Spatiotemporal Profiling Defines Persistence and Resistance Dynamics during Targeted Treatment of Melanoma.
Document Type
Article
Publication Date
3-3-2025
Original Citation
Rubinstein J,
Domanskyi S,
Sheridan T,
Sanderson B,
Park S,
Kaster J,
Li H,
Anczuków O,
Herlyn M,
Chuang J.
Spatiotemporal Profiling Defines Persistence and Resistance Dynamics during Targeted Treatment of Melanoma. Cancer Res. 2025;85(5):987-1002.
Keywords
JGM, SS1, Melanoma, Humans, Drug Resistance, Neoplasm, Animals, Mice, Proto-Oncogene Proteins B-raf, Xenograft Model Antitumor Assays, Cell Proliferation, Molecular Targeted Therapy, Cell Line, Tumor, Transcriptome, Spatio-Temporal Analysis
JAX Source
Cancer Res. 2025;85(5):987-1002.
ISSN
1538-7445
PMID
39700408
DOI
https://doi.org/10.1158/0008-5472.CAN-24-0690
Grant
Work performed by the M. Herlyn group was supported by the following grants: U54CA4224070, P01CA114046, P50CA261608, R01CA258113, and the Dr. Miriam and Sheldon Adelson Foundation. Work performed by the J.H. Chuang group was sup- ported by R01 CA230031 and U24CA224067. We support inclusive, diverse, and equitable conduct of research.
Abstract
Resistance of BRAF-mutant melanomas to targeted therapy arises from the ability of cells to enter a persister state, evade treatment with relative dormancy, and repopulate the tumor when reactivated. A better understanding of the temporal dynamics and specific pathways leading into and out of the persister state is needed to identify strategies to prevent treatment failure. Using spatial transcriptomics in patient-derived xenograft models, we captured clonal lineage evolution during treatment. The persister state showed increased oxidative phosphorylation, decreased proliferation, and increased invasive capacity, with central-to-peripheral gradients. Phylogenetic tracing identified intrinsic and acquired resistance mechanisms (e.g., dual-specific phosphatases, reticulon-4, and cyclin-dependent kinase 2) and suggested specific temporal windows of potential therapeutic susceptibility. Deep learning-enabled analysis of histopathologic slides revealed morphologic features correlating with specific cell states, demonstrating that juxtaposition of transcriptomics and histologic data enabled identification of phenotypically distinct populations from using imaging data alone. In summary, this study defined state change and lineage selection during melanoma treatment with spatiotemporal resolution, elucidating how choice and timing of therapeutic agents will impact the ability to eradicate resistant clones. Significance: Tracking clonal progression during treatment uncovers conserved, global transcriptional changes and local clone-clone and spatial patterns underlying the emergence of resistance, providing insights into therapy-induced tumor evolution.