Uveal melanoma (UM) is highly resistant to current therapies. We hypothesize that precursors of metastatic UM cells are present at a small level in the primary tumor. The level of the mutation bearing cells is related to tumor heterogeneity implying the presence of multiple clones with different mutation spectrums. These cells evolve over time as a function of therapy and a variety of host factors. We will use the methods of next generation sequencing to take an unbiased look at the whole exome followed by cancer exome of multiple tumor genomes. The first objective is to define the somatic mutation profile of metastatic UM and compare the profiles of matched primary and metastatic lesions to see which mutations are selected in the metastatic lesions. In addition, identify mutations in known cancer associated genes, which may be present at very high (common) or low levels (rare), in the primary tumor and selected in metastatic UM. The second objective is to compare the mutation profiles of different sections of the same tumors selected based on the size and cell type profiles. This will detect different frequencies of mutations, if present, in the sections and defie intra-tumor heterogeneity. The third objective is to compare identified intra-tumor heterogeneity to other known genetic, clinical and histological features of the tumor as prognostic markers. The clinical relevance can be the knowledge that one biopsy of a large tumor does not provide enough information about the array of mutations present to design clinical trials or treatments based on the genetic profile of the tumor. In addition, the results may lead to novel therapeutic targets in UM.
Clinical Relevance of the proposed work Uveal melanoma is an adult onset ocular cancer with significant morbidity. About 50% of individuals develop metastasis and metastatic uveal melanoma is resistant to therapy. It is possible that the signature of future metastasis is present in the primary tumor as low level mutations in cancer associated genes. By using next generation sequencing technology, it is possible to undertake an unbiased look at the entire cancer exome of many tumor genomes for both common and rare mutations in a cost effective and timely fashion. We expect that this project will lead to improved classification of UM cases with respect to future risk of metastasis based on mutation signatures and enhance recruitment of patients into individual arms of any clinical trial based on mutation signatures. Currently there are ongoing clinical trials where the assignment of patients included in the trial to different arms of the trial is based on GNAQ/GNA11 mutation status. If tumor heterogeneity is present in UM tumors, then results of GNAQ/GNA11 testing on a single biopsy can be misleading and offset the outcome of the hypothesis to be tested. Therefore it will be important to study tumor heterogeneity in the context of UM primary tumors as well as metastatic tumors to establish guidelines for future testing prior to inclusion in clinical trials.
|Vaquero-Garcia, Jorge; Lalonde, Emilie; Ewens, Kathryn G et al. (2017) PRiMeUM: A Model for Predicting Risk of Metastasis in Uveal Melanoma. Invest Ophthalmol Vis Sci 58:4096-4105|