A cross-scale multimodal framework identifies clinically actionable immunotherapy biomarkers in melanoma through bulk to single-cell and spatial transcriptomics integration
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Key Points
Two melanoma subtypes were identified, each with unique biological characteristics and implications for treatment.
The CMLS prognostic model leveraged six genes to categorize patients into high and low-risk groups for immunotherapy response.
Integration of single-cell and spatial transcriptomics provided insights into the tumor microenvironment dynamics.
Findings suggest a framework for personalizing melanoma treatments and improving patient prognosis.
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Implication
This analysis highlights distinct melanoma molecular subtypes and their implications for immunotherapy outcomes.