Systematic Analysis of the Transcriptome Profiles and Co-Expression Networks of Tumour Endothelial Cells Identifies Several Tumour-Associated Modules and Potential Therapeutic Targets in Hepatocellular Carcinoma

Thomas Mohr; Sonja Katz; Verena Paulitschke; Nadim Aizarani; Alexander Tolios

doi:10.3390/cancers13081768

Systematic Analysis of the Transcriptome Profiles and Co-Expression Networks of Tumour Endothelial Cells Identifies Several Tumour-Associated Modules and Potential Therapeutic Targets in Hepatocellular Carcinoma

Cancers (Basel). 2021 Apr 7;13(8):1768. doi: 10.3390/cancers13081768.

Authors

Thomas Mohr^{1

2}, Sonja Katz¹, Verena Paulitschke³, Nadim Aizarani⁴, Alexander Tolios^{5

6

7}

Affiliations

¹ ScienceConsult-DI Thomas Mohr KG, Enzianweg 10a, A-2353 Guntramsdorf, Austria.
² Institute of Cancer Research, Department of Medicine I, Medical University of Vienna and Comprehensive Cancer Center, A-1090 Vienna, Austria.
³ Department of Dermatology, Medical University of Vienna, A-1090 Vienna, Austria.
⁴ Max-Planck-Institute of Immunobiology and Epigenetics, D-79108 Freiburg, Germany.
⁵ Department of Blood Group Serology and Transfusion Medicine, Medical University of Vienna, A-1090 Vienna, Austria.
⁶ Center of Physiology and Pharmacology, Institute of Vascular Biology and Thrombosis Research, Medical University of Vienna, A-1090 Vienna, Austria.
⁷ Section of Artificial Intelligence and Decision Support, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, A-1090 Vienna, Austria.

Abstract

Hepatocellular carcinoma (HCC) is the sixth most common cancer and the third most common cause of cancer-related death, with tumour associated liver endothelial cells being thought to be major drivers in HCC progression. This study aims to compare the gene expression profiles of tumour endothelial cells from the liver with endothelial cells from non-tumour liver tissue, to identify perturbed biologic functions, co-expression modules, and potentially drugable hub genes that could give rise to novel therapeutic targets and strategies. Gene Set Variation Analysis (GSVA) showed that cell growth-related pathways were upregulated, whereas apoptosis induction, immune and inflammatory-related pathways were downregulated in tumour endothelial cells. Weighted Gene Co-expression Network Analysis (WGCNA) identified several modules strongly associated to tumour endothelial cells or angiogenic activated endothelial cells with high endoglin (ENG) expression. In tumour cells, upregulated modules were associated with cell growth, cell proliferation, and DNA-replication, whereas downregulated modules were involved in immune functions, particularly complement activation. In ENG⁺ cells, upregulated modules were associated with cell adhesion and endothelial functions. One downregulated module was associated with immune system-related functions. Querying the STRING database revealed known functional-interaction networks underlying the modules. Several possible hub genes were identified, of which some (for example FEN1, BIRC5, NEK2, CDKN3, and TTK) are potentially druggable as determined by querying the Drug Gene Interaction database. In summary, our study provides a detailed picture of the transcriptomic differences between tumour and non-tumour endothelium in the liver on a co-expression network level, indicates several potential therapeutic targets and presents an analysis workflow that can be easily adapted to other projects.

Keywords: hepatocellular carcinoma; liver endothelial cells; network analysis; tumour associated endothelial cells.