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Cell Research
Article . 2019 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Cell Research
Article
License: CC BY
Data sources: UnpayWall
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PubMed Central
Other literature type . 2019
Data sources: PubMed Central
Cell Research
Article . 2020
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A two-step lineage reprogramming strategy to generate functionally competent human hepatocytes from fibroblasts

Authors: Bingqing Xie; Da Sun; Yuanyuan Du; Jun Jia; Shicheng Sun; Jun Xu; Yifang Liu; +19 Authors

A two-step lineage reprogramming strategy to generate functionally competent human hepatocytes from fibroblasts

Abstract

Terminally differentiated cells can be generated by lineage reprogramming, which is, however, hindered by incomplete conversion with residual initial cell identity and partial functionality. Here, we demonstrate a new reprogramming strategy by mimicking the natural regeneration route, which permits generating expandable hepatic progenitor cells and functionally competent human hepatocytes. Fibroblasts were first induced into human hepatic progenitor-like cells (hHPLCs), which could robustly expand in vitro and efficiently engraft in vivo. Moreover, hHPLCs could be efficiently induced into mature human hepatocytes (hiHeps) in vitro, whose molecular identity highly resembles primary human hepatocytes (PHHs). Most importantly, hiHeps could be generated in large quantity and were functionally competent to replace PHHs for drug-metabolism estimation, toxicity prediction and hepatitis B virus infection modeling. Our results highlight the advantages of the progenitor stage for successful lineage reprogramming. This strategy is promising for generating other mature human cell types by lineage reprogramming.

Related Organizations
Keywords

Mice, Knockout, Hepatitis B virus, Mice, Inbred BALB C, Stem Cells, Gene Expression, Cell Differentiation, Fibroblasts, Cellular Reprogramming, Article, Mice, Cytochrome P-450 Enzyme System, Liver, Hepatocytes, Animals, Humans, Cell Lineage, Glucuronosyltransferase, Cells, Cultured, Stem Cell Transplantation, Transcription Factors

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    52
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
52
Top 10%
Top 10%
Top 1%
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hybrid