Biomarkers and Early Detection Strategies of Ovarian Cancer
A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Human Genomics and Genetic Diseases".
Deadline for manuscript submissions: closed (15 May 2024) | Viewed by 460
Special Issue Editors
Interests: ovarian cancer; early detection; angiogenesis; lymphangiogenesis; ovarian function
Interests: DNA repair; Fanconi proteins; FANCD2; chemo-resistance; ovarian cancer early detection; ovarian cancer
Special Issue Information
Dear Colleagues,
Ovarian cancer (OC) is the deadliest of all gynecologic malignancies. The 5-year relative survival rate is 92.4% if the disease is diagnosed at the localized (early) stage; however, this decreases to 31.5% when diagnosed at the distant (late) stage. Approximately 70% of patients with OC are diagnosed at advanced stages, which are associated with poor prognosis and low survival rate.
Early detection is critical to achieve a high cure rate for OC patients. Biomarkers have been rapidly emerging for OC, e.g., CA125, HE4, miR-126, and miR-200a. However, an effective strategy for OC early detection is not available currently. Low specificity and high false-positive rates represent limitations of screening programs. Ongoing studies are attempting to identify effective specific biomarkers and screening strategies requiring a single biomarker or a combination of multiple biological measures.
The manuscripts that will be considered for this Special Issue include original research articles and reviews. Studies conducted using cell/tissue culture systems, vertebrate animal models, or human subjects are welcome. The goal is to increase our knowledge of molecular mechanisms, cellular events, and pathological parameters in OC development and metastases. Findings will provide valuable insights into OC pathology, facilitating diagnosis and treatment and the development of early-detection strategies.
Dr. Fuhua Xu
Dr. Tanja Pejovic
Dr. Jing Xu
Guest Editors
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Keywords
- ovarian cancer
- biomarker
- early detection
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