Direct Conversion of Human Endothelial Cells Into Liver Cancer-Forming Cells Using Nonintegrative Episomal Vectors

Abstract

Liver cancer is an aggressive cancer associated with a poor prognosis. Development of therapeutic strategies for liver cancer requires fundamental research using suitable experimental models. Recent progress in direct reprogramming technology has enabled the generation of many types of cells that are difficult to obtain and provide a cellular resource in experimental models of human diseases. In this study, we aimed to establish a simple one-step method for inducing cells that can form malignant human liver tumors directly from healthy endothelial cells using nonintegrating episomal vectors. To screen for factors capable of inducing liver cancer-forming cells (LCCs), we selected nine genes and one short hairpin RNA that suppresses tumor protein p53 (TP53) expression and introduced them into human umbilical vein endothelial cells (HUVECs), using episomal vectors. To identify the essential factors, we examined the effect of changing the amounts and withdrawing individual factors. We then analyzed the proliferation, gene and protein expression, morphologic and chromosomal abnormality, transcriptome, and tumor formation ability of the induced cells. We found that a set of six factors, forkhead box A3 (FOXA3), hepatocyte nuclear factor homeobox 1A (HNF1A), HNF1B, lin-28 homolog B (LIN28B), MYCL proto-oncogene, bHLH transcription factor (L-MYC), and Kruppel-like factor 5 (KLF5), induced direct conversion of HUVECs into LCCs. The gene expression profile of these induced LCCs (iLCCs) was similar to that of human liver cancer cells, and these cells effectively formed tumors that resembled human combined hepatocellular-cholangiocarcinoma following transplantation into immunodeficient mice. Conclusion: We succeeded in the direct induction of iLCCs from HUVECs by using nonintegrating episomal vectors. iLCCs generated from patients with cancer and healthy volunteers will be useful for further advancements in cancer research and for developing methods for the diagnosis, treatment, and prognosis of liver cancer.