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Single-cell trajectories of melanoma cell resistance to targeted treatment

OBJECTIVE: Cellular heterogeneity is regarded as a major factor affecting treatment response and resistance in malignant melanoma. Recent developments in single-cell sequencing technology have provided deeper insights into these mechanisms. METHODS: Here, we analyzed a BRAF(V600E)-mutant melanoma ce...

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Detalles Bibliográficos
Autores principales: Schmidt, Maria, Mortensen, Lena Sünke, Loeffler-Wirth, Henry, Kosnopfel, Corinna, Krohn, Knut, Binder, Hans, Kunz, Manfred
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Compuscript 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8763000/
https://www.ncbi.nlm.nih.gov/pubmed/34591417
http://dx.doi.org/10.20892/j.issn.2095-3941.2021.0267
Descripción
Sumario:OBJECTIVE: Cellular heterogeneity is regarded as a major factor affecting treatment response and resistance in malignant melanoma. Recent developments in single-cell sequencing technology have provided deeper insights into these mechanisms. METHODS: Here, we analyzed a BRAF(V600E)-mutant melanoma cell line by single-cell RNA-seq under various conditions: cells sensitive to BRAF inhibition with BRAF inhibitor vemurafenib and cells resistant to BRAF inhibition with vemurafenib alone or vemurafenib in combination with the MEK1/2 inhibitors cobimetinib or trametinib. Dimensionality reduction by t-distributed stochastic neighbor embedding and self-organizing maps identified distinct trajectories of resistance development clearly separating the 4 treatment conditions in cell and gene state space. RESULTS: Trajectories associated with resistance to single-agent treatment involved cell cycle, extracellular matrix, and de-differentiation programs. In contrast, shifts detected in double-resistant cells primarily affected translation and mitogen-activated protein kinase pathway reactivation, with a small subpopulation showing markers of pluripotency. These findings were validated in pseudotime analyses and RNA velocity measurements. CONCLUSIONS: The single-cell transcriptomic analyses reported here employed a spectrum of bioinformatics methods to identify mechanisms of melanoma resistance to single- and double-agent treatments. This study deepens our understanding of treatment-induced cellular reprogramming and plasticity in melanoma cells and identifies targets of potential relevance to the management of treatment resistance.