Abstract
Purpose :
Uveal melanoma (UM) mortality remains high despite advances in our understanding of genetics and tumor biology. To further elucidate the complexity of pathways involved in UM, we use a comprehensive analysis of human tissue, clinical data, and computational analysis. We describe our methods and results.
Methods :
We examined 9 enucleated eyes from patients with UM. Clinical data was recorded. Hematoxylin and eosin staining was performed to analyze tumor surface and pigmentation (light, moderate, heavy). A PanCancer Immune Profiling Panel by Nanostring with ROSALIND platform analysis identified candidate genes. The expression of each gene was compared to the survival plot from OncoDB from The Cancer Genome Atlas Program (TCGA). IRF4, STAT3, ANGPTL4, IKBKE genes were selected for spatial localization by 4-plex RNAscopeTM in-situ hybridization (RNA-ISH) and confocal microscopy.
Results :
All 9 patients (5 males) were Caucasian with a median age of 60 years (range 50 to 75). Five eyes were primarily enucleated eyes and 4 had primary plaque brachytherapy. cAJCC classification was cT1 = 1, cT2 = 2, and cT3 = 6. Median tumor surface was 16% (range 5 to 46). Pigmentation was graded as light = 4, moderate = 4, and heavy = 1. After comparisons among molecular signature and clinical data, significant differential expression (+1.3 to -1.3, p <0.05) of genes was obtained (Figure 1). Higher levels of expression of IRF4, STAT3, ANGPTL4, and IKBKE were found on tumors compared to normal choroid, and non-uveal tissue (Figure 2).
Conclusions :
We integrate diverse methodologies to understand tumor biology and tumor microenvironment in UM. Through multi-omics analysis, we identified candidate genes and validated their localization using multiplexed imaging. This approach provides invaluable insights into the heterogeneity of gene expression across tissues, bridging molecular findings with clinical relevance. Such an integrative strategy represents a critical advancement in translational applications, addressing challenges posed by UM.
This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.