Early detection and treatment of ovarian cancer: shifting from early stage to minimal volume of disease based on a new model of carcinogenesis.

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This paper proposes a new ovarian carcinogenesis model classifying tumors into type I and II to argue that screening should focus on minimal disease volume rather than early stage to better detect aggressive type II neoplasms.

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Abstract

The goal of ovarian cancer screening is to detect disease when confined to the ovary (stage I) and thereby prolong survival. We believe this is an elusive goal because most ovarian cancer, at its earliest recognizable stage, is probably not confined to the ovary. We propose a new model of ovarian carcinogenesis based on clinical, pathological, and molecular genetic studies that may enable more targeted screening and therapeutic intervention to be developed. The model divides ovarian cancer into 2 groups designated type I and type II. Type I tumors are slow growing, generally confined to the ovary at diagnosis and develop from well-established precursor lesions so-called borderline tumors. Type I tumors include low-grade micropapillary serous carcinoma, mucinous, endometrioid, and clear cell carcinomas. They are genetically stable and are characterized by mutations in a number of different genes including KRAS, BRAF, PTEN, and beta-catenin. Type II tumors are rapidly growing, highly aggressive neoplasms that lack well-defined precursor lesions; most are advanced stage at, or soon after, their inception. These include high-grade serous carcinoma, malignant mixed mesodermal tumors (carcinosarcomas), and undifferentiated carcinomas. The type II tumors are characterized by mutation of TP53 and a high level of genetic instability. Screening tests that focus on stage I disease may detect low-grade type I neoplasms but miss the more aggressive type II tumors, which account for most ovarian cancers. A more rational approach to early detection of ovarian cancer should focus on low volume rather than low stage of disease.

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last seen: 2026-08-23T09:30:01.253652+00:00