Literature DB >> 35693071

MYBL2 accelerates epithelial-mesenchymal transition and hepatoblastoma metastasis via the Smad/SNAI1 pathway.

Meng Wei1, Ran Yang1, Mujie Ye1, Yong Zhan1, Baihui Liu1, Lingdu Meng1, Lulu Xie1, Min Du1,2, Junfeng Wang1, Runnan Gao1, Deqian Chen1, Rui Dong1, Kuiran Dong1.   

Abstract

Hepatoblastoma (HB) accounts for the majority of hepatic malignancies in children. Although the prognosis of patients with HB has improved in past decades, metastasis is an indicator of poor overall survival. Herein, we applied single-cell RNA sequencing to explore the transcriptomic profiling of 25,264 metastatic cells isolated from the lungs of two patients with HB. The transcriptomes uncovered the heterogeneity of malignant cells after metastatic lung colonization, and these cells had varied expression signatures associated with the cell cycle, epithelial-mesenchymal plasticity, and hepatic differentiation. Single-cell regulatory network inference and clustering (SCENIC) was utilized to identify the co-expressed transcriptional factors which regulated and represented the different cell states. We further screened the key factor by bioinformatics analysis and found that MYBL2 upregulation was significantly associated with metastasis and poor prognosis. The relationship between ectopic MYBL2 and metastasis was subsequently proved by immunohistochemistry (IHC) of HB tissues, and the functions of MYBL2 in promoting proliferation, migration, and epithelial-to-mesenchymal transition (EMT) were verified by in vitro and in vivo assays. Importantly, the levels of Smad2/3 phosphorylation and SNAI1 expression were increased in MYBL2-transfected cells. Consequently, these results indicated that the MYBL2-controlled Smad/SNAI1 pathway induced EMT and promoted HB tumorigenesis and metastasis. AJCR
Copyright © 2022.

Entities:  

Keywords:  Epithelial-to-mesenchymal transition; MYBL2; SNAI1; hepatoblastoma; metastasis; single-cell RNA sequencing

Year:  2022        PMID: 35693071      PMCID: PMC9185624     

Source DB:  PubMed          Journal:  Am J Cancer Res        ISSN: 2156-6976            Impact factor:   5.942


  65 in total

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10.  SCENIC: single-cell regulatory network inference and clustering.

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Journal:  Nat Methods       Date:  2017-10-09       Impact factor: 28.547

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