Abstract 1215: Spatial transcriptomic analysis of primary melanomas with extreme clinical outcomes.

Abstract Introduction: Most patients that die from melanoma do so after recurrence of early stage disease. There is, therefore, an urgent need to improve the identification and management of patients with early stage melanoma at high risk of recurrence. The tumour microenvironment (TME), subclonal tumour cell intrinsic features and cellular interactions likely play key roles in melanoma recurrence. Spatial transcriptomics (ST) is optimally positioned to characterize these factors and may provide novel insights and strategies to overcome early stage melanoma recurrence. Methods: We examined 12 early stage (thick, T4b) FFPE primary melanoma samples with extreme clinical outcomes, identified from the prospectively collected Melanoma Research Victoria database. Of these, 7 patients had T4b melanoma with an unexpectedly good outcome of no recurrence ≤5 years of diagnosis and 5 patients had T4b melanoma with an expectedly poor outcome of recurrence ≤5 years of diagnosis (late and early recurrence groups, respectively). Samples were interrogated using 10X CytAssist Visium with comparisons between the two groups. Comprehensive bioinformatics analyses were performed including Bayespace and Harmony for initial spot clustering; SingleR for cluster annotation; RCTD deconvolution to refine cluster identification; edgeR on pseudo-bulk counts and gene set testing of differentially expressed genes (DEG); sscomp for differential cellular composition; SPIAT for spatial immune-tumor architecture analysis and non-negative matrix factorization (NMF) and SpaceMarkers for exploration of gene expression patterns and interacting regions. Results: Key cell types were revealed within each sample, including tumor cells, diverse immune cell subsets, fibroblasts, macrophages and keratinocytes. Tissue architecture including dermis, epidermis and invasive tumour front were well characterised. DEG identified downregulation of SLC5A10, PFKFB2, FBXO32, GABRB3, SMIM38 and CDH7 in the late group relative to the early group. Gene set analysis revealed upregulation of the hallmark hypoxia, angiogenesis, EMT, glycolysis, IL2, TNFa and TGFb pathways in the late relative to the early group. Cellular compositions varied across the two groups, with the late group having significantly lower tumour purity and higher abundance of immune cells than the early group. NMF revealed specific patterns associated with tumor and immune cells, with significant downregulation of IGHA2, CYP4X1, RBMXL3 and AIRE at the interacting region between tumor and immune cells in the late relative to the early group. Conclusion: This study is one of the first to analyze primary melanoma samples with extreme clinical outcomes using ST. Our results reveal that differences in cellular composition of primary melanomas as well as differential expression of key genes involved in immune activation, inflammation and metabolism may be associated with melanoma recurrence. Citation Format: Prachi Bhave, Marie Trussart, Anthony T. Papenfuss, Grant A. McArthur. Spatial transcriptomic analysis of primary melanomas with extreme clinical outcomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1215.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-1215
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 1215: Spatial transcriptomic analysis of primary melanomas with extreme clinical outcomes.

Grant A. McArthur, Marie Trussart, Prachi Bhave, A. T. Papenfuss
Cancer Research
Single-cell and spatial transcriptomics
article

Abstract 1215: Spatial transcriptomic analysis of primary melanomas with extreme clinical outcomes.

Grant A. McArthur, Marie Trussart, Prachi Bhave, A. T. Papenfuss
article en

Abstract

Abstract Introduction: Most patients that die from melanoma do so after recurrence of early stage disease. There is, therefore, an urgent need to improve the identification and management of patients with early stage melanoma at high risk of recurrence. The tumour microenvironment (TME), subclonal tumour cell intrinsic features and cellular interactions likely play key roles in melanoma recurrence. Spatial transcriptomics (ST) is optimally positioned to characterize these factors and may provide novel insights and strategies to overcome early stage melanoma recurrence. Methods: We examined 12 early stage (thick, T4b) FFPE primary melanoma samples with extreme clinical outcomes, identified from the prospectively collected Melanoma Research Victoria database. Of these, 7 patients had T4b melanoma with an unexpectedly good outcome of no recurrence ≤5 years of diagnosis and 5 patients had T4b melanoma with an expectedly poor outcome of recurrence ≤5 years of diagnosis (late and early recurrence groups, respectively). Samples were interrogated using 10X CytAssist Visium with comparisons between the two groups. Comprehensive bioinformatics analyses were performed including Bayespace and Harmony for initial spot clustering; SingleR for cluster annotation; RCTD deconvolution to refine cluster identification; edgeR on pseudo-bulk counts and gene set testing of differentially expressed genes (DEG); sscomp for differential cellular composition; SPIAT for spatial immune-tumor architecture analysis and non-negative matrix factorization (NMF) and SpaceMarkers for exploration of gene expression patterns and interacting regions. Results: Key cell types were revealed within each sample, including tumor cells, diverse immune cell subsets, fibroblasts, macrophages and keratinocytes. Tissue architecture including dermis, epidermis and invasive tumour front were well characterised. DEG identified downregulation of SLC5A10, PFKFB2, FBXO32, GABRB3, SMIM38 and CDH7 in the late group relative to the early group. Gene set analysis revealed upregulation of the hallmark hypoxia, angiogenesis, EMT, glycolysis, IL2, TNFa and TGFb pathways in the late relative to the early group. Cellular compositions varied across the two groups, with the late group having significantly lower tumour purity and higher abundance of immune cells than the early group. NMF revealed specific patterns associated with tumor and immune cells, with significant downregulation of IGHA2, CYP4X1, RBMXL3 and AIRE at the interacting region between tumor and immune cells in the late relative to the early group. Conclusion: This study is one of the first to analyze primary melanoma samples with extreme clinical outcomes using ST. Our results reveal that differences in cellular composition of primary melanomas as well as differential expression of key genes involved in immune activation, inflammation and metabolism may be associated with melanoma recurrence. Citation Format: Prachi Bhave, Marie Trussart, Anthony T. Papenfuss, Grant A. McArthur. Spatial transcriptomic analysis of primary melanomas with extreme clinical outcomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1215.

Cancer ResearchVol. 86(7_Supplement)
Walter and Eliza Hall Institute of Medical Research (AU), Peter MacCallum Cancer Centre (AU)
Openalex Percentile: Top 6%
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.