TNF receptor-related factor 3 inactivation promotes the development of intrahepatic cholangiocarcinoma through NF-κB-inducing kinase-mediated hepatocyte transdifferentiation
Background and aims: Intrahepatic cholangiocarcinoma (ICC) is a deadly but poorly understood disease, and its treatment options are very limited. The aim of this study was to identify the molecular drivers of ICC and search for therapeutic targets. Approach and results: We performed a Sleeping Beauty transposon-based in vivo insertional mutagenesis screen in liver-specific Pten -deficient mice and identified TNF receptor-related factor 3 ( Traf3 ) as the most significantly mutated gene in murine ICCs in a loss-of-function manner. Liver-specific Traf3 deletion caused marked cholangiocyte overgrowth and spontaneous development of ICC in Pten knockout and KrasG12D mutant mice. Hepatocyte-specific, but not cholangiocyte-specific, Traf3 -deficient and Pten -deficient mice recapitulated these phenotypes. Lineage tracing and single-cell RNA sequencing suggested that these ICCs were derived from hepatocytes through transdifferentiation. TRAF3 and PTEN inhibition induced a transdifferentiation-like phenotype of hepatocyte-lineage cells into proliferative cholangiocytes through NF-κB-inducing kinase (NIK) up-regulation in vitro. Intrahepatic NIK levels were elevated in liver-specific Traf3 -deficient and Pten -deficient mice, and NIK inhibition alleviated cholangiocyte overgrowth. In human ICCs, we identified an inverse correlation between TRAF3 and NIK expression, with low TRAF3 or high NIK expression associated with poor prognosis. Finally, we showed that NIK inhibition by a small molecule inhibitor or gene silencing suppressed the growth of multiple human ICC cells in vitro and ICC xenografts in vivo. Conclusions: TRAF3 inactivation promotes ICC development through NIK-mediated hepatocyte transdifferentiation. The oncogenic TRAF3-NIK axis may be a potential therapeutic target for ICC.
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细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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