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Simple Summary  Endothelial cells, the innermost layer of blood vessels, play an essential role in the progression of cancer, particularly liver cancer. To develop cancer therapies targeting those cells, the investigation of gene co-expression networks is of great importance. In this study, we investigated the gene expression profile of tumour endothelial cells. We compared it to endothelial cells from non-tumour liver-tissue. Using gene-network based methods, we could identify genes that may play a unique role in liver cancer progression or be a target for cancer therapy. Additionally, we provided a framework for similar analyses in other cancers.    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.

cancers

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