Integrating multi-omics data to resolve patterns of ion channel regulation in melanoma and predict tumor treatment response

Skin cutaneous melanoma (SKCM) represents a highly aggressive malignancy with rising incidence, characterized by early metastatic potential and development of treatment resistance in advanced stages. While ion channel-related genes (ICRGs) demonstrate therapeutic relevance across cancers, their role in SKCM remains incompletely defined. A comprehensive assessment of ICRG regulatory patterns was conducted in SKCM samples using single-cell spatial transcriptomic and multi-omics data. These patterns were correlated with tumor microenvironment (TME) cell infiltration characteristics to construct ICRG scores quantifying tumor-specific ICRG modification patterns. The ICRG.Gene.cluster stratifies samples into two distinct subpopulations representing divergent immune phenotypes. An ICRG scoring system is constructed based on ICRG phenotype genes and validated in independent cohorts. Through ICRG-associated gene profiling, CD8⁺ T cells are categorized into five subsets, all exhibiting significant temporal dynamics in pseudotime analysis. Spatial transcriptomics confirms prominent co-localization spots between the C3 CD8⁺ T cell subset and melanoma cells. SCENIC analysis identifies that specific ICRG genes function as target nodes regulated by transcription factors. Core ICRG genes demonstrate elevated expression in both cell lines and clinical specimens, supporting their potential role as disease-associated genetic risk loci. ICRG modification patterns provide critical insights into TME infiltration heterogeneity, enabling refined prognostic assessment and therapeutic targeting strategies.

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Publication Details

Journal
Clinical and Experimental Medicine
Published
2025-12-05
DOI
https://doi.org/10.1007/s10238-025-01866-x
Primary Topic
Ion Channels and Receptors
Type
article
Field-Weighted Citation Impact
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article

Integrating multi-omics data to resolve patterns of ion channel regulation in melanoma and predict tumor treatment response

Jiahua Xing, Muzi Chen, Mingyong Yang, Ran Tao
Clinical and Experimental Medicine
Ion Channels and Receptors
article

Integrating multi-omics data to resolve patterns of ion channel regulation in melanoma and predict tumor treatment response

Jiahua Xing, Muzi Chen, Mingyong Yang, Ran Tao
article en

Abstract

Skin cutaneous melanoma (SKCM) represents a highly aggressive malignancy with rising incidence, characterized by early metastatic potential and development of treatment resistance in advanced stages. While ion channel-related genes (ICRGs) demonstrate therapeutic relevance across cancers, their role in SKCM remains incompletely defined. A comprehensive assessment of ICRG regulatory patterns was conducted in SKCM samples using single-cell spatial transcriptomic and multi-omics data. These patterns were correlated with tumor microenvironment (TME) cell infiltration characteristics to construct ICRG scores quantifying tumor-specific ICRG modification patterns. The ICRG.Gene.cluster stratifies samples into two distinct subpopulations representing divergent immune phenotypes. An ICRG scoring system is constructed based on ICRG phenotype genes and validated in independent cohorts. Through ICRG-associated gene profiling, CD8⁺ T cells are categorized into five subsets, all exhibiting significant temporal dynamics in pseudotime analysis. Spatial transcriptomics confirms prominent co-localization spots between the C3 CD8⁺ T cell subset and melanoma cells. SCENIC analysis identifies that specific ICRG genes function as target nodes regulated by transcription factors. Core ICRG genes demonstrate elevated expression in both cell lines and clinical specimens, supporting their potential role as disease-associated genetic risk loci. ICRG modification patterns provide critical insights into TME infiltration heterogeneity, enabling refined prognostic assessment and therapeutic targeting strategies.

Clinical and Experimental MedicineVol. 26(1)
Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Chinese PLA General Hospital (CN)
Openalex Percentile: Top 61%
Ion Channels and Receptors
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Integrating multi-omics data to resolve patterns of ion channel regulation in melanoma and predict tumor treatment response — Jiahua Xing, Muzi Chen, et al. · Clinical and Experimental Medicine (2025) | TGRS Research Map | TGRS