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Clonal dynamics shaped by diverse drug-tolerant persister states in melanoma resistance

Li, H.; Chen, Y.; Kaster, J.; Dunne, M.; Xiao, M.; Li, L.; Thomas, M.; Promi, N.; Fingerman, D.; Brown, G. S.; Zheng, Q.; Zhu, X.; Reale, M.; Patterson, A.; Gao, L.; Zhang, X.; Jiang, S.; Hu, T.; Fang, H.; Ren, J.; Qi, C.; Wang, L.; Mou, H.; Thacker, G.; Salazar, E. R.; Villanueva, J.; Raj, A.; Hoon, D. S.; Bin, T.; Madzo, J.; Wei, Z.; Auslander, N.; Herlyn, M.

2025-09-19 cancer biology
10.1101/2025.09.16.676608 bioRxiv
Show abstract

Most advanced melanomas initially respond to targeted therapy but eventually relapse. Rather than acquiring new mutations, resistance is driven by drug-tolerant persister cells that enter a reversible drug-refractory state. We developed MeRLin, a high-resolution lineage tracing platform integrating cellular barcoding, single-cell transcriptomics, RNA fluorescence in situ hybridization (FISH), and computational analyses to track clonal and transcriptional dynamics in patient-derived melanoma models during prolonged therapy. Clonal dynamics revealed that persister subpopulations first responded to treatment but persisted and expanded during minimal residual disease, ultimately leading to tumor recurrence. Pre-treatment melanoma populations diversified into four conserved persister states characterized by stress-like, lipid metabolism, PI3K signaling, and extracellular matrix remodeling programs associated with adaptive resistance. Spatial transcriptomics showed the organization of these adaptive programs and a complex signaling network of autocrine and paracrine interactions among persister subpopulations. Barcoded RNA-FISH enabled spatial mapping of clonal identity and gene expression, revealing in situ co-localization of a dominant resistant clone with SLC2A1 expression. MeRLin provides a robust framework for dissecting cancer heterogeneity and identifying vulnerabilities in persister populations.

Published in Molecular Cancer (predicted rank #19) · training set

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