Deciphering Melanoma Evolution: Insights into Phylogeny and Structural Variants for Precision Medicine

Authors

• SL Shumaker
• SA Kotler
• KA Butler
• JC Klein
• DR Calabrese
• GY Gomba
• KM Wilson
• CA LeClair

Abstract

Melanoma exhibits extensive intratumoral heterogeneity and complex evolutionary dynamics. To investigate subclonal dynamics, we established a novel model system comprised of 24 single cell-derived clonal sublines (C1-C24) from a melanoma model, M4, which was created from the genetically engineered HGF-transgenic mouse. We used Trisicell, a computational toolkit for intratumor heterogeneity evaluation from single-cell RNA mutations, to build the phylogeny tree. The result revealed the evolutionary patterns of melanoma, with ancestral clones giving rise to genetically distinct subclones. Using long-read sequencing, we identified the structural variants (SVs), including deletion/insertion, amplification, translocation, fusion gene, etc. Through the pattern of gene disruption by the structural variants specific to individual sublines or shared between/among sublines, we can understand the roles of different during melanoma’s progression. The preliminary data from four sublines showed that the SVs shared by all sublines, representing ancestral events, were significantly more than the subline-specific SVs, representing the later events. Interestingly, the individual sublines exhibited a higher ratio of disrupted genes by SVs, suggesting the possibility of functional selection. In chromosomes, the SVs shared among all the sublines are associated with genes enriched in the cell growth pathways, such as Kras, Myc, Pik3r1, etc. Interestingly, genes disrupted by SVs are enriched in pathways of tissue differentiation, especially neural developmental genes. These results shed light on the genetic conditions that can predispose individual melanocytes to melanomagenesis and could uncover relationships between progression and resistance to therapy. Further analysis is ongoing to delineate SVs on the whole mutation-based phylogeny of all sublines.

Scientific Focus Area: Cancer Biology

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