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.

The role of pioneer transcription factors in the induction of direct cellular reprogramming

“…By contrast, recent studies have suggested that all transcription factors can act as pioneer factors depending on their expression levels and abundance ratios [ 31 , 32 ]. This idea is partially supported by other studies showing that the outcome of cellular reprogramming is influenced by the expression levels and abundance ratios of reprogramming-inducing transcription factors [ 16 , 33 , 34 ]. It has also been reported that transcription factors introduced and exogenously expressed in cells can either promote or inhibit chromatin binding to each other [ 35 ].…”

“…These directly induced stem and progenitor cells may be preferred over terminally differentiated cells because of their potential for propagation and differentiation in culture and after transplantation into injured tissues and organs. In addition, cell reprogramming technology has enabled the direct induction of tumor-forming cells from normal somatic cells [ 15 , 16 ] and has evolved to induce stable inhibition of tumor cell proliferation and functional differentiation of tumor cells using a defined set of transcription factors [ [17] , [18] , [19] ]. Direct reprogramming technology, which uses specific combinations of transcription factors, is expanding into many fields beyond regenerative medicine.…”

Hepatocytes differentiate into intestinal epithelial cells through a hybrid epithelial/mesenchymal cell state in culture

“…Total RNA was obtained from hepatocytes freshly isolated from adult mouse livers, hepatocytes and dediHeps in monolayer cultures, dediHep aggregates, dediHep-derived SOs, FIPC-derived SOs, dediHep-derived BOs, ISC-derived BOs, CLiPs, and hepatocytes cultured with DMSO or verteporfin (0.3 µM) for 1 week after plating as described above and analyzed by 3ʹ untranslated region sequencing (CEL-seq2) [46][47][48] . Calculation of log fold-change (logFC) and identification of differentially expressed genes (FDR < 0.1, 2 < logFC) were performed by edgeR program (version 4.0.2) [49][50][51] with unique molecular identifier (UMI) count values.…”