due to the lack of independent validation, only very few prognostic biomarkers have been applied for clinical practice. In order to cross-validate the reliability of potential prognostic biomarkers, some groups have collected the omics datasets (i.e., epigenetics/transcriptome/proteome) with relative follow-up data (such as OS/DSS/PFS) of clinical samples from different cohorts, and developed the easy-to-use online bioinformatics tools and web servers to assist the biomarker screening and validation. These tools and web servers provide great convenience for the development of prognostic biomarkers, for the study of molecular mechanisms of tumorigenesis and progression, and even for the discovery of important therapeutic targets. Aim to help researchers to get a quick learning and understand the function of these tools, the current review delves into the introduction of the usage, characteristics and algorithms of tools, and web servers, such as LOGpc, KM plotter, GEPIA, TCPA, OncoLnc, PrognoScan, MethSurv, SurvExpress, UALCAN, etc., and further help researchers to select more suitable tools for their own research. In addition, all the tools introduced in this review can be reached at http://bioinfo.henu.edu.cn/WebServiceList.html.

预后生物标志物（prognostic biomarkers）对于预测癌症患者的临床结局、指导临床治疗方案、阐明肿瘤发生机制以及发掘治疗靶点均具有重要意义。为筛选并开发预后生物标志物，包括基因芯片（gene microarray）与下一代测序（next-generation sequencing）在内的高通量谱学分析技术已被广泛应用并取得显著成果。然而，由于缺乏独立验证，仅有极少数预后生物标志物得以应用于临床实践。为交叉验证潜在预后生物标志物的可靠性，多个研究团队已收集不同队列临床样本的组学数据集（即[表观基因组学（epigenetics）/转录组学（transcriptome）/蛋白质组学（proteome）]）及配套随访数据（如总生存期（Overall Survival, OS）、疾病特异性生存期（Disease-Specific Survival, DSS）、无进展生存期（Progression-Free Survival, PFS）），并开发了易用的在线生物信息学工具与网络服务器，以辅助生物标志物的筛选与验证。此类工具与网络服务器为预后生物标志物的开发、肿瘤发生与进展的分子机制研究，乃至关键治疗靶点的发掘提供了极大便利。为帮助研究人员快速了解并掌握此类工具的功能，本综述深入阐述了LOGpc、KM plotter、GEPIA、TCPA、OncoLnc、PrognoScan、MethSurv、SurvExpress、UALCAN等多款工具及网络服务器的使用方法、特性与算法，并进一步辅助研究人员为自身研究选择更为适配的工具。此外，本综述中介绍的所有工具均可通过访问http://bioinfo.henu.edu.cn/WebServiceList.html获取。