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.
