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Predicting clinical outcome in patients diagnosed with synchronous ovarian and endometrial cancer

  • Susan J. Ramus
  • , Karim Elmasry
  • , Zhiyuan Luo
  • , Alex Gammerman
  • , Karen Lu
  • , Ayse Ayhan
  • , Naveena Singh
  • , W. Glenn McCluggage
  • , Ian J. Jacobs
  • , John C. Whittaker
  • , Simon A. Gayther

    Research output: Contribution to journal › Article › peer-review

    Abstract

    Purpose: Patients with synchronous ovarian and endometrial cancers may represent cases of a single primary tumor with metastasis (SPM) or dual primary tumors (DP).The diagnosis given will influence the patient's treatment and prognosis. Currently, a diagnosis of SPM or DP is made using histologic criteria, which are frequently unable to make a definitive diagnosis. Experimental Design: In this study, we used genetic profiling to make a genetic diagnosis of SPM or DP in 90 patients with synchronous ovarian/endometrial cancers. We compared genetic diagnoses in these patients with the original histologic diagnoses and evaluated the clinical outcome in this series of patients based on their diagnoses. Results: Combining genetic and histologic approaches, we were able make a diagnosis in 88 of 90 cases, whereas histology alone was able to make a diagnosis in only 64 cases. Patients diagnosed with SPM had a significantly worse survival than patients with DP (P = 0.002). Patients in which both tumors were of endometrioid histology survived longer than patients of other histologic subtypes (P = 0.025), and patients diagnosed with SPM had a worse survival if the mode of spread was from ovary to endometrium rather than from endometrium to ovary (P = 0.019). Conclusions: Genetic analysis may represent a powerful tool for use in clinical practice for distinguishing between SPM and DP in patients with synchronous ovarian/endometrial cancer and predicting disease outcome. The data also suggest a hitherto uncharacterized level of heterogeneity in these cases, which, if accurately defined, could lead to improved treatment and survival. © 2008 American Association for Cancer Research.
    Original languageEnglish
    Pages (from-to)5840-5848
    Number of pages8
    JournalClinical Cancer Research
    Volume14
    Issue number18
    DOIs
    Publication statusPublished - 15 Sept 2008

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

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