ovarian cancer - search results

Researchers have identified three different evolutionary states in tumors from patients with ovarian high-grade serous carcinoma (HGSC) that are characterized by distinct signaling pathways and associated with treatment response.

Presenting at the annual AACR meeting, researchers have identified the B7-H4 protein as a promising target for recurrent ovarian cancer.

Quiescent ovarian cancer cells, which are characterized by very slow growth, overexpress a normal ovarian protein called follistatin, which signals to local cancer cells to grow more slowly and evade killing by chemotherapy.

Data on over-the-counter (OTC) medicine purchases could spot ovarian cancer earlier, according to new research from a team in the U.K.

Researchers from the University of Pittsburgh Swanson School of Engineering were awarded a grant to determine the biology behind cell interactions that cause ovarian cancer to metastasize.

Short-term surveillance can help improve outcomes and treatment costs before preventive surgery in women at high-risk for ovarian cancer.

Known as MAGIC (Malignancy Assessment using Gene Identification in Captured Cells), the algorithm achieved a sensitivity for detecting epithelial ovarian cancer of 95% and an accuracy of 83% for detecting the disease.

Scientists from the University of California (UC), San Diego, and their collaborators have demonstrated how key proteins act together to suppress antitumor activity in high-grade serous ovarian carcinoma (HGSOC) in a mouse model, revealing a new combinatorial strategy to treat this intractable malignancy.

Researchers have uncovered how tumor cells interact with the immune system in ovarian cancer. Utilizing highly multiplex immunofluorescence and image analysis, they investigated how the genetic characteristics of ovarian cancer shape how tumor and immune cells communicate with each other.

The fallopian tube-based organoids may help predict which individuals with BRCA-1 mutations will develop ovarian cancer years or even decades in advance, and could be used to develop personalized therapies.