Ovarian Cancer Biomarker Database (OCBD)

Ovarian cancer is the most common cause of death among gynaecological malignancies. Due to its asymptomatic development, the disease is often diagnosed as an advanced, incurable stage. Although ovarian cancer generally responds well to platinum- and taxane-based first-line chemotherapy, most patients develop relapse and chemotherapy resistance. Despite years of research, reliable diagnostic indicators are still lacking. and other diagnostic methods that enable early detection and are suitable for screening.Therefore, many current studies aim to find new biomarkers with diagnostic, prognostic, and predictive potential, as well as to find new therapeutic targets. Early diagnosis is the most important factor in determining ovarian cancer survival. Current clinically applied diagnostic tools have had very limited success in early detection. The discovery of new diagnostic biomarkers for the early diagnosis of ovarian cancer is one of the major challenges of modern medicine. With advances in genomics and proteomics technology, many molecular biomarkers have been discovered and shown promise for ovarian cancer diagnosis, but further validation is still needed.In order to integrate and evaluate numerous research resources and results, literature review and information extraction analysis were carried out, so as to construct an ovarian cancer biomarker library to assist in the discovery of new ovarian cancer biomarkers in the diagnosis and treatment of ovarian cancer related diseases, and supplement the current inclusion of biomarkers, including data, classification, targets, etc. It covers the name/combination of biomarkers, molecular type, function, sensitivity, specificity, area under the curve, technique, algorithm, sample type, number of cases, target/signaling pathway, reference year region, reference title, and corresponding URL source. The interface supports the query function of the above biomarker content. Therefore, this biomarker database will help to find biomarkers conducive to early ovarian cancer diagnosis from multi-directional molecular types, mechanisms of action, methods of action, and targets, help ovarian cancer treatment, and improve the survival rate of ovarian cancer.卵巢癌是妇科恶性肿瘤中最常见的致死病因。由于其发病进程无明显临床症状，该疾病往往在确诊时已进展至晚期且无法治愈的阶段。尽管卵巢癌对以铂类（platinum）和紫杉类（taxane）为基础的一线化疗通常应答良好，但多数患者会出现疾病复发及化疗耐药。尽管经过多年研究，目前仍缺乏可靠的诊断指标，以及可实现早期检测且适用于大规模筛查的其他诊断手段。早期诊断是决定卵巢癌患者生存结局的最关键因素。当前临床应用的诊断工具在卵巢癌早期检测方面收效甚微，发掘可用于卵巢癌早期诊断的新型生物标志物（biomarker），是现代医学面临的重大挑战之一。随着基因组学（genomics）与蛋白质组学（proteomics）技术的进步，诸多分子生物标志物已被发现并展现出用于卵巢癌诊断的潜力，但仍需开展进一步验证工作。为整合并评估海量研究资源与研究成果，本研究开展了文献综述与信息提取分析，旨在构建卵巢癌生物标志物库，以辅助卵巢癌相关疾病诊疗领域新型卵巢癌生物标志物的发掘，并补充当前已收录的生物标志物相关信息，包括数据、分类、靶点等。该数据库涵盖生物标志物的名称/组合、分子类型、功能、灵敏度、特异性、曲线下面积、检测技术、算法、样本类型、病例数、靶点/信号通路、参考文献的年份与地区、参考文献标题及对应URL来源。其交互界面支持上述生物标志物相关内容的查询功能。因此，该生物标志物数据库将有助于从多维度分子类型、作用机制、作用方式及靶点中，发掘有助于卵巢癌早期诊断的生物标志物，助力卵巢癌临床治疗，提升卵巢癌患者的整体生存率。

搜集汇总

背景与挑战

背景概述

该数据集是一个卵巢癌生物标志物数据库（OCBD），旨在整合和评估研究资源，以辅助发现新的卵巢癌诊断和治疗生物标志物。数据库涵盖生物标志物的名称、分子类型、功能、敏感性等详细信息，支持查询功能，帮助从多方向探索早期诊断和治疗目标，数据量较小为73.19 KB。