Project Overview

In this project, we integrated spatial transcriptomics, spatial metabolomics, single-cell transcriptomics and bulk RNA-seq data to identify the metabolic-transcriptomic features on tumor foci and tumor capsule in Microvascular Invasion HCC

Analysis workflow

📝Figure1: Spatial transcriptomics analysis

• Unsupervised clustering, Differentially Expressed Genes(DEGs) , Pathological annotation, Cell percent ratio, RCTD cell type deconvolution, Cell type spatial co-localization, Spatial region division

📝Figure2: Spatial metabolomics analysis

• Unsupervised clustering, Pathological annotation, Differentially Expressed Metabolites(DEMs), Metabolic cluster correlation, Distribution of Metabolites

📝Figure3: Integrated Multi-omics analysis

• DEGs, Marker gene expression, KEGG pathway enrichment, Spatial gene expression scoring , Phenotypic association analysis, Unsupervised clustering, Comparison of DEGs

📝Figure4: MVI associated analysis

• Pathway activity analysis, AFP-MVI correlation analysis, Clinical stage analysis, Treatment response analysis

📝Figure5: Clinical relevance analysis

• Marker gene expression, Random Forest model, Clinical indicator distribution, Cell subtype proportion, Disease-free survival (DFS) and overall survival (OS) analysis

📝Figure6: Metabolic reprogramming analysis

• Metabolic Score, Spatial distribution of metabolic scoring, Spatial expression of enzyme genes, Spatial intensity mapping of metabolites, Overall survival (OS) analysis

📝Figure7: Spatial microenvironment analysis

• Identification of tumor capsule and boundary, Cell type deconvolution, KEGG enrichment, CAF subtype scoring, Overall survival (OS) analysis

SessionInfo

R version 4.1.3 (2022-03-10)

Platform: x86_64-conda-linux-gnu (64-bit) Running under: CentOS Linux 7 (Core)

R software version

Seurat_4.3.0 , SeuratObject_4.1.3 , Matrix_1.5-4.1, sctransform_0.4.1, harmony_1.2.0, spacexr_2.2.1, mistyR_1.10.1 , Scissor_2.0.0, clusterProfiler_4.8.3, GSVA_1.48.3 , ggplot2_3.4.4 , ggpubr_0.6.0 , pheatmap_1.0.12 , infercnv_1.19.1 , GSEABase_1.62.0 , patchwork_1.1.3 , randomForest_4.7-1.1, Cardinal_3.0.1, survival_3.8-3, MetaboDiff_0.9.5, ComplexHeatmap_2.15.2, CellChat_2.1.1, devil_0.1.0

Data access

Generated in this study

Spatial transcriptomics data:

🔗 https://ngdc.cncb.ac.cn/gsa-human/browse/HRA011344

Spatial metabolomics data:

🔗 https://ngdc.cncb.ac.cn/omix/release/OMIX006935

Public data

scRNA-Seq data:

✅ Gene Expression Omnibus (GSE149614 and GSE242889)

✅ National Genomics Data Center (HRA001748)

Spatial transcriptomics data:

✅ National Genomics Data Center (HRA000437)

bulk RNA-seq data:

✅ UCSC Xena (the TCGA-LIHC, IGCG-LIHC)

✅ Gene Expression Omnibus (GSE14520, GSE40873 & GSE54236)