Dataset Information
Development and validation of gene expression-based signature for high-grade serous ovarian cancer.
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ABSTRACT:
SUBMITTER: Vaicekauskaite I
PROVIDER: S-EPMC12918079 | biostudies-literature | 2026 Jan
REPOSITORIES: biostudies-literature
Publications
Development and validation of gene expression-based signature for high-grade serous ovarian cancer.
Journal of ovarian research 20260127 1
BACKGROUND: High-grade serous ovarian cancer (HGSOC) is the second most lethal gynecologic malignancy, often diagnosed at a late stage due to the lack of reliable early detection strategies. Currently, there are no specific diagnostic or prognostic biomarkers for ovarian cancer (OC). Thus, there is a great need for novel validated biomarkers for OC diagnosis. METHODS: A two-step machine learning approach was employed to identify potential HGSOC biomarkers in The Cancer Genome Atlas (TCGA) and Ge ...[more]