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Int J Stem Cells. 2019 Nov 30;12(3):430-439. doi: 10.15283/ijsc19067.

Reprogramming of Cancer Cells into Induced Pluripotent Stem Cells Questioned.

Bang JS1,2, Choi NY1,2, Lee M1,2, Ko K3, Park YS1,2, Ko K1,2,4.

Author information

1
Department of Stem Cell Biology, Konkuk University School of Medicine, Seoul, Korea.
2
Center for Stem Cell Research, Institute of Advanced Biomedical Science, Konkuk University, Seoul, Korea.
3
Department of Medicine, College of Medicine, Chung-Ang University, Seoul, Korea.
4
Research Institute of Medical Science, Konkuk University, Seoul, Korea.

Abstract

Background and Objectives:

Several recent studies have claimed that cancer cells can be reprogrammed into induced pluripotent stem cells (iPSCs). However, in most cases, cancer cells seem to be resistant to cellular reprogramming. Furthermore, the underlying mechanisms of limited reprogramming in cancer cells are largely unknown. Here, we identified the candidate barrier genes and their target genes at the early stage of reprogramming for investigating cancer reprogramming.

Methods:

We tried induction of pluripotency in normal human fibroblasts (BJ) and both human benign (MCF10A) and malignant (MCF7) breast cancer cell lines using a classical retroviral reprogramming method. We conducted RNA-sequencing analysis to compare the transcriptome of the three cell lines at early stage of reprogramming.

Results:

We could generate iPSCs from BJ, whereas we were unable to obtain iPSCs from cancer cell lines. To address the underlying mechanism of limited reprogramming in cancer cells, we identified 29 the candidate barrier genes based on RNA-sequencing data. In addition, we found 40 their target genes using Cytoscape software.

Conclusions:

Our data suggest that these genes might one of the roadblock for cancer cell reprogramming. Furthermore, we provide new insights into application of iPSCs technology in cancer cell field for therapeutic purposes.

KEYWORDS:

Cancer cell reprogramming; Induced pluripotent stem cells; Pluripotency; RNA-sequencing analysis; iPSC generation

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