Activation of the Notch1-c-myc-VCAM1 signalling axis initiates liver progenitor cell-driven hepatocarcinogenesis and pulmonary metastasis

Wu, Wenrui; Shi, Xiang-De; Zhang, Fa-Peng; Zhu, Ke; Zhang, Rui; Yu, Xiaokang; Qin, Yufei; He, Shun-Peng; Fu, Hou-Wei; Zhang, Lei; Zeng, Hong; Zhu, Man-Sheng; Xu, Lei-Bo; Wong, Ping-Pui; Liu, Chao

doi:10.1038/s41388-022-02246-5

Cited by 18 publications

(16 citation statements)

References 47 publications

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“…In order to further evaluate the in vivo targeted synergistic effect, a C5WN1 subcutaneous tumor model was established [ 27 ]. Animal experiments were carried out with the approval of the experimental animal ethics committee of Jiangnan University (Approval Number: JN.…”

Section: Resultsmentioning

confidence: 99%

“…HEK293 cells were obtained from the Conservation Genetics CAS Kunming Cell Bank. C5WN1 cells were self-established [ 27 ]. C5WN1, Huh7, HepG2 and HEK293 cells were maintained in DMEM medium supplemented with 10% FBS, 1% penicillin and 1% streptomycin (growth medium), in 5% CO 2 and 95% air at 37 °C.…”

Section: Methodsmentioning

confidence: 99%

“…Herein, we synthesized an integrated delivery system based on two monomers [3-azido-2-hydroxypropyl methacrylate (AHPMA) and 2-(dimethylamino) ethyl methacrylate (DMAEMA)] to combine gene therapy against VEGF and VEGFR2 and chemotherapy to inhibit hepatocarcinogenesis and metastasis, which can be initiated with a cancer stem cell (CSC)-like cell line C5WN1 with tumorigenicity and pulmonary metastasis ( Scheme 1 ) [ 27 ]. The monomer DMAEMA can form a stable complex with amino groups of negatively charged nucleic acids to prevent enzymatic degradation.…”

Section: Introductionmentioning

confidence: 99%

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Inhibition of Metastatic Hepatocarcinoma by Combined Chemotherapy with Silencing VEGF/VEGFR2 Genes through a GalNAc-Modified Integrated Therapeutic System

Wang

Liu

et al. 2022

Molecules

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Hepatocellular carcinoma (HCC) is a highly malignant tumor related to high mortality and is still lacking a satisfactory cure. Tumor metastasis is currently a major challenge of cancer treatment, which is highly related to angiogenesis. The vascular endothelial growth factor (VEGF)/VEGFR signaling pathway is thus becoming an attractive therapeutic target. Moreover, chemotherapy combined with gene therapy shows great synergistic potential in cancer treatment with the promise of nanomaterials. In this work, a formulation containing 5-FU and siRNA against the VEGF/VEGFR signaling pathway into N-acetyl-galactosamine (GalNAc)-modified nanocarriers is established. The targeting ability, biocompatibility and pH-responsive degradation capacity ensure the efficient transport of therapeutics by the formulation of 5-FU/siRNA@GalNAc-pDMA to HCC cells. The nano-construct integrated with gene/chemotherapy exhibits significant anti-metastatic HCC activity against C5WN1 liver cancer cells with tumorigenicity and pulmonary metastasis in the C5WN1-induced tumor-bearing mouse model with a tumor inhibition rate of 96%, which is promising for future metastatic HCC treatment.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Inhibition of Metastatic Hepatocarcinoma by Combined Chemotherapy with Silencing VEGF/VEGFR2 Genes through a GalNAc-Modified Integrated Therapeutic System

Wang

Liu

et al. 2022

Molecules

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“…Previous studies showed that VCAM1 was highly expressed in HCC tissues, and most of them showed strong positive expression. Therefore, VCAM-1 and other adhesion molecules were believed to be significantly correlated with the invasion of HCC and could be used as a marker of tumor invasion ( Wu et al, 2022 ). In addition, in the study of breast cancer, the direct role of VCAM1 in tumor metastasis was also confirmed ( Lee et al, 2016 ).…”

Section: Discussionmentioning

confidence: 99%

Comparative glycoproteomics study on the surface of SKOV3 versus IOSE80 cell lines

Zhou

Cai

et al. 2022

Front. Chem.

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Objective: Site- and structure-specific quantitative N-glycoproteomics study of differential cell-surface N-glycosylation of ovarian cancer SKOV3 cells with the non-cancerous ovarian epithelial IOSE80 cells as the control.Methods: C18-RPLC-MS/MS (HCD with stepped normalized collision energies) was used to analyze the 1: 1 mixture of labeled intact N-glycopeptides from SKOV3 and IOSE80 cells, and the site- and structure-specific intact N-glycopeptide search engine GPSeeker was used to conduct qualitative and quantitative search on the obtained raw datasets.Results: With the control of the spectrum-level false discovery rate ≤1%, 13,822 glycopeptide spectral matches coming from 2,918 N-glycoproteins with comprehensive N-glycosite and N-glycan structure information were identified; 3,733 N-glycosites and 3,754 N-glycan sequence structures were confirmed by site-determining and structure-diagnostic fragment ions, respectively. With the control of no less than two observations among the three technical replicates, fold change ≥1.5, and p-value ≤ 0.05, 746 DEPGs in SKOV3 cells relative to IOSE80 cells were quantified, where 421 were upregulated and 325 downregulated.Conclusion: Differential cell-surface N-glycosylation of ovarian cancer SKOV3 cells were quantitatively analyzed by isotopic labeling and site- and structure-specific N-glycoproteomics. This discovery study provides putative N-glycoprotein biomarker candidates for future validation study using multiple reaction monitoring and biochemical methods.

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“…Modeling cancer initiation can provide an effective tool to monitor the histological changes during the early stage of cancer development. It is known that the overexpression of c-Myc may cause HCC [ 97 , 98 , 99 ]. Lulu and coworkers have reported an approach to mimic liver cancer initiation by overexpressing c-Myc in genetically reprogrammed human hepatocyte (hiHeps) organoids [ 100 ].…”

Section: Biomedical Applications Of Bioengineering Liver Organoidsmentioning

confidence: 99%

Bioengineering Liver Organoids for Diseases Modelling and Transplantation

Chu

Lui

et al. 2022

Bioengineering

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Organoids as three-dimension (3D) cellular organizations partially mimic the physiological functions and micro-architecture of native tissues and organs, holding great potential for clinical applications. Advances in the identification of essential factors including physical cues and biochemical signals for controlling organoid development have contributed to the success of growing liver organoids from liver tissue and stem/progenitor cells. However, to recapitulate the physiological properties and the architecture of a native liver, one has to generate liver organoids that contain all the major liver cell types in correct proportions and relative 3D locations as found in a native liver. Recent advances in stem-cell-, biomaterial- and engineering-based approaches have been incorporated into conventional organoid culture methods to facilitate the development of a more sophisticated liver organoid culture resembling a near to native mini-liver in a dish. However, a comprehensive review on the recent advancement in the bioengineering liver organoid is still lacking. Here, we review the current liver organoid systems, focusing on the construction of the liver organoid system with various cell sources, the roles of growth factors for engineering liver organoids, as well as the recent advances in the bioengineering liver organoid disease models and their biomedical applications.

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Activation of the Notch1-c-myc-VCAM1 signalling axis initiates liver progenitor cell-driven hepatocarcinogenesis and pulmonary metastasis

Cited by 18 publications

References 47 publications

Inhibition of Metastatic Hepatocarcinoma by Combined Chemotherapy with Silencing VEGF/VEGFR2 Genes through a GalNAc-Modified Integrated Therapeutic System

Inhibition of Metastatic Hepatocarcinoma by Combined Chemotherapy with Silencing VEGF/VEGFR2 Genes through a GalNAc-Modified Integrated Therapeutic System

Comparative glycoproteomics study on the surface of SKOV3 versus IOSE80 cell lines

Bioengineering Liver Organoids for Diseases Modelling and Transplantation

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