Prolonged inhibition of hepatocellular carcinoma cell proliferation by combinatorial expression of defined transcription factors

Yasuo Takashima, Kenichi Horisawa, Miyako Udono, Yasuyuki Ohkawa, Atsushi Suzuki

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Hepatocellular carcinoma (HCC) accounts for a large proportion of liver cancer cases and has an extremely poor prognosis. Therefore, novel innovative therapies for HCC are strongly desired. As gene therapy tools for HCC, 2 hepatic transcription factors (TF), HNF4A and HNF1A, have been used to suppress proliferation and to extinguish cancer-specific characteristics of target cells. However, our present data demonstrated that single transduction of HNF4A or HNF1A had only a limited effect on suppression of HCC cell proliferation. Thus, in this study, we examined whether combinations of TF could show more effective antitumor activity, and found that combinatorial transduction of 3 hepatic TF, HNF4A, HNF1A and FOXA3, suppressed HCC cell proliferation more stably than single transduction of these TF. The combinatorial transduction also suppressed cancer-specific phenotypes, such as anchorage-independent growth in culture and tumorigenicity after transplantation into mice. HCC cell lines transduced with the 3 TF did not recover their proliferative property after withdrawal of anticancer drugs, indicating that combinatorial expression of the 3 TF suppressed the growth of all cell subtypes within the HCC cell lines, including cancer stem-like cells. Transcriptome analyses revealed that the expression levels of a specific gene set involved in cell proliferation were only decreased in HCC cells overexpressing all 3 TF. Moreover, combined transduction of the 3 TF could facilitate hepatic differentiation of HCC cell lines. Our strategy for inducing stable inhibition and functional differentiation of tumor cells using a defined set of TF will become an effective therapeutic strategy for various types of cancers.

Original languageEnglish
Pages (from-to)3543-3553
Number of pages11
JournalCancer Science
Volume109
Issue number11
DOIs
Publication statusPublished - Nov 2018

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

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