Spatial Transcriptomics of Patients With Kaposi Sarcoma Identifies Mechanisms of Immune Evasion

To identify the cell types that are infected with KSHV and the immune interactions in Kaposi sarcoma (KS) lesions, we performed spatial transcriptomics with seven KS skin tumors. We used a single-cell RNA-sequencing reference data set from healthy skin donors with a method to conduct spatially informed cell-type deconvolution for spatial transcriptomics. This allowed us to predict the relative amounts of each cell type within the patient sample sections. We included custom probes for five KSHV genes that allowed us to measure human and KSHV expression patterns at the same time. We then compared the spatial gene expression data of KS skin samples with six normal skin samples and found higher expression of marker genes corresponding to macrophages/dendritic cells, lymphatic endothelial cells, and vascular endothelial cells in the KS skin lesions when compared to normal skin samples. Our spatial transcriptomic results from thousands of spots across multiple KS tumors indicated a correlation between high levels of STC1 and decreased expression of macrophage markers. Together, these analyses offer potential mechanisms by which KSHV infection may remodel skin tissue, inhibit immune responses against KSHV infection, and confer resistance to anticancer therapies.

Authors

Institutions

Publication Details

Journal
Journal of Medical Virology
Published
2025-12-01
DOI
https://doi.org/10.1002/jmv.70728
Citations
1
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.81

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spatial Transcriptomics of Patients With Kaposi Sarcoma Identifies Mechanisms of Immune Evasion

Bahman Afsari, Daphne R Knudsen-Palmer, Kathryn Lurain, Joseph M. Ziegelbauer et al.
1 citations
Journal of Medical Virology
Single-cell and spatial transcriptomics
0.81
article

Spatial Transcriptomics of Patients With Kaposi Sarcoma Identifies Mechanisms of Immune Evasion

Bahman Afsari, Daphne R Knudsen-Palmer, Kathryn Lurain, Joseph M. Ziegelbauer, Robert Yarchoan, Ameera Mungale, Takanobu Tagawa, Ramya Ramaswami, Guruswamy Mahesh
article en
1 citations

Abstract

To identify the cell types that are infected with KSHV and the immune interactions in Kaposi sarcoma (KS) lesions, we performed spatial transcriptomics with seven KS skin tumors. We used a single-cell RNA-sequencing reference data set from healthy skin donors with a method to conduct spatially informed cell-type deconvolution for spatial transcriptomics. This allowed us to predict the relative amounts of each cell type within the patient sample sections. We included custom probes for five KSHV genes that allowed us to measure human and KSHV expression patterns at the same time. We then compared the spatial gene expression data of KS skin samples with six normal skin samples and found higher expression of marker genes corresponding to macrophages/dendritic cells, lymphatic endothelial cells, and vascular endothelial cells in the KS skin lesions when compared to normal skin samples. Our spatial transcriptomic results from thousands of spots across multiple KS tumors indicated a correlation between high levels of STC1 and decreased expression of macrophage markers. Together, these analyses offer potential mechanisms by which KSHV infection may remodel skin tissue, inhibit immune responses against KSHV infection, and confer resistance to anticancer therapies.

Journal of Medical VirologyVol. 97(12)
Center for Cancer Research (US)
U.S. Department of Health and Human Services, National Institutes of Health
Openalex Percentile: Top 21%
Single-cell and spatial transcriptomics
0.81
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.