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  • Ocular Pathology/Oncology

    In this retrospective study, researchers compared the prognostic accuracy of gene expression profiling with tumor-node-metastasis (TNM) staging for uveal melanoma.

    Study design

    Investigators enrolled 240 patients with uveal melanoma. They performed TNM according to the American Joint Committee on Cancer standards. Patient tumors were classified as class 1 or 2 based on a commercially available, 15-gene assay (DecisionDX-UM test) and expression status of PRAME (Preferentially Expressed Antigen in Melanoma).

    Outcomes

    Gene expression profiling (GEP) detected 128 class 1 and 112 class 2 cases, of which 38 and 45 were PRAME-positive, respectively. Nearly 25% of cases had metastasis at the average follow-up of 42 months. Analysis showed that the only TNM variable that contributed prognostic information independent of gene profiling or PRAME expression was the largest basal diameter.

    A statistical model analysis revealed GEP/PRAME analysis had a superior survival curve prediction compared with TNM staging (P=3.3x10-13 vs. P=6.1x10-5). In a cohort of 45 patients without metastasis for 5 or more years, GEP/PRAME gave a lower rate of false positive “high-risk” classification compared with TNM (6.7% vs. 35.6%). A sub-analysis of tumors using largest basal diameter revealed a similar false-positive pattern.

    Limitations

    Formal analyses of gene expression profiling combined with PRAME status have not yet been conducted but will happen in upcoming studies. Furthermore, this was a single-center study and follow-up was only 29 months, and longer follow-ups would be ideal. Assessment of tumor size, including thickness, can vary from center to center and were not standardized in this study.

    Clinical significance

    Gene expression profiling is highly accurate at predicting metastasis potential and, as we learn more regarding uveal melanoma genetics and metastatic markers, should be used to individualize patient prognostication. However, staging by TNM is still a useful tool that provides dependable prognostic information in epidemiology settings.