Recent developments in prognostic and predictive testing in uveal melanoma

Abstract

Purpose of review: To provide an update on the rapidly evolving methods for assessing prognosis and predicting response to targeted molecular therapy in uveal melanoma.

Recent findings: The techniques for assessing prognosis in uveal melanoma have evolved from simple physical features, such as tumor size, location, and cell morphology, to the slightly more sophisticated counting of chromosomal gains and losses. More recently, gene expression profiling has provided a highly accurate and biologically informative gold standard for molecular prognostication. The latest step in the evolution of molecular testing has been the recent discovery of major driver mutations that allow predictive testing of response to targeted molecular therapies. Mutations in GNAQ and GNA11 are early events that promote cell proliferation, and these mutations are sensitive to MAPK kinase, PKC, and AKT inhibitors. Mutations in BAP1, SF3B1, and EIF1AX are later events that are largely mutually exclusive. Mutations in BAP1 are strongly associated with metastasis, whereas those in SF3B1 and EIF1AX are associated with good prognosis. Uveal melanomas with BAP1 mutations demonstrate sensitivity to epigenetic modulators, such as histone deacetylase inhibitors. Clinical trials are now available to evaluate the efficacy of these targeted molecular agents in patients with uveal melanoma.

Summary: Molecular prognostic testing and enrollment of high-risk patients into clinical trials of targeted molecular therapy are rapidly becoming the standard of care in the management of uveal melanoma.

FIGURE 1

Flow diagram demonstrating how prognostic and predictive testing in uveal melanoma can guide patient care. Following diagnosis of uveal melanoma, prognostic testing determines metastatic risk, which in turn determines the intensity of metastatic surveillance and whether the patient should be offered entry into a clinical trial of adjuvant systemic therapy. In clinical trials of adjuvant therapy in high-risk patients and in patients with overt metastatic disease, predictive testing can be used to guide the choice of therapy and to assess response to therapy.