Transcriptional Profiling of Porcine HCC Xenografts Provides Insights Into Tumor Cell Microenvironment Signaling

Abstract

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide, representing the most common form of liver cancer. As HCC incidence and mortality continue to increase, there is a growing need for improved translational animal models to bridge the gap between basic HCC research and clinical practice to improve early detection and treatment strategies for this deadly disease. Recently the Oncopig cancer model-a novel transgenic swine model that recapitulates human cancer through Cre recombinase induced expression of KRAS ^G12D and TP53 ^R167H driver mutations-has been validated as a large animal translational model for human HCC. Due to the similar size, anatomy, physiology, immunology, genetics, and epigenetics between pigs and humans, the Oncopig has the potential to improve translation of novel diagnostic and therapeutic modalities into clinical practice. Recent studies have demonstrated the importance of tumor cells in shaping its surrounding microenvironment into one that is more proliferative, invasive, and metastatic; however, little is known about the impact of microenvironment signaling on HCC tumor biology and differential gene expression between HCC tumors and its tumor microenvironment (TME). In this study, transcriptional profiling was performed on Oncopig HCC xenograft tumors (n = 3) produced via subcutaneous injection of Oncopig HCC cells into severe combined immunodeficiency (SCID) mice. To differentiate between gene expression in the tumor and surrounding tumor microenvironment, RNA-seq reads originating from porcine (HCC tumor) and murine (microenvironment) cells were bioinformatically separated using Xenome. Principle component analysis (PCA) demonstrated clustering by group based on the expression of orthologous genes. Genes contributing to each principal component were extracted and subjected to functional analysis to identify alterations in pathway signaling between HCC cells and the microenvironment. Altered expression of genes associated with hepatic fibrosis deposition, immune response, and neo angiogenesis were observed. The results of this study provide insights into the interplay between HCC and microenvironment signaling in vivo, improving our understanding of the interplay between HCC tumor cells, the surrounding tumor microenvironment, and the impact on HCC development and progression.

Keywords: RNA sequencing; hepatic fibrosis; hepatocellular carcinoma; microenvironment; porcine cancer model; xenograft.

FIGURE 1

Differential Expression Between HCC Tumors and the TME. (A) PCA plot and (B) Heatmap based on the final filtered list of 14,163 orthologous genes expressed in at least 1 sample. (C) Top 25 genes contributing to the variation of dimension 1. (D) Top 25 genes contributing to the variation of dimension 2.

FIGURE 2

Differential Expression of Genes Involved in Hepatic Fibrosis. (A) Heatmap of the 69 genes differentially expressed in the Hepatic Stellate Cell Activation Pathway for all 6 samples. (B) Heatmap of the 82 differentially expressed genes in the Hepatic Fibrosis Signaling Pathway for all 6 samples.

FIGURE 3

Differential Expression in the Hepatic Fibrosis Signaling Pathway. Differential expression of genes in the hepatic fibrosis signaling canonical pathway in IPA (edited for simpler visualization; for full pathway, see Supplementary Figure 1). Molecule interactions are shown as explained in the legend. DEGs are highlighted either in red (upregulated TME genes) or green (upregulated HCC tumor genes). Color intensity indicates Increasing or decreasing degree of fold change.

FIGURE 4

Differential Expression in the Hepatic Stellate Cell Activation Pathway. (A,B) The hepatic stellate cell activation canonical pathway in IPA (edited for simpler visualization; for full pathway, see Supplementary Figure 2). Molecule interactions are shown as explained in the legend. DEGS are highlighted either in red (upregulated TME genes) or green (upregulated HCC tumor genes). Color intensity indicates increasing or decreasing degree of fold change. (C) Heatmap of the 22 collagen genes differentially expressed in the Hepatic Stellate Cell Activation Pathway for all 6 samples.

FIGURE 5

Differential Expression of Genes Inolved in the Innate Immune and Inflammatory System. (A) Differential expression within the NF-κB canonical pathway in IPA (edited for simpler visualization; for full pathway, see Supplementary Figure 3). Molecule interactions are shown as explained in the legend. DEGs are highlighted either in red (upregulated TME genes) or green (upregulated HCC tumor genes). Color intensity indicates Increasing or decreasing degree of fold change. (B) Heatmap of the 49 genes differentially expressed in the NF-κB signaling pathway for all 6 samples.

FIGURE 6

Differential Expression of Genes Involved in Neo angiogenesis. Differential expression within the (A) HIF1α Signaling canonical pathway and (B) VEGF Family Ligand-Receptor Interactions canonical pathway in IPA. Both pathways are edited for simpler visualization (for full pathway, see Supplementary Figures 4, 5). Molecule interactions are shown as explained in the legend. DEGs are highlighted either in red (upregulated TME genes) or green (upregulated HCC tumor genes). Color intensity indicates increasing or decreasing degree of fold change. (C) Heatmap of the 51 DEGs in the HIF1α Signaling pathway for all 6 samples. (D) Heatmap of the 20 DEGs in the VEGF Family Ligand-Receptor Interactions pathway for all 6 samples.