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Multi-omics identifies the link between intratumor steatosis and exhausted tumor immune microenvironment in hepatocellular carcinoma

ABSTRACT: Multi-omics identifies the link between intratumor steatosis and exhausted tumor immune microenvironment in hepatocellular carcinoma

PROVIDER: PRJNA789195 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR17237400.fastq.gz	Fastqsanger.gz
	SRR17237401.fastq.gz	Fastqsanger.gz
	SRR17237402.fastq.gz	Fastqsanger.gz
	SRR17237403.fastq.gz	Fastqsanger.gz
	SRR17237404.fastq.gz	Fastqsanger.gz

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Multi-omics identifies the link between intratumor steatosis and exhausted tumor immune microenvironment in hepatocellular carcinoma

Project description:Immunotherapy becomes standard-of-care treatment of hepatocellular carcinoma (HCC) but still limited number of patients benefit from immunotherapy due to the high heterogeneity of tumor immune-microenvironment (TIME) of HCC patients. Therefore, it is important to stratify patients who benefit from immunotherapy by analyzing the molecular and immunological diversity of HCC. Since non-viral HCC is rapidly increasing all over the world, in this study, we focused on non-viral HCC and aimed to identify immunotherapy-susceptible patients through multi-omics. Global RNA sequencing of surgically-resected tumor tissues in 113 non-viral HCC patients was performed. Unsupervised hierarchical clustering classified non-viral HCCs into 3 molecular classes associated with patient prognosis and corresponding driver gene abnormality. We further identified the immune-enriched but -exhausted subclass with intratumor steatosis in non-viral HCCs, characterized by T-cell exhaustion, infiltration of M2 macrophage and cancer-associated fibroblast (CAF), high PD-L1 expression, and TGF-β signaling activation..

2022-05-22 | GSE190967 | GEO

Multiomics identifies the link between intratumor steatosis and the exhausted tumor immune microenvironment in hepatocellular carcinoma.

Project description:Background and aimsImmunotherapy has become the standard-of-care treatment for hepatocellular carcinoma (HCC), but its efficacy remains limited. To identify immunotherapy-susceptible HCC, we profiled the molecular abnormalities and tumor immune microenvironment (TIME) of rapidly increasing nonviral HCC.Approaches and resultsWe performed RNA-seq of tumor tissues in 113 patients with nonviral HCC and cancer genome sequencing of 69 genes with recurrent genetic alterations reported in HCC. Unsupervised hierarchical clustering classified nonviral HCCs into three molecular classes (Class I, II, III), which stratified patient prognosis. Class I, with the poorest prognosis, was associated with TP53 mutations, whereas class III, with the best prognosis, was associated with cadherin-associated protein beta 1 (CTNNB1) mutations. Thirty-eight percent of nonviral HCC was defined as an immune class characterized by a high frequency of intratumoral steatosis and a low frequency of CTNNB1 mutations. Steatotic HCC, which accounts for 23% of nonviral HCC cases, presented an immune-enriched but immune-exhausted TIME characterized by T cell exhaustion, M2 macrophage and cancer-associated fibroblast (CAF) infiltration, high PD-L1 expression, and TGF-β signaling activation. Spatial transcriptome analysis suggested that M2 macrophages and CAFs may be in close proximity to exhausted CD8+ T cells in steatotic HCC. An in vitro study showed that palmitic acid-induced lipid accumulation in HCC cells upregulated PD-L1 expression and promoted immunosuppressive phenotypes of cocultured macrophages and fibroblasts. Patients with steatotic HCC, confirmed by chemical-shift MR imaging, had significantly longer PFS with combined immunotherapy using anti-PD-L1 and anti-VEGF antibodies.ConclusionsMultiomics stratified nonviral HCCs according to prognosis or TIME. We identified the link between intratumoral steatosis and immune-exhausted immunotherapy-susceptible TIME.

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Single-cell RNA-seq of human breast tumor samples with exhausted and non-exhausted immune environments

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Interconnected lineage trajectories link conventional and NK-like exhausted CD8+ T cells beneficial in T1D [P452_3]

Project description:Interconnected lineage trajectories link conventional and NK-like exhausted CD8+ T cells beneficial in T1D [P452_3]

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Interconnected lineage trajectories link conventional and NK-like exhausted CD8+ T cells beneficial in T1D [P362-1]

Project description:Interconnected lineage trajectories link conventional and NK-like exhausted CD8+ T cells beneficial in T1D [P362-1]

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Transcription profiling of mouse naive, effector, memory and exhausted virus-specific CD8 T cells after chronic viral infection

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Spatially Annotated Single Cell Sequencing for Unraveling Intratumor Heterogeneity

Project description:Intratumor heterogeneity is a major obstacle to effective cancer treatment. Current methods to study intratumor heterogeneity using single-cell RNA sequencing (scRNAseq) lack information on the spatial organization of cells. While state-of-the art spatial transcriptomics methods capture the spatial distribution, they either lack single cell resolution or have relatively low transcript counts. Here, we introduce spatially annotated single cell sequencing, based on the previously developed functional single cell sequencing (FUNseq) technique, to spatially profile tumor cells with deep scRNA-seq and single cell resolution. Using our approach, we profiled cells located at different distances from the center of a 2D epithelial cell mass. By profiling the cell patch in concentric bands of varying width, we showed that cells at the outermost edge of the patch responded strongest to their local microenvironment, behaved most invasively, and activated the process of epithelial-to-mesenchymal transition (EMT) to migrate to lowconfluence areas. We inferred cell-cell communication networks and demonstrated that cells in the outermost ~10 cell wide band, which we termed the invasive edge, induced similar phenotypic plasticity in neighboring regions. Applying FUNseq to spatially annotate and profile tumor cells enables deep characterization of tumor subpopulations, thereby unraveling the mechanistic basis for intratumor heterogeneity.

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