Using deep learning to decipher the impact of telomerase promoter mutations on the dynamic metastatic morpholome

TL;DR

This study uses deep learning to show how specific telomerase promoter mutations in melanoma cells affect their shape and movement, with one mutation (C250T) being more aggressive than another (C228T).

Contribution

The study introduces a novel approach using isogenic clonal cell lines and deep learning to analyze the morpholomic impact of telomerase promoter mutations in melanoma.

Findings

C250T mutation causes more pronounced morphological and movement changes than C228T or wild-type cells.

TERTp mutations increase wound-healing rates and alter spatiotemporal dynamics in melanoma cells.

C250T mutation may provide a metastatic advantage through distinct morpholomic changes.

Abstract

Melanoma showcases a complex interplay of genetic alterations and intra- and inter-cellular morphological changes during metastatic transformation. While pivotal, the role of specific mutations in dictating these changes still needs to be fully elucidated. Telomerase promoter mutations (TERTp mutations) significantly influence melanoma’s progression, invasiveness, and resistance to various emerging treatments, including chemical inhibitors, telomerase inhibitors, targeted therapy, and immunotherapies. We aim to understand the morphological and phenotypic implications of the two dominant monoallelic TERTp mutations, C228T and C250T, enriched in melanoma metastasis. We developed isogenic clonal cell lines containing the TERTp mutations and utilized dual-color expression reporters steered by the endogenous Telomerase promoter, giving us allelic resolution. This approach allowed us to monitor morpholomic variations induced by these mutations. TERTp mutation-bearing cells exhibited significant morpholome differences from their wild-type counterparts, with increased allele expression patterns, augmented wound-healing rates, and unique spatiotemporal dynamics. Notably, the C250T mutation exerted more pronounced changes in the morpholome than C228T, suggesting a differential role in metastatic potential. Our findings underscore the distinct influence of TERTp mutations on melanoma’s cellular architecture and behavior. The C250T mutation may offer a unique morpholomic and systems-driven advantage for metastasis. These insights provide a foundational understanding of how a non-coding mutation in melanoma metastasis affects the system, manifesting in cellular morpholome.

This work explores how specific genetic changes, known as telomerase promoter mutations, influence the shape and behavior of melanoma cells, a highly metastatic and deadly type of skin cancer. These mutations, C228T and C250T, are common in melanoma and are thought to make the cancer more aggressive and metastatic. Cell lines with these mutations were created, and advanced imaging and deep learning techniques were used to investigate them.

We reveal that cells with the C250T mutation showed more significant cellular morphology and movement changes than cells with the C228T mutation or normal cells. This suggests that the C250T mutation might play a bigger role in helping melanoma spread throughout the body. Detailed changes due to these mutations were visualized and understood using cutting-edge technology to analyze the impact on single cells.

This work is essential because it helps illustrate how tiny genetic changes can lead to significant differences in metastatic behavior. This could lead to better ways to improve early diagnoses and treatment of metastatic melanoma. The findings provide a clearer picture of how melanoma cells evolve and spread, which could guide future cancer research and therapy development.

Figures