面向医生和研究人员的全面且便于用户分析的癌症患者数据库
Comprehensive and user-analytics-friendly cancer patient database for physicians and researchers
AI总结：
本文提出一个整合基因突变、糖组学、半乳凝素谱及临床生活方式数据的交互式癌症患者数据库，帮助医生和研究人员发现分子特征并提升个体化诊疗能力。
摘要：
癌症患者需要精细化的护理，因为癌症的发展和临床进程是多因素的，受到患者总体健康状况、胚系突变和肿瘤突变、合并症以及环境的影响。为了有效地为每位患者量身定制个体化治疗方案，必须以易于访问和易于分析的方式向医疗服务提供者呈现这些多因素数据。为满足这一需求，我们开发了一个关系型数据库，将癌症关键基因突变状态、血清半乳凝素谱、血清和肿瘤糖组学谱与个体癌症患者的临床、人口统计学和生活方式数据点进行整合。该数据库作为后端，为医生和研究人员提供了一个单一、易于访问的癌症谱分析数据存储库，以辅助和增强个体化治疗。我们的交互式数据库允许医疗服务提供者从这些群体中合并队列，以发现不同数据类型之间的相关性，并有可能基于基因突变、半乳凝素血清水平、聚糖组成以及患者临床数据和生活方式选择的组合来发现“分子特征”。我们的项目为构建一个集成的、交互式的、不断增长的数据库提供了框架，用于分析跨癌症分期和亚型的分子与临床模式，并为提高诊断和预后能力提供了机会。
英文摘要：
Nuanced cancer patient care is needed, as the development and clinical course of cancer is multifactorial with influences from the general health status of the patient, germline and neoplastic mutations, co-morbidities, and environment. To effectively tailor an individualized treatment to each patient, such multifactorial data must be presented to providers in an easy-to-access and easy-to-analyze fashion. To address the need, a relational database has been developed integrating status of cancer-critical gene mutations, serum galectin profiles, serum and tumor glycomic profiles, with clinical, demographic, and lifestyle data points of individual cancer patients. The database, as a backend, provides physicians and researchers with a single, easily accessible repository of cancer profiling data to aid-in and enhance individualized treatment. Our interactive database allows care providers to amalgamate cohorts from these groups to find correlations between different data types with the possibility of finding "molecular signatures" based upon a combination of genetic mutations, galectin serum levels, glycan compositions, and patient clinical data and lifestyle choices. Our project provides a framework for an integrated, interactive, and growing database to analyze molecular and clinical patterns across cancer stages and subtypes and provides opportunities for increased diagnostic and prognostic power.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
