Spatial and Single-Cell Multi-Omics Analyses of T-Cell Subsets and Interactions in Melanoma Lymph Node Metastasis.
4 affiliations
- 1Faculty of Medicine, Universiti Sultan Zainal Abidin, Kuala Terengganu, Malaysia.
- 2Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
- 3QIMR Berghofer, Brisbane, Queensland, Australia.
- 4Frazer Institute, The University of Queensland, Brisbane, Queensland, Australia.
Abstract
Melanoma is a highly immunogenic malignancy, yet responses to systemic therapy remain variable. The tumour-draining lymph node (TDLN), including the sentinel lymph node (SLN) during early regional spread, is not only a site of metastatic dissemination but also an important setting for T-cell priming and immune regulation. Conventional classification of nodes as tumour-positive or tumour-negative provides essential staging information but reveals little about their immune state. Single-cell immune transcriptomics, T-cell receptor sequencing and single-cell epigenomics now allow T-cell states, clonal dynamics and regulatory programmes to be examined in greater detail. Spatial transcriptomics, multiplex imaging, spatial proteomics and emerging spatial metabolomics add the anatomical context needed to determine where these cells and molecular programmes occur within the intact tissue architecture. In this review, we examine how these approaches are being utilised to study T-cell heterogeneity, spatial organisation and immune interactions within melanoma TDLNs, together with the emerging contribution of artificial intelligence (AI)-assisted pathology. We also critically evaluate how these technologies are applied, with attention to tissue requirements, spatial resolution, molecular coverage, computational demands, scalability to archival haematoxylin and eosin (H&E) imaging cohorts and careful interpretation of predicted or inferred spatial features. By combining biological profiling with methodological appraisal, we highlight how multi-omics immune signatures may refine nodal disease assessment and guide future biomarker development, while noting that clinical translation will require standardised analytical pipelines and disease-specific validation across independent melanoma cohorts.
Related
- Spatiotemporal lineage tracing reveals the dynamic spatial architecture of tumor growth and metastasis
- From liquid biopsy to spatial liquid biopsy: extracellular vesicles as molecular maps of cancer metastasis
- Spatial multi-omics analyses of the tumor immune microenvironment: advances and novel therapeutic avenues.
- Single-cell multi-omics reveals archetypal regulatory programs shared across T cell subsets
- PPARγ: a transfactor for Th-cell subsets
BibTeX
@article{ramli2026spatial,
title = {{Spatial and Single-Cell Multi-Omics Analyses of T-Cell Subsets and Interactions in Melanoma Lymph Node Metastasis.}},
author = {Ras Azira Ramli and Samuel Tan and Yibi Chen and Glen Boyle and Quan Nguyen},
journal = {Experimental dermatology},
year = {2026},
month = oct,
doi = {10.1111/exd.70376},
url = {https://europepmc.org/article/MED/42876116},
note = {CC BY},
}
RIS
TY - JOUR
TI - Spatial and Single-Cell Multi-Omics Analyses of T-Cell Subsets and Interactions in Melanoma Lymph Node Metastasis.
AU - Ras Azira Ramli
AU - Samuel Tan
AU - Yibi Chen
AU - Glen Boyle
AU - Quan Nguyen
PY - 2026
DA - 2026/10/01
JO - Experimental dermatology
DO - 10.1111/exd.70376
UR - https://europepmc.org/article/MED/42876116
AB - Melanoma is a highly immunogenic malignancy, yet responses to systemic therapy remain variable. The tumour-draining lymph node (TDLN), including the sentinel lymph node (SLN) during early regional spread, is not only a site of metastatic dissemination but also an important setting for T-cell priming and immune regulation. Conventional classification of nodes as tumour-positive or tumour-negative provides essential staging information but reveals little about their immune state. Single-cell immune transcriptomics, T-cell receptor sequencing and single-cell epigenomics now allow T-cell states, clonal dynamics and regulatory programmes to be examined in greater detail. Spatial transcriptomics, multiplex imaging, spatial proteomics and emerging spatial metabolomics add the anatomical context needed to determine where these cells and molecular programmes occur within the intact tissue architecture. In this review, we examine how these approaches are being utilised to study T-cell heterogeneity, spatial organisation and immune interactions within melanoma TDLNs, together with the emerging contribution of artificial intelligence (AI)-assisted pathology. We also critically evaluate how these technologies are applied, with attention to tissue requirements, spatial resolution, molecular coverage, computational demands, scalability to archival haematoxylin and eosin (H&E) imaging cohorts and careful interpretation of predicted or inferred spatial features. By combining biological profiling with methodological appraisal, we highlight how multi-omics immune signatures may refine nodal disease assessment and guide future biomarker development, while noting that clinical translation will require standardised analytical pipelines and disease-specific validation across independent melanoma cohorts.
SN - 0906-6705
SN - 1600-0625
ER -