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case_images: The expression of genes involved in mucin and mucopolysaccharide biosynthesis is up-regulating in IMCC. KEGG analysis identified the main enriched signaling pathways of up-regulated genes (A) and of down-regulated genes (B) in IMCC. Gene enrichment analysis shows the activation of O-linked glycosylated mucins (C). Heatmaps of expression levels in IMCC, IHCC and SSC-IHCC of mucin (D) and of mucopolysaccharide synthesis-related genes (E).
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case_images: Enhanced CT scans confirmed the presence of liver space and the diagnose of primary liver cancer ( Supplementary Figure 1A ). After surgery, the extracted tissue was results of H&E staining showed that the nuclei of tumorous tissue were of different sizes and the cells were irregularly arranged ( Supplementary Figures 1B, C ). The results of immunohistochemistry showed that the markers CAE, CK19, and CK5/6 were all positive ( Supplementary Figures 1D-I ). The periodic acid-Schiff staining (PAS) indicated presence of multiple mucinous polysaccharides in the tissue ( Supplementary Figures 1J, K ). Up-regulated genes were found to be significantly enriched in mucin and mucopolysaccharide synthesis, cell cycle and inflammation-related pathways ( Figure 1A ). The down-regulated genes were mainly enriched in pathways of bile synthesis and secretion and fat digestion ( Figure 1B ). A Gene Set Enrichment Analysis (GSEA) was also performed, which showed that oxygen-linked mucin glycosylation was activated in IMCC ( Figure 1C ). Except for MUC1, MUC6 (partially positive in IHCC) and MUCL1 (positive in SCC-IHCC), MUC5B, MUC4, MUC16, and MUC5AC were all specifically highly expressed in IMCC ( Figure 1D ). Among the genes related to mucopolysaccharide biosynthesis, GALNT5, B3GNT6, and ST6GALNAC1 were expressed in SCC-IHCC, but they were specifically highly expressed in IMCC ( Figure 1E ).
case_images: Up-regulated proteins of IMCC are mainly enriched in inflammation and cell cycle signaling pathways, while down-regulated proteins are mainly enriched in the regulation of bile acid synthesis. Dotplots show consistent KEGG enrichment in transcriptome and proteome of upregulated (A) and of downregulated (B) genes in IMCC. Venn diagram of RNA and protein of the up- and down-regulated genes (C). Scatter plot of gene and protein expression to illustrate their consistency in IMCC (D). Bar graph showing the enrichment of signaling pathways of genes or proteins that are jointly up-regulated or down-regulated in IMCC (E). The different metabolites identified in IMCC cancer tissue and adjacent tissue (F). The bubble charts show the enriched pathways of differential metabolites in IMCC (G, H).
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case_images: After comparison we found that 2 of the 54 genes were oncogenes and 2 were tumor suppressor genes ( Supplementary Figure 2A ). However, the expression levels of RNA and protein were not consistent ( Supplementary Figures 2B, C ). IMCC ( Supplementary Table 1 ). IMCC and the other two subtypes shared 17 mutant genes, of which 16 were shared with IHCC, while 1 was shared with SCC-IHCC ( Supplementary Figures 2D, E ). Sequenced the KRAS gene identified the mutation locus in G12D (rs121913529) of IMCC ( Supplementary Figure 2F ). We found that the up-regulated proteins were mainly enriched in extracellular matrix receptor interactions, cell cycle and inflammation-related signaling pathways ( Figure 2A ). The down-regulated proteins were mainly enriched in the synthesis and secretion of bile, retinol metabolism, and amino acid metabolism-related signaling pathways ( Figure 2B ). A total of 162 genes were identified as up-regulated and 217 genes were down-regulated both in RNA and protein levels ( Figure 2C ). The highly expressed genes were mainly enriched in mucin synthesis, mucopolysaccharide and the IL-17 signaling pathway ( Figure 2D ). The genes both up-regulated in RNA and protein were enriched in pathways such as extracellular matrix receptor interaction, IL-17 signaling and mucin secretion, while down-regulated genes were mainly enriched in bile synthesis and secretion, retinol metabolism and amino acid metabolism ( Figure 2E ). We further explored the changes of metabolites in IMCC, showing that the number of metabolites in IMCC was decreased ( Figure 2F ). This indicated that fatty acid metabolism in IMCC patients is hindered ( Figure 2G ). The up-regulated metabolites in IMCC were enriched in fat cell lipid catabolism pathways ( Figure 2H ).
case_images: Multi-omics comprehensive analysis of IMCC showing molecules that changed together in genes, RNA and protein levels (A). The heatmap shows the expression of cell death-related genes in IMCC, IHCC and SCC-IHCC (B). String analysis of the interactions between multi-omics convergent genes and mucin and mucopolysaccharide biosynthesis genes (C). Expression comparison in IMCC, IHCC and SCC-IHCC of MSLN (D) and of ASGR1 (E). The heatmap (F) shows the transcription factors in IMCC that may regulate the expression of mucin and mucopolysaccharide. JASPAR predicts the genes that ONECUT3 may target (G).
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case_images: By comprehensively analyzing the multi-omics, we found that there are 196 genes with the same changing trend in IMCC ( Figure 3A ). Figure 3B ). Further screening of molecules that might regulate the expression of mucin-producing genes (MUC4, MUC5AC, MUC5B, MUC16) and genes producing mucopolysaccharides (GALNT5, ST6GALNAC1, B3GNT6) revealed that ASGR1 may regulate the expression of MUC4, while MSLN may regulate the expression of MUC4 and MUC16 ( Figure 3C ). IMCC, while ASGR1 was not ( Figures 3D, E ). It is speculated that IMCC may increase mucus secretion by up-regulating MSLN. The results showed that the expression of ONECUT3 was specifically elevated in IMCC ( Figure 3F ). Using the JASPAR database (http://jaspar.genereg.net/) to predict the target genes of ONECUT3, it was found that the motif of ONECUT3 may target for MUC16, MUC5AC, GALNT5 and B3GNT6 ( Figure 3G ).