Uveal Melanoma: Prognostication Methods

  • Sarah E. CouplandEmail author
  • Azzam Taktak
  • Antonio Eleuteri
  • Helen Kalirai
  • Sophie Thornton
  • Bertil E. Damato


Almost 50% of uveal melanoma (UM) patients develop metastatic disease, despite successful ocular treatment. Metastases usually involve the liver and only rarely respond to treatment so that most patients die within a year of onset of symptoms. There are hopes that systemic adjuvant therapy may delay or prevent metastatic disease. This requires targeting of high-risk patients, according to anatomic, histologic, and genetic predictors. Metastatic disease occurs almost exclusively in patients whose tumor shows genetic aberrations such as chromosome 3 loss, chromosome 8q gains, and BAP1 mutation. The detection of lethal genetic aberrations has become more sensitive with the development of methods such as comparative genomic hybridization, microsatellite analysis, multiplex ligation-dependent probe amplification, single-nucleotide polymorphisms, gene expression profiling, next-generation sequencing, and immunohistochemical analysis of nuclear BAP1 expression. The time from ocular treatment to the onset of metastatic disease tends to be shorter in patients with a larger, more extensive ocular tumor and a higher grade of malignancy as evidenced by epithelioid cytomorphology and higher mitotic count. Ideally, prognostication is performed by multivariable analysis using a tool such as the Liverpool Uveal Melanoma Prognosticator Online (LUMPO). Accurate prognostication enhances quality of life, especially in patients with a good prognosis. It also allows targeting of systemic surveillance and systemic adjuvant therapy in high-risk patients and enhances opportunities for research.


Prognostication FISH fluorescence in situ hybridization CGH comparative genomic hybridization MSA microsatellite analysis MLPA multiplex ligation-dependent probe amplification SNP single-nucleotide polymorphisms UM-GEP uveal melanoma gene expression profiling LOH loss of heterozygosity FFPE formalin-fixed paraffin-embedded material NGS next-generation sequencing 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Sarah E. Coupland
    • 1
    Email author
  • Azzam Taktak
    • 2
  • Antonio Eleuteri
    • 2
  • Helen Kalirai
    • 1
  • Sophie Thornton
    • 1
  • Bertil E. Damato
    • 3
  1. 1.Department of Molecular and Clinical Cancer Medicine, Institute of Translational MedicineUniversity of LiverpoolLiverpool, MerseysideUK
  2. 2.Department of Medical Physics and Clinical EngineeringRoyal Liverpool University HospitalLiverpoolUK
  3. 3.Nuffield Department of Clinical NeurosciencesUniversity of Oxford, John Radcliffe HospitalOxfordUK

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