Search

Uveal melanoma (UM) is the most common intraocular tumour in adults and despite surgical or radiation treatment of primary tumours, ~50% of patients progress to metastatic disease. Therapeutic options for metastatic UM are limited, with clinical trials having little impact. Here we perform whole-genome sequencing (WGS) of 103 UM from all sites of the uveal tract (choroid, ciliary body, iris). While most UM have low tumour mutation burden (TMB), two subsets with high TMB are seen; one driven by germline MBD4 mutation, and another by ultraviolet radiation (UVR) exposure, which is restricted to iris UM. All but one tumour have a known UM driver gene mutation (GNAQ, GNA11, BAP1, PLCB4, CYSLTR2, SF3B1, EIF1AX). We identify three other significantly mutated genes (TP53, RPL5 and CENPE).

Advancements in high-resolution HPLC and mass spectrometry have reinvigorated the application of this technology to identify peptides eluted from immunopurified MHC class I molecules. Three melanoma cell lines were assessed using w6/32 isolation, peptide elution and HPLC purification; peptides were identified by mass spectrometry. A total of 13,829 peptides were identified; 83-87% of these were 8-11 mers. Only approximately 15% have been described before. Subcellular locations of the source proteins showed even sampling; mRNA expression and total protein length were predictive of the number of peptides detected from a single protein. HLA-type binding prediction for 10,078 9/10 mer peptides assigned 88-95% to a patient-specific HLA subtype, revealing a disparity in strength of predicted binding. HLA-B*27-specific isolation successfully identified some peptides not found using w6/32. Sixty peptides were selected for immune screening, based on source protein and predicted HLA binding; no new peptides recognized by antimelanoma T cells were discovered. Additionally, mass spectrometry was unable to identify several epitopes targeted ex vivo by one patient's T cells., (© 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

We have used microarray gene expression profiling and machine learning to predict the presence of BRAF mutations in a panel of 61 melanoma cell lines. The BRAF gene was found to be mutated in 42 samples (69%) and intragenic mutations of the NRAS gene were detected in seven samples (11%). No cell line carried mutations of both genes. Using support vector machines, we have built a classifier that differentiates between melanoma cell lines based on BRAF mutation status. As few as 83 genes are able to discriminate between BRAF mutant and BRAF wild-type samples with clear separation observed using hierarchical clustering. Multidimensional scaling was used to visualize the relationship between a BRAF mutation signature and that of a generalized mitogen-activated protein kinase (MAPK) activation (either BRAF or NRAS mutation) in the context of the discriminating gene list. We observed that samples carrying NRAS mutations lie somewhere between those with or without BRAF mutations. These observations suggest that there are gene-specific mutation signals in addition to a common MAPK activation that result from the pleiotropic effects of either BRAF or NRAS on other signaling pathways, leading to measurably different transcriptional changes.