Clonal dynamics shaped by diverse drug-tolerant persister states in melanoma resistance
Haiyin LiiD, Yeqing CheniD, Jessica KasteriD, Maggie Dunne, Min XiaoiD, Ling Li, Monzy Thomas, Nazifa Promi, Dylan F. FingermaniD, Gregory Schuyler BrowniD, Qiuxian ZhengiD, Xingyue Zhu, McKenna Reale, Andrew PattersoniD, Le GaoiD, Xuxiang Zhang, Siqi JiangiD, Tianxing Hu, Hanzhang Fang, Jianlan ReniD, Cong QiiD, Luyang WangiD, Haiwei MouiD, Gatha ThackeriD, Eric G. Ramírez-SalazariD, , Meenhard HerlyniD
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.
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