bioRxivImmunologyPreprint
Single-cell and spatial atlas of steatotic liver-related hepatocellular carcinoma
Aldo PrawiraiD, Hang XuiD, Wei Qiang LeowiD, Masayuki OtsukaiD, Ziyao CheniD, Mohammad RahbariiD, Sharifah Nur HazirahiD, Martin WasseriD, Alexander Yaw Fui ChungiD, Brian K. P. GohiD, Pierce K. H. ChowiD, Salvatore AlbaniiD, Joycelyn Jie Xin LeeiD, Tony K.H. Lim, Weiwei ZhaiiD, Yock Young DaniD, George Boon‐Bee GohiD, David Wai-Meng TaiiD, Ramanuj DasGuptaiD, Mathias F HeikenwälderiD, Jinmiao CheniD, Valerie ChewiD
Abstract
Steatotic liver disease-related hepatocellular carcinoma (SLD-HCC) poses significant challenges in liver cancer management. Our current study investigates the tumor microenvironment (TME) of SLD-HCC using single-cell transcriptomic, proteomic and spatial transcriptomic analyses. We identified altered immune-related and lipid metabolism pathways, particularly in regulatory T cells (Tregs) and cancer-associated fibroblasts (CAFs) within the SLD-HCC microenvironment, suggesting distinct cellular adaptations to a high-fat TME and general immunosuppression. Cytometry by time-of-flight revealed a cold and immunosuppressive TME depleted with CD8+ T cells and enriched with Tregs, while spatial transcriptomics uncovered a unique spatial architecture with Treg/CAF clusters specifically located at the tumor margins in SLD-HCC. Crucially, we identified Treg-CAF interactions as a key mediator associated with lack of response to immunotherapy in SLD-HCC. Our findings highlight the intricate immune dynamics of SLD-HCC, indicating potential therapeutic targets to counteract immune evasion and restore anti-tumor immunity in SLD-HCC. HighlightsO_LIThe TME of SLD-HCC exhibits altered immune and lipid pathways C_LIO_LIImmunosuppressive SLD-HCC TME is depleted with CD8+ T cells and enriched with Tregs C_LIO_LISLD-HCC has a unique spatial architecture with Treg-CAF clusters at tumor margins C_LIO_LITreg-CAF interaction via TNFSF14-TNFRSF14 axis mediates immunotherapy resistance C_LI
- organism: human
- assay: scRNA-seq
- assay: proteomics
- assay: spatial transcriptomics
- research focus: cell type annotation
- research focus: cell-cell communication
- research focus: spatial domain detection
- approach: deep learning
- approach: statistical model
- Citations
- 1
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